context stringlengths 362 4.81k | question stringlengths 2.11k 2.25k | answer stringlengths 1 260 | max_new_tokens int64 128 128 | answer_prefix stringclasses 1
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|---|---|---|---|---|
Table InputTable: [["Season", "Date", "Location", "Discipline", "Place"], ["2014", "22 Dec 2013", "Val-d'Isère, France", "Giant slalom", "1st"], ["2014", "1 Dec 2013", "Beaver Creek, USA", "Giant slalom", "3rd"], ["2014", "25 Jan 2014", "Cortina d'Ampezzo, Italy", "Downhill", "3rd"], ["2014", "24 Jan 2014", "Cortina d'Ampezzo, Italy", "Downhill", "2nd"], ["2014", "7 Dec 2013", "Lake Louise, Canada", "Downhill", "2nd"], ["2014", "14 Dec 2013", "St. Moritz, Switzerland", "Super-G", "1st"], ["2012", "2 Dec 2011", "Lake Louise, Canada", "Downhill", "2nd"], ["2012", "28 Jan 2012", "St. Moritz, Switzerland", "Downhill", "3rd"], ["2013", "30 Nov 2012", "Lake Louise, Canada", "Downhill", "3rd"], ["2014", "8 Dec 2013", "Lake Louise, Canada", "Super-G", "2nd"], ["2013", "1 Mar 2013", "Garmisch, Germany", "Super-G", "1st"], ["2014", "29 Nov 2013", "Beaver Creek, USA", "Downhill", "2nd"], ["2014", "26 Jan 2014", "Cortina d'Ampezzo, Italy", "Super-G", "2nd"], ["2012", "4 Feb 2012", "Garmisch, Germany", "Downhill", "3rd"], ["2012", "26 Feb 2012", "Bansko, Bulgaria", "Super-G", "2nd"], ["2012", "5 Feb 2012", "Garmisch, Germany", "Super-G", "3rd"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 season did weirather get her first 1st place podium finish? | 2013 | 128 | Answer: |
Table InputTable: [["Season", "Series", "Team", "Races", "Wins", "Poles", "F/Laps", "Podiums", "Points", "Position"], ["2009", "Formula Renault 2.0 Northern European Cup", "Krenek Motorsport", "14", "0", "0", "0", "0", "44", "21st"], ["2012", "Formula 3 Euro Series", "Angola Racing Team", "21", "0", "0", "0", "0", "14", "14th"], ["2010", "Austria Formula 3 Cup", "Sonangol Motopark", "4", "1", "2", "3", "2", "35", "9th"], ["2010", "ATS Formel 3 Cup", "China Sonangol", "5", "0", "0", "0", "0", "0", "19th"], ["2011", "Formula Pilota China", "Asia Racing Team", "12", "2", "0", "0", "3", "124", "2nd"], ["2012", "59th Macau Grand Prix Formula 3", "Angola Racing Team", "2", "0", "0", "0", "0", "β", "23rd"], ["2012", "Masters of Formula 3", "Angola Racing Team", "1", "0", "0", "0", "0", "β", "18th"], ["2009", "Asian Formula Renault Challenge", "Asia Racing Team", "12", "6", "2", "4", "7", "287", "2nd"], ["2012", "British Formula 3 Championship", "Angola Racing Team", "5", "0", "0", "0", "0", "β", "β"], ["2007", "Asian Formula Renault Challenge", "Champ Motorsports", "12", "0", "0", "0", "1", "64", "14th"], ["2008", "Asian Formula Renault Challenge", "Champ Motorsports", "13", "0", "0", "0", "3", "193", "4th"], ["2013", "GP3 Series", "Carlin", "16", "0", "0", "0", "0", "0", "23rd"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 2 teams are listed as having 2 as the number of poles? | Asia Racing Team, Sonangol Motopark | 128 | Answer: |
Table InputTable: [["Position", "Officer", "current officers", "superseded by", "Royal Household"], ["5", "Lord Privy Seal", "The Rt Hon Andrew Lansley, CBE, MP", "", ""], ["7", "Lord High Constable", "vacant", "Earl Marshal", "Master of the Horse"], ["6", "Lord Great Chamberlain", "The Marquess of Cholmondeley", "Lord High Treasurer", "Lord Chamberlain"], ["8", "Earl Marshal", "The Duke of Norfolk", "", "Master of the Horse"], ["9", "Lord High Admiral", "HRH The Duke of Edinburgh", "", ""], ["1", "Lord High Steward", "vacant", "Justiciar", "Lord Steward"], ["2", "Lord High Chancellor", "The Rt Hon Chris Grayling, MP", "", ""], ["3", "Lord High Treasurer", "in commission", "", ""], ["4", "Lord President of the Council", "The Rt Hon Nick Clegg, MP", "", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 earl marshal listed above or below lord privy seal? | below | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "1st", "400 m hurdles", "48.45"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "400 m hurdles", "49.23"], ["2007", "World Championships", "Osaka, Japan", "3rd", "400 m hurdles", "48.12 (NR)"], ["2001", "World Championships", "Edmonton, Canada", "18th (sf)", "400 m hurdles", "49.80"], ["2012", "European Championships", "Helsinki, Finland", "18th (sf)", "400 m hurdles", "50.77"], ["2006", "European Championships", "Gothenburg, Sweden", "2nd", "400 m hurdles", "48.71"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "1st", "4x400 m relay", "3:03.32"], ["1999", "European Junior Championships", "Riga, Latvia", "4th", "400 m hurdles", "52.17"], ["2004", "Olympic Games", "Athens, Greece", "6th", "400 m hurdles", "49.00"], ["2007", "World Championships", "Osaka, Japan", "3rd", "4x400 m relay", "3:00.05"], ["2002", "European Indoor Championships", "Vienna, Austria", "1st", "400 m", "45.39 (CR, NR)"], ["2001", "Universiade", "Beijing, China", "8th", "400 m hurdles", "49.68"], ["2002", "European Championships", "Munich, Germany", "4th", "400 m", "45.40"], ["2008", "Olympic Games", "Beijing, China", "6th", "400 m hurdles", "48.42"], ["2002", "European Indoor Championships", "Vienna, Austria", "1st", "4x400 m relay", "3:05.50 (CR)"], ["2003", "World Indoor Championships", "Birmingham, United Kingdom", "3rd", "4x400 m relay", "3:06.61"], ["2003", "World Indoor Championships", "Birmingham, United Kingdom", "7th (sf)", "400 m", "46.82"], ["2002", "European Championships", "Munich, Germany", "8th", "4x400 m relay", "DQ"], ["2004", "Olympic Games", "Athens, Greece", "10th (h)", "4x400 m relay", "3:03.69"], ["2008", "Olympic Games", "Beijing, China", "7th", "4x400 m relay", "3:00.32"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 1st place finishes has plawgo had? | 5 | 128 | Answer: |
Table InputTable: [["Date", "Site", "Winning team", "Winning team", "Losing team", "Losing team", "Series"], ["September 17, 1998", "Colorado Springs", "Air Force", "30", "Colorado State", "27", "AFA 22β14β1"], ["September 16, 1995", "Colorado Springs", "Colorado State", "27", "Air Force", "20", "AFA 20β13β1"], ["September 29, 2012", "Colorado Springs", "Air Force", "42", "Colorado State", "21", "AFA 31β19β1"], ["September 3, 1994", "Colorado Springs", "Colorado State", "34", "Air Force", "21", "AFA 20β12β1"], ["October 16, 2003", "Fort Collins", "Colorado State", "30", "Air Force", "20", "AFA 23β18β1"], ["October 31, 2002", "Colorado Springs", "Colorado State", "31", "Air Force", "12", "AFA 23β17β1"], ["November 30, 2013", "Fort Collins", "Colorado State", "58", "Air Force", "13", "AFA 31β20β1"], ["September 27, 1986", "Colorado Springs", "Air Force", "24", "Colorado State", "7", "AFA 16β8β1"], ["September 29, 1984", "Colorado Springs", "Air Force", "52", "Colorado State", "10", "AFA 14β8β1"], ["September 1, 1990", "Colorado Springs", "Colorado State", "35", "Air Force", "33", "AFA 19β9β1"], ["September 30, 1989", "Fort Collins", "Air Force", "46", "Colorado State", "21", "AFA 19β8β1"], ["October 17, 1992", "Colorado Springs", "Colorado State", "32", "Air Force", "28", "AFA 20β10β1"], ["November 20, 2004", "Colorado Springs", "Air Force", "47", "Colorado State", "17", "AFA 24β18β1"], ["October 9, 2010", "Colorado Springs", "Air Force", "49", "Colorado State", "27", "AFA 29β19β1"], ["October 16, 1982", "Colorado Springs", "Colorado State", "21", "Air Force", "11", "AFA 12β8β1"], ["November 8, 2008", "Colorado Springs", "Air Force", "38", "Colorado State", "17", "AFA 27β19β1"], ["November 2, 1996", "Colorado Springs", "Colorado State", "42", "Air Force", "41", "AFA 20β14β1"], ["September 26, 1987", "Fort Collins", "Air Force", "27", "Colorado State", "19", "AFA 17β8β1"], ["October 3, 1981", "Colorado Springs", "Air Force", "28", "Colorado State", "14", "AFA 12β7β1"], ["September 29, 2005", "Fort Collins", "Colorado State", "41", "Air Force", "23", "AFA 24β19β1"], ["October 12, 2006", "Colorado Springs", "Air Force", "24", "Colorado State", "21", "AFA 25β19β1"], ["September 20, 1997", "Fort Collins", "Air Force", "24", "Colorado State", "0", "AFA 21β14β1"], ["September 3, 1983", "Fort Collins", "Air Force", "34", "Colorado State", "13", "AFA 13β8β1"], ["November 11, 2000", "Colorado Springs", "Air Force", "44", "Colorado State", "40", "AFA 23β15β1"], ["November 26, 2011", "Fort Collins", "Air Force", "45", "Colorado State", "21", "AFA 30β19β1"], ["November 18, 1999", "Fort Collins", "Colorado State", "41", "Air Force", "21", "AFA 22β15β1"], ["October 19, 1985", "Fort Collins", "#10 Air Force", "35", "Colorado State", "19", "AFA 15β8β1"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 how many games has the winning team scored at least 30 points? | 23 | 128 | Answer: |
Table InputTable: [["Pick #", "Player", "Position", "Nationality", "NHL team", "College/junior/club team"], ["163", "Steve Taylor", "Left Wing", "United States", "Philadelphia Flyers", "Providence College (ECAC)"], ["149", "Rick Zombo", "Defence", "United States", "Detroit Red Wings", "Austin Mavericks (USHL)"], ["148", "Dan McFall", "Defence", "United States", "Winnipeg Jets", "Buffalo Jr. Sabres (NAJHL)"], ["164", "Gates Orlando", "Centre", "Canada", "Buffalo Sabres", "Providence College (ECAC)"], ["155", "Mike Sturgeon", "Defence", "Canada", "Edmonton Oilers", "Kelowna Buckaroos (BCJHL)"], ["165", "Dan Brennan", "Left Wing", "Canada", "Los Angeles Kings", "University of North Dakota (WCHA)"], ["154", "Mitch Lamoureux", "Centre", "Canada", "Pittsburgh Penguins", "Oshawa Generals (OMJHL)"], ["162", "Dale DeGray", "Defence", "Canada", "Calgary Flames", "Oshawa Generals (OMJHL)"], ["159", "Johan Mellstrom", "Left Wing", "Sweden", "Chicago Black Hawks", "Falun (Sweden)"], ["157", "Petri Skriko", "Right Wing", "Finland", "Vancouver Canucks", "Saipa (Finland)"], ["161", "Armel Parisee", "Defence", "Canada", "Boston Bruins", "Chicoutimi Saguenéens (QMJHL)"], ["150", "Tony Arima", "Left Wing", "Finland", "Colorado Rockies", "Jokerit (Finland)"], ["151", "Denis Dore", "Right Wing", "Canada", "Hartford Whalers", "Chicoutimi Saguenéens (QMJHL)"], ["168", "Bill Dowd", "Defence", "Canada", "New York Islanders", "Ottawa 67's (OMJHL)"], ["166", "Paul Gess", "Left Wing", "United States", "Montreal Canadiens", "Bloomington Jefferson High School (USHS-MN)"], ["167", "Alain Vigneault", "Defence", "Canada", "St. Louis Blues", "Trois-Rivières Draveurs (QMJHL)"], ["152", "Gaetan Duchesne", "Left Wing", "Canada", "Washington Capitals", "Quebec Remparts (QMJHL)"], ["160", "Kari Kanervo", "Centre", "Finland", "Minnesota North Stars", "TPS (Finland)"], ["153", "Richard Turmel", "Defence", "Canada", "Toronto Maple Leafs", "Shawinigan Cataractes (QMJHL)"], ["158", "Andre Cote", "Right Wing", "Canada", "Quebec Nordiques", "Quebec Remparts (QMJHL)"], ["156", "Ari Lahteenmaki", "Right Wing", "Finland", "New York Rangers", "HIFK (Finland)"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 had the first pick this round? | Winnipeg Jets | 128 | Answer: |
Table InputTable: [["Date", "Location", "Air/Ground", "Number", "Type", "Status"], ["13 April 1944", "West of Mannheim, Germany", "Air", "1", "FW-190", "Destroyed"], ["27 November 1944", "South of Magdeburg, Germany", "Air", "4", "FW-190", "Destroyed"], ["16 March 1944", "20 miles south of Stuttgart, Germany", "Air", "1", "Me-110", "Destroyed"], ["18 August 1944", "20 miles northeast of Paris, France", "Air", "0.5", "Me-109", "Destroyed"], ["14 January 1945", "20 miles northwest of Berlin, Germany", "Air", "1", "Me-109", "Destroyed"], ["13 September 1944", "South of Nordhausen, Germany", "Air", "2.5", "Me-109", "Destroyed"], ["6 October 1944", "20 miles northwest of Berlin, Germany", "Air", "2", "Me-109", "Destroyed"], ["8 March 1944", "Near Steinhuder Meer (Lake), Germany", "Air", "1", "Me-109", "Destroyed"], ["24 April 1944", "South of Munich, Germany", "Air", "3", "Me-110", "Destroyed"], ["6 October 1944", "20 miles northwest of Berlin, Germany", "Air", "1", "Me-109", "Damaged"], ["27 May 1944", "North of Strasbourg, France", "Air", "1", "Me-109", "Damaged"], ["11 April 1944", "20 miles northeast of Magdeburg, Germany", "Air", "0.5", "Me-109", "Destroyed"], ["25 January 1952", "Korea", "Air", "1", "Mig-15", "Damaged"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 fw-190's he damaged or destroyed? | 2 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["6", "South Korea", "0", "0", "2", "2"], ["2", "Japan", "7", "10", "7", "24"], ["5", "North Korea", "1", "0", "1", "2"], ["4", "Kazakhstan", "2", "2", "0", "4"], ["3", "Uzbekistan", "1", "2", "3", "6"], ["1", "China", "13", "9", "13", "35"], ["Total", "Total", "24", "23", "26", "73"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 received more bronze medals: japan or south korea? | Japan | 128 | Answer: |
Table InputTable: [["Pick #", "NFL Team", "Player", "Position", "College"], ["3", "Baltimore Colts", "Alan Ameche", "Fullback", "Wisconsin"], ["1", "Baltimore Colts (Lottery bonus pick)", "George Shaw", "Quarterback", "Oregon"], ["5", "Green Bay Packers", "Tom Bettis", "Guard", "Purdue"], ["2", "Chicago Cardinals", "Max Boydston", "End", "Oklahoma"], ["9", "Philadelphia Eagles", "Dick Bielski", "Fullback", "Maryland"], ["11", "Chicago Bears", "Ron Drzewiecki", "Halfback", "Marquette"], ["6", "Pittsburgh Steelers", "Frank Varrichione", "Tackle", "Notre Dame"], ["8", "New York Giants", "Joe Heap", "Halfback", "Notre Dame"], ["7", "Los Angeles Rams", "Larry Morris", "Center", "Georgia Tech"], ["4", "Washington Redskins", "Ralph Guglielmi", "Quarterback", "Notre Dame"], ["12", "Detroit Lions", "Dave Middleton", "Halfback", "Auburn"], ["13", "Cleveland Browns", "Kurt Burris", "Center", "Oklahoma"], ["10", "San Francisco 49ers", "Dickey Moegle", "Halfback", "Rice"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 drafted above alan ameche? | Max Boydston | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Runner-up", "7.", "22 July 2012", "Swiss Open, Switzerland", "Clay", "Thomaz Bellucci", "7β6(8β6), 4β6, 2β6"], ["Runner-up", "6.", "8 January 2012", "Chennai Open, India", "Hard", "Milos Raonic", "7β6(7β4), 6β7(4β7), 6β7(4β7)"], ["Winner", "4.", "6 January 2013", "Chennai Open, India", "Hard", "Roberto Bautista-Agut", "3β6, 6β1, 6β3"], ["Winner", "3.", "15 July 2012", "Stuttgart Open, Germany", "Clay", "Juan MΓ³naco", "6β4, 5β7, 6β3"], ["Winner", "1.", "2 October 2011", "Malaysian Open, Malaysia", "Hard (i)", "Marcos Baghdatis", "6β4, 7β5"], ["Runner-up", "5.", "30 October 2011", "St. Petersburg Open, Russia", "Hard (i)", "Marin ΔiliΔ", "3β6, 6β3, 2β6"], ["Runner-up", "2.", "19 June 2010", "UNICEF Open, Netherlands", "Grass", "Sergiy Stakhovsky", "3β6, 0β6"], ["Runner-up", "3.", "27 February 2011", "International Tennis Championships, United States", "Hard", "Juan MartΓn del Potro", "4β6, 4β6"], ["Runner-up", "1.", "25 October 2009", "Kremlin Cup, Russia", "Hard (i)", "Mikhail Youzhny", "7β6(7β5), 0β6, 4β6"], ["Winner", "2.", "23 October 2011", "Kremlin Cup, Russia", "Hard (i)", "Viktor Troicki", "6β4, 6β2"], ["Runner-up", "4.", "18 June 2011", "Aegon International, United Kingdom", "Grass", "Andreas Seppi", "6β7(5β7), 6β3, 3β5 ret."]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:does the chennai open tournament and the swiss open tournament have the same surface listed? | No | 128 | Answer: |
Table InputTable: [["Thread\\nnominal size", "Outer diameter\\n[mm (in)]", "Threads per inch\\n(TPI)", "Pitch\\n[in (mm)]", "Inner diameter\\n[mm (in)]", "Cable diameter\\n[mm (in)]"], ["PG21", "28.3 (1.114)", "16", "0.0625 (1.5875)", "26.78 (1.054)", "13 to 18 (0.512 to 0.709)"], ["PG16", "22.5 (0.886)", "18", "0.05556 (1.4112)", "21.16 (0.833)", "10 to 14 (0.394 to 0.551)"], ["PG29", "37.0 (1.457)", "16", "0.0625 (1.5875)", "35.48 (1.397)", "18 to 25 (0.709 to 0.984)"], ["PG42", "54.0 (2.126)", "16", "0.0625 (1.5875)", "52.48 (2.066)", ""], ["PG48", "59.3 (2.335)", "16", "0.0625 (1.5875)", "57.78 (2.275)", ""], ["PG36", "47.0 (1.850)", "16", "0.0625 (1.5875)", "45.48 (1.791)", ""], ["PG11", "18.6 (0.732)", "18", "0.05556 (1.4112)", "17.26 (0.680)", "5 to 10 (0.197 to 0.394)"], ["PG7", "12.5 (0.492)", "20", "0.05 (1.270)", "11.28 (0.444)", "3 to 6.5 (0.118 to 0.256)"], ["PG9", "15.5 (0.610)", "18", "0.05556 (1.4112)", "13.86 (0.546)", "4 to 8 (0.157 to 0.315)"], ["PG13.5", "20.4 (0.803)", "18", "0.05556 (1.4112)", "19.06 (0.750)", "6 to 12 (0.236 to 0.472)"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 only thread nominal size with a 21.16mm inner diameter? | PG16 | 128 | Answer: |
Table InputTable: [["Pos", "Name", "Team", "Laps", "Time/Retired", "Grid", "Points"], ["8", "Oriol ServiΓ ", "Forsythe Racing", "69", "+23.406", "13", "15"], ["13", "Robert Doornbos", "Minardi Team USA", "69", "+1:00.638", "9", "8"], ["2", "Jan Heylen", "Conquest Racing", "69", "+7.227", "7", "27"], ["1", "Justin Wilson", "RuSPORT", "69", "1:46:02.236", "2", "32"], ["3", "Bruno Junqueira", "Dale Coyne Racing", "69", "+8.419", "11", "26"], ["15", "Alex Tagliani", "Rocketsports", "68", "+ 1 Lap", "12", "6"], ["11", "Dan Clarke", "Minardi Team USA", "69", "+38.903", "10", "11"], ["6", "Simon Pagenaud", "Team Australia", "69", "+22.698", "5", "19"], ["5", "Neel Jani", "PKV Racing", "69", "+22.262", "4", "21"], ["4", "Tristan Gommendy", "PKV Racing", "69", "+9.037", "3", "23"], ["9", "Graham Rahal", "N/H/L Racing", "69", "+23.949", "6", "13"], ["12", "Katherine Legge", "Dale Coyne Racing", "69", "+44.860", "14", "9"], ["7", "SΓ©bastien Bourdais", "N/H/L Racing", "69", "+22.955", "1", "18"], ["16", "Alex Figge", "Pacific Coast Motorsports", "68", "+ 1 Lap", "16", "5"], ["14", "Will Power", "Team Australia", "69", "+1:01.204", "8", "7"], ["17", "Paul Tracy", "Forsythe Racing", "14", "Mechanical", "17", "4"], ["10", "Ryan Dalziel", "Pacific Coast Motorsports", "69", "+29.554", "15", "11"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 finished directly before servia? | SΓ©bastien Bourdais | 128 | Answer: |
Table InputTable: [["Common name", "Binomial nomenclature", "Colour", "Density ΒΉ", "Location", "Characteristics, Usage and Status"], ["Deodar", "Cedrus deodara", "Yellowish brown", "560Β kg/mΒ³", "Himalayas, Punjab, Uttar Pradesh", "Deodar is the most important timber tree providing soft wood. It can be easily worked and it is moderately strong. It possesses distinct annual rings. It is used for making cheap furniture, railway carriages, railway sleepers, packing boxes, structural work and so forth."], ["Bamboo", "Family Poaceae, tribe Bambuseae", "", "", "Throughout India, especially Assam and Bengal", "Not actually a tree, but a woody grass, it is flexible, very strong and durable. It is used for scaffoldings, thatched roofs, rafters, temporary bridges, and so forth."], ["Satinwood", "Chloroxylon swietenia", "Yellow", "960Β kg/mΒ³", "Central and Southern India", "It is very hard and durable. It is close grained. It is used for furniture and other ornamental works. Vulnerable"], ["Ironwood, Penaga Lilin,\\nBosneak, Gangaw, Mesua", "Mesua ferrea", "Reddish brown", "960β1060Β kg/mΒ³", "", "Ironwood is durable though it is very hard and is not easily worked. It even resists penetration of nails. It is used for ordinary house construction, bridges, piles, agricultural instruments, railway wagons, and railway sleepers."], ["Teak", "Tectona grandis", "Deep yellow to dark brown", "639Β kg/mΒ³", "Central India and Southern India", "Moderately hard, teak is durable and fire-resistant. It can be easily seasoned and worked. It takes up a good polish and is not attacked by white ants and dry rot. It does not corrode iron fastenings and it shrinks little. It is among the most valuable timber trees of the world and its use is limited to superior work only."], ["Palm", "Arecaceae", "Dark brown", "1040Β kg/mΒ³", "Throughout India", "It contains ripe wood in the outer crust. The colour of this ripened wood is dark brown. It is strong, durable and fibrous. Palm is used for furniture, roof covering, rafters and joists."], ["Axlewood", "Anogeissus latifolia", "", "930Β kg/mΒ³", "Andhra Pradesh, Tamil Nadu, Maharashtra, Madhya Pradesh, Bihar, Uttar Pradesh", "It is very strong, hard and tough. It takes a smooth finish. It is subject to cracking."], ["Sandalwood", "Santalum spp.", "White or Red", "930Β kg/mΒ³", "Karnataka, Tamil Nadu, Kerala, Assam, Nagpur, Bengal", "It has a pleasant smell. It is commonly used for agricultural instruments, well curbs, wheels, and mallets. Vulnerable"], ["Spruce", "Picea spp.", "", "480Β kg/mΒ³", "", "Spruce wood resists decay and is not affected by the attack of marine borers. It is however liable to shrink, twist and warp. It is used for piles under water and (formerly) for aeroplane construction."], ["Siris", "Albizia spp.", "Dark brown", "", "North India", "Hard and durable, Siris wood is difficult to work. It is used for well curbs in salty water, beams, posts, and furniture."], ["Tamarind", "Tamarindus indica", "Dark brown", "1280Β kg/mΒ³[citation needed]", "All over India", "Tamarind is knotty and durable. It is a beautiful tree for avenue and gardens. Its development is very slow but it ultimately forms a massive appearance. Its fruit is also very useful. It is used for agricultural instruments, well curbs, sugar mills, carts and brick burning."], ["Benteak", "Lagerstoemia parviflora", "", "675Β kg/mΒ³", "Kerala, Madras, Maharashtra, Karnataka", "It is strong and takes up a smooth surface. It may be used for building constructions, boat building and furniture."], ["Red cedar", "", "Red", "480Β kg/mΒ³", "Assam, Nagpur", "It is soft and even grained. It is used for furniture, door panels and well curbs."], ["Rosewood", "Dalbergia latifolia", "Dark", "850Β kg/mΒ³", "Kerala, Karnataka, Maharashtra, Madhya Pradesh, Tamil Nadu, Orrissa", "It is strong, tough and close-grained. It is a handsome wood that takes up a high polish. It maintains its shape well and is available in large sizes. It is used for furniture of superior quality, cabinet work, ornamental carvings and so forth. Vulnerable"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 species of timber used for engineering purposes in india are listed as vulnerable? | 4 | 128 | Answer: |
