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You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who has the same number as greg foster?
|
[['Player', 'No.', 'Nationality', 'Position', 'Years for Jazz', 'School/Club Team'], ['Jim Farmer', '30', 'United States', 'Guard', '1988-89', 'Alabama'], ['Bernie Fryer', '25', 'United States', 'Guard', '1975-76', 'BYU'], ['Todd Fuller', '52', 'United States', 'Center', '1998-99', 'North Carolina State'], ['Greg Foster', '44', 'United States', 'Center/Forward', '1995-99', 'UTEP'], ['Kyrylo Fesenko', '44', 'Ukraine', 'Center', '2007-11', 'Cherkasy Monkeys (Ukraine)'], ['Derek Fisher', '2', 'United States', 'Guard', '2006-2007', 'Arkansas-Little Rock'], ['Derrick Favors', '15', 'United States', 'Forward', '2011-present', 'Georgia Tech'], ['Terry Furlow', '25', 'United States', 'Guard/Forward', '1979-80', 'Michigan State']]
|
Kyrylo Fesenko
|
Answer:
| 128
| 8
| 242
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides "th' wife", what other single came out in 1964?
|
[['Year', 'Single', 'Chart Positions\\nUS Country', 'Chart Positions\\nUS', 'Album'], ['1966', '"You\'re the Guilty One"', '—', '—', 'single only'], ['1964', '"Th\' Wife"', '45', '—', 'singles only'], ['1968', '"Odd Folks of Okracoke"', '—', '—', 'single only'], ['1979', '"Every Day I Learn a Little More About Love"', '—', '—', 'Just Passing Through'], ['1962', '"Road Hog"', '—', '65', 'Twelve Sides'], ['1965', '"That Ain\'t All"', '20', '—', 'singles only'], ['1966', '"Silver Cloud Talkin\' Blues"', '—', '—', 'A Bizarre Collection of the Most Unusual Songs'], ['1964', '"Blue Train (Of the Heartbreak Line)"', '44', '132', 'singles only'], ['1961', '"Language of Love"', '—', '32', 'Language of Love'], ['1967', '"It\'s My Time"', '51', '—', 'Suburban Attitudes in Country Verse'], ['1962', '"Thou Shalt Not Steal"', '—', '73', 'singles only'], ['1962', '"Callin\' Dr. Casey"', '—', '83', 'singles only'], ['1971', '"Lord Have Mercy"', '—', '—', 'Volume 1-Elloree'], ['1957', '"Sittin\' in the Balcony"', '—', '38', 'single only'], ['1969', '"Brown Girl"', '—', '—', 'The Open Mind of John D. Loudermilk'], ['1963', '"Bad News" (b/w "Guitar Player(Her and Him)")', '23', '—', 'singles only']]
|
"Blue Train (Of the Heartbreak Line)"
|
Answer:
| 128
| 16
| 415
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the first voted out?
|
[['Contestant', 'Original Tribe', 'Switched Tribe', 'Merged Tribe', 'Finish', 'Total Votes'], ['Ivar Kalnynsh\\n54.the actor', '', '', 'Crocodiles', '10th Voted Out\\n5th Jury Member\\nDay 30', '3'], ['Yelena Kondulaynen\\n44.the actress', 'Pelicans', '', '', '1st Voted Out\\nDay 3', '5'], ['Ivan Demidov\\n39.the TV presenter', 'Barracudas', 'Pelicans', 'Crocodiles', 'Eliminated\\n2nd Jury Member\\nDay 23', '3'], ['Dana Borisova\\n26.the TV presenter', 'Pelicans', 'Barracudas', '', '4th Voted Out\\nDay 12', '5'], ['Yelena Proklova\\n49.the TV presenter', 'Pelicans', 'Barracudas', 'Crocodiles', '8th Voted Out\\n3rd Jury Member\\nDay 24', '4'], ['Aleksandr Byalko\\n50.the physicist', 'Pelicans', 'Barracudas', '', '5th Voted Out\\nDay 15', '6'], ['Viktor Gusev\\n47.the sport commentator', 'Pelicans', 'Pelicans', 'Crocodiles', '7th Voted Out\\n1st Jury Member\\nDay 21', '6'], ["Igor' Livanov\\n49.the actor", 'Pelicans', '', '', 'Eliminated\\nDay 11', '0'], ["Tat'yana Ovsiyenko\\n36.the singer", 'Barracudas', 'Pelicans', '', 'Eliminated\\nDay 19', '1'], ['Olga Orlova\\n25.the singer', 'Barracudas', 'Baracudas', 'Crocodiles', 'Eliminated\\n9th Jury Member\\nDay 38', '10'], ['Yelena Perova\\n26.the singer', 'Pelicans', 'Pelicans', 'Crocodiles', 'Runner-Up', '2'], ['Tatyana Dogileva\\n45.the actress', 'Pelicans', 'Barracudas', '', '6th Voted Out\\nDay 18', '3'], ['Aleksandr Lykov\\n41.the actor', 'Barracudas', 'Barracudas', 'Crocodiles', '13th Voted Out\\n8th Jury Member\\nDay 37', '6'], ['Marina Aleksandrova\\n20.the actress', 'Barracudas', 'Pelicans', 'Crocodiles', '9th Voted Out\\n4th Jury Member\\nDay 27', '6'], ['Vera Glagoleva\\n46.the actress', '', '', 'Crocodiles', '11th Voted Out\\n6th Jury Member\\nDay 33', '4'], ['Aleksandr Pashutin\\n60.the actor', 'Barracudas', '', '', '3rd Voted Out\\nDay 9', '7'], ['Vladimir Presnyakov, Jr.\\n34.the singer', 'Pelicans', 'Pelicans', 'Crocodiles', 'Sole Survivor', '6'], ['Kris Kelmi\\n47.the singer', 'Barracudas', '', '', '2nd Voted Out\\nDay 6', '1'], ['Larisa Verbitskaya\\n43.the TV presenter', 'Barracudas', 'Pelicans', 'Crocodiles', '12th Voted Out\\n7th Jury Member\\nDay 36', '11']]
|
Yelena Kondulaynen
|
Answer:
| 128
| 19
| 808
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the name of the circuit listed before portland?
|
[['Round', 'Date', 'Circuit', 'Winning driver (TA2)', 'Winning vehicle (TA2)', 'Winning driver (TA1)', 'Winning vehicle (TA1)'], ['6', 'August 13', 'Brainerd', 'Jerry Hansen', 'Chevrolet Monza', 'Bob Tullius', 'Jaguar XJS'], ['2', 'June 4', 'Westwood', 'Ludwig Heimrath', 'Porsche 935', 'Nick Engels', 'Chevrolet Corvette'], ['5', 'July 8', 'Watkins Glen‡', 'Hal Shaw, Jr.\\n Monte Shelton', 'Porsche 935', 'Brian Fuerstenau\\n Bob Tullius', 'Jaguar XJS'], ['10', 'November 5', 'Mexico City', 'Ludwig Heimrath', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['3', 'June 11', 'Portland', 'Tuck Thomas', 'Chevrolet Monza', 'Bob Matkowitch', 'Chevrolet Corvette'], ['8', 'September 4', 'Road America', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['4', 'June 25', 'Mont-Tremblant', 'Monte Sheldon', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['1', 'May 21', 'Sears Point', 'Greg Pickett', 'Chevrolet Corvette', 'Gene Bothello', 'Chevrolet Corvette'], ['9', 'October 8', 'Laguna Seca', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['7', 'August 19', 'Mosport', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS']]
|
Westwood
|
Answer:
| 128
| 10
| 426
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long does the swiss open series run for?
|
[['Tour', 'Official title', 'Venue', 'City', 'Date\\nStart', 'Date\\nFinish', 'Prize money\\nUSD', 'Report'], ['9', 'Denmark Super Series', 'Arena Fyn', 'Odense', 'October 23', 'October 28', '200,000', 'Report'], ['4', 'Swiss Open Super Series', 'St. Jakobshalle', 'Basel', 'March 12', 'March 18', '200,000', 'Report'], ['7', 'China Masters Super Series', 'Sichuan Provincial Gymnasium', 'Chengdu', 'July 10', 'July 15', '250,000', 'Report'], ['11', 'China Open Super Series', 'Tianhe Gymnasium', 'Guangzhou', 'November 20', 'November 25', '250,000', 'Report'], ['1', 'Malaysia Super Series', 'Stadium Badminton Kuala Lumpur', 'Kuala Lumpur', 'January 16', 'January 21', '200,000', 'Report'], ['8', 'Japan Super Series', 'Tokyo Metropolitan Gymnasium', 'Tokyo', 'September 11', 'September 16', '200,000', 'Report'], ['5', 'Singapore Super Series', 'Singapore Indoor Stadium', 'Singapore', 'May 1', 'May 6', '200,000', 'Report'], ['12', 'Hong Kong Super Series', 'Ma On Shan Sports Centre\\nQueen Elizabeth Stadium', 'Ma On Shan\\nWan Chai', 'November 26', 'December 2', '200,000', 'Report'], ['2', 'Korea Open Super Series', 'Seoul National University Gymnasium', 'Seoul', 'January 23', 'January 28', '300,000', 'Report'], ['6', 'Indonesia Super Series', 'Bung Karno Stadium', 'Jakarta', 'May 7', 'May 13', '250,000', 'Report'], ['10', 'French Super Series', 'Stade Pierre de Coubertin', 'Paris', 'October 30', 'November 4', '200,000', 'Report'], ['13', 'Super Series Finals', 'Cancelled', 'Cancelled', 'Cancelled', 'Cancelled', '500,000', 'Report'], ['3', 'All England Super Series', 'National Indoor Arena', 'Birmingham', 'March 6', 'March 11', '200,000', 'Report']]
|
6 days
|
Answer:
| 128
| 13
| 538
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which racer was the only one not to finish on the final lap?
|
[['Pos', 'Rider', 'Manufacturer', 'Time/Retired', 'Points'], ['Ret', 'Andre Romein', 'Honda', 'Retirement', ''], ['23', 'Arno Visscher', 'Aprilia', '+1:40.635', ''], ['3', 'Jeremy McWilliams', 'Aprilia', '+0.534', '16'], ['Ret', 'Maurice Bolwerk', 'TSR-Honda', 'Retirement', ''], ['8', 'Stefano Perugini', 'Honda', '+20.891', '8'], ['1', 'Loris Capirossi', 'Honda', '38:04.730', '25'], ['19', 'Fonsi Nieto', 'Yamaha', '+1:25.622', ''], ['9', 'Jason Vincent', 'Honda', '+21.310', '7'], ['17', 'Johann Stigefelt', 'Yamaha', '+1:07.433', ''], ['11', 'Alex Hofmann', 'TSR-Honda', '+26.933', '5'], ['12', 'Sebastian Porto', 'Yamaha', '+27.054', '4'], ['16', 'Luca Boscoscuro', 'TSR-Honda', '+56.432', ''], ['7', 'Franco Battaini', 'Aprilia', '+20.889', '9'], ['2', 'Valentino Rossi', 'Aprilia', '+0.180', '20'], ['Ret', 'Roberto Rolfo', 'Aprilia', 'Retirement', ''], ['18', 'Julien Allemand', 'TSR-Honda', '+1:16.347', ''], ['4', 'Tohru Ukawa', 'Honda', '+0.537', '13'], ['22', 'Rudie Markink', 'Aprilia', '+1:40.280', ''], ['14', 'Masaki Tokudome', 'TSR-Honda', '+33.161', '2'], ['10', 'Anthony West', 'TSR-Honda', '+26.816', '6'], ['6', 'Ralf Waldmann', 'Aprilia', '+7.019', '10'], ['24', 'Henk Van De Lagemaat', 'Honda', '+1 Lap', ''], ['Ret', 'Marcellino Lucchi', 'Aprilia', 'Retirement', ''], ['15', 'Jarno Janssen', 'TSR-Honda', '+56.248', '1'], ['13', 'Tomomi Manako', 'Yamaha', '+27.903', '3'], ['5', 'Shinya Nakano', 'Yamaha', '+0.742', '11'], ['21', 'David Garcia', 'Yamaha', '+1:33.867', ''], ['20', 'Lucas Oliver Bulto', 'Yamaha', '+1:25.758', '']]
|
Henk Van De Lagemaat
|
Answer:
| 128
| 28
| 627
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:when did leonor piuza last compete in a race?
|
[['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['2009', 'World Championships', 'Berlin, Germany', '36th (h)', '800 m', '2:06.72'], ['2007', 'All-Africa Games', 'Algiers, Algeria', '1st', '800 m', '2:02.83'], ['2006', 'Lusophony Games', 'Macau', '1st', '800 m', '2:07.34'], ['2006', 'Commonwealth Games', 'Melbourne, Australia', '9th (sf)', '800 m', '2:01.84'], ['2010', 'Commonwealth Games', 'Delhi, India', '–', '800 m', 'DNF'], ['2010', 'African Championships', 'Nairobi, Kenya', '7th', '800 m', '2:08.45'], ['2006', 'African Championships', 'Bambous, Mauritius', '13th (h)', '800 m', '2:10.50'], ['2008', 'African Championships', 'Addis Ababa, Ethiopia', '6th', '800 m', '2:05.95'], ['2011', 'All-Africa Games', 'Maputo, Mozambique', '12th (h)', '800 m', '2:06.72'], ['2003', 'All-Africa Games', 'Abuja, Nigeria', '11th (h)', '800 m', '2:05.19'], ['2009', 'Lusophony Games', 'Lisbon, Portugal', '4th', '800 m', '2:07.48']]
|
2011
|
Answer:
| 128
| 11
| 364
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what continent is listed at the top of the table?
|
[['Naturalisations by origin', '2000', '2005', '2009', '% Total 2009'], ['Asia', '27 941', '26 286', '19 494', '14.4'], ['Maghreb', '68 185', '75 224', '56 024', '41.2'], ['Others', '8 882', '3 245', '4 962', '3.7'], ['South-East Asia', '7 265', '4 069', '2 475', '1.8'], ['CIS', '1 181', '2 108', '4 704', '3.5'], ['South Asia', '4 246', '4 436', '3 660', '2.7'], ['Oceania', '87', '127', '108', '0.1'], ['East Asia', '1 139', '1 280', '1 622', '1.2'], ['CIS (Europe)', '1 000', '1 535', '4 454', '3.3'], ['Europe (not including CIS )', '22 085', '18 072', '14 753', '10.9'], ['America', '5 668', '6 352', '6 677', '4.9'], ['South and Central America', '4 620', '5 498', '5 930', '4.4'], ['Africa', '84 182', '98 453', '85 144', '62.7'], ['North America', '1 048', '854', '747', '0.5'], ['Total', '150 026', '154 643', '135 842', '100'], ['CIS (Asia)', '181', '573', '250', '0.2'], ['Other Asia', '15 291', '16 501', '11 737', '8.6'], ['Other Africa', '5 375', '7 605', '6 906', '5.1'], ['Sub-Saharan Africa', '10 622', '15 624', '22 214', '16.4']]
|
Africa
|
Answer:
| 128
| 19
| 471
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year was the only year in which the team won the co-championship title?
|
[['Year', 'Division', 'League', 'Reg. Season', 'Playoffs', 'National Cup'], ['1943/44', 'N/A', 'ASL', '3rd', 'No playoff', '?'], ['1948/49', 'N/A', 'ASL', 'Withdrew after 3 games', 'N/A', 'N/A'], ['1946/47', 'N/A', 'ASL', '4th', 'No playoff', '?'], ['1942/43', 'N/A', 'ASL', '5th', 'No playoff', '?'], ['1934/35', 'N/A', 'ASL', '6th', 'No playoff', '?'], ['1944/45', 'N/A', 'ASL', '4th', 'No playoff', '?'], ['1935/36', 'N/A', 'ASL', '2nd', 'No playoff', '?'], ['1936/37', 'N/A', 'ASL', '2nd, American', '1st Round', '?'], ['1941/42', 'N/A', 'ASL', '5th', 'No playoff', '?'], ['1938/39', 'N/A', 'ASL', '5th, American', 'Did not qualify', '?'], ['1945/46', 'N/A', 'ASL', '1st', 'Champion (no playoff)', '?'], ['1937/38', 'N/A', 'ASL', '4th, American', 'Did not qualify', '?'], ['1940/41', 'N/A', 'ASL', '3rd', 'No playoff', '?'], ['1939/40', 'N/A', 'ASL', '2nd(t)', 'No playoff', 'Co-champion'], ['1947/48', 'N/A', 'ASL', '4th', 'No playoff', '?']]
|
1939/40
|
Answer:
| 128
| 15
| 405
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what were the total number of deaths in 2003?
|
[['Year', 'Injuries (US $000)', 'Deaths (age <15)', 'CPSC toy safety funding\\n(US$ Millions)', 'Toy sales\\n(US $ Billions)'], ['1995', '139', '', '', ''], ['2001', '255', '25', '12.4', ''], ['1996', '130', '', '', ''], ['2000', '191', '17', '12.0', ''], ['2006', 'no data', '22', 'no data†', '22.3'], ['1994', '154', '', '', ''], ['2002', '212', '13', '12.2', '21.3'], ['2003', '206', '11', '12.8', '20.7'], ['1998', '153', '14', '', ''], ['1999', '152', '16', '13.6', ''], ['1997', '141', '', '', ''], ['2004', '210', '16', '11.5', '22.4'], ['2005', '202 (estimate)', '20', '11.0', '22.2'], ['2008', 'no data', '19', 'no data', ''], ['2009', 'no data', '12', 'no data', ''], ['2007', 'no data', '22', 'no data', '']]
|
11
|
Answer:
| 128
| 16
| 305
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many hard surface courts are there?
|
[['Outcome', 'No.', 'Date', 'Tournament', 'Surface', 'Opponent', 'Score'], ['Runner-up', '2.', '20 July 2003', 'Mercedes Cup, Stuttgart, Germany', 'Clay', 'Guillermo Coria', '2–6, 2–6, 1–6'], ['Runner-up', '5.', '14 January 2007', 'Heineken Open, Auckland, New Zealand', 'Hard', 'David Ferrer', '4–6, 2–6'], ['Winner', '4.', '16 July 2006', 'Swedish Open, Båstad, Sweden', 'Clay', 'Nikolay Davydenko', '6–2, 6–1'], ['Winner', '8.', '14 February 2009', 'Brasil Open, Costa do Sauípe, Brazil', 'Clay', 'Thomaz Bellucci', '6–3, 3–6, 6–4'], ['Winner', '11.', '14 April 2013', 'Grand Prix Hassan II, Casablanca, Morocco', 'Clay', 'Kevin Anderson', '7–6(8–6), 4–6, 6–3'], ['Winner', '2.', '2 May 2004', 'Torneo Godó, Barcelona, Spain', 'Clay', 'Gastón Gaudio', '6–3, 4–6, 6–2, 3–6, 6–3'], ['Winner', '9.', '22 February 2009', 'Copa Telmex, Buenos Aires, Argentina', 'Clay', 'Juan Mónaco', '7–5, 2–6, 7–6(7–5)'], ['Runner-up', '4.', '30 April 2006', 'Torneo Godó, Barcelona, Spain', 'Clay', 'Rafael Nadal', '4–6, 4–6, 0–6'], ['Winner', '6.', '7 October 2007', 'Open de Moselle, Metz, France', 'Hard (i)', 'Andy Murray', '0–6, 6–2, 6–3'], ['Runner-up', '6.', '16 September 2007', 'China Open, Beijing, China', 'Hard (i)', 'Fernando González', '1–6, 6–3, 1–6'], ['Winner', '7.', '13 July 2008', 'Swedish Open, Båstad, Sweden (2)', 'Clay', 'Tomáš Berdych', '6–4, 6–1'], ['Runner-up', '1.', '15 April 2001', 'Grand Prix Hassan II, Casablanca, Morocco', 'Clay', 'Guillermo Cañas', '5–7, 2–6'], ['Winner', '5.', '5 August 2007', 'Orange Warsaw Open, Sopot, Poland (2)', 'Clay', 'José Acasuso', '7–5, 6–0'], ['Winner', '1.', '29 July 2001', 'Orange Warsaw Open, Sopot, Poland', 'Clay', 'Albert Portas', '1–6, 7–5, 7–6(7–2)'], ['Winner', '10.', '6 February 2011', 'Chile Open, Santiago, Chile', 'Clay', 'Santiago Giraldo', '6–2, 2–6, 7–6(7–5)'], ['Winner', '3.', '21 May 2006', 'Hamburg Masters, Hamburg, Germany', 'Clay', 'Radek Štěpánek', '6–1, 6–3, 6–3'], ['Winner', '12.', '28 July 2013', 'ATP Vegeta Croatia Open Umag, Umag, Croatia', 'Clay', 'Fabio Fognini', '6–0, 6–3'], ['Runner-up', '3.', '1 May 2005', 'Estoril Open, Estoril, Portugal', 'Clay', 'Gastón Gaudio', '1–6, 6–2, 1–6'], ['Runner-up', '7.', '15 June 2008', 'Orange Warsaw Open, Warsaw, Poland', 'Clay', 'Nikolay Davydenko', '3–6, 3–6']]
|
3
|
Answer:
| 128
| 19
| 976
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the least amount of points scored in a season?
|
[['Season', 'Class', 'Moto', 'Races', 'Win', 'Podiums', 'Pole', 'Pts', 'Position'], ['2007', '125cc', 'Derbi', '17', '0', '0', '0', '19', '22nd'], ['2013', 'Moto2', 'Suter', '17', '3', '4', '1', '150', '7th'], ['2014', 'Moto2', 'Suter', '1', '0', '0', '0', '0*', 'NC*'], ['2006', '125cc', 'Derbi', '16', '0', '0', '0', '53', '14th'], ['2009', '125cc', 'Aprilia', '16', '1', '4', '0', '179.5', '3rd'], ['Total', '', '', '147', '16', '39', '9', '1213.5', ''], ['2012', 'Moto2', 'Suter', '17', '0', '1', '0', '37', '17th'], ['2010', '125cc', 'Aprilia', '16', '3', '14', '1', '296', '2nd'], ['2008', '125cc', 'Aprilia', '17', '1', '5', '0', '176', '5th'], ['2004', '125cc', 'Aprilia', '1', '0', '0', '0', '0', 'NC'], ['2005', '125cc', 'Derbi', '13', '0', '0', '0', '1', '36th'], ['2011', '125cc', 'Aprilia', '16', '8', '11', '7', '302', '1st']]
|
0
|
Answer:
| 128
| 12
| 402
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many specifications have no active directory federation services?
|
[['Specifications', 'Foundation', 'Essentials', 'Standard', 'Datacenter'], ['Server Manager', 'Yes', 'Yes', 'Yes', 'Yes'], ['Licensing model', 'Per server', 'Per server', 'Per CPU pair + CAL', 'Per CPU pair + CAL'], ['Processor chip limit', '1', '2', '64', '64'], ['File Services limits', '1 standalone DFS root', '1 standalone DFS root', 'Unlimited', 'Unlimited'], ['User limit', '15', '25', 'Unlimited', 'Unlimited'], ['Memory limit', '32 GB', '64 GB', '4 TB', '4 TB'], ['Active Directory Domain Services', 'Must be root of forest and domain', 'Must be root of forest and domain', 'Yes', 'Yes'], ['Active Directory Certificate Services', 'Certificate Authorities only', 'Certificate Authorities only', 'Yes', 'Yes'], ['Active Directory Lightweight Directory Services', 'Yes', 'Yes', 'Yes', 'Yes'], ['Remote Desktop Services limits', '50 Remote Desktop Services connections', 'Gateway only', 'Unlimited', 'Unlimited'], ['Application server role', 'Yes', 'Yes', 'Yes', 'Yes'], ['Fax server role', 'Yes', 'Yes', 'Yes', 'Yes'], ['DHCP role', 'Yes', 'Yes', 'Yes', 'Yes'], ['Active Directory Rights Management Services', 'Yes', 'Yes', 'Yes', 'Yes'], ['DNS server role', 'Yes', 'Yes', 'Yes', 'Yes'], ['Print and Document Services', 'Yes', 'Yes', 'Yes', 'Yes'], ['Active Directory Federation Services', 'Yes', 'No', 'Yes', 'Yes'], ['Virtualization rights', 'N/A', 'Either in 1 VM or 1 physical server, but not both at once', '2 VMs', 'Unlimited'], ['Windows Powershell', 'Yes', 'Yes', 'Yes', 'Yes'], ['Distribution', 'OEM only', 'Retail, volume licensing, OEM', 'Retail, volume licensing, OEM', 'Volume licensing and OEM'], ['Windows Server Update Services', 'No', 'Yes', 'Yes', 'Yes'], ['Web Services (Internet Information Services)', 'Yes', 'Yes', 'Yes', 'Yes'], ['Hyper-V', 'No', 'No', 'Yes', 'Yes'], ['Windows Deployment Services', 'Yes', 'Yes', 'Yes', 'Yes'], ['UDDI Services', 'Yes', 'Yes', 'Yes', 'Yes'], ['Server Core mode', 'No', 'No', 'Yes', 'Yes'], ['Network Policy and Access Services limits', '50 RRAS connections and 10 IAS connections', '250 RRAS connections, 50 IAS connections, and 2 IAS Server Groups', 'Unlimited', 'Unlimited']]
|
1
|
Answer:
| 128
| 27
| 596
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total major races has melissa morrison-howard placed first in?
|
[['Year', 'Competition', 'Venue', 'Position', 'Event'], ['1997', 'USA Outdoor Championships', 'Indianapolis, United States', '1st', '100 m hurdles'], ['2000', 'Olympic Games', 'Sydney, Australia', '3rd', '100 m hurdles'], ['1997', 'World Indoor Championships', 'Paris, France', '5th', '60 m hurdles'], ['1998', 'Grand Prix Final', 'Moscow, Russia', '2nd', '100 m hurdles'], ['1998', 'USA Indoor Championships', '', '1st', '60 m hurdles'], ['2002', 'Grand Prix Final', 'Paris, France', '7th', '100 m hurdles'], ['2004', 'Olympic Games', 'Athens, Greece', '3rd', '100 m hurdles'], ['2000', 'Grand Prix Final', 'Doha, Qatar', '4th', '100 m hurdles'], ['1999', 'World Indoor Championships', 'Maebashi, Japan', '6th', '60 m hurdles'], ['2003', 'World Athletics Final', 'Monaco', '6th', '100 m hurdles'], ['2002', 'USA Indoor Championships', '', '1st', '60 m hurdles'], ['2003', 'World Indoor Championships', 'Birmingham, England', '3rd', '60 m hurdles']]
|
3
|
Answer:
| 128
| 12
| 294
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many distributions support the x86 architecture?
|
[['Distribution', 'x86', 'x86-64', 'ia64', 'ppc', 'ppc64', 'sparc32', 'sparc64', 'arm', 'hppa', 'mips', 'sh', 's390', 's390x', 'alpha', 'm68k'], ['Porteus', 'Yes', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['BOSS Linux', 'Yes', 'Yes', 'No', 'Yes', 'Yes', 'No', 'No', '?', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['MEPIS', 'Yes', 'Yes', 'No', 'No', 'No', 'No', 'No', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['SUSE Linux Enterprise Server', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'Yes', 'No', 'No'], ['Red Hat Linux', 'Yes', 'No', 'Discontinued\\n7.1-7.2', 'Test release\\n5.1', 'No', 'Discontinued\\n4.0-4.2\\n5.1-6.2', 'Test release\\n5.1', 'No', 'No', 'Test release\\n5.1', 'No', 'Discontinued\\n7.2', 'Discontinued\\n7.1', 'Discontinued\\n2.1-7.1', 'Test release\\n5.1'], ['Gentoo', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes', 'Yes'], ['Oracle Linux', 'Yes', 'Yes', 'Discontinued\\n5', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['BackTrack', 'Yes', 'Yes', 'No', 'No', 'No', 'No', 'No', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['Source Mage GNU/Linux', 'Yes', 'Yes', 'No', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['Finnix', 'Yes', 'Yes', 'No', 'Yes', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['XBMC', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['Distribution', 'x86', 'x86-64', 'ia64', 'ppc', 'ppc64', 'sparc32', 'sparc64', 'arm', 'hppa', 'mips', 'sh', 's390', 's390x', 'alpha', 'm68k'], ['CRUX', 'Yes', 'Yes', 'No', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['Fedora', 'Yes', 'Yes', 'Discontinued from\\nFedora 9', 'Yes', 'Yes', 'No', 'Still active but slow in development, Last available is\\nFedora 12\\n, Working on\\nFedora 18', 'Yes', 'No', 'Inactive from\\nFedora 13', 'No', 'No', 'Yes', 'No', 'No'], ['OpenELEC', 'Yes', 'Yes', 'No', 'No', 'No', 'No', 'No', 'Yes', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['Scientific Linux', 'Yes', 'Yes', 'Discontinued\\n3-4', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No', 'No'], ['Arch Linux', 'Yes (>=i686)', 'Yes', 'No', 'Discontinued unofficial port', 'No', 'No', 'No', 'Yes\\nUnofficial', 'No', 'No', 'No', 'No', 'No', 'No', 'No']]
|
29
|
Answer:
| 128
| 17
| 1,066
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the only player to come from westmeath county?
