context stringlengths 362 2.82k | question stringlengths 2.11k 2.25k | answer stringlengths 1 260 | answer_prefix stringclasses 1
value | max_new_tokens int64 128 128 |
|---|---|---|---|---|
Table InputTable: [["Round", "Round", "Race", "Date", "Pole Position", "Fastest Lap", "Winning Club", "Winning Team", "Report"], ["3", "R1", "Zolder", "October 5", "Borussia Dortmund", "Liverpool F.C.", "Liverpool F.C.", "Hitech Junior Team", "Report"], ["6", "R1", "Jerez", "November 23", "Liverpool F.C.", "R.S.C. Anderlecht", "A.C. Milan", "Scuderia Playteam", "Report"], ["4", "R1", "Estoril", "October 19", "A.S. Roma", "Atlético Madrid", "Liverpool F.C.", "Hitech Junior Team", "Report"], ["5", "R2", "Vallelunga", "November 2", "", "Atlético Madrid", "F.C. Porto", "Hitech Junior Team", "Report"], ["5", "R1", "Vallelunga", "November 2", "Liverpool F.C.", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "Report"], ["2", "R1", "Nürburgring", "September 21", "A.C. Milan", "PSV Eindhoven", "A.C. Milan", "Scuderia Playteam", "Report"], ["1", "R2", "Donington Park", "August 31", "", "PSV Eindhoven", "Sevilla FC", "GTA Motor Competición", "Report"], ["3", "R2", "Zolder", "October 5", "", "Atlético Madrid", "Beijing Guoan", "Zakspeed", "Report"], ["6", "R2", "Jerez", "November 23", "", "Beijing Guoan", "Borussia Dortmund", "Zakspeed", "Report"], ["4", "R2", "Estoril", "October 19", "", "Borussia Dortmund", "Al Ain", "Azerti Motorsport", "Report"], ["2", "R2", "Nürburgring", "September 21", "", "SC Corinthians", "PSV Eindhoven", "Azerti Motorsport", "Report"], ["1", "R1", "Donington Park", "August 31", "Beijing Guoan", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the first winning club? | Beijing Guoan | Answer: | 128 |
Table InputTable: [["Name of place", "Number of counties", "Principal county", "Lower zip code", "Upper zip code"], ["Sadlers Corner", "1", "Venango County", "", ""], ["Shaffers Corners", "1", "Lackawanna County", "", ""], ["St. Martins", "1", "Philadelphia County", "", ""], ["Sheraden", "1", "Allegheny County", "", ""], ["Sharpe Hill", "1", "Allegheny County", "", ""], ["Shadow Shuttle", "1", "Allegheny County", "15235", ""], ["Scotia", "1", "Allegheny County", "15025", ""], ["Shaffers Corner", "1", "Fayette County", "15416", ""], ["Sedgwick", "1", "Philadelphia County", "", ""], ["Shousetown", "1", "Allegheny County", "", ""], ["Shields", "1", "Allegheny County", "15143", ""], ["Sharps Hill", "1", "Allegheny County", "15215", ""], ["Schades Corner", "1", "Chester County", "", ""], ["Sixtieth Street", "1", "Philadelphia County", "19139", ""], ["Sample Heights", "1", "Allegheny County", "15209", ""], ["Shalercrest", "1", "Allegheny County", "15223", ""], ["Sample", "1", "Allegheny County", "", ""], ["Shawmont", "1", "Philadelphia County", "", ""], ["Saint Pauls Church", "1", "Philadelphia County", "", ""], ["Shadyside", "1", "Allegheny County", "15232", ""], ["Selinsgrove Junction", "1", "Northumberland County", "", ""], ["Seven Points", "1", "Northumberland County", "17801", ""], ["Sharpsburg", "1", "Allegheny County", "15215", ""], ["Simmonstown", "1", "Lancaster County", "17527", ""], ["Siegfried", "1", "Northampton County", "18067", ""], ["Sewickley", "1", "Allegheny County", "15143", ""], ["Shippensburg", "2", "Cumberland County", "17257", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:alphabetically, which place in pennsylvania comes before sadlers corner? | Sacramento | Answer: | 128 |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["2", "Italy (ITA)", "1", "1", "1", "3"], ["7", "France (FRA)", "0", "0", "1", "1"], ["3", "Germany (EUA)", "1", "0", "1", "2"], ["5", "Switzerland (SUI)", "0", "2", "1", "3"], ["7", "Great Britain (GBR)", "0", "0", "1", "1"], ["4", "Soviet Union (URS)", "1", "0", "0", "1"], ["1", "Australia (AUS)", "2", "1", "0", "3"], ["6", "United States (USA)", "0", "1", "0", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total medals did italy win? | 3 | Answer: | 128 |
Table InputTable: [["Season", "Date", "Location", "Discipline", "Place"], ["2013", "30 Nov 2012", "Lake Louise, Canada", "Downhill", "3rd"], ["2012", "2 Dec 2011", "Lake Louise, Canada", "Downhill", "2nd"], ["2014", "8 Dec 2013", "Lake Louise, Canada", "Super-G", "2nd"], ["2014", "7 Dec 2013", "Lake Louise, Canada", "Downhill", "2nd"], ["2012", "28 Jan 2012", "St. Moritz, Switzerland", "Downhill", "3rd"], ["2014", "29 Nov 2013", "Beaver Creek, USA", "Downhill", "2nd"], ["2012", "26 Feb 2012", "Bansko, Bulgaria", "Super-G", "2nd"], ["2014", "1 Dec 2013", "Beaver Creek, USA", "Giant slalom", "3rd"], ["2014", "22 Dec 2013", "Val-d'Isère, France", "Giant slalom", "1st"], ["2012", "4 Feb 2012", "Garmisch, Germany", "Downhill", "3rd"], ["2014", "14 Dec 2013", "St. Moritz, Switzerland", "Super-G", "1st"], ["2012", "5 Feb 2012", "Garmisch, Germany", "Super-G", "3rd"], ["2013", "1 Mar 2013", "Garmisch, Germany", "Super-G", "1st"], ["2014", "25 Jan 2014", "Cortina d'Ampezzo, Italy", "Downhill", "3rd"], ["2014", "24 Jan 2014", "Cortina d'Ampezzo, Italy", "Downhill", "2nd"], ["2014", "26 Jan 2014", "Cortina d'Ampezzo, Italy", "Super-G", "2nd"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which location is previous to lake louise canada on 30 nov 2012 | Bansko, Bulgaria | Answer: | 128 |
Table InputTable: [["Rd.", "Event", "Circuit", "Location", "Date", "Winner"], ["3", "Dunlop Townsville 400", "Townsville Street Circuit", "Townsville, Queensland", "10-12 Jul", "James Moffat"], ["2", "Winton", "Winton Motor Raceway", "Benalla, Victoria", "1-3 May", "Jonathon Webb"], ["1", "Clipsal 500", "Adelaide Street Circuit", "Adelaide, South Australia", "19-22 Mar", "David Russell"], ["4", "Norton 360 Sandown Challenge", "Sandown Raceway", "Melbourne, Victoria", "31 Jul-Aug 2", "David Russell"], ["6", "Supercheap Auto Bathurst 1000", "Mount Panorama Circuit", "Bathurst, New South Wales", "8-11 Oct", "Jonathon Webb"], ["5", "Queensland House & Land 300", "Queensland Raceway", "Ipswich, Queensland", "21-23 Aug", "Jonathon Webb"], ["7", "Sydney Telstra 500", "Homebush Street Circuit", "Sydney, New South Wales", "4-6 Dec", "Jonathon Webb"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what are the number of rounds in the 2009 fujitsu v* supercar season? | 7 | Answer: | 128 |
Table InputTable: [["Route", "Destinations", "Via", "Frequency\\n(minutes)", "Peak Hours Only", "Former"], ["4", "Princess Street", "Cataraqui Town Centre\\nDowntown", "30", "", ""], ["6", "Cataraqui Town Centre\\nSt. Lawrence College", "Gardiners Town Centre", "30", "", "Downtown"], ["7", "Dalton/Division\\nMidland/Gardiners", "Cataraqui Town Centre\\nTrain Station\\nBus Terminal", "30", "", ""], ["1", "Montreal Street\\nSt. Lawrence College", "Downtown", "30", "", "Cataraqui Town Centre-Woods"], ["11", "Kingston Centre\\nCataraqui Town Centre", "Bath Road\\nGardiners Town Centre", "30", "", "(formerly Route 71)"], ["15", "Reddendale\\nCataraqui Town Centre - Woods", "Gardiners Town Centre", "30", "", "(formerly Route B)"], ["10", "Amherstview\\nCataraqui Town Centre", "Collins Bay Road", "30", "", "Kingston Centre"], ["9", "Downtown\\nCataraqui Town Centre", "Brock St. / Barrie St.\\nGardiners Town Centre", "20", "", ""], ["14", "Train Station\\nCataraqui Town Centre / Midland Avenue", "Waterloo-Davis\\nMultiplex", "30", "", "(formerly Route A)"], ["16", "Train Station\\nBus Terminal", "Kingston Centre", "30", "", "(formerly Route C)"], ["2", "Kingston Centre\\nDivision Street", "St. Lawrence College\\nDowntown", "30", "", ""], ["3", "Kingston Centre\\nDowntown", "Queen Mary Road\\nSt. Lawrence College\\nKing Street", "30", "", ""], ["12", "Kingston Centre\\nHighway 15", "Downtown\\nCFB Kingston (off-peak only)", "30", "", "-"], ["19", "Montreal Street\\nQueen's University", "Downtown", "30", "X", ""], ["18", "Train Station\\nBus Terminal", "Downtown\\nQueen's University\\nSt. Lawrence College", "*", "", "Student Circuit"], ["12A", "CFB Kingston\\nDowntown", "", "30", "X", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times is the cataraqui town centre listed as a destination? | 6 | Answer: | 128 |
Table InputTable: [["Subject", "Robot's Name", "Who?", "When?", "Where?", "Occupation"], ["Painting", "Pierro-Bot", "Stone-Age Humans", "35,000 B.C.", "Europe", "Clown/Artist"], ["Nursing", "Dr. Bug-Bot", "Florence Nightengale", "1860", "England", "Doctor"], ["Boomerang", "Oswald the Mailman Robot", "Aborigines", "40,000 years ago", "Australia", "Mailman"], ["Microscope", "Slobot", "Antonie van Leeuwenhoek", "1674", "The Netherlands", "Dirty Person"], ["Tools", "Hank the Handyman Robot", "Stone-Age Humans", "2½ million years ago", "Africa", "Mechanic"], ["Writing", "Eraser-Bot", "Sumerians", "3,500 B.C.", "Middle East", "Pencil Man"], ["Sausage", "Sock-Bot", "Babylonians", "3,000 B.C.", "Middle East", "Sock Man"], ["Radium", "Miss Battery-Bot", "Marie Curie", "1898", "France", "Battery Lady"], ["Solar System", "Cosmo-Bot", "Copernicus", "1531", "Poland", "Cosmonaut"], ["Round Earth", "Vasco da Robot", "Ferdinand Magellan", "1522", "Spain", "Early Sailor"], ["Germs", "Roast-Bot", "Louis Pasteur", "1865", "France", "Firefighter"], ["Bicycle", "Booster-Bot", "Karl von Drais", "1816", "Germany", "Rocket Man"], ["Phonograph", "Slide the Heavy-Metal Robot", "Thomas Edison", "1877", "New Jersey", "Rock Star"], ["Helicopter", "Amelia Air-Bot", "Leonardo da Vinci", "1483", "Italy", "Pilot"], ["Olympics", "Rhonda Robot", "Greeks", "776 B.C.", "Greece", "Beauty queen"], ["Toilet", "Brunwella the Bombshell", "Minoans", "2000 B.C.", "Crete", "Demolisher"], ["Saxophone", "Bongo-Bot the Six-Armed Robot", "Antoine-Joseph Sax", "1846", "France", "Six-Armed Drum Player"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the oldest subject listed? | Tools | Answer: | 128 |
Table InputTable: [["Outcome", "No.", "Date", "Championship", "Surface", "Opponent in the final", "Score in the final"], ["Runner-up", "9.", "February 26, 1996", "Memphis, Tennessee, USA", "Hard (i)", "Pete Sampras", "4–6, 6–7(2–7)"], ["Runner-up", "5.", "January 31, 1994", "Australian Open, Melbourne, Australia", "Hard", "Pete Sampras", "6–7(4–7), 4–6, 4–6"], ["Winner", "3.", "June 13, 1994", "London (Queen's Club), UK", "Grass", "Pete Sampras", "7–6(7–4), 7–6(7–4)"], ["Winner", "5.", "January 15, 1996", "Sydney, Australia", "Hard", "Goran Ivanišević", "5–7, 6–3, 6–4"], ["Runner-up", "10.", "August 22, 1996", "Stockholm, Sweden", "Hard (i)", "Thomas Enqvist", "5–7, 4–6, 6–7(0–7)"], ["Runner-up", "8.", "December 18, 1995", "Grand Slam Cup, Munich, Germany", "Carpet", "Goran Ivanišević", "6–7(4–7), 3–6, 4–6"], ["Winner", "4.", "February 20, 1995", "Memphis, Tennessee, USA", "Hard", "Paul Haarhuis", "7–6(7–2), 6–4"], ["Runner-up", "12.", "September 12, 1999", "US Open, New York City, USA", "Hard", "Andre Agassi", "4–6, 7–6(7–5), 7–6(7–2), 3–6, 2–6"], ["Winner", "8.", "January 18, 1999", "Sydney, Australia", "Hard", "Àlex Corretja", "6–3, 7–6(7–5)"], ["Winner", "6.", "April 20, 1998", "Barcelona, Spain", "Clay", "Alberto Berasategui", "6–2, 1–6, 6–3, 6–2"]] | 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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times was pete sampras the opponent in the final round? | 3 | Answer: | 128 |
Table InputTable: [["Year", "Class", "No", "Tyres", "Car", "Team", "Co-Drivers", "Laps", "Pos.", "Class\\nPos."], ["1996", "GT1", "38", "M", "McLaren F1 GTR\\nBMW S70 6.1L V12", "Team Bigazzi SRL", "Steve Soper\\n Marc Duez", "318", "11th", "9th"], ["1993", "GT", "71", "D", "Venturi 500LM\\nRenault PRV 3.0 L Turbo V6", "Jacadi Racing", "Michel Maisonneuve\\n Christophe Dechavanne", "210", "DNF", "DNF"], ["1994", "GT2", "49", "P", "Porsche 911 Carrera RSR\\nPorsche 3.8 L Flat-6", "Larbre Compétition", "Jacques Alméras\\n Jean-Marie Alméras", "94", "DNF", "DNF"], ["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"], ["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"], ["1977", "S\\n+2.0", "8", "", "Renault Alpine A442\\nRenault 2.0L Turbo V6", "Renault Sport", "Patrick Depailler", "289", "DNF", "DNF"], ["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"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the last team that this racer was a part of at this race? | Team Bigazzi SRL | Answer: | 128 |
Table InputTable: [["ZOOM", "Cast Member 1", "Cast Member 2", "Cast Member 3", "Cast Member 4", "Cast Member 5", "Cast Member 6", "Cast Member 7"], ["Season 3 (2001)", "Frances Domond", "Kenneth \"Kenny\" Yates", "Rachel Redd", "Eric Rollins", "Kaleigh Cronin", "Kevin \"Buzz\" Barrette", "Caroline Botelho"], ["Season 7 (2005)", "W. Nick Henry", "Taylor Garron", "Francesco Tena", "Noreen Raja", "Emily Marshall", "Kyle Larrow", "Elena \"Shing Ying\" Shieh"], ["Season 5 (2003)", "Caroline Botelho", "Aline Toupi", "Estuardo Alvizures", "Garrett DiBona", "Michael \"Mike\" Hansen", "Kortney Sumner", "Elena \"Shing Ying\" Shieh"], ["Season 6 (2004)", "Michael \"Mike\" Hansen", "Kortney Sumner", "Francesco Tena", "Cara Harvey", "Kyle Larrow", "Maya Morales", "Elena \"Shing Ying\" Shieh"], ["Season 4 (2002)", "Aline Toupi", "Garrett DiBona", "Rachel Redd", "Matthew \"Matt\" Runyon", "Estuardo Alvizures", "Kaleigh Cronin", "Caroline Botelho"], ["Season 2 (2000)", "Raymond \"Ray\" MacMore", "Caroline Botelho", "Claudio Schwartz", "Alisa Besher", "Jessica \"Jessie\" Ogungbadero", "Kenneth \"Kenny\" Yates", "Zoe Costello"], ["Season 1 (1999)", "Zoe Costello", "Jared Nathan", "Keiko Yoshida", "Pablo Velez, Jr.", "Alisa Besher", "David Toropov", "Lynese Browder"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the last season of zoom | SEASON 7 | Answer: | 128 |
Table InputTable: [["Fence", "Name", "Jockey", "Age", "Handicap (st-lb)", "Starting price", "Fate"], ["13", "Phebu", "J Morrissey", "8", "10-13", "33/1", "Brought Down"], ["18", "Leedsy", "George Robinson", "7", "10-13", "18/1", "Fell"], ["22", "Kapeno", "David Dick", "8", "11-6", "100/8", "Fell"], ["?", "Blonde Warrior", "Mr D Crossley-Cooke", "13", "10-13", "100/1", "Fell"], ["?", "Mr McTaffy", "T Jackson", "13", "10-13", "100/1", "Pulled Up"], ["09", "Groomsman", "Beltrán Osorio", "10", "10-13", "100/1", "Fell"], ["17", "Bold Biri", "Michael Scudamore", "9", "10-13", "100/1", "Fell"], ["?", "Solonace", "RW Jones", "13", "10-13", "100/1", "Pulled Up"], ["06", "Barleycroft", "Phil Harvey", "10", "10-13", "100/1", "Brought Down"], ["26", "Rondetto", "Jeff King", "9", "11-6", "100/8", "Fell"], ["?", "Leslie", "P Jones", "9", "10-13", "33/1", "Pulled Up"], ["24", "Pontin-Go", "Johnny Lehane", "13", "10-13", "50/1", "Fell"], ["?", "Reproduction", "Robin Langley", "12", "10-13", "40/1", "Pulled-Up"], ["?", "Lizawake", "Mr George Hartigan", "12", "10-13", "100/1", "Pulled Up"], ["06", "Sizzle-On", "P Hurley", "9", "10/13", "100/1", "Brought Down"], ["06", "Nedsmar", "John Hudson", "11", "10-13", "100/1", "Fell"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many jockeys were 13 years old? | 5 | Answer: | 128 |
Table InputTable: [["Round", "Pick", "Name", "Position", "College"], ["6", "170", "Frank Murphy", "WR", "Kansas State"], ["2", "39", "Mike Brown", "S", "Nebraska"], ["7", "223", "James Cotton", "DE", "Ohio State"], ["6", "174", "Paul Edinger", "K", "Michigan State"], ["3", "69", "Dez White", "WR", "Georgia Tech"], ["1", "9", "Brian Urlacher", "S", "New Mexico"], ["7", "254", "Michael Green", "S", "Northwestern State"], ["4", "125", "Reggie Austin", "DB", "Wake Forest"], ["3", "87", "Dustin Lyman", "TE", "Wake Forest"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the total number of players drafted by the chicago bears in 2000? | 9 | Answer: | 128 |