Table InputTable: [["School", "Season", "Record", "Conference Record", "Place", "Postseason"], ["Illinois", "1912β20", "85β34", "64β31", "β", ""], ["Illinois", "1912β13", "10β6", "7β6", "5th", ""], ["Illinois", "1918β19", "6β8", "5β7", "5th", ""], ["Illinois", "1919β20", "9β4", "8β4", "3rd", ""], ["Illinois", "1913β14", "9β4", "7β3", "3rd", ""], ["Illinois", "1915β16", "13β3", "9β3", "T2nd", ""], ["Illinois", "1917β18", "9β6", "6β6", "T4th", ""], ["Illinois", "1916β17", "13β3", "10β2", "T1st", "Big Ten Champions"], ["Illinois", "1914β15", "16β0", "12β0", "T1st", "National Champions"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 consecutive years did illinois place in the top 5 between 1912 and 1920? | 8 | 128 | Answer: |
Table InputTable: [["Series", "Name", "Age", "Hometown", "Occupation", "Status"], ["BB2", "Amma Antwi-Agyei", "23", "London", "Table Dancer", "7th - Evicted"], ["BB7", "Imogen Thomas", "23", "Llanelli", "Bar Hostess", "7th - Evicted"], ["BB8", "Shanessa Reilly", "26", "Cardiff", "Care Assistant/Stripper", "12th - Evicted"], ["BB13", "Lydia Louisa", "25", "Cheshire", "Dancer", "14th - Evicted"], ["BB14", "Jackie Travers", "59", "Hertfordshire", "Dance Instructor", "10th - Evicted"], ["BB12", "Rebeckah Vaughan", "28", "Wirral", "Hostess/Entrepreneur", "14th - Evicted"], ["BB11", "Ife Kuku", "25", "Milton Keynes", "Dancer", "16th - Evicted"], ["BB12", "Faye Palmer", "20", "Tamworth", "Professional Wrestler", "6th - Evicted"], ["BB8", "SeΓ‘ny O'Kane", "25", "Derry", "Charity Worker", "19th - Evicted"], ["BB6", "Kemal Shahin", "19", "London", "Student/Male Belly dancer", "8th - Evicted"], ["BB:CH", "Latoya Satnarine", "19", "London", "Dancer", "9th - Evicted"], ["BB9", "Kathreya Kasisopa", "30", "Kent", "Massage Therapist", "6th - Evicted"], ["BB7", "Nikki Grahame", "24", "London", "Model/Dancer", "5th - Evicted"], ["BB7", "Richard Newman", "33", "Northampton", "Waiter", "4th - Evicted"], ["BB14", "Sallie Axl", "26", "Wirral", "Glamour Model", "14th - Evicted"], ["BB7", "Susie Verrico", "43", "Kent", "Model", "8th - Evicted"], ["BB13", "Shievonne Robinson", "28", "London", "Shop Assistant Manager", "12th - Evicted"], ["BB3", "Tim Culley", "23", "Worcester", "Tennis coach", "5th - Evicted"], ["BB8", "Carole Vincent", "53", "London", "Sexual Health Worker", "5th - Evicted"], ["BB12", "Louise Cliffe", "25", "Manchester", "Model/Actress", "4th - Evicted"], ["BB7", "Bonnie Holt", "19", "Leicester", "Care Worker", "20th - Evicted"], ["BB8", "Nicky Maxwell", "27", "Hertfordshire", "Bank Worker", "15th - Evicted"], ["BB7", "Jayne Kitt", "36", "Berkshire", "Recruitment adviser", "12th - Evicted"], ["BB1", "Nichola Holt", "29", "Bolton", "Teacher", "7th - Evicted"], ["BB10", "Karly Ashworth", "21", "Fife", "Unemployed/Model", "15th - Evicted"], ["BB4", "Lisa Jeynes", "35", "South Wales", "Shop Manager", "6th - Evicted"], ["BB11", "Sam (Samuel) Pepper", "21", "Kent", "Graffiti artist", "7th - Evicted"], ["BB11", "Nathan Dunn", "25", "Bradford", "Joiner", "17th - Evicted"], ["BB7", "Grace Adams-Short", "20", "London", "Dance Teacher", "16th - Evicted"], ["BB9", "Rebecca Shiner", "21", "Coventry", "Nursery Nurse", "14th - Evicted"], ["BB1", "Claire Strutton", "25", "Buckinghamshire", "Florist", "5th - Evicted"], ["BB11", "Jo Butler", "41", "Luton", "Makeup artist", "10th - Evicted"], ["BB13", "Arron Lowe", "23", "Manchester", "Model", "13th - Evicted"], ["BB2", "Josh Rafter", "32", "London", "Property manager", "6th - Evicted"], ["BB10", "Beinazir Lasharie", "28", "London", "Receptionist", "22nd - Evicted"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 table dancers were evicted? | 1 | 128 | Answer: |
Table InputTable: [["Round", "Date", "Home/Away", "Opponent team", "Score", "Scorers"], ["24", "March 15, 2009", "Away", "KS Bylis Ballsh", "0β0", ""], ["6", "October 4, 2008", "Away", "KS Bylis Ballsh", "0β0", ""], ["16", "December 21, 2008", "Away", "KS Flamurtari VlorΓ«", "2β0", ""], ["18", "January 31, 2009", "Away", "KS Dinamo Tirana", "2β4", "Migen Memelli Β 8' Β 77', Ansi Agolli Β 58', Daniel Xhafa Β 88'"], ["14", "December 7, 2008", "Away", "KF Partizani Tirana", "2β2", "Jetmir Sefa Β 2', Migen Memelli Β 82'"], ["10", "November 9, 2008", "Away", "KS Elbasani", "1β0", ""], ["25", "March 21, 2009", "Home", "Apolonia Fier", "2β0", "Bledar Devolli Β 32', Devis Mukaj Β 75'"], ["5", "September 27, 2008", "Home", "KS Flamurtari VlorΓ«", "3β1", "Migen Memelli Β 17' Β 57' Β 61'"], ["17", "December 27, 2008", "Home", "KS Bylis Ballsh", "6β2", "Pedro Neves (O.G) Β 2', Migen Memelli Β 4' Β 35' Β 57', Gjergji Muzaka Β 13', Daniel Xhafa Β 32'"], ["7", "October 19, 2008", "Home", "KS Dinamo Tirana", "2β1", "Migen Memelli Β 32', Gjergji Muzaka Β 51'"], ["2", "August 30, 2008", "Away", "KS Teuta DurrΓ«s", "0β1", "Migen Memelli Β 42',"], ["4", "September 20, 2008", "Away", "KS Apolonia Fier", "0β2", "Andi Lila Β 28', Migen Memelli Β 32'"], ["26", "April 5, 2009", "Away", "Flamurtari Vlore", "1β2", "Migen Memelli Β 1' Β 37'"], ["32", "May 16, 2009", "Away", "Dinamo Tirana", "2β3", "Ansi Agolli Β 12', Sabien Lila Β 40', Ergys Sorra Β 73'"], ["8", "October 25, 2008", "Away", "KS Shkumbini Peqin", "0β0", ""], ["19", "February 5, 2009", "Home", "KS Shkumbini Peqin", "2β0", "Andi Lila Β 27', Ansi Agolli Β 70'"], ["28", "April 18, 2009", "Away", "Partizani Tirana", "2β2", "Daniel Xhafa Β 56' Β 87'"], ["11", "November 15, 2008", "Home", "KS Lushnja", "1β0", "Laert Ndoni (O.G) Β 13'"], ["15", "December 13, 2008", "Home", "KS Apolonia Fier", "3β0", "Daniel Xhafa Β 37' Β 48', Andi Lila Β 64'"], ["29", "April 25, 2009", "Home", "KS Teuta Durres", "4β1", "Migen Memelli Β 5' Β 74', Daniel Xhafa Β 41', Ansi Agolli Β 83'"], ["12", "November 23, 2008", "Home", "KS Vllaznia Shkoder", "1β1", "Bledar Devolli Β 79'"], ["27", "April 11, 2009", "Home", "KF Elbasani", "3β0", "Daniel Xhafa Β 51', Devis Mukaj Β 77', Migen Memelli Β 86'"], ["20", "February 15, 2009", "Away", "KS Besa Kavaje", "1β3", "Daniel Xhafa Β 29', Ansi Agolli Β 53', Migen Memelli Β 73'"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:one what date were the most total goals scored in a game? | December 27, 2008 | 128 | Answer: |
Table InputTable: [["Rnd", "Circuit", "GTP Winning Team\\nGTP Winning Drivers", "GTO Winning Team\\nGTO Winning Drivers", "GTU Winning Team\\nGTU Winning Drivers", "Results"], ["1", "Daytona", "#00 Kreepy Krauly Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["6", "Laguna Seca", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#99 All American Racers", "Results"], ["17", "Daytona", "#14 Holbert Racing", "#67 Roush Racing", "#87 Performance Motorsports", "Results"], ["4", "Road Atlanta", "#16 Marty Hinze Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["16", "Watkins Glen", "Dale Whittington\\n Randy Lanier", "Chester Vincentz\\n Jim Mullen", "Clay Young", "Results"], ["11", "Portland", "#56 Blue Thunder Racing", "#51 Corvette", "#76 Malibu Grand Prix", "Results"], ["15", "Michigan", "#56 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["7", "Charlotte", "#56 Blue Thunder Racing", "#4 Stratagraph Inc.", "#99 All American Racers", "Results"], ["14", "Pocono", "#14 Holbert Racing", "#65 English Enterprises", "#87 Performance Motorsports", "Results"], ["2", "Miami", "#04 Group 44", "#47 Dingman Bros. Racing", "#99 All American Racers", "Results"], ["10", "Watkins Glen", "#14 Holbert Racing", "#91 Electrodyne", "#87 Performance Motorsports", "Results"], ["8", "Lime Rock", "#00 Kreepy Krauly Racing", "#38 Mandeville Auto Tech", "#76 Malibu Grand Prix", "Results"], ["16", "Watkins Glen", "#57 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["6", "Laguna Seca", "Randy Lanier", "John Bauer", "Jim Adams", "Results"], ["1", "Daytona", "Sarel van der Merwe\\n Graham Duxbury\\n Tony Martin", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Jim Cook\\n Ira Young\\n Bob Reed", "Results"], ["12", "Sears Point", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#98 All American Racers", "Results"], ["5", "Riverside", "#56 Blue Thunder Racing", "#38 Mandeville Auto Tech", "#87 Performance Motorsports", "Results"], ["13", "Road America", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["9", "Mid-Ohio", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["10", "Watkins Glen", "Al Holbert\\n Jim Adams\\n Derek Bell", "Chester Vincentz\\n Jim Mullen", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["17", "Daytona", "Al Holbert\\n Derek Bell", "Wally Dallenbach, Jr.\\n Willy T. Ribbs", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["13", "Road America", "Al Holbert\\n Derek Bell", "Chester Vincentz\\n Jim Mullen", "Jack Dunham\\n Jeff Kline", "Results"], ["3", "Sebring", "Mauricio DeNarvaez\\n Hans Heyer\\n Stefan Johansson", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed\\n Ira Young", "Results"], ["4", "Road Atlanta", "Don Whittington", "Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed", "Results"], ["3", "Sebring", "#48 DeNarvaez Enterprises", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["7", "Charlotte", "Bill Whittington\\n Randy Lanier", "Billy Hagan\\n Gene Felton", "Chris Cord\\n Jim Adams", "Results"], ["14", "Pocono", "Al Holbert\\n Derek Bell", "Gene Felton", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["8", "Lime Rock", "Sarel van der Merwe", "Roger Mandeville", "Jack Baldwin", "Results"], ["9", "Mid-Ohio", "Al Holbert\\n Derek Bell", "Chester Vincentz\\n Dave White", "Jack Dunham\\n Jeff Kline", "Results"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 there a circuit where there was not more than one gto winning driver? | yes | 128 | Answer: |
Table InputTable: [["Date", "Opponents", "Venue", "Result", "Scorers", "Attendance"], ["9 Sep 1920", "Bristol Rovers", "H", "0β2", "", "8,000"], ["26 Mar 1921", "Queens Park Rangers", "A", "0β2", "", "10,000"], ["5 Mar 1921", "Brighton & Hove Albion", "A", "0β1", "", "8,000"], ["4 Dec 1920", "Watford", "H", "0β2", "", "6,000"], ["26 Feb 1921", "Brighton & Hove Albion", "H", "0β4", "", "8,000"], ["23 Oct 1920", "Portsmouth", "H", "1β0", "Devlin", "9,000"], ["25 Dec 1920", "Southend United", "H", "1β1", "Dobson", "9,000"], ["19 Feb 1921", "Crystal Palace", "A", "0β2", "", "7,000"], ["27 Nov 1920", "Swindon Town", "A", "0β5", "", "7,000"], ["12 Feb 1921", "Crystal Palace", "H", "0β1", "", "12,000"], ["2 Oct 1920", "Exeter City", "H", "2β0", "Wolstenholme 2", "8,000"], ["18 Sep 1920", "Plymouth Argyle", "H", "0β0", "", "8,000"], ["30 Oct 1920", "Portsmouth", "A", "2β0", "Devlin, Dobson", "13,679"], ["21 Oct 1920", "Swindon Town", "H", "0β1", "", "10,000"], ["7 May 1921", "Southampton", "H", "0β0", "", "8,000"], ["2 May 1921", "Southampton", "A", "0β0", "", "6,000"], ["22 Jan 1921", "Norwich City", "A", "0β3", "", "5,000"], ["9 Apr 1921", "Swansea Town", "H", "1β1", "Walker", "6,000"], ["11 Dec 1920", "Watford", "A", "1β5", "Wright", "7,000"], ["5 Feb 1921", "Northampton Town", "A", "2β0", "Groves, Wright", "8,000"], ["23 Apr 1921", "Luton Town", "A", "2β2", "Walker, Devlin", "9,000"], ["27 Dec 1920", "Southend United", "A", "1β2", "Walker", "10,000"], ["25 Sep 1920", "Exeter City", "A", "1β0", "Wolstenholme", "8,000"], ["30 Apr 1921", "Luton Town", "H", "2β0", "Devlin 2", "5,000"], ["19 Mar 1921", "Grimsby Town", "A", "1β1", "Devlin", "9,000"], ["2 Apr 1921", "Queens Park Rangers", "H", "1β3", "Devlin", "7,500"], ["16 Oct 1920", "Millwall", "A", "0β1", "", "20,000"], ["18 Dec 1920", "Brentford", "A", "2β2", "Wright, Thompson", "6,000"], ["13 Jan 1921", "Norwich City", "H", "2β0", "Wright, Cox", "4,000"], ["1 Sep 1920", "Bristol Rovers", "A", "2β3", "Walker, Wolstenholme", "10,000"], ["12 Mar 1921", "Grimsby Town", "H", "2β1", "Devlin, Kelson", "8,000"], ["11 Sep 1920", "Plymouth Argyle", "A", "1β5", "Wolstenholme", "12,000"], ["6 Nov 1920", "Gillingham", "H", "1β0", "Wolstenholme", "7,000"], ["16 Apr 1921", "Swansea Town", "A", "2β1", "Dobson, Wolstenholme", "14,000"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 date of the game with the largest attendance? | 16 Oct 1920 | 128 | Answer: |
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["6", "August 13", "Brainerd", "Jerry Hansen", "Chevrolet Monza", "Bob Tullius", "Jaguar XJS"], ["9", "October 8", "Laguna Seca", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["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"], ["10", "November 5", "Mexico City", "Ludwig Heimrath", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["5", "July 8", "Watkins Glenβ‘", "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"], ["2", "June 4", "Westwood", "Ludwig Heimrath", "Porsche 935", "Nick Engels", "Chevrolet Corvette"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 ta1 vehicle won previous to the jaguar xjs? | Chevrolet Corvette | 128 | Answer: |
Table InputTable: [["Release date", "Album Title", "Record Company", "Song Title", "Certification"], ["December 2007", "H.O.P.E. (Healing Of Pain and Enlightenment)", "Star Records", "\"Count On Me\"", "PARI: Gold"], ["July 25, 2007", "Nagmamahal, Kapamilya: Songs for Global Pinoys", "Star Records", "\"Super Pinoy\"", "PARI: 6X Platinum"], ["March 5, 2011", "Kris Aquino: My Heartβs Journey", "Universal Records", "\"God Bless the Broken Road\"", "PARI: Platinum"], ["April 2009", "OPM Number 1's", "Star Records", "\"Can't Hurry Love\"", "PARI:"], ["January 17, 2013", "Himig Handog P-Pop Love Songs 2013", "Star Records", "\"Kahit Na\"", "PARI:"], ["June 2011", "Bida Best Hits Da Best", "Star Records", "\"Mahal Kita Kasi\", \"Catch Me I'm Falling\", \"You Are The One\" with Sam Milby", "PARI:"], ["November 12, 2011", "Happy Yipee Yehey! Nananana!", "Star Records", "\"Mahalin Ka Ng Totoo\"", "PARI: Gold"], ["January 2011", "OPM Number 1's Vol. 2", "Star Records", "\"All Me (Remix)\"", "PARI:"], ["October 8, 2006", "Hotsilog: The ASAP Hotdog Compilation", "ASAP Music", "\"Annie Batungbakal\"", "PARI: Platinum"], ["June 2010", "60 Taon ng Musika at Soap Opera", "Star Records", "\"Crazy For You\"", "PARI:"], ["February 2011", "I Love You", "Star Records", "\"Catch Me I'm Falling\"", "PARI:"], ["November 18, 2011", "Da Best ang Pasko ng Pilipino", "Star Records", "\"Ganyan ang Pasko\", \"Ngayong Pasko Magniningning ang Pilipino\" (Solo) & with Gary Valenciano", "PARI:"], ["June 24, 2009", "I Move, I Give, I Love", "Star Records", "\"Power of the Dream\", \"Bagong Umaga\" with Erik Santos & Yeng Constantino", "PARI: Gold"], ["November 2010", "Ngayong Pasko Magniningning ang Pilipino: Christmas Songs Compilation", "Star Records", "\"Ganyan ang Pasko\", \"Ngayong Pasko Magniningning ang Pilipino\" (Solo) & with Gary Valenciano", "PARI:"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 titles were released in 2007? | 2 | 128 | Answer: |
Table InputTable: [["Year", "Recipient", "Nationality", "Profession", "Speech"], ["2008", "David Be'eri, Mordechai Eliav, Rabbi Yehuda Maly", "Israel", "", ""], ["1997", "Elie Wiesel", "United States", "Professional writer\\nWinner of the Nobel Peace Prize (1986)", ""], ["2009", "Caroline Glick", "Israel", "Journalist", ""], ["2000", "Sir Martin Gilbert", "United Kingdom", "Historian and writer", ""], ["2005", "William Safire", "United States", "Author, journalist and speechwriter\\n1978 Pulitzer Prize winner", ""], ["2004", "Arthur Cohn", "Switzerland", "Filmmaker and writer", ""], ["1998", "Herman Wouk", "United States", "Professional writer and 1952 Pulitzer Prize winner", ""], ["2007", "Norman Podhoretz", "United States", "Author, columnist", ""], ["2006", "Daniel Pipes", "United States", "Author and historian", ""], ["2003", "Ruth Roskies Wisse", "United States", "Yiddish professor of Harvard University", "[2]"], ["2001", "Cynthia Ozick", "United States", "Professional writer", ""], ["1999", "A.M. Rosenthal", "United States", "Former New York Times editor\\nFormer New York Daily News columnist", ""], ["2010", "Malcolm Hoenlein", "United States", "Executive Vice Chairman of the Conference of Presidents of Major American Jewish Organizations", ""], ["2002", "Charles Krauthammer", "United States", "The Washington Post columnist", "[1]"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 what year did the first person of israel nationality actually win the award? | 2008 | 128 | Answer: |
Table InputTable: [["Contestant", "Original Tribe", "Switched Tribe", "Merged Tribe", "Finish", "Total Votes"], ["Aleksandr Byalko\\n50.the physicist", "Pelicans", "Barracudas", "", "5th Voted Out\\nDay 15", "6"], ["Aleksandr Pashutin\\n60.the actor", "Barracudas", "", "", "3rd Voted Out\\nDay 9", "7"], ["Aleksandr Lykov\\n41.the actor", "Barracudas", "Barracudas", "Crocodiles", "13th Voted Out\\n8th Jury Member\\nDay 37", "6"], ["Kris Kelmi\\n47.the singer", "Barracudas", "", "", "2nd Voted Out\\nDay 6", "1"], ["Ivar Kalnynsh\\n54.the actor", "", "", "Crocodiles", "10th Voted Out\\n5th Jury Member\\nDay 30", "3"], ["Vera Glagoleva\\n46.the actress", "", "", "Crocodiles", "11th Voted Out\\n6th Jury Member\\nDay 33", "4"], ["Yelena Proklova\\n49.the TV presenter", "Pelicans", "Barracudas", "Crocodiles", "8th Voted Out\\n3rd Jury Member\\nDay 24", "4"], ["Larisa Verbitskaya\\n43.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "12th Voted Out\\n7th Jury Member\\nDay 36", "11"], ["Olga Orlova\\n25.the singer", "Barracudas", "Baracudas", "Crocodiles", "Eliminated\\n9th Jury Member\\nDay 38", "10"], ["Viktor Gusev\\n47.the sport commentator", "Pelicans", "Pelicans", "Crocodiles", "7th Voted Out\\n1st Jury Member\\nDay 21", "6"], ["Yelena Kondulaynen\\n44.the actress", "Pelicans", "", "", "1st Voted Out\\nDay 3", "5"], ["Igor' Livanov\\n49.the actor", "Pelicans", "", "", "Eliminated\\nDay 11", "0"], ["Marina Aleksandrova\\n20.the actress", "Barracudas", "Pelicans", "Crocodiles", "9th Voted Out\\n4th Jury Member\\nDay 27", "6"], ["Tatyana Dogileva\\n45.the actress", "Pelicans", "Barracudas", "", "6th Voted Out\\nDay 18", "3"], ["Ivan Demidov\\n39.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "Eliminated\\n2nd Jury Member\\nDay 23", "3"], ["Vladimir Presnyakov, Jr.\\n34.the singer", "Pelicans", "Pelicans", "Crocodiles", "Sole Survivor", "6"], ["Dana Borisova\\n26.the TV presenter", "Pelicans", "Barracudas", "", "4th Voted Out\\nDay 12", "5"], ["Yelena Perova\\n26.the singer", "Pelicans", "Pelicans", "Crocodiles", "Runner-Up", "2"], ["Tat'yana Ovsiyenko\\n36.the singer", "Barracudas", "Pelicans", "", "Eliminated\\nDay 19", "1"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:tell me the number of total votes for the physicist? | 6 | 128 | Answer: |
Table InputTable: [["Week", "Date", "Opponent", "Score", "Result", "Record"], ["10", "Oct 30", "vs. Hamilton Tiger-Cats", "30β9", "Loss", "1β11"], ["8", "Oct 16", "vs. Toronto Argonauts", "27β11", "Loss", "1β9"], ["7", "Oct 9", "vs. Montreal Alouettes", "25β11", "Loss", "1β7"], ["2", "Sept 6", "vs. Montreal Alouettes", "20β11", "Loss", "0β3"], ["5", "Sept 25", "vs. Hamilton Tiger-Cats", "38β12", "Loss", "1β5"], ["4", "Sept 18", "vs. Toronto Argonauts", "34β6", "Loss", "1β4"], ["12", "Nov 13", "vs. Montreal Alouettes", "14β12", "Win", "2β12"], ["1", "Aug 28", "at Toronto Argonauts", "13β6", "Loss", "0β1"], ["2", "Sept 4", "at Montreal Alouettes", "21β2", "Loss", "0β2"], ["7", "Oct 11", "at Montreal Alouettes", "24β6", "Loss", "1β8"], ["6", "Oct 2", "at Hamilton Tiger-Cats", "45β0", "Loss", "1β6"], ["11", "Nov 6", "at Toronto Argonauts", "18β12", "Loss", "1β12"], ["9", "Oct 23", "at Hamilton Tiger-Cats", "25β17", "Loss", "1β10"], ["3", "Sept 11", "at Toronto Argonauts", "12β5", "Win", "1β3"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 did the rough riders lose to by the most points? | Hamilton Tiger-Cats | 128 | Answer: |
Table InputTable: [["Callsign", "Area served", "Frequency", "Band", "Fate", "Freq currently", "Purpose"], ["7QT", "Queenstown", "0837", "AM", "Changed call to 7XS in 1988", "7XS", "Commercial"], ["7UV", "Ulverstone", "", "AM", "Moved to Devonport and changed call to 7AD in 1940", "7AD", "Commercial"], ["7ZL", "Hobart", "0603", "AM", "Changed call to 7RN in 1991", "7RN", "National"], ["7CAE", "Hobart", "092.1", "FM", "Changed call to 7THE ca. 1980", "7THE", "Community"], ["7NT", "Launceston", "0711", "AM", "Moved to FM in 2006, retained call", "silent", "National"], ["7QN", "Queenstown", "0630", "AM", "Moved to FM in 1991, retained call", "7RN", "National"], ["7DY", "Derby", "", "AM", "Moved to Scottsdale and changed call to 7SD in 1954", "7SD", "Commercial"], ["7EX", "Launceston", "1008", "AM", "Moved to FM in 2008 as 7EXX", "silent", "Commercial"], ["7LA", "Launceston", "1098", "AM", "Moved to FM in 2008 as 7LAA", "silent", "Commercial"], ["7HT", "Hobart", "1080", "AM", "Moved to FM in 1998 as 7XXX", "7TAB (HPON)", "Commercial"], ["7HO", "Hobart", "0864", "AM", "Moved to FM in 1990 as 7HHO", "7RPH", "Commercial"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 defunct callsigns are there? | 11 | 128 | Answer: |