|
[['Rank', 'Player', 'County', 'Tally', 'Total', 'Opposition'], ['9', 'Tom Dempsey', 'Wexford', '1–5', '8', 'Offaly'], ['3', 'Gary Kirby', 'Limerick', '0–10', '10', 'Tipperary'], ['9', 'John Byrne', 'Carlow', '2–2', '8', 'Westmeath'], ['9', 'Paul Flynn', 'Waterford', '1–5', '8', 'Tipperary'], ['6', 'David Martin', 'Meath', '1–6', '9', 'Offaly'], ['2', 'Niall English', 'Carlow', '1–9', '12', 'Westmeath'], ['9', 'John Leahy', 'Tipperary', '2–2', '8', 'Kerry'], ['6', 'Seán McLoughlin', 'Westmeath', '1–6', '9', 'Carlow'], ['9', 'Francis Forde', 'Galway', '1–5', '8', 'New York'], ['1', 'Francis Forde', 'Galway', '2–8', '14', 'Roscommon'], ['3', 'Kevin Broderick', 'Galway', '3–1', '10', 'New York'], ['3', 'Gary Kirby', 'Limerick', '1–7', '10', 'Tipperary'], ['6', 'Gary Kirby', 'Limerick', '0–9', '9', 'Antrim'], ['9', 'John Troy', 'Offaly', '2–2', '8', 'Laois']]
|
Seán McLoughlin
|
Answer:
| 128
| 14
| 367
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:are the dates in a consecutive order?
|
[['Wrestler:', 'Reigns:', 'Date:', 'Place:', 'Notes:'], ['Ricky Santana', '2', 'March 23, 1996', 'Caguas, Puerto Rico', ''], ['TNT', '1', 'June 17, 1989', 'San Juan, Puerto Rico', 'Defeats Abudda Dein; vacant on February 9, 1990 when TNT wins the WWC Universal Heavyweight Title'], ['B.J.', '1', 'January 6, 2008', 'Choliseo, Puerto Rico', 'Wins the title after winning an 11 man Battle Royal'], ['Invader I', '1', 'November 5, 1986', 'San Juan, Puerto Rico', ''], ['Dick Murdoch', '2', 'January 6, 1992', 'San Juan, Puerto Rico', 'Vacant on January 6, 1993 when Murdoch leaves the promotion.'], ['Ray Gonzalez', '1', 'April 27, 2002', 'San Lorenzo, Puerto Rico', ''], ['Mighty Koadiak', '1', '1994', '', ''], ['Super Black Ninja', '1', 'February 6, 1988', 'Guaynabo, Puerto Rico', ''], ['Ash Rubinsky', '1', 'November 24, 2007', 'Bayamon, Puerto Rico', 'Wins a 7-man battle royal.'], ['Glamour Boy Shane', '1', 'April 2, 1999', 'Guaynabo, Puerto Rico', 'Defeated "Jungle" Jim Steele for vacant title.'], ['Ron Starr', '2', 'June 25, 1988', 'Carolina, Puerto Rico', ''], ['Glamour Boy Shane', '2', 'September 19, 1999', 'Guaynabo, Puerto Rico', ''], ['Crazy Rudy', '1', 'April 28, 2007', 'Bayamon, Puerto Rico', ''], ['TNT', '2', 'April 25, 1990', 'San Juan, Puerto Rico', 'Won the vacant title'], ['Sean Morley', '1', '1995', '', ''], ['Sweet Brown Sugar (Skip Young)', '1', 'January 6, 1996', 'Caguas, Puerto Rico', ''], ['Fidel Sierra', '1', 'October 19, 1991', 'Bayamon, Puerto Rico', ''], ['Vengador Boricua', '1', 'July 19, 2003', 'Carolina, Puerto Rico', 'title becomes inactive when Vengador Boricua leaves the company.'], ['Mighty Koadiak', '2', 'November 26, 1995', '', ''], ['Carlos Colon', '1', 'August 20, 1988', 'Bayamon, Puerto Rico', ''], ['TNT', '3', 'March 30, 1991', 'Bayamon, Puerto Rico', ''], ['Carlos Colon', '2', 'March 1, 1989', 'Carolina, Puerto Rico', 'Vacant on May 22, 1989 after Colon was injured by Steve Strong on May 20, 1989'], ['Vacant', '', '', '', 'Chris Joel Jumps to IWA'], ['Alex Porteau', '1', 'July 7, 2001', 'Carolina, Puerto Rico', ''], ['Chris Grant', '1', 'April 21, 2001', 'Orocovis, Puerto Rico', ''], ['Rex King', '3', 'March 19, 2000', 'Cabo Rojo, Puerto Rico', ''], ['Rico Suave', '2', 'March 17, 2007', 'Bayamon, Puerto Rico', ''], ['Wilfredo Alejandro', '1', 'July 6, 2002', 'Cayey, Puerto Rico', 'wins a battle royal for the vacant title.'], ['Invader I', '5', 'December 25, 1991', 'San Juan, Puerto Rico', ''], ['Hammett', '1', 'March 1, 2008', 'Tao Baja, Puerto Rico', ''], ['Chris Candido', '1', 'June 6, 2003', 'Cayey, Puerto Rico', ''], ['Jason The Terrible', '2', 'January 28, 1989', 'Carolina, Puerto Rico', ''], ['Carlos Colon', '4', 'June 8, 2002', 'Toa Baja, Puerto Rico', ''], ['TNT', '5', 'October 26, 1991', 'Carolina, Puerto Rico', '']]
|
yes
|
Answer:
| 128
| 34
| 1,023
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the first name on the chart?
|
[['#', 'Name', 'Height', 'Weight (lbs.)', 'Position', 'Class', 'Hometown', 'Previous Team(s)'], ['40', 'Jon Brockman', '6\'7"', '255', 'F', 'Jr.', 'Snohomish, WA, U.S.', 'Snohomish Sr. HS'], ['44', 'Darnell Gant', '6\'8"', '215', 'F', 'Fr.', 'Los Angeles, CA, U.S.', 'Crenshaw HS'], ['20', 'Ryan Appleby', '6\'3"', '170', 'G', 'Sr.', 'Stanwood, WA, U.S.', 'Florida'], ['32', 'Joe Wolfinger', '7\'0"', '255', 'C', 'RS So.', 'Portland, OR, U.S.', 'Northfield Mount Hermon School'], ['0', 'Joel Smith', '6\'4"', '210', 'G', 'RS Jr.', 'Lompoc, CA, U.S.', 'Brewster Academy'], ['1', 'Venoy Overton', '5\'11"', '180', 'G', 'Fr.', 'Seattle, WA, U.S.', 'Franklin HS'], ['11', 'Matthew Bryan-Amaning', '6\'9"', '235', 'F', 'Fr.', 'London, England, U.K.', 'South Kent School'], ['24', 'Quincy Pondexter', '6\'6"', '210', 'F', 'So.', 'Fresno, CA, U.S.', 'San Joaquin Memorial HS'], ['5', 'Justin Dentmon', '5\'11"', '185', 'G', 'Jr.', 'Carbondale, IL, U.S.', 'Winchendon School'], ['22', 'Justin Holiday', '6\'6"', '170', 'F', 'Fr.', 'Chatsworth, CA, U.S.', 'Campbell Hall School'], ['4', 'Tim Morris', '6\'4"', '210', 'G', 'Sr.', 'Spokane Wa, U.S.', 'Central Valley HS'], ['21', 'Artem Wallace', '6\'8"', '250', 'C', 'Jr.', 'Toledo, WA, U.S.', 'Toledo HS']]
|
Joel Smith
|
Answer:
| 128
| 12
| 486
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which date had the most attendance?
|
[['Date', 'Opponent#', 'Rank#', 'Site', 'TV', 'Result', 'Attendance'], ['January 1', 'vs.\xa0#12\xa0Washington*', '#13', 'Rose Bowl • Pasadena, CA (Rose Bowl)', 'NBC', 'L\xa00-28', '105,611'], ['September 12', '#7\xa0Nebraska*', '', 'Kinnick Stadium • Iowa City, IA', '', 'W\xa010-7', '60,160'], ['November 14', 'at\xa0Wisconsin', '', 'Camp Randall Stadium • Madison, WI', 'ABC', 'W\xa017-7', '78,731'], ['October 3', 'at\xa0Northwestern', '#18', 'Dyche Stadium • Evanston, IL', '', 'W\xa064-0', '30,113'], ['November 21', 'Michigan State', '#19', 'Kinnick Stadium • Iowa City, IA', '', 'W\xa036-7', '60,103'], ['October 31', 'at\xa0Illinois', '#16', 'Memorial Stadium • Champaign, IL', '', 'L\xa07-24', '66,877'], ['October 10', 'Indiana', '#15', 'Kinnick Stadium • Iowa City, IA', '', 'W\xa042-28', '60,000'], ['September 26', '#6\xa0UCLA*', '', 'Kinnick Stadium • Iowa City, IA', '', 'W\xa020-7', '60,004'], ['October 24', 'Minnesota', '#6', 'Kinnick Stadium • Iowa City, IA (Floyd of Rosedale)', 'ABC', 'L\xa010-12', '60,000'], ['October 17', 'at\xa0#5\xa0Michigan', '#12', 'Michigan Stadium • Ann Arbor, MI', '', 'W\xa09-7', '105,915'], ['November 7', 'Purdue', '', 'Kinnick Stadium • Iowa City, IA', '', 'W\xa033-7', '60,114'], ['September 19', 'at\xa0Iowa State*', '', 'Cyclone Stadium • Ames, IA (Cy-Hawk Trophy)', '', 'L\xa012-23', '53,922']]
|
October 17
|
Answer:
| 128
| 12
| 489
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:fulham and stoke city both won with how many points?
|
[['Tie no', 'Home team', 'Score', 'Away team', 'Date', 'Attendance'], ['2', 'Southampton', '1 – 1', 'Millwall', '25 January 2003', '23,809'], ['4', 'Walsall', '2 – 0', 'Wimbledon', '25 January 2003', '6,693'], ['Replay', 'Millwall', '1 – 2', 'Southampton', '5 February 2003', '10,197'], ['15', 'Farnborough Town', '1 – 5', 'Arsenal', '25 January 2003', '35,108'], ['Replay', 'Sunderland', '2 – 2', 'Blackburn Rovers', '5 February 2003', '15,745'], ['16', 'Stoke City', '3 – 0', 'Bournemouth', '26 January 2003', '12,004'], ['3', 'Watford', '1 – 0', 'West Bromwich Albion', '25 January 2003', '16,975'], ['11', 'Brentford', '0 – 3', 'Burnley', '25 January 2003', '9,563'], ['10', 'Fulham', '3 – 0', 'Charlton Athletic', '26 January 2003', '12,203'], ['9', 'Sheffield United', '4 – 3', 'Ipswich Town', '25 January 2003', '12,757'], ['1', 'Rochdale', '2 – 0', 'Coventry City', '25 January 2003', ''], ['13', 'Norwich City', '1 – 0', 'Dagenham & Redbridge', '25 January 2003', '21,164'], ['7', 'Wolverhampton Wanderers', '4 – 1', 'Leicester City', '25 January 2003', '28,164'], ['8', 'Shrewsbury Town', '0 – 4', 'Chelsea', '26 January 2003', '7,950'], ['12', 'Manchester United', '6 – 0', 'West Ham United', '26 January 2003', '67,181'], ['6', 'Blackburn Rovers', '3 – 3', 'Sunderland', '25 January 2003', '14,315'], ['5', 'Gillingham', '1 – 1', 'Leeds United', '25 January 2003', '11,093'], ['Replay', 'Liverpool', '0 – 2', 'Crystal Palace', '5 February 2003', '35,109'], ['Replay', 'Leeds United', '2 – 1', 'Gillingham', '4 February 2003', '29,359'], ['14', 'Crystal Palace', '0 – 0', 'Liverpool', '26 January 2003', '26,054']]
|
3
|
Answer:
| 128
| 20
| 641
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of times the team did not qualify for playoffs?
|
[['Year', 'Division', 'League', 'Reg. Season', 'Playoffs'], ['2013', '1', 'USL W-League', '4th, Western', 'Did not qualify'], ['2008', '1', 'USL W-League', '6th, Western', 'Did not qualify'], ['2004', '1', 'USL W-League', '8th, Western', ''], ['2005', '1', 'USL W-League', '6th, Western', ''], ['2007', '1', 'USL W-League', '5th, Western', ''], ['2009', '1', 'USL W-League', '7th, Western', 'Did not qualify'], ['2010', '1', 'USL W-League', '6th, Western', 'Did not qualify'], ['2012', '1', 'USL W-League', '4th, Western', 'Did not qualify'], ['2011', '1', 'USL W-League', '7th, Western', 'Did not qualify'], ['2006', '1', 'USL W-League', '5th, Western', ''], ['2003', '2', 'USL W-League', '5th, Western', '']]
|
6
|
Answer:
| 128
| 11
| 267
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country placed first the most?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['7', 'Egypt', '0', '1', '7', '8'], ['5', 'Turkey', '1', '1', '0', '2'], ['1', 'France', '11', '5', '3', '19'], ['3', 'Yugoslavia', '3', '2', '1', '6'], ['4', 'Spain', '1', '5', '5', '11'], ['2', 'Greece', '6', '7', '6', '19'], ['5', 'Morocco', '1', '1', '0', '2'], ['8', 'Tunisia', '0', '1', '0', '1'], ['Totaal', 'Totaal', '23', '23', '22', '68']]
|
France
|
Answer:
| 128
| 9
| 192
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many designers do not have an associated publication?
|
[['Year', 'Designer(s)', 'Brief description', 'Selected by:', 'Associated publication'], ['1986', 'Giorgio Armani', 'Female: Checked wool jacket, skirt, and black suede shoes\\nMale: Jacket, trousers, shirt and brogues', 'Colin McDowell', 'Country Life'], ['1978', 'Female: Gordon Luke Clarke\\nMale: Cerruti', 'Female: Printed cotton & polyester jersey tunic, skirt and trousers worn with black leather skirt and coat\\nMale: Coat, jacket, waistcoat & trousers, knitted wool and wool tweed', 'Barbara Griggs', 'The Daily Mail'], ['1971', 'Female: Graziella Fontana for Judith Hornby\\nRavel (sandals)\\nMale: Rupert Lycett Green for Blades', 'Female: Hot pants suit in checked Liberty cotton\\nMale: Black velvet evening suit & boots', 'Serena Sinclair and Patrick Lichfield', 'The Daily Telegraph'], ['1993', 'Donna Karan', 'Purple wool & stretch velvet dress, hat & boots', 'Glenda Bailey', 'Marie Claire'], ['2002', 'Junya Watanabe', 'Dress, pieced together knit & jersey fabrics, with distressed cow-hide shoes', 'Hilary Alexander', 'The Daily Telegraph'], ['2003', 'Marni', 'Colorful printed dress', 'Lucinda Chambers', 'Vogue'], ['1977', 'Kenzo Takada of Jungle Jap', 'Shirt-dress in khaki cotton, straw hat & plimsolls', 'Ann Boyd', 'The Observer'], ['1984', 'Female: BodyMap\\nFemale: Betty Jackson\\nBrian Bolger: (scarf)\\nMale: Katharine Hamnett', 'Female: Ensemble comprising skirt, jumper, stockings, hat, waxed jacket & earrings (BodyMap)\\nFemale: Dress, cardigan & hat and scarf (Jackson & Bolger)\\nMale: T-shirt, shirt and cotton trousers', 'Brenda Polan', 'The Guardian'], ['1967', 'David Bond for Slimma\\nEdward Mann (hat)\\nSaxone (shoes)', "Woman's trouser suit, hat & blouse in striped cotton", 'Felicity Green', 'The Daily Mirror'], ['2009', 'Antonio Berardi', "White and black trompe l'oeil corset dress", 'Lucy Yeomans', "Harper's Bazaar"], ['2000', 'Donatella Versace for Versace', 'Bamboo-print silk chiffon evening dress and jeweled mules', 'Lisa Armstrong', 'The Times'], ['1999', 'Alexander McQueen', 'Cream lace dress with brown leather collar and sandals', 'Susannah Frankel', 'The Independent'], ['1981', 'Karl Lagerfeld for Chloé\\nWalter Steiger (shoes)\\nUgo Correani (necklace)', 'Printed white silk dress', 'Vanessa de Lisle', "Harper's & Queen"], ['1995', 'Female: Catherine Rayner\\nEmma Hope (shoes)\\nMale: Tom Gilbey', 'Female: Beaded ivory silk satin wedding dress\\nMale: Ivory silk frock coat, cream wool trousers and embroidered waistcoat', 'Sandra Boler', 'Brides'], ['1976', 'Female: Kenzo Takada of Jungle Jap\\nMale: Fiorucci', 'Female: Two printed cotton ensembles with wooden jewellery\\nMale: Hand-knitted sweater, two shirts and jeans', 'Helena Matheopoulos', 'The Daily Express'], ['2012', 'Raf Simons for Christian Dior', 'Embroidered and appliquéd silk cut-off ballgown and black cigarette pants', 'Vanessa Friedman', 'Financial Times'], ['2006', 'Prada', "Woman's olive green coat with fur patch pockets", 'Sarah Mower', ''], ['1973', 'Female: Marc Bohan for Christian Dior London\\nMale: Yves Saint Laurent Rive Gauche', 'Female: White wool coat & hat\\nMale: Wool jacket, trousers & sweater', 'Alison Adburgham', 'The Guardian'], ['1996', 'Female: Alexander McQueen\\nMale: Paul Smith', "Female: Floral brocade top with red 'bumster' trousers\\nMale: Bright blue two-piece suit and shirt", 'Tamsin Blanchard', 'The Independent'], ['1998', 'Female: Sonia Rykiel\\nMale: Chris Bailey for Jigsaw Menswear', 'Female: Black knitted sweater & combat trousers, with pink marabou stole\\nMale: Silver-grey suit, white T-shirt and ankle-length puffa jacket', 'Iain R. Webb', 'Elle']]
|
6
|
Answer:
| 128
| 20
| 1,028
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what were the most labels?
|
[['Year', 'Name', 'Label', 'Hot Black Singles', 'Club Play Singles'], ['1983', '"I Need You Now"', 'Jive', '―', '―'], ['1986', '"Say It Again"', 'Spring', '―', '―'], ['1982', '"Thanks to You"', 'Becket', '#44', '#1'], ['1986', '"Say It Again"', 'Spring', '―', '―'], ['1984', '"Thin Line"', 'Power House', '―', '―'], ['1987', '"Send It C.O.D."', 'New Image', '―', '―'], ['1982', '"He\'s Gonna Take You Home"', 'Becket', '―', '―']]
|
Becket
|
Answer:
| 128
| 7
| 157
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many seasons were played ?
|
[['Season', 'Club', 'Competition', 'Games', 'Goals'], ['2006/07', 'KSV Roeselare', 'Jupiler League', '29', '1'], ['2003/04', 'RAEC Mons', 'Jupiler League', '23', '0'], ['2007/08', 'KSV Roeselare', 'Jupiler League', '25', '0'], ['2005/06', 'KSV Roeselare', 'Jupiler League', '26', '0'], ['2009/10', 'Excelsior Mouscron', 'Jupiler League', '14', '1'], ['', '', 'Totaal', '278', '4'], ['2002/03', 'RAEC Mons', 'Jupiler League', '19', '0'], ['2009/10', 'Győri ETO FC', 'Soproni Liga', '1', '0'], ['2008/09', 'Excelsior Mouscron', 'Jupiler League', '31', '1'], ['2010/11', 'Kortrijk', 'Jupiler League', '0', '0'], ['2004/05', 'KSV Roeselare', 'Belgian Second Division', '29', '1']]
|
10
|
Answer:
| 128
| 11
| 284
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which party was in office the most?
|
[['#', 'Name', 'Took office', 'Left office', 'Party', 'Governor', 'Notes'], ['31', 'F. Harold Van Orman', 'January 12, 1925', 'January 14, 1929', 'Republican', 'Edward L. Jackson', ''], ['20', 'Mahlon Dickerson Manson', 'January 12, 1885', 'August 3, 1886', 'Democrat', 'Isaac P. Gray', ''], ['13', 'Abram A. Hammond', 'January 12, 1857', 'October 3, 1860', 'Democrat', 'Ashbel P. Willard', ''], ['2', 'Ratliff Boon', 'December 8, 1819', 'September 12, 1822', 'Democratic-Republican', 'Jonathan Jennings', ''], ['40', 'Crawford F. Parker', 'January 14, 1957', 'January 9, 1961', 'Republican', 'Harold W. Handley', ''], ['9', 'Jesse D. Bright', 'December 6, 1843', 'December 6, 1845', 'Democrat', 'James Whitcomb', ''], ['7', 'David Hillis', 'December 6, 1837', 'December 9, 1840', 'Whig', 'David Wallace', ''], ['35', 'Charles M. Dawson', 'January 13, 1941', 'January 8, 1945', 'Democrat', 'Henry F. Schricker', ''], ['49', 'Becky Skillman', 'January 10, 2005', 'January 14, 2013', 'Republican', 'Mitch Daniels', ''], ['28', "William P. O'Neill", 'January 13, 1913', 'January 8, 1917', 'Democrat', 'Samuel M. Ralston', ''], ['33', 'M. Clifford Townsend', 'January 9, 1933', 'January 11, 1937', 'Democrat', 'Paul V. McNutt', ''], ['—', 'James J. Nejdl', 'April 30, 1924', 'January 12, 1925', 'Republican', 'Warren T. McCray', 'acting'], ['16', 'William Cumback', 'January 11, 1869', 'January 13, 1873', 'Republican', 'Conrad Baker', ''], ['–', 'Alonzo G. Smith', 'November 8, 1886', 'January 14, 1889', 'Democrat', 'Isaac P. Gray', 'acting'], ['32', 'Edgar D. Bush', 'January 14, 1929', 'January 9, 1933', 'Republican', 'Harry G. Leslie', ''], ['5', 'Milton Stapp', 'December 3, 1828', 'December 7, 1831', 'Independent', 'James B. Ray', ''], ['36', 'Richard T. James', 'January 8, 1945', 'January 10, 1948', 'Republican', 'Ralph F. Gates', ''], ['50', 'Sue Ellspermann', 'January 14, 2013', 'Incumbent', 'Republican', 'Mike Pence', ''], ['12', 'Ashbel P. Willard', 'January 10, 1853', 'January 12, 1857', 'Democrat', 'Joseph A. Wright', ''], ['30', 'Emmett Forrest Branch', 'January 10, 1921', 'April 30, 1924', 'Republican', 'Warren T. McCray', ''], ['45', 'John Mutz', 'January 12, 1981', 'January 9, 1989', 'Republican', 'Robert D. Orr', ''], ['22', 'Ira Joy Chase', 'January 14, 1889', 'November 24, 1891', 'Republican', 'Alvin Peterson Hovey', 'acting'], ['14', 'Oliver P. Morton', 'January 14, 1861', 'January 16, 1861', 'Republican', 'Henry Smith Lane', ''], ['21', 'Robert S. Robertson', 'January 10, 1887', 'January 13, 1889', 'Republican', 'Isaac P. Gray', ''], ['15', 'Conrad Baker', 'January 9, 1865', 'January 23, 1867', 'Republican', 'Oliver P. Morton', '']]
|
Republican
|
Answer:
| 128
| 25
| 1,010
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what nation comes first?
|
[['Rank', 'Lane', 'Nation', 'Swimmers', 'Time', 'Time behind', 'Notes'], ['7', '8', 'France', 'Amaury Leveaux (1:48.57)\\nFabien Horth (1:48.67)\\nNicolas Kintz (1:50.01)\\nNicolas Rostoucher (1:50.18)', '7:17.43', '10.10', ''], ['6', '3', 'Germany', 'Jens Schreiber (1:49.08)\\nHeiko Hell (1:49.15)\\nLars Conrad (1:48.23)\\nChristian Keller (1:50.05)', '7:16.51', '9.18', ''], ['', '4', 'United States', 'Michael Phelps (1:46.49)\\nRyan Lochte (1:47.52)\\nPeter Vanderkaay (1:47.79)\\nKlete Keller (1:45.53)', '7:07.33', '', 'AM'], ['8', '1', 'Greece', 'Apostolos Antonopoulos (1:50.34)\\nDimitrios Manganas (1:51.33)\\nAndreas Zisimos (1:50.26)\\nNikolaos Xylouris (1:51.09)', '7:23.02', '15.67', ''], ['4', '6', 'Great Britain', "Simon Burnett (1:47.90)\\nGavin Meadows (1:48.46)\\nDavid O'Brien (1:49.05)\\nRoss Davenport (1:47.19)", '7:12.60', '5.27', ''], ['', '7', 'Italy', 'Emiliano Brembilla (1:48.16)\\nMassimiliano Rosolino (1:46.24)\\nSimone Cercato (1:49.85)\\nFilippo Magnini (1:47.58)', '7:11.83', '4.50', ''], ['5', '2', 'Canada', 'Brent Hayden (1:49.08)\\nBrian Johns (1:49.15)\\nAndrew Hurd (1:48.09)\\nRick Say (1:47.01)', '7:13.33', '6.00', ''], ['', '5', 'Australia', 'Grant Hackett (1:47.50)\\nMichael Klim (1:47.62)\\nNicholas Sprenger (1:48.16)\\nIan Thorpe (1:44.18)', '7:07.46', '0.13', '']]
|
United States
|
Answer:
| 128
| 8
| 613
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:last year a mf won?
|
[['Season', 'Footballer', 'Club', 'Position', 'Nationality'], ['2010-11', 'Thulani Serero', 'Ajax Cape Town', 'MF', 'South Africa'], ['2002-03', 'Moeneeb Josephs', 'Ajax Cape Town', 'GK', 'South Africa'], ['2009-10', 'Katlego Mphela', 'Mamelodi Sundowns', 'FW', 'South Africa'], ['2006-07', 'Godfrey Sapula', 'Mamelodi Sundowns', 'MF', 'South Africa'], ['2012-13', 'Itumeleng Khune', 'Kaizer Chiefs', 'GK', 'South Africa'], ['2000-01', 'Benjani Mwaruwari', 'Jomo Cosmos', 'FW', 'Zimbabwe'], ['2003-04', 'Tinashe Nengomasha', 'Kaizer Chiefs', 'MF', 'Zimbabwe'], ['2005-06', 'Surprise Moriri', 'Mamelodi Sundowns', 'MF', 'South Africa'], ['2008-09', 'Teko Modise', 'Orlando Pirates', 'MF', 'South Africa'], ['2001-02', 'Jabu Pule', 'Kaizer Chiefs', 'MF', 'South Africa'], ['1997-98', 'Raphael Chukwu', 'Mamelodi Sundowns', 'FW', 'Nigeria'], ['1999-00', 'Siyabonga Nomvethe', 'Kaizer Chiefs', 'FW', 'South Africa'], ['2011-12', 'Siyabonga Nomvethe', 'Moroka Swallows', 'FW', 'South Africa'], ['1998-99', 'Roger Feutmba', 'Mamelodi Sundowns', 'MF', 'Cameroon'], ['1996-97', 'Wilfred Mugeyi', 'Bush Bucks', 'FW', 'Zimbabwe'], ['2007-08', 'Itumeleng Khune', 'Kaizer Chiefs', 'GK', 'South Africa'], ['2004-05', 'Sandile Ndlovu', 'Dynamos', 'FW', 'South Africa']]
|
2010-11
|
Answer:
| 128
| 17
| 462
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what date had the least number of attendees?