Table InputTable: [["Rank", "Athlete", "Nationality", "2.15", "2.20", "2.24", "2.27", "Result", "Notes"], ["1.", "Víctor Moya", "Cuba", "o", "o", "o", "o", "2.27", "q, PB"], ["9.", "Ramsay Carelse", "South Africa", "xo", "xo", "o", "xxx", "2.24", ""], ["1.", "Yaroslav Rybakov", "Russia", "o", "o", "o", "o", "2.27", "q"], ["10.", "Nicola Ciotti", "Italy", "o", "o", "xo", "xxx", "2.24", ""], ["1.", "Andriy Sokolovskyy", "Ukraine", "o", "o", "o", "o", "2.27", "q"], ["1.", "Stefan Holm", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["13.", "Tomáš Janku", "Czech Republic", "o", "o", "xxo", "xxx", "2.24", ""], ["16.", "Adam Shunk", "United States", "o", "xxx", "", "2.15", "", ""], ["16.", "Roman Fricke", "Germany", "o", "xxx", "", "2.15", "", ""], ["1.", "Linus Thörnblad", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["7.", "Giulio Ciotti", "Italy", "o", "o", "o", "xxx", "2.24", "q"], ["1.", "Andrey Tereshin", "Russia", "o", "o", "o", "o", "2.27", "q"], ["13.", "Mustapha Raifak", "France", "o", "o", "xxo", "xxx", "2.24", ""], ["15.", "Svatoslav Ton", "Czech Republic", "o", "xo", "xxx", "", "2.20", ""], ["8.", "Robert Wolski", "Poland", "xo", "o", "o", "xxx", "2.24", "q"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many competitors scored at least 2.24 points during qualification? | 14 | Answer: | 128 |
Table InputTable: [["#", "Name", "Hanzi", "Hanyu Pinyin", "Population (2003 est.)", "Area (km²)", "Density (/km²)"], ["2", "Dong'an District", "东安区", "Dōng'ān Qū", "180,000", "566", "318"], ["4", "Xi'an District", "西安区", "Xī'ān Qū", "210,000", "325", "646"], ["3", "Yangming District", "阳明区", "Yángmíng Qū", "160,000", "358", "447"], ["5", "Muling City", "穆棱市", "Mùlíng Shì", "330,000", "6,094", "54"], ["8", "Ning'an City", "宁安市", "Níng'ān Shì", "440,000", "7,870", "56"], ["6", "Suifenhe City", "绥芬河市", "Suífēnhé Shi", "60,000", "427", "141"], ["1", "Aimin District", "爱民区", "Àimín Qū", "230,000", "359", "641"], ["10", "Linkou County", "林口县", "Línkǒu Xiàn", "450,000", "7,191", "63"], ["9", "Dongning County", "东宁县", "Dōngníng Xiàn", "210,000", "7,368", "29"], ["7", "Hailin City", "海林市", "Hǎilín Shì", "440,000", "9,877", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many divisions have an area of more than 1000 km^2? | 5 | Answer: | 128 |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event"], ["2000", "Olympic Games", "Sydney, Australia", "3rd", "100 m hurdles"], ["2004", "Olympic Games", "Athens, Greece", "3rd", "100 m hurdles"], ["1997", "World Indoor Championships", "Paris, France", "5th", "60 m hurdles"], ["2003", "World Athletics Final", "Monaco", "6th", "100 m hurdles"], ["1997", "USA Outdoor Championships", "Indianapolis, United States", "1st", "100 m hurdles"], ["2003", "World Indoor Championships", "Birmingham, England", "3rd", "60 m hurdles"], ["2000", "Grand Prix Final", "Doha, Qatar", "4th", "100 m hurdles"], ["2002", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["1998", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["1999", "World Indoor Championships", "Maebashi, Japan", "6th", "60 m hurdles"], ["2002", "Grand Prix Final", "Paris, France", "7th", "100 m hurdles"], ["1998", "Grand Prix Final", "Moscow, Russia", "2nd", "100 m hurdles"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many olympic games total did melissa morrison-howard place in? | 2 | Answer: | 128 |
Table InputTable: [["Season", "Episodes", "Time slot (EST)", "Original airing\\nSeason premiere", "Original airing\\nSeason finale", "Original airing\\nTV season", "Rank", "Viewers\\n(in millions)"], ["1", "23", "Friday 9pm/8c (October 6, 2000 – January 12, 2001)\\nThursday 9pm/8c (February 1, 2001 – May 17, 2001)", "October 6, 2000", "May 17, 2001", "2000–2001", "#10", "17.80"], ["5", "25", "Thursday 9pm/8c", "September 23, 2004", "May 19, 2005", "2004–2005", "#2", "26.26"], ["4", "23", "Thursday 9pm/8c", "September 25, 2003", "May 20, 2004", "2003–2004", "#2", "25.27"], ["6", "24", "Thursday 9pm/8c", "September 22, 2005", "May 18, 2006", "2005–2006", "#3", "24.86"], ["9", "24", "Thursday 9pm/8c", "October 9, 2008", "May 14, 2009", "2008–2009", "#4", "18.52"], ["3", "23", "Thursday 9pm/8c", "September 26, 2002", "May 15, 2003", "2002–2003", "#1", "26.20"], ["2", "23", "Thursday 9pm/8c", "September 27, 2001", "May 16, 2002", "2001–2002", "#2", "23.69"], ["8", "17", "Thursday 9pm/8c", "September 27, 2007", "May 15, 2008", "2007–2008", "#9", "16.62"], ["7", "24", "Thursday 9pm/8c", "September 21, 2006", "May 17, 2007", "2006–2007", "#4", "20.34"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which season had the highest ranking? | 3 | Answer: | 128 |
Table InputTable: [["Specifications", "Foundation", "Essentials", "Standard", "Datacenter"], ["User limit", "15", "25", "Unlimited", "Unlimited"], ["File Services limits", "1 standalone DFS root", "1 standalone DFS root", "Unlimited", "Unlimited"], ["Licensing model", "Per server", "Per server", "Per CPU pair + CAL", "Per CPU pair + CAL"], ["Processor chip limit", "1", "2", "64", "64"], ["Remote Desktop Services limits", "50 Remote Desktop Services connections", "Gateway only", "Unlimited", "Unlimited"], ["Memory limit", "32 GB", "64 GB", "4 TB", "4 TB"], ["Server Core mode", "No", "No", "Yes", "Yes"], ["Virtualization rights", "N/A", "Either in 1 VM or 1 physical server, but not both at once", "2 VMs", "Unlimited"], ["Active Directory Certificate Services", "Certificate Authorities only", "Certificate Authorities only", "Yes", "Yes"], ["Active Directory Rights Management Services", "Yes", "Yes", "Yes", "Yes"], ["Network Policy and Access Services limits", "50 RRAS connections and 10 IAS connections", "250 RRAS connections, 50 IAS connections, and 2 IAS Server Groups", "Unlimited", "Unlimited"], ["Fax server role", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Federation Services", "Yes", "No", "Yes", "Yes"], ["Active Directory Domain Services", "Must be root of forest and domain", "Must be root of forest and domain", "Yes", "Yes"], ["Distribution", "OEM only", "Retail, volume licensing, OEM", "Retail, volume licensing, OEM", "Volume licensing and OEM"], ["Application server role", "Yes", "Yes", "Yes", "Yes"], ["Server Manager", "Yes", "Yes", "Yes", "Yes"], ["Windows Server Update Services", "No", "Yes", "Yes", "Yes"], ["Hyper-V", "No", "No", "Yes", "Yes"], ["DNS server role", "Yes", "Yes", "Yes", "Yes"], ["Print and Document Services", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Lightweight Directory Services", "Yes", "Yes", "Yes", "Yes"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which edition has a user limit below 20? | Foundation | Answer: | 128 |
Table InputTable: [["Season", "Date", "Location", "Discipline", "Place"], ["1993", "27 Feb 1993", "Whistler, BC, Canada", "Downhill", "2nd"], ["1994", "12 Mar 1994", "Whistler, BC, Canada", "Downhill", "3rd"], ["1995", "11 Dec 1994", "Tignes, France", "Super G", "2nd"], ["1994", "16 Mar 1994", "Vail, CO, USA", "Downhill", "3rd"], ["1994", "29 Dec 1993", "Bormio, Italy", "Downhill", "3rd"], ["1994", "13 Mar 1994", "Whistler, BC, Canada", "Super G", "1st"], ["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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the location of the latest race? | Tignes, France | Answer: | 128 |
Table InputTable: [["Match", "Date", "Venue", "Opponents", "Score"], ["GL-A-5", "2006..", "[[]]", "[[]]", "-"], ["GL-A-3", "2006..", "[[]]", "[[]]", "-"], ["GL-A-4", "2006..", "[[]]", "[[]]", "-"], ["GL-A-2", "2006..", "[[]]", "[[]]", "-"], ["GL-A-1", "2006..", "[[]]", "[[]]", "-"], ["GL-A-6", "2006..", "[[]]", "[[]]", "-"], ["Semifinals-2", "2006..", "[[]]", "[[]]", "-"], ["Quarterfinals-2", "2006..", "[[]]", "[[]]", "-"], ["Semifinals-1", "2006..", "[[]]", "[[]]", "-"], ["Quarterfinals-1", "2006..", "[[]]", "[[]]", "-"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which is next after gl-a5 | GL-A-6 | Answer: | 128 |
Table InputTable: [["#", "Name", "Hanzi", "Hanyu Pinyin", "Population (2003 est.)", "Area (km²)", "Density (/km²)"], ["4", "Xi'an District", "西安区", "Xī'ān Qū", "210,000", "325", "646"], ["2", "Dong'an District", "东安区", "Dōng'ān Qū", "180,000", "566", "318"], ["3", "Yangming District", "阳明区", "Yángmíng Qū", "160,000", "358", "447"], ["9", "Dongning County", "东宁县", "Dōngníng Xiàn", "210,000", "7,368", "29"], ["5", "Muling City", "穆棱市", "Mùlíng Shì", "330,000", "6,094", "54"], ["1", "Aimin District", "爱民区", "Àimín Qū", "230,000", "359", "641"], ["8", "Ning'an City", "宁安市", "Níng'ān Shì", "440,000", "7,870", "56"], ["10", "Linkou County", "林口县", "Línkǒu Xiàn", "450,000", "7,191", "63"], ["6", "Suifenhe City", "绥芬河市", "Suífēnhé Shi", "60,000", "427", "141"], ["7", "Hailin City", "海林市", "Hǎilín Shì", "440,000", "9,877", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which division has the most area? | Hailin City | Answer: | 128 |
Table InputTable: [["Date", "Time", "", "Score", "", "Set 1", "Set 2", "Set 3", "Set 4", "Set 5", "Total", "Report"], ["17 Nov", "14:00", "Canada", "3–0", "Kazakhstan", "25–21", "26–24", "25–21", "", "", "76–66", "P2 P3"], ["19 Nov", "18:00", "Canada", "0–3", "Russia", "19–25", "20–25", "21–25", "", "", "60–75", "P2 P3"], ["22 Nov", "16:00", "Canada", "0–3", "Serbia and Montenegro", "18–25", "18–25", "17–25", "", "", "53–75", "P2 P3"], ["18 Nov", "18:10", "South Korea", "1–3", "Canada", "28–26", "23–25", "16–25", "23–25", "", "90–101", "P2 P3"], ["21 Nov", "14:00", "Tunisia", "2–3", "Canada", "15–25", "29–27", "25–21", "21–25", "13–15", "103–113", "P2 P3"], ["21 Nov", "18:50", "Russia", "3–0", "Kazakhstan", "25–16", "25–18", "25–18", "", "", "75–52", "P2 P3"], ["18 Nov", "14:00", "Russia", "3–0", "Tunisia", "25–15", "29–27", "25–20", "", "", "79–62", "P2 P3"], ["22 Nov", "14:00", "Kazakhstan", "0–3", "Tunisia", "19–25", "23–25", "24–26", "", "", "66–76", "P2 P3"], ["22 Nov", "18:00", "South Korea", "0–3", "Russia", "13–25", "21–25", "13–25", "", "", "47–75", "P2 P3"], ["19 Nov", "16:15", "Tunisia", "0–3", "Serbia and Montenegro", "21–25", "12–25", "23–25", "", "", "56–75", "P2 P3"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many games did canada win? | 3 | Answer: | 128 |
Table InputTable: [["Year", "Winner", "Jockey", "Trainer", "Owner", "Distance\\n(Miles)", "Time", "Win $"], ["1989", "Highest Glory", "Jose A. Santos", "D. Wayne Lukas", "H. Joseph Allen", "1", "1:37.20", "$70,440"], ["1978", "Late Bloomer", "Jorge Velasquez", "John M. Gaver, Jr.", "Greentree Stable", "1-1/16", "1:41.60", ""], ["1979", "Danielle B.", "Ruben Hernandez", "John O. Hertler", "Our Precious Stable", "1-1/16", "1:45.40", "$33,000"], ["2011", "Winter Memories", "Javier Castellano", "James J. Toner", "Phillips Racing Partnership", "1-1/8", "1:51.06", "$150,000"], ["2001", "Voodoo Dancer", "Corey Nakatani", "Christophe Clement", "Green Hills Farms", "1-1/8", "1:47.69", "$150,000"], ["1988", "Topicount", "Angel Cordero, Jr.", "H. Allen Jerkens", "Centennial Farms", "1", "1:38.00", "$82,260"], ["2003", "Indy Five Hundred", "Pat Day", "Robert Barbara", "Georgica Stable", "1-1/8", "1:48.44", "$150,000"], ["1995", "Perfect Arc", "John Velazquez", "Angel Penna, Jr.", "Brazil Stables", "1-1/16", "1:42.35", "$101,070"], ["1983", "Pretty Sensible", "Alfredo Smith, Jr.", "George Travers", "John Zervas", "1", "1:37.80", "$33,600"], ["2012", "Samitar", "Ramon Dominguez", "Chad C. Brown", "Martin S. Schwartz", "1-1/8", "1:48.74", "$180,000"], ["1980", "Mitey Lively", "Jorge Velasquez", "Douglas R. Peterson", "Tayhill Stable", "1", "1:36.40", "$33,480"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long was the most miles they ran? | 1-1/8 | Answer: | 128 |
Table InputTable: [["Season", "Footballer", "Club", "Position", "Nationality"], ["2012-13", "Itumeleng Khune", "Kaizer Chiefs", "GK", "South Africa"], ["2007-08", "Itumeleng Khune", "Kaizer Chiefs", "GK", "South Africa"], ["2002-03", "Moeneeb Josephs", "Ajax Cape Town", "GK", "South Africa"], ["1999-00", "Siyabonga Nomvethe", "Kaizer Chiefs", "FW", "South Africa"], ["1997-98", "Raphael Chukwu", "Mamelodi Sundowns", "FW", "Nigeria"], ["2001-02", "Jabu Pule", "Kaizer Chiefs", "MF", "South Africa"], ["2011-12", "Siyabonga Nomvethe", "Moroka Swallows", "FW", "South Africa"], ["1996-97", "Wilfred Mugeyi", "Bush Bucks", "FW", "Zimbabwe"], ["2008-09", "Teko Modise", "Orlando Pirates", "MF", "South Africa"], ["2010-11", "Thulani Serero", "Ajax Cape Town", "MF", "South Africa"], ["2003-04", "Tinashe Nengomasha", "Kaizer Chiefs", "MF", "Zimbabwe"], ["2006-07", "Godfrey Sapula", "Mamelodi Sundowns", "MF", "South Africa"], ["2004-05", "Sandile Ndlovu", "Dynamos", "FW", "South Africa"], ["2000-01", "Benjani Mwaruwari", "Jomo Cosmos", "FW", "Zimbabwe"], ["2005-06", "Surprise Moriri", "Mamelodi Sundowns", "MF", "South Africa"], ["1998-99", "Roger Feutmba", "Mamelodi Sundowns", "MF", "Cameroon"], ["2009-10", "Katlego Mphela", "Mamelodi Sundowns", "FW", "South Africa"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:first gk awarded? | Moeneeb Josephs | Answer: | 128 |
Table InputTable: [["Week", "Date", "Opponent", "Result", "Record", "TV Time", "Attendance"], ["13", "December 9, 2001", "San Francisco 49ers", "W 27–14", "10–2", "FOX 12:00pm", "66,218"], ["7", "October 28, 2001", "New Orleans Saints", "L 34–31", "6–1", "FOX 12:00pm", "66,189"], ["2", "September 23, 2001", "at San Francisco 49ers", "W 30–26", "2–0", "FOX 3:15pm", "67,536"], ["9", "November 11, 2001", "Carolina Panthers", "W 48–14", "7–1", "FOX 12:00pm", "66,069"], ["16", "December 30, 2001", "Indianapolis Colts", "W 42–17", "13–2", "CBS 12:00pm", "66,084"], ["17", "January 6, 2002", "Atlanta Falcons", "W 31–13", "14–2", "FOX 3:15pm", "66,033"], ["3", "September 30, 2001", "Miami Dolphins", "W 42–10", "3–0", "CBS 12:00pm", "66,046"], ["1", "September 9, 2001", "at Philadelphia Eagles", "W 20–17 (OT)", "1–0", "FOX 3:15pm", "66,243"], ["4", "October 8, 2001", "at Detroit Lions", "W 35–0", "4–0", "ABC 8:00pm", "77,765"], ["5", "October 14, 2001", "New York Giants", "W 15–14", "5–0", "FOX 12:00pm", "65,992"], ["11", "November 26, 2001", "Tampa Bay Buccaneers", "L 24–17", "8–2", "ABC 8:00pm", "66,198"], ["12", "December 2, 2001", "at Atlanta Falcons", "W 35–6", "9–2", "FOX 3:15pm", "60,787"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many wins do the st. louis rams have in total? | 14 | Answer: | 128 |
Table InputTable: [["Fence", "Name", "Jockey", "Age", "Handicap (st-lb)", "Starting price", "Fate"], ["06", "Nedsmar", "John Hudson", "11", "10-13", "100/1", "Fell"], ["18", "Leedsy", "George Robinson", "7", "10-13", "18/1", "Fell"], ["26", "Rondetto", "Jeff King", "9", "11-6", "100/8", "Fell"], ["22", "Kapeno", "David Dick", "8", "11-6", "100/8", "Fell"], ["04", "Red Tide", "Johnny Haine", "8", "10-13", "33/1", "Fell"], ["06", "Forgotten Dreams", "R Coonan", "11", "11-0", "22/1", "Fell"], ["24", "Pontin-Go", "Johnny Lehane", "13", "10-13", "50/1", "Fell"], ["01", "Ayala", "Stan Mellor", "11", "10-13", "50/1", "Fell"], ["09", "Groomsman", "Beltrán Osorio", "10", "10-13", "100/1", "Fell"], ["06", "Barleycroft", "Phil Harvey", "10", "10-13", "100/1", "Brought Down"], ["?", "Blonde Warrior", "Mr D Crossley-Cooke", "13", "10-13", "100/1", "Fell"], ["17", "Bold Biri", "Michael Scudamore", "9", "10-13", "100/1", "Fell"], ["?", "Black Spot", "J Gamble", "8", "10-13", "100/1", "Fell"], ["?", "Leslie", "P Jones", "9", "10-13", "33/1", "Pulled Up"], ["?", "Reproduction", "Robin Langley", "12", "10-13", "40/1", "Pulled-Up"], ["06", "Crobeg", "Mr Macer Gifford", "12", "10-13", "100/1", "Brought Down"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many non-finishing horses fell? | 15 | Answer: | 128 |
Table InputTable: [["Title", "Year", "Authors", "Publisher", "Pages"], ["Global Turf Wars: Re-Inventing the Telecoms Operator for the Age of Global Competition", "1999", "Tim Hills, David Cleevely, Andrea Smith", "Analysis Publications", "218"], ["Regulating the Telecoms Market: Competition and Innovation in the Broadband Economy", "2003", "Tim Hills, David Cleevely, Ross Pow", "Analysis Publications", "35"], ["Rural Telecoms Handbook: Equipment and Manufacturers", "1992", "Tim Hills, David Cleevely", "Analysys Publications", "-"], ["Regional Structure and Telecommunications Demand: A Case Study of Kenya (Ph.D. thesis)", "1982", "D. D. Cleevely", "University of Cambridge", "-"], ["The Far Reaching Effects of Broadband", "2002", "David Cleevely", "Institution of Engineering & Technology", "415"], ["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"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many more pages is global turf wars than regulating the telecoms market? | 183 pages | Answer: | 128 |