Table InputTable: [["Naturalisations by origin", "2000", "2005", "2009", "% Total 2009"], ["South Asia", "4 246", "4 436", "3 660", "2.7"], ["South-East Asia", "7 265", "4 069", "2 475", "1.8"], ["Other Asia", "15 291", "16 501", "11 737", "8.6"], ["Asia", "27 941", "26 286", "19 494", "14.4"], ["CIS (Asia)", "181", "573", "250", "0.2"], ["East Asia", "1 139", "1 280", "1 622", "1.2"], ["South and Central America", "4 620", "5 498", "5 930", "4.4"], ["Africa", "84 182", "98 453", "85 144", "62.7"], ["Sub-Saharan Africa", "10 622", "15 624", "22 214", "16.4"], ["Europe (not including CIS )", "22 085", "18 072", "14 753", "10.9"], ["Other Africa", "5 375", "7 605", "6 906", "5.1"], ["Maghreb", "68 185", "75 224", "56 024", "41.2"], ["Oceania", "87", "127", "108", "0.1"], ["Total", "150 026", "154 643", "135 842", "100"], ["CIS (Europe)", "1 000", "1 535", "4 454", "3.3"], ["America", "5 668", "6 352", "6 677", "4.9"], ["North America", "1 048", "854", "747", "0.5"], ["Others", "8 882", "3 245", "4 962", "3.7"], ["CIS", "1 181", "2 108", "4 704", "3.5"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:does any area have the same percentage listed as south asia? | no | 128 | Answer: |
Table InputTable: [["Week", "Date", "Result", "Record", "Opponent", "Points For", "Points Against", "First Downs", "Attendance"], ["9", "November 14", "Loss", "8β1", "St. Louis Cardinals", "17", "24", "16", "64,038"], ["10", "November 20", "Loss", "8β2", "at Pittsburgh Steelers", "13", "28", "20", "49,761"], ["3", "October 2", "Win", "3β0", "Tampa Bay Buccaneers", "23", "7", "23", "55,316"], ["1", "September 18", "Win", "1β0", "at Minnesota Vikings", "16", "10", "16", "47,678"], ["13", "December 12", "Win", "11β2", "at San Francisco 49ers", "42", "35", "24", "55,851"], ["2", "September 25", "Win", "2β0", "New York Giants", "41", "21", "25", "64,215"], ["14", "December 18", "Win", "12β2", "Denver Broncos", "14", "6", "15", "63,752"], ["7", "October 30", "Win", "7β0", "Detroit Lions", "37", "0", "20", "63,160"], ["8", "November 6", "Win", "8β0", "at New York Giants", "24", "10", "13", "74,532"], ["12", "December 4", "Win", "10β2", "Philadelphia Eagles", "24", "14", "19", "60,289"], ["11", "November 27", "Win", "9β2", "at Washington Redskins", "14", "7", "19", "55,031"], ["5", "October 16", "Win", "5β0", "Washington Redskins", "34", "16", "23", "62,115"], ["6", "October 23", "Win", "6β0", "at Philadelphia Eagles", "16", "10", "17", "65,507"], ["4", "October 9", "Win", "4β0", "at St. Louis Cardinals", "30", "24", "22", "50,129"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 first loss of the season came against the... | St. Louis Cardinals | 128 | Answer: |
Table InputTable: [["Season", "Club", "Competition", "Games", "Goals"], ["2005/06", "KSV Roeselare", "Jupiler League", "26", "0"], ["2006/07", "KSV Roeselare", "Jupiler League", "29", "1"], ["2003/04", "RAEC Mons", "Jupiler League", "23", "0"], ["2004/05", "KSV Roeselare", "Belgian Second Division", "29", "1"], ["2002/03", "RAEC Mons", "Jupiler League", "19", "0"], ["2008/09", "Excelsior Mouscron", "Jupiler League", "31", "1"], ["2007/08", "KSV Roeselare", "Jupiler League", "25", "0"], ["2010/11", "Kortrijk", "Jupiler League", "0", "0"], ["2009/10", "Excelsior Mouscron", "Jupiler League", "14", "1"], ["2009/10", "GyΕri ETO FC", "Soproni Liga", "1", "0"], ["", "", "Totaal", "278", "4"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 games were held before 2005/06? | 71 | 128 | Answer: |
Table InputTable: [["#", "Name", "Took office", "Left office", "Party", "Governor", "Notes"], ["32", "Edgar D. Bush", "January 14, 1929", "January 9, 1933", "Republican", "Harry G. Leslie", ""], ["29", "Edgar D. Bush", "January 8, 1917", "January 10, 1921", "Republican", "James P. Goodrich", ""], ["2", "Ratliff Boon", "December 8, 1819", "September 12, 1822", "Democratic-Republican", "Jonathan Jennings", ""], ["7", "David Hillis", "December 6, 1837", "December 9, 1840", "Whig", "David Wallace", ""], ["17", "Leonidas Sexton", "January 13, 1873", "January 13, 1877", "Republican", "Thomas A. Hendricks", ""], ["21", "Robert S. Robertson", "January 10, 1887", "January 13, 1889", "Republican", "Isaac P. Gray", ""], ["19", "Thomas Hanna", "January 10, 1881", "November 12, 1885", "Republican", "Albert G. Porter", ""], ["10", "Paris C. Dunning", "December 9, 1846", "December 26, 1848", "Democrat", "James Whitcomb", ""], ["25", "Newton W. Gilbert", "January 14, 1901", "January 9, 1905", "Republican", "Winfield T. Durbin", ""], ["1", "Christopher Harrison", "November 7, 1816", "December 17, 1818", "Democratic-Republican", "Jonathan Jennings", ""], ["37", "Rue J. Alexander", "April 14, 1948", "January 2, 1949", "Republican", "Henry F. Schricker", ""], ["16", "William Cumback", "January 11, 1869", "January 13, 1873", "Republican", "Conrad Baker", ""], ["46", "Frank O'Bannon", "January 9, 1989", "January 13, 1997", "Democrat", "Evan Bayh", ""], ["11", "James Henry Lane", "December 5, 1849", "January 10, 1853", "Democrat", "Joseph A. Wright", ""], ["36", "Richard T. James", "January 8, 1945", "January 10, 1948", "Republican", "Ralph F. Gates", ""], ["35", "Charles M. Dawson", "January 13, 1941", "January 8, 1945", "Democrat", "Henry F. Schricker", ""], ["9", "Jesse D. Bright", "December 6, 1843", "December 6, 1845", "Democrat", "James Whitcomb", ""], ["45", "John Mutz", "January 12, 1981", "January 9, 1989", "Republican", "Robert D. Orr", ""], ["5", "Milton Stapp", "December 3, 1828", "December 7, 1831", "Independent", "James B. Ray", ""], ["44", "Robert D. Orr", "January 8, 1973", "January 12, 1981", "Republican", "Otis R. Bowen", ""], ["50", "Sue Ellspermann", "January 14, 2013", "Incumbent", "Republican", "Mike Pence", ""], ["31", "F. Harold Van Orman", "January 12, 1925", "January 14, 1929", "Republican", "Edward L. Jackson", ""], ["12", "Ashbel P. Willard", "January 10, 1853", "January 12, 1857", "Democrat", "Joseph A. Wright", ""], ["28", "William P. O'Neill", "January 13, 1913", "January 8, 1917", "Democrat", "Samuel M. Ralston", ""], ["43", "Richard E. Folz", "January 13, 1969", "January 8, 1973", "Republican", "Edgar Whitcomb", ""], ["26", "Hugh Thomas Miller", "January 9, 1905", "January 11, 1909", "Republican", "Frank Hanly", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 in office for only two days? | Oliver P. Morton | 128 | Answer: |
Table InputTable: [["Name", "Country", "Town", "Height\\nmetres / ft", "Structural type", "Held record", "Notes"], ["Burj Khalifa", "United Arab Emirates", "Dubai", "829.8 / 2,722", "Skyscraper", "2007βpresent", "Topped-out on 17 January 2009"], ["Eiffel Tower", "France", "Paris", "300.6 / 986", "Tower", "1889β1930", "Currently stands at a height of 324 metres (1,063Β ft)."], ["CN Tower", "Canada", "Toronto", "553 / 1,815", "Tower", "1976β2007", ""], ["Lincoln Cathedral", "England", "Lincoln", "159.7 / 524", "Church", "1311β1549", "Spire collapsed in 1549; today, stands at a height of 83 metres (272Β ft)."], ["St. Mary's Church", "Germany", "Stralsund", "151 / 500", "Church", "1549β1647", "Spire destroyed by lightning in 1647; today stands at a height of 104 metres (341Β ft)."], ["Empire State Building", "United States", "New York City", "448 / 1,472", "Skyscraper", "1931β1967", ""], ["Ostankino Tower", "Russia", "Moscow", "540 / 1,772", "Tower", "1967β1976", ""], ["Great Pyramid of Giza", "Egypt", "Giza", "146 / 480", "Mausoleum", "2570 BCβ1311", "Due to erosion today it stands at the height of 138.8 metres (455Β ft)."], ["Chrysler Building", "United States", "New York City", "319 / 1,046", "Skyscraper", "1930β1931", ""], ["Strasbourg Cathedral", "Germany and/or France (today France)", "Strasbourg", "142 / 470", "Church", "1647β1874", ""], ["Notre-Dame Cathedral", "France", "Rouen", "151 / 500", "Church", "1876β1880", ""], ["Washington Monument", "United States", "Washington, D.C.", "169.3 / 555", "Monument", "1884β1889", ""], ["Cologne Cathedral", "Germany", "Cologne", "157.4 / 516", "Church", "1880β1884", ""], ["St Nikolai", "Germany", "Hamburg", "147.3 / 483", "Church", "1874β1876", "Due to aerial bombing in World War II the nave was demolished; only the spire remains."]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 current tallest building in the world a tower or skyscraper? | Skyscraper | 128 | Answer: |
Table InputTable: [["Pos", "Name", "Team", "Laps", "Time/Retired", "Grid", "Points"], ["3", "Bruno Junqueira", "Dale Coyne Racing", "69", "+8.419", "11", "26"], ["7", "SΓ©bastien Bourdais", "N/H/L Racing", "69", "+22.955", "1", "18"], ["12", "Katherine Legge", "Dale Coyne Racing", "69", "+44.860", "14", "9"], ["16", "Alex Figge", "Pacific Coast Motorsports", "68", "+ 1 Lap", "16", "5"], ["10", "Ryan Dalziel", "Pacific Coast Motorsports", "69", "+29.554", "15", "11"], ["9", "Graham Rahal", "N/H/L Racing", "69", "+23.949", "6", "13"], ["2", "Jan Heylen", "Conquest Racing", "69", "+7.227", "7", "27"], ["5", "Neel Jani", "PKV Racing", "69", "+22.262", "4", "21"], ["4", "Tristan Gommendy", "PKV Racing", "69", "+9.037", "3", "23"], ["8", "Oriol ServiΓ ", "Forsythe Racing", "69", "+23.406", "13", "15"], ["17", "Paul Tracy", "Forsythe Racing", "14", "Mechanical", "17", "4"], ["15", "Alex Tagliani", "Rocketsports", "68", "+ 1 Lap", "12", "6"], ["11", "Dan Clarke", "Minardi Team USA", "69", "+38.903", "10", "11"], ["13", "Robert Doornbos", "Minardi Team USA", "69", "+1:00.638", "9", "8"], ["6", "Simon Pagenaud", "Team Australia", "69", "+22.698", "5", "19"], ["1", "Justin Wilson", "RuSPORT", "69", "1:46:02.236", "2", "32"], ["14", "Will Power", "Team Australia", "69", "+1:01.204", "8", "7"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 participated in the race? | 17 | 128 | Answer: |
Table InputTable: [["Week", "Date", "TV Time", "Opponent", "Result", "Attendance"], ["15", "December 13, 1998", "FOX 11:00 am MT", "at Philadelphia Eagles", "W 20β17", "62,176"], ["13", "November 29, 1998", "FOX 11:00 am MT", "at Kansas City Chiefs", "L 34β24", "69,613"], ["16", "December 20, 1998", "FOX 2:05 pm MT", "New Orleans Saints", "W 19β17", "51,617"], ["14", "December 6, 1998", "FOX 2:15 pm MT", "New York Giants", "L 23β19", "46,128"], ["17", "December 27, 1998", "CBS 2:05 pm MT", "San Diego Chargers", "W 16β13", "71,670"], ["2", "September 13, 1998", "FOX 1:15 pm MT", "at Seattle Seahawks", "L 33β14", "57,678"], ["12", "November 22, 1998", "FOX 11:00 am MT", "at Washington Redskins", "W 45β42", "63,435"], ["10", "November 8, 1998", "FOX 2:15 pm MT", "Washington Redskins", "W 29β27", "45,950"], ["4", "September 27, 1998", "FOX 10:00 am MT", "at St. Louis Rams", "W 20β17", "55,832"], ["3", "September 20, 1998", "ESPN 5:15 pm MT", "Philadelphia Eagles", "W 17β3", "39,782"], ["6", "October 11, 1998", "FOX 1:05 pm MT", "Chicago Bears", "W 20β7", "50,495"], ["11", "November 15, 1998", "FOX 2:15 pm MT", "Dallas Cowboys", "L 35β28", "71,670"], ["1", "September 6, 1998", "FOX 1:05 pm MT", "at Dallas Cowboys", "L 38β10", "63,602"], ["9", "November 1, 1998", "FOX 11:00 am MT", "at Detroit Lions", "W 17β15", "66,087"], ["7", "October 18, 1998", "FOX 10:00 am MT", "at New York Giants", "L 34β7", "70,456"], ["5", "October 4, 1998", "CBS 1:05 pm MT", "Oakland Raiders", "L 23β20", "53,240"], ["8", "Bye", "Bye", "Bye", "Bye", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 attended the december 13, 1998 game? | 62,176 | 128 | Answer: |
Table InputTable: [["Year", "Chassis", "Engine", "Start", "Finish", "Team"], ["2006", "Dallara", "Honda", "2", "25", "Team Penske"], ["2009", "Dallara", "Honda", "1", "1", "Team Penske"], ["2008", "Dallara", "Honda", "4", "4", "Team Penske"], ["2007", "Dallara", "Honda", "1", "3", "Team Penske"], ["2011", "Dallara", "Honda", "16", "17", "Team Penske"], ["2010", "Dallara", "Honda", "1", "9", "Team Penske"], ["2002", "Dallara", "Chevrolet", "13", "1", "Team Penske"], ["2012", "Dallara", "Chevrolet", "6", "10", "Team Penske"], ["2013", "Dallara", "Chevrolet", "8", "6", "Team Penske"], ["2003", "Dallara", "Toyota", "1", "2", "Team Penske"], ["2001", "Dallara", "Oldsmobile", "11", "1", "Team Penske"], ["2004", "Dallara", "Toyota", "8", "9", "Team Penske"], ["2005", "Dallara", "Toyota", "5", "9", "Team Penske"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 was castroneves racing in the indianapolis 500? | 13 | 128 | Answer: |
Table InputTable: [["Year", "Single", "Peak chart\\npositions\\nUS Country", "Peak chart\\npositions\\nCAN Country", "Album"], ["1984", "\"I'm a Country Song\"", "72", "β", "singles only"], ["1979", "\"You Are My Rainbow\"", "36", "β", "singles only"], ["1979", "\"Darlin'\"", "18", "36", "singles only"], ["1976", "\"Mahogany Bridge\"", "84", "β", "singles only"], ["1979", "\"You're Amazing\"", "39", "β", "singles only"], ["1977", "\"I'm Gonna Love You Right Out of This World\"", "21", "38", "singles only"], ["1981", "\"Houston Blue\"", "88", "β", "singles only"], ["1974", "\"Loving You Has Changed My Life\"", "9", "21", "Hey There Girl"], ["1969", "\"Dearly Beloved\"", "59", "β", "single only"], ["1983", "\"You've Still Got Me\"", "71", "β", "singles only"], ["1974", "\"I Just Can't Help Believin'\"", "59", "β", "Hey There Girl"], ["1972", "\"All Heaven Breaks Loose\"", "35", "β", "single only"], ["1971", "\"Ruby, You're Warm\"", "21", "16", "single only"], ["1976", "\"Whispers and Grins\"", "66", "β", "singles only"], ["1983", "\"Hold Me\"", "67", "β", "singles only"], ["1982", "\"Crown Prince of the Barroom\"", "92", "β", "singles only"], ["1977", "\"Do You Hear My Heart Beat\"", "47", "β", "Lovingly"], ["1977", "\"I Love What My Woman Does to Me\"", "49", "33", "singles only"], ["1977", "\"You and Me Alone\"", "24", "β", "Lovingly"], ["1978", "\"I'll Be There (When You Get Lonely)\"", "22", "β", "Lovingly"], ["1974", "\"Hey There Girl\"", "21", "42", "Hey There Girl"], ["1968", "\"I'd Be Your Fool Again\"", "69", "β", "A World Called You"], ["1969", "\"A World Called You\"", "23", "β", "A World Called You"], ["1973", "\"It'll Be Her\"", "22", "16", "Just Thank Me"], ["1977", "\"The Lady and the Baby\"", "76", "β", "singles only"], ["1970", "\"So Much in Love with You\"", "46", "β", "A World Called You"], ["1968", "\"I'm in Love with My Wife\"", "38", "β", "A World Called You"], ["1967", "\"Forbidden Fruit\"", "β", "β", "A World Called You"], ["1973", "\"Just Thank Me\"", "17", "18", "Just Thank Me"], ["1968", "\"You Touched My Heart\"", "37", "β", "A World Called You"], ["1971", "\"She Don't Make Me Cry\"", "19", "9", "She Don't Make Me Cry"], ["1978", "\"Let's Try to Remember\"", "32", "β", "Lovingly"], ["1983", "\"The Devil Is a Woman\"", "87", "β", "singles only"], ["1978", "\"When a Woman Cries\"", "31", "β", "singles only"], ["1972", "\"Need You\"", "9", "9", "Need You"], ["1975", "\"It Takes a Whole Lot of Livin' in a House\"", "60", "β", "Whole Lotta Livin' in a House"], ["1970", "\"I Wake Up in Heaven\"", "26", "β", "She Don't Make Me Cry"], ["1972", "\"Goodbye\"", "38", "β", "Need You"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 he have a single make it onto the can country charts in 1979, yes or no? | Yes | 128 | Answer: |
Table InputTable: [["School", "2007", "2008", "2009", "2010", "2011"], ["James A. Garfield High School", "553", "597", "593", "632", "705"], ["Woodrow Wilson High School", "582", "585", "600", "615", "636"], ["Santee Education Complex", "", "502", "521", "552", "565"], ["Francisco Bravo Medical Magnet High School", "807", "818", "815", "820", "832"], ["Abraham Lincoln High School", "594", "609", "588", "616", "643"], ["Thomas Jefferson High School", "457", "516", "514", "546", "546"], ["Oscar De La Hoya Animo Charter High School", "662", "726", "709", "710", "744"], ["Marc and Eva Stern Math and Science School", "718", "792", "788", "788", "809"], ["Theodore Roosevelt High School", "557", "551", "576", "608", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 schools scored above 600 in 2010? | 7 | 128 | Answer: |
Table InputTable: [["Date", "Location", "Air/Ground", "Number", "Type", "Status"], ["27 May 1944", "North of Strasbourg, France", "Air", "1", "Me-109", "Damaged"], ["27 November 1944", "South of Magdeburg, Germany", "Air", "4", "FW-190", "Destroyed"], ["18 August 1944", "20 miles northeast of Paris, France", "Air", "0.5", "Me-109", "Destroyed"], ["13 April 1944", "West of Mannheim, Germany", "Air", "1", "FW-190", "Destroyed"], ["24 April 1944", "South of Munich, Germany", "Air", "3", "Me-110", "Destroyed"], ["16 March 1944", "20 miles south of Stuttgart, Germany", "Air", "1", "Me-110", "Destroyed"], ["8 March 1944", "Near Steinhuder Meer (Lake), Germany", "Air", "1", "Me-109", "Destroyed"], ["13 September 1944", "South of Nordhausen, Germany", "Air", "2.5", "Me-109", "Destroyed"], ["25 January 1952", "Korea", "Air", "1", "Mig-15", "Damaged"], ["6 October 1944", "20 miles northwest of Berlin, Germany", "Air", "2", "Me-109", "Destroyed"], ["11 April 1944", "20 miles northeast of Magdeburg, Germany", "Air", "0.5", "Me-109", "Destroyed"], ["14 January 1945", "20 miles northwest of Berlin, Germany", "Air", "1", "Me-109", "Destroyed"], ["6 October 1944", "20 miles northwest of Berlin, Germany", "Air", "1", "Me-109", "Damaged"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 aircraft did france lose? | 2 | 128 | Answer: |
Table InputTable: [["Week", "Date", "Opponent", "Result", "Attendance"], ["1", "September 13, 1987", "San Diego Chargers", "W 20β13", "56,940"], ["9", "November 15, 1987", "New York Jets", "L 16β9", "40,718"], ["8", "November 8, 1987", "Pittsburgh Steelers", "L 17β16", "45,249"], ["7", "November 1, 1987", "at Chicago Bears", "L 31β28", "63,498"], ["15", "December 27, 1987", "Seattle Seahawks", "W 41β20", "20,370"], ["2", "September 20, 1987", "at Seattle Seahawks", "L 43β14", "61,667"], ["6", "October 25, 1987", "at San Diego Chargers", "L 42β21", "47,972"], ["β", "September 27, 1987", "Minnesota Vikings", "canceled", ""], ["13", "December 13, 1987", "Los Angeles Raiders", "W 16β10", "63,834"], ["11", "November 26, 1987", "at Detroit Lions", "W 27β20", "43,820"], ["5", "October 18, 1987", "Denver Broncos", "L 26β17", "20,296"], ["14", "December 19, 1987", "at Denver Broncos", "L 20β17", "75,053"], ["10", "November 22, 1987", "Green Bay Packers", "L 23β3", "34,611"], ["12", "December 6, 1987", "at Cincinnati Bengals", "L 30β27", "46,489"], ["3", "October 4, 1987", "at Los Angeles Raiders", "L 35β17", "10,708"], ["4", "October 11, 1987", "at Miami Dolphins", "L 42β0", "25,867"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 largest difference in attendance? | 64,345 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["5", "Australia", "26", "38", "36", "100"], ["8", "Germany", "19", "28", "31", "78"], ["4", "United States", "27", "22", "39", "88"], ["1", "China", "63", "46", "32", "141"], ["6", "Ukraine", "24", "12", "19", "55"], ["10", "Japan", "17", "16", "20", "53"], ["3", "Canada", "28", "19", "25", "72"], ["2", "Great Britain", "35", "30", "29", "94"], ["7", "Spain", "20", "27", "24", "71"], ["9", "France", "18", "26", "30", "74"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 the most gold medals in the 2004 summer paralympics? | China | 128 | Answer: |
Table InputTable: [["Season", "Date", "Location", "Discipline", "Place"], ["1994", "16 Mar 1994", "Vail, CO, USA", "Downhill", "3rd"], ["1994", "13 Mar 1994", "Whistler, BC, Canada", "Super G", "1st"], ["1994", "12 Mar 1994", "Whistler, BC, Canada", "Downhill", "3rd"], ["1993", "27 Feb 1993", "Whistler, BC, Canada", "Downhill", "2nd"], ["1994", "29 Dec 1993", "Bormio, Italy", "Downhill", "3rd"], ["1995", "11 Dec 1994", "Tignes, France", "Super G", "2nd"], ["1994", "12 Dec 1993", "Val-d'Isère, France", "Super G", "3rd"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:at what location did tommy moe place first? | Whistler, BC, Canada | 128 | Answer: |
Table InputTable: [["No.", "Date/time", "Aircraft", "Foe", "Result", "Location", "Notes"], ["1", "4 December 1916 @ 1100 hours", "Nieuport serial number 3958", "Albatros D.I", "Driven down out of control", "Northeast of Bapaume, France", "Victory shared with another pilot"], ["5", "11 May 1917 @ 1950 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Set afire in midair; destroyed", "Douai, France", ""], ["6", "23 May 1917 @ 1800 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Douai, France", ""], ["2", "24 April 1917 @ 0840 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Sailly, France", ""], ["4", "11 May 1917 @ 1950 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Douai, France", ""], ["3", "2 May 1917 @ 0945 hours", "Sopwith Triplane s/n N5460", "German two-seater aircraft", "Driven down out of control", "Douai, France", ""], ["8", "28 July 1917 @ 1735 hours", "Sopwith Triplane s/n N5462", "German two-seater aircraft", "Driven down out of control", "Middelkerke, Belgium", "Victory shared with Francis Mellersh"], ["7", "24 July 1917 @ 0635 hours", "Sopwith Triplane s/n N5462", "German two-seater aircraft", "Driven down out of control", "Leffinghe", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 was the longest flight located in france. | 1950 hours | 128 | Answer: |