|
[['Date', 'Opponent', 'Venue', 'Result', 'Attendance', 'Scorers'], ['10 September 2005', 'Chelsea', 'Stamford Bridge', '0–2', '41,969', ''], ['20 August 2005', 'Liverpool', 'Anfield', '0–1', '44,913', ''], ['11 March 2006', 'Wigan Athletic', 'Stadium of Light', '0–1', '31,194', ''], ['26 December 2005', 'Bolton Wanderers', 'Stadium of Light', '0–0', '32,232', ''], ['2 January 2006', 'Fulham', 'Craven Cottage', '1–2', '19,372', 'Lawrence'], ['14 April 2006', 'Manchester United', 'Old Trafford', '0–0', '72,519', ''], ['7 May 2006', 'Aston Villa', 'Villa Park', '1–2', '33,820', 'D. Collins'], ['15 October 2005', 'Manchester United', 'Stadium of Light', '1–3', '39,085', 'Elliott'], ['29 October 2005', 'Portsmouth', 'Stadium of Light', '1–4', '34,926', 'Whitehead (pen)'], ['12 February 2006', 'Tottenham Hotspur', 'Stadium of Light', '1–1', '34,700', 'Murphy'], ['30 November 2005', 'Liverpool', 'Stadium of Light', '0–2', '32,697', ''], ['22 April 2006', 'Portsmouth', 'Fratton Park', '1–2', '20,078', 'Miller'], ['21 January 2006', 'West Bromwich Albion', 'The Hawthorns', '1–0', '26,464', 'Watson (own goal)'], ['26 November 2005', 'Birmingham City', 'Stadium of Light', '0–1', '32,442', ''], ['23 August 2005', 'Manchester City', 'Stadium of Light', '1–2', '33,357', 'Le Tallec'], ['25 February 2006', 'Birmingham City', "St. Andrew's", '0–1', '29,257', ''], ['1 October 2005', 'West Ham United', 'Stadium of Light', '1–1', '31,212', 'Miller'], ['5 November 2005', 'Arsenal', 'Highbury', '1–3', '38,210', 'Stubbs'], ['4 February 2006', 'West Ham United', 'Boleyn Ground', '0–2', '34,745', ''], ['18 March 2006', 'Bolton Wanderers', 'Reebok Stadium', '0–2', '23,568', ''], ['17 April 2006', 'Newcastle United', 'Stadium of Light', '1–4', '40,032', 'Hoyte'], ['25 March 2006', 'Blackburn Rovers', 'Stadium of Light', '0–1', '29,593', ''], ['23 October 2005', 'Newcastle United', "St James' Park", '2–3', '52,302', 'Lawrence, Elliott'], ['1 April 2006', 'Everton', 'Goodison Park', '2–2', '38,093', 'Stead, Delap'], ['19 November 2005', 'Aston Villa', 'Stadium of Light', '1–3', '39,707', 'Whitehead (pen)'], ['13 August 2005', 'Charlton Athletic', 'Stadium of Light', '1–3', '34,446', 'Gray'], ['3 March 2006', 'Manchester City', 'City of Manchester Stadium', '1–2', '42,200', 'Kyle'], ['15 February 2006', 'Blackburn Rovers', 'Ewood Park', '0–2', '18,220', ''], ['25 September 2005', 'Middlesbrough', 'Riverside Stadium', '2–0', '29,583', 'Miller, Arca'], ['27 August 2005', 'Wigan Athletic', 'JJB Stadium', '0–1', '17,223', ''], ['31 December 2005', 'Everton', 'Stadium of Light', '0–1', '30,567', ''], ['10 December 2005', 'Charlton Athletic', 'The Valley', '0–2', '26,065', '']]
|
27 August 2005
|
Answer:
| 128
| 32
| 1,018
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how may away games did they win?
|
[['Week', 'Date', 'Opponent', 'Result', 'Attendance'], ['4', 'September 27, 1981', 'at New York Jets', 'L 33–17', '50,309'], ['9', 'November 1, 1981', 'at Cincinnati Bengals', 'L 34–21', '54,736'], ['1', 'September 6, 1981', 'at Los Angeles Rams', 'W 27–20', '63,198'], ['12', 'November 22, 1981', 'New Orleans Saints', 'L 27–24', '49,581'], ['6', 'October 11, 1981', 'Seattle Seahawks', 'W 35–17', '42,671'], ['14', 'December 3, 1981', 'Cleveland Browns', 'W 17–13', '44,502'], ['16', 'December 20, 1981', 'Pittsburgh Steelers', 'W 21–20', '41,056'], ['5', 'October 4, 1981', 'Cincinnati Bengals', 'W 17–10', '44,350'], ['15', 'December 13, 1981', 'at San Francisco 49ers', 'L 28–6', '55,707'], ['3', 'September 20, 1981', 'Miami Dolphins', 'L 16–10', '47,379'], ['11', 'November 15, 1981', 'at Kansas City Chiefs', 'L 23–10', '73,984'], ['8', 'October 26, 1981', 'at Pittsburgh Steelers', 'L 26–13', '52,732'], ['10', 'November 8, 1981', 'Oakland Raiders', 'W 17–16', '45,519'], ['2', 'September 13, 1981', 'at Cleveland Browns', 'W 9–3', '79,483'], ['7', 'October 18, 1981', 'at New England Patriots', 'L 38–10', '60,474'], ['13', 'November 29, 1981', 'Atlanta Falcons', 'L 31–27', '40,201']]
|
7
|
Answer:
| 128
| 16
| 485
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total subjects are listed?
|
[['Subject', "Robot's Name", 'Who?', 'When?', 'Where?', 'Occupation'], ['Phonograph', 'Slide the Heavy-Metal Robot', 'Thomas Edison', '1877', 'New Jersey', 'Rock Star'], ['Nursing', 'Dr. Bug-Bot', 'Florence Nightengale', '1860', 'England', 'Doctor'], ['Basketball', 'Danny Defrost-Bot', 'James Naismith', '1891', 'United States', 'Snowman'], ['Helicopter', 'Amelia Air-Bot', 'Leonardo da Vinci', '1483', 'Italy', 'Pilot'], ['Chewing Gum', 'Bubble-Bot', 'Mayans', '400', 'Mexico', 'Bubble Man'], ['Sausage', 'Sock-Bot', 'Babylonians', '3,000 B.C.', 'Middle East', 'Sock Man'], ['Wheel', "Rollin' Road-Bot", 'Sumerians', '3,000 B.C.', 'Middle East', 'Race Starter'], ['Writing', 'Eraser-Bot', 'Sumerians', '3,500 B.C.', 'Middle East', 'Pencil Man'], ['Germs', 'Roast-Bot', 'Louis Pasteur', '1865', 'France', 'Firefighter'], ['Scuba Gear', 'Flip the High-Diving Robot', 'Jacques Cousteau', '1946', 'France', 'Diver'], ['Radium', 'Miss Battery-Bot', 'Marie Curie', '1898', 'France', 'Battery Lady'], ['Solar System', 'Cosmo-Bot', 'Copernicus', '1531', 'Poland', 'Cosmonaut'], ['Dynamite', 'Robby Robot', 'Alfred Nobel', '1866', 'Sweden', 'Prankster'], ['Boomerang', 'Oswald the Mailman Robot', 'Aborigines', '40,000 years ago', 'Australia', 'Mailman'], ['Coins', 'Verna the Vend-Bot', 'Lydians', '600 B.C.', 'Turkey', 'Vending Machine'], ['Tools', 'Hank the Handyman Robot', 'Stone-Age Humans', '2½ million years ago', 'Africa', 'Mechanic'], ['Bicycle', 'Booster-Bot', 'Karl von Drais', '1816', 'Germany', 'Rocket Man'], ['Microscope', 'Slobot', 'Antonie van Leeuwenhoek', '1674', 'The Netherlands', 'Dirty Person'], ['Round Earth', 'Vasco da Robot', 'Ferdinand Magellan', '1522', 'Spain', 'Early Sailor'], ['Olympics', 'Rhonda Robot', 'Greeks', '776 B.C.', 'Greece', 'Beauty queen'], ['Toilet', 'Brunwella the Bombshell', 'Minoans', '2000 B.C.', 'Crete', 'Demolisher'], ['Painting', 'Pierro-Bot', 'Stone-Age Humans', '35,000 B.C.', 'Europe', 'Clown/Artist'], ['Saxophone', 'Bongo-Bot the Six-Armed Robot', 'Antoine-Joseph Sax', '1846', 'France', 'Six-Armed Drum Player'], ['Corn Flakes', 'Chef Boy-Robot', 'William Kellogg', '1894', 'Battle Creek, Michigan', 'Cook'], ['Paper', 'Noshi Origami', "Ts'ai Lun", '105', 'China', 'Origami Maker']]
|
25
|
Answer:
| 128
| 25
| 759
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which manufacturer did the top racer use?
|
[['Pos', 'Rider', 'Manufacturer', 'Time/Retired', 'Points'], ['19', 'Fonsi Nieto', 'Yamaha', '+1:25.622', ''], ['Ret', 'Marcellino Lucchi', 'Aprilia', 'Retirement', ''], ['6', 'Ralf Waldmann', 'Aprilia', '+7.019', '10'], ['9', 'Jason Vincent', 'Honda', '+21.310', '7'], ['Ret', 'Roberto Rolfo', 'Aprilia', 'Retirement', ''], ['7', 'Franco Battaini', 'Aprilia', '+20.889', '9'], ['5', 'Shinya Nakano', 'Yamaha', '+0.742', '11'], ['2', 'Valentino Rossi', 'Aprilia', '+0.180', '20'], ['10', 'Anthony West', 'TSR-Honda', '+26.816', '6'], ['4', 'Tohru Ukawa', 'Honda', '+0.537', '13'], ['13', 'Tomomi Manako', 'Yamaha', '+27.903', '3'], ['15', 'Jarno Janssen', 'TSR-Honda', '+56.248', '1'], ['Ret', 'Andre Romein', 'Honda', 'Retirement', ''], ['23', 'Arno Visscher', 'Aprilia', '+1:40.635', ''], ['3', 'Jeremy McWilliams', 'Aprilia', '+0.534', '16'], ['18', 'Julien Allemand', 'TSR-Honda', '+1:16.347', ''], ['21', 'David Garcia', 'Yamaha', '+1:33.867', ''], ['1', 'Loris Capirossi', 'Honda', '38:04.730', '25'], ['14', 'Masaki Tokudome', 'TSR-Honda', '+33.161', '2'], ['8', 'Stefano Perugini', 'Honda', '+20.891', '8'], ['12', 'Sebastian Porto', 'Yamaha', '+27.054', '4'], ['20', 'Lucas Oliver Bulto', 'Yamaha', '+1:25.758', ''], ['17', 'Johann Stigefelt', 'Yamaha', '+1:07.433', ''], ['24', 'Henk Van De Lagemaat', 'Honda', '+1 Lap', ''], ['Ret', 'Maurice Bolwerk', 'TSR-Honda', 'Retirement', ''], ['22', 'Rudie Markink', 'Aprilia', '+1:40.280', ''], ['16', 'Luca Boscoscuro', 'TSR-Honda', '+56.432', ''], ['11', 'Alex Hofmann', 'TSR-Honda', '+26.933', '5']]
|
Honda
|
Answer:
| 128
| 28
| 627
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many have a water level under 240cm?
|
[['', 'Chronological\\nNo.', 'Date\\n(New style)', 'Water level\\ncm', 'Peak hour'], ['3', '71', '9 September 1777', '321', 'morning'], ['45', '116', '8 October 1863', '227', '2:00'], ['18', '83', '24 January 1822', '254', 'night'], ['14', '25', '10 September 1736', '261', ''], ['42', '125', '19 January 1866', '229', '10:00'], ['49', '202', '24 August 1918', '224', '9:10'], ['21', '201', '17 November 1917', '244', '6:50'], ['28', '260', '20 December 1973', '240', '7:15'], ['40', '269', '7 September 1977', '231', '16:50'], ['13', '319', '30 November 1999', '262', '4:35'], ['35', '227', '9 September 1937', '236', '5:30'], ['37', '41', '26 October 1752', '234', '12:00'], ['32', '76', '29 September 1788', '237', '–'], ['8', '14', '1 November 1726', '270', '–'], ['11', '86', '20 August 1831', '264', 'night'], ['12', '3', '9 September 1706', '262', 'daytime'], ['20', '55', '20 November 1764', '244', '–'], ['39', '228', '14 September 1938', '233', '2:25'], ['9', '183', '13 November 1903', '269', '9:00'], ['43', '208', '24 November 1922', '228', '19:15'], ['44', '315', '12 October 1994', '228', '13:50'], ['10', '7', '5 November 1721', '265', 'daytime'], ['48', '122', '19 May 1865', '224', '9:10'], ['24', '136', '20 October 1873', '242', '–'], ['47', '81', '6 September 1802', '224', 'daytime'], ['34', '171', '2 November 1895', '237', '3:00'], ['4', '244', '15 October 1955', '293', '20:45'], ['27', '177', '26 November 1898', '240', '23:30'], ['26', '261', '17 November 1974', '242', '1:00'], ['19', '144', '29 October 1874', '252', '4:00'], ['50', '242', '14 October 1954', '222', '21:00'], ['31', '18', '12 October 1729', '237', '10:00'], ['36', '37', '17 October 1744', '234', '–'], ['41', '292', '1 January 1984', '231', '21:20'], ['22', '254', '18 October 1967', '244', '13:30'], ['6', '39', '22 October 1752', '280', '10:00'], ['38', '43', '11 December 1752', '234', 'night'], ['46', '211', '3 January 1925', '225', '21:30'], ['29', '219', '8 January 1932', '239', '3:00'], ['23', '45', '29 September 1756', '242', ''], ['7', '9', '2 October 1723', '272', '–'], ['16', '215', '15 October 1929', '258', '17:15'], ['15', '298', '6 December 1986', '260', '13:30'], ['5', '264', '29 September 1975', '281', '4:00'], ['25', '175', '4 November 1897', '242', '12:00'], ['33', '145', '26 November 1874', '237', '4:00'], ['2', '210', '23 September 1924', '380', '19:15'], ['30', '225', '8 October 1935', '239', '5:50'], ['1', '84', '19 November 1824', '421', '14:00']]
|
22
|
Answer:
| 128
| 49
| 1,028
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:besides seattle what other american city was a venue?
|
[['Date', 'Venue', 'Opponent', 'Result', 'Scoreline', 'China scorers'], ['January 27', 'Zhongshan', 'Syria', 'Won', '2-1', "Qu Bo 64'\\nZhu Ting 90'"], ['Dec 21', 'Amman', 'Jordan', 'Won', '1-0', "Cao Yang 77'"], ['Dec 19', 'Muscat', 'Iran', 'Lost', '0-2', ''], ['January 20', 'Zhongshan', 'Lebanon', 'Drawn', '0-0', '—'], ['May 25', 'Kunshan', 'Jordan', 'Won', '2-0', "Hao Junmin 23' pen\\nLi Weifeng 48'"], ['April 16', 'Seattle', 'Mexico', 'Lost', '0-1', '—'], ['April 23', 'Los Angeles', 'El Salvador', 'Drawn', '2-2', "Xiao Zhanbo 62' pen\\nQu Bo 63'"], ['January 10', 'Dubai', 'United Arab Emirates', 'Drawn', '0-0', '—'], ['March 15', 'Kunming', 'Thailand', 'Drawn', '3-3', "Qu Bo 34'\\nHan Peng 67'\\nZhu Ting 90'"], ['Dec 17', 'Muscat', 'Oman', 'Lost', '1-3', "Qu Bo 58'"]]
|
Los Angeles
|
Answer:
| 128
| 10
| 337
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:is the first reagent for a hydroxyalkyl usually a halogenoalkane or an epoxide?
|
[['Cellulose ethers', 'Reagent', 'Example', 'Reagent', 'Group R = H or', 'Water solubility', 'Application', 'E number'], ['', '', 'Hydroxypropyl cellulose (HPC)', 'Propylene oxide', '-CH2CH(OH)CH3', 'Cold water soluble', '', 'E463'], ['', '', 'Hydroxyethyl methyl cellulose', 'Chloromethane and ethylene oxide', '-CH3 or -CH2CH2OH', 'Cold water soluble', 'Production of cellulose films', ''], ['', '', 'Ethyl methyl cellulose', 'Chloromethane and chloroethane', '-CH3 or -CH2CH3', '', '', 'E465'], ['Hydroxyalkyl', 'Epoxides', 'Hydroxyethyl cellulose', 'Ethylene oxide', '-CH2CH2OH', 'Cold/hot water soluble', 'Gelling and thickening agent', ''], ['', '', 'Ethyl hydroxyethyl cellulose', 'Chloroethane and ethylene oxide', '-CH2CH3 or—CH2CH2OH', '', '', 'E467'], ['', '', 'Ethylcellulose', 'Chloroethane', '-CH2CH3', 'Water insoluble', 'A commercial thermoplastic used in coatings, inks, binders, and controlled-release drug tablets', 'E462'], ['', '', 'Hydroxypropyl methyl cellulose (HPMC)', 'Chloromethane and propylene oxide', '-CH3 or -CH2CH(OH)CH3', 'Cold water soluble', 'Viscosity modifier, gelling, foaming and binding agent', 'E464'], ['Carboxyalkyl', 'Halogenated carboxylic acids', 'Carboxymethyl cellulose (CMC)', 'Chloroacetic acid', '-CH2COOH', 'Cold/Hot water soluble', 'Often used as its sodium salt, sodium carboxymethyl cellulose (NaCMC)', 'E466'], ['Alkyl', 'Halogenoalkanes', 'Methylcellulose', 'Chloromethane', '-CH3', 'Cold water soluble', '', 'E461']]
|
Epoxides
|
Answer:
| 128
| 9
| 485
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many matches were attended by at least 8,000 people?
|
[['Match Day', 'Date', 'Opponent', 'H/A', 'Score', 'Aberdeen Scorer(s)', 'Attendance'], ['16', '21 November', 'Dumbarton', 'H', '0–0', '', '5,000'], ['22', '1 January', 'Dundee', 'H', '2–1', 'Walker, J. Wyllie', '7,000'], ['35', '27 March', 'Rangers', 'A', '1–1', 'W. Wylie', '10,000'], ['1', '15 August', 'Dundee', 'A', '3–1', 'Soye, Walker, Cail', '10,000'], ['17', '28 November', 'Kilmarnock', 'A', '2–5', 'MacLachlan, McLeod', '2,500'], ['6', '19 September', 'Motherwell', 'H', '3–1', 'J. Wyllie, MacLachlan, Walker', '7,000'], ['25', '16 January', 'Clyde', 'A', '0–3', '', '3,000'], ['5', '12 September', 'Ayr United', 'A', '0–1', '', '2,000'], ['30', '20 February', 'Hibernian', 'H', '0–0', '', '8,500'], ['11', '17 October', 'Third Lanark', 'H', '1–2', 'Archibald', '6,000'], ['2', '22 August', 'Rangers', 'H', '0–2', '', '15,000'], ['7', '26 September', 'Heart of Midlothian', 'A', '0–2', '', '14,000'], ['8', '28 September', "Queen's Park", 'H', '1–1', 'Main', '5,000'], ['23', '2 January', 'Raith Rovers', 'A', '1–5', 'Cail', '6,000'], ['15', '14 November', 'Hamilton Academical', 'A', '0–3', '', '4,000'], ['19', '12 December', 'Partick Thistle', 'A', '0–3', '', '6,000'], ['38', '17 April', 'Hamilton Academical', 'H', '1–0', 'J. Wyllie', '4,000'], ['12', '24 October', 'Falkirk', 'A', '1–1', 'J. Wyllie', '5,500'], ['18', '5 December', 'Celtic', 'H', '0–1', '', '7,000'], ['37', '10 April', 'Celtic', 'A', '0–1', '', '10,000'], ['4', '5 September', 'Clyde', 'H', '2–0', 'MacLachlan, Archibald', '6,000'], ['33', '13 March', "Queen's Park", 'A', '1–3', 'Cail', '6,000'], ['9', '3 October', 'St. Mirren', 'H', '0–0', '', '6,000'], ['34', '20 March', 'Airdrieonians', 'H', '3–0', 'Brewster, Cail, Main', '5,500'], ['10', '10 October', 'Airdrieonians', 'A', '0–3', '', '7,000'], ['24', '9 January', 'Ayr United', 'H', '1–1', 'Cail', '4,500'], ['20', '19 December', 'Kilmarnock', 'H', '3–0', 'MacLachlan, Cail, Main', '4,000'], ['21', '26 December', 'Motherwell', 'A', '1–1', 'Walker', '3,000'], ['31', '27 February', 'Third Lanark', 'A', '1–0', 'Walker', '5,000'], ['29', '13 February', 'St. Mirren', 'A', '2–0', 'Cail, Walker', '3,000'], ['36', '3 April', 'Heart of Midlothian', 'H', '0–0', '', '6,000'], ['28', '6 February', 'Morton', 'H', '2–0', 'Brewster, Archibald', '2,000'], ['3', '29 August', 'Morton', 'A', '1–1', 'Cail', '4,500'], ['26', '23 January', 'Falkirk', 'H', '1–2', 'Walker', '4,000']]
|
6
|
Answer:
| 128
| 34
| 1,041
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:the chords e minor major seventh and a minor major seventh have which note in common?
|
[['Chord', 'Root', 'Minor Third', 'Perfect Fifth', 'Major Seventh'], ['CmM7', 'C', 'E♭', 'G', 'B'], ['F♯mM7', 'F♯', 'A', 'C♯', 'E♯ (F)'], ['EmM7', 'E', 'G', 'B', 'D♯'], ['G♯mM7', 'G♯', 'B', 'D♯', 'F (G)'], ['G♭mM7', 'G♭', 'B (A)', 'D♭', 'F'], ['B♭mM7', 'B♭', 'D♭', 'F', 'A'], ['AmM7', 'A', 'C', 'E', 'G♯'], ['C♯mM7', 'C♯', 'E', 'G♯', 'B♯ (C)'], ['D♭mM7', 'D♭', 'F♭ (E)', 'A♭', 'C'], ['D♯mM7', 'D♯', 'F♯', 'A♯', 'C (D)'], ['FmM7', 'F', 'A♭', 'C', 'E'], ['E♭mM7', 'E♭', 'G♭', 'B♭', 'D'], ['A♭mM7', 'A♭', 'C♭ (B)', 'E♭', 'G'], ['BmM7', 'B', 'D', 'F♯', 'A♯'], ['GmM7', 'G', 'B♭', 'D', 'F♯'], ['A♯mM7', 'A♯', 'C♯', 'E♯ (F)', 'G (A)'], ['DmM7', 'D', 'F', 'A', 'C♯']]
|
E
|
Answer:
| 128
| 17
| 438
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many individuals had at least 460+ points their final score?
|
[['Rank', 'Diver', 'Preliminary\\nPoints', 'Preliminary\\nRank', 'Final\\nPoints'], ['', 'Sylvie Bernier\xa0(CAN)', '489.51', '3', '530.70'], ['12', 'Verónica Ribot\xa0(ARG)', '443.25', '9', '422.52'], ['11', 'Anita Rossing\xa0(SWE)', '464.58', '7', '424.98'], ['24', 'Rim Hassan\xa0(EGY)', '258.63', '24', ''], ['22', 'Joana Figueiredo\xa0(POR)', '374.07', '22', ''], ['20', 'Kerstin Finke\xa0(FRG)', '393.93', '20', ''], ['13', 'Ann Fargher\xa0(NZL)', '421.65', '13', ''], ['8', 'Debbie Fuller\xa0(CAN)', '437.04', '11', '450.99'], ['16', 'Guadalupe Canseco\xa0(MEX)', '411.96', '16', ''], ['6', 'Elsa Tenorio\xa0(MEX)', '460.56', '8', '463.56'], ['5', 'Li Qiaoxian\xa0(CHN)', '466.83', '6', '487.68'], ['18', 'Valerie McFarland-Beddoe\xa0(AUS)', '401.13', '18', ''], ['19', 'Alison Childs\xa0(GBR)', '400.68', '19', ''], ['14', 'Tine Tollan\xa0(NOR)', '419.55', '14', ''], ['23', 'Angela Ribeiro\xa0(BRA)', '370.68', '23', ''], ['9', 'Jennifer Donnet\xa0(AUS)', '432.78', '12', '443.13'], ['21', 'Nicole Kreil\xa0(AUT)', '382.68', '21', ''], ['15', 'Antonette Wilken\xa0(ZIM)', '414.66', '15', ''], ['10', 'Daphne Jongejans\xa0(NED)', '487.95', '4', '437.40'], ['17', 'Claire Izacard\xa0(FRA)', '403.17', '17', ''], ['', 'Kelly McCormick\xa0(USA)', '516.75', '2', '527.46'], ['', 'Christina Seufert\xa0(USA)', '481.41', '5', '517.62'], ['4', 'Li Yihua\xa0(CHN)', '517.92', '1', '506.52'], ['7', 'Lesley Smith\xa0(ZIM)', '438.72', '10', '451.89']]
|
6
|
Answer:
| 128
| 24
| 630
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did the great pyramid of giza hold the record for tallest freestanding structure?
|
[['Name', 'Country', 'Town', 'Height\\nmetres / ft', 'Structural type', 'Held record', 'Notes'], ['Notre-Dame Cathedral', 'France', 'Rouen', '151 / 500', 'Church', '1876–1880', ''], ['Ostankino Tower', 'Russia', 'Moscow', '540 / 1,772', 'Tower', '1967–1976', ''], ['Burj Khalifa', 'United Arab Emirates', 'Dubai', '829.8 / 2,722', 'Skyscraper', '2007–present', 'Topped-out on 17 January 2009'], ['Washington Monument', 'United States', 'Washington, D.C.', '169.3 / 555', 'Monument', '1884–1889', ''], ['Strasbourg Cathedral', 'Germany and/or France (today France)', 'Strasbourg', '142 / 470', 'Church', '1647–1874', ''], ['Cologne Cathedral', 'Germany', 'Cologne', '157.4 / 516', 'Church', '1880–1884', ''], ['Eiffel Tower', 'France', 'Paris', '300.6 / 986', 'Tower', '1889–1930', 'Currently stands at a height of 324 metres (1,063\xa0ft).'], ['CN Tower', 'Canada', 'Toronto', '553 / 1,815', 'Tower', '1976–2007', ''], ['St Nikolai', 'Germany', 'Hamburg', '147.3 / 483', 'Church', '1874–1876', 'Due to aerial bombing in World War II the nave was demolished; only the spire remains.'], ['Chrysler Building', 'United States', 'New York City', '319 / 1,046', 'Skyscraper', '1930–1931', ''], ['Great Pyramid of Giza', 'Egypt', 'Giza', '146 / 480', 'Mausoleum', '2570 BC–1311', 'Due to erosion today it stands at the height of 138.8 metres (455\xa0ft).'], ['Empire State Building', 'United States', 'New York City', '448 / 1,472', 'Skyscraper', '1931–1967', ''], ['Lincoln Cathedral', 'England', 'Lincoln', '159.7 / 524', 'Church', '1311–1549', 'Spire collapsed in 1549; today, stands at a height of 83 metres (272\xa0ft).'], ["St. Mary's Church", 'Germany', 'Stralsund', '151 / 500', 'Church', '1549–1647', 'Spire destroyed by lightning in 1647; today stands at a height of 104 metres (341\xa0ft).']]
|
3881
|
Answer:
| 128
| 14
| 623
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many websites are free of advertising?