Table InputTable: [["Date", "Date", "", "Rank", "Tournament name", "Venue", "City", "Winner", "Runner-up", "Score"], ["11–15", "12–01", "ENG", "WR", "UK Championship", "Guild Hall", "Preston", "Stephen Hendry", "John Higgins", "10–9"], ["05–??", "05–??", "WAL", "", "Pontins Professional", "Pontins", "Prestatyn", "Martin Clark", "Andy Hicks", "9–7"], ["10–16", "10–27", "ENG", "WR", "Grand Prix", "Bournemouth International Centre", "Bournemouth", "Mark Williams", "Euan Henderson", "9–5"], ["10–05", "10–14", "SCO", "", "Benson & Hedges Championship", "JP Snooker Centre", "Edinburgh", "Brian Morgan", "Drew Henry", "9–8"], ["09–09", "09–15", "THA", "WR", "Asian Classic", "Riverside Montien Hotel", "Bangkok", "Ronnie O'Sullivan", "Brian Morgan", "9–8"], ["02–13", "02–22", "SCO", "WR", "International Open", "A.E.C.C.", "Aberdeen", "Stephen Hendry", "Tony Drago", "9–1"], ["04–19", "05–05", "ENG", "WR", "World Snooker Championship", "Crucible Theatre", "Sheffield", "Ken Doherty", "Stephen Hendry", "18–12"], ["03–18", "03–23", "IRL", "", "Irish Masters", "Goff's", "Kill", "Stephen Hendry", "Darren Morgan", "9–8"], ["01–02", "01–05", "ENG", "", "Charity Challenge", "International Convention Centre", "Birmingham", "Stephen Hendry", "Ronnie O'Sullivan", "9–8"], ["12–28", "05–18", "ENG", "", "European League", "Diamond Centre", "Irthlingborough", "Ronnie O'Sullivan", "Stephen Hendry", "10–8"], ["02–02", "02–09", "ENG", "", "Masters", "Wembley Conference Centre", "London", "Steve Davis", "Ronnie O'Sullivan", "10–8"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the next runner up after brian morgan? | Alan McManus | Answer: | 128 |
Table InputTable: [["ZOOM", "Cast Member 1", "Cast Member 2", "Cast Member 3", "Cast Member 4", "Cast Member 5", "Cast Member 6", "Cast Member 7"], ["Season 2 (2000)", "Raymond \"Ray\" MacMore", "Caroline Botelho", "Claudio Schwartz", "Alisa Besher", "Jessica \"Jessie\" Ogungbadero", "Kenneth \"Kenny\" Yates", "Zoe Costello"], ["Season 5 (2003)", "Caroline Botelho", "Aline Toupi", "Estuardo Alvizures", "Garrett DiBona", "Michael \"Mike\" Hansen", "Kortney Sumner", "Elena \"Shing Ying\" Shieh"], ["Season 4 (2002)", "Aline Toupi", "Garrett DiBona", "Rachel Redd", "Matthew \"Matt\" Runyon", "Estuardo Alvizures", "Kaleigh Cronin", "Caroline Botelho"], ["Season 3 (2001)", "Frances Domond", "Kenneth \"Kenny\" Yates", "Rachel Redd", "Eric Rollins", "Kaleigh Cronin", "Kevin \"Buzz\" Barrette", "Caroline Botelho"], ["Season 7 (2005)", "W. Nick Henry", "Taylor Garron", "Francesco Tena", "Noreen Raja", "Emily Marshall", "Kyle Larrow", "Elena \"Shing Ying\" Shieh"], ["Season 6 (2004)", "Michael \"Mike\" Hansen", "Kortney Sumner", "Francesco Tena", "Cara Harvey", "Kyle Larrow", "Maya Morales", "Elena \"Shing Ying\" Shieh"], ["Season 1 (1999)", "Zoe Costello", "Jared Nathan", "Keiko Yoshida", "Pablo Velez, Jr.", "Alisa Besher", "David Toropov", "Lynese Browder"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which cast member went on to teach spanish? | Keiko Yoshida | Answer: | 128 |
Table InputTable: [["Player", "League", "Cup", "Europa\\nLeague", "Total"], ["Stanislav Kostov", "1", "0", "0", "1"], ["Tomislav Kostadinov", "0", "0", "1", "1"], ["Christian Tiboni", "0", "0", "1", "1"], ["Pavel Vidanov", "0", "0", "1", "1"], ["Kostadin Stoyanov", "1", "0", "0", "1"], ["Michel Platini", "10", "0", "0", "10"], ["Spas Delev", "13", "7", "2", "22"], ["Giuseppe Aquaro", "3", "0", "2", "5"], ["Apostol Popov", "2", "0", "0", "2"], ["Rumen Trifonov", "2", "0", "1", "3"], ["Emil Gargorov", "2", "0", "0", "2"], ["Aleksandar Tonev", "2", "0", "0", "2"], ["Marquinhos", "9", "1", "3", "13"], ["Todor Yanchev", "0", "1", "1", "2"], ["Cillian Sheridan", "4", "2", "1", "7"], ["Boris Galchev", "1", "0", "0", "1"], ["Total", "53", "11", "14", "78"], ["Gregory Nelson", "3", "0", "1", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the top scorer in this season? | Spas Delev | Answer: | 128 |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "3.", "21 May 2006", "Hamburg Masters, Hamburg, Germany", "Clay", "Radek Štěpánek", "6–1, 6–3, 6–3"], ["Winner", "11.", "14 April 2013", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Kevin Anderson", "7–6(8–6), 4–6, 6–3"], ["Winner", "2.", "2 May 2004", "Torneo Godó, Barcelona, Spain", "Clay", "Gastón Gaudio", "6–3, 4–6, 6–2, 3–6, 6–3"], ["Winner", "1.", "29 July 2001", "Orange Warsaw Open, Sopot, Poland", "Clay", "Albert Portas", "1–6, 7–5, 7–6(7–2)"], ["Runner-up", "1.", "15 April 2001", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Guillermo Cañas", "5–7, 2–6"], ["Winner", "9.", "22 February 2009", "Copa Telmex, Buenos Aires, Argentina", "Clay", "Juan Mónaco", "7–5, 2–6, 7–6(7–5)"], ["Runner-up", "2.", "20 July 2003", "Mercedes Cup, Stuttgart, Germany", "Clay", "Guillermo Coria", "2–6, 2–6, 1–6"], ["Winner", "5.", "5 August 2007", "Orange Warsaw Open, Sopot, Poland (2)", "Clay", "José Acasuso", "7–5, 6–0"], ["Winner", "4.", "16 July 2006", "Swedish Open, Båstad, Sweden", "Clay", "Nikolay Davydenko", "6–2, 6–1"], ["Runner-up", "3.", "1 May 2005", "Estoril Open, Estoril, Portugal", "Clay", "Gastón Gaudio", "1–6, 6–2, 1–6"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many winners total are there? | 12 | Answer: | 128 |
Table InputTable: [["District\\nbalance\\n[clarification needed]", "Area\\nkm2", "Area\\nsq mi", "Pop.\\n1998", "Pop.\\n2008", "Pop./km²\\n2008"], ["Sandy Bay", "15.3", "5.9", "254", "205", "13.4"], ["Longwood", "33.4", "12.9", "960", "715", "21.4"], ["Half Tree Hollow", "1.6", "0.6", "1,140", "901", "563.1"], ["Levelwood", "14.0", "5.4", "376", "316", "22.6"], ["Royal Mail Ship\\nSt. Helena[clarification needed]", "–", "–", "149", "171", "–"], ["Jamestown\\nHarbour", "–", "–", "20", "9", "–"], ["Blue Hill", "36.5", "14.1", "177", "153", "4.2"], ["Jamestown", "3.6", "1.4", "884", "714", "198.3"], ["Saint Paul's", "11.4", "4.4", "908", "795", "69.7"], ["Total", "121.7", "47.0", "5,157", "4,255", "35.0"], ["Alarm Forest", "5.9", "2.3", "289", "276", "46.8"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of square miles in sandy bay and longwood? | 18.8 | Answer: | 128 |
Table InputTable: [["Rank", "Player", "From", "Transfer Fee\\n(€ millions)", "Year"], ["2.", "Cesc Fàbregas", "Arsenal", "29+5(variables)", "2011"], ["1.", "Neymar", "Santos FC", "86.0", "2013"], ["7.", "Adriano", "Sevilla", "13.5", "2010"], ["4.", "Javier Mascherano", "Liverpool", "26.8", "2010"], ["3.", "Alexis Sánchez", "Udinese", "26+11(add ons)", "2011"], ["6.", "Jordi Alba", "Valencia", "14.0", "2012"], ["5.", "Alex Song", "Arsenal", "19.0", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the largest transfer fee? | 86.0 | Answer: | 128 |
Table InputTable: [["Year", "Record", "Finish", "Manager", "Playoffs"], ["1967", "60-87", "12th", "Wayne Terwilliger", ""], ["1987", "65-75", "9th", "Bob Bailey", ""], ["1974", "67-77", "6th", "Roy Hartsfield", ""], ["1961", "68-86", "6th", "Tommy Heath / Bill Werle", "none"], ["1978", "56-82", "8th", "Dick Phillips", ""], ["1986", "65-79", "9th", "Tommy Sandt", ""], ["1964", "60-98", "10th", "Bob Lemon", ""], ["1968", "78-69", "3rd", "Bill Adair", ""], ["1969", "74-72", "4th", "Chuck Tanner", ""], ["1962", "77-76", "5th", "Irv Noren", "none"], ["1976", "77-68", "2nd", "Roy Hartsfield", "League Champs"], ["1966", "63-84", "10th", "George Case", ""], ["1982", "73-71", "5th", "Doug Rader", ""], ["1963", "81-77", "4th", "Irv Noren", ""], ["1975", "88-56", "1st", "Roy Hartsfield", "League Champs"], ["1965", "75-72", "6th (t)", "George Case", ""], ["1984", "87-53", "1st", "Tommy Sandt", "Lost League Finals"], ["1983", "72-71", "5th", "Tom Trebelhorn", ""], ["1977", "79-67", "2nd", "Dick Phillips", "Lost League Finals"], ["1980", "76-65", "5th", "Doug Rader", "Lost League Finals"], ["1985", "84-59", "1st", "Tommy Sandt", "Lost in 1st round"], ["1970", "98-48", "1st", "Chuck Tanner", "Lost League Finals"], ["1979", "72-76", "8th", "Dick Phillips", "Lost League Finals"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many managers were there between 1961 and 1987? | 16 | Answer: | 128 |
Table InputTable: [["Poll Source", "Sample Size", "Margin of Error", "Date", "Democrat", "%", "Republican", "%"], ["Rasmussen Reports", "500", "", "Feb 18, 2008", "Hillary Clinton", "37", "John McCain", "47"], ["Survey USA", "563", "4.2", "Feb 15-17, 2008", "Hillary Clinton", "41", "John McCain", "52"], ["Rasmussen Reports", "500", "", "Feb 18, 2008", "Barack Obama", "44", "John McCain", "41"], ["Survey USA", "563", "4.2", "Feb 15-17, 2008", "Barack Obama", "51", "John McCain", "41"], ["Survey USA", "517", "4.4", "Mar 14-16, 2008", "Hillary Clinton", "44", "John McCain", "48"], ["Rasmussen Reports", "500", "4.5", "Mar 31, 2008", "Hillary Clinton", "36", "John McCain", "51"], ["Rasmussen Reports", "500", "4.5", "Mar 31, 2008", "Barack Obama", "46", "John McCain", "42"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Hillary Clinton", "48", "Mitt Romney", "40"], ["Survey USA", "506", "4.4", "Oct 12-14, 2007", "Hillary Clinton", "50", "Mitt Romney", "42"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Hillary Clinton", "44", "John McCain", "48"], ["Survey USA", "509", "4.4", "Oct 12-14, 2007", "Hillary Clinton", "50", "Fred Thompson", "42"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Hillary Clinton", "47", "Mike Huckabee", "45"], ["Survey USA", "543", "4.3", "Jan 4-6, 2008", "Barack Obama", "59", "Mitt Romney", "33"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what poll source was used the most? | Survey USA | Answer: | 128 |
Table InputTable: [["Name", "Type", "Builder", "Works number", "Date", "Notes"], ["Leonidas", "0-4-0ST", "Hawthorn Leslie", "3159", "1916", "To G. Simm (Machinery) Ltd. 11/4/1949 thence to T.Hall & Co.(Llansamlet) Ltd, dealer, 1949. To Norton Hill Colliery, Somerset 1951, scrapped circa 1955"], ["Lucifer", "0-4-0ST", "Hawthorn Leslie", "3168", "1916", "To T. Hall & Co. (Llansamlet) Ltd. 1949 thence to NCB Graigola Fuel Works, Swansea, 1950. To Caerphilly Tar Distillation Plant 3/1959, thence to J. Pesci & Sons Ltd. for scrap circa 1961; scrapped circa 3/1963"], ["Arethusa", "0-4-0ST", "Hawthorn Leslie", "3090", "1914", "To T. Hall & Co. (Llanshamlet), dealer, 1949, thence to Stella South Power Station, Blaydon-on-Tyne 12/1952. To Blaydon Generating Station 11/1955; scrapped 1965"], ["Lance", "0-4-0ST", "Hawthorn Leslie", "3155", "1915", "To South Staffs Mond Gas Company, Dudley Port, Staffs. circa 1920. To J. Cashmore for scrap 1952"], ["Lord Kitchener", "0-4-0ST", "Bagnall", "1702", "1902", "To Walter Scott & Middleton (contractors), White Nile Dam, Sudan by 9/1920. To Pauling & Co. Ltd. (Contractors), Park Royal, London by 1950 and transferred to Crymlyn Burrows Depot. Sold to Benjamin Hughes & Co. Ltd., Loughor, Glamorgan 2/1950 and scrapped 1964"], ["Pioneer", "0-4-0ST", "Manning Wardle", "676", "1878", "To Isherwood & Co. (contractor), Brentford 1920, sold or scrapped shortly after 6/1920"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which builder built more than any other builder? | Hawthorn Leslie | Answer: | 128 |
Table InputTable: [["Year", "Result", "Award", "Film"], ["2008", "Nominated", "Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2010", "Nominated", "SAG Award Outstanding Performance by a Male Actor in a Comedy Series", "Two and a Half Men"], ["2006", "Nominated", "Emmy Award for Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2006", "Nominated", "Golden Globe Award for Best Actor – Television Series Musical or Comedy", "Two and a Half Men"], ["2007", "Nominated", "Emmy Award for Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2005", "Nominated", "SAG Award Outstanding Performance by a Male Actor in a Comedy Series", "Two and a Half Men"], ["2006", "Won", "Golden Icon Award Best Actor - Comedy Series", "Two and a Half Men"], ["2007", "Nominated", "Teen Choice Award Choice TV Actor: Comedy", "Two and a Half Men"], ["2008", "Nominated", "Teen Choice Awards Choice TV Actor: Comedy", "Two and a Half Men"], ["2005", "Nominated", "Golden Globe Award for Best Actor – Television Series Musical or Comedy", "Two and a Half Men"], ["2002", "Nominated", "Kids' Choice Awards Favorite Television Actor", "Two and a Half Men"], ["2008", "Won", "ALMA Award Outstanding Actor in a Comedy Television Series", "Two and a Half Men"], ["2008", "Nominated", "People's Choice Award Favorite Male TV Star", ""], ["2002", "Nominated", "ALMA Award Outstanding Actor in a Television Series", "Spin City"], ["2007", "Nominated", "People's Choice Award Favorite Male TV Star", ""], ["2001", "Nominated", "ALMA Award Outstanding Actor in a Television Series", "Spin City"], ["2002", "Won", "Golden Globe Award Best Performance by an Actor in a Television Series - Musical or Comedy", "Spin City"], ["1989", "Won", "Bronze Wrangler Theatrical Motion Picture", "Young Guns"], ["1999", "Nominated", "SAG Award Outstanding Performance by a Cast in a Theatrical Motion Picture", "Being John Malkovich"], ["1999", "Nominated", "Online Film Critics Society Award for Best Cast", "Being John Malkovich"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of awards (nominations and wins) for two and a half men? | 12 | Answer: | 128 |
Table InputTable: [["Pos", "Team", "Played", "Won", "Draw", "Lost", "Goals For", "Goals Against", "Goal Difference", "Points", "Notes"], ["1", "KR", "18", "11", "4", "3", "27", "14", "+13", "37", "UEFA Champions League"], ["4", "ÍBV", "18", "8", "5", "5", "29", "17", "+12", "29", "Inter-Toto Cup"], ["3", "Grindavík", "18", "8", "6", "4", "25", "18", "+7", "30", "UEFA Cup"], ["2", "Fylkir", "18", "10", "5", "3", "39", "16", "+23", "35", "UEFA Cup"], ["10", "Leiftur", "18", "3", "7", "8", "24", "39", "-15", "16", "Relegated"], ["9", "Stjarnan", "18", "4", "5", "9", "18", "31", "-13", "17", "Relegated"], ["6", "Keflavík", "18", "4", "7", "7", "21", "35", "-14", "19", ""], ["8", "Fram", "18", "4", "5", "9", "22", "33", "-11", "17", ""], ["7", "Breiðablik", "18", "5", "3", "10", "29", "35", "-6", "18", ""], ["5", "ÍA", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many teams won at least half or more of their games? | 2 | Answer: | 128 |
Table InputTable: [["#", "Player", "Goals", "Caps", "Career"], ["9T", "Earnie Stewart", "17", "101", "1990–2004"], ["1", "Landon Donovan", "57", "155", "2000–present"], ["8", "Eddie Johnson", "19", "62", "2004–present"], ["2", "Clint Dempsey", "36", "103", "2004–present"], ["4", "Brian McBride", "30", "95", "1993–2006"], ["6T", "Bruce Murray", "21", "86", "1985–1993"], ["5", "Joe-Max Moore", "24", "100", "1992–2002"], ["6T", "Jozy Altidore", "21", "67", "2007–present"], ["9T", "DaMarcus Beasley", "17", "114", "2001–present"], ["3", "Eric Wynalda", "34", "106", "1990–2000"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many goals did earnie stewart score? | 17 | Answer: | 128 |