Table InputTable: [["isn", "name", "arrival\\ndate", "departure\\ndate", "notes"], ["209", "Almasm Rabilavich Sharipov", "2002-01-21", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nGranted asylum by the Netherlands."], ["203", "Ravil Shafeyavich Gumarov", "2002-01-21", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nAlleged to have played a role in a 2005 bombing.\\nDefense Intelligence Agency classifies him as a former detainee who \"returned to terrorism\"."], ["492", "Aiat Nasimovich Vahitov", "2002-06-14", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men."], ["211", "Ruslan Anatoloivich Odijev", "2002-06-14", "2004-02-27", "Reported to have been repatriated on 24 February 2004, as \"Ruslan Anatolovich Odijev\", with six other Russian men.\\nCharged with a role in bombing a gas pipeline in 2005.\\nShot by police in 2007.\\nHuman Rights advocates argue he was falsely accused.\\nDefense Intelligence Agency classifies him as a former detainee who \"returned to terrorism\"."], ["82", "Rasul Kudayev", "", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nAlso called \"Abdullah D. Kafkas\"."], ["674", "Timur Ravilich Ishmurat", "2002-06-14", "2004-02-27", "Repatriated to Russia.\\nReported to have been repatriated on 24 February 2004, as \"Timur Ravilich Ismurat\", with six other Russian men.\\nAlleged to have played a role in a 2005 bombing."], ["573", "Rustam Akhmyarov", "2002-05-01", "2004-02-27", "Reported to have been repatriated on 24 February 2004 with six other Russian men."], ["702", "Ravil Mingazov", "2002-10-28", "", ""], ["672", "Zakirjan Asam", "2002-06-08", "2006-11-17", "NLEC"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 russian detainees in guantanamo are listed in the chart? | 9 | 128 | Answer: |
Table InputTable: [["Tour", "Official title", "Venue", "City", "Date\\nStart", "Date\\nFinish", "Prize money\\nUSD", "Report"], ["13", "Super Series Finals", "Cancelled", "Cancelled", "Cancelled", "Cancelled", "500,000", "Report"], ["10", "French Super Series", "Stade Pierre de Coubertin", "Paris", "October 30", "November 4", "200,000", "Report"], ["11", "China Open Super Series", "Tianhe Gymnasium", "Guangzhou", "November 20", "November 25", "250,000", "Report"], ["8", "Japan Super Series", "Tokyo Metropolitan Gymnasium", "Tokyo", "September 11", "September 16", "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"], ["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"], ["2", "Korea Open Super Series", "Seoul National University Gymnasium", "Seoul", "January 23", "January 28", "300,000", "Report"], ["1", "Malaysia Super Series", "Stadium Badminton Kuala Lumpur", "Kuala Lumpur", "January 16", "January 21", "200,000", "Report"], ["3", "All England Super Series", "National Indoor Arena", "Birmingham", "March 6", "March 11", "200,000", "Report"], ["5", "Singapore Super Series", "Singapore Indoor Stadium", "Singapore", "May 1", "May 6", "200,000", "Report"], ["6", "Indonesia Super Series", "Bung Karno Stadium", "Jakarta", "May 7", "May 13", "250,000", "Report"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 super series took place after november 15th? | 2 | 128 | Answer: |
Table InputTable: [["Pos", "Team", "Played", "Won", "Draw", "Lost", "Goals For", "Goals Against", "Goal Difference", "Points", "Notes"], ["10", "Leiftur", "18", "3", "7", "8", "24", "39", "-15", "16", "Relegated"], ["2", "Fylkir", "18", "10", "5", "3", "39", "16", "+23", "35", "UEFA Cup"], ["7", "BreiΓ°ablik", "18", "5", "3", "10", "29", "35", "-6", "18", ""], ["8", "Fram", "18", "4", "5", "9", "22", "33", "-11", "17", ""], ["3", "GrindavΓk", "18", "8", "6", "4", "25", "18", "+7", "30", "UEFA Cup"], ["1", "KR", "18", "11", "4", "3", "27", "14", "+13", "37", "UEFA Champions League"], ["4", "ΓBV", "18", "8", "5", "5", "29", "17", "+12", "29", "Inter-Toto Cup"], ["6", "KeflavΓk", "18", "4", "7", "7", "21", "35", "-14", "19", ""], ["9", "Stjarnan", "18", "4", "5", "9", "18", "31", "-13", "17", "Relegated"], ["5", "ΓA", "18", "7", "5", "6", "21", "17", "+4", "26", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:fram had how many more points than leiftur? | 1 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2007", "Universiade", "Bangkok, Thailand", "1st", "400 m", ""], ["2006", "Asian Games", "Doha, Qatar", "1st", "400 m", ""], ["2006", "World Cup", "Athens, Greece", "7th", "400 m", ""], ["2001", "World Youth Championships", "Debrecen, Hungary", "4th", "400 m", ""], ["2006", "Asian Games", "Doha, Qatar", "2nd", "4x400 m relay", ""], ["2002", "Asian Games", "Busan, South Korea", "2nd", "4x400 m relay", ""], ["2011", "Universiade", "Shenzhen, China", "β", "400 m", "DQ"], ["2005", "Asian Championships", "Incheon, South Korea", "2nd", "4x400 m relay", ""], ["2005", "Universiade", "Izmir, Turkey", "6th", "4x400 m relay", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 she do same as 2007 | 2006 | 128 | Answer: |
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["10", "8", "Tim Schenken", "Brabham-Ford", "76", "+ 4 Laps", "18", ""], ["8", "27", "Henri Pescarolo", "March-Ford", "77", "+ 3 Laps", "13", ""], ["Ret", "7", "Graham Hill", "Brabham-Ford", "1", "Accident", "9", ""], ["5", "1", "Emerson Fittipaldi", "Lotus-Ford", "79", "+ 1 Lap", "17", "2"], ["Ret", "10", "Peter Gethin", "McLaren-Ford", "22", "Accident", "14", ""], ["4", "9", "Denny Hulme", "McLaren-Ford", "80", "+ 1:06.7", "8", "3"], ["7", "22", "John Surtees", "Surtees-Ford", "79", "+ 1 Lap", "10", ""], ["DNQ", "6", "Mario Andretti", "Ferrari", "", "", "", ""], ["6", "24", "Rolf Stommelen", "Surtees-Ford", "79", "+ 1 Lap", "16", "1"], ["9", "15", "Pedro RodrΓguez", "BRM", "76", "+ 4 Laps", "5", ""], ["Ret", "2", "Reine Wisell", "Lotus-Ford", "21", "Wheel bearing", "12", ""], ["1", "11", "Jackie Stewart", "Tyrrell-Ford", "80", "1:52:21.3", "1", "9"], ["Ret", "5", "Clay Regazzoni", "Ferrari", "24", "Accident", "11", ""], ["DNQ", "19", "Nanni Galli*", "March-Alfa-Romeo", "", "", "", ""], ["Ret", "12", "FranΓ§ois Cevert", "Tyrrell-Ford", "5", "Accident", "15", ""], ["3", "4", "Jacky Ickx", "Ferrari", "80", "+ 53.3", "2", "4"], ["2", "17", "Ronnie Peterson", "March-Ford", "80", "+ 25.6", "6", "6"], ["DNQ", "18", "Alex Soler-Roig", "March-Ford", "", "", "", ""], ["Ret", "20", "Chris Amon", "Matra", "45", "Differential", "4", ""], ["Ret", "21", "Jean-Pierre Beltoise", "Matra", "47", "Differential", "7", ""], ["Ret", "14", "Jo Siffert", "BRM", "58", "Oil Pipe", "3", ""], ["DNQ", "28", "Skip Barber", "March-Ford", "", "", "", ""], ["DNQ", "16", "Howden Ganley", "BRM", "", "", "", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 number of drivers who retired after this race? | 8 | 128 | Answer: |
Table InputTable: [["Name", "League", "FA Cup", "League Cup", "JP Trophy", "Total"], ["Danny Coles", "3", "0", "0", "0", "3"], ["Liam Sercombe", "1", "0", "0", "0", "1"], ["OWN GOALS", "0", "0", "0", "0", "0"], ["Jamie Cureton", "20", "0", "0", "0", "20"], ["Pat Baldwin", "1", "0", "0", "0", "1"], ["Alan Gow", "4", "0", "0", "0", "4"], ["Scot Bennett", "5", "0", "0", "0", "5"], ["Guillem Bauza", "2", "0", "0", "0", "2"], ["Jimmy Keohane", "3", "0", "0", "0", "3"], ["John O'Flynn", "11", "0", "1", "0", "12"], ["Total", "0", "0", "0", "0", "0"], ["Jake Gosling", "1", "0", "0", "0", "1"], ["Arron Davies", "3", "0", "0", "0", "3"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 jp trophies does each person have? | 0 | 128 | Answer: |
Table InputTable: [["Date", "Venue", "Opponents", "Score", "Competition"], ["9 August", "Toyota (A)", "Japan", "2β2", "Toyota Cup"], ["8 August", "Toyota (N)", "Brazil", "0β0", "Toyota Cup"], ["10 August", "Toyota (N)", "United Arab Emirates", "6β0", "Toyota Cup"], ["20 March", "Fukuoka (A)", "Japan", "2β0", "Sanix Cup"], ["12 October", "Tashkent (A)", "Uzbekistan", "3β0", "AFC U-16 Championship (Quarterfinal)"], ["20 March", "Fukuoka (A)", "China PR", "1β0", "Sanix Cup"], ["15 October", "Tashkent (N)", "Japan", "2β1", "AFC U-16 Championship (Semifinal)"], ["4 October", "Tashkent (N)", "India", "5β2", "AFC U-16 Championship (Group B)"], ["18 October", "Tashkent (N)", "Iran", "1β2", "AFC U-16 Championship (Final)"], ["6 October", "Tashkent (N)", "Indonesia", "9β0", "AFC U-16 Championship (Group B)"], ["8 October", "Tashkent (N)", "Syria", "1β1", "AFC U-16 Championship (Group B)"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 was the venue after the last time toyota hosted? | Tashkent (N) | 128 | Answer: |
Table InputTable: [["Name", "Date time (UT)", "Local time zone", "Location", "Elevation + height", "Delivery", "Purpose", "Yield", "Venting", "Notes"], ["Cebolla - 1 (with Cuchillo,Solano)", "9 August 1972 13:03:11.04", "PST (-8 hrs)", "NTS Area U3jc 37Β°00β²26β³N 116Β°01β²11β³Wο»Ώ / ο»Ώ37.00717Β°N 116.01976Β°W", "1,180Β m (3,870Β ft) - 287Β m (942Β ft)", "underground shaft", "weapons development", "less than 5Β kt", "Venting detected", "Simultaneous, separate holes."], ["Oscuro", "21 September 1972 15:00:30.19", "PST (-8 hrs)", "NTS Area U7z 37Β°04β²55β³N 116Β°02β²15β³Wο»Ώ / ο»Ώ37.08201Β°N 116.03742Β°W", "1,225Β m (4,019Β ft) - 560.21Β m (1,838.0Β ft)", "underground shaft", "weapons development", "160Β kt", "", ""], ["Atarque", "25 July 1972 13:00:30.06", "PST (-8 hrs)", "NTS Area U3ht 37Β°00β²45β³N 116Β°00β²57β³Wο»Ώ / ο»Ώ37.01247Β°N 116.01577Β°W", "1,182Β m (3,878Β ft) - 294.2Β m (965Β ft)", "underground shaft", "weapons development", "1.5Β kt", "Venting detected", ""], ["Angus - 1 (with Velarde)", "25 April 1973 22:00:25.03", "PST (-8 hrs)", "NTS Area U3jg 37Β°00β²17β³N 116Β°01β²45β³Wο»Ώ / ο»Ώ37.00483Β°N 116.0292Β°W", "1,180Β m (3,870Β ft) - 452.63Β m (1,485.0Β ft)", "underground shaft", "weapons development", "9Β kt", "Venting detected, 0.6Β Ci (22Β GBq)", "Simultaneous, separate holes."], ["Canna-Umbrinus - 1", "17 November 1972 18:00:00.16", "PST (-8 hrs)", "NTS Area U9itsyz2 37Β°08β²22β³N 116Β°02β²00β³Wο»Ώ / ο»Ώ37.13953Β°N 116.03324Β°W", "1,273Β m (4,177Β ft) - 213.36Β m (700.0Β ft)", "underground shaft", "weapons development", "less than 20Β kt", "", "Simultaneous, same hole."], ["Arsenate", "9 November 1972 18:00:15.16", "PST (-8 hrs)", "NTS Area U9ci 37Β°07β²17β³N 116Β°02β²00β³Wο»Ώ / ο»Ώ37.12151Β°N 116.03326Β°W", "1,268Β m (4,160Β ft) - 250.24Β m (821.0Β ft)", "underground shaft", "weapons development", "600Β t", "Venting detected, 12Β Ci (440Β GBq)", ""], ["Velarde - 2 (with Angus)", "25 April 1973 22:00:25.07", "PST (-8 hrs)", "NTS Area U3jk 36Β°59β²37β³N 116Β°01β²18β³Wο»Ώ / ο»Ώ36.99367Β°N 116.02173Β°W", "1,176Β m (3,858Β ft) - 277Β m (909Β ft)", "underground shaft", "weapons development", "8Β kt", "Venting detected, 250Β Ci (9,200Β GBq)", "Simultaneous, separate holes."], ["Solanum", "14 December 1972 15:00:30.16", "PST (-8 hrs)", "NTS Area U9itsw24 37Β°08β²17β³N 116Β°02β²08β³Wο»Ώ / ο»Ώ37.13804Β°N 116.03559Β°W", "1,267Β m (4,157Β ft) - 201.17Β m (660.0Β ft)", "underground shaft", "weapons development", "less than 20Β kt", "Venting detected", ""], ["Mesita", "9 May 1973 13:00:30.04", "PST (-8 hrs)", "NTS Area U3jd 37Β°00β²23β³N 116Β°01β²01β³Wο»Ώ / ο»Ώ37.00626Β°N 116.01681Β°W", "1,180Β m (3,870Β ft) - 149.25Β m (489.7Β ft)", "underground shaft", "weapons development", "less than 20Β kt", "Venting detected", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 happened after august 1st? | 33 | 128 | Answer: |
Table InputTable: [["No", "Driver", "Entrant", "Constructor", "Chassis", "Engine"], ["12", "Luigi Fagioli", "Officine Alfieri Maserati", "Maserati", "Maserati 26", "1.7 L8"], ["34", "Cesare Pastore", "Private entry", "Maserati", "Maserati 26B", "2.1 L8"], ["22", "Mario Tadini", "Scuderia Ferrari", "Alfa Romeo", "Alfa Romeo 6C 1750GS", "1.8 L6"], ["8", "Pietro Nicolotti", "Private entry", "Alfa Romeo", "Alfa Romeo 6C 1500", "1.5 L6"], ["2", "Luigi Arcangeli", "Officine Alfieri Maserati", "Maserati", "Maserati 26M", "2.5 L8"], ["20", "Arrigo Sartorio", "Private entry", "Maserati", "Maserati 26", "1.5 L8"], ["10", "Cleto Nenzioni", "Private entry", "Maserati", "Maserati 26B", "2.1 L8"], ["18", "Giuseppe Campari", "Scuderia Ferrari", "Alfa Romeo", "Alfa Romeo 6C 1750GS", "1.8 L6"], ["?", "Filippo Sartorio", "Enrico or F. Sartorio", "Alfa Romeo", "Alfa Romeo 6C 1750", "1.5 L6"], ["36", "Colonna de Stigliano", "Private entry", "Alfa Romeo", "Alfa Romeo 6C 1750", "1.8 L6"], ["6", "Clemente Biondetti", "Scuderia Materassi", "Talbot", "Talbot 700", "1.5 L8"], ["4", "Louis Chiron", "Automobiles Ettore Bugatti", "Bugatti", "Bugatti T35B", "2.3 L8"], ["?", "?", "Scuderia Ferrari", "Alfa Romeo", "Alfa Romeo 6C 1500", "1.5 L6"], ["?", "?", "Scuderia Ferrari", "Alfa Romeo", "Alfa Romeo P2", "2.0 L8"], ["16", "Achille Varzi", "SA Alfa Romeo", "Alfa Romeo", "Alfa Romeo P2", "2.0 L8"], ["?", "Arrigo Nenzioni", "A. or E. Nenzioni", "Maserati", "Maserati 26", "1.5 L8"], ["30", "Guy Bouriat", "Automobiles Ettore Bugatti", "Bugatti", "Bugatti T35B", "2.3 L8"], ["28", "Tazio Nuvolari", "SA Alfa Romeo", "Alfa Romeo", "Alfa Romeo P2", "2.0 L8"], ["?", "William Grover-Williams", "Automobiles Ettore Bugatti", "Bugatti", "Bugatti T35B", "2.3 L8"], ["32", "Cesare Renzi", "Private entry", "Bugatti", "Bugatti T37A", "1.5 L8"], ["24", "Heinrich Joachim von Morgen", "Private entry", "Bugatti", "Bugatti T35B", "2.3 L8"], ["14", "Fritz Caflisch", "Private entry", "Mercedes-Benz", "Mercedes-Benz SS", "7.1 L6"], ["26", "Emil Frankl", "Private entry", "Steyr", "Steyr 4.5 Liter", "4.5 L6"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 entrants in the 1930 rome grand prix had cars constructed by maserati? | 6 | 128 | Answer: |
Table InputTable: [["isn", "name", "arrival\\ndate", "departure\\ndate", "notes"], ["82", "Rasul Kudayev", "", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nAlso called \"Abdullah D. Kafkas\"."], ["492", "Aiat Nasimovich Vahitov", "2002-06-14", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men."], ["209", "Almasm Rabilavich Sharipov", "2002-01-21", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nGranted asylum by the Netherlands."], ["674", "Timur Ravilich Ishmurat", "2002-06-14", "2004-02-27", "Repatriated to Russia.\\nReported to have been repatriated on 24 February 2004, as \"Timur Ravilich Ismurat\", with six other Russian men.\\nAlleged to have played a role in a 2005 bombing."], ["203", "Ravil Shafeyavich Gumarov", "2002-01-21", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nAlleged to have played a role in a 2005 bombing.\\nDefense Intelligence Agency classifies him as a former detainee who \"returned to terrorism\"."], ["573", "Rustam Akhmyarov", "2002-05-01", "2004-02-27", "Reported to have been repatriated on 24 February 2004 with six other Russian men."], ["211", "Ruslan Anatoloivich Odijev", "2002-06-14", "2004-02-27", "Reported to have been repatriated on 24 February 2004, as \"Ruslan Anatolovich Odijev\", with six other Russian men.\\nCharged with a role in bombing a gas pipeline in 2005.\\nShot by police in 2007.\\nHuman Rights advocates argue he was falsely accused.\\nDefense Intelligence Agency classifies him as a former detainee who \"returned to terrorism\"."], ["702", "Ravil Mingazov", "2002-10-28", "", ""], ["672", "Zakirjan Asam", "2002-06-08", "2006-11-17", "NLEC"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 men repatriated with rasul kudayev? | 6 | 128 | Answer: |
Table InputTable: [["Year", "Class", "No", "Tyres", "Car", "Team", "Co-Drivers", "Laps", "Pos.", "Class\\nPos."], ["1973", "S\\n3.0", "62", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Guy Ligier", "24", "DSQ", "DSQ"], ["1974", "S\\n3.0", "15", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Alain Serpaggi", "310", "8th", "5th"], ["1972", "S\\n3.0", "22", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Pierre Maublanc", "195", "DNF", "DNF"], ["1996", "GT1", "38", "M", "McLaren F1 GTR\\nBMW S70 6.1L V12", "Team Bigazzi SRL", "Steve Soper\\n Marc Duez", "318", "11th", "9th"], ["1977", "S\\n+2.0", "8", "", "Renault Alpine A442\\nRenault 2.0L Turbo V6", "Renault Sport", "Patrick Depailler", "289", "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"], ["1994", "GT2", "49", "P", "Porsche 911 Carrera RSR\\nPorsche 3.8 L Flat-6", "Larbre CompΓ©tition", "Jacques AlmΓ©ras\\n Jean-Marie AlmΓ©ras", "94", "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"], ["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"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 year the ligier ran for team automobiles ligier? | 1974 | 128 | Answer: |
Table InputTable: [["School", "2007", "2008", "2009", "2010", "2011"], ["Oscar De La Hoya Animo Charter High School", "662", "726", "709", "710", "744"], ["Marc and Eva Stern Math and Science School", "718", "792", "788", "788", "809"], ["Francisco Bravo Medical Magnet High School", "807", "818", "815", "820", "832"], ["Santee Education Complex", "", "502", "521", "552", "565"], ["James A. Garfield High School", "553", "597", "593", "632", "705"], ["Woodrow Wilson High School", "582", "585", "600", "615", "636"], ["Abraham Lincoln High School", "594", "609", "588", "616", "643"], ["Thomas Jefferson High School", "457", "516", "514", "546", "546"], ["Theodore Roosevelt High School", "557", "551", "576", "608", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 number of schools with a number higher than 600 in 2008? | 4 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Notes"], ["2006", "World Junior Championships", "Beijing, China", "5th", "5.30 m"], ["2011", "World Championships", "Daegu, South Korea", "9th", "5.65 m"], ["2005", "World Youth Championships", "Marrakech, Morocco", "6th", "5.05 m"], ["2008", "Olympic Games", "Beijing, China", "10th", "5.45 m"], ["2009", "World Championships", "Berlin, Germany", "22nd (q)", "5.40 m"], ["2014", "World Indoor Championships", "Sopot, Poland", "3rd", "5.80 m"], ["2012", "European Championships", "Helsinki, Finland", "6th", "5.60 m"], ["2013", "European Indoor Championships", "Gothenburg, Sweden", "5th", "5.71 m"], ["2010", "European Championships", "Barcelona, Spain", "10th", "5.60 m"], ["2012", "Olympic Games", "London, United Kingdom", "8th", "5.65 m"], ["2009", "European U23 Championships", "Kaunas, Lithuania", "8th", "5.15 m"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 world junior championships 2006, what other competition was held in beijing, china? | Olympic Games | 128 | Answer: |
Table InputTable: [["Name", "Nationality", "From", "To", "Honours", "Comments"], ["RenΓ© Heitmann", "Denmark", "17 July 2010", "27 July 2010", "", "Never coached the team in a match"], ["John 'Tune' Kristiansen", "Denmark", "18 June 2012", "23 June 2012", "", "Caretaker for one league match"], ["Ebbe Skovdahl", "Denmark", "11 October 2003", "6 November 2005", "Team was relegated to second tier", "Originally had contract until summer 2007"], ["Johnny Petersen", "Denmark", "5 May 1998", "14 October 2001", "", "Originally had contract until end of 2001"], ["Anders Theil", "Denmark", "7 November 2005", "7 July 2009", "", "Originally had contract until summer 2011"], ["Christian Andersen", "Denmark", "11 July 2009", "19 June 2010", "Team was relegated to third tier", "Club went bankrupt after the season"], ["Henrik Jensen", "Denmark", "1 July 2012", "Present", "", ""], ["Ole MΓΈrk", "Denmark", "15 October 2001", "10 October 2003", "Won promotion to first tier", "Originally had contract until end of 2004"], ["Peer F. Hansen", "Denmark", "1 January 2012", "18 June 2012", "won promotion to the third tier", ""], ["John 'Tune' Kristiansen", "Denmark", "1996", "4 May 1998", "Won promotion to second tier", ""], ["John 'Tune' Kristiansen", "Denmark", "27 July 2010", "30 December 2011", "won promotion to the fourth tier", "Originally had contract until summer 2012"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 coach before rene heitmann? | Christian Andersen | 128 | Answer: |
Table InputTable: [["Model", "Fuel Type", "mpg (US gallons)", "L/100Β km", "NZ Rating\\n(Stars)"], ["Fiat 500 1.4 POP", "petrol", "37.3", "6.3", "4.5"], ["Fiat 500 1.3 JTD POP", "diesel", "56", "4.2", "5.5"], ["Fiat 500 1.2 POP", "petrol", "46", "5.1", "5"], ["Fiat 500 1.4 SPORT", "petrol", "37.3", "6.3", "4.5"], ["Fiat 500 1.4 LOUNGE 3D", "petrol", "37.3", "6.3", "4.5"], ["Fiat Grande Punto 1.4 DYNAMIC 5 SPEED", "petrol", "38.5", "6.1", "4.5"], ["Fiat Grande Punto 1.9 JTD 5D 6SPEED", "diesel", "42", "5.6", "5"], ["Fiat Multipla DYNAMIC 1.9 JTD 5D", "diesel", "36.7", "6.4", "4.5"], ["Fiat Grande Punto 1.9 EMOTION 5DR 6SPD", "diesel", "42", "5.6", "5"], ["Fiat Grande Punto 1.9 JTD SPORT 3D 6SP", "diesel", "42", "5.6", "5"], ["Citroen C4 2.0 SX 5DR 6SP A D", "diesel", "37.3", "6.3", "4.5"], ["Citroen C4 1.6 SX 5DR 5SP M D", "diesel", "50", "4.7", "5"], ["Citroen C3 1.6 5DR 5SPD", "petrol", "36.2", "6.5", "4.5"], ["Fiat Grande Punto 1.3 JTD 5D DUALOGIC", "diesel", "51", "4.6", "5"], ["Citroen C4 1.6 HDI 6A EGS 5DR", "diesel", "52", "4.5", "5.5"], ["Fiat Grande Punto 1.4 5D DUAL LOGIC", "petrol", "35", "6.7", "4.5"], ["Fiat Grande Punto 1.3 JTD 5D 6SP", "diesel", "51", "4.6", "5"], ["Fiat Bravo SPORT JTD 16V 5DR", "diesel", "42", "5.6", "5"], ["Fiat Grande Punto 1.3 JTD DUAL LOGIC", "diesel", "46", "5.1", "5"], ["Kia Rio 1.5 DIESEL SEDAN MAN", "diesel", "52", "4.5", "5.5"], ["Suzuki SX4 GLXF 1.6 5DR", "petrol", "34.6", "6.8", "4.5"], ["Volkswagen Caddy LIFE 1.9 TDI DSG", "diesel", "38.5", "6.1", "4.5"], ["Mini Cooper HATCH 6M 2DR 1.5L Diesel", "diesel", "53", "4.4", "5.5"], ["Citroen C3 1.6 HDI 5DR 5SPD", "diesel", "48", "4.9", "5"], ["Kia Rio 1.5 DIESEL HATCH MAN", "diesel", "52", "4.5", "5.5"], ["Renault Clio 1.6 3DR 4SP A P", "petrol", "35", "6.7", "4.5"], ["Ford Fiesta 5DR 1.6 M", "petrol", "35.6", "6.6", "4.5"], ["Alfa Romeo Brera 2.4 JTD 3D 6 SPEED", "diesel", "34.6", "6.8", "4.5"], ["Kia Picanto 1.1 AUTO", "petrol", "40.5", "5.8", "5"], ["Mini Cooper COUPE 6A 3DR 1.6L Diesel", "diesel", "43.5", "5.4", "5"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:name all models with the same mpg as fiat 500 1.4 pop. | Fiat 500 1.4 LOUNGE 3D, Fiat 500 1.4 SPORT, Citroen C4 2.0 SX 5DR 6SP A D, Volkswagen Golf TDI 103KW 4MOTION, Peugeot 207 XS 1.4 5DR 5SPD M P, Saab 9-3 Linear CONVERTIBLE 1.9TID M, Suzuki Swift GLX 1.5 5DR, Suzuki Swift GLXH 1.5 5DR, Suzuki Swift GLXH2 1.5 5DR | 128 | Answer: |