|
[['Name', 'Topic', 'Cost', 'Target age', 'Advertising'], ['HyperPhysics', 'Physics', 'Free', '15+', 'None'], ['Awesome Library', 'All', 'Free', 'All', 'Yes - large'], ['Le Patron', 'French', 'Free', '12+', 'Yes'], ['Fact Monster', 'World & News, U.S., People, English, Science, Math & Money, Sports', 'Free', '4-14 (K-8)', 'Yes'], ['Ask A Biologist', 'Biology', 'Free', '5+', 'None'], ['Smartygames.com', 'Math Games, Reading, Art, Word Scramble, Spanish, Puzzles, Kids Sudoku and more', 'Free', '2-9', 'None'], ['IXL', 'Math', '$80/year', '4-12', '?'], ['HackMath.net', 'Mathematics', 'Free', '9-18', 'None'], ['Geometry from the Land of the Incas', 'Geometry', 'Free', '12+', 'Yes - extensive'], ['LearnAlberta.ca', 'Everything (mainly aimed at teachers)', 'Free', '5-18', 'No'], ['Nafham', 'Multidisciplinary 5-20min K-12 school video lessons for Arabic students', 'Free', '6-18', 'Yes'], ['BrainPop', 'Science, Social studies, English, Maths, Art & Music, Health, Technology', 'from US$75/year', '4-17', 'None'], ['WatchKnowLearn', 'All', 'Free', '2-17', 'None'], ['Starfall.com', 'Reading', 'Free', '2-9', 'None'], ['Cut-the-Knot', 'Maths', 'Free', '8+', 'Yes - extensive'], ['Archimedes-lab.org', 'Mathematics', 'Free', '10+', 'Yes - limited'], ['Bitesize by the BBC', 'Art & Design, Business Studies, Design & Technology, DiDA, Drama, English, English Literature, French, Geography, German, History, ICT, Irish, Maths, Music, Physical Education, Religious Studies, Science, Spanish', 'Free', '5-16', 'None']]
|
9
|
Answer:
| 128
| 17
| 474
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country had the most competitors?
|
[['Pos', 'No', 'Driver', 'Constructor', 'Laps', 'Time/Retired', 'Grid', 'Points'], ['Ret', '9', 'Michele Alboreto', 'Arrows-Ford', '37', 'Engine', '25', ''], ['4', '29', 'Éric Bernard', 'Lola-Lamborghini', '64', '+ 1:15.302', '8', '3'], ['8', '4', 'Jean Alesi', 'Tyrrell-Ford', '63', '+ 1 Lap', '6', ''], ['14', '28', 'Gerhard Berger', 'McLaren-Honda', '60', 'Throttle', '3', ''], ['Ret', '16', 'Ivan Capelli', 'Leyton House-Judd', '48', 'Fuel Leak', '10', ''], ['DNQ', '7', 'David Brabham', 'Brabham-Judd', '', '', '', ''], ['5', '20', 'Nelson Piquet', 'Benetton-Ford', '64', '+ 1:24.003', '11', '2'], ['Ret', '17', 'Gabriele Tarquini', 'AGS-Ford', '41', 'Engine', '26', ''], ['Ret', '3', 'Satoru Nakajima', 'Tyrrell-Ford', '20', 'Electrical', '12', ''], ['Ret', '23', 'Pierluigi Martini', 'Minardi-Ford', '3', 'Alternator', '18', ''], ['DNPQ', '33', 'Roberto Moreno', 'EuroBrun-Judd', '', '', '', ''], ['DNPQ', '39', 'Bruno Giacomelli', 'Life', '', '', '', ''], ['1', '1', 'Alain Prost', 'Ferrari', '64', '1:18:30.999', '5', '9'], ['13', '26', 'Philippe Alliot', 'Ligier-Ford', '61', '+ 3 Laps', '22', ''], ['6', '30', 'Aguri Suzuki', 'Lola-Lamborghini', '63', '+ 1 Lap', '9', '1'], ['7', '10', 'Alex Caffi', 'Arrows-Ford', '63', '+ 1 Lap', '17', ''], ['Ret', '11', 'Derek Warwick', 'Lotus-Lamborghini', '46', 'Engine', '16', ''], ['DNQ', '14', 'Olivier Grouillard', 'Osella-Ford', '', '', '', ''], ['Ret', '22', 'Andrea de Cesaris', 'Dallara-Ford', '12', 'Fuel System', '23', ''], ['DNPQ', '18', 'Yannick Dalmas', 'AGS-Ford', '', '', '', ''], ['Ret', '12', 'Martin Donnelly', 'Lotus-Lamborghini', '48', 'Engine', '14', ''], ['Ret', '6', 'Riccardo Patrese', 'Williams-Renault', '26', 'Chassis', '7', ''], ['2', '5', 'Thierry Boutsen', 'Williams-Renault', '64', '+ 39.092', '4', '6'], ['9', '8', 'Stefano Modena', 'Brabham-Judd', '62', '+ 2 Laps', '20', ''], ['DNPQ', '31', 'Bertrand Gachot', 'Coloni-Subaru', '', '', '', ''], ['DNS', '15', 'Maurício Gugelmin', 'Leyton House-Judd', '0', 'Fuel Pump', '15', ''], ['3', '27', 'Ayrton Senna', 'McLaren-Honda', '64', '+ 43.088', '2', '4'], ['10', '25', 'Nicola Larini', 'Ligier-Ford', '62', '+ 2 Laps', '21', ''], ['12', '24', 'Paolo Barilla', 'Minardi-Ford', '62', '+ 2 Laps', '24', ''], ['11', '21', 'Emanuele Pirro', 'Dallara-Ford', '62', '+ 2 Laps', '19', ''], ['DNQ', '35', 'Gregor Foitek', 'Onyx-Ford', '', '', '', ''], ['DNPQ', '34', 'Claudio Langes', 'EuroBrun-Judd', '', '', '', ''], ['Ret', '2', 'Nigel Mansell', 'Ferrari', '55', 'Gearbox', '1', '']]
|
Italy
|
Answer:
| 128
| 33
| 1,042
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total wins did the citadel bulldogs have before 1908?
|
[['Season', 'Conference', 'Head Coach', 'Total Wins', 'Total Losses', 'Total Ties', 'Conference Wins', 'Conference Losses', 'Conference Ties', 'Conference Standing', 'Postseason Result'], ['1931', 'Southern Intercollegiate', 'Johnny Floyd', '5', '4', '1', '4', '1', '0', '—', '—'], ['1988', 'Southern', 'Charlie Taaffe', '8', '4', '0', '5', '2', '0', '3', 'First Round'], ['1912', 'Southern Intercollegiate', 'L. S. LeTellier', '3', '4', '0', '0', '3', '0', '—', '—'], ['1981', 'Southern', 'Art Baker', '7', '3', '1', '3', '2', '1', '4', '—'], ['1938', 'Southern', 'Tatum Gressette', '6', '5', '0', '2', '3', '0', '10', '—'], ['1972', 'Southern', 'Red Parker', '5', '6', '0', '4', '3', '0', '4', '—'], ['1999', 'Southern', 'Don Powers', '2', '9', '0', '1', '7', '0', '8', '—'], ['1936', 'Southern', 'Tatum Gressette', '4', '6', '0', '0', '4', '0', '14', '—'], ['1945', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team'], ['1944', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team', 'No Team'], ['1968', 'Southern', 'Red Parker', '5', '5', '0', '4', '2', '0', '2', '—'], ['1951', 'Southern', 'J. Quinn Decker', '4', '6', '0', '1', '3', '0', '14', '—'], ['Totals:\\n105 Seasons', '2 Conferences', '23 Head Coaches', 'Total\\nWins\\n473', 'Total\\nLosses\\n536', 'Total\\nTies\\n32', '239 Conference Wins\\n55 SIAA\\n184 SoCon', '379 Conference Losses\\n58 SIAA\\n321 SoCon', '13 Conference Ties\\n8 SIAA\\n5 SoCon', 'Regular Season\\nChampions\\n2 times', '1–0 Bowl Record\\n1–3 Playoff Record'], ['1963', 'Southern', 'Eddie Teague', '4', '6', '0', '2', '4', '0', '7', '—'], ['1983', 'Southern', 'Tom Moore', '3', '8', '0', '1', '6', '0', '7', '—'], ['1979', 'Southern', 'Art Baker', '6', '5', '0', '4', '2', '0', '3', '—'], ['1926', 'Southern Intercollegiate', 'Carl Prause', '7', '3', '0', '4', '3', '0', '—', '—'], ['1915', 'Southern Intercollegiate', 'George C. Rogers', '5', '3', '0', '2', '3', '0', '—', '—'], ['1989', 'Southern', 'Charlie Taaffe', '5', '5', '1', '1', '5', '1', '8', '—'], ['1947', 'Southern', 'J. Quinn Decker', '3', '5', '0', '1', '4', '0', '12', '—'], ['1998', 'Southern', 'Don Powers', '5', '6', '0', '4', '4', '0', '4', '—'], ['1976', 'Southern', 'Bobby Ross', '6', '5', '0', '1', '4', '0', '6', '—'], ['2008', 'Southern', 'Kevin Higgins', '4', '8', '—', '2', '6', '—', '7', '—'], ['1937', 'Southern', 'Tatum Gressette', '7', '4', '0', '2', '3', '0', '8', '—']]
|
6
|
Answer:
| 128
| 24
| 1,039
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:on what date did the toll for class 1 first go above 2.00?
|
[['Date introduced', 'Class 1 (e.g. Motorbike)', 'Class 2 (e.g. Car)', 'Class 3 (e.g. Car with trailer)', 'Class 4 (e.g. Van)', 'Class 5 (e.g. HGV)'], ['14 June 2005', '£2.50', '£3.50', '£7.00', '£7.00', '£7.00'], ['1 March 2011', '£3.00', '£5.30', '£9.60', '£10.60', '£10.60'], ['1 March 2010', '£2.70', '£5.00', '£9.00', '£10.00', '£10.00'], ['1 March 2012', '£3.00', '£5.50', '£10.00', '£11.00', '£11.00'], ['16 August 2004', '£2.00', '£3.00', '£6.00', '£6.00', '£6.00'], ['1 January 2009', '£2.70', '£4.70', '£8.40', '£9.40', '£9.40'], ['23 July 2004', '£1.00', '£2.00', '£5.00', '£5.00', '£6.00'], ['9 December 2003', '£1.00', '£2.00', '£5.00', '£5.00', '£10.00'], ['1 January 2008', '£2.50', '£4.50', '£8.00', '£9.00', '£9.00']]
|
14 June 2005
|
Answer:
| 128
| 9
| 392
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many number of conferences had 2 bids?
|
[['Conference', '# of Bids', 'Record', 'Win\xa0%', 'Round\\nof 32', 'Sweet\\nSixteen', 'Elite\\nEight', 'Final\\nFour', 'Championship\\nGame'], ['Atlantic Coast', '3', '9–2', '.818', '3', '2', '1', '1', '1'], ['Missouri Valley', '2', '2–2', '.500', '2', '–', '–', '–', '–'], ['Big West', '2', '0–2', '–', '–', '–', '–', '–', '–'], ['Western Athletic', '1', '1–1', '.500', '1', '–', '–', '–', '–'], ['Big East', '2', '5–2', '.714', '2', '2', '1', '–', '–'], ['Big Ten', '5', '9–5', '.643', '4', '2', '2', '1', '–'], ['Mid-Continent', '2', '0–2', '–', '–', '–', '–', '–', '–'], ['Southeastern', '6', '10–6', '.625', '5', '3', '1', '1', '–'], ['Pacific-10', '5', '8–5', '.615', '4', '2', '2', '–', '–'], ['Atlantic 10', '3', '1–3', '.250', '1', '–', '–', '–', '–'], ['Big Sky', '2', '1–2', '.333', '1', '–', '–', '–', '–'], ['Sun Belt', '2', '6–2', '.750', '2', '1', '1', '1', '1'], ['Metro', '2', '2–2', '.500', '1', '1', '–', '–', '–'], ['Great Midwest', '2', '0–2', '–', '–', '–', '–', '–', '–'], ['West Coast', '2', '0–2', '–', '–', '–', '–', '–', '–'], ['Colonial', '1', '1–1', '.500', '1', '–', '–', '–', '–'], ['Big Eight', '4', '3–4', '.429', '2', '1', '–', '–', '–'], ['Southwest', '4', '5–4', '.556', '3', '2', '–', '–', '–']]
|
9
|
Answer:
| 128
| 18
| 594
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the last listed historical place in strafford county, new hampshire?
|
[['', 'Name on the Register', 'Date listed', 'Location', 'City or town', 'Summary'], ['37', 'Wiswall Falls Mills Site', 'March 18, 1988\\n(#88000184)', 'John Hatch Park\\nSouth of Wiswall Road just east of the Lamprey River\\n43°06′15″N 70°57′44″W\ufeff / \ufeff43.1043°N 70.9621°W', 'Durham', ''], ['38', 'Woodbury Mill', 'March 25, 2013\\n(#13000156)', '1 Dover St.\\n43°12′07″N 70°52′29″W\ufeff / \ufeff43.201985°N 70.874587°W', 'Dover', ''], ['34', 'Thompson Hall', 'December 6, 1996\\n(#96001468)', 'Off Main St., University of New Hampshire campus\\n43°08′09″N 70°55′59″W\ufeff / \ufeff43.135833°N 70.933056°W', 'Durham', ''], ['6', 'First Parish Church', 'March 11, 1982\\n(#82001696)', '218 Central Ave.\\n43°10′56″N 70°52′27″W\ufeff / \ufeff43.182222°N 70.874167°W', 'Dover', ''], ['33', 'Gen. John Sullivan House', 'November 28, 1972\\n(#72000089)', '23 Newmarket Rd.\\n43°07′48″N 70°55′05″W\ufeff / \ufeff43.13°N 70.918056°W', 'Durham', 'Home of American Revolutionary War General John Sullivan, elected President of New Hampshire.'], ['23', 'Religious Society of Friends Meetinghouse', 'February 29, 1980\\n(#80000421)', '141 Central Ave.\\n43°11′12″N 70°52′25″W\ufeff / \ufeff43.186667°N 70.873611°W', 'Dover', ''], ['10', 'Green Street School', 'March 7, 1985\\n(#85000481)', '104 Green St.\\n43°15′23″N 70°51′50″W\ufeff / \ufeff43.256389°N 70.863889°W', 'Somersworth', ''], ['3', 'County Farm Bridge', 'May 21, 1975\\n(#75000237)', 'Northwest of Dover on County Farm Rd.\\n43°13′14″N 70°56′38″W\ufeff / \ufeff43.220556°N 70.943889°W', 'Dover', 'Over Cocheco River'], ['9', 'Garrison Hill Park and Tower', 'September 11, 1987\\n(#87001413)', 'Abbie Sawyer Memorial Dr.\\n43°12′34″N 70°52′13″W\ufeff / \ufeff43.209444°N 70.870278°W', 'Dover', ''], ['21', 'Queensbury Mill', 'April 10, 1987\\n(#86003362)', '1 Market St.\\n43°15′54″N 70°51′58″W\ufeff / \ufeff43.265°N 70.866111°W', 'Somersworth', ''], ['40', 'Samuel Wyatt House', 'December 2, 1982\\n(#82000626)', '7 Church St.\\n43°11′30″N 70°52′31″W\ufeff / \ufeff43.191667°N 70.875278°W', 'Dover', ''], ['14', 'Lehoullier Building', 'December 26, 1979\\n(#79000211)', '161-169 Main St.\\n43°15′31″N 70°51′46″W\ufeff / \ufeff43.258611°N 70.862778°W', 'Somersworth', ''], ['20', 'Public Market', 'March 7, 1985\\n(#85000541)', '93 Washington St.\\n43°11′43″N 70°52′31″W\ufeff / \ufeff43.195278°N 70.875278°W', 'Dover', '']]
|
Samuel Wyatt House
|
Answer:
| 128
| 13
| 995
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who scored the same number of league goals this season as gregory nelson?
|
[['Player', 'League', 'Cup', 'Europa\\nLeague', 'Total'], ['Michel Platini', '10', '0', '0', '10'], ['Boris Galchev', '1', '0', '0', '1'], ['Gregory Nelson', '3', '0', '1', '4'], ['Total', '53', '11', '14', '78'], ['Christian Tiboni', '0', '0', '1', '1'], ['Marquinhos', '9', '1', '3', '13'], ['Rumen Trifonov', '2', '0', '1', '3'], ['Todor Yanchev', '0', '1', '1', '2'], ['Aleksandar Tonev', '2', '0', '0', '2'], ['Cillian Sheridan', '4', '2', '1', '7'], ['Apostol Popov', '2', '0', '0', '2'], ['Pavel Vidanov', '0', '0', '1', '1'], ['Spas Delev', '13', '7', '2', '22'], ['Kostadin Stoyanov', '1', '0', '0', '1'], ['Emil Gargorov', '2', '0', '0', '2'], ['Giuseppe Aquaro', '3', '0', '2', '5'], ['Tomislav Kostadinov', '0', '0', '1', '1'], ['Stanislav Kostov', '1', '0', '0', '1']]
|
Giuseppe Aquaro
|
Answer:
| 128
| 18
| 354
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which track comes after "like that"?
|
[['#', 'Title', 'Featured guest(s)', 'Producer(s)', 'Time', 'Sample (s)'], ['17', '"The Outcome"', '', 'Douglas Coleman', '2:45', ''], ['12', '"Rich Rollin\'"', '', 'Dutch', '3:40', ''], ['13', '"Cheddar"', 'Mack 10 & Ice Cube', 'Mo-Suave-A', '4:12', '*"Gotta Get My Hands on Some (Money)" by The Fatback Band'], ['16', '"Better Days"', 'Ron Banks', 'Barr Nine', '3:53', '*"It\'s Gonna Be Alright" by Crimies'], ['14', '"Bank Lick"', '', 'WC', '0:49', ''], ['10', '"Like That"', 'Ice Cube, Daz Dillinger & CJ Mac', 'Daz Dillinger', '4:29', '*"Just Rhymin\' With Biz" by Big Daddy Kane\\n*"West Up!" by WC and the Maad Circle'], ['3', '"Fuckin Wit uh House Party"', '', 'Battlecat', '4:49', '*"Hollywood Squares" by Bootsy\'s Rubber Band\\n*"(Not Just) Knee Deep" by Funkadelic'], ['6', '"Keep Hustlin"', 'E-40 & Too Short', 'Young Tre', '3:39', '*"Yearning for Your Love" by The Gap Band\\n*"Intimate Connection" by Kleeer'], ['11', '"Call It What You Want"', '', 'Crazy Toones', '4:29', '*"Knucklehead" by Grover Washington, Jr.'], ['7', '"Just Clownin\'"', '', 'Battlecat', '3:59', '*"(Not Just) Knee Deep" by Funkadelic\\n*"Too Tight for Light" by Funkadelic'], ['5', '"Can\'t Hold Back"', 'Ice Cube', 'Skooby Doo', '3:34', '*"Ain\'t No Half-Steppin\'" by Big Daddy Kane'], ['2', '"Where Y\'all From"', '', 'Battlecat', '1:11', ''], ['4', '"The Shadiest One"', 'CJ Mac', 'Ant Banks', '4:26', ''], ['1', '"Hog"', '', 'Battlecat', '4:24', '*"3 Time Felons" by Westside Connection'], ['15', '"It\'s All Bad"', '', 'Battlecat', '4:15', '*"Chocolate City" by Parliament'], ['9', '"Worldwide Gunnin\'"', '', 'Skooby Doo', '3:25', ''], ['8', '"The Autobiography"', '', 'Crazy Toones', '1:21', '']]
|
"Call It What You Want"
|
Answer:
| 128
| 17
| 603
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many gold medals did south korea win?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['Total', 'Total', '24', '23', '26', '73'], ['1', 'China', '13', '9', '13', '35'], ['5', 'North Korea', '1', '0', '1', '2'], ['2', 'Japan', '7', '10', '7', '24'], ['3', 'Uzbekistan', '1', '2', '3', '6'], ['6', 'South Korea', '0', '0', '2', '2'], ['4', 'Kazakhstan', '2', '2', '0', '4']]
|
0
|
Answer:
| 128
| 7
| 151
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:after the 2006 world junior championships what was the other competition held in beijing?
|
[['Year', 'Competition', 'Venue', 'Position', 'Notes'], ['2012', 'European Championships', 'Helsinki, Finland', '6th', '5.60 m'], ['2013', 'European Indoor Championships', 'Gothenburg, Sweden', '5th', '5.71 m'], ['2005', 'World Youth Championships', 'Marrakech, Morocco', '6th', '5.05 m'], ['2009', 'World Championships', 'Berlin, Germany', '22nd (q)', '5.40 m'], ['2009', 'European U23 Championships', 'Kaunas, Lithuania', '8th', '5.15 m'], ['2011', 'World Championships', 'Daegu, South Korea', '9th', '5.65 m'], ['2014', 'World Indoor Championships', 'Sopot, Poland', '3rd', '5.80 m'], ['2012', 'Olympic Games', 'London, United Kingdom', '8th', '5.65 m'], ['2010', 'European Championships', 'Barcelona, Spain', '10th', '5.60 m'], ['2008', 'Olympic Games', 'Beijing, China', '10th', '5.45 m'], ['2006', 'World Junior Championships', 'Beijing, China', '5th', '5.30 m']]
|
Olympic Games
|
Answer:
| 128
| 11
| 296
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total points did fram have?
|
[['Pos', 'Team', 'Played', 'Won', 'Draw', 'Lost', 'Goals For', 'Goals Against', 'Goal Difference', 'Points', 'Notes'], ['2', 'Fylkir', '18', '10', '5', '3', '39', '16', '+23', '35', 'UEFA Cup'], ['5', 'ÍA', '18', '7', '5', '6', '21', '17', '+4', '26', ''], ['8', 'Fram', '18', '4', '5', '9', '22', '33', '-11', '17', ''], ['1', 'KR', '18', '11', '4', '3', '27', '14', '+13', '37', 'UEFA Champions League'], ['6', 'Keflavík', '18', '4', '7', '7', '21', '35', '-14', '19', ''], ['4', 'ÍBV', '18', '8', '5', '5', '29', '17', '+12', '29', 'Inter-Toto Cup'], ['7', 'Breiðablik', '18', '5', '3', '10', '29', '35', '-6', '18', ''], ['3', 'Grindavík', '18', '8', '6', '4', '25', '18', '+7', '30', 'UEFA Cup'], ['10', 'Leiftur', '18', '3', '7', '8', '24', '39', '-15', '16', 'Relegated'], ['9', 'Stjarnan', '18', '4', '5', '9', '18', '31', '-13', '17', 'Relegated']]
|
17
|
Answer:
| 128
| 10
| 396
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who became the oldest living president before john adams?
|
[['President', 'Became Oldest Living President', 'Ceased to Be Oldest Living President', 'Age at Start Date', 'Age at End Date', 'Duration (Years, Days)', 'Duration (Days)'], ['George Washington', 'April 30, 1789', 'December 14, 1799', '57\xa0years, 67\xa0days', '67\xa0years, 295\xa0days', '10\xa0years, 228\xa0days', '3,880 days'], ['Woodrow Wilson', 'March 4, 1913', 'February 3, 1924', '56\xa0years, 66\xa0days', '67\xa0years, 37\xa0days', '10\xa0years, 336\xa0days', '3,988 days'], ['Andrew Jackson', 'June 28, 1836', 'June 8, 1845', '69\xa0years, 105\xa0days', '78\xa0years, 85\xa0days', '8\xa0years, 345\xa0days', '3,267 days'], ['Calvin Coolidge', 'March 8, 1930', 'January 5, 1933', '57\xa0years, 247\xa0days', '60\xa0years, 185\xa0days', '2\xa0years, 303\xa0days', '1,034 days'], ['Richard Nixon', 'January 22, 1973', 'January 20, 1981', '60\xa0years, 13\xa0days', '68\xa0years, 11\xa0days', '7\xa0years, 364\xa0days', '2,920 days'], ['Martin Van Buren', 'February 23, 1848', 'July 24, 1862', '65\xa0years, 80\xa0days', '79\xa0years, 231\xa0days', '14\xa0years, 151\xa0days', '5,265 days'], ['John Adams', 'December 14, 1799', 'July 4, 1826', '64\xa0years, 45\xa0days', '90\xa0years, 247\xa0days', '26\xa0years, 202\xa0days', '9,698 days'], ['William Howard Taft', 'February 3, 1924', 'March 8, 1930', '66\xa0years, 141\xa0days', '72\xa0years, 174\xa0days', '6\xa0years, 33\xa0days', '2,225 days'], ['John Quincy Adams', 'June 8, 1845', 'February 23, 1848', '77\xa0years, 332\xa0days', '80\xa0years, 227\xa0days', '2\xa0years, 260\xa0days', '990 days'], ['Harry S. Truman', 'October 20, 1964', 'December 26, 1972', '80\xa0years, 165\xa0days', '88\xa0years, 232\xa0days', '8\xa0years, 67\xa0days', '2,989 days'], ['Herbert Hoover', 'January 5, 1933', 'October 20, 1964', '58\xa0years, 148\xa0days', '90\xa0years, 71\xa0days', '31\xa0years, 289\xa0days', '11,611 days'], ['James Buchanan', 'July 24, 1862', 'June 1, 1868', '71\xa0years, 92\xa0days', '77\xa0years, 39\xa0days', '5\xa0years, 313\xa0days', '2,139 days'], ['Ronald Reagan', 'January 20, 1981', 'June 5, 2004', '69\xa0years, 349\xa0days', '93\xa0years, 120\xa0days', '23\xa0years, 137\xa0days', '8,537 days'], ['Grover Cleveland', 'March 13, 1901', 'June 24, 1908', '63\xa0years, 360\xa0days', '71\xa0years, 98\xa0days', '7\xa0years, 103\xa0days', '2,660 days'], ['Gerald Ford', 'June 5, 2004', 'December 26, 2006', '90\xa0years, 327\xa0days', '93\xa0years, 165\xa0days', '2\xa0years, 204\xa0days', '934 days'], ['President', 'Became Oldest Living President', 'Ceased to Be Oldest Living President', 'Age at Start Date', 'Age at End Date', 'Duration (Years, Days)', 'Duration (Days)']]
|
George Washington
|
Answer:
| 128
| 16
| 1,064
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many years after the levanger church was built was the bamberg church built?
|
[['Parish', 'Church name', 'Location', 'Year built'], ['Okkenhaug', 'Okkenhaug Chapel', 'Okkenhaug', '1893'], ['Alstadhaug', 'Alstadhaug Church', 'Alstadhaug', '1180'], ['Levanger', 'Bamberg Church', 'Levanger', '1998'], ['Markabygd', 'Markabygda Church', 'Markabygd', '1887'], ['Levanger', 'Levanger Church', 'Levanger', '1902'], ['Ekne', 'Ekne Church', 'Ekne', '1893'], ['Ytterøy', 'Ytterøy Church', 'Ytterøya', '1890'], ['Åsen', 'Åsen Church', 'Åsen', '1904']]
|
96
|
Answer:
| 128
| 8
| 180
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:number of players who scored at least 1 friendly
|
[['Player', 'Friendlies', 'FIFA Confederations Cup', 'FIFA World Cup Qual.', 'Total Goals'], ['Aloisi', '1', '4', '-', '5'], ['Griffiths', '1', '-', '-', '1'], ['Colosimo', '1', '-', '-', '1'], ['Chipperfield', '1', '-', '1', '2'], ['Viduka', '1', '-', '2', '3'], ['Elrich', '1', '-', '-', '1'], ['Cahill', '-', '-', '1', '1'], ['Milicic', '2', '-', '-', '2'], ['Emerton', '-', '-', '2', '2'], ['Thompson', '1', '-', '2', '3'], ['Skoko', '-', '1', '-', '1'], ['Bresciano', '2', '-', '1', '3'], ['Culina', '-', '-', '1', '1'], ['Zdrilic', '1', '-', '-', '1']]
|
10
|
Answer:
| 128
| 14
| 216
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:calculate the average percentage of each selection.