Table InputTable: [["Name", "Route number(s)", "Length (mi)", "Location", "Notes"], ["Wilbur Cross Highway", "*", "8.0", "Sturbridge", "I-84 in Massachusetts is designated the Wilbur Cross Highway. It runs 8 miles (13 km) from the Connecticut state border to the Mass Pike at Exit 9."], ["Pilgrims Highway", "", "42.5", "Bourne to Braintree", "The Pilgrims Highway is the southern portion of Route 3, a 42-mile (68 km) long freeway which serves as a connector between Cape Cod (via U.S. Route 6) and the Boston metropolitan area (via I-93 and I-95).\\n- U.S. Route 44 runs along the highway between Exits 6 and 7."], ["Grand Army of the Republic Highway", "*", "117.46", "Seekonk to Provincetown", "The cross-country U.S. Route 6 is designated Grand Army of the Republic Highway over its entire length, which spans 3,205 miles (5,158 km)."], ["Yankee Division Highway\\n(Circumferential Highway)", "*", "64.74", "Braintree to Gloucester", "The Yankee Division Highway consists of the Route 128 beltway before it was truncated to its southern terminus in Canton, and continues to span its entire length. It stretches from I-93's Exit 7 in Braintree to Route 128's northern terminus at Route 127A in Gloucester.\\n- I-95 runs along the highway between Exits 12 and 45 (concurrent with 128).\\n- I-93 runs along the highway between Exits 1 and 7.\\n- U.S. Route 1 runs along the highway between I-95 Exit 15B and I-93 Exit 7."], ["Massachusetts Turnpike", "*", "138.1", "West Stockbridge\\nto Boston", "The Mass Pike is a toll road running from the New York state border to downtown Boston. It serves as the main cross-state freeway connecting the western and eastern portions of the state. The \"Pike\" carries the easternmost 138 miles (222 km) of cross-country Interstate 90."], ["Taunton-New Bedford Expressway\\n(Alfred M. Bessette Memorial Highway)", "", "19.3", "New Bedford to Taunton", "The New Bedford Expressway comprises the southern 19 miles (31 km) of Route 140, and serves as a freeway connection between U.S. Route 6 in New Bedford and Route 24 (Exit 12) in Taunton, near I-495."]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what road has the longest length? | Massachusetts Turnpike | Answer: | 128 |
Table InputTable: [["Polling Firm", "Source", "Date Published", "N.Anastasiades", "G.Lillikas", "S.Malas", "Others"], ["Noverna", "[11]", "2 December 2012", "35.6%", "17.2%", "18.1%", "4.1%"], ["Evresis", "[14]", "22 December 2012", "37.4%", "19.8%", "21.8%", "0.5%"], ["Noverna", "[3]", "23 September 2012", "35.02%", "15.81%", "17.78%", ""], ["Evresis", "[6]", "2 November 2012", "36.9%", "17.7%", "20.6%", "1.4%"], ["Evresis", "[18]", "1 February 2013", "40.8%", "19.9%", "22.2%", "2.5%"], ["Evresis", "[10]", "27 November 2012", "37.1%", "19.6%", "20.8%", "0.6%"], ["Evresis", "[2]", "18 September 2012", "35.2%", "17.5%", "19.7%", "1.7%"], ["Prime Consulting Ltd", "[12]", "3 December 2012", "35%", "19.1%", "18.6%", "1.4%"], ["Prime Consulting Ltd", "[19]", "4 February 2013", "39.8%", "19.3%", "20%", "3%"], ["RAI Consultants Ltd", "[21]", "9 February 2013", "42.1%", "19.4%", "21.1%", "4.4%"], ["Prime Consulting Ltd", "[20]", "9 February 2013", "40.6%", "19.6%", "20.4%", "2.9%"], ["RAI Consultants", "[7]", "4 November 2012", "38.8%", "19.8%", "21.1%", "2.3%"], ["Prime Consulting Ltd", "[9]", "18 November 2012", "35.9%", "18.7%", "19.6%", "0.6%"], ["Prime Consulting Ltd", "[17]", "27 January 2013", "39.2%", "18.8%", "19.8%", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which poll did anastasiades win by a larger margin, feb 1 2013 or dec 3 2012? | 1 February 2013 | Answer: | 128 |
Table InputTable: [["Year", "Date", "Winner", "Result", "Loser", "Location"], ["2009", "November 1", "Philadelphia Eagles", "40-17", "New York Giants", "Lincoln Financial Field"], ["2008", "November 9", "New York Giants", "36-31", "Philadelphia Eagles", "Lincoln Financial Field"], ["2007", "January 7", "Philadelphia Eagles", "23-20", "New York Giants", "Lincoln Financial Field"], ["2004", "September 12", "Philadelphia Eagles", "31-17", "New York Giants", "Lincoln Financial Field"], ["2007", "December 9", "New York Giants", "16-13", "Philadelphia Eagles", "Lincoln Financial Field"], ["2003", "November 16", "Philadelphia Eagles", "28-10", "New York Giants", "Lincoln Financial Field"], ["2006", "September 17", "New York Giants", "30-24 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2005", "December 11", "New York Giants", "26-23 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2009", "January 11", "Philadelphia Eagles", "23-11", "New York Giants", "Giants Stadium"], ["2009", "December 13", "Philadelphia Eagles", "45-38", "New York Giants", "Giants Stadium"], ["2006", "December 17", "Philadelphia Eagles", "36-22", "New York Giants", "Giants Stadium"], ["2008", "December 7", "Philadelphia Eagles", "20-14", "New York Giants", "Giants Stadium"], ["2001", "October 22", "Philadelphia Eagles", "10-9", "New York Giants", "Giants Stadium"], ["2003", "October 19", "Philadelphia Eagles", "14-10", "New York Giants", "Giants Stadium"], ["2004", "November 28", "Philadelphia Eagles", "27-6", "New York Giants", "Giants Stadium"], ["2000", "October 29", "New York Giants", "24-7", "Philadelphia Eagles", "Giants Stadium"], ["2005", "November 20", "New York Giants", "27-17", "Philadelphia Eagles", "Giants Stadium"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the next location after the lincoln financial field in 2009? | Giants Stadium | Answer: | 128 |
Table InputTable: [["Chart Year", "Artist", "Album", "Song", "Billboard Hot 100", "Billboard Hot R&B/Hip Hop", ""], ["2009", "Mary J. Blige", "Stronger with Each Tear", "The One ft. Drake", "63", "32", ""], ["2009", "Musiq Soulchild", "OnMyRadio", "IfULeave ft. Mary J. Blige", "71", "6", ""], ["2008", "Usher", "Here I Stand", "Trading Places", "45", "4", ""], ["2007", "Sean Paul", "The Trinity", "(When You Gonna) Give It Up To Me", "3", "5", ""], ["2008", "Usher", "Here I Stand", "Moving Mountains", "67", "18", ""], ["2009", "Lupe Fiasco", "Lasers", "Shining Down ft. Matthew Santos", "93", "", ""], ["2009", "Jamie Foxx", "Intuition", "Digital Girl ft. The-Dream & Kanye West", "92", "38", ""], ["2009", "The-Dream", "Love vs. Money", "Rockin' That Shit", "22", "2", ""], ["2012", "Future", "Pluto", "Neva End f/Kelly Rowland", "21", "", ""], ["2011", "Marsha Ambrosius", "Late Nights & Early Mornings", "Late Nights & Early Mornings", "New Single", "30", ""], ["2011", "Big Sean", "Finally Famous", "Dance (A$$)", "10", "3", ""], ["2014", "Marsha Ambrosius", "FVCK&LOVE", "Stronger Than Pride", "New Single", "", ""], ["2010", "Trey Songz", "Passion, Pain & Pleasure", "Can't Be Friends", "43", "1", ""], ["2010", "The-Dream", "Love vs. Money", "Walkin' on the Moon ft. Kanye West", "87", "38", ""], ["2009", "Whitney Houston", "I Look to You", "I Look To You", "70", "19", ""], ["2013", "Chris Brown", "X", "Fine China", "31", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which artist is above the last artist | Rihanna | Answer: | 128 |
Table InputTable: [["Title", "Year", "Peak chart positions\\nUS", "Peak chart positions\\nUS R&B", "Peak chart positions\\nUS Rap", "Album"], ["\"Gotta Believe It\"\\n(featuring Just Blaze)", "2009", "—", "—", "—", "Warning Shots 2"], ["\"Pain In My Life\"\\n(featuring Trey Songz)", "2006", "—", "—", "—", "N/A"], ["\"Not Like Them\"\\n(featuring Styles P)", "2012", "—", "—", "—", "The Greatest Story Never Told Chapter 2: Bread and Circuses"], ["\"Clap\"\\n(featuring Faith Evans)", "2011", "—", "—", "—", "The Greatest Story Never Told"], ["\"Best Mistake\"\\n(featuring G. Martin)", "2013", "—", "—", "—", "The Greatest Story Never Told Chapter 3: The Troubled Times of Brian Carenard"], ["\"Best Thing That I Found\"\\n(featuring Lecrae and Corbett)", "2012", "—", "—", "—", "The Greatest Story Never Told Chapter 2: Bread and Circuses"], ["\"C'mon Baby\"\\n(featuring Swizz Beatz)", "2007", "—", "—", "—", "N/A"], ["\"Do You Know\"", "2002", "—", "—", "—", "N/A"], ["\"Bring Me Down\"", "2010", "—", "—", "—", "N/A"], ["\"The Greatest Story Never Told\"", "2011", "—", "—", "—", "The Greatest Story Never Told"], ["\"Favorite Things\"", "2004", "—", "—", "—", "N/A"], ["\"Say Yes\"", "2001", "—", "—", "—", "N/A"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what were the number of albums released? | 4 | Answer: | 128 |
Table InputTable: [["No.", "Score", "Player", "Team", "Balls", "Inns.", "Opposing team", "Date", "Result"], ["29", "192*", "Viv Richards (1/2)", "West Indies", "NR", "2", "India", "11 December 1974", "Won"], ["46", "109*", "Viv Richards (2/2)", "West Indies", "111", "4", "India", "25 November 1987", "Won"], ["31", "120", "Sunil Gavaskar (1/3)", "India", "NR", "1", "West Indies", "24 January 1979", "Drawn"], ["43", "103", "Clive Lloyd", "West Indies", "202", "2", "India", "29 October 1983", "Drawn"], ["41", "121", "Sunil Gavaskar (3/3)", "India", "128", "1", "West Indies", "29 October 1983", "Drawn"], ["15", "100*", "Joe Solomon", "West Indies", "NR", "2", "India", "6 February 1959", "Drawn"], ["32", "109", "Dilip Vengsarkar (1/4)", "India", "NR", "1", "West Indies", "24 January 1979", "Drawn"], ["3", "128", "Everton Weekes", "West Indies", "NR", "1", "India", "10 November 1948", "Drawn"], ["45", "102", "Dilip Vengsarkar (4/4)", "India", "257", "3", "West Indies", "25 November 1987", "Lost"], ["42", "159", "Dilip Vengsarkar (3/4)", "India", "238", "1", "West Indies", "29 October 1983", "Drawn"], ["33", "126*", "Kapil Dev", "India", "124", "1", "West Indies", "24 January 1979", "Drawn"], ["30", "179", "Dennis Amiss", "England", "397", "1", "India", "17 December 1976", "Won"], ["12", "109", "Chandu Borde", "India", "NR", "1", "West Indies", "6 February 1959", "Drawn"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:tell me the date of the last time the west indies appear on the list. | 25 November 1987 | Answer: | 128 |
Table InputTable: [["Series", "Name", "Age", "Hometown", "Occupation", "Status"], ["BB11", "Dave (David) Vaughan", "39", "Torfaen", "Minister", "2nd - Runner-up"], ["BB1", "Anna Nolan", "29", "Dublin", "Office Manager", "2nd - Runner-up"], ["BB8", "Lesley Brain", "60", "Gloucestershire", "Retired", "21st - Walked"], ["BB14", "Callum Knell", "28", "Kent", "Sports coach", "8th - Evicted"], ["BB6", "Eugene Sully", "27", "Crawley", "Student", "2nd - Runner-up"], ["BB13", "Deana Uppal", "23", "Sandwell", "Model", "3rd - Third Place"], ["BB9", "Dennis McHugh", "23", "Edinburgh", "Dance Teacher", "19th - Ejected"], ["BB13", "Adam Kelly", "27", "Dudley", "Unemployed", "2nd - Runner-up"], ["BB2", "Helen Adams", "22", "South Wales", "Hairdresser", "2nd - Runner-up"], ["BB2", "Narinder Kaur", "28", "Leicester", "Medical rep", "9th - Evicted"], ["BB14", "Dexter Koh", "28", "London", "Celebrity publicist", "2nd - Runner-up"], ["BB10", "Siavash Sabbaghpour", "23", "London", "Event Organiser/Stylist/Model", "2nd - Runner-up"], ["TBB", "Caroline Cloke", "18", "Kent", "Student", "2nd - Runner-up"], ["BB:CH", "John Loughton", "20", "Edinburgh", "Politician", "1st - Winner"], ["BB10", "Kenneth Tong", "24", "Edinburgh", "Self Employed", "14th - Walked"], ["BB12", "Jay McKray", "27", "Newcastle", "Plumber/Fitness Instructor/DJ/barber", "2nd - Runner-up"], ["BB7", "Dawn Blake", "38", "Birmingham", "Exercise Scientist", "21st - Ejected"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:name two people who both are 28 years old | Craig Phillips, Tom McDermott | Answer: | 128 |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event"], ["1997", "World Indoor Championships", "Paris, France", "5th", "60 m hurdles"], ["1997", "USA Outdoor Championships", "Indianapolis, United States", "1st", "100 m hurdles"], ["2004", "Olympic Games", "Athens, Greece", "3rd", "100 m hurdles"], ["2000", "Olympic Games", "Sydney, Australia", "3rd", "100 m hurdles"], ["2003", "World Indoor Championships", "Birmingham, England", "3rd", "60 m hurdles"], ["2002", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["2003", "World Athletics Final", "Monaco", "6th", "100 m hurdles"], ["1998", "USA Indoor Championships", "", "1st", "60 m hurdles"], ["2002", "Grand Prix Final", "Paris, France", "7th", "100 m hurdles"], ["2000", "Grand Prix Final", "Doha, Qatar", "4th", "100 m hurdles"], ["1998", "Grand Prix Final", "Moscow, Russia", "2nd", "100 m hurdles"], ["1999", "World Indoor Championships", "Maebashi, Japan", "6th", "60 m hurdles"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many events did melissa morrison-howard place 3rd or better between 1997 and 2004? | 7 | Answer: | 128 |
Table InputTable: [["Place", "Code", "Area (km2)", "Population", "Most spoken language"], ["Dendron", "91103", "2.98", "1,885", "Northern Sotho"], ["Sekgosese", "91108", "349.99", "46,749", "Northern Sotho"], ["Sekhokho", "91109", "1.24", "1,852", "Northern Sotho"], ["Ga-Ramokgopha", "91104", "11.22", "15,806", "Northern Sotho"], ["Remainder of the municipality", "91106", "2,944.04", "10,463", "Northern Sotho"], ["Moletji", "91107", "11.66", "4,989", "Northern Sotho"], ["Bochum", "91102", "11.64", "4,142", "Northern Sotho"], ["Soekmekaar", "91110", "1.06", "217", "Northern Sotho"], ["Manthata", "91105", "12.24", "22,121", "Northern Sotho"], ["Backer", "91101", "0.34", "1,217", "Northern Sotho"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the difference between the population of sekgosese and the population of dendron? | 44864 | Answer: | 128 |
Table InputTable: [["Team", "No", "Driver", "Class", "Rounds"], ["Fortec Motorsport", "24", "Jack Harvey", "", "All"], ["Fortec Motorsport", "25", "George Katsinis", "", "All"], ["Fortec Motorsport", "26", "Christof von Grünigen", "", "All"], ["Mücke Motorsport", "8", "Timmy Hansen", "", "All"], ["Mücke Motorsport", "7", "Maciej Bernacik", "R", "All"], ["Eifelland Racing", "20", "Marc Coleselli", "R", "All"], ["Josef Kaufmann Racing", "4", "Robin Frijns", "", "All"], ["Josef Kaufmann Racing", "6", "Petri Suvanto", "R", "All"], ["Josef Kaufmann Racing", "5", "Hannes van Asseldonk", "R", "All"], ["Eifelland Racing", "19", "Côme Ledogar", "", "All"], ["Eifelland Racing", "18", "Facundo Regalia", "", "All"], ["EuroInternational", "11", "Daniil Kvyat", "R", "All"], ["EuroInternational", "12", "Carlos Sainz, Jr.", "R", "All"], ["DAMS", "17", "Dustin Sofyan", "", "8"], ["DAMS", "16", "Dustin Sofyan", "", "5"], ["DAMS", "17", "Fahmi Ilyas", "", "1–6"], ["DAMS", "16", "Luciano Bacheta", "", "7–8"], ["DAMS", "15", "Javier Tarancón", "", "All"], ["EuroInternational", "14", "Michael Lewis", "", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which team only had two drivers? | Mücke Motorsport | Answer: | 128 |
Table InputTable: [["Description Losses", "1939/40", "1940/41", "1941/42", "1942/43", "1943/44", "1944/45", "Total"], ["Deaths other countries", "", "", "", "", "", "", "2,000"], ["Deaths Outside of Prisons & Camps", "", "42,000", "71,000", "142,000", "218,000", "", "473,000"], ["Deaths In Prisons & Camps", "69,000", "210,000", "220,000", "266,000", "381,000", "", "1,146,000"], ["Direct War Losses", "360,000", "", "", "", "", "183,000", "543,000"], ["Murdered in Eastern Regions", "", "", "", "", "", "100,000", "100,000"], ["Total", "504,000", "352,000", "407,000", "541,000", "681,000", "270,000", "2,770,000"], ["Murdered", "75,000", "100,000", "116,000", "133,000", "82,000", "", "506,000"]] | 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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of ethnic pole deaths recorded during 1940/41 of the german occupation? | 352,000 | Answer: | 128 |
Table InputTable: [["Title", "Year", "Authors", "Publisher", "Pages"], ["The Far Reaching Effects of Broadband", "2002", "David Cleevely", "Institution of Engineering & Technology", "415"], ["Regulating the Telecoms Market: Competition and Innovation in the Broadband Economy", "2003", "Tim Hills, David Cleevely, Ross Pow", "Analysis Publications", "35"], ["Rural Telecoms Handbook: Equipment and Manufacturers", "1992", "Tim Hills, David Cleevely", "Analysys Publications", "-"], ["Global Turf Wars: Re-Inventing the Telecoms Operator for the Age of Global Competition", "1999", "Tim Hills, David Cleevely, Andrea Smith", "Analysis Publications", "218"], ["Regional Structure and Telecommunications Demand: A Case Study of Kenya (Ph.D. thesis)", "1982", "D. D. Cleevely", "University of Cambridge", "-"], ["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"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long is the publication the far reaching effects of broadband? | 415 pages | Answer: | 128 |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "China", "63", "46", "32", "141"], ["8", "Germany", "19", "28", "31", "78"], ["10", "Japan", "17", "16", "20", "53"], ["6", "Ukraine", "24", "12", "19", "55"], ["5", "Australia", "26", "38", "36", "100"], ["4", "United States", "27", "22", "39", "88"], ["3", "Canada", "28", "19", "25", "72"], ["9", "France", "18", "26", "30", "74"], ["7", "Spain", "20", "27", "24", "71"], ["2", "Great Britain", "35", "30", "29", "94"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which nation has the most bronze medals? | United States | Answer: | 128 |