Table InputTable: [["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)"], ["1 January 2009", "Β£2.70", "Β£4.70", "Β£8.40", "Β£9.40", "Β£9.40"], ["1 January 2008", "Β£2.50", "Β£4.50", "Β£8.00", "Β£9.00", "Β£9.00"], ["1 March 2012", "Β£3.00", "Β£5.50", "Β£10.00", "Β£11.00", "Β£11.00"], ["1 March 2011", "Β£3.00", "Β£5.30", "Β£9.60", "Β£10.60", "Β£10.60"], ["1 March 2010", "Β£2.70", "Β£5.00", "Β£9.00", "Β£10.00", "Β£10.00"], ["9 December 2003", "Β£1.00", "Β£2.00", "Β£5.00", "Β£5.00", "Β£10.00"], ["14 June 2005", "Β£2.50", "Β£3.50", "Β£7.00", "Β£7.00", "Β£7.00"], ["23 July 2004", "Β£1.00", "Β£2.00", "Β£5.00", "Β£5.00", "Β£6.00"], ["16 August 2004", "Β£2.00", "Β£3.00", "Β£6.00", "Β£6.00", "Β£6.00"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 top price for a class 1 toll rate? | Β£3.00 | 128 | Answer: |
Table InputTable: [["Name", "Type", "R.A. (J2000)", "Dec. (J2000)", "Redshift (km/s)", "Apparent Magnitude"], ["NGC 1569", "Sbrst", "04hΒ 30mΒ 49.1s", "+64° 50β²Β 52,6β³", "-104 Β± 4", "11,2"], ["UGCA 86", "Im", "03hΒ 59mΒ 50.5s", "+67° 08β²Β 37β³", "67 Β± 4", "13.5"], ["UGCA 92", "Im", "04hΒ 32mΒ 04.9s", "+63° 36β²Β 49.0β³", "-99 Β± 5", "13.8"], ["IC 342", "SAB(rs)cd", "03hΒ 46mΒ 48.5s", "+68° 05β²Β 46β³", "31 Β± 3", "9.1"], ["Cassiopeia 1", "dIrr", "02hΒ 06mΒ 02.8s", "+68° 59β²Β 59β³", "35", "16.4"], ["UGCA 105", "Im", "05hΒ 14mΒ 15.3s", "+62° 34β²Β 48β³", "111 Β± 5", "13.9"], ["NGC 1560", "SA(s)d", "04hΒ 32mΒ 49.1s", "+71° 52β²Β 59β³", "-36 Β± 5", "12.2"], ["Camelopardalis B", "Irr", "04hΒ 53mΒ 07.1s", "+67° 05β²Β 57β³", "77", "16.1"], ["Camelopardalis A", "Irr", "04hΒ 26mΒ 16.3s", "+72° 48β²Β 21β³", "-46 Β± 1", "14.8"], ["KK 35", "Irr", "03hΒ 45mΒ 12.6s", "+67° 51β²Β 51β³", "105 Β± 1", "17.2"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 name is first on the chart? | Camelopardalis A | 128 | Answer: |
Table InputTable: [["Name", "Pennant", "Namesake", "Builder", "Ordered", "Laid down", "Launched", "Commissioned", "Fate"], ["Apollo", "63", "Apollo, God of Light", "HM Dockyard, Devonport", "1 March 1933", "15 August 1933", "9 October 1934", "13 January 1936", "Sold to Royal Australian Navy as HMAS Hobart, 1938\\nBroken up at Osaka, 1962"], ["Amphion", "29", "Amphion of Thebes", "HM Dockyard, Portsmouth", "1 December 1932", "22 June 1933", "27 July 1934", "15 June 1936", "Sold to Royal Australian Navy as HMAS Perth, 1939\\nSunk in torpedo attack, 1 March 1942"], ["Leander", "75", "Leander of Abydos", "HM Dockyard, Devonport", "18 February 1928", "1 August 1928", "13 July 1929", "23 July 1931", "Transferred to Royal New Zealand Navy as HMNZS Leander 1941-1945\\nBroken up at Blyth 1950"], ["Achilles", "70", "Achilles", "Cammell Laird", "16 February 1931", "11 June 1931", "1 September 1932", "24 March 1936", "Transferred to Royal New Zealand Navy as HMNZS Achilles 1941-1946\\nSold to Indian Navy as HIMS Delhi 1948"], ["Sydney\\n(ex-Phaeton)", "48", "City of Sydney", "Swan Hunter", "10 February 1933", "8 July 1933", "22 September 1934", "24 September 1935", "Sunk in surface action, 19 November 1941"], ["Orion", "85", "Orion the Hunter", "HM Dockyard, Devonport", "24 March 1931", "26 September 1931", "24 November 1932", "18 January 1934", "Broken up at Dalmuir, 1949"], ["Neptune", "20", "Neptune, God of the Sea", "HM Dockyard, Portsmouth", "2 March 1931", "24 September 1931", "31 January 1933", "23 February 1934", "Sunk in minefield off Tripoli, 19 December 1941"], ["Ajax", "22", "Ajax the Great", "Vickers Armstrong", "1 October 1932", "7 February 1933", "1 March 1934", "12 April 1935", "Broken up at Newport, 1949"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 ships have a pennant number higher than 50? | Leander, Orion, Achilles, Apollo | 128 | Answer: |
Table InputTable: [["Rank", "Heat", "Name", "Nationality", "Time", "Notes"], ["2", "1", "Hiroyasu Tsuchie", "Japan", "10.64", "Q"], ["", "3", "Sudath Ravindra Kumara", "Sri Lanka", "DQ", ""], ["2", "2", "Yuta Kanno", "Japan", "10.64", "Q"], ["6", "1", "Vissanu Sophanich", "Thailand", "10.87", ""], ["7", "2", "Tang Yui Han", "Singapore", "11.61", "PB"], ["5", "4", "Nguyen Thanh Hai", "Vietnam", "11.16", "PB"], ["7", "4", "Bona Kong", "Cambodia", "11.75", "PB"], ["4", "1", "Chintake De Zoysa", "Sri Lanka", "10.78", "q"], ["6", "4", "Piphop Rasme Prum Keo", "Cambodia", "11.70", "PB"], ["2", "3", "Reanchai Srihawong", "Thailand", "10.72", "Q"], ["1", "2", "Gennadiy Chernovol", "Kazakhstan", "10.59", "Q"], ["8", "2", "Chaleunsouk Oudomphanh", "Laos", "11.76", "SB"], ["5", "3", "To Wai Lok", "Hong Kong", "10.92", ""], ["4", "4", "Chiang Wai Hung", "Malaysia", "10.89", ""], ["4", "2", "Tsai Meng-Lin", "Chinese Taipei", "10.74", "q"], ["3", "4", "Azmi Ibrahim", "Malaysia", "10.78", "Q"], ["7", "1", "Zakaria MessaikΓ©", "Lebanon", "11.06", ""], ["7", "3", "Abdullah Ibrahim", "Maldives", "12.04", "PB"], ["", "4", "Hamood Al-Dalhami", "Oman", "DQ", ""], ["6", "2", "Ahmad Hudeib Al-Mamari", "Oman", "10.97", ""], ["", "1", "Khalil Al-Hanahneh", "Jordan", "DNS", ""], ["4", "3", "Chen Tien-Wen", "Chinese Taipei", "10.74", "q"], ["3", "2", "Shen Yunbao", "China", "10.72", "Q"], ["3", "3", "Shin Jung-Ki", "South Korea", "10.79", ""], ["5", "1", "Suminda Mendis", "Sri Lanka", "10.82", "q, PB"], ["1", "1", "Salem Al-Yami", "Saudi Arabia", "10.55", "Q"], ["5", "2", "Tan Kok Lim", "Malaysia", "10.83", "q"], ["3", "1", "Khaled Yousef Al-Obaidli", "Qatar", "10.68", "Q"], ["2", "4", "Saad Faraj Al-Shahwani", "Qatar", "10.67", "Q"], ["1", "4", "Chen Haijian", "China", "10.65", "Q"], ["1", "3", "Jamal Al-Saffar", "Saudi Arabia", "10.57", "Q"], ["6", "3", "Poh Seng Song", "Singapore", "11.10", "SB"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 after hiroyasu tuchie? | Khaled Yousef Al-Obaidli | 128 | Answer: |
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2006", "Spartak Nizhny Novgorod", "Russia", "2", "36", "1"], ["2005", "CSKA Moscow", "Russia", "1", "0", "0"], ["2004", "CSKA Moscow", "Russia", "1", "0", "0"], ["2006/07", "Dnipro Dnipropetrovsk", "Ukraine", "1", "12", "0"], ["2009/10", "Dnipro Dnipropetrovsk", "Ukraine", "1", "28", "0"], ["2012/13", "Lokomotiv Moscow", "Russia", "1", "8", "0"], ["2013/14", "Lokomotiv Moscow", "Russia", "1", "14", "1"], ["2011/12", "Dnipro Dnipropetrovsk", "Ukraine", "1", "16", "0"], ["2008/09", "Dnipro Dnipropetrovsk", "Ukraine", "1", "22", "1"], ["2007/08", "Dnipro Dnipropetrovsk", "Ukraine", "1", "24", "0"], ["2010/11", "Dnipro Dnipropetrovsk", "Ukraine", "1", "23", "0"], ["2012/13", "Dnipro Dnipropetrovsk", "Ukraine", "1", "10", "1"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 last team on this chart? | Lokomotiv Moscow | 128 | Answer: |
Table InputTable: [["Title", "Year", "Authors", "Publisher", "Pages"], ["The Route to Advanced Communications", "1991", "David Cleevely, Stefan Stanislawski, Ade Ajibulu", "Analysys Publications", "178"], ["ATM Vendor & Operator Strategies", "1993", "David Cleevely, Peter Aknai, Ian Leslie", "Analysis Publications", "180"], ["Global Turf Wars: Re-Inventing the Telecoms Operator for the Age of Global Competition", "1999", "Tim Hills, David Cleevely, Andrea Smith", "Analysis Publications", "218"], ["The Far Reaching Effects of Broadband", "2002", "David Cleevely", "Institution of Engineering & Technology", "415"], ["Rural Telecoms Handbook: Equipment and Manufacturers", "1992", "Tim Hills, David Cleevely", "Analysys Publications", "-"], ["Regulating the Telecoms Market: Competition and Innovation in the Broadband Economy", "2003", "Tim Hills, David Cleevely, Ross Pow", "Analysis Publications", "35"], ["Regional Structure and Telecommunications Demand: A Case Study of Kenya (Ph.D. thesis)", "1982", "D. D. Cleevely", "University of Cambridge", "-"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 co-authored a publication with david cleevely more than once? | Tim Hills | 128 | Answer: |
Table InputTable: [["Date", "Opponent", "Site", "Result"], ["September 24", "Millsaps*", "Denny Field β’ Tuscaloosa, AL", "WΒ 54β0"], ["November 13", "Florida", "Cramton Bowl β’ Montgomery, AL", "WΒ 49β0"], ["November 6", "Kentucky", "Rickwood Field β’ Birmingham, AL", "WΒ 14β0"], ["January 1, 1927", "vs.Β Stanford*", "Rose Bowl β’ Pasadena, CA (Rose Bowl)", "TΒ 7β7"], ["October 23", "Sewanee", "Rickwood Field β’ Birmingham, AL", "WΒ 2β0"], ["November 25", "Georgia", "Rickwood Field β’ Birmingham, AL", "WΒ 33β6"], ["October 9", "atΒ Mississippi A&M", "Meridian Fairgrounds β’ Meridian, MS (Rivalry)", "WΒ 26β7"], ["October 2", "atΒ Vanderbilt", "Dudley Field β’ Nashville, TN", "WΒ 19β7"], ["October 16", "atΒ Georgia Tech", "Grant Field β’ Atlanta, GA", "WΒ 21β0"], ["October 30", "LSU", "Denny Field β’ Tuscaloosa, AL (Rivalry)", "WΒ 24β0"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 wins are listed? | 9 | 128 | Answer: |
Table InputTable: [["Year", "Award", "Category", "Recipient", "Result"], ["2013", "15th Mnet Asian Music Awards", "Best Female Artist", "Herself", "Nominated"], ["2013", "15th Mnet Asian Music Awards", "Artist of the Year", "Herself", "Nominated"], ["2013", "Mnet Pre-Grammy Awards", "Mnet Rising Star", "Herself", "Won"], ["2012", "So-Loved Awards", "Best Female Newcomer", "Herself", "Won"], ["2013", "5th MelOn Music Awards", "Top 10 Artists", "Herself", "Won"], ["2013", "15th Mnet Asian Music Awards", "Best Vocal Performance - Female", "\"U&I\"", "Won"], ["2013", "15th Mnet Asian Music Awards", "BC - UnionPay Song of the year", "\"U&I\"", "Nominated"], ["2012", "4th MelOn Music Awards", "Best New Artist", "Herself", "Won"], ["2014", "Soompi Music Awards", "Best Female Artist", "\"U&I\"", "Won"], ["2012", "14th Mnet Asian Music Awards", "Best New Female Artist", "Herself", "Won"], ["2013", "27th Golden Disk Awards", "Best New Artist", "Herself", "Won"], ["2013", "23rd Seoul Music Awards", "Rookie Award", "Herself", "Won"], ["2012", "Asia Song Festival", "New Artist Award", "Herself", "Won"], ["2013", "2nd Gaon Chart K-Pop Awards", "New Female Solo Artist", "Herself", "Won"], ["2012", "Cyworld Digital Music Awards", "Rookie & Song of the Month (February)", "\"Heaven\"", "Won"], ["2012", "Soompi Gayo Awards", "Top 50 Songs (#3)", "\"Heaven\"", "Won"], ["2014", "28th Golden Disk Awards", "Digital Bonsang", "\"U&I\"", "Won"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 was ailee only nominated for an award? | 3 | 128 | Answer: |
Table InputTable: [["#", "Title", "Featured guest(s)", "Producer(s)", "Time", "Sample (s)"], ["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"], ["16", "\"Better Days\"", "Ron Banks", "Barr Nine", "3:53", "*\"It's Gonna Be Alright\" by Crimies"], ["12", "\"Rich Rollin'\"", "", "Dutch", "3:40", ""], ["7", "\"Just Clownin'\"", "", "Battlecat", "3:59", "*\"(Not Just) Knee Deep\" by Funkadelic\\n*\"Too Tight for Light\" by Funkadelic"], ["11", "\"Call It What You Want\"", "", "Crazy Toones", "4:29", "*\"Knucklehead\" by Grover Washington, Jr."], ["5", "\"Can't Hold Back\"", "Ice Cube", "Skooby Doo", "3:34", "*\"Ain't No Half-Steppin'\" by Big Daddy Kane"], ["15", "\"It's All Bad\"", "", "Battlecat", "4:15", "*\"Chocolate City\" by Parliament"], ["6", "\"Keep Hustlin\"", "E-40 & Too Short", "Young Tre", "3:39", "*\"Yearning for Your Love\" by The Gap Band\\n*\"Intimate Connection\" by Kleeer"], ["13", "\"Cheddar\"", "Mack 10 & Ice Cube", "Mo-Suave-A", "4:12", "*\"Gotta Get My Hands on Some (Money)\" by The Fatback Band"], ["4", "\"The Shadiest One\"", "CJ Mac", "Ant Banks", "4:26", ""], ["3", "\"Fuckin Wit uh House Party\"", "", "Battlecat", "4:49", "*\"Hollywood Squares\" by Bootsy's Rubber Band\\n*\"(Not Just) Knee Deep\" by Funkadelic"], ["8", "\"The Autobiography\"", "", "Crazy Toones", "1:21", ""], ["17", "\"The Outcome\"", "", "Douglas Coleman", "2:45", ""], ["14", "\"Bank Lick\"", "", "WC", "0:49", ""], ["2", "\"Where Y'all From\"", "", "Battlecat", "1:11", ""], ["9", "\"Worldwide Gunnin'\"", "", "Skooby Doo", "3:25", ""], ["1", "\"Hog\"", "", "Battlecat", "4:24", "*\"3 Time Felons\" by Westside Connection"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 tracks are on the album? | 17 | 128 | Answer: |
Table InputTable: [["Week", "Date", "Opponent", "Result", "Attendance"], ["14", "December 19, 1987", "at Denver Broncos", "L 20β17", "75,053"], ["8", "November 8, 1987", "Pittsburgh Steelers", "L 17β16", "45,249"], ["5", "October 18, 1987", "Denver Broncos", "L 26β17", "20,296"], ["15", "December 27, 1987", "Seattle Seahawks", "W 41β20", "20,370"], ["12", "December 6, 1987", "at Cincinnati Bengals", "L 30β27", "46,489"], ["4", "October 11, 1987", "at Miami Dolphins", "L 42β0", "25,867"], ["13", "December 13, 1987", "Los Angeles Raiders", "W 16β10", "63,834"], ["3", "October 4, 1987", "at Los Angeles Raiders", "L 35β17", "10,708"], ["6", "October 25, 1987", "at San Diego Chargers", "L 42β21", "47,972"], ["1", "September 13, 1987", "San Diego Chargers", "W 20β13", "56,940"], ["10", "November 22, 1987", "Green Bay Packers", "L 23β3", "34,611"], ["7", "November 1, 1987", "at Chicago Bears", "L 31β28", "63,498"], ["2", "September 20, 1987", "at Seattle Seahawks", "L 43β14", "61,667"], ["β", "September 27, 1987", "Minnesota Vikings", "canceled", ""], ["9", "November 15, 1987", "New York Jets", "L 16β9", "40,718"], ["11", "November 26, 1987", "at Detroit Lions", "W 27β20", "43,820"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 did they face that last game of the year? | Seattle Seahawks | 128 | Answer: |
Table InputTable: [["Year", "Premiers", "Score", "Runners Up", "Score"], ["2008", "Cairns Saints", "12.15 (87)", "North Cairns Tigers", "2.9 (21)"], ["2012", "Cairns Saints", "17.6 (108)", "North Cairns Tigers", "11.12 (78)"], ["2010", "North Cairns Tigers", "8.10 (58)", "Port Douglas Crocs", "8.5 (53)"], ["2013", "North Cairns Tigers", "14.14 (98)", "Port Douglas Crocs", "13.6 (84)"], ["2003", "Centrals Trinity Beach Bulldogs", "14.11 (95)", "North Cairns", "6.7 (43)"], ["2007", "Centrals Trinity Beach Bulldogs", "14.16 (100)", "Cairns Saints", "11.2 (68)"], ["2004", "Port Douglas Crocs", "17.13 (115)", "North Cairns Tigers", "8.9 (57)"], ["2005", "Port Douglas Crocs", "19.14 (128)", "Cairns Saints", "4.11 (35)"], ["2006", "Manunda Hawks", "11.11 (77)", "Centrals Trinity Beach Bulldogs", "10.9 (69)"], ["2009", "South Cairns Cutters", "9.11 (65)", "Cairns Saints", "9.4 (58)"], ["2011", "Manunda Hawks", "11.8 (74)", "Port Douglas Crocs", "6.9 (45)"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 premier had the least number of points in their score? | North Cairns Tigers | 128 | Answer: |
Table InputTable: [["Description Losses", "1939/40", "1940/41", "1941/42", "1942/43", "1943/44", "1944/45", "Total"], ["Deaths In Prisons & Camps", "69,000", "210,000", "220,000", "266,000", "381,000", "", "1,146,000"], ["Deaths Outside of Prisons & Camps", "", "42,000", "71,000", "142,000", "218,000", "", "473,000"], ["Deaths other countries", "", "", "", "", "", "", "2,000"], ["Murdered in Eastern Regions", "", "", "", "", "", "100,000", "100,000"], ["Direct War Losses", "360,000", "", "", "", "", "183,000", "543,000"], ["Murdered", "75,000", "100,000", "116,000", "133,000", "82,000", "", "506,000"], ["Total", "504,000", "352,000", "407,000", "541,000", "681,000", "270,000", "2,770,000"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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's the number of deaths in prisons & camps that happened in 1941/42? | 220,000 | 128 | Answer: |
Table InputTable: [["Rank", "Diver", "Preliminary\\nPoints", "Preliminary\\nRank", "Final\\nPoints"], ["6", "Elsa TenorioΒ (MEX)", "460.56", "8", "463.56"], ["4", "Li YihuaΒ (CHN)", "517.92", "1", "506.52"], ["22", "Joana FigueiredoΒ (POR)", "374.07", "22", ""], ["5", "Li QiaoxianΒ (CHN)", "466.83", "6", "487.68"], ["17", "Claire IzacardΒ (FRA)", "403.17", "17", ""], ["", "Kelly McCormickΒ (USA)", "516.75", "2", "527.46"], ["11", "Anita RossingΒ (SWE)", "464.58", "7", "424.98"], ["15", "Antonette WilkenΒ (ZIM)", "414.66", "15", ""], ["", "Christina SeufertΒ (USA)", "481.41", "5", "517.62"], ["23", "Angela RibeiroΒ (BRA)", "370.68", "23", ""], ["20", "Kerstin FinkeΒ (FRG)", "393.93", "20", ""], ["21", "Nicole KreilΒ (AUT)", "382.68", "21", ""], ["12", "VerΓ³nica RibotΒ (ARG)", "443.25", "9", "422.52"], ["13", "Ann FargherΒ (NZL)", "421.65", "13", ""], ["19", "Alison ChildsΒ (GBR)", "400.68", "19", ""], ["7", "Lesley SmithΒ (ZIM)", "438.72", "10", "451.89"], ["18", "Valerie McFarland-BeddoeΒ (AUS)", "401.13", "18", ""], ["10", "Daphne JongejansΒ (NED)", "487.95", "4", "437.40"], ["16", "Guadalupe CansecoΒ (MEX)", "411.96", "16", ""], ["9", "Jennifer DonnetΒ (AUS)", "432.78", "12", "443.13"], ["8", "Debbie FullerΒ (CAN)", "437.04", "11", "450.99"], ["14", "Tine TollanΒ (NOR)", "419.55", "14", ""], ["", "Sylvie BernierΒ (CAN)", "489.51", "3", "530.70"], ["24", "Rim HassanΒ (EGY)", "258.63", "24", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 rank 4 li yihua or elsa tenorio? | Li Yihua | 128 | Answer: |
Table InputTable: [["Distribution", "x86", "x86-64", "ia64", "ppc", "ppc64", "sparc32", "sparc64", "arm", "hppa", "mips", "sh", "s390", "s390x", "alpha", "m68k"], ["Distribution", "x86", "x86-64", "ia64", "ppc", "ppc64", "sparc32", "sparc64", "arm", "hppa", "mips", "sh", "s390", "s390x", "alpha", "m68k"], ["Slackware", "Yes", "Yes", "No", "No", "No", "Discontinued\\n?", "No", "Yes", "No", "No", "No", "Discontinued\\n?", "Discontinued\\n?", "Discontinued\\n8.1", "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"], ["Red Hat Enterprise Linux", "Discontinued\\n2.1-6", "Yes\\n3+", "Discontinued\\n2.1-5", "Yes\\n3+", "Yes\\n3+", "No", "No", "No", "No", "No", "No", "Discontinued\\n3-4", "Yes\\n3+", "No", "No"], ["Gentoo", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes"], ["Frugalware", "Yes", "Yes", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No"], ["Debian", "Yes", "Yes\\n4.0+", "Discontinued\\n3.0-7.0", "Yes\\n2.2+", "Yes", "Discontinued on Lenny", "Yes", "Yes\\n2.2+", "Discontinued\\n3.0-5.0", "Yes\\n3.0+", "In progress", "Discontinued\\n3.0-7", "Yes\\n7+", "Discontinued\\n2.1-5.0", "Discontinued\\n2.0-3.1"], ["CentOS", "Yes", "Yes", "Discontinued\\n3.5-3.8\\n4.1-4.7", "Beta\\n4.0", "No", "Beta\\n4.2", "No", "No", "No", "No", "No", "Discontinued\\n3.5-3.8\\n4.1-4.7", "Discontinued\\n3.5-3.8\\n4.1-4.7", "Discontinued\\n4.2-4.3", "No"], ["Tor-ramdisk", "Yes", "Yes", "No", "No", "No", "No", "No", "No", "No", "Yes", "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"], ["Finnix", "Yes", "Yes", "No", "Yes", "Yes", "No", "No", "No", "No", "No", "No", "No", "No", "No", "No"], ["MintPPC", "No", "No", "No", "Yes", "Yes", "No", "No", "No", "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"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 distributor at the top of the list | Arch Linux | 128 | Answer: |
Table InputTable: [["Chord", "Root", "Minor Third", "Perfect Fifth", "Major Seventh"], ["AmM7", "A", "C", "E", "Gβ―"], ["FmM7", "F", "Aβ", "C", "E"], ["CmM7", "C", "Eβ", "G", "B"], ["Cβ―mM7", "Cβ―", "E", "Gβ―", "Bβ― (C)"], ["Gβ―mM7", "Gβ―", "B", "Dβ―", "F (G)"], ["Dβ―mM7", "Dβ―", "Fβ―", "Aβ―", "C (D)"], ["Aβ―mM7", "Aβ―", "Cβ―", "Eβ― (F)", "G (A)"], ["Fβ―mM7", "Fβ―", "A", "Cβ―", "Eβ― (F)"], ["GmM7", "G", "Bβ", "D", "Fβ―"], ["BmM7", "B", "D", "Fβ―", "Aβ―"], ["EmM7", "E", "G", "B", "Dβ―"], ["DmM7", "D", "F", "A", "Cβ―"], ["BβmM7", "Bβ", "Dβ", "F", "A"], ["DβmM7", "Dβ", "Fβ (E)", "Aβ", "C"], ["GβmM7", "Gβ", "B (A)", "Dβ", "F"], ["AβmM7", "Aβ", "Cβ (B)", "Eβ", "G"], ["EβmM7", "Eβ", "Gβ", "Bβ", "D"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 chords are listed? | 17 | 128 | Answer: |
Table InputTable: [["#", "Name", "Took office", "Left office", "Party", "Governor", "Notes"], ["36", "Richard T. James", "January 8, 1945", "January 10, 1948", "Republican", "Ralph F. Gates", ""], ["44", "Robert D. Orr", "January 8, 1973", "January 12, 1981", "Republican", "Otis R. Bowen", ""], ["31", "F. Harold Van Orman", "January 12, 1925", "January 14, 1929", "Republican", "Edward L. Jackson", ""], ["45", "John Mutz", "January 12, 1981", "January 9, 1989", "Republican", "Robert D. Orr", ""], ["38", "John A. Watkins", "January 10, 1949", "January 12, 1953", "Democrat", "Henry F. Schricker", ""], ["50", "Sue Ellspermann", "January 14, 2013", "Incumbent", "Republican", "Mike Pence", ""], ["48", "Kathy Davis", "October 20, 2003", "January 10, 2005", "Democrat", "Joe E. Kernan", ""], ["5", "Milton Stapp", "December 3, 1828", "December 7, 1831", "Independent", "James B. Ray", ""], ["41", "Richard O. Ristine", "January 9, 1961", "January 11, 1965", "Republican", "Matthew E. Welsh", ""], ["32", "Edgar D. Bush", "January 14, 1929", "January 9, 1933", "Republican", "Harry G. Leslie", ""], ["29", "Edgar D. Bush", "January 8, 1917", "January 10, 1921", "Republican", "James P. Goodrich", ""], ["21", "Robert S. Robertson", "January 10, 1887", "January 13, 1889", "Republican", "Isaac P. Gray", ""], ["9", "Jesse D. Bright", "December 6, 1843", "December 6, 1845", "Democrat", "James Whitcomb", ""], ["14", "Oliver P. Morton", "January 14, 1861", "January 16, 1861", "Republican", "Henry Smith Lane", ""], ["34", "Henry F. Schricker", "January 11, 1937", "January 13, 1941", "Democrat", "M. Clifford Townsend", ""], ["19", "Thomas Hanna", "January 10, 1881", "November 12, 1885", "Republican", "Albert G. Porter", ""], ["40", "Crawford F. Parker", "January 14, 1957", "January 9, 1961", "Republican", "Harold W. Handley", ""], ["35", "Charles M. Dawson", "January 13, 1941", "January 8, 1945", "Democrat", "Henry F. Schricker", ""], ["33", "M. Clifford Townsend", "January 9, 1933", "January 11, 1937", "Democrat", "Paul V. McNutt", ""], ["1", "Christopher Harrison", "November 7, 1816", "December 17, 1818", "Democratic-Republican", "Jonathan Jennings", ""], ["11", "James Henry Lane", "December 5, 1849", "January 10, 1853", "Democrat", "Joseph A. Wright", ""], ["3", "Ratliff Boon", "September 12, 1822", "January 30, 1824", "Democratic-Republican", "William Hendricks", ""], ["12", "Ashbel P. Willard", "January 10, 1853", "January 12, 1857", "Democrat", "Joseph A. Wright", ""], ["22", "Ira Joy Chase", "January 14, 1889", "November 24, 1891", "Republican", "Alvin Peterson Hovey", "acting"], ["13", "Abram A. Hammond", "January 12, 1857", "October 3, 1860", "Democrat", "Ashbel P. Willard", ""], ["47", "Joe E. Kernan", "January 13, 1997", "September 13, 2003", "Democrat", "Frank O'Bannon", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 has there been a lieutenant governor of indiana? | 198 | 128 | Answer: |