|
[['Polling Firm', 'Source', 'Date Published', 'N.Anastasiades', 'G.Lillikas', 'S.Malas', 'Others'], ['Evresis', '[18]', '1 February 2013', '40.8%', '19.9%', '22.2%', '2.5%'], ['RAI Consultants', '[1][dead link]', '16 September 2012', '37.2%', '14.2%', '21.9%', '1.5%'], ['Prime Consulting Ltd', '[17]', '27 January 2013', '39.2%', '18.8%', '19.8%', '4%'], ['CMR Cypronetwork / Cybc', '[8]', '15 November 2012', '36.8%', '18.9%', '22.8%', '1.6%'], ['Prime Consulting Ltd', '[9]', '18 November 2012', '35.9%', '18.7%', '19.6%', '0.6%'], ['Prime Consulting Ltd', '[19]', '4 February 2013', '39.8%', '19.3%', '20%', '3%'], ['CMR Cypronetwork / Cybc', '[5][dead link]', '18 October 2012', '36.9%', '17%', '23.8%', '1.2%'], ['RAI Consultants Ltd', '[21]', '9 February 2013', '42.1%', '19.4%', '21.1%', '4.4%'], ['RAI Consultants Ltd', '[15][dead link]', '13 January 2013', '40.3%', '17.9%', '20.5%', '6.1%'], ['Noverna', '[11]', '2 December 2012', '35.6%', '17.2%', '18.1%', '4.1%'], ['Evresis', '[6]', '2 November 2012', '36.9%', '17.7%', '20.6%', '1.4%'], ['Prime Consulting Ltd', '[4]', '7 October 2012', '34.7%', '17.4%', '18.5%', ''], ['Evresis', '[14]', '22 December 2012', '37.4%', '19.8%', '21.8%', '0.5%'], ['CMR Cypronetwork / Cybc', '[16]', '17 January 2013', '38%', '19.7%', '23.7%', '2.7%'], ['Prime Consulting Ltd', '[12]', '3 December 2012', '35%', '19.1%', '18.6%', '1.4%'], ['Evresis', '[10]', '27 November 2012', '37.1%', '19.6%', '20.8%', '0.6%'], ['Noverna', '[3]', '23 September 2012', '35.02%', '15.81%', '17.78%', ''], ['CMR Cypronetwork / Cybc', '[22]', '9 February 2013', '39.9%', '20.2%', '24.2%', '3%'], ['Average (only valid votes)', '–', '–', '48.4%', '22.52%', '25.29%', '3.79%'], ['RAI Consultants', '[7]', '4 November 2012', '38.8%', '19.8%', '21.1%', '2.3%'], ['Evresis', '[2]', '18 September 2012', '35.2%', '17.5%', '19.7%', '1.7%'], ['CMR Cypronetwork / Cybc', '[13][dead link]', '17 December 2012', '37.1%', '20.4%', '23.1%', '3.1%'], ['Prime Consulting Ltd', '[20]', '9 February 2013', '40.6%', '19.6%', '20.4%', '2.9%']]
|
48.4%, 22.52%, 25.29%, 3.79%
|
Answer:
| 128
| 23
| 878
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many silver medals did macau earn?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['5', 'Macau\xa0(MAC)', '11', '16', '17', '44'], ['6', 'North Korea\xa0(PRK)', '6', '10', '20', '36'], ['2', 'Japan\xa0(JPN)', '46', '56', '77', '179'], ['Total', 'Total', '237', '230', '254', '721'], ['3', 'South Korea\xa0(KOR)', '32', '48', '65', '145'], ['8', 'Mongolia\xa0(MGL)', '1', '1', '6', '8'], ['7', 'Hong Kong\xa0(HKG)', '2', '2', '9', '13'], ['4', 'Chinese Taipei\xa0(TPE)', '12', '34', '26', '72'], ['1', 'China\xa0(CHN)', '127', '63', '33', '223'], ['9', 'Guam\xa0(GUM)', '0', '0', '1', '1']]
|
16
|
Answer:
| 128
| 10
| 243
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many different movies are on the list?
|
[['#', 'Weekend End Date', 'Film', 'Box Office'], ['29', 'July 19, 1998', 'Godzilla', '£4,176,960'], ['4', 'January 25, 1998', 'Titanic', '£4,805,270'], ['48', 'November 29, 1998', 'Antz', '£978,414'], ['24', 'June 14, 1998', 'The Wedding Singer', '£974,719'], ['51', 'December 20, 1998', 'Rush Hour', '£744,783'], ['25', 'June 21, 1998', 'City of Angels', '£1,141,654'], ['17', 'April 26, 1998', 'U.S. Marshals', '£780,012'], ['33', 'August 16, 1998', 'Armageddon', '£2,243,095'], ['52', 'December 27, 1998', 'Enemy of the State', '£1,420,216'], ['36', 'September 6, 1998', 'Lock, Stock and Two Smoking Barrels', '£1,147,448'], ['6', 'February 8, 1998', 'Titanic', '£4,274,375'], ['21', 'May 24, 1998', 'Deep Impact', '£1,601,651'], ['50', 'December 13, 1998', 'Rush Hour', '£1,179,123'], ['46', 'November 15, 1998', 'Antz', '£1,737,782'], ['5', 'February 1, 1998', 'Titanic', '£4,773,404'], ['39', 'September 27, 1998', "There's Something About Mary", '£2,076,411'], ['12', 'March 22, 1998', 'Titanic', '£1,953,082'], ['19', 'May 10, 1998', 'Scream 2', '£1,213,184'], ['26', 'June 28, 1998', 'City of Angels', '£674,705'], ['22', 'May 31, 1998', 'Deep Impact', '£1,070,805'], ['42', 'October 18, 1998', 'The Truman Show', '£1,687,037'], ['44', 'November 1, 1998', 'The Exorcist', '£2,186,977'], ['43', 'October 25, 1998', 'Small Soldiers', '£1,137,725'], ['23', 'June 7, 1998', 'The Wedding Singer', '£1,031,660'], ['28', 'July 12, 1998', 'Six Days Seven Nights', '£706,928'], ['31', 'August 2, 1998', 'Lost in Space', '£3,127,079'], ['20', 'May 17, 1998', 'Deep Impact', '£1,763,805'], ['34', 'August 23, 1998', 'The X-Files', '£2,506,148'], ['40', 'October 4, 1998', "There's Something About Mary", '£2,026,662'], ['18', 'May 3, 1998', 'Scream 2', '£2,493,950'], ['16', 'April 19, 1998', 'Titanic', '£981,940'], ['37', 'September 13, 1998', 'Saving Private Ryan', '£2,704,522'], ['41', 'October 11, 1998', 'The Truman Show', '£2,210,999'], ['10', 'March 8, 1998', 'Titanic', '£3,010,921'], ['49', 'December 6, 1998', 'Rush Hour', '£1,809,093'], ['15', 'April 12, 1998', 'Titanic', '£1,373,363'], ['27', 'July 5, 1998', 'Six Days Seven Nights', '£908,713'], ['14', 'April 5, 1998', 'Titanic', '£1,504,551'], ['7', 'February 15, 1998', 'Titanic', '£3,849,120'], ['30', 'July 26, 1998', 'Godzilla', '£2,145,088'], ['32', 'August 9, 1998', 'Armageddon', '£2,732,785']]
|
23
|
Answer:
| 128
| 41
| 1,026
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the last place driver to complete at least 50 laps?
|
[['Pos', 'No', 'Driver', 'Constructor', 'Laps', 'Time/Retired', 'Grid', 'Points'], ['10', '8', 'Nick Heidfeld', 'Williams-BMW', '65', '+1 lap', '17', ''], ['6', '7', 'Mark Webber', 'Williams-BMW', '66', '+1:08.542', '2', '3'], ['3', '16', 'Jarno Trulli', 'Toyota', '66', '+45.947', '5', '6'], ['Ret', '1', 'Michael Schumacher', 'Ferrari', '46', 'Puncture', '8', ''], ['7', '10', 'Juan Pablo Montoya', 'McLaren-Mercedes', '65', '+1 lap', '7', '2'], ['Ret', '15', 'Vitantonio Liuzzi', 'Red Bull-Cosworth', '9', 'Spun off', '11', ''], ['Ret', '11', 'Jacques Villeneuve', 'Sauber-Petronas', '51', 'Engine', '12', ''], ['Ret', '20', 'Patrick Friesacher', 'Minardi-Cosworth', '11', 'Spun off', '15', ''], ['5', '6', 'Giancarlo Fisichella', 'Renault', '66', '+57.936', '6', '4'], ['9', '2', 'Rubens Barrichello', 'Ferrari', '65', '+1 lap', '16', ''], ['1', '9', 'Kimi Räikkönen', 'McLaren-Mercedes', '66', '1:27:16.830', '1', '10'], ['13', '19', 'Narain Karthikeyan', 'Jordan-Toyota', '63', '+3 laps', '13', ''], ['8', '14', 'David Coulthard', 'Red Bull-Cosworth', '65', '+1 lap', '9', '1'], ['12', '18', 'Tiago Monteiro', 'Jordan-Toyota', '63', '+3 laps', '18', ''], ['11', '12', 'Felipe Massa', 'Sauber-Petronas', '63', 'Wheel rim', '10', ''], ['4', '17', 'Ralf Schumacher', 'Toyota', '66', '+46.719', '4', '5'], ['Ret', '21', 'Christijan Albers', 'Minardi-Cosworth', '19', 'Gearbox', '14', ''], ['2', '5', 'Fernando Alonso', 'Renault', '66', '+27.652', '3', '8']]
|
Jacques Villeneuve
|
Answer:
| 128
| 18
| 605
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers earned more than 2 points at the 2003 grand prix of monterey?
|
[['Pos', 'No', 'Driver', 'Team', 'Laps', 'Time/Retired', 'Grid', 'Points'], ['14', '33', 'Alex Tagliani', 'Rocketsports Racing', '85', '+ 2 Laps', '14', '0'], ['2', '1', 'Bruno Junqueira', 'Newman/Haas Racing', '87', '+0.8 secs', '2', '17'], ['3', '3', 'Paul Tracy', "Team Player's", '87', '+28.6 secs', '3', '14'], ['15', '4', 'Roberto Moreno', 'Herdez Competition', '85', '+ 2 Laps', '9', '0'], ['18', '15', 'Darren Manning', 'Walker Racing', '12', 'Mechanical', '7', '0'], ['16', '11', 'Geoff Boss', 'Dale Coyne Racing', '83', 'Mechanical', '19', '0'], ['7', '51', 'Adrian Fernández', 'Fernández Racing', '87', '+1:01.4', '5', '6'], ['11', '27', 'Bryan Herta', 'PK Racing', '86', '+ 1 Lap', '12', '2'], ['4', '9', 'Michel Jourdain, Jr.', 'Team Rahal', '87', '+40.8 secs', '13', '12'], ['5', '34', 'Mario Haberfeld', 'Mi-Jack Conquest Racing', '87', '+42.1 secs', '6', '10'], ['6', '20', 'Oriol Servià', 'Patrick Racing', '87', '+1:00.2', '10', '8'], ['17', '2', 'Sébastien Bourdais', 'Newman/Haas Racing', '77', 'Mechanical', '4', '0'], ['19', '5', 'Rodolfo Lavín', 'Walker Racing', '10', 'Mechanical', '16', '0'], ['8', '12', 'Jimmy Vasser', 'American Spirit Team Johansson', '87', '+1:01.8', '8', '5'], ['1', '32', 'Patrick Carpentier', "Team Player's", '87', '1:48:11.023', '1', '22'], ['10', '55', 'Mario Domínguez', 'Herdez Competition', '86', '+ 1 Lap', '11', '3'], ['9', '7', 'Tiago Monteiro', 'Fittipaldi-Dingman Racing', '86', '+ 1 Lap', '15', '4'], ['13', '19', 'Joël Camathias', 'Dale Coyne Racing', '85', '+ 2 Laps', '18', '0'], ['12', '31', 'Ryan Hunter-Reay', 'American Spirit Team Johansson', '86', '+ 1 Lap', '17', '1']]
|
10
|
Answer:
| 128
| 19
| 656
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many different flyby's have been done for the halley comet?
|
[['Comet', 'Discoverer(s) or namesake(s)', 'Orbital period (years)', 'Spacecraft encounter(s)'], ['102P/Shoemaker (Shoemaker 1)', 'C. Shoemaker & E. Shoemaker', '7.22', ''], ['293P/Spacewatch', 'Spacewatch', '6.94', ''], ['242P/Spahr', 'Spahr', '13.20', ''], ['81P/Wild (Wild 2)', 'Wild', '6.41', 'Stardust (flyby/sample return 2004)'], ['152P/Helin–Lawrence', 'Helin & Lawrence', '9.54', ''], ['217P/LINEAR', 'LINEAR', '7.83', ''], ['178P/Hug–Bell', 'Hug & Bell', '7.06', ''], ['179P/Jedicke', 'Jedicke', '14.31', ''], ['204P/LINEAR–NEAT', 'LINEAR & NEAT IAUC 8974', '7.00', ''], ['294P/LINEAR', 'LINEAR', '5.74', ''], ['100P/Hartley (Hartley 1)', 'Hartley', '6.35', ''], ['84P/Giclas', 'Giclas', '6.97', ''], ['175P/Hergenrother', 'Hergenrother', '6.34', ''], ['276P/Vorobjov', 'Vorobjov', '12.5', ''], ['78P/Gehrels (Gehrels 2)', 'Gehrels', '7.22', ''], ['30P/Reinmuth (Reinmuth 1)', 'Reinmuth', '7.34', ''], ['25D/Neujmin (Neujmin 2)', 'Neujmin', '', ''], ['33P/Daniel', 'Daniel', '8.07', ''], ['269P/Jedicke', 'V. Jedicke & R. Jedicke', '19.55', ''], ['157P/Tritton', 'Tritton', '6.29', ''], ['158P/Kowal–LINEAR', 'Kowal & LINEAR', '10.26', ''], ['202P/Scotti', 'Scotti [4]', '7.32', ''], ['273P/Pons–Gambart', 'Pons & Gambart', '188', ''], ['208P/McMillan', 'McMillan IAUC 8997, IAUC 9000', '8.16', ''], ['234P/LINEAR', 'LINEAR', '7.47', ''], ['88P/Howell', 'Howell', '5.49', ''], ['271P/van Houten–Lemmon', 'C. van Houten & I. van Houten-Groeneveld & Mount Lemmon Survey', '18.42', ''], ['146P/Shoemaker–LINEAR', 'C. Shoemaker, E. Shoemaker & LINEAR', '8.12', ''], ['210P/Christensen', 'Christensen IAUC 9005', '5.71', ''], ['39P/Oterma', 'Oterma', '19.53', ''], ['126P/IRAS', 'IRAS', '13.41', ''], ['258P/PANSTARRS', 'Pan-STARRS', '9.22', ''], ['267P/LONEOS', 'LONEOS', '5.96', ''], ['266P/Christensen', 'Christensen', '6.63', ''], ['290P/Jäger', 'Jäger', '15.2', ''], ['10P/Tempel (Tempel 2)', 'Tempel', '5.37', ''], ['159P/LONEOS', 'LONEOS', '14.32', ''], ['211P/Hill', 'Hill (Catalina Sky Survey) IAUC 9001', '6.71', ''], ['59P/Kearns–Kwee', 'Kearns & Kwee', '9.51', ''], ['251P/LINEAR', 'LINEAR', '6.52', ''], ['227P/Catalina–LINEAR', 'Catalina Sky Survey & LINEAR', '6.79', ''], ['224P/LINEAR–NEAT', 'LINEAR & NEAT', '6.30', ''], ['38P/Stephan–Oterma', 'Stephan & Oterma', '37.72', ''], ['260P/McNaught', 'McNaught', '7.07', '']]
|
6
|
Answer:
| 128
| 44
| 1,039
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long is the time frame in years of the table?
|
[['Year', 'Division', 'League', 'Regular Season', 'Playoffs', 'Open Cup'], ['2013', '4', 'USL PDL', '4th, Heartland', 'Did not qualify', 'Did not qualify'], ['1999', '4', 'USL PDL', '5th, Heartland', 'Did not qualify', 'Did not qualify'], ['2012', '4', 'USL PDL', '5th, Heartland', 'Did not qualify', 'Did not qualify'], ['2007', '4', 'USL PDL', '3rd, Heartland', 'Did not qualify', '1st Round'], ['2006', '4', 'USL PDL', '3rd, Heartland', 'Did not qualify', 'Did not qualify'], ['2010', '4', 'USL PDL', '7th, Heartland', 'Did not qualify', 'Did not qualify'], ['2001', '4', 'USL PDL', '5th, Rocky Mountain', 'Did not qualify', 'Did not qualify'], ['2008', '4', 'USL PDL', '5th, Heartland', 'Did not qualify', 'Did not qualify'], ['2005', '4', 'USL PDL', '3rd, Heartland', 'Did not qualify', 'Did not qualify'], ['2011', '4', 'USL PDL', '4th, Heartland', 'Did not qualify', 'Did not qualify'], ['2002', '4', 'USL PDL', '5th, Heartland', 'Did not qualify', 'Did not qualify'], ['1998', '4', 'USISL PDSL', '4th, Central', 'Division Finals', '1st Round'], ['2004', '4', 'USL PDL', '6th, Heartland', 'Did not qualify', 'Did not qualify'], ['2003', '4', 'USL PDL', '5th, Heartland', 'Did not qualify', 'Did not qualify'], ['2009', '4', 'USL PDL', '6th, Heartland', 'Did not qualify', 'Did not qualify'], ['2000', '4', 'USL PDL', '4th, Rocky Mountain', 'Did not qualify', 'Did not qualify']]
|
16
|
Answer:
| 128
| 16
| 500
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many races took place after august?
|
[['Date', 'Rnd', 'Race Name', 'Circuit', 'City/Location', 'Pole position', 'Winning driver', 'Winning team', 'Report'], ['2', 'April 22', 'Toyota Long Beach Grand Prix', 'Streets of Long Beach', 'Long Beach, California', 'Al Unser, Jr.', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['6', 'June 24', "Budweiser/G.I.Joe's 200", 'Portland International Raceway', 'Portland, Oregon', 'Danny Sullivan', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['5', 'June 17', 'Valvoline Grand Prix of Detroit', 'Streets of Detroit', 'Detroit, Michigan', 'Michael Andretti', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['3', 'May 27', '74th Indianapolis 500', 'Indianapolis Motor Speedway', 'Speedway, Indiana', 'Emerson Fittipaldi', 'Arie Luyendyk', 'Doug Shierson Racing', 'Report'], ['9', 'July 22', 'Molson Indy Toronto', 'Exhibition Place', 'Toronto, Ontario', 'Danny Sullivan', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['8', 'July 15', 'Marlboro Grand Prix at the Meadowlands', 'Meadowlands Sports Complex', 'East Rutherford, New Jersey', 'Michael Andretti', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['12', 'September 2', 'Molson Indy Vancouver', 'Streets of Vancouver', 'Vancouver, British Columbia', 'Michael Andretti', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['10', 'August 5', 'Marlboro 500', 'Michigan International Speedway', 'Brooklyn, Michigan', 'Emerson Fittipaldi', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['1', 'April 8', 'Autoworks 200', 'Phoenix International Raceway', 'Phoenix, Arizona', 'Rick Mears', 'Rick Mears', 'Team Penske', 'Report'], ['NC', 'October 6', 'Marlboro Challenge', 'Nazareth Speedway', 'Nazareth, Pennsylvania', 'Michael Andretti', 'Rick Mears', 'Team Penske', 'Report'], ['11', 'August 26', 'Texaco/Havoline Grand Prix of Denver', 'Streets of Denver', 'Denver, Colorado', 'Teo Fabi', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['16', 'October 21', 'Champion Spark Plug 300K', 'Laguna Seca Raceway', 'Monterey, California', 'Danny Sullivan', 'Danny Sullivan', 'Team Penske', 'Report'], ['4', 'June 3', 'Miller Genuine Draft 200', 'Milwaukee Mile', 'West Allis, Wisconsin', 'Rick Mears', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['14', 'September 23', 'Texaco/Havoline 200', 'Road America', 'Elkhart Lake, Wisconsin', 'Danny Sullivan', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['7', 'July 8', 'Budweiser Grand Prix of Cleveland', 'Cleveland Burke Lakefront Airport', 'Cleveland, Ohio', 'Rick Mears', 'Danny Sullivan', 'Team Penske', 'Report'], ['15', 'October 7', 'Bosch Spark Plug Grand Prix', 'Nazareth Speedway', 'Nazareth, Pennsylvania', 'Bobby Rahal', 'Emerson Fittipaldi', 'Team Penske', 'Report'], ['13', 'September 16', 'Red Roof Inns 200', 'Mid-Ohio Sports Car Course', 'Lexington, Ohio', 'Michael Andretti', 'Michael Andretti', 'Newman/Haas Racing', 'Report']]
|
6
|
Answer:
| 128
| 17
| 900
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what nation has won more gold medals than korea?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['3', 'Korea', '1', '1', '2', '4'], ['6', 'Denmark', '0', '1', '0', '1'], ['8', 'India', '0', '0', '1', '1'], ['9', 'Spain', '0', '0', '1', '1'], ['5', 'Chinese Taipei', '0', '1', '2', '3'], ['4', 'Thailand', '1', '0', '0', '1'], ['7', 'Japan', '0', '0', '2', '2'], ['1', 'Malaysia', '3', '0', '1', '4'], ['2', 'Indonesia', '1', '3', '2', '6']]
|
Malaysia
|
Answer:
| 128
| 9
| 187
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many of the schools serve the roman catholic diocese of cleveland?
|
[['District', 'Location', 'Communities served'], ['Hershey Montessori Farm School', 'Huntsburg Township, Ohio', 'parent-owned, and chartered by Ohio Department of Education: application deadline January each year'], ['Notre Dame-Cathedral Latin', 'Munson Township, Ohio', 'Roman Catholic Diocese of Cleveland: open to 8th grade students who have attended a Catholic elementary school and others who have not'], ['Saint Anselm School', 'Chester Township, Ohio', 'Roman Catholic Diocese of Cleveland K - 8th grade; preschool'], ['Hawken School', 'Gates Mills, Ohio', 'College preparatory day school: online application, site visit and testing'], ['Solon/Bainbridge Montessori School of Languages', 'Bainbridge Township, Ohio', 'nonsectarian Montessori School: quarterly enrollment periods'], ['Agape Christian Academy', 'Burton Township, Ohio and Troy Township, Ohio', 'Accepts applications prior to the start of each school year'], ["Saint Mary's School", 'Chardon, Ohio', 'Roman Catholic Diocese of Cleveland preschool - 8th grade; parishioners and non-parishioners'], ["Saint Helen's School", 'Newbury, Ohio', 'Roman Catholic Diocese of Cleveland K - 8th grade; parishioners and non-parishioners']]
|
4
|
Answer:
| 128
| 8
| 288
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total medals did guyana win in the competition?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['4', 'Chile', '2', '0', '2', '4'], ['3', 'Colombia', '2', '3', '4', '9'], ['1', 'Brazil', '7', '5', '3', '15'], ['5', 'Argentina', '1', '2', '5', '8'], ['9', 'Panama', '0', '0', '1', '1'], ['6', 'Peru', '1', '1', '2', '4'], ['Total', 'Total', '16', '16', '30', '62'], ['9', 'Netherlands Antilles', '0', '0', '1', '1'], ['9', 'Uruguay', '0', '0', '1', '1'], ['9', 'Aruba', '0', '0', '1', '1'], ['2', 'Venezuela', '3', '2', '8', '13'], ['8', 'Guyana', '0', '1', '0', '1'], ['7', 'Ecuador', '0', '2', '2', '4']]
|
1
|
Answer:
| 128
| 13
| 267
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many titles were listed as having 3 acts and a prologue?
|
[['Opus', 'Title', 'Sub\xaddivisions', 'Compo-sition', 'Première date', 'Place, theatre'], ['11', 'An allem ist Hütchen Schuld!', '3 acts', '1915', '6 December 1917', 'Stuttgart, Hofopera'], ['16', 'Wahnopfer', '3 acts', '1928', '1994', 'Rudolstadt, Heidecksburg only libretto and Act 1 finished'], ['18', 'Das Flüchlein, das Jeder mitbekam', '3 acts', '1929', '29 April 1984', 'Kiel (completed by Hans Peter Mohr)'], ['9', 'Der Heidenkönig', 'prologue and 3\xa0acts', '1913', '16 December 1933', 'Cologne, Städtische Bühnen'], ['7', 'Schwarzschwanenreich', '3 acts', '1910', '5 November 1918', 'Karlsruhe, Hoftheater'], ['2', 'Herzog Wildfang', '3 acts', '1900', '23 March 1901', 'Munich, Hofopera'], ['8', 'Sonnenflammen', '3 acts', '1912', '30 October 1918', 'Darmstadt, Hoftheater'], ['5', 'Sternengebot', 'prologue and 3\xa0acts', '1906', '21 January 1908', 'Hamburg, Stadttheater'], ['6', 'Banadietrich', '3 acts', '1909', '23 January 1910', 'Karlsruhe, Hoftheater'], ['13', 'Der Schmied von Marienburg', '3 acts', '1920', '16 December 1920', 'Rostock, Städtische Bühnen'], ['15', 'Die heilige Linde', '3 acts', '1927', '2001', 'Keulen (prelude only)'], ['14', 'Rainulf und Adelasia', '3 acts', '1922', '1923', 'Rostock (prelude only)'], ['17', 'Walamund (libretto only, no music completed)', '3 acts', '1928', '', ''], ['4', 'Bruder Lustig', '3 acts', '1904', '13 October 1905', 'Hamburg, Stadttheater'], ['12a', 'Das Liebesopfer (libretto only, no music completed)', '4 acts', '1917', '', ''], ['10', 'Der Friedensengel', '3 acts', '1914', '4 March 1926', 'Karlsruhe, Badisches Landestheater'], ['3', 'Der Kobold', '3 acts', '1903', '29 January 1904', 'Hamburg, Stadttheater'], ['1', 'Der Bärenhäuter', '3 acts', '1898', '22 January 1899', 'Munich, Hofopera']]
|
2
|
Answer:
| 128
| 18
| 664
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the first cyclist to finish?
|
[['Rank', 'Cyclist', 'Team', 'Time', 'UCI ProTour\\nPoints'], ['7', 'Samuel Sánchez\xa0(ESP)', 'Euskaltel-Euskadi', 's.t.', '7'], ['10', 'David Moncoutié\xa0(FRA)', 'Cofidis', '+ 2"', '1'], ['5', 'Franco Pellizotti\xa0(ITA)', 'Liquigas', 's.t.', '15'], ['2', 'Alexandr Kolobnev\xa0(RUS)', 'Team CSC Saxo Bank', 's.t.', '30'], ['8', 'Stéphane Goubert\xa0(FRA)', 'Ag2r-La Mondiale', '+ 2"', '5'], ['6', 'Denis Menchov\xa0(RUS)', 'Rabobank', 's.t.', '11'], ['1', 'Alejandro Valverde\xa0(ESP)', "Caisse d'Epargne", '5h 29\' 10"', '40'], ['3', 'Davide Rebellin\xa0(ITA)', 'Gerolsteiner', 's.t.', '25'], ['4', 'Paolo Bettini\xa0(ITA)', 'Quick Step', 's.t.', '20'], ['9', 'Haimar Zubeldia\xa0(ESP)', 'Euskaltel-Euskadi', '+ 2"', '3']]
|
Alejandro Valverde
|
Answer:
| 128
| 10
| 310
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the first book published by harper & brothers between 1903-1923?