Table InputTable: [["Team", "City", "Years active", "Seasons played", "Win–loss record", "Win%", "Playoffs appearances"], ["Indianapolis Jets", "Indianapolis, Indiana", "1948–1949", "1", "18–42", ".300", "0"], ["Detroit Falcons", "Detroit, Michigan", "1946–1947", "1", "20–40", ".333", "0"], ["Baltimore Bullets*", "Baltimore, Maryland", "1947–1954", "8", "158–292", ".351", "3"], ["Denver Nuggets", "Denver, Colorado", "1949–1950", "1", "11–51", ".177", "0"], ["Pittsburgh Ironmen", "Pittsburgh, Pennsylvania", "1946–1947", "1", "15–45", ".250", "0"], ["Toronto Huskies", "Toronto, Ontario", "1946–1947", "1", "22–38", ".367", "0"], ["Cleveland Rebels", "Cleveland, Ohio", "1946–1947", "1", "30–30", ".500", "1"], ["Waterloo Hawks", "Waterloo, Iowa", "1949–1950", "1", "19–43", ".306", "0"], ["Chicago Stags", "Chicago, Illinois", "1946–1950", "4", "145–92", ".612", "4"], ["St. Louis Bombers", "St. Louis, Missouri", "1946–1950", "4", "122–115", ".515", "3"], ["Anderson Packers", "Anderson, Indiana", "1949–1950", "1", "37–27", ".578", "1"], ["Indianapolis Olympians", "Indianapolis, Indiana", "1949–1953", "4", "132–137", ".491", "4"], ["BAA Indianapolis", "Indianapolis, Indiana", "Never Played", "0", "0–0", "N/A", "0"], ["BAA Buffalo", "Buffalo, New York", "Never Played", "0", "0–0", "N/A", "0"], ["Providence Steamrollers", "Providence, Rhode Island", "1946–1949", "3", "46–122", ".274", "0"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many defunct teams had at least one playoff appearance? | 8 | Answer: | 128 |
Table InputTable: [["Year", "Film", "Rotten Tomatoes", "Metacritic", "IMDb"], ["2000", "Dancer in the Dark", "68%", "61%", "8.0/10"], ["1998", "The Idiots", "70%", "47%", "6.9/10"], ["2003", "Dogville", "70%", "59%", "8.0/10"], ["2006", "The Boss of It All", "74%", "71%", "6.7/10"], ["2003", "The Five Obstructions", "88%", "79%", "7.5/10"], ["1984", "The Element of Crime", "77%", "N/A", "6.9/10"], ["1987", "Epidemic", "33%", "66%", "6.1/10"], ["2009", "Antichrist", "48%", "49%", "6.6/10"], ["2013", "Nymphomaniac: Volume I", "77%", "63%", "7.5/10"], ["2011", "Melancholia", "77%", "80%", "7.1/10"], ["1982", "Images of Liberation", "N/A", "N/A", "5.1/10"], ["1996", "Breaking the Waves", "86%", "76%", "7.9/10"], ["2005", "Manderlay", "51%", "46%", "7.4/10"], ["2013", "Nymphomaniac: Volume II", "79%", "76%", "7.2/10"], ["1991", "Europa", "85%", "66%", "7.7/10"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of films made, with a rating of 8 or higher? | 2 | Answer: | 128 |
Table InputTable: [["Date", "Rnd", "Race Name", "Circuit", "City/Location", "Pole position", "Winning driver", "Winning team", "Report"], ["7", "July 8", "Budweiser Grand Prix of Cleveland", "Cleveland Burke Lakefront Airport", "Cleveland, Ohio", "Rick Mears", "Danny Sullivan", "Team Penske", "Report"], ["15", "October 7", "Bosch Spark Plug Grand Prix", "Nazareth Speedway", "Nazareth, Pennsylvania", "Bobby Rahal", "Emerson Fittipaldi", "Team Penske", "Report"], ["9", "July 22", "Molson Indy Toronto", "Exhibition Place", "Toronto, Ontario", "Danny Sullivan", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["NC", "October 6", "Marlboro Challenge", "Nazareth Speedway", "Nazareth, Pennsylvania", "Michael Andretti", "Rick Mears", "Team Penske", "Report"], ["6", "June 24", "Budweiser/G.I.Joe's 200", "Portland International Raceway", "Portland, Oregon", "Danny Sullivan", "Michael Andretti", "Newman/Haas Racing", "Report"], ["12", "September 2", "Molson Indy Vancouver", "Streets of Vancouver", "Vancouver, British Columbia", "Michael Andretti", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["3", "May 27", "74th Indianapolis 500", "Indianapolis Motor Speedway", "Speedway, Indiana", "Emerson Fittipaldi", "Arie Luyendyk", "Doug Shierson Racing", "Report"], ["10", "August 5", "Marlboro 500", "Michigan International Speedway", "Brooklyn, Michigan", "Emerson Fittipaldi", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["1", "April 8", "Autoworks 200", "Phoenix International Raceway", "Phoenix, Arizona", "Rick Mears", "Rick Mears", "Team Penske", "Report"], ["11", "August 26", "Texaco/Havoline Grand Prix of Denver", "Streets of Denver", "Denver, Colorado", "Teo Fabi", "Al Unser, Jr.", "Galles-Kraco Racing", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which team earned first place in "budweiser grand prix of cleveland"? | Team Penske | Answer: | 128 |
Table InputTable: [["No. in\\nseries", "No. in\\nseason", "Title", "Directed by", "Written by", "Original air date", "Prod.\\ncode"], ["4", "7", "\"Danny was a Million Laughs\"", "Mark Rydell", "Arthur Dales", "October 27, 1965", "107"], ["11", "10", "\"Tatia\"", "David Friedkin", "Robert Lewin", "November 17, 1965", "110"], ["8", "6", "\"The Loser\"", "Mark Rydell", "Robert Culp", "October 20, 1965", "106"], ["7", "5", "\"Dragon's Teeth\"", "Leo Penn", "Gilbert Ralston", "October 13, 1965", "105"], ["28", "27", "\"It's All Done with Mirrors\"", "Robert Butler", "Stephen Kandell", "April 13, 1966", "127"], ["25", "24", "\"Crusade to Limbo\"", "Richard Sarafian", "Teleplay by: Morton Fine & David Freidkin & Jack Turley Story by: Jack Turley", "March 23, 1966", "124"], ["12", "11", "\"Weight of the World\"", "Paul Wendkos", "Robert Lewin", "December 1, 1965", "111"], ["14", "12", "\"Three Hours on a Sunday\"", "Paul Wendkos", "Morton Fine & David Friedkin", "December 8, 1965", "112"], ["3", "1", "\"So Long, Patrick Henry\"", "Leo Penn", "Robert Culp", "September 15, 1965", "101"], ["21", "21", "\"Return to Glory\"", "Robert Sarafian", "David Friedkin & Morton Fine", "February 23, 1966", "121"], ["10", "8", "\"The Time of the Knife\"", "Paul Wendkos", "Gilbert Ralston", "November 3, 1965", "108"], ["23", "23", "\"A Day Called 4 Jaguar\"", "Richard Sarafian", "Michael Zagar", "March 9, 1966", "123"], ["16", "15", "\"The Tiger\"", "Paul Wendkos", "Robert Culp", "January 5, 1966", "115"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:did robert lewin write more episodes than arthur dales? | Yes | Answer: | 128 |
Table InputTable: [["Name", "City", "State/Country", "Designed", "Completed", "Other Information"], ["Cranbrook School for Boys furnishings", "Bloomfield Hills", "Michigan", "1925", "1931", "With Eliel Saarinen"], ["Brandeis University plan and buildings", "Waltham", "Massachusetts", "1949", "1952", "With Matthew Nowicki. Ridgewood Quadrangle Dormitories (1950), Hamilton Quadrangle Dormitory & Student Center (1952), Sherman Student Center (1952)"], ["Case Study House #9", "Los Angeles", "California", "1945", "1949", "With Charles Eames. Saarinen also provided an original plan for House #8, but Eames completely redesigned it. Listed on the National Register of Historic Places in 2013"], ["Crow Island School", "Winnetka", "Illinois", "1938", "1942", "With Eliel Saarinen and Perkins & Will. Designated a National Historic Landmark in 1990"], ["Womb Chair & Ottoman", "n/a", "n/a", "1946", "1948", "Chair design for Knoll Associates"], ["Grasshopper Chair", "n/a", "n/a", "1943", "1946", "Chair design for Knoll Associates"], ["Models 71 and 73", "n/a", "n/a", "1945", "1950", "Chair design for Knoll Associates"], ["Kingswood School for Girls furnishings", "Bloomfield Hills", "Michigan", "1929", "1931", ""], ["Concordia Senior College", "Fort Wayne", "Indiana", "1953", "1958", ""], ["J. F. Spencer House", "Huntington Woods", "Michigan", "1937", "1938", "First building designed independently"], ["United States Chancellery Building", "London", "England", "1955", "1960", ""], ["Christ Church Lutheran", "Minneapolis", "Minnesota", "1947", "1949", "With Eliel Saarinen; solo addition in 1962. Designated a National Historic Landmark in 2009."], ["Pedestal Series", "n/a", "n/a", "1954", "1957", "Furniture design for Knoll Associates. Includes the tulip chair"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many years, from design to completion, did it take to build the cranbrook school for boys? | 6 | Answer: | 128 |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2007", "All-Africa Games", "Algiers, Algeria", "3rd", "Discus throw", "57.79 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "5th", "Shot put", "17.76 m"], ["2003", "All-Africa Games", "Abuja, Nigeria", "2nd", "Discus throw", "62.86 m"], ["2006", "Commonwealth Games", "Melbourne, Australia", "7th", "Shot put", "18.44 m"], ["2004", "African Championships", "Brazzaville, Republic of the Congo", "2nd", "Discus throw", "63.50 m"], ["2008", "African Championships", "Addis Ababa, Ethiopia", "2nd", "Discus throw", "56.98 m"], ["2006", "Commonwealth Games", "Melbourne, Australia", "4th", "Discus throw", "60.99 m"], ["2004", "Olympic Games", "Athens, Greece", "8th", "Discus throw", "62.58 m"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "Discus throw", "59.51 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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which competition in 2003 appears in the same year as 2007? | All-Africa Games | Answer: | 128 |
Table InputTable: [["Leg", "Stage", "Time", "Name", "Length", "Winner", "Time", "Avg. spd.", "Rally leader"], ["1\\n(16 Feb)", "SS4", "12:30", "Grue", "14.36 km", "S. Loeb", "7:31.8", "114.42 km/h", "M. Hirvonen"], ["1\\n(16 Feb)", "SS6", "14:36", "Kongsvinger", "14.60 km", "S. Loeb", "9:44.5", "89.92 km/h", "M. Hirvonen"], ["1\\n(16 Feb)", "SS2", "08:34", "Haslemoen", "11.92 km", "S. Loeb", "8:08.4", "87.86 km/h", "M. Hirvonen"], ["1\\n(16 Feb)", "SS8", "16:33", "Kirkanaer", "6.75 km", "S. Loeb", "5:48.9", "69.65 km/h", "M. Hirvonen"], ["1\\n(16 Feb)", "SS5", "13:52", "Opaker", "14.64 km", "J. Latvala", "7:59.8", "109.85 km/h", "M. Hirvonen"], ["3\\n(18 Feb)", "SS17", "10:05", "Hamar 2", "1.14 km", "X. Pons\\n S. Loeb\\n P. Solberg", "1:11.8", "57.16 km/h", "M. Hirvonen"], ["3\\n(18 Feb)", "SS15", "08:08", "Mountain 2", "24.36 km", "S. Loeb", "13:18.2", "109.87 km/h", "M. Hirvonen"], ["2\\n(17 Feb)", "SS10", "09:23", "Terningmoen", "12.71 km", "D. Sordo", "7:59.1", "95.5 km/h", "M. Hirvonen"], ["1\\n(16 Feb)", "SS7", "15:30", "Finnskogen", "21.29 km", "S. Loeb", "12:42.3", "100.54 km/h", "M. Hirvonen"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:s loeb won how many consectutuive races | 3 | Answer: | 128 |
Table InputTable: [["Name", "City", "State/Country", "Designed", "Completed", "Other Information"], ["Christ Church Lutheran", "Minneapolis", "Minnesota", "1947", "1949", "With Eliel Saarinen; solo addition in 1962. Designated a National Historic Landmark in 2009."], ["United States Chancellery Building", "Oslo", "Norway", "1955", "1959", ""], ["Des Moines Art Center", "Des Moines", "Iowa", "1944", "1948", "With Eliel Saarinen and J. Robert F. Swanson. Listed on the National Register of Historic Places in 2004"], ["Concordia Senior College", "Fort Wayne", "Indiana", "1953", "1958", ""], ["Kleinhans Music Hall", "Buffalo", "New York", "1938", "1940", "With Eliel Saarinen. Designated a National Historic Landmark in 1989"], ["United States Chancellery Building", "London", "England", "1955", "1960", ""], ["Milwaukee County War Memorial", "Milwaukee", "Wisconsin", "1952", "1957", ""], ["Hill Hall", "Philadelphia", "Pennsylvania", "1957", "1960", ""], ["North Christian Church", "Columbus", "Indiana", "1959", "1964", "Designated a National Historic Landmark in 2000"], ["Fenton Community Center", "Fenton", "Michigan", "1937", "1938", "With Eliel Saarinen"], ["Crow Island School", "Winnetka", "Illinois", "1938", "1942", "With Eliel Saarinen and Perkins & Will. Designated a National Historic Landmark in 1990"], ["Saarinen House furnishings", "Bloomfield Hills", "Michigan", "1928", "1930", ""], ["Eero Saarinen & Associates Building", "Bloomfield Hills", "Michigan", "1953", "1953", ""], ["Drake University plan and buildings", "Des Moines", "Iowa", "1945", "1957", "Harvey Ingham Hall of Science, Fitch Hall of Pharmacy, Women's Dormitory & Dining Hall (all in 1945 with Eliel Saarinen and J. Robert F. Swanson), Bible School & Prayer Chapel in 1952, Women's Dormitory #4 in 1957, Jewett Union addition in 1957"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what religious symbol is located on top of the christ church lutheran in minneapolis? | Cross | Answer: | 128 |
Table InputTable: [["Date", "Rnd", "Race Name", "Circuit", "City/Location", "Pole position", "Winning driver", "Winning team", "Report"], ["NC", "October 6", "Marlboro Challenge", "Nazareth Speedway", "Nazareth, Pennsylvania", "Michael Andretti", "Rick Mears", "Team Penske", "Report"], ["3", "May 27", "74th Indianapolis 500", "Indianapolis Motor Speedway", "Speedway, Indiana", "Emerson Fittipaldi", "Arie Luyendyk", "Doug Shierson Racing", "Report"], ["12", "September 2", "Molson Indy Vancouver", "Streets of Vancouver", "Vancouver, British Columbia", "Michael Andretti", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["9", "July 22", "Molson Indy Toronto", "Exhibition Place", "Toronto, Ontario", "Danny Sullivan", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["1", "April 8", "Autoworks 200", "Phoenix International Raceway", "Phoenix, Arizona", "Rick Mears", "Rick Mears", "Team Penske", "Report"], ["15", "October 7", "Bosch Spark Plug Grand Prix", "Nazareth Speedway", "Nazareth, Pennsylvania", "Bobby Rahal", "Emerson Fittipaldi", "Team Penske", "Report"], ["2", "April 22", "Toyota Long Beach Grand Prix", "Streets of Long Beach", "Long Beach, California", "Al Unser, Jr.", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["16", "October 21", "Champion Spark Plug 300K", "Laguna Seca Raceway", "Monterey, California", "Danny Sullivan", "Danny Sullivan", "Team Penske", "Report"], ["8", "July 15", "Marlboro Grand Prix at the Meadowlands", "Meadowlands Sports Complex", "East Rutherford, New Jersey", "Michael Andretti", "Michael Andretti", "Newman/Haas Racing", "Report"], ["7", "July 8", "Budweiser Grand Prix of Cleveland", "Cleveland Burke Lakefront Airport", "Cleveland, Ohio", "Rick Mears", "Danny Sullivan", "Team Penske", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what team won the least? | Doug Shierson Racing | Answer: | 128 |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "China (CHN)", "127", "63", "33", "223"], ["3", "South Korea (KOR)", "32", "48", "65", "145"], ["8", "Mongolia (MGL)", "1", "1", "6", "8"], ["7", "Hong Kong (HKG)", "2", "2", "9", "13"], ["4", "Chinese Taipei (TPE)", "12", "34", "26", "72"], ["2", "Japan (JPN)", "46", "56", "77", "179"], ["6", "North Korea (PRK)", "6", "10", "20", "36"], ["5", "Macau (MAC)", "11", "16", "17", "44"], ["Total", "Total", "237", "230", "254", "721"], ["9", "Guam (GUM)", "0", "0", "1", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which nation won more bronze medals than china? | Japan (JPN), South Korea (KOR) | Answer: | 128 |