Table InputTable: [["Eps #", "Prod #", "Title", "Summary", "Air Date"], ["12", "13", "Return Of the Mole Man", "The Mole Man is creating earthquakes and causing buildings to sink deep into the Earth. In addition, he and his Moloids kidnap Susan. The Mole Man as usual has been expecting the other three and sends them back to the surface to tell the Army not to get involved. They manage to halt them and seek an alternate entrance in the underworld. Johnny rescues Susan, then they penetrate the laboratory. They all return the buildings to the surface and escape the exploding caves.", "11/25/1967"], ["2", "3", "Diablo", "The Fantastic Four find a ruined castle in the middle of a forest in Transylvania. Ben is summoned by Diablo and unable to resist, opens Diablo's prison, unleashing him and later brainwashing Ben. Diablo tricks the world into thinking he has the power to help them. The world then realises what a fraud Diablo really is. The Fantastic Four seize this opportunity to attack Diabloβs castle. After getting far in the dungeons, the four get captured. Ben escapes, releases the others and they defeat Diablo.", "9/16/1967"], ["13", "19", "Rama-Tut", "After coming back from vacation Reed tells Ben an interesting theory on attempting to restore him. They head to Dr. Doomβs deserted castle to use the time machine the doctor left behind. In 2000 B.C the four weaken during a fight and are taken by Pharaoh Rama-Tut, who is a lot more than he would seem at first sight. Susan is to be Rama-Tutβs queen while the other three are put to work with some mind control. Ben turns back to his former self. As he rescues Susan, he is once again the Thing. The four battle Rama-Tut to his sphinx. Finally, they destroy his sphinx and return to their own time.", "12/9/1967"], ["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. Doomβs 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. Doomβs 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. Doomβs global destruction for good.", "10/28/1967"], ["3", "7", "The Way It All Began", "While on a television show, Reed recalls the time he first met Victor von Doom before he became Dr. Doom. He had Ben as his roommate at university. Victor was working on dangerous experiments, especially a test that brought him to the hospital and got him expelled from university. Worse than that, the test altered his face and he swore revenge on Reed having to hide his work from him. Ben and Reed became soldiers in World War II. Ben, Susan, Johnny and Reed all went aboard a space rocket for space exploration. And so the origin of the Fantastic Four began. Dr. Doom confronts the Fantastic Four on the television show and briefs them on his origin. After that Dr. Doom attempts to get his revenge, but fails and escapes only to crash.", "9/23/1967"], ["10", "12", "Demon in the Deep", "The Fantastic Four beat the criminal forces working for Dr. Gamma, and blow up the island with its secret weapons. While escaping, Dr. Gamma is infected by the radiation levels in the seabed and morphs into some creature. Johnny is flustered with being moved around and quits from the Fantastic Four. In the town Johnny goes to, there have been sightings of the Gamma Ray. Johnny defeats the Gamma Ray by himself, but he comes back with the hideous giant sea monster Giganto. Johnny rejoins the Fantastic Four. Ben succeeds in eliminating the sea monster. The Gamma Ray is defeated but not finished.", "11/11/1967"], ["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 Attumaβs 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"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 ago did danger in the depths air after demon in the deep? | 7 days | 128 | Answer: |
Table InputTable: [["School Name", "Low grade", "High grade", "Students (K-12)", "FTE Teachers", "Student/teacher ratio"], ["Bethany Lutheran School", "PK", "8", "28", "3.6", "7.78"], ["Peace Lutheran School", "PK", "8", "229", "", ""], ["Immanuel Lutheran School", "PK", "8", "82", "5.6", "14.64"], ["Holy Cross Lutheran School", "PK", "8", "135", "7.9", "17.09"], ["Sheridan Road Christian School", "K", "12", "42", "5.9", "7.12"], ["St Pauls Lutheran School", "PK", "8", "155", "9.6", "16.15"], ["Christ Lutheran School", "K", "8", "12", "2", "6"], ["Valley Lutheran High School", "9", "12", "344", "21", "16.38"], ["Grace Christian School", "PK", "12", "117", "13", "9"], ["Community Baptist Christian School", "PK", "12", "120", "9.8", "12.24"], ["Nouvel Catholic Central High School", "9", "12", "505", "37", "13.65"], ["St John's Evangelical Lutheran School", "K", "8", "32", "3", "10.67"], ["St Thomas Aquinas Elementary School", "K", "8", "403", "25", "16.12"], ["St Stephen Elementary School", "PK", "8", "364", "23.1", "15.76"], ["St Helen Elementary School", "K", "8", "182", "10.9", "16.7"], ["Tri-City Seventh-Day Adventist School", "1", "8", "18", "2.1", "8.57"], ["Bethlehem Lutheran School", "PK", "8", "182", "10", "18.2"], ["Michigan Lutheran Seminary", "9", "12", "313", "31", "10.1"], ["Good Shepherd Early Childhood", "PK", "K", "20", "1", "20"], ["Notes", "", "", "", "", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 private schools in saginaw that offer classes from kindergarten to high school graduation? | 1 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "NetherlandsΒ (NED)", "4", "3", "2", "9"], ["2", "United StatesΒ (USA)", "2", "1", "1", "4"], ["3", "West GermanyΒ (FRG)", "2", "0", "0", "2"], ["4", "NorwayΒ (NOR)", "0", "2", "2", "4"], ["5", "Soviet UnionΒ (URS)", "0", "1", "2", "3"], ["6", "SwedenΒ (SWE)", "0", "1", "1", "2"], ["", "Total", "8", "8", "8", "24"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 medals did the netherlands and united states have combined? | 13 | 128 | Answer: |
Table InputTable: [["Name of place", "Number of counties", "Principal county", "Lower zip code", "Upper zip code"], ["Sides", "1", "Indiana County", "", ""], ["Sidell", "1", "Clarion County", "", ""], ["Shanktown", "1", "Indiana County", "15777", ""], ["Shamburg", "1", "Clarion County", "", ""], ["Schills", "1", "Clarion County", "", ""], ["Sandy Hollow", "1", "Clarion County", "16248", ""], ["Saltsburg", "1", "Indiana County", "15681", ""], ["Shippenville", "1", "Clarion County", "16254", ""], ["Scotch Hill", "1", "Clarion County", "16233", ""], ["Shelocta", "1", "Indiana County", "15774", ""], ["St. Petersburg", "1", "Clarion County", "16054", ""], ["Salem Township", "1", "Clarion County", "", ""], ["St. Charles", "1", "Clarion County", "16242", ""], ["Shannondale", "1", "Clarion County", "16240", ""], ["Seamentown", "1", "Indiana County", "15729", ""], ["Sarah Furnace", "1", "Clarion County", "16248", ""], ["Savan", "1", "Indiana County", "", ""], ["Sidney", "1", "Indiana County", "", ""], ["Shunk", "1", "Sullivan County", "17768", ""], ["Searights", "1", "Fayette County", "15401", ""], ["Shamrock", "1", "Fayette County", "15401", ""], ["Salisbury Junction", "1", "Somerset County", "15552", ""], ["Sample Run", "1", "Indiana County", "15728", ""], ["Satterfield Junction", "1", "Sullivan County", "18614", ""], ["Shehawken", "1", "Wayne County", "18462", ""], ["Shamrock", "1", "Somerset County", "", ""], ["Shadyside", "1", "Allegheny County", "15232", ""], ["Schofield Corners", "1", "Mercer County", "", ""], ["Saltlick Township", "1", "Fayette County", "", ""], ["Shado-wood Village", "1", "Indiana County", "15701", ""], ["Sabula", "1", "Clearfield County", "15801", ""], ["Shaners Crossroads", "1", "Westmoreland County", "15656", ""], ["Schenley", "1", "Armstrong County", "15682", ""], ["Savage", "1", "Somerset County", "", ""], ["Schaefferstown", "1", "Lebanon County", "17088", ""], ["Shade Gap", "1", "Huntingdon County", "17255", ""], ["Shenandoah Junction", "1", "Schuylkill County", "17976", ""], ["Shohola", "1", "Pike County", "18458", ""], ["Shirks Corner", "1", "Montgomery County", "19473", ""], ["Schellsburg", "1", "Bedford County", "15559", ""], ["Shrewsbury Township", "1", "Lycoming County", "", ""], ["Seward", "1", "Westmoreland County", "15954", ""], ["Salisbury", "1", "Somerset County", "15558", ""], ["Shaffers Corner", "1", "Fayette County", "15416", ""], ["Sipesville", "1", "Somerset County", "15561", ""], ["Shippensburg", "2", "Cumberland County", "17257", ""], ["Shrewsbury Township", "1", "Sullivan County", "", ""], ["Sankertown", "1", "Cambria County", "16630", ""], ["Sandy Hill", "1", "Montgomery County", "19401", ""], ["Salida", "1", "Allegheny County", "15227", ""], ["Shirleysburg", "1", "Huntingdon County", "17260", ""], ["Shades Glen", "1", "Luzerne County", "18661", ""], ["Sarversville", "1", "Butler County", "16055", ""], ["Satterfield", "1", "Sullivan County", "18614", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 sides located in clarion or indiana county? | Indiana County | 128 | Answer: |
Table InputTable: [["Team", "No", "Driver", "Class", "Rounds"], ["Fortec Motorsport", "25", "George Katsinis", "", "All"], ["Fortec Motorsport", "24", "Jack Harvey", "", "All"], ["Fortec Motorsport", "26", "Christof von GrΓΌnigen", "", "All"], ["Josef Kaufmann Racing", "6", "Petri Suvanto", "R", "All"], ["Josef Kaufmann Racing", "4", "Robin Frijns", "", "All"], ["Eifelland Racing", "20", "Marc Coleselli", "R", "All"], ["MΓΌcke Motorsport", "8", "Timmy Hansen", "", "All"], ["MΓΌcke Motorsport", "7", "Maciej Bernacik", "R", "All"], ["Josef Kaufmann Racing", "5", "Hannes van Asseldonk", "R", "All"], ["Eifelland Racing", "19", "CΓ΄me Ledogar", "", "All"], ["Eifelland Racing", "18", "Facundo Regalia", "", "All"], ["EuroInternational", "11", "Daniil Kvyat", "R", "All"], ["DAMS", "17", "Fahmi Ilyas", "", "1β6"], ["EuroInternational", "12", "Carlos Sainz, Jr.", "R", "All"], ["DAMS", "17", "Dustin Sofyan", "", "8"], ["EuroInternational", "14", "Michael Lewis", "", "All"], ["DAMS", "16", "Dustin Sofyan", "", "5"], ["DAMS", "16", "Luciano Bacheta", "", "7β8"], ["DAMS", "15", "Javier TarancΓ³n", "", "All"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 first driver listed on this chart? | Robin Frijns | 128 | Answer: |
Table InputTable: [["City", "County", "Population (2011)", "Population (2002)", "Altitude (m)", "Year status\\ngranted* or\\nfirst attestedβ "], ["PloieΘti", "Prahova", "209,945", "232,527", "150", "1596β "], ["BoldeΘti-ScΔeni", "Prahova", "11,137", "11,505", "", ""], ["Plopeni", "Prahova", "7,718", "10,083", "", "1968*"], ["GΔeΘti", "DΓ’mboviΘa", "13,317", "16,598", "", ""], ["PiteΘti", "ArgeΘ", "155,383", "168,458", "287", "1388β "], ["BudeΘti", "CΔlΔraΘi", "7,725", "9,596", "", "1989*"], ["UrlaΘi", "Prahova", "10,541", "11,858", "", ""], ["BerbeΘti", "VΓ’lcea", "4,836", "5,704", "", "2003*"], ["CosteΘti", "ArgeΘ", "10,375", "12,091", "", "1968*"], ["OrΘova", "MehedinΘi", "10,441", "15,379", "", ""], ["CΔzΔneΘti", "IalomiΘa", "3,271", "3,641", "", "2004*"], ["PopeΘti-Leordeni", "Ilfov", "21,895", "15,115", "", "2004*"], ["Chitila", "Ilfov", "14,184", "12,643", "", "2005*"], ["Moldova NouΔ", "CaraΘ-Severin", "12,350", "15,112", "", "1968*"], ["Bucharest", "-", "1,883,425", "1,926,334", "85", "1459β "], ["Slobozia", "IalomiΘa", "45,891", "52,677", "", ""], ["FocΘani", "Vrancea", "79,315", "103,219", "55", "1575β "], ["Breaza", "Prahova", "15,928", "18,863", "", "1952*"], ["Topoloveni", "ArgeΘ", "10,219", "10,329", "", "1968*"], ["Moreni", "DΓ’mboviΘa", "18,687", "22,868", "", "1948*"], ["SΔcele", "BraΘov", "30,798", "29,967", "", "1971*"], ["Mioveni", "ArgeΘ", "31,998", "35,849", "", "1989*"], ["Θtei", "Bihor", "6,529", "9,466", "", "1956*"], ["SlΔnic Moldova", "BacΔu", "4,198", "5,375", "", ""], ["PaΘcani", "IaΘi", "33,745", "42,172", "", ""], ["Bolintin-Vale", "Giurgiu", "12,929", "11,464", "", "1989*"], ["Ghimbav", "BraΘov", "4,698", "5,112", "", "2002*"], ["ZΔrneΘti", "BraΘov", "23,476", "26,520", "", "1951*"], ["Podu Iloaiei", "IaΘi", "9,573", "9,739", "", "2005*"], ["Mizil", "Prahova", "14,312", "17,075", "", "1830*"], ["Gheorgheni", "Harghita", "18,377", "21,245", "", ""], ["Otopeni", "Ilfov", "13,861", "10,515", "", "2000*"], ["MihΔileΘti", "Giurgiu", "7,923", "7,161", "", ""], ["SlΔnic", "Prahova", "6,034", "7,249", "", "1892*"], ["Sighetu MarmaΘiei", "MaramureΘ", "37,640", "41,246", "", ""], ["Jimbolia", "TimiΘ", "10,808", "10,497", "", "1950*"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 number of the population 2011 for the city of ploiesti? | 209,945 | 128 | Answer: |
Table InputTable: [["Year", "Premiers", "Score", "Runners Up", "Score"], ["2008", "Cairns Saints", "12.15 (87)", "North Cairns Tigers", "2.9 (21)"], ["2007", "Centrals Trinity Beach Bulldogs", "14.16 (100)", "Cairns Saints", "11.2 (68)"], ["2006", "Manunda Hawks", "11.11 (77)", "Centrals Trinity Beach Bulldogs", "10.9 (69)"], ["2012", "Cairns Saints", "17.6 (108)", "North Cairns Tigers", "11.12 (78)"], ["2010", "North Cairns Tigers", "8.10 (58)", "Port Douglas Crocs", "8.5 (53)"], ["2003", "Centrals Trinity Beach Bulldogs", "14.11 (95)", "North Cairns", "6.7 (43)"], ["2013", "North Cairns Tigers", "14.14 (98)", "Port Douglas Crocs", "13.6 (84)"], ["2004", "Port Douglas Crocs", "17.13 (115)", "North Cairns Tigers", "8.9 (57)"], ["2009", "South Cairns Cutters", "9.11 (65)", "Cairns Saints", "9.4 (58)"], ["2011", "Manunda Hawks", "11.8 (74)", "Port Douglas Crocs", "6.9 (45)"], ["2005", "Port Douglas Crocs", "19.14 (128)", "Cairns Saints", "4.11 (35)"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 under runners up after 2007 had more than 10 points? | 2 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["3", "West GermanyΒ (FRG)", "2", "0", "0", "2"], ["5", "Soviet UnionΒ (URS)", "0", "1", "2", "3"], ["4", "NorwayΒ (NOR)", "0", "2", "2", "4"], ["6", "SwedenΒ (SWE)", "0", "1", "1", "2"], ["1", "NetherlandsΒ (NED)", "4", "3", "2", "9"], ["2", "United StatesΒ (USA)", "2", "1", "1", "4"], ["", "Total", "8", "8", "8", "24"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 country had the least amount of bronze medals? | West Germany | 128 | Answer: |
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["12", "24", "Paolo Barilla", "Minardi-Ford", "62", "+ 2 Laps", "24", ""], ["9", "8", "Stefano Modena", "Brabham-Judd", "62", "+ 2 Laps", "20", ""], ["13", "26", "Philippe Alliot", "Ligier-Ford", "61", "+ 3 Laps", "22", ""], ["10", "25", "Nicola Larini", "Ligier-Ford", "62", "+ 2 Laps", "21", ""], ["11", "21", "Emanuele Pirro", "Dallara-Ford", "62", "+ 2 Laps", "19", ""], ["7", "10", "Alex Caffi", "Arrows-Ford", "63", "+ 1 Lap", "17", ""], ["DNQ", "7", "David Brabham", "Brabham-Judd", "", "", "", ""], ["2", "5", "Thierry Boutsen", "Williams-Renault", "64", "+ 39.092", "4", "6"], ["14", "28", "Gerhard Berger", "McLaren-Honda", "60", "Throttle", "3", ""], ["8", "4", "Jean Alesi", "Tyrrell-Ford", "63", "+ 1 Lap", "6", ""], ["1", "1", "Alain Prost", "Ferrari", "64", "1:18:30.999", "5", "9"], ["Ret", "12", "Martin Donnelly", "Lotus-Lamborghini", "48", "Engine", "14", ""], ["3", "27", "Ayrton Senna", "McLaren-Honda", "64", "+ 43.088", "2", "4"], ["DNPQ", "31", "Bertrand Gachot", "Coloni-Subaru", "", "", "", ""], ["Ret", "6", "Riccardo Patrese", "Williams-Renault", "26", "Chassis", "7", ""], ["5", "20", "Nelson Piquet", "Benetton-Ford", "64", "+ 1:24.003", "11", "2"], ["4", "29", "Γric Bernard", "Lola-Lamborghini", "64", "+ 1:15.302", "8", "3"], ["Ret", "11", "Derek Warwick", "Lotus-Lamborghini", "46", "Engine", "16", ""], ["6", "30", "Aguri Suzuki", "Lola-Lamborghini", "63", "+ 1 Lap", "9", "1"], ["Ret", "9", "Michele Alboreto", "Arrows-Ford", "37", "Engine", "25", ""], ["Ret", "16", "Ivan Capelli", "Leyton House-Judd", "48", "Fuel Leak", "10", ""], ["Ret", "2", "Nigel Mansell", "Ferrari", "55", "Gearbox", "1", ""], ["Ret", "19", "Alessandro Nannini", "Benetton-Ford", "15", "Collision", "13", ""], ["Ret", "17", "Gabriele Tarquini", "AGS-Ford", "41", "Engine", "26", ""], ["Ret", "22", "Andrea de Cesaris", "Dallara-Ford", "12", "Fuel System", "23", ""], ["DNPQ", "33", "Roberto Moreno", "EuroBrun-Judd", "", "", "", ""], ["DNQ", "36", "JJ Lehto", "Onyx-Ford", "", "", "", ""], ["DNPQ", "34", "Claudio Langes", "EuroBrun-Judd", "", "", "", ""], ["Ret", "23", "Pierluigi Martini", "Minardi-Ford", "3", "Alternator", "18", ""], ["Ret", "3", "Satoru Nakajima", "Tyrrell-Ford", "20", "Electrical", "12", ""], ["DNPQ", "18", "Yannick Dalmas", "AGS-Ford", "", "", "", ""], ["DNS", "15", "MaurΓcio Gugelmin", "Leyton House-Judd", "0", "Fuel Pump", "15", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:name the number of drivers that completed 64 laps. | 5 | 128 | Answer: |
Table InputTable: [["Rnd", "Circuit", "GTP Winning Team\\nGTP Winning Drivers", "GTO Winning Team\\nGTO Winning Drivers", "GTU Winning Team\\nGTU Winning Drivers", "Results"], ["2", "Miami", "#04 Group 44", "#47 Dingman Bros. Racing", "#99 All American Racers", "Results"], ["1", "Daytona", "#00 Kreepy Krauly Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["14", "Pocono", "#14 Holbert Racing", "#65 English Enterprises", "#87 Performance Motorsports", "Results"], ["4", "Road Atlanta", "#16 Marty Hinze Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["2", "Miami", "Doc Bundy\\n Brian Redman", "Walt Bohren", "Chris Cord", "Results"], ["7", "Charlotte", "#56 Blue Thunder Racing", "#4 Stratagraph Inc.", "#99 All American Racers", "Results"], ["9", "Mid-Ohio", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["15", "Michigan", "#56 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["11", "Portland", "#56 Blue Thunder Racing", "#51 Corvette", "#76 Malibu Grand Prix", "Results"], ["13", "Road America", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["8", "Lime Rock", "#00 Kreepy Krauly Racing", "#38 Mandeville Auto Tech", "#76 Malibu Grand Prix", "Results"], ["16", "Watkins Glen", "Dale Whittington\\n Randy Lanier", "Chester Vincentz\\n Jim Mullen", "Clay Young", "Results"], ["3", "Sebring", "#48 DeNarvaez Enterprises", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["6", "Laguna Seca", "Randy Lanier", "John Bauer", "Jim Adams", "Results"], ["8", "Lime Rock", "Sarel van der Merwe", "Roger Mandeville", "Jack Baldwin", "Results"], ["17", "Daytona", "Al Holbert\\n Derek Bell", "Wally Dallenbach, Jr.\\n Willy T. Ribbs", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["17", "Daytona", "#14 Holbert Racing", "#67 Roush Racing", "#87 Performance Motorsports", "Results"], ["12", "Sears Point", "Bill Whittington", "John Bauer", "Dennis Aase", "Results"], ["9", "Mid-Ohio", "Al Holbert\\n Derek Bell", "Chester Vincentz\\n Dave White", "Jack Dunham\\n Jeff Kline", "Results"], ["14", "Pocono", "Al Holbert\\n Derek Bell", "Gene Felton", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["13", "Road America", "Al Holbert\\n Derek Bell", "Chester Vincentz\\n Jim Mullen", "Jack Dunham\\n Jeff Kline", "Results"], ["12", "Sears Point", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#98 All American Racers", "Results"], ["10", "Watkins Glen", "#14 Holbert Racing", "#91 Electrodyne", "#87 Performance Motorsports", "Results"], ["10", "Watkins Glen", "Al Holbert\\n Jim Adams\\n Derek Bell", "Chester Vincentz\\n Jim Mullen", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["7", "Charlotte", "Bill Whittington\\n Randy Lanier", "Billy Hagan\\n Gene Felton", "Chris Cord\\n Jim Adams", "Results"], ["4", "Road Atlanta", "Don Whittington", "Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed", "Results"], ["11", "Portland", "Bill Whittington\\n Randy Lanier", "David Schroeder\\n Tom Hendrickson", "Jack Baldwin", "Results"], ["16", "Watkins Glen", "#57 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["5", "Riverside", "#56 Blue Thunder Racing", "#38 Mandeville Auto Tech", "#87 Performance Motorsports", "Results"], ["3", "Sebring", "Mauricio DeNarvaez\\n Hans Heyer\\n Stefan Johansson", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed\\n Ira Young", "Results"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 circuit was next after round two? | Sebring | 128 | Answer: |