|
[['Year', 'Title', 'Genre', 'Publisher', 'Notes'], ['1920', 'The Man of the Forest', 'Western', 'Grosset & Dunlap', ''], ['1912', 'Riders of the Purple Sage', 'Western', 'Harper & Brothers', ''], ['1931', 'Book of Camps and Trails', 'Adventure', 'Harper & Brothers', 'Partial re-print of Tales of Lonely Trails'], ['2008', 'The Great Trek', 'Western', 'Five Star', 'Unabridged version of The Wilderness Trek (1944)'], ['1920', 'The Redheaded Outfield and other Baseball Stories', 'Baseball', 'Harper & Brothers', ''], ['1912', 'Ken Ward in the Jungle', 'Western', 'Harper & Brothers', ''], ['1928', 'Wild Horse Mesa', 'Western', 'Harper & Brothers', ''], ['1961', 'Blue Feather and other Stories', 'Western', 'Harper & Row', ''], ['1940', 'Thirty thousand on the Hoof', 'Western', 'Harper & Brothers', ''], ['1909', 'The Last Trail', 'Western', 'Outing Publishing', 'Sequel to Spirit of the Border'], ['1958', 'Arizona Clan', 'Western', 'Harper & Brothers', ''], ['1940', 'Twin Sombreros', 'Western', 'Harper & Brothers', 'Sequel to Knights of the Range'], ['1953', 'Wyoming', 'Western', 'Harper & Brothers', ''], ['1935', 'The Trail Driver', 'Western', 'Whitman Publishing', ''], ['1903', 'Betty Zane', 'Historical', 'Charles Francis Press', ''], ['1915', 'The Rainbow Trail', 'Western', 'Harper & Brothers', 'Sequel to Riders of the Purple Sage'], ['1911', 'The Young Lion Hunter', 'Western', 'Harper & Brothers', ''], ['1982', "Angler's Eldorado: Zane Grey in New Zealand", 'Fishing', 'Walter J. Black', 'Partial reprint of 1926 edition (first 10 chapters, plus additional content)'], ['1914', 'The Light of Western Stars', 'Western', 'Harper & Brothers', ''], ['1934', 'The Code of the West', 'Western', 'Harper & Brothers', ''], ['2009', 'Tales of the Gladiator', 'Fishing', 'ZG Collections', ''], ['1952', 'Adventures in Fishing', 'Fishing', 'Harper & Brothers', ''], ['1963', 'Boulder Dam', 'Historical', 'HarperCollins', ''], ['1951', 'The Dude Ranger', 'Western', 'Harper & Brothers', ''], ['1927', 'Forlorn River', 'Western', 'Harper & Brothers', ''], ['2004', 'Tonto Basin', 'Western', 'Leisure Books', 'Unabridged version of To the Last Man (1921)'], ['1909', 'The ShortStop', 'Baseball', 'A. C. McClurg', ''], ['1929', 'Fighting Caravans', 'Western', 'Harper & Brothers', ''], ['1939', 'Western Union', 'Western', 'Harper & Brothers', ''], ['1978', 'Tales from a Fisherman’s Log', 'Fishing', 'Hodder & Stoughton', ''], ['1959', 'Horse Heaven Hill', 'Western', 'Harper & Brothers', ''], ['1910', 'The Heritage of the Desert', 'Western', 'Harper & Brothers', ''], ['1954', 'Lost Pueblo', 'Western', 'Harper & Brothers', ''], ['1922', 'The Day of the Beast', 'Fiction', 'Harper & Brothers', ''], ['1935', 'Thunder Mountain', 'Western', 'Harper & Brothers', ''], ['1930', 'The Wolf Tracker', 'Western', 'Harper & Brothers', ''], ['1923', "Tappan's Burro", 'Western', 'Harper & Brothers', ''], ['1913', 'Desert Gold', 'Western', 'Harper & Brothers', ''], ['2007', 'Shower of Gold', 'Western', 'Leisure Books', 'Unabridged version of Desert Gold (1915)'], ['1928', 'Avalanche', 'Western', 'Harper & Brothers', ''], ['1916', 'The Border Legion', 'Western', 'Harper & Brothers', ''], ['1926', 'Under the Tonto Rim', 'Western', 'Harper & Brothers', ''], ['1921', 'To the Last Man', 'Western', 'Harper & Brothers', '']]
|
The Heritage of the Desert
|
Answer:
| 128
| 43
| 1,026
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which song topped the club play singles list?
|
[['Year', 'Name', 'Label', 'Hot Black Singles', 'Club Play Singles'], ['1987', '"Send It C.O.D."', 'New Image', '―', '―'], ['1984', '"Thin Line"', 'Power House', '―', '―'], ['1983', '"I Need You Now"', 'Jive', '―', '―'], ['1982', '"Thanks to You"', 'Becket', '#44', '#1'], ['1982', '"He\'s Gonna Take You Home"', 'Becket', '―', '―'], ['1986', '"Say It Again"', 'Spring', '―', '―'], ['1986', '"Say It Again"', 'Spring', '―', '―']]
|
"Thanks to You"
|
Answer:
| 128
| 7
| 157
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year did a judge or official first start officiating the olympic oath?
|
[['Olympics', 'Athlete', 'Judge (Official)', 'Coach', 'Language'], ['1984 Winter Olympics', 'Bojan Križaj', 'Dragan Perovic', '-', 'Serbo-Croatian'], ['1960 Summer Olympics', 'Adolfo Consolini', '-', '-', '-'], ['1992 Summer Olympics', 'Luis Doreste Blanco', 'Eugeni Asensio', '-', 'Spanish/Catalan'], ['1960 Winter Olympics', 'Carol Heiss', '-', '-', '-'], ['2006 Winter Olympics', 'Giorgio Rocca', 'Fabio Bianchetti', '-', 'Italian'], ['1932 Summer Olympics', 'George Calnan', '-', '-', 'English'], ['1952 Winter Olympics', 'Torbjørn Falkanger', '-', '-', '-'], ['1928 Winter Olympics', 'Hans Eidenbenz', '-', '-', '-'], ['1980 Summer Olympics', 'Nikolai Andrianov', 'Alexander Medved', '-', 'Russian'], ['1952 Summer Olympics', 'Heikki Savolainen', '-', '-', '-'], ['1964 Winter Olympics', 'Paul Aste', '-', '-', 'German'], ['1994 Winter Olympics', 'Vegard Ulvang', 'Kari Kåring', '-', 'English (Ulvang)/Norwegian (Kåring)'], ['1976 Winter Olympics', 'Werner Delle Karth', 'Willy Köstinger', '-', 'German'], ['1932 Winter Olympics', 'Jack Shea', '-', '-', '-'], ['2012 Summer Olympics', 'Sarah Stevenson', 'Mik Basi', 'Eric Farrell', 'English'], ['1984 Summer Olympics', 'Edwin Moses', 'Sharon Weber', '-', 'English'], ['1972 Winter Olympics', 'Keiichi Suzuki', 'Fumio Asaki', '-', 'Japanese'], ['2010 Winter Olympics', 'Hayley Wickenheiser', 'Michel Verrault', '-', 'English/French'], ['1998 Winter Olympics', 'Kenji Ogiwara', 'Junko Hiramatsu', '-', 'Japanese'], ['1968 Winter Olympics', 'Léo Lacroix', '-', '-', 'French'], ['1948 Winter Olympics', 'Bibi Torriani', '-', '-', '-'], ['1972 Summer Olympics', 'Heidi Schüller', 'Heinz Pollay', '-', 'German'], ['2000 Summer Olympics', 'Rechelle Hawkes', 'Peter Kerr', '-', 'English'], ['2004 Summer Olympics', 'Zoi Dimoschaki', 'Lazaros Voreadis', '-', 'Greek'], ['2014 Winter Olympics', 'Ruslan Zakharov', 'Vyacheslav Vedenin, Jr', 'Anastassia Popkova', 'Russian'], ['2008 Summer Olympics', 'Zhang Yining', 'Huang Liping', '-', 'Chinese'], ['1988 Winter Olympics', 'Pierre Harvey', 'Suzanna Morrow-Francis', '-', 'English'], ['1956 Winter Olympics', 'Giuliana Minuzzo', '-', '-', '-'], ['1968 Summer Olympics', 'Pablo Garrido', '-', '-', 'Spanish'], ['1992 Winter Olympics', 'Surya Bonaly', 'Pierre Bornat', '-', 'French'], ['2002 Winter Olympics', 'Jimmy Shea', 'Allen Church', '-', 'English'], ['1928 Summer Olympics', 'Harry Dénis', '-', '-', '-'], ['1996 Summer Olympics', 'Teresa Edwards', 'Hobie Billingsley', '-', 'English'], ['1988 Summer Olympics', 'Hur Jae\\nShon Mi-Na', 'Lee Hak-Rae', '-', 'Korean'], ['1936 Winter Olympics', 'Willy Bogner, Sr.', '-', '-', '-'], ['1936 Summer Olympics', 'Rudolf Ismayr', '-', '-', '-'], ['1924 Summer Olympics', 'Géo André', '-', '-', 'French.'], ['1956 Summer Olympics', 'John Landy (Melbourne)\\nHenri Saint Cyr (Stockholm)', '-', '-', 'English/Swedish'], ['1964 Summer Olympics', 'Takashi Ono', '-', '-', 'Japanese'], ['1924 Winter Olympics', 'Camille Mandrillon', '-', '-', '-'], ['1948 Summer Olympics', 'Donald Finlay', '-', '-', 'English'], ['1980 Winter Olympics', 'Eric Heiden', 'Terry McDermott', '-', 'English'], ['1920 Summer Olympics', 'Victor Boin', '-', '-', '-'], ['1976 Summer Olympics', 'Pierre St.-Jean', 'Maurice Fauget', '-', 'French (St.-Jean)/English (Fauget)']]
|
1972
|
Answer:
| 128
| 44
| 976
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many circuits are there total?
|
[['Round', 'Date', 'Circuit', 'Winning driver (TA2)', 'Winning vehicle (TA2)', 'Winning driver (TA1)', 'Winning vehicle (TA1)'], ['2', 'June 4', 'Westwood', 'Ludwig Heimrath', 'Porsche 935', 'Nick Engels', 'Chevrolet Corvette'], ['7', 'August 19', 'Mosport', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['8', 'September 4', 'Road America', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['9', 'October 8', 'Laguna Seca', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['5', 'July 8', 'Watkins Glen‡', 'Hal Shaw, Jr.\\n Monte Shelton', 'Porsche 935', 'Brian Fuerstenau\\n Bob Tullius', 'Jaguar XJS'], ['3', 'June 11', 'Portland', 'Tuck Thomas', 'Chevrolet Monza', 'Bob Matkowitch', 'Chevrolet Corvette'], ['1', 'May 21', 'Sears Point', 'Greg Pickett', 'Chevrolet Corvette', 'Gene Bothello', 'Chevrolet Corvette'], ['4', 'June 25', 'Mont-Tremblant', 'Monte Sheldon', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['6', 'August 13', 'Brainerd', 'Jerry Hansen', 'Chevrolet Monza', 'Bob Tullius', 'Jaguar XJS'], ['10', 'November 5', 'Mexico City', 'Ludwig Heimrath', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS']]
|
10
|
Answer:
| 128
| 10
| 426
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where did she achieve first place for the first time
|
[['Year', 'Competition', 'Venue', 'Position', 'Event', 'Notes'], ['2002', 'Asian Games', 'Busan, South Korea', '2nd', '4x400 m relay', ''], ['2011', 'Universiade', 'Shenzhen, China', '–', '400 m', 'DQ'], ['2005', 'Universiade', 'Izmir, Turkey', '6th', '4x400 m relay', ''], ['2005', 'Asian Championships', 'Incheon, South Korea', '2nd', '4x400 m relay', ''], ['2007', 'Universiade', 'Bangkok, Thailand', '1st', '400 m', ''], ['2006', 'Asian Games', 'Doha, Qatar', '2nd', '4x400 m relay', ''], ['2006', 'Asian Games', 'Doha, Qatar', '1st', '400 m', ''], ['2001', 'World Youth Championships', 'Debrecen, Hungary', '4th', '400 m', ''], ['2006', 'World Cup', 'Athens, Greece', '7th', '400 m', '']]
|
Doha, Qatar
|
Answer:
| 128
| 9
| 257
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of medals won by australia?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['5', 'Switzerland\xa0(SUI)', '0', '2', '1', '3'], ['6', 'United States\xa0(USA)', '0', '1', '0', '1'], ['7', 'Great Britain\xa0(GBR)', '0', '0', '1', '1'], ['1', 'Australia\xa0(AUS)', '2', '1', '0', '3'], ['7', 'France\xa0(FRA)', '0', '0', '1', '1'], ['2', 'Italy\xa0(ITA)', '1', '1', '1', '3'], ['4', 'Soviet Union\xa0(URS)', '1', '0', '0', '1'], ['3', 'Germany\xa0(EUA)', '1', '0', '1', '2']]
|
3
|
Answer:
| 128
| 8
| 203
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times did this racer not finish the race?
|
[['Year', 'Class', 'No', 'Tyres', 'Car', 'Team', 'Co-Drivers', 'Laps', 'Pos.', 'Class\\nPos.'], ['1994', 'GT2', '49', 'P', 'Porsche 911 Carrera RSR\\nPorsche 3.8 L Flat-6', 'Larbre Compétition', 'Jacques Alméras\\n Jean-Marie Alméras', '94', 'DNF', 'DNF'], ['1973', 'S\\n3.0', '62', '', 'Ligier JS2\\nMaserati 3.0L V6', 'Automobiles Ligier', 'Guy Ligier', '24', 'DSQ', 'DSQ'], ['1972', 'S\\n3.0', '22', '', 'Ligier JS2\\nMaserati 3.0L V6', 'Automobiles Ligier', 'Pierre Maublanc', '195', 'DNF', 'DNF'], ['1993', 'GT', '71', 'D', 'Venturi 500LM\\nRenault PRV 3.0 L Turbo V6', 'Jacadi Racing', 'Michel Maisonneuve\\n Christophe Dechavanne', '210', 'DNF', 'DNF'], ['1978', 'S\\n+2.0', '10', '', 'Mirage M9\\nRenault 2.0L Turbo V6', 'Grand Touring Cars Inc.', 'Vern Schuppan\\n Sam Posey', '293', '10th', '5th'], ['1974', 'S\\n3.0', '15', '', 'Ligier JS2\\nMaserati 3.0L V6', 'Automobiles Ligier', 'Alain Serpaggi', '310', '8th', '5th'], ['1977', 'S\\n+2.0', '8', '', 'Renault Alpine A442\\nRenault 2.0L Turbo V6', 'Renault Sport', 'Patrick Depailler', '289', 'DNF', 'DNF'], ['1990', 'C1', '6', 'G', 'Porsche 962C\\nPorsche Type-935 3.0L Turbo Flat-6', 'Joest Porsche Racing', 'Henri Pescarolo\\n Jean-Louis Ricci', '328', '14th', '14th'], ['1996', 'GT1', '38', 'M', 'McLaren F1 GTR\\nBMW S70 6.1L V12', 'Team Bigazzi SRL', 'Steve Soper\\n Marc Duez', '318', '11th', '9th']]
|
4
|
Answer:
| 128
| 9
| 604
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:did hillary clinton or john mccain win 51% of the vote in the march 31, 2008 rasmussen reports poll?
|
[['Poll Source', 'Sample Size', 'Margin of Error', 'Date', 'Democrat', '%', 'Republican', '%'], ['Survey USA', '546', '4.3', 'Nov 9-11, 2007', 'Hillary Clinton', '44', 'John McCain', '48'], ['Survey USA', '543', '4.3', 'Jan 4-6, 2008', 'Barack Obama', '58', 'Mike Huckabee', '35'], ['Survey USA', '546', '4.3', 'Nov 9-11, 2007', 'Hillary Clinton', '49', 'Mike Huckabee', '43'], ['Survey USA', '546', '4.3', 'Nov 9-11, 2007', 'Barack Obama', '50', 'John McCain', '42'], ['Survey USA', '543', '4.3', 'Jan 4-6, 2008', 'Barack Obama', '55', 'John McCain', '38'], ['Rasmussen Reports', '500', '', 'Feb 18, 2008', 'Hillary Clinton', '37', 'John McCain', '47'], ['Survey USA', '', '', 'Dec. 17, 2007', 'Hillary Clinton', '46', 'Mike Huckabee', '45'], ['Survey USA', '543', '4.3', 'Jan 4-6, 2008', 'Hillary Clinton', '48', 'Mitt Romney', '40'], ['Survey USA', '546', '4.3', 'Nov 9-11, 2007', 'Barack Obama', '53', 'Mitt Romney', '39'], ['Survey USA', '506', '4.4', 'Oct 12-14, 2007', 'Hillary Clinton', '50', 'Mitt Romney', '42'], ['Survey USA', '563', '4.2', 'Feb 15-17, 2008', 'Hillary Clinton', '41', 'John McCain', '52'], ['Survey USA', '513', '4.4', 'Oct 12-14, 2007', 'Hillary Clinton', '48', 'Rudy Giuliani', '43'], ['Survey USA', '543', '4.3', 'Jan 4-6, 2008', 'Barack Obama', '59', 'Mitt Romney', '33'], ['Survey USA', '546', '4.3', 'Nov 9-11, 2007', 'Barack Obama', '56', 'Mike Huckabee', '35'], ['Survey USA', '498', '4.5', 'Oct 12-14, 2007', 'Hillary Clinton', '52', 'Ron Paul', '36'], ['Survey USA', '543', '4.3', 'Jan 4-6, 2008', 'Hillary Clinton', '51', 'Rudy Giuliani', '35'], ['Rasmussen Reports', '500', '', 'Feb 18, 2008', 'Barack Obama', '44', 'John McCain', '41'], ['Survey USA', '502', '4.5', 'Oct 12-14, 2007', 'Hillary Clinton', '49', 'John McCain', '44'], ['Rasmussen Reports', '500', '4.5', 'Mar 31, 2008', 'Hillary Clinton', '36', 'John McCain', '51'], ['Survey USA', '506', '4.3', 'Oct 12-14, 2007', 'Hillary Clinton', '51', 'Mike Huckabee', '41'], ['Survey USA', '543', '4.3', 'Jan 4-6, 2008', 'Barack Obama', '66', 'Rudy Giuliani', '26'], ['Survey USA', '546', '4.3', 'Nov 9-11, 2007', 'Hillary Clinton', '47', 'Rudy Giuliani', '43'], ['Survey USA', '509', '4.4', 'Oct 12-14, 2007', 'Hillary Clinton', '50', 'Fred Thompson', '42'], ['Survey USA', '546', '4.3', 'Nov 9-11, 2007', 'Barack Obama', '52', 'Rudy Giuliani', '39'], ['Survey USA', '517', '4.4', 'Mar 14-16, 2008', 'Hillary Clinton', '44', 'John McCain', '48'], ['Survey USA', '563', '4.2', 'Feb 15-17, 2008', 'Barack Obama', '51', 'John McCain', '41'], ['Survey USA', '543', '4.3', 'Jan 4-6, 2008', 'Hillary Clinton', '47', 'Mike Huckabee', '45']]
|
John McCain
|
Answer:
| 128
| 27
| 1,030
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who has the most quantity of all nations?
|
[['Nation', 'Date', 'Quantity', 'Type', 'Notes'], ['Mexico', '2012', '6', '4207', 'The Mexican Navy – Armada de México – inducted the first two of what could be several Tenochtitlan-class coastal patrol boats.[citation needed] The two StanPatrol 4207 patrol boats – ARM Tenochtitlan (PC-331) and ARM Teotihuacan (PC-332) were built at a cost of $9 million USD each at ASTIMAR 1 in Tampico, Tamaulipas and completed in April and May 2012.'], ['Canada', '2009', '9', '4207', 'In 2009 the Department of Fisheries and Oceans announced it would be purchasing 9 patrol vessels for the Canadian Coast Guard. The Hero-class patrol vessels began entering service in 2011.'], ['Vietnam', '2004', '3', '4100', 'SAR-411, SAR-412 and SAR-413 employed by Vietnam Coast Guard search and rescue service.'], ['Jamaica', '2005', '3', '4207', 'The three vessels which form the County-class are HMJS Surrey, HMJS Cornwall and HMJS Middlesex. They were built in the Netherlands, and the last vessel was delivered in December 2006.'], ['Bulgaria', '2010', '1', '4207', 'The Bulgarian Border Police accepted delivery of the Obzor on July 16, 2010.'], ["Bahama's", '2013', '4', '4207', 'The Royal Bahamas Defence Forces ordered 4 vessels together with 4 x Sea Axe 3007 Patrols and 1 x Stan Lander 5612 Logistics Support and Landing Craft in April 2013.'], ['Honduras', '2013', '2', '4207', 'Honduran Navy 2 patrol vessels 4207 (FNH 1401 Lempira and FNH 1402 Morazan) and 6 Damen Interceptor 1102 in service 2013'], ['Barbados', '2007', '3', '4207', 'Built for the Barbados Coast Guard. HMBS Leonard C Banfield and HMBS Rudyard Lewis were scheduled to be delivered in 2008. HMBS Trident was scheduled for delivery in 2009.'], ['Venezuela', '2014', '6', '5009', 'The Bolivarian Armada of Venezuela ordered 6 vessels together with 6 Damen Stan Patrol 4207 in March 2014. They are being built in UCOCAR shipyard with the assistance of DAMEX Shipbuilding & Engineering, Cuba.'], ['United Kingdom', '2001', '4', '4207', 'the UKBA 42m Customs Cutters Seeker, Searcher, Vigilant and Valiant are operated by the United Kingdom Border Agency.'], ['Qatar', '2014', '6', '5009', 'The Qatar Armed Forces ordered 6 vessels together with 1 x 52 meter Diving Support Vessel on March 31st 2014. The vessels are to be build by Nakilat Damen Shipyard Qatar'], ['Netherlands', '2001', '2', '4207', "In 2001 the Netherlands ordered two vessels to serve in the Dutch customs' service. Visarend commissioned in 2001, Zeearend in 2002. now operated by the Dutch Coast Guard"], ['Venezuela', '2014', '6', '4207', 'The Bolivarian Armada of Venezuela ordered 6 vessels together with 6 Damen Ocean Patrol 5007 in March 2014. They are being built in UCOCAR shipyard with the assistance of DAMEX Shipbuilding & Engineering, Cuba.'], ['Netherlands Antilles & Aruba', '1998', '3', '4100', 'Jaguar, Panter and Poema employed by the Netherlands Antilles & Aruba Coast Guard.'], ['United States', '2012', '', '4708', 'The United States Coast Guard is proposing the purchase of 24-34 cutters as the Sentinel class.'], ['Albania', '2007', '4', '4207', 'The Iliria and three other vessels: Oriku, Lisus and Butrindi operated by the Albanian Naval Defense Forces'], ['South Africa', '2004', '3', '4708', 'Lillian Ngoyi-class environmental inshore patrol vessels: Lillian Ngoyi, Ruth First and Victoria Mxenge are employed by the Department of Agriculture, Forestry and Fisheries.']]
|
Canada
|
Answer:
| 128
| 17
| 988
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the difference in points scored between norway and sweden?
|
[['Place', 'Shooter', '5 pts', '4 pts', '3 pts', '2 pts', '1 pts', '0 pts', 'Total', 'Rank'], ['6', 'Gusztáv Szomjas', '-', '4', '4', '1', '-', '1', '30', '20'], ['6', 'Hungary\xa0(HUN)', '1', '8', '17', '4', '1', '9', '97', ''], ['5', 'Karl Magnus Wegelius', '2', '6', '2', '-', '-', '-', '40', '5'], ['3', 'John Boles', '3', '5', '2', '-', '-', '-', '41', '3'], ['4', 'Great Britain\xa0(GBR)', '8', '9', '18', '3', '-', '2', '136', ''], ['2', 'Mauritz Johansson', '2', '4', '3', '1', '-', '-', '37', '11'], ['4', 'Cyril Mackworth-Praed', '6', '-', '3', '1', '-', '-', '41', '3'], ['6', 'László Szomjas', '-', '1', '5', '1', '-', '3', '21', '25'], ['6', 'Rezső Velez', '-', '1', '5', '2', '-', '2', '23', '23'], ['1', 'Norway\xa0(NOR)', '12', '16', '12', '-', '-', '-', '160', ''], ['3', 'Dennis Fenton', '1', '2', '5', '2', '-', '-', '32', '16'], ['5', 'Jalo Autonen', '1', '1', '5', '2', '-', '1', '28', '21'], ['3', 'Walter Stokes', '1', '6', '3', '-', '-', '-', '38', '8'], ['5', 'Finland\xa0(FIN)', '7', '10', '15', '5', '-', '3', '130', ''], ['1', 'Ole Lilloe-Olsen', '4', '5', '1', '-', '-', '-', '43', '1'], ['1', 'Einar Liberg', '5', '2', '3', '-', '-', '-', '42', '2'], ['2', 'Alfred Swahn', '3', '4', '3', '-', '-', '-', '40', '5'], ['4', "John O'Leary", '1', '2', '6', '-', '-', '1', '31', '19'], ['–', 'Miloslav Hlaváč', '1', '2', '6', '1', '-', '-', '33', '15'], ['4', 'Alexander Rogers', '1', '2', '5', '2', '-', '-', '32', '16'], ['3', 'Raymond Coulter', '2', '4', '3', '1', '-', '-', '37', '11'], ['5', 'Toivo Tikkanen', '1', '1', '5', '1', '-', '2', '26', '22'], ['6', 'Elemér Takács', '1', '2', '3', '-', '1', '3', '23', '23'], ['1', 'Otto Olsen', '1', '5', '4', '-', '-', '-', '37', '11'], ['3', 'United States\xa0(USA)', '7', '17', '13', '3', '-', '-', '148', ''], ['1', 'Harald Natvig', '2', '4', '4', '-', '-', '-', '38', '8'], ['–', 'Czechoslovakia\xa0(TCH)', '1', '2', '6', '1', '-', '-', '33', ''], ['5', 'Martti Liuttula', '3', '2', '3', '2', '-', '-', '36', '14'], ['2', 'Otto Hultberg', '1', '6', '3', '-', '-', '-', '38', '8'], ['2', 'Sweden\xa0(SWE)', '8', '19', '12', '1', '-', '-', '154', ''], ['2', 'Fredric Landelius', '2', '5', '3', '-', '-', '-', '39', '7'], ['4', 'John Faunthorpe', '-', '5', '4', '-', '-', '1', '32', '16']]
|
6
|
Answer:
| 128
| 32
| 983
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many teams played in a championship game?
|
[['Conference', '# of Bids', 'Record', 'Win\xa0%', 'Round\\nof 32', 'Sweet\\nSixteen', 'Elite\\nEight', 'Final\\nFour', 'Championship\\nGame'], ['Sun Belt', '2', '6–2', '.750', '2', '1', '1', '1', '1'], ['Great Midwest', '2', '0–2', '–', '–', '–', '–', '–', '–'], ['Atlantic 10', '3', '1–3', '.250', '1', '–', '–', '–', '–'], ['Big Eight', '4', '3–4', '.429', '2', '1', '–', '–', '–'], ['Pacific-10', '5', '8–5', '.615', '4', '2', '2', '–', '–'], ['Big Ten', '5', '9–5', '.643', '4', '2', '2', '1', '–'], ['Missouri Valley', '2', '2–2', '.500', '2', '–', '–', '–', '–'], ['Big Sky', '2', '1–2', '.333', '1', '–', '–', '–', '–'], ['Big East', '2', '5–2', '.714', '2', '2', '1', '–', '–'], ['Southeastern', '6', '10–6', '.625', '5', '3', '1', '1', '–'], ['West Coast', '2', '0–2', '–', '–', '–', '–', '–', '–'], ['Mid-Continent', '2', '0–2', '–', '–', '–', '–', '–', '–'], ['Colonial', '1', '1–1', '.500', '1', '–', '–', '–', '–'], ['Western Athletic', '1', '1–1', '.500', '1', '–', '–', '–', '–'], ['Big West', '2', '0–2', '–', '–', '–', '–', '–', '–'], ['Southwest', '4', '5–4', '.556', '3', '2', '–', '–', '–'], ['Atlantic Coast', '3', '9–2', '.818', '3', '2', '1', '1', '1'], ['Metro', '2', '2–2', '.500', '1', '1', '–', '–', '–']]
|
2
|
Answer:
| 128
| 18
| 594
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:were more episodes aired in 1967 or 1968?