Table InputTable: [["Year", "Single", "Peak chart\\npositions\\nUS Country", "Peak chart\\npositions\\nCAN Country", "Album"], ["1983", "\"Hold Me\"", "67", "—", "singles only"], ["1983", "\"You've Still Got Me\"", "71", "—", "singles only"], ["1979", "\"Darlin'\"", "18", "36", "singles only"], ["1976", "\"Mahogany Bridge\"", "84", "—", "singles only"], ["1977", "\"I'm Gonna Love You Right Out of This World\"", "21", "38", "singles only"], ["1981", "\"Houston Blue\"", "88", "—", "singles only"], ["1972", "\"All Heaven Breaks Loose\"", "35", "—", "single only"], ["1982", "\"Crown Prince of the Barroom\"", "92", "—", "singles only"], ["1979", "\"You Are My Rainbow\"", "36", "—", "singles only"], ["1976", "\"Whispers and Grins\"", "66", "—", "singles only"], ["1979", "\"You're Amazing\"", "39", "—", "singles only"], ["1969", "\"Dearly Beloved\"", "59", "—", "single only"], ["1984", "\"I'm a Country Song\"", "72", "—", "singles only"], ["1971", "\"Ruby, You're Warm\"", "21", "16", "single only"], ["1983", "\"The Devil Is a Woman\"", "87", "—", "singles only"], ["1977", "\"I Love What My Woman Does to Me\"", "49", "33", "singles only"], ["1974", "\"Loving You Has Changed My Life\"", "9", "21", "Hey There Girl"], ["1978", "\"I'll Be There (When You Get Lonely)\"", "22", "—", "Lovingly"], ["1978", "\"When a Woman Cries\"", "31", "—", "singles only"], ["1977", "\"The Lady and the Baby\"", "76", "—", "singles only"], ["1968", "\"I'm in Love with My Wife\"", "38", "—", "A World Called You"], ["1970", "\"So Much in Love with You\"", "46", "—", "A World Called 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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of years he released any singles? | 17 | Answer: | 128 |
Table InputTable: [["Year", "Title", "Role", "Notes"], ["1999", "Sabrina, Down Under", "Gwen", ""], ["1998", "Sabrina Goes to Rome", "Gwen", ""], ["2010", "Big Time Rush", "Miss Collins", "Recurring Role"], ["2014", "Arrow", "Deranged Squad Female (voice)", "Episode: \"Suicide Squad\""], ["1992", "The Judge", "Millie Waters", ""], ["1986", "Desiree's Wish", "Waitress", ""], ["2007", "The Bad Girls Club", "Season 2 Narrator", ""], ["1999", "Black Mask", "Additional Voices", ""], ["1989", "Mosquito Lake", "Tara Harrison", ""], ["1988", "T. and T.", "Sydney", ""], ["1994", "Reform School Girl", "Lucille", ""], ["1994", "Thicker Than Blood: The Larry McLinden Story", "Terra (age 16)", ""], ["1995", "Party of Five", "Lorna", ""], ["1995", "Skin Deep", "Tina", ""], ["1992", "Forever Knight", "", ""], ["2006", "Take Home Chef", "Herself", ""], ["1986", "Street Legal", "Angela", ""], ["1991", "Married to It", "Student in Pageant", ""], ["2013", "Super Fun Night", "Young Pamela", ""], ["1993", "Kung Fu: The Legend Continues", "Elizabeth", ""], ["1999", "Touched by an Angel", "", ""], ["2004", "Comic Book: The Movie", "", ""], ["1996", "3rd Rock from the Sun", "Yoga Lady", "Episode: \"My Mother the Alien\""], ["2008", "According to Jim", "Kayla", ""], ["1992", "A Town Torn Apart", "", ""], ["1993", "Family Pictures", "", ""], ["1999", "1999 Kids' Choice Awards", "Herself", "Presenter, Winner (with the cast of Rugrats) for Favorite Cartoon, Winner (with the cast of The Rugrats Movie) for Favorite Movie"], ["1999", "1998 Kids' Choice Awards", "Herself", "Winner (with the cast of Rugrats) for Favorite Cartoon"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times does the role of gwen appear? | 2 | Answer: | 128 |
Table InputTable: [["Year", "Network", "NASCAR\\nCountdown", "Lap-by-lap", "Color commentator(s)", "Pit reporters", "Ratings", "Viewers"], ["2011", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "4.0 (4.6 cable)", "6.337 million"], ["2009", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Jerry Punch", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nShannon Spake\\nVince Welch", "4.1 (4.8 cable)", "6.487 million"], ["2007", "ESPN", "Brent Musburger\\nSuzy Kolber\\nBrad Daugherty", "Jerry Punch", "Rusty Wallace\\nAndy Petree", "Dave Burns\\nJamie Little\\nAllen Bestwick\\nMike Massaro", "4.2 (4.9 cable)", "6.574 million"], ["2010", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Marty Reid", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.6 (4.2 cable)", "5.709 million"], ["2012", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.3", "5.1 million"], ["2008", "ESPN", "Allen Bestwick\\nRusty Wallace\\nBrad Daugherty", "Jerry Punch", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nShannon Spake\\nMike Massaro", "4.3 (5.1 cable)", "6.668 million"], ["2013", "ESPN", "Nicole Briscoe\\nRusty Wallace\\nBrad Daugherty\\nRay Evernham", "Allen Bestwick", "Dale Jarrett\\nAndy Petree", "Dave Burns\\nJamie Little\\nJerry Punch\\nVince Welch", "3.6", "5.5 million"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:list the number of times the rating was above a 4.0. | 3 | Answer: | 128 |
Table InputTable: [["Number", "Name", "Term Started", "Term Ended", "Alma Mater", "Field(s)", "Educational Background"], ["1", "Dr Abdus Salam", "1961", "1967", "Imperial College", "Theoretical Physics", "Doctor of Philosophy (Ph.D)"], ["8", "Major General Raza Hussain", "2001", "2010", "Pakistan Army Corps of Electrical and Mechanical Engineers", "Electrical Engineering", "B.S."], ["7", "Dr Abdul Majid", "1997", "2001", "University of Wales", "Astrophysics", "Ph.D"], ["3", "Air Commodore K. M. Ahmad", "1979", "1980", "Pakistan Air Force Academy", "Flight Instructor", "Certificated Flight Instructor (CFI)"], ["5", "Dr M. Shafi Ahmad", "1989", "1990", "University of London", "Astronomy", "Ph.D"], ["9", "Major General Ahmed Bilal", "2010", "Present", "Pakistan Army Corps of Signals Engineering", "Computer Engineering", "Master of Science (M.S)"], ["2", "Air Commodore Dr Władysław Turowicz", "1967", "1979", "Warsaw University of Technology", "Aeronautical Engineering", "Ph.D"], ["4", "Dr Salim Mehmud", "1980", "1989", "Oak Ridge Institute for Science and Education and Oak Ridge National Laboratory", "Nuclear Engineering, Electrical engineering, Physics, Mathematics, Electronics engineering", "Ph.D"], ["6", "Engr.Sikandar Zaman", "1990", "1997", "University of Leeds", "Mechanical Engineering", "Bachelor of Science (B.S.)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many administrators of suparco have there been in total since 1961? | 9 | Answer: | 128 |
Table InputTable: [["Polling Firm", "Source", "Date Published", "N.Anastasiades", "G.Lillikas", "S.Malas", "Others"], ["Prime Consulting Ltd", "[19]", "4 February 2013", "39.8%", "19.3%", "20%", "3%"], ["Prime Consulting Ltd", "[4]", "7 October 2012", "34.7%", "17.4%", "18.5%", ""], ["Prime Consulting Ltd", "[20]", "9 February 2013", "40.6%", "19.6%", "20.4%", "2.9%"], ["Prime Consulting Ltd", "[9]", "18 November 2012", "35.9%", "18.7%", "19.6%", "0.6%"], ["Prime Consulting Ltd", "[17]", "27 January 2013", "39.2%", "18.8%", "19.8%", "4%"], ["Prime Consulting Ltd", "[12]", "3 December 2012", "35%", "19.1%", "18.6%", "1.4%"], ["RAI Consultants", "[1][dead link]", "16 September 2012", "37.2%", "14.2%", "21.9%", "1.5%"], ["RAI Consultants Ltd", "[21]", "9 February 2013", "42.1%", "19.4%", "21.1%", "4.4%"], ["RAI Consultants", "[7]", "4 November 2012", "38.8%", "19.8%", "21.1%", "2.3%"], ["RAI Consultants Ltd", "[15][dead link]", "13 January 2013", "40.3%", "17.9%", "20.5%", "6.1%"], ["Average (only valid votes)", "–", "–", "48.4%", "22.52%", "25.29%", "3.79%"], ["Evresis", "[6]", "2 November 2012", "36.9%", "17.7%", "20.6%", "1.4%"], ["Evresis", "[14]", "22 December 2012", "37.4%", "19.8%", "21.8%", "0.5%"], ["Evresis", "[2]", "18 September 2012", "35.2%", "17.5%", "19.7%", "1.7%"]] | 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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:name a poll that was published the same day as prime consulting's last poll. | RAI Consultants Ltd | Answer: | 128 |
Table InputTable: [["#", "Date", "Venue", "Opponent", "Score", "Result", "Competition"], ["1.", "27 March 1999", "Mestalla, Valencia, Spain", "Austria", "3–0", "9–0", "Euro 2000 qualifying"], ["4.", "8 September 1999", "Vivero, Badajoz, Spain", "Cyprus", "1–0", "8–0", "Euro 2000 qualifying"], ["2.", "27 March 1999", "Mestalla, Valencia, Spain", "Austria", "5–0", "9–0", "Euro 2000 qualifying"], ["6.", "8 September 1999", "Vivero, Badajoz, Spain", "Cyprus", "4–0", "8–0", "Euro 2000 qualifying"], ["5.", "8 September 1999", "Vivero, Badajoz, Spain", "Cyprus", "2–0", "8–0", "Euro 2000 qualifying"], ["3.", "31 March 1999", "Olimpico, Serravalle, San Marino", "San Marino", "0–3", "0–6", "Euro 2000 qualifying"], ["8.", "26 January 2000", "Cartagonova, Cartagena, Spain", "Poland", "3–0", "3–0", "Friendly"], ["7.", "26 January 2000", "Cartagonova, Cartagena, Spain", "Poland", "2–0", "3–0", "Friendly"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:where did he score his first international goal? | Mestalla, Valencia, Spain | Answer: | 128 |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["2", "Greece", "6", "7", "6", "19"], ["1", "France", "11", "5", "3", "19"], ["8", "Tunisia", "0", "1", "0", "1"], ["5", "Morocco", "1", "1", "0", "2"], ["3", "Yugoslavia", "3", "2", "1", "6"], ["4", "Spain", "1", "5", "5", "11"], ["7", "Egypt", "0", "1", "7", "8"], ["5", "Turkey", "1", "1", "0", "2"], ["Totaal", "Totaal", "23", "23", "22", "68"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:france and greece both have how many overall total medals? | 19 | Answer: | 128 |
Table InputTable: [["Match", "Date", "Venue", "Opponents", "Score"], ["GL-A-1", "2006..", "[[]]", "[[]]", "-"], ["Semifinals-2", "2006..", "[[]]", "[[]]", "-"], ["GL-A-2", "2006..", "[[]]", "[[]]", "-"], ["GL-A-3", "2006..", "[[]]", "[[]]", "-"], ["GL-A-6", "2006..", "[[]]", "[[]]", "-"], ["GL-A-4", "2006..", "[[]]", "[[]]", "-"], ["Semifinals-1", "2006..", "[[]]", "[[]]", "-"], ["GL-A-5", "2006..", "[[]]", "[[]]", "-"], ["Quarterfinals-2", "2006..", "[[]]", "[[]]", "-"], ["Quarterfinals-1", "2006..", "[[]]", "[[]]", "-"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many matches were there? | 10 | Answer: | 128 |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["10", "Thailand (THA)", "1", "1", "2", "4"], ["11", "Kyrgyzstan (KGZ)", "1", "1", "0", "2"], ["8", "Sri Lanka (SRI)", "2", "0", "2", "4"], ["9", "Qatar (QAT)", "1", "4", "3", "8"], ["12", "Kuwait (KUW)", "1", "0", "0", "1"], ["6", "Japan (JPN)", "2", "13", "8", "23"], ["5", "South Korea (KOR)", "3", "2", "1", "6"], ["3", "Saudi Arabia (KSA)", "7", "1", "0", "8"], ["14", "Uzbekistan (UZB)", "0", "1", "3", "4"], ["4", "Kazakhstan (KAZ)", "3", "4", "5", "12"], ["2", "India (IND)", "7", "6", "4", "17"], ["15", "Iran (IRI)", "0", "1", "0", "1"], ["12", "North Korea (PRK)", "1", "0", "0", "1"], ["1", "China (CHN)", "14", "14", "13", "41"], ["Total", "Total", "45", "49", "42", "136"], ["7", "Bahrain (BRN)", "2", "1", "1", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many countries have less than 10 total medals? | 11 | Answer: | 128 |
Table InputTable: [["Year", "Network", "Race caller", "Color commentator", "Reporters", "Trophy Presentation"], ["1953", "CBS", "Bryan Field", "Mel Allen", "Phil Sutterfield", "Phil Sutterfield"], ["1959", "CBS", "Fred Capossela", "Bryan Field and Chris Schenkel", "", "Chris Schenkel"], ["1954", "CBS", "Bryan Field", "Mel Allen", "", "Bill Corum"], ["1956", "CBS", "Fred Capossela", "Bryan Field", "", ""], ["1952", "CBS", "Bryan Field", "Sam Renick", "", ""], ["1958", "CBS", "Fred Capossela", "Bryan Field", "", ""], ["1957", "CBS", "Fred Capossela", "Bryan Field", "", ""], ["1955", "CBS", "Fred Capossela", "Phil Sutterfield and Win Elliot", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the color commentator the most? | Bryan Field | Answer: | 128 |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["5", "North Korea", "1", "0", "1", "2"], ["6", "South Korea", "0", "0", "2", "2"], ["2", "Japan", "7", "10", "7", "24"], ["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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who had more gold medals, japan or north korea? | Japan | Answer: | 128 |
Table InputTable: [["Pick #", "NFL Team", "Player", "Position", "College"], ["3", "Baltimore Colts", "Alan Ameche", "Fullback", "Wisconsin"], ["2", "Chicago Cardinals", "Max Boydston", "End", "Oklahoma"], ["9", "Philadelphia Eagles", "Dick Bielski", "Fullback", "Maryland"], ["5", "Green Bay Packers", "Tom Bettis", "Guard", "Purdue"], ["6", "Pittsburgh Steelers", "Frank Varrichione", "Tackle", "Notre Dame"], ["8", "New York Giants", "Joe Heap", "Halfback", "Notre Dame"], ["11", "Chicago Bears", "Ron Drzewiecki", "Halfback", "Marquette"], ["7", "Los Angeles Rams", "Larry Morris", "Center", "Georgia Tech"], ["4", "Washington Redskins", "Ralph Guglielmi", "Quarterback", "Notre Dame"], ["12", "Detroit Lions", "Dave Middleton", "Halfback", "Auburn"], ["1", "Baltimore Colts (Lottery bonus pick)", "George Shaw", "Quarterback", "Oregon"], ["10", "San Francisco 49ers", "Dickey Moegle", "Halfback", "Rice"], ["13", "Cleveland Browns", "Kurt Burris", "Center", "Oklahoma"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:alan ameche played the same position as? | Dick Bielski | Answer: | 128 |
Table InputTable: [["#", "Title", "Performer(s)", "Film", "Length"], ["8", "\"It's Not Just Make Believe\"", "Kari Kimmel", "Ella Enchanted", "3:06"], ["2", "\"That's How You Know\"", "Demi Lovato", "Enchanted", "3:12"], ["5", "\"Reflection\"", "Christina Aguilera", "Mulan", "3:33"], ["12", "\"Happy Working Song\"", "Amy Adams", "Enchanted", "2:09"], ["6", "\"So This Is Love\"", "The Cheetah Girls", "Cinderella", "3:40"], ["11", "\"True to Your Heart\"", "Keke Palmer", "Mulan", "3:22"], ["3", "\"Some Day My Prince Will Come\"", "Ashley Tisdale", "Snow White and the Seven Dwarfs", "3:30"], ["4", "\"Colors of the Wind\"", "Vanessa Hudgens", "Pocahontas", "3:58"], ["14", "\"A Dream Is a Wish Your Heart Makes\"", "Disney Channel Stars", "Cinderella", "3:46"], ["13", "\"Part of Your World\"", "Original Broadway Cast", "The Little Mermaid", "3:23"], ["10", "\"Ever Ever After\"", "Jordan Pruitt", "Enchanted", "3:12"], ["7", "\"Kiss the Girl\"", "Colbie Caillat", "The Little Mermaid", "3:16"], ["1", "\"Once Upon a Dream\"", "Emily Osment", "Sleeping Beauty", "3:32"], ["9", "\"Under the Sea\"", "Raven-Symoné", "The Little Mermaid", "3:15"]] | 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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which performer is listed below kari kimmel? | Raven-Symoné | Answer: | 128 |
Table InputTable: [["Place", "Player", "Country", "Score", "To par"], ["T7", "Tiger Woods", "United States", "70-71-72=213", "+3"], ["T2", "Jason Gore", "United States", "71-67-72=210", "E"], ["6", "David Toms", "United States", "70-72-70=212", "+2"], ["T2", "Olin Browne", "United States", "67-71-72=210", "E"], ["T7", "Lee Westwood", "England", "68-72-73=213", "+3"], ["1", "Retief Goosen", "South Africa", "68-70-69=207", "–3"], ["T7", "K. J. Choi", "South Korea", "69-70-74=213", "+3"], ["T7", "Peter Hedblom", "Sweden", "77-66-70=213", "+3"], ["T4", "Mark Hensby", "Australia", "71-68-72=211", "+1"], ["T4", "Michael Campbell", "New Zealand", "71-69-71=211", "+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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in total, what did the players from united states score? | 845 | Answer: | 128 |
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["23 October 2005", "Newcastle United", "St James' Park", "2–3", "52,302", "Lawrence, Elliott"], ["1 October 2005", "West Ham United", "Stadium of Light", "1–1", "31,212", "Miller"], ["23 August 2005", "Manchester City", "Stadium of Light", "1–2", "33,357", "Le Tallec"], ["15 October 2005", "Manchester United", "Stadium of Light", "1–3", "39,085", "Elliott"], ["20 August 2005", "Liverpool", "Anfield", "0–1", "44,913", ""], ["5 November 2005", "Arsenal", "Highbury", "1–3", "38,210", "Stubbs"], ["25 September 2005", "Middlesbrough", "Riverside Stadium", "2–0", "29,583", "Miller, Arca"], ["10 September 2005", "Chelsea", "Stamford Bridge", "0–2", "41,969", ""], ["30 November 2005", "Liverpool", "Stadium of Light", "0–2", "32,697", ""], ["26 November 2005", "Birmingham City", "Stadium of Light", "0–1", "32,442", ""], ["10 December 2005", "Charlton Athletic", "The Valley", "0–2", "26,065", ""], ["29 October 2005", "Portsmouth", "Stadium of Light", "1–4", "34,926", "Whitehead (pen)"], ["26 December 2005", "Bolton Wanderers", "Stadium of Light", "0–0", "32,232", ""], ["17 September 2005", "West Bromwich Albion", "Stadium of Light", "1–1", "31,657", "Breen"], ["31 December 2005", "Everton", "Stadium of Light", "0–1", "30,567", ""], ["3 December 2005", "Tottenham Hotspur", "White Hart Lane", "2–3", "36,244", "Whitehead, Le Tallec"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who scored on 23 october 2005? | Lawrence, Elliott | Answer: | 128 |