Table InputTable: [["Rank", "Athlete", "Nationality", "2.15", "2.20", "2.24", "2.27", "Result", "Notes"], ["9.", "Ramsay Carelse", "South Africa", "xo", "xo", "o", "xxx", "2.24", ""], ["1.", "Yaroslav Rybakov", "Russia", "o", "o", "o", "o", "2.27", "q"], ["1.", "Andrey Tereshin", "Russia", "o", "o", "o", "o", "2.27", "q"], ["1.", "Linus ThΓΆrnblad", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["16.", "Roman Fricke", "Germany", "o", "xxx", "", "2.15", "", ""], ["8.", "Robert Wolski", "Poland", "xo", "o", "o", "xxx", "2.24", "q"], ["1.", "Stefan Holm", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["1.", "Andriy Sokolovskyy", "Ukraine", "o", "o", "o", "o", "2.27", "q"], ["16.", "Adam Shunk", "United States", "o", "xxx", "", "2.15", "", ""], ["10.", "Nicola Ciotti", "Italy", "o", "o", "xo", "xxx", "2.24", ""], ["13.", "TomΓ‘Ε‘ Janku", "Czech Republic", "o", "o", "xxo", "xxx", "2.24", ""], ["13.", "Mustapha Raifak", "France", "o", "o", "xxo", "xxx", "2.24", ""], ["7.", "Giulio Ciotti", "Italy", "o", "o", "o", "xxx", "2.24", "q"], ["15.", "Svatoslav Ton", "Czech Republic", "o", "xo", "xxx", "", "2.20", ""], ["10.", "Tora Harris", "United States", "o", "o", "xo", "xxx", "2.24", ""], ["10.", "Wojciech Theiner", "Poland", "o", "o", "xo", "xxx", "2.24", ""], ["1.", "VΓctor Moya", "Cuba", "o", "o", "o", "o", "2.27", "q, PB"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 next highest qualifier after ramsay carelse? | Tora Harris | 128 | Answer: |
Table InputTable: [["Contestant", "Age", "Height", "Home City", "Rank"], ["Melisa PopaniciΔ", "16", "175Β cm (5Β ft 9 in)", "WΓΆrgl", "2nd Eliminated in Episode 10"], ["Christine Riener", "20", "181Β cm (5Β ft 11.25 in)", "Bludenz", "Eliminated in Episode 4"], ["Nadine Trinker", "21", "183Β cm (6Β ft 0 in)", "Bodensdorf", "Eliminated in Episode 9"], ["Dzejlana \"Lana\" BaltiΔ", "20", "179Β cm (5Β ft 10.5 in)", "Graz (originally from Bosnia)", "1st Eliminated in Episode 10"], ["Sabrina Angelika Rauch β ", "21", "175Β cm (5Β ft 9 in)", "Graz", "Eliminated in Episode 2"], ["Bianca Ebelsberger", "24", "179Β cm (5Β ft 10.5 in)", "Aurach am Hongar", "Eliminated in Episode 9"], ["Isabelle Raisa", "16", "170Β cm (5Β ft 7 in)", "Vienna", "Eliminated in Episode 1"], ["Yemisi Rieger", "17", "177Β cm (5Β ft 9.5 in)", "Vienna", "Eliminated in Episode 7"], ["Katharina MihaloviΔ", "23", "179Β cm (5Β ft 10.5 in)", "Vienna", "Eliminated in Episode 2"], ["Alina Chlebecek", "18", "170Β cm (5Β ft 7 in)", "Deutsch-Wagram", "Eliminated in Episode 1"], ["NataΕ‘a MariΔ", "16", "175Β cm (5Β ft 9 in)", "Liefering (originally from Serbia)", "Eliminated in Episode 3"], ["Teodora-MΔdΔlina Andreica", "17", "177Β cm (5Β ft 9.5 in)", "Romania", "Eliminated in Episode 6"], ["Izabela Pop KostiΔ", "20", "170Β cm (5Β ft 7 in)", "Vienna (originally from Bosnia)", "Eliminated in Episode 8"], ["Gina Zeneb Adamu", "17", "175Β cm (5Β ft 9 in)", "Bad VΓΆslau", "Runner-Up"], ["Michaela Schopf", "21", "172Β cm (5Β ft 7.5 in)", "Salzburg (originally from Germany)", "Quit in Episode 4"], ["Antonia Maria Hausmair", "16", "175Β cm (5Β ft 9 in)", "Siegendorf", "Winner"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 contestant to be eliminated? | Melisa PopaniciΔ | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event"], ["1996", "World Junior Championships", "Sydney, Australia", "2nd", "3000 m st."], ["2001", "IAAF Grand Prix Final", "Melbourne, Australia", "4th", "3000 m st."], ["", "Commonwealth Games", "Kuala Lumpur, Malaysia", "3rd", "3000 m st."], ["2005", "World Athletics Final", "Monte Carlo, Monaco", "8th", "3000 m st."], ["2004", "World Athletics Final", "Monte Carlo, Monaco", "4th", "3000 m st."], ["1999", "All-Africa Games", "Johannesburg, South Africa", "1st", "3000 m st."], ["1998", "World Cross Country Championships", "Marrakech, Morocco", "8th", "Short race"], ["", "IAAF Grand Prix Final", "Munich, Germany", "4th", "3000 m st."]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 name of the last competition in australia? | IAAF Grand Prix Final | 128 | Answer: |
Table InputTable: [["Pos", "Rider", "Manufacturer", "Time/Retired", "Points"], ["2", "Valentino Rossi", "Aprilia", "+0.180", "20"], ["6", "Ralf Waldmann", "Aprilia", "+7.019", "10"], ["20", "Lucas Oliver Bulto", "Yamaha", "+1:25.758", ""], ["16", "Luca Boscoscuro", "TSR-Honda", "+56.432", ""], ["Ret", "Roberto Rolfo", "Aprilia", "Retirement", ""], ["1", "Loris Capirossi", "Honda", "38:04.730", "25"], ["Ret", "Maurice Bolwerk", "TSR-Honda", "Retirement", ""], ["23", "Arno Visscher", "Aprilia", "+1:40.635", ""], ["19", "Fonsi Nieto", "Yamaha", "+1:25.622", ""], ["17", "Johann Stigefelt", "Yamaha", "+1:07.433", ""], ["8", "Stefano Perugini", "Honda", "+20.891", "8"], ["Ret", "Andre Romein", "Honda", "Retirement", ""], ["18", "Julien Allemand", "TSR-Honda", "+1:16.347", ""], ["Ret", "Marcellino Lucchi", "Aprilia", "Retirement", ""], ["15", "Jarno Janssen", "TSR-Honda", "+56.248", "1"], ["21", "David Garcia", "Yamaha", "+1:33.867", ""], ["12", "Sebastian Porto", "Yamaha", "+27.054", "4"], ["22", "Rudie Markink", "Aprilia", "+1:40.280", ""], ["11", "Alex Hofmann", "TSR-Honda", "+26.933", "5"], ["5", "Shinya Nakano", "Yamaha", "+0.742", "11"], ["14", "Masaki Tokudome", "TSR-Honda", "+33.161", "2"], ["13", "Tomomi Manako", "Yamaha", "+27.903", "3"], ["24", "Henk Van De Lagemaat", "Honda", "+1 Lap", ""], ["7", "Franco Battaini", "Aprilia", "+20.889", "9"], ["10", "Anthony West", "TSR-Honda", "+26.816", "6"], ["9", "Jason Vincent", "Honda", "+21.310", "7"], ["3", "Jeremy McWilliams", "Aprilia", "+0.534", "16"], ["4", "Tohru Ukawa", "Honda", "+0.537", "13"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 between valentino rossi and ralf waldmann's time? | 6.839 | 128 | Answer: |
Table InputTable: [["", "Chronological\\nNo.", "Date\\n(New style)", "Water level\\ncm", "Peak hour"], ["32", "76", "29 September 1788", "237", "β"], ["14", "25", "10 September 1736", "261", ""], ["8", "14", "1 November 1726", "270", "β"], ["1", "84", "19 November 1824", "421", "14:00"], ["27", "177", "26 November 1898", "240", "23:30"], ["37", "41", "26 October 1752", "234", "12:00"], ["36", "37", "17 October 1744", "234", "β"], ["23", "45", "29 September 1756", "242", ""], ["24", "136", "20 October 1873", "242", "β"], ["25", "175", "4 November 1897", "242", "12:00"], ["33", "145", "26 November 1874", "237", "4:00"], ["19", "144", "29 October 1874", "252", "4:00"], ["20", "55", "20 November 1764", "244", "β"], ["7", "9", "2 October 1723", "272", "β"], ["47", "81", "6 September 1802", "224", "daytime"], ["46", "211", "3 January 1925", "225", "21:30"], ["18", "83", "24 January 1822", "254", "night"], ["11", "86", "20 August 1831", "264", "night"], ["6", "39", "22 October 1752", "280", "10:00"], ["2", "210", "23 September 1924", "380", "19:15"], ["48", "122", "19 May 1865", "224", "9:10"], ["34", "171", "2 November 1895", "237", "3:00"], ["38", "43", "11 December 1752", "234", "night"], ["9", "183", "13 November 1903", "269", "9:00"], ["45", "116", "8 October 1863", "227", "2:00"], ["42", "125", "19 January 1866", "229", "10:00"], ["43", "208", "24 November 1922", "228", "19:15"], ["16", "215", "15 October 1929", "258", "17:15"], ["3", "71", "9 September 1777", "321", "morning"], ["10", "7", "5 November 1721", "265", "daytime"], ["39", "228", "14 September 1938", "233", "2:25"], ["31", "18", "12 October 1729", "237", "10:00"], ["29", "219", "8 January 1932", "239", "3:00"], ["28", "260", "20 December 1973", "240", "7:15"], ["30", "225", "8 October 1935", "239", "5:50"], ["35", "227", "9 September 1937", "236", "5:30"], ["21", "201", "17 November 1917", "244", "6:50"], ["22", "254", "18 October 1967", "244", "13:30"], ["49", "202", "24 August 1918", "224", "9:10"], ["26", "261", "17 November 1974", "242", "1:00"], ["12", "3", "9 September 1706", "262", "daytime"], ["15", "298", "6 December 1986", "260", "13:30"], ["50", "242", "14 October 1954", "222", "21:00"], ["4", "244", "15 October 1955", "293", "20:45"], ["5", "264", "29 September 1975", "281", "4:00"], ["40", "269", "7 September 1977", "231", "16:50"], ["41", "292", "1 January 1984", "231", "21:20"], ["13", "319", "30 November 1999", "262", "4:35"], ["44", "315", "12 October 1994", "228", "13:50"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 entries in the 1800s have a water level above 250? | 4 | 128 | Answer: |
Table InputTable: [["Name", "City", "Hospital beds", "Operating rooms", "Total", "Trauma designation", "Affiliation", "Notes"], ["Hugh Chatham Memorial Hospital", "Elkin", "220", "8", "228", "-", "QHR", "-"], ["Chatham Hospital", "Siler City", "25", "3", "28", "-", "UNC", "-"], ["Vidant Edgecombe Hospital", "Tarboro", "117", "8", "125", "-", "Vidant", "-"], ["Durham Regional Hospital", "Durham", "369", "19", "388", "-", "Duke", "-"], ["Lenoir Memorial Hospital", "Kinston", "261", "12", "273", "-", "-", "-"], ["Martin General Hospital", "Williamston", "49", "3", "52", "-", "-", "-"], ["Grace Hospital", "Morganton", "184", "7", "191", "-", "CHS", "-"], ["Vidant Beaufort Hospital", "Washington", "142", "7", "149", "-", "Vidant", "-"], ["Select Specialty Hospital - Durham", "Durham", "30", "0", "30", "-", "-", "-"], ["Select Specialty Hospital - Winston-Salem", "Winston-Salem", "42", "0", "42", "-", "-", "-"], ["Kindred Hospital - Greensboro", "Greensboro", "124", "1", "125", "-", "-", "-"], ["North Carolina Specialty Hospital", "Durham", "18", "4", "22", "-", "-", "-"], ["Carolinas Specialty Hospital", "Charlotte", "40", "0", "40", "-", "-", "-"], ["Novant Health Medical Park Hospital", "Winston-Salem", "22", "13", "35", "-", "Novant", "-"], ["Gaston Memorial Hospital", "Gastonia", "435", "30", "465", "-", "-", "-"], ["FirstHealth Moore Regional Hospital Hoke Campus", "Pinehurst, North Carolina", "8", "1", "9", "-", "FirstHealth", "-"], ["Novant Health Rowan Medical Center", "Salisbury", "268", "17", "285", "-", "Novant", "-"], ["Kings Mountain Hospital", "Kings Mountain", "102", "3", "105", "-", "CHS", "-"], ["Morehead Memorial Hospital", "Eden", "229", "8", "237", "-", "QHR", "-"], ["Duke Health Raleigh Hospital", "Raleigh", "186", "16", "202", "-", "Duke", "-"], ["Crawley Memorial Hospital", "Boiling Springs", "50", "10", "60", "-", "CHS", "-"], ["Carolinas Medical Center-Lincoln", "Lincolnton", "101", "6", "107", "-", "CHS", "-"], ["University of North Carolina Hospitals", "Chapel Hill", "778", "48", "826", "Level I", "UNC", "Primary teaching hospital of University of North Carolina at Chapel Hill School of Medicine"], ["FirstHealth Richmond Memorial Hospital", "Rockingham", "150", "6", "156", "-", "FirstHealth", "-"], ["Carolinas Medical Center-Union", "Monroe", "227", "9", "236", "-", "CHS", "-"], ["Select Specialty Hospital-Greensboro", "Greensboro", "30", "0", "30", "-", "-", "-"], ["Stokes-Reynolds Memorial Hospital", "Danbury", "93", "5", "98", "-", "-", "-"], ["WakeMed Cary Hospital", "Cary", "192", "15", "207", "-", "WakeMed", "-"], ["J. Arthur Dosher Memorial Hospital", "Southport", "100", "4", "104", "-", "-", "-"], ["Lexington Memorial Hospital", "Lexington", "94", "6", "100", "-", "WFU", "-"], ["Granville Health System", "Oxford", "142", "4", "146", "-", "-", "-"], ["Our Community Hospital", "Scotland Neck", "100", "0", "100", "-", "-", "-"], ["Scotland Memorial Hospital and Edwin Morgan Center", "Laurinburg", "154", "8", "162", "-", "CHS", "-"], ["Caldwell Memorial Hospital", "Lenoir", "110", "10", "120", "-", "UNC", "-"], ["Iredell Memorial Hospital", "Statesville", "247", "14", "261", "-", "-", "-"], ["Highsmith-Rainey Specialty Hospital", "Fayetteville", "66", "7", "73", "-", "Cape Fear", "-"], ["Alleghany Memorial Hospital", "Sparta", "41", "2", "43", "-", "QHR", "-"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 hospital beds at chatham hospital? | 25 | 128 | Answer: |
Table InputTable: [["Date", "Venue", "Opponents", "Score", "Competition"], ["9 August", "Toyota (A)", "Japan", "2β2", "Toyota Cup"], ["8 August", "Toyota (N)", "Brazil", "0β0", "Toyota Cup"], ["20 March", "Fukuoka (A)", "Japan", "2β0", "Sanix Cup"], ["4 October", "Tashkent (N)", "India", "5β2", "AFC U-16 Championship (Group B)"], ["20 March", "Fukuoka (A)", "China PR", "1β0", "Sanix Cup"], ["6 October", "Tashkent (N)", "Indonesia", "9β0", "AFC U-16 Championship (Group B)"], ["8 October", "Tashkent (N)", "Syria", "1β1", "AFC U-16 Championship (Group B)"], ["10 August", "Toyota (N)", "United Arab Emirates", "6β0", "Toyota Cup"], ["12 October", "Tashkent (A)", "Uzbekistan", "3β0", "AFC U-16 Championship (Quarterfinal)"], ["18 October", "Tashkent (N)", "Iran", "1β2", "AFC U-16 Championship (Final)"], ["15 October", "Tashkent (N)", "Japan", "2β1", "AFC U-16 Championship (Semifinal)"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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? | yes | 128 | Answer: |
Table InputTable: [["Year", "Single", "Peak chart\\npositions\\nUS Country", "Peak chart\\npositions\\nCAN Country", "Album"], ["1984", "\"I'm a Country Song\"", "72", "β", "singles only"], ["1983", "\"You've Still Got Me\"", "71", "β", "singles only"], ["1977", "\"I'm Gonna Love You Right Out of This World\"", "21", "38", "singles only"], ["1983", "\"Hold Me\"", "67", "β", "singles only"], ["1972", "\"All Heaven Breaks Loose\"", "35", "β", "single only"], ["1971", "\"Ruby, You're Warm\"", "21", "16", "single only"], ["1976", "\"Mahogany Bridge\"", "84", "β", "singles only"], ["1974", "\"Loving You Has Changed My Life\"", "9", "21", "Hey There Girl"], ["1981", "\"Houston Blue\"", "88", "β", "singles only"], ["1979", "\"You Are My Rainbow\"", "36", "β", "singles only"], ["1968", "\"I'd Be Your Fool Again\"", "69", "β", "A World Called You"], ["1979", "\"Darlin'\"", "18", "36", "singles only"], ["1978", "\"I'll Be There (When You Get Lonely)\"", "22", "β", "Lovingly"], ["1979", "\"You're Amazing\"", "39", "β", "singles only"], ["1969", "\"A World Called You\"", "23", "β", "A World Called You"], ["1967", "\"Forbidden Fruit\"", "β", "β", "A World Called You"], ["1977", "\"Do You Hear My Heart Beat\"", "47", "β", "Lovingly"], ["1969", "\"Dearly Beloved\"", "59", "β", "single only"], ["1982", "\"Crown Prince of the Barroom\"", "92", "β", "singles only"], ["1977", "\"You and Me Alone\"", "24", "β", "Lovingly"], ["1970", "\"So Much in Love with You\"", "46", "β", "A World Called You"], ["1968", "\"You Touched My Heart\"", "37", "β", "A World Called You"], ["1976", "\"Whispers and Grins\"", "66", "β", "singles only"], ["1977", "\"I Love What My Woman Does to Me\"", "49", "33", "singles only"], ["1974", "\"I Just Can't Help Believin'\"", "59", "β", "Hey There Girl"], ["1973", "\"Just Thank Me\"", "17", "18", "Just Thank Me"], ["1973", "\"It'll Be Her\"", "22", "16", "Just Thank Me"], ["1968", "\"I'm in Love with My Wife\"", "38", "β", "A World Called You"], ["1983", "\"The Devil Is a Woman\"", "87", "β", "singles only"], ["1974", "\"Hey There Girl\"", "21", "42", "Hey There Girl"], ["1975", "\"It Takes a Whole Lot of Livin' in a House\"", "60", "β", "Whole Lotta Livin' in a House"], ["1972", "\"Need You\"", "9", "9", "Need You"], ["1977", "\"The Lady and the Baby\"", "76", "β", "singles only"], ["1972", "\"Goodbye\"", "38", "β", "Need You"], ["1978", "\"Let's Try to Remember\"", "32", "β", "Lovingly"], ["1971", "\"She Don't Make Me Cry\"", "19", "9", "She Don't Make Me Cry"], ["1978", "\"When a Woman Cries\"", "31", "β", "singles only"], ["1970", "\"I Wake Up in Heaven\"", "26", "β", "She Don't Make Me Cry"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 single did he get the same chart position in the us country as he did in the can country? | "Need You" | 128 | Answer: |
Table InputTable: [["Date", "Site", "Winning team", "Winning team", "Losing team", "Losing team", "Series"], ["September 30, 1989", "Fort Collins", "Air Force", "46", "Colorado State", "21", "AFA 19β8β1"], ["September 29, 1984", "Colorado Springs", "Air Force", "52", "Colorado State", "10", "AFA 14β8β1"], ["September 27, 1986", "Colorado Springs", "Air Force", "24", "Colorado State", "7", "AFA 16β8β1"], ["September 3, 1988", "Fort Collins", "Air Force", "29", "Colorado State", "23", "AFA 18β8β1"], ["September 17, 1998", "Colorado Springs", "Air Force", "30", "Colorado State", "27", "AFA 22β14β1"], ["September 16, 1995", "Colorado Springs", "Colorado State", "27", "Air Force", "20", "AFA 20β13β1"], ["September 3, 1994", "Colorado Springs", "Colorado State", "34", "Air Force", "21", "AFA 20β12β1"], ["September 1, 1990", "Colorado Springs", "Colorado State", "35", "Air Force", "33", "AFA 19β9β1"], ["September 7, 1991", "Fort Collins", "Air Force", "31", "Colorado State", "26", "AFA 20β9β1"], ["September 3, 1983", "Fort Collins", "Air Force", "34", "Colorado State", "13", "AFA 13β8β1"], ["September 29, 2005", "Fort Collins", "Colorado State", "41", "Air Force", "23", "AFA 24β19β1"], ["September 29, 2012", "Colorado Springs", "Air Force", "42", "Colorado State", "21", "AFA 31β19β1"], ["September 6, 1980", "Fort Collins", "Colorado State", "21", "Air Force", "9", "AFA 11β7β1"], ["October 3, 1981", "Colorado Springs", "Air Force", "28", "Colorado State", "14", "AFA 12β7β1"], ["November 2, 1996", "Colorado Springs", "Colorado State", "42", "Air Force", "41", "AFA 20β14β1"], ["September 20, 1997", "Fort Collins", "Air Force", "24", "Colorado State", "0", "AFA 21β14β1"], ["October 17, 1992", "Colorado Springs", "Colorado State", "32", "Air Force", "28", "AFA 20β10β1"], ["September 26, 1987", "Fort Collins", "Air Force", "27", "Colorado State", "19", "AFA 17β8β1"], ["September 11, 1993", "Fort Collins", "Colorado State", "8", "Air Force", "5", "AFA 20β11β1"], ["November 11, 2000", "Colorado Springs", "Air Force", "44", "Colorado State", "40", "AFA 23β15β1"], ["November 20, 2004", "Colorado Springs", "Air Force", "47", "Colorado State", "17", "AFA 24β18β1"], ["October 16, 1982", "Colorado Springs", "Colorado State", "21", "Air Force", "11", "AFA 12β8β1"], ["October 16, 2003", "Fort Collins", "Colorado State", "30", "Air Force", "20", "AFA 23β18β1"], ["October 9, 2010", "Colorado Springs", "Air Force", "49", "Colorado State", "27", "AFA 29β19β1"], ["October 31, 2002", "Colorado Springs", "Colorado State", "31", "Air Force", "12", "AFA 23β17β1"], ["November 8, 2008", "Colorado Springs", "Air Force", "38", "Colorado State", "17", "AFA 27β19β1"], ["October 19, 1985", "Fort Collins", "#10 Air Force", "35", "Colorado State", "19", "AFA 15β8β1"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 next winner after the air force won in september 1989? | Colorado State | 128 | Answer: |
Table InputTable: [["Date", "Competition", "Location", "Country", "Event", "Placing", "Rider", "Nationality"], ["1 November 2008", "2008β09 World Cup", "Manchester", "United Kingdom", "500 m time trial", "1", "Victoria Pendleton", "GBR"], ["1 November 2008", "2008β09 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Jason Kenny", "GBR"], ["31 October 2008", "2008β09 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Victoria Pendleton", "GBR"], ["2 November 2008", "5th International Keirin Event", "Manchester", "United Kingdom", "International keirin", "2", "Ross Edgar", "GBR"], ["2 November 2008", "2008β09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Ross Edgar", "GBR"], ["13 February 2009", "2008β09 World Cup", "Copenhagen", "Denmark", "Sprint", "1", "Victoria Pendleton", "GBR"], ["2 November 2008", "2008β09 World Cup", "Manchester", "United Kingdom", "Keirin", "1", "Victoria Pendleton", "GBR"], ["1 November 2009", "2009β10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Ross Edgar", "GBR"], ["13 February 2009", "2008β09 World Cup", "Copenhagen", "Denmark", "Team sprint", "1", "Chris Hoy", "GBR"], ["2 November 2008", "2008β09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jamie Staff", "GBR"], ["2 November 2008", "2008β09 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jason Kenny", "GBR"], ["1 November 2009", "2009β10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Chris Hoy", "GBR"], ["13 February 2009", "2008β09 World Cup", "Copenhagen", "Denmark", "Team sprint", "1", "Jamie Staff", "GBR"], ["13 February 2009", "2008β09 World Cup", "Copenhagen", "Denmark", "Team sprint", "1", "Jason Kenny", "GBR"], ["1 November 2009", "2009β10 World Cup", "Manchester", "United Kingdom", "Team sprint", "1", "Jamie Staff", "GBR"], ["30 October 2009", "2009β10 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Victoria Pendleton", "GBR"], ["31 October 2008", "2008β09 World Cup", "Manchester", "United Kingdom", "Keirin", "2", "Jason Kenny", "GBR"], ["30 October 2009", "2009β10 World Cup", "Manchester", "United Kingdom", "Sprint", "1", "Chris Hoy", "GBR"], ["30 October 2009", "2009β10 World Cup", "Manchester", "United Kingdom", "500 m time trial", "2", "Victoria Pendleton", "GBR"], ["30 October 2009", "2009β10 World Cup", "Manchester", "United Kingdom", "Keirin", "1", "Chris Hoy", "GBR"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 was the first date? | 31 October 2008 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["14", "UzbekistanΒ (UZB)", "0", "1", "3", "4"], ["11", "KyrgyzstanΒ (KGZ)", "1", "1", "0", "2"], ["8", "Sri LankaΒ (SRI)", "2", "0", "2", "4"], ["12", "KuwaitΒ (KUW)", "1", "0", "0", "1"], ["4", "KazakhstanΒ (KAZ)", "3", "4", "5", "12"], ["9", "QatarΒ (QAT)", "1", "4", "3", "8"], ["5", "South KoreaΒ (KOR)", "3", "2", "1", "6"], ["3", "Saudi ArabiaΒ (KSA)", "7", "1", "0", "8"], ["10", "ThailandΒ (THA)", "1", "1", "2", "4"], ["15", "IranΒ (IRI)", "0", "1", "0", "1"], ["12", "North KoreaΒ (PRK)", "1", "0", "0", "1"], ["7", "BahrainΒ (BRN)", "2", "1", "1", "4"], ["2", "IndiaΒ (IND)", "7", "6", "4", "17"], ["1", "ChinaΒ (CHN)", "14", "14", "13", "41"], ["6", "JapanΒ (JPN)", "2", "13", "8", "23"], ["Total", "Total", "45", "49", "42", "136"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 number of bronze medals won by uzbekistan? | 3 | 128 | Answer: |