|
[['Eps #', 'Prod #', 'Title', 'Summary', 'Air Date'], ['17', '10', 'The Mysterious Molecule Man', 'The Fantastic Four study a radiated meteor. The Molecule Man appears and threatens the public. After the Fantastic Four tastes some of his power, he leaves to undergo his ruling the world. Reed has developed a weapon he thinks will defeat the Molecule Man. The weapon works, but the Molecule Man gets away. The Fantastic Four continue their pursuit. The plan to stop the Molecule Man is tricky. They manage to reverse the Molecule Man’s form with a fragment of the meteor.', '1/13/1968'], ['14', '15', 'Galactus', 'The Watcher has made strange events in hope of preventing the Silver Surfer from coming but the plan fails and the Surfer summons Galactus. Susan assists the unconscious Surfer and he begins to think differently. The Watcher has a plan only Johnny can undergo. Reed and Ben sabotage Galactus\' Earth draining machine and the Silver Surfer arrives to battle Galactus. This angers Galactus, but Johnny gets back with the weapon that makes Galactus see reason not to destroy the Earth. NOTE: In the episode "Galactus", Susan Richards (The Invisible Girl) has the role originated by Alicia Masters (explaining to the Silver Surfer about humanity).', '12/16/1967'], ['18', '18', 'The Terrible Tribunal', 'The Fantastic Four are taken to another planet where they are regarded as criminals against evil, charged by three old enemies. Reed is forced to recall his memories on Klaw, Molecule, Man and Blastaar’s defeat. Meanwhile the other three escape and they rescue Reed just as the verdict is given. At the surface, they have to battle the court judge before they are able to leave the planet for Earth.', '9/14/1968'], ['9', '8', 'Behold A Distant Star', "The Fantastic Four are testing their rocket when they are drawn into the Skrull Galaxy. After beating the first round of Skrulls, the Fantastic Four weaken and are taken prisoner. The cruel Skrull Warlord Morrat wishes to overthrow the Skrull Emperor. The Warlord gives the Fantastic Four the option to assist them or die. Reed tricks the Warlord into getting him and his friends' powers fully charged. They defeat the Warlord as the Emperor arrives and he allows the Fantastic 4 to go freely back to Earth.", '11/4/1967'], ['15', '16', 'The Micro World Of Dr. Doom', 'The Fantastic Four have been shrunken to small size. Dr. Doom is after them and takes them to the Micro World. Dr. Doom briefs them on his micro genius experiments involving a king and a princess from the micro world. The four battle the giant guards but Dr. Doom catches them and imprisons them with the King and Princess. They all escape and enlarge themselves. Ben puts a stop to the Lizard Men, then the four return to their own world.', '12/30/1967'], ['11', '11', 'Danger In The Depths', 'Johnny finds a mysterious lady named Lady Dorma and takes her back to the Headquarters. She claims to have come from a land beneath the sea called Pacifica, which is under siege by Attuma. They manage to slip past Attuma’s forces. Pacifica is losing hope and Attuma has shadowed the seabed. Triton can only fight man-to-man with Attuma while his men prepare traps to weaken Triton into a losing battle. The Fantastic 4 thwart every trap. Triton beats Attuma and the forces retreat. NOTE: Due to the rights to the Sub-Mariner being held by Grantray-Lawrence Animation, the adaptation of the first meeting between the FF and Namor was altered. Instead, Prince Triton, an original pastiche of Namor was reworked into the Namor role.', '11/18/1967'], ['8', '6', 'Three Predictions Of Dr. Doom', 'Dr. Doom challenges the Fantastic Four. Doctor Doom begins his plans by capturing Susan. Soon the Fantastic Four manage to locate and penetrate Dr. Doom’s flying fortress, but Ben is turned back to his former self and the other three are trapped. Ben turns himself back into the Thing, releases the others and aborts Dr. Doom’s tidal waves. They chase Dr. Doom out and back to the flying fortress. After a struggle through the dangerous complex of the fortress, they abort Dr. Doom’s global destruction for good.', '10/28/1967']]
|
1967
|
Answer:
| 128
| 7
| 967
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the position of the player above kari kanervo?
|
[['Pick #', 'Player', 'Position', 'Nationality', 'NHL team', 'College/junior/club team'], ['164', 'Gates Orlando', 'Centre', 'Canada', 'Buffalo Sabres', 'Providence College (ECAC)'], ['157', 'Petri Skriko', 'Right Wing', 'Finland', 'Vancouver Canucks', 'Saipa (Finland)'], ['148', 'Dan McFall', 'Defence', 'United States', 'Winnipeg Jets', 'Buffalo Jr. Sabres (NAJHL)'], ['149', 'Rick Zombo', 'Defence', 'United States', 'Detroit Red Wings', 'Austin Mavericks (USHL)'], ['152', 'Gaetan Duchesne', 'Left Wing', 'Canada', 'Washington Capitals', 'Quebec Remparts (QMJHL)'], ['158', 'Andre Cote', 'Right Wing', 'Canada', 'Quebec Nordiques', 'Quebec Remparts (QMJHL)'], ['165', 'Dan Brennan', 'Left Wing', 'Canada', 'Los Angeles Kings', 'University of North Dakota (WCHA)'], ['154', 'Mitch Lamoureux', 'Centre', 'Canada', 'Pittsburgh Penguins', 'Oshawa Generals (OMJHL)'], ['150', 'Tony Arima', 'Left Wing', 'Finland', 'Colorado Rockies', 'Jokerit (Finland)'], ['166', 'Paul Gess', 'Left Wing', 'United States', 'Montreal Canadiens', 'Bloomington Jefferson High School (USHS-MN)'], ['163', 'Steve Taylor', 'Left Wing', 'United States', 'Philadelphia Flyers', 'Providence College (ECAC)'], ['153', 'Richard Turmel', 'Defence', 'Canada', 'Toronto Maple Leafs', 'Shawinigan Cataractes (QMJHL)'], ['159', 'Johan Mellstrom', 'Left Wing', 'Sweden', 'Chicago Black Hawks', 'Falun (Sweden)'], ['151', 'Denis Dore', 'Right Wing', 'Canada', 'Hartford Whalers', 'Chicoutimi Saguenéens (QMJHL)'], ['167', 'Alain Vigneault', 'Defence', 'Canada', 'St. Louis Blues', 'Trois-Rivières Draveurs (QMJHL)'], ['161', 'Armel Parisee', 'Defence', 'Canada', 'Boston Bruins', 'Chicoutimi Saguenéens (QMJHL)'], ['160', 'Kari Kanervo', 'Centre', 'Finland', 'Minnesota North Stars', 'TPS (Finland)'], ['156', 'Ari Lahteenmaki', 'Right Wing', 'Finland', 'New York Rangers', 'HIFK (Finland)'], ['162', 'Dale DeGray', 'Defence', 'Canada', 'Calgary Flames', 'Oshawa Generals (OMJHL)'], ['168', 'Bill Dowd', 'Defence', 'Canada', 'New York Islanders', "Ottawa 67's (OMJHL)"], ['155', 'Mike Sturgeon', 'Defence', 'Canada', 'Edmonton Oilers', 'Kelowna Buckaroos (BCJHL)']]
|
Left Wing
|
Answer:
| 128
| 21
| 710
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:previous to november 15, 2007 how often was the overall rank in the 30s?
|
[['#', 'Episode', 'Air date', 'Rating', 'Share', '18-49 (Rating/Share)', 'Viewers (m)', 'Rank (night)', 'Rank (timeslot)', 'Rank (overall)'], ['11', '"Father\'s Day"', 'April 29, 2008', '5.8', '9', '1.9/5', '8.14', '#7', '#2', '#42'], ['1', '"Welcome to the Club"', 'October 12, 2007', '7.3', '13', '2.5/8', '10.82', '#1', '#1', '#26'], ['6', '"Play Through the Pain"', 'November 15, 2007', '6.1', '10', '3.3/9', '8.93', '#8', '#3', '#45'], ['10', '"FBI Guy"', 'January 4, 2008', '5.2', '9', '1.8/5', '7.68', '#2', '#1', '#36'], ['9', '"To Drag & To Hold"', 'December 7, 2007', '5.8', '10', '1.8/5', '8.58', '#2', '#1', '#32'], ['3', '"Blind Dates and Bleeding Hearts"', 'October 26, 2007', '6.1', '11', '1.9/6', '8.90', '#1', '#1', '#41'], ['12', '"And the Truth Will (Sometimes) Set You Free"', 'May 6, 2008', '6.1', '10', '2.2/6', '8.68', '#8', '#2', ''], ['13', '"Never Tell"', 'May 13, 2008', '5.8', '10', '2.1/6', '8.46', '', '#2', ''], ['5', '"Maybe, Baby"', 'November 9, 2007', '6.5', '11', '2.0/6', '9.70', '#1', '#1', '#36'], ['8', '"No Opportunity Necessary"', 'November 23, 2007', '5.3', '9', '1.6/5', '7.76', '#3', '#1', '#45'], ['2', '"Train In Vain"', 'October 19, 2007', '6.5', '12', '2.0/6', '9.69', '#2', '#1', '#37'], ['7', '"The Past Comes Back to Haunt You"', 'November 16, 2007', '6.2', '11', '1.7/5', '8.94', '#4', '#1', '#41'], ['4', '"Grannies, Guns, Love Mints"', 'November 2, 2007', '6.4', '11', '1.9/6', '9.47', '#1', '#1', '#35']]
|
3
|
Answer:
| 128
| 13
| 668
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what element is after radium?
|
[['Atomic\\nno.', 'Name', 'Symbol', 'Group', 'Period', 'Block', 'State at\\nSTP', 'Occurrence', 'Description'], ['51', 'Antimony', 'Sb', '15', '5', 'p', 'Solid', 'Primordial', 'Metalloid'], ['46', 'Palladium', 'Pd', '10', '5', 'd', 'Solid', 'Primordial', 'Transition metal'], ['85', 'Astatine', 'At', '17', '6', 'p', 'Solid', 'Transient', 'Halogen'], ['39', 'Yttrium', 'Y', '3', '5', 'd', 'Solid', 'Primordial', 'Transition metal'], ['53', 'Iodine', 'I', '17', '5', 'p', 'Solid', 'Primordial', 'Halogen'], ['28', 'Nickel', 'Ni', '10', '4', 'd', 'Solid', 'Primordial', 'Transition metal'], ['61', 'Promethium', 'Pm', '3', '6', 'f', 'Solid', 'Transient', 'Lanthanide'], ['59', 'Praseodymium', 'Pr', '3', '6', 'f', 'Solid', 'Primordial', 'Lanthanide'], ['75', 'Rhenium', 'Re', '7', '6', 'd', 'Solid', 'Primordial', 'Transition metal'], ['79', 'Gold', 'Au', '11', '6', 'd', 'Solid', 'Primordial', 'Transition metal'], ['97', 'Berkelium', 'Bk', '3', '7', 'f', 'Solid', 'Transient', 'Actinide'], ['101', 'Mendelevium', 'Md', '3', '7', 'f', 'Solid', 'Synthetic', 'Actinide'], ['113', '(Ununtrium)', 'Uut', '13', '7', 'p', '', 'Synthetic', ''], ['56', 'Barium', 'Ba', '2', '6', 's', 'Solid', 'Primordial', 'Alkaline earth metal'], ['115', '(Ununpentium)', 'Uup', '15', '7', 'p', '', 'Synthetic', ''], ['76', 'Osmium', 'Os', '8', '6', 'd', 'Solid', 'Primordial', 'Transition metal'], ['102', 'Nobelium', 'No', '3', '7', 'f', 'Solid', 'Synthetic', 'Actinide'], ['35', 'Bromine', 'Br', '17', '4', 'p', 'Liquid', 'Primordial', 'Halogen'], ['16', 'Sulfur', 'S', '16', '3', 'p', 'Solid', 'Primordial', 'Non-metal'], ['111', 'Roentgenium', 'Rg', '11', '7', 'd', '', 'Synthetic', ''], ['98', 'Californium', 'Cf', '3', '7', 'f', 'Solid', 'Transient', 'Actinide'], ['83', 'Bismuth', 'Bi', '15', '6', 'p', 'Solid', 'Primordial', 'Metal'], ['41', 'Niobium', 'Nb', '5', '5', 'd', 'Solid', 'Primordial', 'Transition metal'], ['33', 'Arsenic', 'As', '15', '4', 'p', 'Solid', 'Primordial', 'Metalloid'], ['8', 'Oxygen', 'O', '16', '2', 'p', 'Gas', 'Primordial', 'Non-metal'], ['15', 'Phosphorus', 'P', '15', '3', 'p', 'Solid', 'Primordial', 'Non-metal'], ['1', 'Hydrogen', 'H', '1', '1', 's', 'Gas', 'Primordial', 'Non-metal'], ['49', 'Indium', 'In', '13', '5', 'p', 'Solid', 'Primordial', 'Metal'], ['84', 'Polonium', 'Po', '16', '6', 'p', 'Solid', 'Transient', 'Metal'], ['88', 'Radium', 'Ra', '2', '7', 's', 'Solid', 'Transient', 'Alkaline earth metal'], ['103', 'Lawrencium', 'Lr', '3', '7', 'd', 'Solid', 'Synthetic', 'Actinide'], ['99', 'Einsteinium', 'Es', '3', '7', 'f', 'Solid', 'Synthetic', 'Actinide'], ['7', 'Nitrogen', 'N', '15', '2', 'p', 'Gas', 'Primordial', 'Non-metal']]
|
Actinium
|
Answer:
| 128
| 33
| 1,059
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of games played at stadium of light?
|
[['Date', 'Opponent', 'Venue', 'Result', 'Attendance', 'Scorers'], ['22 April 2006', 'Portsmouth', 'Fratton Park', '1–2', '20,078', 'Miller'], ['4 May 2006', 'Fulham', 'Stadium of Light', '2–1', '28,226', 'Le Tallec, Brown'], ['1 April 2006', 'Everton', 'Goodison Park', '2–2', '38,093', 'Stead, Delap'], ['26 November 2005', 'Birmingham City', 'Stadium of Light', '0–1', '32,442', ''], ['10 December 2005', 'Charlton Athletic', 'The Valley', '0–2', '26,065', ''], ['10 September 2005', 'Chelsea', 'Stamford Bridge', '0–2', '41,969', ''], ['3 December 2005', 'Tottenham Hotspur', 'White Hart Lane', '2–3', '36,244', 'Whitehead, Le Tallec'], ['15 January 2006', 'Chelsea', 'Stadium of Light', '1–2', '32,420', 'Lawrence'], ['23 October 2005', 'Newcastle United', "St James' Park", '2–3', '52,302', 'Lawrence, Elliott'], ['30 November 2005', 'Liverpool', 'Stadium of Light', '0–2', '32,697', ''], ['31 December 2005', 'Everton', 'Stadium of Light', '0–1', '30,567', ''], ['3 March 2006', 'Manchester City', 'City of Manchester Stadium', '1–2', '42,200', 'Kyle'], ['20 August 2005', 'Liverpool', 'Anfield', '0–1', '44,913', ''], ['17 September 2005', 'West Bromwich Albion', 'Stadium of Light', '1–1', '31,657', 'Breen'], ['25 September 2005', 'Middlesbrough', 'Riverside Stadium', '2–0', '29,583', 'Miller, Arca'], ['15 October 2005', 'Manchester United', 'Stadium of Light', '1–3', '39,085', 'Elliott'], ['1 May 2006', 'Arsenal', 'Stadium of Light', '0–3', '44,003', ''], ['5 November 2005', 'Arsenal', 'Highbury', '1–3', '38,210', 'Stubbs'], ['23 August 2005', 'Manchester City', 'Stadium of Light', '1–2', '33,357', 'Le Tallec'], ['27 August 2005', 'Wigan Athletic', 'JJB Stadium', '0–1', '17,223', ''], ['18 March 2006', 'Bolton Wanderers', 'Reebok Stadium', '0–2', '23,568', ''], ['29 October 2005', 'Portsmouth', 'Stadium of Light', '1–4', '34,926', 'Whitehead (pen)'], ['4 February 2006', 'West Ham United', 'Boleyn Ground', '0–2', '34,745', ''], ['2 January 2006', 'Fulham', 'Craven Cottage', '1–2', '19,372', 'Lawrence'], ['25 March 2006', 'Blackburn Rovers', 'Stadium of Light', '0–1', '29,593', ''], ['13 August 2005', 'Charlton Athletic', 'Stadium of Light', '1–3', '34,446', 'Gray'], ['7 May 2006', 'Aston Villa', 'Villa Park', '1–2', '33,820', 'D. Collins'], ['25 February 2006', 'Birmingham City', "St. Andrew's", '0–1', '29,257', ''], ['26 December 2005', 'Bolton Wanderers', 'Stadium of Light', '0–0', '32,232', ''], ['17 April 2006', 'Newcastle United', 'Stadium of Light', '1–4', '40,032', 'Hoyte'], ['12 February 2006', 'Tottenham Hotspur', 'Stadium of Light', '1–1', '34,700', 'Murphy'], ['1 October 2005', 'West Ham United', 'Stadium of Light', '1–1', '31,212', 'Miller']]
|
19
|
Answer:
| 128
| 32
| 1,026
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year had the highest results?
|
[['Year', 'Date', 'Winner', 'Result', 'Loser', 'Location'], ['2005', 'December 11', 'New York Giants', '26-23 (OT)', 'Philadelphia Eagles', 'Lincoln Financial Field'], ['2004', 'September 12', 'Philadelphia Eagles', '31-17', 'New York Giants', 'Lincoln Financial Field'], ['2009', 'November 1', 'Philadelphia Eagles', '40-17', 'New York Giants', 'Lincoln Financial Field'], ['2005', 'November 20', 'New York Giants', '27-17', 'Philadelphia Eagles', 'Giants Stadium'], ['2008', 'November 9', 'New York Giants', '36-31', 'Philadelphia Eagles', 'Lincoln Financial Field'], ['2000', 'October 29', 'New York Giants', '24-7', 'Philadelphia Eagles', 'Giants Stadium'], ['2007', 'January 7', 'Philadelphia Eagles', '23-20', 'New York Giants', 'Lincoln Financial Field'], ['2007', 'September 30', 'New York Giants', '16-3', 'Philadelphia Eagles', 'Giants Stadium'], ['2001', 'December 30', 'Philadelphia Eagles', '24-21', 'New York Giants', 'Veterans Stadium'], ['2002', 'October 28', 'Philadelphia Eagles', '17-3', 'New York Giants', 'Veterans Stadium'], ['2000', 'September 10', 'New York Giants', '33-18', 'Philadelphia Eagles', 'Veterans Stadium'], ['2008', 'December 7', 'Philadelphia Eagles', '20-14', 'New York Giants', 'Giants Stadium'], ['2003', 'November 16', 'Philadelphia Eagles', '28-10', 'New York Giants', 'Lincoln Financial Field'], ['2004', 'November 28', 'Philadelphia Eagles', '27-6', 'New York Giants', 'Giants Stadium'], ['2009', 'January 11', 'Philadelphia Eagles', '23-11', 'New York Giants', 'Giants Stadium'], ['2006', 'September 17', 'New York Giants', '30-24 (OT)', 'Philadelphia Eagles', 'Lincoln Financial Field'], ['2001', 'October 22', 'Philadelphia Eagles', '10-9', 'New York Giants', 'Giants Stadium'], ['2003', 'October 19', 'Philadelphia Eagles', '14-10', 'New York Giants', 'Giants Stadium'], ['2007', 'December 9', 'New York Giants', '16-13', 'Philadelphia Eagles', 'Lincoln Financial Field'], ['2009', 'December 13', 'Philadelphia Eagles', '45-38', 'New York Giants', 'Giants Stadium'], ['2006', 'December 17', 'Philadelphia Eagles', '36-22', 'New York Giants', 'Giants Stadium'], ['2002', 'December 28', 'New York Giants', '10-7', 'Philadelphia Eagles', 'Giants Stadium'], ['2001', 'January 7', 'New York Giants', '20-10', 'Philadelphia Eagles', 'Giants Stadium']]
|
2009
|
Answer:
| 128
| 23
| 675
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total attendance of the first 10 games this season?
|
[['Match Day', 'Date', 'Opponent', 'H/A', 'Score', 'Aberdeen Scorer(s)', 'Attendance'], ['27', '30 January', 'Dumbarton', 'A', '2–3', 'Cail, Walker', '3,000'], ['38', '17 April', 'Hamilton Academical', 'H', '1–0', 'J. Wyllie', '4,000'], ['2', '22 August', 'Rangers', 'H', '0–2', '', '15,000'], ['35', '27 March', 'Rangers', 'A', '1–1', 'W. Wylie', '10,000'], ['25', '16 January', 'Clyde', 'A', '0–3', '', '3,000'], ['11', '17 October', 'Third Lanark', 'H', '1–2', 'Archibald', '6,000'], ['29', '13 February', 'St. Mirren', 'A', '2–0', 'Cail, Walker', '3,000'], ['21', '26 December', 'Motherwell', 'A', '1–1', 'Walker', '3,000'], ['30', '20 February', 'Hibernian', 'H', '0–0', '', '8,500'], ['22', '1 January', 'Dundee', 'H', '2–1', 'Walker, J. Wyllie', '7,000'], ['5', '12 September', 'Ayr United', 'A', '0–1', '', '2,000'], ['28', '6 February', 'Morton', 'H', '2–0', 'Brewster, Archibald', '2,000'], ['19', '12 December', 'Partick Thistle', 'A', '0–3', '', '6,000'], ['3', '29 August', 'Morton', 'A', '1–1', 'Cail', '4,500'], ['37', '10 April', 'Celtic', 'A', '0–1', '', '10,000'], ['15', '14 November', 'Hamilton Academical', 'A', '0–3', '', '4,000'], ['14', '7 November', 'Raith Rovers', 'H', '1–3', 'Main', '6,000'], ['4', '5 September', 'Clyde', 'H', '2–0', 'MacLachlan, Archibald', '6,000'], ['31', '27 February', 'Third Lanark', 'A', '1–0', 'Walker', '5,000'], ['33', '13 March', "Queen's Park", 'A', '1–3', 'Cail', '6,000'], ['34', '20 March', 'Airdrieonians', 'H', '3–0', 'Brewster, Cail, Main', '5,500'], ['7', '26 September', 'Heart of Midlothian', 'A', '0–2', '', '14,000'], ['8', '28 September', "Queen's Park", 'H', '1–1', 'Main', '5,000'], ['17', '28 November', 'Kilmarnock', 'A', '2–5', 'MacLachlan, McLeod', '2,500'], ['36', '3 April', 'Heart of Midlothian', 'H', '0–0', '', '6,000'], ['23', '2 January', 'Raith Rovers', 'A', '1–5', 'Cail', '6,000'], ['18', '5 December', 'Celtic', 'H', '0–1', '', '7,000'], ['32', '6 March', 'Partick Thistle', 'H', '0–0', '', '6,000'], ['26', '23 January', 'Falkirk', 'H', '1–2', 'Walker', '4,000'], ['6', '19 September', 'Motherwell', 'H', '3–1', 'J. Wyllie, MacLachlan, Walker', '7,000'], ['20', '19 December', 'Kilmarnock', 'H', '3–0', 'MacLachlan, Cail, Main', '4,000'], ['1', '15 August', 'Dundee', 'A', '3–1', 'Soye, Walker, Cail', '10,000'], ['10', '10 October', 'Airdrieonians', 'A', '0–3', '', '7,000'], ['24', '9 January', 'Ayr United', 'H', '1–1', 'Cail', '4,500']]
|
76,000
|
Answer:
| 128
| 34
| 1,043
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the only goalscorer to score between 18 and 20 goals?
|
[['#', 'Player', 'Goals', 'Caps', 'Career'], ['9T', 'DaMarcus Beasley', '17', '114', '2001–present'], ['6T', 'Bruce Murray', '21', '86', '1985–1993'], ['5', 'Joe-Max Moore', '24', '100', '1992–2002'], ['4', 'Brian McBride', '30', '95', '1993–2006'], ['6T', 'Jozy Altidore', '21', '67', '2007–present'], ['3', 'Eric Wynalda', '34', '106', '1990–2000'], ['2', 'Clint Dempsey', '36', '103', '2004–present'], ['9T', 'Earnie Stewart', '17', '101', '1990–2004'], ['1', 'Landon Donovan', '57', '155', '2000–present'], ['8', 'Eddie Johnson', '19', '62', '2004–present']]
|
Eddie Johnson
|
Answer:
| 128
| 10
| 229
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which nationality has the most forward position players?
|
[['Player', 'No.', 'Nationality', 'Position', 'Years for Jazz', 'School/Club Team'], ['Greg Foster', '44', 'United States', 'Center/Forward', '1995-99', 'UTEP'], ['Derek Fisher', '2', 'United States', 'Guard', '2006-2007', 'Arkansas-Little Rock'], ['Derrick Favors', '15', 'United States', 'Forward', '2011-present', 'Georgia Tech'], ['Jim Farmer', '30', 'United States', 'Guard', '1988-89', 'Alabama'], ['Kyrylo Fesenko', '44', 'Ukraine', 'Center', '2007-11', 'Cherkasy Monkeys (Ukraine)'], ['Bernie Fryer', '25', 'United States', 'Guard', '1975-76', 'BYU'], ['Terry Furlow', '25', 'United States', 'Guard/Forward', '1979-80', 'Michigan State'], ['Todd Fuller', '52', 'United States', 'Center', '1998-99', 'North Carolina State']]
|
United States
|
Answer:
| 128
| 8
| 242
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where did the only 100 m hurdle take place in 1997?
|
[['Year', 'Competition', 'Venue', 'Position', 'Event'], ['1997', 'USA Outdoor Championships', 'Indianapolis, United States', '1st', '100 m hurdles'], ['1998', 'Grand Prix Final', 'Moscow, Russia', '2nd', '100 m hurdles'], ['1997', 'World Indoor Championships', 'Paris, France', '5th', '60 m hurdles'], ['2000', 'Grand Prix Final', 'Doha, Qatar', '4th', '100 m hurdles'], ['2000', 'Olympic Games', 'Sydney, Australia', '3rd', '100 m hurdles'], ['1999', 'World Indoor Championships', 'Maebashi, Japan', '6th', '60 m hurdles'], ['2002', 'Grand Prix Final', 'Paris, France', '7th', '100 m hurdles'], ['2002', 'USA Indoor Championships', '', '1st', '60 m hurdles'], ['2003', 'World Indoor Championships', 'Birmingham, England', '3rd', '60 m hurdles'], ['1998', 'USA Indoor Championships', '', '1st', '60 m hurdles'], ['2003', 'World Athletics Final', 'Monaco', '6th', '100 m hurdles'], ['2004', 'Olympic Games', 'Athens, Greece', '3rd', '100 m hurdles']]
|
Indianapolis, United States
|
Answer:
| 128
| 12
| 294
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many episodes aired before december 1st, 1965?