Table InputTable: [["Series", "Years", "Volumes", "Writer", "Editor", "Remarks"], ["Ivan Zourine", "1979", "2", "Jacques Stoquart", "Magic-Strip", ""], ["Shelena", "2005", "1", "Jéromine Pasteur", "Casterman", ""], ["Daddy", "1991-92", "2", "Loup Durand", "Cl. Lefrancq", ""], ["Ikar", "1995–1997", "2", "Pierre Makyo", "Glénat", ""], ["Alain Brisant", "1985", "1", "Maurice Tillieux", "Dupuis", ""], ["Les zingari", "2004–2005", "2", "Yvan Delporte", "Hibou", ""], ["Bruno Brazil", "1973–1977", "5", "Greg", "Magic-Strip", "William Vance drew the comics, Follet provided the page lay-out"], ["Valhardi", "1984–1986", "2", "Jacques Stoquart and André-Paul Duchâteau", "Dupuis", "Continuation of the series after Jijé and Eddy Paape"], ["Terreur", "2002–2004", "2", "André-Paul Duchâteau", "Le Lombard", "Fictional biography of Madame Tussaud"], ["Harricana", "1992", "1", "Jean-Claude de la Royère", "Claude Lefrancq", "Drawn by Denis Mérezette, Follet did the page lay-out"], ["L'affaire Dominici", "2010", "1", "Pascal Bresson", "Glénat", ""], ["L'étoile du soldat", "2007", "1", "Christophe De Ponfilly", "Casterman", "Announced (28 August 2007)"], ["Marshall Blueberry", "1994", "1", "Jean Giraud", "Alpen", "Drawn by William Vance, Follet did the page lay-out"], ["Jacques Le Gall", "1984–1985", "2", "Jean-Michel Charlier", "Dupuis", "A collaboration with MiTacq"], ["Steve Severin", "1981–2003", "9", "Jacques Stoquart and Yvan Delporte", "Glénat", "3 in French - 6 additional in Dutch"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did ivan zourine last? | 1 year | Answer: | 128 |
Table InputTable: [["Team", "Chassis", "Engine", "Tires", "No", "Drivers"], ["Team KOOL Green", "Reynard 98i", "Honda", "Firestone", "26", "Paul Tracy"], ["Team KOOL Green", "Reynard 98i", "Honda", "Firestone", "27", "Dario Franchitti"], ["Team Rahal", "Reynard 98i", "Ford XB", "Firestone", "8", "Bryan Herta"], ["Team Rahal", "Reynard 98i", "Ford XB", "Firestone", "7", "Bobby Rahal"], ["PacWest Racing Group", "Reynard 98i", "Mercedes", "Firestone", "17", "Maurício Gugelmin"], ["Marlboro Team Penske", "Penske PC27-98", "Mercedes", "Goodyear", "3", "André Ribeiro"], ["Davis Racing", "Lola T98/00", "Ford XB", "Goodyear", "77", "Arnd Meier"], ["Newman-Haas Racing", "Swift 009.c", "Ford XB", "Goodyear", "11", "Christian Fittipaldi\\n Roberto Moreno"], ["PacWest Racing Group", "Reynard 98i", "Mercedes", "Firestone", "18", "Mark Blundell"], ["Project Indy", "Reynard 97i", "Ford XB", "Goodyear", "15", "Roberto Moreno\\n Domenico Schiattarella"], ["Arciero-Wells Racing", "Reynard 98i", "Toyota", "Firestone", "25", "Max Papis"], ["Bettenhausen Racing", "Reynard 98i", "Mercedes", "Goodyear", "16", "Hélio Castroneves"], ["All American Racing", "Reynard 98i\\nEagle 987", "Toyota", "Goodyear", "98", "P. J. Jones\\n Vincenzo Sospiri"], ["Hogan Racing", "Reynard 98i", "Mercedes", "Firestone", "9", "JJ Lehto"], ["Tasman Motorsports Group", "Reynard 98i", "Honda", "Firestone", "21", "Tony Kanaan"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the only team that has lola t98/00? | Davis Racing | Answer: | 128 |
Table InputTable: [["Year", "Total\\npassengers", "Passenger\\nChange", "Domestic", "International\\n(total)", "International\\n(non-CIS)", "CIS", "Aircraft\\nLandings", "Cargo\\n(tonnes)"], ["2003", "1 335 757", "+12,9%", "879 665", "456 092", "297 421", "158 671", "10 092", "18 054"], ["2012", "3 783 069", "+12.7%", "1 934 016", "1 849 053", "1 448 765", "439 668", "21 728", "25 866"], ["2004", "1 553 628", "+16,3%", "972 287", "581 341", "429 049", "152 292", "11 816", "20 457"], ["2008", "2 529 395", "+7,8%", "1 523 102", "1 006 293", "815 124", "191 169", "16 407", "17 142"], ["2013", "4 293 002", "+13.5%", "2 180 227", "2 112 775", "", "", "25 728", "27 800"], ["2011", "3 355 883", "+22,1%", "1 856 948", "1 498 935", "1 184 771", "314 164", "20 142", "24 890"], ["2001", "1 028 295", "+10,5%", "733 022", "295 273", "186 861", "108 412", "9 062", "22 178"], ["2007", "2 345 097", "+32,9%", "1 486 888", "858 209", "683 092", "175 117", "16 767", "16 965"], ["2002", "1 182 815", "+15,0%", "793 295", "389 520", "239 461", "150 059", "10 162", "20 153"], ["2010", "2 748 919", "+26,7%", "1 529 245", "1 219 674", "1 017 509", "202 165", "15 989", "22 946"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:the last year to have less than 3 million total passengers. | 2010 | Answer: | 128 |
Table InputTable: [["Departure", "Going to", "Calling at", "Arrival", "Operator"], ["18.51", "Grantham", "Rauceby, Ancaster, Honington, Barkston", "19.28", "GNR"], ["08.17", "Grantham", "Rauceby, Ancaster, Barkston", "08.45", "GNR"], ["11.34", "Grantham", "Rauceby, Ancaster, Barkston, Honington", "12.05", "GNR"], ["09.50", "Grantham", "Rauceby, Ancaster, Honington", "10.20", "GNR"], ["13.48", "Grantham", "Rauceby, Ancaster, Honington", "14.21", "GNR"], ["17.55", "Nottingham Victoria", "", "18.46", "GNR"], ["22.04", "Grantham", "", "22.27", "GNR"], ["11.01", "Skegness / Mablethorpe", "Boston, Firsby: Part to Skegness. Part to Willoughby, Sutton-on-Sea, Mablethorpe", "12.08 / 12.20", "GNR"], ["14.00", "York", "Lincoln, Gainsborough, Doncaster, Selby", "16.33", "GN&GE"], ["10.02", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "10.33", "GNR"], ["10.05", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "10.41", "GNR"], ["11.34", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "12.07", "GNR"], ["16.25", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "17.00", "GNR"], ["13.48", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "14.24", "GNR"], ["19.22", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "19.55", "GNR"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which operator runs a higher number of routes? | GNR | Answer: | 128 |
Table InputTable: [["Pos", "No", "Driver", "Team", "Laps", "Time/Retired", "Grid", "Points"], ["11", "27", "Bryan Herta", "PK Racing", "86", "+ 1 Lap", "12", "2"], ["16", "11", "Geoff Boss", "Dale Coyne Racing", "83", "Mechanical", "19", "0"], ["1", "32", "Patrick Carpentier", "Team Player's", "87", "1:48:11.023", "1", "22"], ["14", "33", "Alex Tagliani", "Rocketsports Racing", "85", "+ 2 Laps", "14", "0"], ["6", "20", "Oriol Servià", "Patrick Racing", "87", "+1:00.2", "10", "8"], ["17", "2", "Sébastien Bourdais", "Newman/Haas Racing", "77", "Mechanical", "4", "0"], ["18", "15", "Darren Manning", "Walker Racing", "12", "Mechanical", "7", "0"], ["12", "31", "Ryan Hunter-Reay", "American Spirit Team Johansson", "86", "+ 1 Lap", "17", "1"], ["2", "1", "Bruno Junqueira", "Newman/Haas Racing", "87", "+0.8 secs", "2", "17"], ["13", "19", "Joël Camathias", "Dale Coyne Racing", "85", "+ 2 Laps", "18", "0"], ["7", "51", "Adrian Fernández", "Fernández Racing", "87", "+1:01.4", "5", "6"], ["19", "5", "Rodolfo Lavín", "Walker Racing", "10", "Mechanical", "16", "0"], ["9", "7", "Tiago Monteiro", "Fittipaldi-Dingman Racing", "86", "+ 1 Lap", "15", "4"], ["3", "3", "Paul Tracy", "Team Player's", "87", "+28.6 secs", "3", "14"], ["5", "34", "Mario Haberfeld", "Mi-Jack Conquest Racing", "87", "+42.1 secs", "6", "10"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the team after patrick racing called? | Fernández Racing | Answer: | 128 |
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)", ""], ["Bengali", "230,000,000", "200,595,738", "28.30%", "320 M"], ["Urdu", "51,536,111", "43,406,932", "5.18%", "60.3 M"], ["Assamese", "13,168,484", "13,079,696", "1.56%", "15.4 M"], ["Nepali", "23,017,446", "28,061,313", "3.35%", "32.3 M"], ["Punjabi", "130,000,000", "100,017,615", "20.87%", "113 M"], ["Hindi", "422,048,642", "337,272,114", "40.0%", "336 M"], ["Maithili", "12,179,122", "1.18%", "", ""], ["Kannada", "37,924,011", "32,753,676", "3.91%", "40.3 M"], ["Marathi", "71,936,894", "62,481,681", "7.45%", "68.0 M"], ["Malayalam", "33,066,392", "30,377,176", "3.62%", "35.7 M"], ["Khandeshi", "2,075,258", "0.21%", "", ""], ["Meitei (Manipuri)", "1,466,705*", "0.14%", "1,270,216", "0.151%"], ["Telugu", "70,002,856", "65,595,738", "8.30%", "70 M"], ["Kashmiri", "5,527,698", "0.54%", "", ""], ["Bhili/Bhilodi", "9,582,957", "5,572,308", "0.665%", ""], ["Sindhi", "25,535,485", "25,122,848", "0.248%", "32.3 M"], ["Gujarati", "46,091,617", "40,673,814", "4.85%", "46.1 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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which language has more speakers than bengali? | Hindi | Answer: | 128 |
Table InputTable: [["Round", "Round", "Race", "Date", "Pole Position", "Fastest Lap", "Winning Club", "Winning Team", "Report"], ["4", "R2", "Estoril", "October 19", "", "Borussia Dortmund", "Al Ain", "Azerti Motorsport", "Report"], ["2", "R2", "Nürburgring", "September 21", "", "SC Corinthians", "PSV Eindhoven", "Azerti Motorsport", "Report"], ["2", "R1", "Nürburgring", "September 21", "A.C. Milan", "PSV Eindhoven", "A.C. Milan", "Scuderia Playteam", "Report"], ["1", "R1", "Donington Park", "August 31", "Beijing Guoan", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "Report"], ["1", "R2", "Donington Park", "August 31", "", "PSV Eindhoven", "Sevilla FC", "GTA Motor Competición", "Report"], ["6", "R2", "Jerez", "November 23", "", "Beijing Guoan", "Borussia Dortmund", "Zakspeed", "Report"], ["3", "R2", "Zolder", "October 5", "", "Atlético Madrid", "Beijing Guoan", "Zakspeed", "Report"], ["5", "R1", "Vallelunga", "November 2", "Liverpool F.C.", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "Report"], ["3", "R1", "Zolder", "October 5", "Borussia Dortmund", "Liverpool F.C.", "Liverpool F.C.", "Hitech Junior Team", "Report"], ["6", "R1", "Jerez", "November 23", "Liverpool F.C.", "R.S.C. Anderlecht", "A.C. Milan", "Scuderia Playteam", "Report"], ["4", "R1", "Estoril", "October 19", "A.S. Roma", "Atlético Madrid", "Liverpool F.C.", "Hitech Junior Team", "Report"], ["5", "R2", "Vallelunga", "November 2", "", "Atlético Madrid", "F.C. Porto", "Hitech Junior Team", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the date of the first race in the 2008 schedule? | August 31 | Answer: | 128 |
Table InputTable: [["Rank", "Country", "Box Office", "Year", "Box office\\nfrom national films"], ["9", "Russia", "$1.2 billion", "2012", "–"], ["8", "Germany", "$1.3 billion", "2012", "–"], ["12", "Brazil", "$0.72 billion", "2013", "17% (2013)"], ["2", "China", "$3.6 billion", "2013", "59% (2013)"], ["3", "Japan", "$1.88 billion", "2013", "61% (2013)"], ["5", "France", "$1.7 billion", "2012", "33.3% (2013)"], ["6", "South Korea", "$1.47 billion", "2013", "59.7% (2013)"], ["11", "Italy", "$0.84 billion", "2013", "30% (2013)"], ["-", "World", "$34.7 billion", "2012", "–"], ["4", "United Kingdom", "$1.7 billion", "2012", "36.1% (2011)"], ["7", "India", "$1.4 billion", "2012", "–"], ["10", "Australia", "$1.2 billion", "2012", "4.1% (2011)"], ["1", "Canada/United States", "$10.8 billion", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many countries' film industries made more by box office than russia? | 8 | Answer: | 128 |
Table InputTable: [["Year", "Award", "Category", "Recipient", "Result"], ["2013", "27th Golden Disk Awards", "Best New Artist", "Herself", "Won"], ["2012", "So-Loved Awards", "Best Female Newcomer", "Herself", "Won"], ["2012", "Soompi Gayo Awards", "Top 50 Songs (#3)", "\"Heaven\"", "Won"], ["2012", "Asia Song Festival", "New Artist Award", "Herself", "Won"], ["2012", "Cyworld Digital Music Awards", "Rookie & Song of the Month (February)", "\"Heaven\"", "Won"], ["2013", "Mnet Pre-Grammy Awards", "Mnet Rising Star", "Herself", "Won"], ["2013", "23rd Seoul Music Awards", "Rookie Award", "Herself", "Won"], ["2013", "15th Mnet Asian Music Awards", "Artist of the Year", "Herself", "Nominated"], ["2013", "15th Mnet Asian Music Awards", "Best Female Artist", "Herself", "Nominated"], ["2014", "28th Golden Disk Awards", "Digital Bonsang", "\"U&I\"", "Won"], ["2012", "4th MelOn Music Awards", "Best New Artist", "Herself", "Won"], ["2013", "15th Mnet Asian Music Awards", "BC - UnionPay Song of the year", "\"U&I\"", "Nominated"], ["2012", "14th Mnet Asian Music Awards", "Best New Female Artist", "Herself", "Won"], ["2013", "2nd Gaon Chart K-Pop Awards", "New Female Solo Artist", "Herself", "Won"], ["2013", "5th MelOn Music Awards", "Top 10 Artists", "Herself", "Won"], ["2014", "Soompi Music Awards", "Best Female Artist", "\"U&I\"", "Won"], ["2013", "15th Mnet Asian Music Awards", "Best Vocal Performance - Female", "\"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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year was the recipient not herself nor "heaven"? | 2014 | Answer: | 128 |
Table InputTable: [["Award", "Category", "Nominee", "Result"], ["Golden Globe Awards, 1972", "Best Director", "William Friedkin", "Won"], ["Academy Awards, 1972", "Best Director", "William Friedkin", "Won"], ["Academy Awards, 1972", "Best Sound", "Theodore Soderberg\\nChristopher Newman", "Nominated"], ["BAFTA, 1972", "Best Sound Track", "Christopher Newman\\nTheodore Soderberg", "Nominated"], ["Academy Awards, 1972", "Best Adapted Screenplay", "Ernest Tidyman", "Won"], ["BAFTA, 1972", "Best Film", "Philip D'Antoni", "Nominated"], ["BAFTA, 1972", "Best Actor", "Gene Hackman", "Won"], ["Golden Globe Awards, 1972", "Best Screenplay", "Ernest Tidyman", "Nominated"], ["Academy Awards, 1972", "Best Picture", "Phillip D'Antoni", "Won"], ["Golden Globe Awards, 1972", "Best Motion Picture", "Phillip D'Antoni", "Won"], ["Academy Awards, 1972", "Best Cinematography", "Owen Roizman", "Nominated"], ["BAFTA, 1972", "Best Film Editing", "Gerald B. Greenberg", "Won"], ["Academy Awards, 1972", "Best Actor", "Gene Hackman", "Won"], ["Academy Awards, 1972", "Best Supporting Actor", "Roy Scheider", "Nominated"], ["David di Donatello Award, 1972", "Best Foreign Film", "Philip D'Antoni", "Won"], ["Golden Globe Awards, 1972", "Best Actor", "Gene Hackman", "Won"], ["BAFTA, 1972", "Best Direction", "William Friedkin", "Nominated"], ["Directors Guild of America, 1972", "Outstanding Directorial Achievement", "William Friedkin", "Won"], ["New York Film Critics Circle, 1971", "Best Actor", "Gene Hackman", "Won"], ["Edgar Allan Poe Awards, 1972", "Best Motion Picture", "Ernest Tidyman", "Won"], ["National Society of Film Critics, 1972", "Best Actor", "Gene Hackman", "Nominated"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who won an academy award for best director in the film, "the french connection."? | William Friedkin | Answer: | 128 |
Table InputTable: [["Year", "Film", "Rotten Tomatoes", "Metacritic", "IMDb"], ["2000", "Dancer in the Dark", "68%", "61%", "8.0/10"], ["1998", "The Idiots", "70%", "47%", "6.9/10"], ["2006", "The Boss of It All", "74%", "71%", "6.7/10"], ["1984", "The Element of Crime", "77%", "N/A", "6.9/10"], ["1996", "Breaking the Waves", "86%", "76%", "7.9/10"], ["2005", "Manderlay", "51%", "46%", "7.4/10"], ["2003", "The Five Obstructions", "88%", "79%", "7.5/10"], ["2003", "Dogville", "70%", "59%", "8.0/10"], ["2011", "Melancholia", "77%", "80%", "7.1/10"], ["2009", "Antichrist", "48%", "49%", "6.6/10"], ["2013", "Nymphomaniac: Volume I", "77%", "63%", "7.5/10"], ["1987", "Epidemic", "33%", "66%", "6.1/10"], ["1982", "Images of Liberation", "N/A", "N/A", "5.1/10"], ["2013", "Nymphomaniac: Volume II", "79%", "76%", "7.2/10"], ["1991", "Europa", "85%", "66%", "7.7/10"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was each film called that scored a 7.5 from imdb? | The Five Obstructions, Nymphomaniac: Volume I | Answer: | 128 |