Table InputTable: [["Stage", "Date", "Route", "Terrain", "Length", "Winner", "Race leader"], ["15", "17 July", "Nice β Gap", "Stage with mountain(s)", "233Β km (145Β mi)", "Jef DemuysereΒ (BEL)", "Antonin MagneΒ (FRA)"], ["9", "8 July", "Pau β Luchon", "Stage with mountain(s)", "231Β km (144Β mi)", "Antonin MagneΒ (FRA)", "Antonin MagneΒ (FRA)"], ["10", "10 July", "Luchon β Perpignan", "Stage with mountain(s)", "322Β km (200Β mi)", "Rafaele di PacoΒ (ITA)", "Antonin MagneΒ (FRA)"], ["14", "15 July", "Cannes β Nice", "Stage with mountain(s)", "132Β km (82Β mi)", "Eugenio GestriΒ (ITA)", "Antonin MagneΒ (FRA)"], ["20", "22 July", "Belfort β Colmar", "Stage with mountain(s)", "209Β km (130Β mi)", "AndrΓ© LeducqΒ (FRA)", "Antonin MagneΒ (FRA)"], ["18", "20 July", "Aix-les-Bains β Evian", "Stage with mountain(s)", "204Β km (127Β mi)", "Jef DemuysereΒ (BEL)", "Antonin MagneΒ (FRA)"], ["16", "18 July", "Gap β Grenoble", "Stage with mountain(s)", "102Β km (63Β mi)", "Charles PΓ©lissierΒ (FRA)", "Antonin MagneΒ (FRA)"], ["19", "21 July", "Evian β Belfort", "Stage with mountain(s)", "282Β km (175Β mi)", "Rafaele di PacoΒ (ITA)", "Antonin MagneΒ (FRA)"], ["17", "19 July", "Grenoble β Aix-les-Bains", "Stage with mountain(s)", "230Β km (140Β mi)", "Max BullaΒ (AUT)", "Antonin MagneΒ (FRA)"], ["3", "2 July", "Dinan β Brest", "Plain stage", "206Β km (128Β mi)", "Fabio BattesiniΒ (ITA)", "LΓ©on Le CalvezΒ (FRA)"], ["2", "1 July", "Caen β Dinan", "Plain stage", "212Β km (132Β mi)", "Max BullaΒ (AUT)", "Max BullaΒ (AUT)"], ["8", "7 July", "Bayonne β Pau", "Plain stage", "106Β km (66Β mi)", "Charles PΓ©lissierΒ (FRA)", "Charles PΓ©lissierΒ (FRA)"], ["23", "25 July", "Charleville β Malo-les-Bains", "Plain stage", "271Β km (168Β mi)", "Gaston RebryΒ (BEL)", "Antonin MagneΒ (FRA)"], ["22", "24 July", "Metz β Charleville", "Plain stage", "159Β km (99Β mi)", "Raffaele di PacoΒ (ITA)", "Antonin MagneΒ (FRA)"], ["5", "4 July", "Vannes β Les Sables d'Olonne", "Plain stage", "202Β km (126Β mi)", "Charles PΓ©lissierΒ (FRA)", "Charles PΓ©lissierΒ (FRA)\\nΒ Rafaele di PacoΒ (ITA)"], ["11", "12 July", "Perpignan β Montpellier", "Plain stage", "164Β km (102Β mi)", "Rafaele di PacoΒ (ITA)", "Antonin MagneΒ (FRA)"], ["7", "6 July", "Bordeaux β Bayonne", "Plain stage", "180Β km (110Β mi)", "GΓ©rard LonckeΒ (BEL)", "Rafaele di PacoΒ (ITA)"], ["1", "30 June", "Paris β Caen", "Plain stage", "208Β km (129Β mi)", "Alfred HaemerlinckΒ (BEL)", "Alfred HaemerlinckΒ (BEL)"], ["12", "13 July", "Montpellier β Marseille", "Plain stage", "207Β km (129Β mi)", "Max BullaΒ (AUT)", "Antonin MagneΒ (FRA)"], ["21", "23 July", "Colmar β Metz", "Plain stage", "192Β km (119Β mi)", "Rafaele di PacoΒ (ITA)", "Antonin MagneΒ (FRA)"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 each winner win on stage with mountain(s)? | no | 128 | Answer: |
Table InputTable: [["Sl no", "Name of the prabandham", "Starting from", "Ending with", "Number of pasurams", "Sung by"], ["5", "Thiruchchanda Viruththam", "752", "871", "120", "Thirumalisai alvar"], ["22", "Peria Thirumadal", "2674", "2674", "1", "Thirumangai alvar"], ["19", "Peria Thiruvandhadhi", "2585", "2671", "87", "Nammalvar"], ["", "Total number of pasurams", "", "", "3776", ""], ["3", "Nachiar Tirumozhi", "504", "646", "143", "Aandaal"], ["11", "Kurun Thandagam", "2032", "2051", "20", "Thirumangai alvar"], ["17", "Thiruviruththam", "2478", "2577", "100", "Nammalvar"], ["1", "Periazhvar Thirumozhi", "1", "473", "473", "Periyalvar"], ["10", "Peria Thirumozhi", "948", "2031", "1084", "Thirumangai alvar"], ["12", "Nedum Thandagam", "2052", "2081", "30", "Thirumangai alvar"], ["8", "Amalanadhi piran", "927", "936", "10", "Thiruppaan alvar"], ["2", "Thiruppavai", "474", "503", "30", "Aandaal"], ["21", "Siriya Thirumadal", "2673", "2673", "1", "Thirumangai alvar"], ["4", "Perumal Thirumozhi", "647", "751", "105", "Kulasekara alvar"], ["20", "Thiruvezhukkurrirukkai", "2672", "2672", "1", "Thirumangai alvar"], ["18", "Thiruvasiriyam", "2578", "2584", "7", "Nammalvar"], ["15", "Moonram Thiruvandhadhi", "2282", "2381", "100", "Peyalvar"], ["9", "Kanni Nun Siruththambu", "937", "947", "11", "Madhurakavi Alvar"], ["6", "Thirumalai", "872", "916", "45", "Thondaradippodi alvar"], ["16", "Naanmugan Thiruvandhadhi", "2382", "2477", "96", "Thirumalisai alvar"], ["13", "Mudhal Thiruvandhadhi", "2082", "2181", "100", "Poigai Alvar"], ["14", "Irandam Thiruvandhadhi", "2182", "2281", "100", "Bhoothathalvar"], ["7", "Thiruppalliyezhuchchi", "917", "926", "10", "Thondaradippodi alvar"], ["23", "Thiruvay Mozhi", "2674", "3776", "1102", "Nammalvar"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 name of the prabandham on the chart? | Thiruvay Mozhi | 128 | Answer: |
Table InputTable: [["Eps #", "Prod #", "Title", "Summary", "Air Date"], ["13", "19", "Rama-Tut", "After coming back from vacation Reed tells Ben an interesting theory on attempting to restore him. They head to Dr. Doomβs deserted castle to use the time machine the doctor left behind. In 2000 B.C the four weaken during a fight and are taken by Pharaoh Rama-Tut, who is a lot more than he would seem at first sight. Susan is to be Rama-Tutβs queen while the other three are put to work with some mind control. Ben turns back to his former self. As he rescues Susan, he is once again the Thing. The four battle Rama-Tut to his sphinx. Finally, they destroy his sphinx and return to their own time.", "12/9/1967"], ["3", "7", "The Way It All Began", "While on a television show, Reed recalls the time he first met Victor von Doom before he became Dr. Doom. He had Ben as his roommate at university. Victor was working on dangerous experiments, especially a test that brought him to the hospital and got him expelled from university. Worse than that, the test altered his face and he swore revenge on Reed having to hide his work from him. Ben and Reed became soldiers in World War II. Ben, Susan, Johnny and Reed all went aboard a space rocket for space exploration. And so the origin of the Fantastic Four began. Dr. Doom confronts the Fantastic Four on the television show and briefs them on his origin. After that Dr. Doom attempts to get his revenge, but fails and escapes only to crash.", "9/23/1967"], ["6", "9", "Prisoners Of Planet X", "A UFO has been sighted. The pilot abducts the Fantastic Four from the Science Center and is setting course for Planet X. There, their dictator Kurrgo requests the Fantastic Four save their planet from another planet knocked off its orbit. Reed manages to formulate a working plan to save the population. While the plan is in process, Kurrgo has other ideas. However, Reed tricks Kurrgo and leaves him on the exploding planet while the micro-sized population and the Fantastic Four get away to safety.", "10/14/1967"], ["7", "14", "It Started On Yancy Street", "The Fantastic Four face a bunch of old rivals in Yancy Street, but their old enemy Red Ghost and his primates show up and capture them. During their voyage to the moon, the four turn the tables, but Red Ghost gets away and the four are dumped on the moon. They barely manage to get to a source of oxygen which is the Watcherβs laboratory. Using one of the Watcherβs machines, Reed brings down Red Ghostβs ship. Susan gets Dr. Kragoff banished into a trans-nitron machine. Reed uses that machine to get back to Earth.", "10/21/1967"], ["12", "13", "Return Of the Mole Man", "The Mole Man is creating earthquakes and causing buildings to sink deep into the Earth. In addition, he and his Moloids kidnap Susan. The Mole Man as usual has been expecting the other three and sends them back to the surface to tell the Army not to get involved. They manage to halt them and seek an alternate entrance in the underworld. Johnny rescues Susan, then they penetrate the laboratory. They all return the buildings to the surface and escape the exploding caves.", "11/25/1967"], ["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"], ["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. Doomβs 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. Doomβs 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. Doomβs global destruction for good.", "10/28/1967"], ["5b", "4", "The Red Ghost", "Reed is competing with Dr. Kragoff in race to the moon for astronomical research. During the launch, Dr. Kragoff and his primate crew have developed some reverse energy powers. Dr. Kragoff is now transparent and becomes the Red Ghost. Red Ghost kidnaps Susan after counter attacking. She escapes and thwarts Red Ghostβs attempt to eliminate her companions. Using a special device, Reed turns Red Ghost into a plastic statue.", "10/7/1967"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 episode was next after "the way it all began"? | Invasion Of The Super-Skrull | 128 | Answer: |
Table InputTable: [["School", "2007", "2008", "2009", "2010", "2011"], ["Marc and Eva Stern Math and Science School", "718", "792", "788", "788", "809"], ["Santee Education Complex", "", "502", "521", "552", "565"], ["Woodrow Wilson High School", "582", "585", "600", "615", "636"], ["James A. Garfield High School", "553", "597", "593", "632", "705"], ["Francisco Bravo Medical Magnet High School", "807", "818", "815", "820", "832"], ["Thomas Jefferson High School", "457", "516", "514", "546", "546"], ["Abraham Lincoln High School", "594", "609", "588", "616", "643"], ["Theodore Roosevelt High School", "557", "551", "576", "608", ""], ["Oscar De La Hoya Animo Charter High School", "662", "726", "709", "710", "744"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 school had no api for 2011? | Theodore Roosevelt High School | 128 | Answer: |
Table InputTable: [["Language", "2001 census[1]\\n(total population 1,004.59 million)", "1991 censusIndian Census [2]\\n(total population 838.14 million)", "1991 censusIndian Census [2]\\n(total population 838.14 million)", ""], ["Marathi", "71,936,894", "62,481,681", "7.45%", "68.0 M"], ["Telugu", "70,002,856", "65,595,738", "8.30%", "70 M"], ["Kannada", "37,924,011", "32,753,676", "3.91%", "40.3 M"], ["Konkani", "2,489,015", "1,760,607", "0.210%", ""], ["Tamil", "60,793,814", "53,006,368", "6.32%", "66.0 M"], ["Nepali", "23,017,446", "28,061,313", "3.35%", "32.3 M"], ["Bodo", "1,350,478", "0.13%", "1,221,881", "0.146%"], ["Malayalam", "33,066,392", "30,377,176", "3.62%", "35.7 M"], ["Gujarati", "46,091,617", "40,673,814", "4.85%", "46.1 M"], ["Santali", "6,469,600", "5,216,325", "0.622%", ""], ["Maithili", "12,179,122", "1.18%", "", ""], ["Sindhi", "25,535,485", "25,122,848", "0.248%", "32.3 M"], ["Meitei (Manipuri)", "1,466,705*", "0.14%", "1,270,216", "0.151%"], ["Urdu", "51,536,111", "43,406,932", "5.18%", "60.3 M"], ["Bengali", "230,000,000", "200,595,738", "28.30%", "320 M"], ["Hindi", "422,048,642", "337,272,114", "40.0%", "336 M"], ["Assamese", "13,168,484", "13,079,696", "1.56%", "15.4 M"], ["Kashmiri", "5,527,698", "0.54%", "", ""], ["Khandeshi", "2,075,258", "0.21%", "", ""], ["Punjabi", "130,000,000", "100,017,615", "20.87%", "113 M"], ["Bhili/Bhilodi", "9,582,957", "5,572,308", "0.665%", ""], ["Sinhalese", "19,017,446", "28,061,313", "3.35%", "32.3 M"], ["Mundari", "1,061,352", "0.105%", "", ""], ["Khasi", "1,128,575", "0.112%", "", ""], ["Kurukh", "1,751,489", "0.17%", "1,426,618", "0.170%"], ["Oriya", "33,017,446", "28,061,313", "3.35%", "32.3 M"], ["Tulu", "1,722,768", "0.17%", "1,552,259", "0.185%"], ["Gondi", "2,713,790", "2,124,852", "0.253%", ""], ["Dogri", "2,282,589[dubious β discuss]", "0.22%", "", ""], ["Ho", "1,042,724", "0.103%", "", ""], ["", "Speakers", "Speakers", "Percentage", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 had a higher percentage? telugu or marathi? | Telugu | 128 | Answer: |
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["10 September 2005", "Chelsea", "Stamford Bridge", "0β2", "41,969", ""], ["1 October 2005", "West Ham United", "Stadium of Light", "1β1", "31,212", "Miller"], ["25 September 2005", "Middlesbrough", "Riverside Stadium", "2β0", "29,583", "Miller, Arca"], ["5 November 2005", "Arsenal", "Highbury", "1β3", "38,210", "Stubbs"], ["3 December 2005", "Tottenham Hotspur", "White Hart Lane", "2β3", "36,244", "Whitehead, Le Tallec"], ["20 August 2005", "Liverpool", "Anfield", "0β1", "44,913", ""], ["15 October 2005", "Manchester United", "Stadium of Light", "1β3", "39,085", "Elliott"], ["26 December 2005", "Bolton Wanderers", "Stadium of Light", "0β0", "32,232", ""], ["23 August 2005", "Manchester City", "Stadium of Light", "1β2", "33,357", "Le Tallec"], ["31 December 2005", "Everton", "Stadium of Light", "0β1", "30,567", ""], ["17 September 2005", "West Bromwich Albion", "Stadium of Light", "1β1", "31,657", "Breen"], ["30 November 2005", "Liverpool", "Stadium of Light", "0β2", "32,697", ""], ["10 December 2005", "Charlton Athletic", "The Valley", "0β2", "26,065", ""], ["26 November 2005", "Birmingham City", "Stadium of Light", "0β1", "32,442", ""], ["15 January 2006", "Chelsea", "Stadium of Light", "1β2", "32,420", "Lawrence"], ["23 October 2005", "Newcastle United", "St James' Park", "2β3", "52,302", "Lawrence, Elliott"], ["13 August 2005", "Charlton Athletic", "Stadium of Light", "1β3", "34,446", "Gray"], ["4 February 2006", "West Ham United", "Boleyn Ground", "0β2", "34,745", ""], ["29 October 2005", "Portsmouth", "Stadium of Light", "1β4", "34,926", "Whitehead (pen)"], ["25 March 2006", "Blackburn Rovers", "Stadium of Light", "0β1", "29,593", ""], ["19 November 2005", "Aston Villa", "Stadium of Light", "1β3", "39,707", "Whitehead (pen)"], ["1 May 2006", "Arsenal", "Stadium of Light", "0β3", "44,003", ""], ["18 March 2006", "Bolton Wanderers", "Reebok Stadium", "0β2", "23,568", ""], ["1 April 2006", "Everton", "Goodison Park", "2β2", "38,093", "Stead, Delap"], ["31 January 2006", "Middlesbrough", "Stadium of Light", "0β3", "31,675", ""], ["14 April 2006", "Manchester United", "Old Trafford", "0β0", "72,519", ""], ["27 August 2005", "Wigan Athletic", "JJB Stadium", "0β1", "17,223", ""], ["21 January 2006", "West Bromwich Albion", "The Hawthorns", "1β0", "26,464", "Watson (own goal)"], ["3 March 2006", "Manchester City", "City of Manchester Stadium", "1β2", "42,200", "Kyle"], ["15 February 2006", "Blackburn Rovers", "Ewood Park", "0β2", "18,220", ""], ["4 May 2006", "Fulham", "Stadium of Light", "2β1", "28,226", "Le Tallec, Brown"], ["17 April 2006", "Newcastle United", "Stadium of Light", "1β4", "40,032", "Hoyte"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 goals did chelsea score on 10 september 2005? | 2 | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Championship", "Surface", "Opponent in the final", "Score in the final"], ["Runner-up", "6.", "May 2, 1994", "Atlanta, Georgia, USA", "Clay", "Michael Chang", "7β6(7β4), 6β7(4β7), 0β6"], ["Winner", "5.", "January 15, 1996", "Sydney, Australia", "Hard", "Goran IvaniΕ‘eviΔ", "5β7, 6β3, 6β4"], ["Winner", "8.", "January 18, 1999", "Sydney, Australia", "Hard", "Γlex Corretja", "6β3, 7β6(7β5)"], ["Winner", "6.", "April 20, 1998", "Barcelona, Spain", "Clay", "Alberto Berasategui", "6β2, 1β6, 6β3, 6β2"], ["Runner-up", "12.", "September 12, 1999", "US Open, New York City, USA", "Hard", "Andre Agassi", "4β6, 7β6(7β5), 7β6(7β2), 3β6, 2β6"], ["Runner-up", "11.", "April 12, 1999", "Estoril, Portugal", "Clay", "Albert Costa", "6β7(4β7), 6β2, 3β6"], ["Runner-up", "7.", "May 9, 1994", "Pinehurst, USA", "Clay", "Jared Palmer", "4β6, 6β7(5β7)"], ["Winner", "2.", "February 14, 1994", "Memphis, Tennessee, USA", "Hard", "Brad Gilbert", "6β4, 7β5"], ["Winner", "4.", "February 20, 1995", "Memphis, Tennessee, USA", "Hard", "Paul Haarhuis", "7β6(7β2), 6β4"], ["Runner-up", "8.", "December 18, 1995", "Grand Slam Cup, Munich, Germany", "Carpet", "Goran IvaniΕ‘eviΔ", "6β7(4β7), 3β6, 4β6"], ["Runner-up", "1.", "February 15, 1993", "Memphis, Tennessee, USA", "Hard (i)", "Jim Courier", "7β5, 6β7(4β7), 6β7(4β7)"], ["Runner-up", "4.", "October 18, 1993", "Tokyo, Japan", "Carpet", "Ivan Lendl", "4β6, 4β6"], ["Runner-up", "5.", "January 31, 1994", "Australian Open, Melbourne, Australia", "Hard", "Pete Sampras", "6β7(4β7), 4β6, 4β6"], ["Runner-up", "10.", "August 22, 1996", "Stockholm, Sweden", "Hard (i)", "Thomas Enqvist", "5β7, 4β6, 6β7(0β7)"], ["Winner", "3.", "June 13, 1994", "London (Queen's Club), UK", "Grass", "Pete Sampras", "7β6(7β4), 7β6(7β4)"], ["Runner-up", "3.", "August 2, 1993", "Montreal, Canada", "Hard", "Mikael Pernfors", "6β2, 2β6, 5β7"], ["Runner-up", "9.", "February 26, 1996", "Memphis, Tennessee, USA", "Hard (i)", "Pete Sampras", "4β6, 6β7(2β7)"], ["Winner", "7.", "November 16, 1998", "Stockholm, Sweden", "Hard", "Thomas Johansson", "6β3, 6β4, 6β4"], ["Runner-up", "2.", "July 26, 1993", "Washington D.C., USA", "Hard", "Amos Mansdorf", "6β7(3β7), 5β7"], ["Winner", "1.", "May 17, 1993", "Coral Springs, Florida, USA", "Clay", "David Wheaton", "6β3, 6β4"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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:name a match that was in the same month as the one in atlanta, georgia. | Pinehurst, USA | 128 | Answer: |
Table InputTable: [["Pos", "No.", "Driver", "Team", "Laps", "Time/Retired", "Grid", "Laps Led", "Points"], ["13", "18", "Justin Wilson", "Dale Coyne Racing", "85", "+ 53.5768", "2", "28", "17"], ["19", "7", "Danica Patrick", "Andretti Green Racing", "83", "+ 2 Laps", "12", "0", "12"], ["1", "9", "Scott Dixon", "Chip Ganassi Racing", "85", "1:46:05.7985", "3", "51", "52"], ["12", "3", "HΓ©lio Castroneves", "Penske Racing", "85", "+ 53.2362", "5", "0", "18"], ["16", "4", "Dan Wheldon", "Panther Racing", "84", "+ 1 Lap", "17", "0", "14"], ["3", "10", "Dario Franchitti", "Chip Ganassi Racing", "85", "+ 30.0551", "6", "0", "35"], ["14", "33", "Robert Doornbos (R)", "HVM Racing", "85", "+ 1:10.0812", "18", "0", "16"], ["11", "06", "Oriol ServiΓ ", "Newman/Haas/Lanigan Racing", "85", "+ 52.6215", "14", "0", "19"], ["10", "11", "Tony Kanaan", "Andretti Green Racing", "85", "+ 52.0810", "8", "0", "20"], ["5", "27", "Hideki Mutoh", "Andretti Green Racing", "85", "+ 34.1839", "11", "0", "30"], ["6", "26", "Marco Andretti", "Andretti Green Racing", "85", "+ 46.7669", "13", "0", "28"], ["17", "20", "Ed Carpenter", "Vision Racing", "84", "+ 1 Lap", "21", "0", "13"], ["8", "02", "Graham Rahal", "Newman/Haas/Lanigan Racing", "85", "+ 50.4517", "4", "0", "24"], ["20", "24", "Mike Conway (R)", "Dreyer & Reinbold Racing", "69", "Mechanical", "16", "0", "12"], ["2", "6", "Ryan Briscoe", "Penske Racing", "85", "+ 29.7803", "1", "6", "41"], ["18", "98", "Richard Antinucci", "Team 3G", "83", "+ 2 Laps", "19", "0", "12"], ["15", "13", "E. J. Viso", "HVM Racing", "84", "+ 1 Lap", "9", "0", "15"], ["21", "23", "Milka Duno", "Dreyer & Reinbold Racing", "56", "Handling", "20", "0", "12"], ["9", "2", "Raphael Matos (R)", "Luczo-Dragon Racing", "85", "+ 51.2286", "15", "0", "22"], ["7", "5", "Paul Tracy", "KV Racing Technology", "85", "+ 49.7020", "10", "0", "26"], ["4", "14", "Ryan Hunter-Reay", "A. J. Foyt Enterprises", "85", "+ 33.7307", "7", "0", "32"]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 driver to actually finish this race? | Danica Patrick | 128 | Answer: |
Table InputTable: [["Week", "Date", "TV Time", "Opponent", "Result", "Attendance"], ["13", "November 29, 1998", "FOX 11:00 am MT", "at Kansas City Chiefs", "L 34β24", "69,613"], ["3", "September 20, 1998", "ESPN 5:15 pm MT", "Philadelphia Eagles", "W 17β3", "39,782"], ["4", "September 27, 1998", "FOX 10:00 am MT", "at St. Louis Rams", "W 20β17", "55,832"], ["17", "December 27, 1998", "CBS 2:05 pm MT", "San Diego Chargers", "W 16β13", "71,670"], ["16", "December 20, 1998", "FOX 2:05 pm MT", "New Orleans Saints", "W 19β17", "51,617"], ["14", "December 6, 1998", "FOX 2:15 pm MT", "New York Giants", "L 23β19", "46,128"], ["1", "September 6, 1998", "FOX 1:05 pm MT", "at Dallas Cowboys", "L 38β10", "63,602"], ["6", "October 11, 1998", "FOX 1:05 pm MT", "Chicago Bears", "W 20β7", "50,495"], ["2", "September 13, 1998", "FOX 1:15 pm MT", "at Seattle Seahawks", "L 33β14", "57,678"], ["7", "October 18, 1998", "FOX 10:00 am MT", "at New York Giants", "L 34β7", "70,456"], ["5", "October 4, 1998", "CBS 1:05 pm MT", "Oakland Raiders", "L 23β20", "53,240"], ["11", "November 15, 1998", "FOX 2:15 pm MT", "Dallas Cowboys", "L 35β28", "71,670"], ["10", "November 8, 1998", "FOX 2:15 pm MT", "Washington Redskins", "W 29β27", "45,950"], ["9", "November 1, 1998", "FOX 11:00 am MT", "at Detroit Lions", "W 17β15", "66,087"], ["12", "November 22, 1998", "FOX 11:00 am MT", "at Washington Redskins", "W 45β42", "63,435"], ["15", "December 13, 1998", "FOX 11:00 am MT", "at Philadelphia Eagles", "W 20β17", "62,176"], ["8", "Bye", "Bye", "Bye", "Bye", ""]] | 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", "1907β1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909β1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911β1920", "4 inline", "1,292 cc", "9.6β10.3 kW (13β14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909β1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911β1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911β1914", "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 longest consecutive wins? | 3 | 128 | Answer: |
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