|
[['No. in\\nseries', 'No. in\\nseason', 'Title', 'Directed by', 'Written by', 'Original air date', 'Prod.\\ncode'], ['27', '26', '"There was a Little Girl"', 'John Rich', 'Teleplay by: Stephen Kandell Story by: Robert Bloch', 'April\xa06,\xa01966', '126'], ['12', '11', '"Weight of the World"', 'Paul Wendkos', 'Robert Lewin', 'December\xa01,\xa01965', '111'], ['14', '12', '"Three Hours on a Sunday"', 'Paul Wendkos', 'Morton Fine & David Friedkin', 'December\xa08,\xa01965', '112'], ['24', '28', '"One Thousand Fine"', 'Paul Wendkos', 'Eric Bercovici', 'April\xa027,\xa01966', '128'], ['25', '24', '"Crusade to Limbo"', 'Richard Sarafian', 'Teleplay by: Morton Fine & David Freidkin & Jack Turley Story by: Jack Turley', 'March\xa023,\xa01966', '124'], ['13', '13', '"Tigers of Heaven"', 'Allen Reisner', 'Morton Fine & David Friedkin', 'December\xa015,\xa01965', '113'], ['22', '22', '"The Conquest of Maude Murdock"', 'Paul Wendkos', 'Robert C. Dennis & Earl Barrett', 'March\xa02,\xa01966', '122'], ['28', '27', '"It\'s All Done with Mirrors"', 'Robert Butler', 'Stephen Kandell', 'April\xa013,\xa01966', '127'], ['19', '19', '"Turkish Delight"', 'Paul Wendkos', 'Eric Bercovici', 'February\xa09,\xa01966', '119'], ['16', '15', '"The Tiger"', 'Paul Wendkos', 'Robert Culp', 'January\xa05,\xa01966', '115'], ['6', '4', '"Chrysanthemum"', 'David Friedkin', 'Edward J. Lakso', 'October\xa06,\xa01965', '104'], ['2', '3', '"Carry Me Back to Old Tsing-Tao"', 'Mark Rydell', 'David Karp', 'September\xa029,\xa01965', '103'], ['3', '1', '"So Long, Patrick Henry"', 'Leo Penn', 'Robert Culp', 'September\xa015,\xa01965', '101'], ['23', '23', '"A Day Called 4 Jaguar"', 'Richard Sarafian', 'Michael Zagar', 'March\xa09,\xa01966', '123'], ['5', '2', '"A Cup of Kindness"', 'Leo Penn', 'Morton Fine & David Friedkin', 'September\xa022,\xa01965', '102'], ['11', '10', '"Tatia"', 'David Friedkin', 'Robert Lewin', 'November\xa017,\xa01965', '110'], ['17', '16', '"The Barter"', 'Allen Reisner', 'Harvey Bullock & P.S. Allen', 'January\xa012,\xa01966', '116'], ['26', '25', '"My Mother, The Spy"', 'Richard Benedict', 'Howard Gast', 'March\xa030,\xa01966', '125'], ['8', '6', '"The Loser"', 'Mark Rydell', 'Robert Culp', 'October\xa020,\xa01965', '106'], ['20', '20', '"Bet Me a Dollar"', 'Richard Sarafian', 'David Friedkin & Morton Fine', 'February\xa016,\xa01966', '120'], ['4', '7', '"Danny was a Million Laughs"', 'Mark Rydell', 'Arthur Dales', 'October\xa027,\xa01965', '107'], ['21', '21', '"Return to Glory"', 'Robert Sarafian', 'David Friedkin & Morton Fine', 'February\xa023,\xa01966', '121'], ['9', '9', '"No Exchange on Damaged Merchandise"', 'Leo Penn', 'Gary Marshall & Jerry Belson', 'November\xa010,\xa01965', '109'], ['1', '14', '"Affair in T\'Sien Cha"', 'Sheldon Leonard', 'Morton Fine & David Friedkin', 'December\xa029,\xa01965', '114'], ['18', '18', '"Court of the Lion"', 'Robert Culp', 'Robert Culp', 'February\xa02,\xa01966', '118'], ['10', '8', '"The Time of the Knife"', 'Paul Wendkos', 'Gilbert Ralston', 'November\xa03,\xa01965', '108'], ['7', '5', '"Dragon\'s Teeth"', 'Leo Penn', 'Gilbert Ralston', 'October\xa013,\xa01965', '105']]
|
10
|
Answer:
| 128
| 27
| 1,060
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of goals scored in the game between haiti and south korea on september 6, 2013?
|
[['Date', 'Location', 'Opponent', 'Result', 'Competition'], ['September 6, 2013', 'Incheon, South Korea', 'South Korea', '1-4', 'F'], ['February 6, 2013', 'Santa Cruz de la Sierra, Bolivia', 'Bolivia', '1–2', 'F'], ['March 5, 2014', 'Mitrovica, Kosovo', 'Kosovo', '0–0', 'F'], ['July 8, 2013', 'Harrison, United States', 'Honduras', '0–2', 'GC'], ['July 12, 2013', 'Miami Gardens, United States', 'Trinidad and Tobago', '2-0', 'GC'], ['March 24, 2013', 'Santo Domingo, Dominican Republic', 'Dominican Republic', '1–3', 'F'], ['June 11, 2013', 'Rio de Janeiro, Brazil', 'Italy', '2–2', 'F'], ['January 19, 2013', 'Concepción, Chile', 'Chile', '0–3', 'F'], ['July 15, 2013', 'Houston, United States', 'El Salvador', '0-1', 'GC'], ['June 8, 2013', 'Miami, United States', 'Spain', '1–2', 'F'], ['March 20, 2013', 'Muscat, Oman', 'Oman', '0–3', 'F']]
|
5
|
Answer:
| 128
| 11
| 331
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times did brent christensen make it to europe?
|
[['Season', 'League\\nPos.', 'League\\nCompetition', 'League\\nTop scorer', 'Danish Cup', 'Europe', 'Others'], ['1984-85', '1', '1985 1st Division', 'Claus Nielsen (17)', '3rd round', '', ''], ['1989-90', '1', '1990 1st Division', 'Bent Christensen (17)', 'Quarter-final', 'EC1 1st round', ''], ['2001-02', '1', '2001-02 Superliga', 'Peter Madsen (22)', '5th round', 'EC3 3rd round', ''], ['2009-10', '3', '2009-10 Superliga', 'Morten Rasmussen (12)', '4th round', 'EC3 qual play-off round', ''], ['1986-87', '1', '1987 1st Division', 'Claus Nielsen (20)', '4th round', 'EC1 quarter-final', ''], ['2003-04', '2', '2003-04 Superliga', 'Thomas Kahlenberg (11)', 'Semi-final', 'EC3 3rd round', ''], ['2011-12', '9', '2011-12 Superliga', 'Simon Makienok Christoffersen (10)', '', '', ''], ['1983-84', '4', '1984 1st Division', 'Jens Kolding (11)', '3rd round', '', ''], ['2010-11', '3', '2010-11 Superliga', 'Michael Krohn-Dehli (11)', '', '', ''], ['1998-99', '2', '1998-99 Superliga', 'Ebbe Sand (19)', 'Semi-final', 'EC1 group stage', ''], ['1996-97', '1', '1996-97 Superliga', 'Peter Møller (22)', 'Semi-final', 'EC1 qualification round\\nEC3 quarter-final', 'Danish Supercup winner'], ['1982-83', '4', '1983 1st Division', 'Brian Chrøis (12)', '4th round', '', ''], ['2002-03', '2', '2002-03 Superliga', 'Mattias Jonson (11)', 'Winner', 'EC1 qual 3rd round\\nEC3 1st round', 'Danish Supercup winner'], ['1997-98', '1', '1997-98 Superliga', 'Ebbe Sand (28)', 'Winner', 'EC1 qual 2nd round\\nEC3 1st round', 'Danish Supercup winner'], ['1992-93', '3', '1992-93 Superliga', 'Kim Vilfort (10)', '5th round', '', ''], ['2000-01', '2', '2000-01 Superliga', 'Peter Graulund (21)', 'Quarter-final', 'EC1 qual 3rd round\\nEC3 1st round', ''], ['2006-07', '6', '2006-07 Superliga', 'Morten Rasmussen (15)', '4th round', 'EC3 1st round', 'Royal League winner\\nDanish League Cup winner'], ['1995-96', '1', '1995-96 Superliga', 'Peter Møller (15)', 'Finalist', 'EC3 3rd round', ''], ['1994-95', '2', '1994-95 Superliga', 'Mark Strudal (12)', 'Quarter-final', 'EC2 2nd round', 'Danish Supercup winner'], ['1990-91', '1', '1991 Superliga', 'Bent Christensen (11)', 'Semi-final', 'EC3 semi-final', ''], ['2004-05', '1', '2004-05 Superliga', 'Thomas Kahlenberg (13)', 'Winner', 'EC3 qual 2nd round', 'Royal League group stage'], ['1987-88', '1', '1988 1st Division', 'Bent Christensen (21)', 'Finalist', 'EC3 2nd round', ''], ['1988-89', '2', '1989 1st Division', 'Bent Christensen (10)', 'Winner', 'EC1 1st round', ''], ['1999-00', '2', '1999-00 Superliga', 'Bent Christensen (13)', 'Semi-final', 'EC1 qual 3rd round\\nEC3 1st round', ''], ['1991-92', '7', '1991-92 Superliga', 'Kim Vilfort (9)', '4th round', 'EC1 2nd round', '']]
|
5
|
Answer:
| 128
| 25
| 1,046
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the last film that lars von trier made?
|
[['Year', 'Film', 'Rotten Tomatoes', 'Metacritic', 'IMDb'], ['2000', 'Dancer in the Dark', '68%', '61%', '8.0/10'], ['2003', 'The Five Obstructions', '88%', '79%', '7.5/10'], ['1998', 'The Idiots', '70%', '47%', '6.9/10'], ['1982', 'Images of Liberation', 'N/A', 'N/A', '5.1/10'], ['2003', 'Dogville', '70%', '59%', '8.0/10'], ['2006', 'The Boss of It All', '74%', '71%', '6.7/10'], ['2011', 'Melancholia', '77%', '80%', '7.1/10'], ['1987', 'Epidemic', '33%', '66%', '6.1/10'], ['2005', 'Manderlay', '51%', '46%', '7.4/10'], ['2013', 'Nymphomaniac: Volume II', '79%', '76%', '7.2/10'], ['2009', 'Antichrist', '48%', '49%', '6.6/10'], ['2013', 'Nymphomaniac: Volume I', '77%', '63%', '7.5/10'], ['1991', 'Europa', '85%', '66%', '7.7/10'], ['1984', 'The Element of Crime', '77%', 'N/A', '6.9/10'], ['1996', 'Breaking the Waves', '86%', '76%', '7.9/10']]
|
Nymphomaniac: Volume II
|
Answer:
| 128
| 15
| 369
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which mountain peak has the most elevation in feet?
|
[['Rank', 'Mountain Peak', 'Nation', 'Province', 'Elevation', 'Prominence', 'Isolation'], ['14', 'Montaña San Ildefonso PB', 'Honduras', 'Cortés', '2242\xa0m\\n7,356\xa0ft', '1702\xa0m\\n5,584\xa0ft', '68\xa0km\\n42\xa0mi'], ['6', 'Alto Cuchumatanes PB', 'Guatemala', 'Huehuetenango', '3837\xa0m\\n12,589\xa0ft', '1877\xa0m\\n6,158\xa0ft', '65\xa0km\\n40\xa0mi'], ['5', 'Volcán de Agua PB', 'Guatemala', 'Escuintla\\nSacatepéquez', '3761\xa0m\\n12,339\xa0ft', '1981\xa0m\\n6,499\xa0ft', '16\xa0km\\n10\xa0mi'], ['2', 'Chirripó Grande PB', 'Costa Rica', 'Cartago\\nLimón\\nSan José', '3819\xa0m\\n12,530\xa0ft', '3726\xa0m\\n12,224\xa0ft', '864\xa0km\\n537\xa0mi'], ['12', 'Volcán Atitlán PB', 'Guatemala', 'Sololá', '3537\xa0m\\n11,604\xa0ft', '1754\xa0m\\n5,755\xa0ft', '35\xa0km\\n21\xa0mi'], ['7', 'Volcán Irazú PB', 'Costa Rica', 'Cartago\\nSan José', '3402\xa0m\\n11,161\xa0ft', '1872\xa0m\\n6,142\xa0ft', '48\xa0km\\n30\xa0mi'], ['1', 'Volcán Tajumulco PB', 'Guatemala', 'San Marcos', '4220\xa0m\\n13,845\xa0ft', '3980\xa0m\\n13,058\xa0ft', '722\xa0km\\n448\xa0mi'], ['10', 'Volcán San Miguel PB', 'El Salvador', 'San Miguel', '2131\xa0m\\n6,991\xa0ft', '1831\xa0m\\n6,007\xa0ft', '64\xa0km\\n40\xa0mi'], ['8', 'Montañas Peña Blanca High Point PB', 'Guatemala', 'Huehuetenango', '3518\xa0m\\n11,542\xa0ft', '1858\xa0m\\n6,096\xa0ft', '42\xa0km\\n26\xa0mi'], ['4', 'Cerro las Minas PB', 'Honduras', 'Lempira', '2849\xa0m\\n9,347\xa0ft', '2069\xa0m\\n6,788\xa0ft', '130\xa0km\\n81\xa0mi'], ['9', 'Volcán Acatenango PB', 'Guatemala', 'Chimaltenango\\nSacatepéquez', '3975\xa0m\\n13,041\xa0ft', '1835\xa0m\\n6,020\xa0ft', '126\xa0km\\n78\xa0mi'], ['3', 'Montaña de Santa Bárbara PB', 'Honduras', 'Santa Bárbara', '2744\xa0m\\n9,003\xa0ft', '2084\xa0m\\n6,837\xa0ft', '74\xa0km\\n46\xa0mi'], ['15', 'Volcán San Cristóbal PB', 'Nicaragua', 'Chinandega', '1745\xa0m\\n5,725\xa0ft', '1665\xa0m\\n5,463\xa0ft', '134\xa0km\\n83\xa0mi'], ['13', 'Pico Bonito PB', 'Honduras', 'Atlántida', '2450\xa0m\\n8,038\xa0ft', '1710\xa0m\\n5,610\xa0ft', '152\xa0km\\n95\xa0mi'], ['11', 'Cerro Tacarcuna PB', 'Panama', 'Darién', '1875\xa0m\\n6,152\xa0ft', '1770\xa0m\\n5,807\xa0ft', '99\xa0km\\n61\xa0mi']]
|
Volcán Tajumulco PB
|
Answer:
| 128
| 15
| 1,009
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which team(s)did not win more than once?
|
[['Date', 'Rnd', 'Race Name', 'Circuit', 'City/Location', 'Pole position', 'Winning driver', 'Winning team', 'Report'], ['13', 'September 16', 'Red Roof Inns 200', 'Mid-Ohio Sports Car Course', 'Lexington, Ohio', 'Michael Andretti', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['6', 'June 24', "Budweiser/G.I.Joe's 200", 'Portland International Raceway', 'Portland, Oregon', 'Danny Sullivan', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['2', 'April 22', 'Toyota Long Beach Grand Prix', 'Streets of Long Beach', 'Long Beach, California', 'Al Unser, Jr.', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['NC', 'October 6', 'Marlboro Challenge', 'Nazareth Speedway', 'Nazareth, Pennsylvania', 'Michael Andretti', 'Rick Mears', 'Team Penske', 'Report'], ['16', 'October 21', 'Champion Spark Plug 300K', 'Laguna Seca Raceway', 'Monterey, California', 'Danny Sullivan', 'Danny Sullivan', 'Team Penske', 'Report'], ['12', 'September 2', 'Molson Indy Vancouver', 'Streets of Vancouver', 'Vancouver, British Columbia', 'Michael Andretti', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['3', 'May 27', '74th Indianapolis 500', 'Indianapolis Motor Speedway', 'Speedway, Indiana', 'Emerson Fittipaldi', 'Arie Luyendyk', 'Doug Shierson Racing', 'Report'], ['5', 'June 17', 'Valvoline Grand Prix of Detroit', 'Streets of Detroit', 'Detroit, Michigan', 'Michael Andretti', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['4', 'June 3', 'Miller Genuine Draft 200', 'Milwaukee Mile', 'West Allis, Wisconsin', 'Rick Mears', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['8', 'July 15', 'Marlboro Grand Prix at the Meadowlands', 'Meadowlands Sports Complex', 'East Rutherford, New Jersey', 'Michael Andretti', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['15', 'October 7', 'Bosch Spark Plug Grand Prix', 'Nazareth Speedway', 'Nazareth, Pennsylvania', 'Bobby Rahal', 'Emerson Fittipaldi', 'Team Penske', 'Report'], ['7', 'July 8', 'Budweiser Grand Prix of Cleveland', 'Cleveland Burke Lakefront Airport', 'Cleveland, Ohio', 'Rick Mears', 'Danny Sullivan', 'Team Penske', 'Report'], ['10', 'August 5', 'Marlboro 500', 'Michigan International Speedway', 'Brooklyn, Michigan', 'Emerson Fittipaldi', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['1', 'April 8', 'Autoworks 200', 'Phoenix International Raceway', 'Phoenix, Arizona', 'Rick Mears', 'Rick Mears', 'Team Penske', 'Report'], ['14', 'September 23', 'Texaco/Havoline 200', 'Road America', 'Elkhart Lake, Wisconsin', 'Danny Sullivan', 'Michael Andretti', 'Newman/Haas Racing', 'Report'], ['9', 'July 22', 'Molson Indy Toronto', 'Exhibition Place', 'Toronto, Ontario', 'Danny Sullivan', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report'], ['11', 'August 26', 'Texaco/Havoline Grand Prix of Denver', 'Streets of Denver', 'Denver, Colorado', 'Teo Fabi', 'Al Unser, Jr.', 'Galles-Kraco Racing', 'Report']]
|
Doug Shierson Racing
|
Answer:
| 128
| 17
| 900
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:number of first episode in which the iron chef did not win
|
[['Episode', 'Show #', 'Iron Chef', 'Challenger', 'Challenger specialty', 'Secret ingredient(s) or theme', 'Winner', 'Final score'], ['11', 'IA0503', 'Cat Cora', 'Todd Richards', 'Modern Southern', 'Carrots', 'Cat Cora', '48-46'], ['5', 'IA0504', 'Cat Cora', 'Mark Tarbell', 'Seasonal Organic', 'Apples', 'Mark Tarbell', '50-44'], ['12', 'IA0505', 'Masaharu Morimoto', 'Fortunato Nicotra', 'Seasonal Italian', 'Kampachi', 'Masaharu Morimoto', '59-50'], ['8', 'IA0507', 'Cat Cora', 'Mary Dumont', 'French-American', 'Milk and cream', 'Cat Cora', '51-46'], ['3', 'IA0509', 'Cat Cora', 'Alexandra Guarnaschelli', 'French-American', "Farmers' Market", 'Cat Cora', '45-41'], ['7', 'IA0510', 'Mario Batali', 'Charles Clark', 'New American', 'Halibut', 'Mario Batali', '51-50'], ['10', 'IASP08', 'Cat Cora & Paula Deen', 'Tyler Florence & Robert Irvine', 'Southern (Deen), Contemporary American (Florence), International (Irvine)', 'Sugar', 'Cat Cora & Paula Deen', '49-47'], ['2', 'IA0508', 'Mario Batali', 'Tony Liu', 'Pan-European', 'Opah', 'Mario Batali', '55-47'], ['4', 'IA0501', 'Mario Batali', 'Andrew Carmellini', 'Urban Italian', 'Parmigiano-Reggiano', 'Mario Batali', '56-55'], ['1', 'IA0502', 'Bobby Flay', 'Ben Ford', 'Regional American', 'Blue foot chicken', 'Bobby Flay', '44-35'], ['9', 'IASP07', 'Michael Symon', 'Ricky Moore', 'Contemporary American', 'Traditional Thanksgiving', 'Michael Symon', '51-43'], ['6', 'IA0506', 'Bobby Flay', 'Kurt Boucher', 'French-American', 'Arctic char', 'Bobby Flay', '46-39']]
|
5
|
Answer:
| 128
| 12
| 526
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did charlie sheen go without a nomination after 2008?
|
[['Year', 'Result', 'Award', 'Film'], ['1999', 'Nominated', 'SAG Award Outstanding Performance by a Cast in a Theatrical Motion Picture', 'Being John Malkovich'], ['2005', 'Nominated', 'Golden Globe Award for Best Actor – Television Series Musical or Comedy', 'Two and a Half Men'], ['1989', 'Won', 'Bronze Wrangler Theatrical Motion Picture', 'Young Guns'], ['2001', 'Nominated', 'ALMA Award Outstanding Actor in a Television Series', 'Spin City'], ['2006', 'Nominated', 'Emmy Award for Outstanding Lead Actor - Comedy Series', 'Two and a Half Men'], ['2002', 'Nominated', "Kids' Choice Awards Favorite Television Actor", 'Two and a Half Men'], ['2005', 'Nominated', 'SAG Award Outstanding Performance by a Male Actor in a Comedy Series', 'Two and a Half Men'], ['2002', 'Won', 'Golden Globe Award Best Performance by an Actor in a Television Series - Musical or Comedy', 'Spin City'], ['2007', 'Nominated', 'Emmy Award for Outstanding Lead Actor - Comedy Series', 'Two and a Half Men'], ['2008', 'Won', 'ALMA Award Outstanding Actor in a Comedy Television Series', 'Two and a Half Men'], ['2008', 'Nominated', 'Outstanding Lead Actor - Comedy Series', 'Two and a Half Men'], ['2007', 'Nominated', 'Teen Choice Award Choice TV Actor: Comedy', 'Two and a Half Men'], ['2010', 'Nominated', 'SAG Award Outstanding Performance by a Male Actor in a Comedy Series', 'Two and a Half Men'], ['2006', 'Won', 'Golden Icon Award Best Actor - Comedy Series', 'Two and a Half Men'], ['2008', 'Nominated', 'Teen Choice Awards Choice TV Actor: Comedy', 'Two and a Half Men'], ['2002', 'Nominated', 'ALMA Award Outstanding Actor in a Television Series', 'Spin City'], ['2007', 'Nominated', "People's Choice Award Favorite Male TV Star", ''], ['1999', 'Nominated', 'Online Film Critics Society Award for Best Cast', 'Being John Malkovich'], ['2012', 'Won', 'WWE Slammy Award Top Social Media Ambassador', 'WWE Raw'], ['2008', 'Nominated', "People's Choice Award Favorite Male TV Star", ''], ['2006', 'Nominated', 'Golden Globe Award for Best Actor – Television Series Musical or Comedy', 'Two and a Half Men']]
|
2 years
|
Answer:
| 128
| 21
| 547
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which nation earned more medals than austria?
|
[['Rank', 'Nation', 'Gold', 'Silver', 'Bronze', 'Total'], ['5', 'Sweden', '2', '4', '4', '10'], ['6', 'United States', '2', '3', '2', '7'], ['9', 'Germany', '1', '0', '1', '2'], ['7', 'Norway', '2', '1', '1', '4'], ['1', 'Soviet Union', '*7*', '3', '6', '16'], ['4', 'Switzerland', '3', '2', '1', '6'], ['2', 'Austria', '4', '3', '4', '11'], ['3', 'Finland', '3', '3', '1', '7'], ['8', 'Italy', '1', '2', '0', '3'], ['10', 'Canada', '0', '1', '2', '3']]
|
Soviet Union
|
Answer:
| 128
| 10
| 207
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the only winning driver not from the us?
|
[['Round', 'Date', 'Circuit', 'Winning driver (TA2)', 'Winning vehicle (TA2)', 'Winning driver (TA1)', 'Winning vehicle (TA1)'], ['9', 'October 8', 'Laguna Seca', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['3', 'June 11', 'Portland', 'Tuck Thomas', 'Chevrolet Monza', 'Bob Matkowitch', 'Chevrolet Corvette'], ['4', 'June 25', 'Mont-Tremblant', 'Monte Sheldon', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['5', 'July 8', 'Watkins Glen‡', 'Hal Shaw, Jr.\\n Monte Shelton', 'Porsche 935', 'Brian Fuerstenau\\n Bob Tullius', 'Jaguar XJS'], ['1', 'May 21', 'Sears Point', 'Greg Pickett', 'Chevrolet Corvette', 'Gene Bothello', 'Chevrolet Corvette'], ['8', 'September 4', 'Road America', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['10', 'November 5', 'Mexico City', 'Ludwig Heimrath', 'Porsche 935', 'Bob Tullius', 'Jaguar XJS'], ['7', 'August 19', 'Mosport', 'Greg Pickett', 'Chevrolet Corvette', 'Bob Tullius', 'Jaguar XJS'], ['2', 'June 4', 'Westwood', 'Ludwig Heimrath', 'Porsche 935', 'Nick Engels', 'Chevrolet Corvette'], ['6', 'August 13', 'Brainerd', 'Jerry Hansen', 'Chevrolet Monza', 'Bob Tullius', 'Jaguar XJS']]
|
Ludwig Heimrath
|
Answer:
| 128
| 10
| 426
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where did marcos pizzelli score his only international goal in 1008?
|
[['Goal', 'Date', 'Venue', 'Opponent', 'Score', 'Result', 'Competition'], ['3', '2011-6-4', 'Petrovsky Stadium, Saint Petersburg, Russia', 'Russia', '0-1', '3–1', 'Euro 2012 Q'], ['5', '2011-10-7', 'Hanrapetakan Stadium, Yerevan, Armenia', 'Macedonia', '1-0', '4-1', 'Euro 2012 Q'], ['7', '2012-2-29', 'Tsirion Stadium, Limassol, Cyprus', 'Canada', '1-2', '1-3', 'Friendly match'], ['4', '2011-9-2', "Estadi Comunal d'Aixovall, Andorra la Vella, Andorra", 'Andorra', '0-1', '0-3', 'Euro 2012 Q'], ['6', '2012-2-29', 'Tsirion Stadium, Limassol, Cyprus', 'Canada', '1-1', '1-3', 'Friendly match'], ['2', '2010-10-12', 'Hanrapetakan Stadium, Yerevan, Armenia', 'Andorra', '4–0', '4–0', 'Euro 2012 Q'], ['1', '2008-5-28', 'Sheriff Stadium, Tiraspol, Moldova', 'Moldova', '0-1', '2–2', 'Friendly match']]
|
Sheriff Stadium, Tiraspol, Moldova
|
Answer:
| 128
| 7
| 331
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in the 16th hashida awards, did inoue win best actress or the newcomer award?
|
[['Year', 'Organization', 'Award', 'Work', 'Result'], ['2011', '3rd TAMA Film Award', 'Best Emerging Actress', 'Miracle in the Pacific', 'Won'], ['2007', '2007 MTV Student Voice Awards', 'Best Actress', 'Hana Yori Dango 2', 'Won'], ['2007', '54th The Television Academy Drama Awards', 'Best Actress', 'First Kiss', 'Nominated'], ['2007', '10th Nikkan Sports Drama Grand Prix', 'Best Actress', 'Hana Yori Dango 2', 'Won'], ['2010', 'Nikkan Sports Grand Prix (Fall)', 'Best Supporting Actress', 'Veterinarian Dolittle', 'Nominated'], ['2012', '16th Nikkan Sport Grand Prix', 'Best Actress', 'Tokkan', 'Nominated'], ['2011', '70th The Television Drama Academy Awards', 'Best Actress', 'Ohisama', 'Won'], ['2011', 'TV Navi', 'Best Actress', 'Ohisama', 'Won'], ['2011', '35th Fumiko Yamaji Award Film Awards', 'Newcomer Actress', 'Youkame no Semi', 'Won'], ['2007', '16th Hashida Awards', 'Newcomer Award', 'Hana Yori Dango 2', 'Won'], ['2008', "Nickelodeon Kids' Choice Awards", 'Best Actress', 'Hana Yori Dango 2', 'Won'], ['2012', '35th Japan Academy Awards', 'Best Starring Actress', 'Youkame no Semi', 'Won'], ['2005', '47th The Television Drama Academy Awards', 'Best Actress', 'Hana Yori Dango', 'Won'], ['2011', '26th Nikkan Sport Film Awards', 'Best Newcomer', 'Youkame no Semi, Miracle in the Pacific', 'Won'], ['2012', 'Japan Film Festival Theater Staff', 'Best Actress', 'Youkame no Semi', 'Won']]
|
Newcomer Award
|
Answer:
| 128
| 15
| 435
|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year was the only year tasmania won the sate/ territory men's division?
|
[['Year', "State/Territory Men's Division", "State/Territory Women's Division", 'Major Centres Division', 'Community Division', "Women's Division"], ['2012', 'Queensland', 'New South Wales', '', '', ''], ['2006', 'Queensland', '', 'Alice Springs', 'Melville Island', 'Darwin'], ['2011', 'New South Wales', 'New South Wales', 'Maranoa Murris', 'Gap Angels', 'Bush Potatoes'], ['2001', 'Tasmania', '', '', '', ''], ['2007', 'New South Wales', '', 'Alkupitja', 'Cat Tigers', 'CGA Cougars'], ['2004', 'Queensland', '', 'Alice Springs', 'Normanton', 'Tennant Creek'], ['2009', 'Queensland', '', 'Alkupitja', 'Tangentyere', 'New South Wales'], ['2010', 'Western Australia', '', '', '', ''], ['2003', 'New South Wales', '', 'Darwin', '', ''], ['2008', 'Queensland', '', 'Katherine', 'Cooktown', 'New South Wales'], ['2012', 'New South Wales', 'New South Wales', 'Darwin', 'Brothers in Arms', 'Bush Potatoes'], ['2005', 'Queensland', '', 'Alice Springs', 'Alkupitja', 'Darwin'], ['2002', 'Northern Territory', '', 'Darwin', '', '']]
|
2001
|
Answer:
| 128
| 13
| 320
|
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