Table InputTable: [["Date", "Opponent#", "Rank#", "Site", "TV", "Result", "Attendance"], ["October 22", "Ole Miss", "#8", "Bryant–Denny Stadium • Tuscaloosa, AL (Rivalry)", "ABC", "W 21–10", "70,123"], ["October 8", "Southern Miss*", "#11", "Bryant–Denny Stadium • Tuscaloosa, AL", "", "W 14–6", "70,123"], ["December 3", "vs. #6 Florida", "#3", "Georgia Dome • Atlanta, GA (SEC Championship Game)", "ABC", "L 23–24", "74,751"], ["September 10", "Vanderbilt", "#11", "Bryant–Denny Stadium • Tuscaloosa, AL", "JPS", "W 17–7", "70,123"], ["November 19", "#6 Auburn", "#4", "Legion Field • Birmingham, AL (Iron Bowl)", "ABC", "W 21–14", "83,091"], ["January 2, 1995", "vs. #13 Ohio State*", "#6", "Citrus Bowl • Orlando, FL (Florida Citrus Bowl)", "ABC", "W 24–17", "71,195"], ["November 12", "at #20 Mississippi State", "#6", "Scott Field • Starkville, MS (Rivalry)", "ABC", "W 29–25", "41,358"], ["September 24", "Tulane*", "#11", "Legion Field • Birmingham, AL", "", "W 20–10", "81,421"], ["October 1", "Georgia", "#11", "Bryant–Denny Stadium • Tuscaloosa, AL", "ESPN", "W 29–28", "70,123"], ["November 5", "at LSU", "#6", "Tiger Stadium • Baton Rouge, LA (Rivalry)", "ESPN", "W 35–17", "75,453"], ["September 17", "at Arkansas", "#12", "Razorback Stadium • Fayetteville, AR", "ABC", "W 13–6", "52,089"], ["September 3", "Tennessee–Chattanooga*", "#11", "Legion Field • Birmingham, AL", "", "W 42–13", "82,109"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many wins did the tide have by 7 points. | 3 | Answer: | 128 |
Table InputTable: [["Year", "Division", "League", "Reg. Season", "Playoffs", "National Cup"], ["1935/36", "N/A", "ASL", "1st", "Champion (no playoff)", "?"], ["1952/53", "N/A", "ASL", "6th", "No playoff", "Semifinals"], ["1953/54", "N/A", "ASL", "1st", "Champion (no playoff)", "Champion"], ["1954/55", "N/A", "ASL", "8th", "No playoff", "?"], ["1950/51", "N/A", "ASL", "5th", "No playoff", "?"], ["1946/47", "N/A", "ASL", "6th", "No playoff", "?"], ["1942/43", "N/A", "ASL", "6th", "No playoff", "?"], ["1955/56", "N/A", "ASL", "6th", "No playoff", "?"], ["1943/44", "N/A", "ASL", "9th", "No playoff", "?"], ["1945/46", "N/A", "ASL", "5th", "No playoff", "?"], ["1936/37", "N/A", "ASL", "5th, National", "Did not qualify", "Champion"], ["1933/34", "N/A", "ASL", "2nd", "No playoff", "?"], ["1947/48", "N/A", "ASL", "6th", "No playoff", "?"], ["1949/50", "N/A", "ASL", "3rd", "No playoff", "?"], ["1944/45", "N/A", "ASL", "9th", "No playoff", "?"], ["1951/52", "N/A", "ASL", "6th", "No playoff", "?"], ["1940/41", "N/A", "ASL", "6th", "No playoff", "?"], ["1939/40", "N/A", "ASL", "4th", "No playoff", "?"], ["1934/35", "N/A", "ASL", "2nd", "No playoff", "?"], ["Spring 1932", "1", "ASL", "5th?", "No playoff", "1st Round"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of times that the new york americans did not qualify for the playoffs? | 2 | Answer: | 128 |
Table InputTable: [["Pick #", "NFL Team", "Player", "Position", "College"], ["1", "Baltimore Colts (Lottery bonus pick)", "George Shaw", "Quarterback", "Oregon"], ["5", "Green Bay Packers", "Tom Bettis", "Guard", "Purdue"], ["3", "Baltimore Colts", "Alan Ameche", "Fullback", "Wisconsin"], ["12", "Detroit Lions", "Dave Middleton", "Halfback", "Auburn"], ["4", "Washington Redskins", "Ralph Guglielmi", "Quarterback", "Notre Dame"], ["8", "New York Giants", "Joe Heap", "Halfback", "Notre Dame"], ["6", "Pittsburgh Steelers", "Frank Varrichione", "Tackle", "Notre Dame"], ["9", "Philadelphia Eagles", "Dick Bielski", "Fullback", "Maryland"], ["7", "Los Angeles Rams", "Larry Morris", "Center", "Georgia Tech"], ["10", "San Francisco 49ers", "Dickey Moegle", "Halfback", "Rice"], ["2", "Chicago Cardinals", "Max Boydston", "End", "Oklahoma"], ["13", "Cleveland Browns", "Kurt Burris", "Center", "Oklahoma"], ["11", "Chicago Bears", "Ron Drzewiecki", "Halfback", "Marquette"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which position was picked more than the others? | Halfback | Answer: | 128 |
Table InputTable: [["County", "Brown", "Votes", "Nixon", "Votes", "Wyckoff", "Votes"], ["Santa Barbara", "47.50%", "30,424", "51.24%", "32,821", "1.26%", "807"], ["Sonoma", "49.19%", "29,373", "49.65%", "29,647", "1.17%", "696"], ["Siskiyou", "59.98%", "7,718", "38.41%", "4,942", "1.62%", "208"], ["Sutter", "41.19%", "4,816", "57.59%", "6,734", "1.21%", "142"], ["Alameda", "57.98%", "206,861", "40.88%", "145,851", "1.13%", "4,038"], ["San Luis Obispo", "52.86%", "16,110", "45.36%", "13,825", "1.78%", "543"], ["Nevada", "51.02%", "4,818", "47.12%", "4,450", "1.85%", "175"], ["Lassen", "62.50%", "3,500", "35.14%", "1,968", "2.36%", "132"], ["Sacramento", "60.69%", "115,462", "37.74%", "71,788", "1.57%", "2,988"], ["San Bernardino", "51.68%", "88,437", "46.78%", "80,054", "1.54%", "2,634"], ["Merced", "57.62%", "14,105", "41.14%", "10,071", "1.23%", "302"], ["Riverside", "46.60%", "50,257", "51.86%", "55,926", "1.54%", "1,666"], ["San Joaquin", "49.40%", "43,276", "49.25%", "43,147", "1.34%", "1,178"], ["San Francisco", "62.19%", "180,298", "36.96%", "107,165", "0.85%", "2,455"], ["Santa Clara", "51.20%", "121,149", "47.63%", "112,700", "1.18%", "2,783"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many counties had at least 200 votes for wyckoff? | 36 | Answer: | 128 |
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["24 December 1960", "Manchester United", "H", "1-2", "37,601", "Brabrook"], ["26 December 1960", "Manchester United", "A", "0-6", "50,213", ""], ["10 December 1960", "Cardiff City", "A", "1-2", "21,840", "Greaves"], ["19 September 1960", "Blackburn Rovers", "A", "1-3", "21,508", "Brabrook"], ["5 November 1960", "Newcastle United", "H", "4-2", "30,489", "Brabrook, Tindall (3)"], ["19 November 1960", "Manchester City", "H", "6-3", "37,346", "Greaves (3), Tindall (2), Tambling"], ["26 November 1960", "Nottingham Forest", "A", "1-2", "22,121", "Brabrook"], ["31 December 1960", "Wolverhampton Wanderers", "A", "1-6", "28,503", "Anderton"], ["3 December 1960", "West Bromwich Albion", "H", "7-1", "19,568", "Brabrook, Greaves (5), Tindall"], ["7 September 1960", "Blackburn Rovers", "H", "5-2", "23,224", "Greaves (3), Livesey (2)"], ["17 December 1960", "Aston Villa", "H", "2-4", "23,805", "Greaves (2)"], ["3 September 1960", "Bolton Wanderers", "A", "1-4", "21,609", "Greaves"], ["10 September 1960", "West Ham United", "H", "3-2", "37,873", "Greaves, Livesey, Blunstone"], ["12 November 1960", "Arsenal", "A", "4-1", "38,666", "Mortimore, Greaves, Tindall, Tambling"], ["15 October 1960", "Birmingham City", "A", "0-1", "22,337", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many attended the game on 10 december 1960? | 21,840 | Answer: | 128 |
Table InputTable: [["Divisions", "Prize (EUR)", "Odds of winning (1 in)", "Number of winning tickets", "In order to win"], ["Sub", "180.00", "2,000", "2", "Nearest number to 1st prize"], ["Sub", "180.00", "2,000", "2", "Nearest number to 3rd prize"], ["Sub", "180.00", "2,000", "2", "Nearest number to 2nd prize"], ["All", "45,000.00", "3.54", "565", "Any Prize"], ["4th", "450.00", "2,000", "1", "Match all 5 in order"], ["3rd", "600.00", "2,000", "1", "Match all 5 in order"], ["1st", "18,000.00", "2,000", "1", "Match all 5 in order"], ["2nd", "750.00", "2,000", "1", "Match all 5 in order"], ["6th", "135.00", "2,000", "1", "Match all 5 in order"], ["5th", "300.00", "2,000", "1", "Match all 5 in order"], ["Sub", "17,820.00", "20.2", "297", "First 3 Digits of 1st, 2nd & 3rd"], ["Sub", "3,420.00", "105.3", "57", "Last 2 Digits of 1st, 2nd & 3rd"], ["Sub", "2,985.00", "10.1", "199", "Last 1 Digit of 1st"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:for which odds of winning is the prize greater than $450.00? | 2,000 | Answer: | 128 |
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2009", "16 Jan 2009", "Wengen, Switzerland", "Super Combined", "", "", "", ""], ["2009", "13 Dec 2008", "Val d'Isère, France", "Giant slalom", "", "", "", ""], ["2010", "4 Dec 2009", "Beaver Creek, USA", "Super Combined", "", "", "", ""], ["2010", "6 Dec 2009", "Beaver Creek, USA", "Giant Slalom", "", "", "", ""], ["2010", "12 Mar 2010", "Garmisch, Germany", "Giant Slalom", "", "", "", ""], ["2011", "5 Mar 2011", "Kranjska Gora, Slovenia", "Giant Slalom", "", "", "", ""], ["2010", "10 Mar 2010", "Garmisch, Germany", "Downhill", "", "", "", ""], ["2010", "5 Dec 2009", "Beaver Creek, USA", "Downhill", "", "", "", ""], ["2010", "16 Jan 2010", "Wengen, Switzerland", "Downhill", "", "", "", ""], ["Season", "Date", "Location", "Race", "", "", "", ""], ["2009", "22", "7", "–", "6", "16", "16", "1"], ["2008", "21", "64", "–", "28", "46", "46", "31"], ["2010", "23", "1", "–", "2", "6", "2", "2"], ["2007", "20", "130", "–", "40", "–", "–", "—"], ["2012", "25", "24", "–", "16", "28", "17", "19"], ["2011", "24", "3", "–", "5", "6", "9", "6"], ["2013", "26", "48", "–", "48", "27", "38", "4"], ["2014", "27", "18", "–", "25", "14", "20", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what race was run previous to the super combined in 2009? | Giant slalom | Answer: | 128 |
Table InputTable: [["No. in\\nseason", "No. in\\nseries", "Title", "Canadian airdate", "US airdate", "Production code"], ["22", "339", "\"Basket Case\"", "March 4, 2014", "March 4, 2014", "1322"], ["19", "336", "\"Dig Me Out\"", "February 11, 2014", "February 11, 2014", "1319"], ["30", "347", "\"Sparks Will Fly\" Part Two", "April 22, 2014", "April 22, 2014", "1330"], ["29", "346", "\"Sparks Will Fly\" Part One", "April 15, 2014", "April 15, 2014", "1329"], ["4", "321", "\"My Own Worst Enemy\"", "July 25, 2013", "July 25, 2013", "1304"], ["13", "330", "\"Who Do You Think You Are\"", "October 31, 2013", "October 31, 2013", "1313"], ["39", "356", "\"Thunderstruck\" Part One", "July 29, 2014", "July 29, 2014", "1339"], ["36", "353", "\"Out Of My Head\"", "July 8, 2014", "July 8, 2014", "1336"], ["18", "335", "\"Better Man\"", "February 4, 2014", "February 4, 2014", "1318"], ["10", "327", "\"You Got Me\"", "October 10, 2013", "October 10, 2013", "1310"], ["26", "343", "\"Close to Me\"", "March 25, 2014", "March 25, 2014", "1326"], ["27", "344", "\"Army of Me\"", "April 1, 2014", "April 1, 2014", "1327"], ["34", "351", "\"My Hero\"", "June 24, 2014", "June 24, 2014", "1334"], ["31", "348", "\"You Are Not Alone\"", "June 3, 2014", "June 3, 2014", "1331"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which was an earlier episode, "dig me out" or "basket case"? | "Dig Me Out" | Answer: | 128 |
Table InputTable: [["Player", "No.", "Nationality", "Position", "Years for Jazz", "School/Club Team"], ["Terry Furlow", "25", "United States", "Guard/Forward", "1979-80", "Michigan State"], ["Todd Fuller", "52", "United States", "Center", "1998-99", "North Carolina State"], ["Jim Farmer", "30", "United States", "Guard", "1988-89", "Alabama"], ["Derrick Favors", "15", "United States", "Forward", "2011-present", "Georgia Tech"], ["Bernie Fryer", "25", "United States", "Guard", "1975-76", "BYU"], ["Greg Foster", "44", "United States", "Center/Forward", "1995-99", "UTEP"], ["Derek Fisher", "2", "United States", "Guard", "2006-2007", "Arkansas-Little Rock"], ["Kyrylo Fesenko", "44", "Ukraine", "Center", "2007-11", "Cherkasy Monkeys (Ukraine)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many players played for the jazz for at least 3 years? | 3 | Answer: | 128 |
Table InputTable: [["Year", "Film", "Role", "Language", "Notes"], ["2014", "Endendigu", "", "", "Filming"], ["2012", "18th Cross", "Punya", "Kannada", ""], ["2013", "Bahaddoor", "Anjali", "Kannada", "Filming"], ["2013", "Dilwala", "Preethi", "Kannada", ""], ["2012", "Alemari", "Neeli", "Kannada", ""], ["2012", "Drama", "Nandini", "Kannada", ""], ["2013", "Kaddipudi", "Uma", "Kannada", ""], ["2012", "Sagar", "Kajal", "Kannada", ""], ["2008", "Moggina Manasu", "Chanchala", "Kannada", "Filmfare Award for Best Actress - Kannada\\nKarnataka State Film Award for Best Actress"], ["2010", "Krishnan Love Story", "Geetha", "Kannada", "Filmfare Award for Best Actress - Kannada\\nUdaya Award for Best Actress"], ["2012", "Addhuri", "Poorna", "Kannada", "Udaya Award for Best Actress\\nNominated — SIIMA Award for Best Actress\\nNominated — Filmfare Award for Best Actress – Kannada"], ["2010", "Gaana Bajaana", "Radhey", "Kannada", ""], ["2012", "Breaking News", "Shraddha", "Kannada", ""], ["2014", "Mr. & Mrs. Ramachari", "", "", "Announced"], ["2011", "Hudugaru", "Gayithri", "Kannada", "Nominated, Filmfare Award for Best Actress – Kannada"], ["2009", "Olave Jeevana Lekkachaara", "Rukmini", "Kannada", "Innovative Film Award for Best Actress"], ["2009", "Love Guru", "Kushi", "Kannada", "Filmfare Award for Best Actress - Kannada"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total films have they already appeared in? | 17 | Answer: | 128 |
Table InputTable: [["#", "Office", "Current Officer"], ["", "Governor of New Mexico", "Susana Martinez"], ["1", "Lieutenant Governor of New Mexico", "John Sanchez"], ["2", "Secretary of State of New Mexico", "Dianna Duran"], ["4", "Attorney General of New Mexico", "Gary King"], ["6", "State Treasurer", "James B. Lewis"], ["7", "Commissioner of Public Lands", "Ray Powell"], ["4", "Speaker of the House of Representatives", "W. Ken Martinez"], ["5", "State Auditor", "Hector Balderas"], ["8", "Public Regulation Commission, Chair", "Patrick Lyons"], ["", "May succeed to Governorship", ""], ["10", "Public Regulation Commissioner", "Valerie Espinoza"], ["12", "Public Regulation Commissioner", "Ben Hall"], ["9", "Public Regulation Commissioner", "Karen Montoya"], ["3", "President Pro Tempore of the Senate", "Mary Kay Papen"], ["11", "Public Regulation Commissioner", "Theresa Becenti–Aguilar"], ["", "May serve as Emergency Interim Successor", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the governor of new mexico? | Susana Martinez | Answer: | 128 |
Table InputTable: [["School", "Season", "Record", "Conference Record", "Place", "Postseason"], ["Illinois", "1919–20", "9–4", "8–4", "3rd", ""], ["Illinois", "1913–14", "9–4", "7–3", "3rd", ""], ["Illinois", "1917–18", "9–6", "6–6", "T4th", ""], ["Illinois", "1914–15", "16–0", "12–0", "T1st", "National Champions"], ["Illinois", "1912–13", "10–6", "7–6", "5th", ""], ["Illinois", "1915–16", "13–3", "9–3", "T2nd", ""], ["Illinois", "1916–17", "13–3", "10–2", "T1st", "Big Ten Champions"], ["Illinois", "1918–19", "6–8", "5–7", "5th", ""], ["Illinois", "1912–20", "85–34", "64–31", "–", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many seasons did they lose no more than 3 conference games? | 4 | Answer: | 128 |
Table InputTable: [["Publication", "Country", "Accolade", "Year", "Rank"], ["VPRO", "Netherlands", "299 Nominations of the Best Album of All Time", "2006", "*"], ["The Times", "United Kingdom", "The 100 Best Albums of All Time", "1993", "58"], ["NME", "United Kingdom", "All Times Top 100 Albums + Top 50 by Decade", "1993", "145"], ["The Wire", "United Kingdom", "The 100 Most Important Records Ever Made", "1992", "*"], ["Pop", "Sweden", "The World's 100 Best Albums + 300 Complements", "1994", "101"], ["NME", "United Kingdom", "All Times Top 100 Albums", "1985", "46"], ["Adresseavisen", "Norway", "The 100 (+23) Best Albums of All Time", "1995", "101"], ["Time Out", "United Kingdom", "The 100 Best Albums of All Time", "1989", "3"], ["Hot Press", "Ireland", "The 100 Best Albums of All Time", "1989", "32"], ["Sounds", "United Kingdom", "The 100 Best Albums of All Time", "1986", "24"], ["Rock de Lux", "Spain", "The 100 Best Albums of the 1970s", "1988", "39"], ["Rock de Lux", "Spain", "The 200 Best Albums of All Time", "2002", "53"], ["OOR", "Netherlands", "Albums of the Year", "1973", "41"], ["Spex", "Germany", "The 100 Albums of the Century", "1999", "93"], ["Paul Gambaccini", "United States", "The World Critics Best Albums of All Time", "1987", "84"], ["Jimmy Guterman", "United States", "The 100 Best Rock and Roll Records of All Time", "1992", "27"], ["Rolling Stone", "United States", "The 500 Greatest Albums of All Time", "2003", "165"], ["The New Nation", "United Kingdom", "Top 100 Albums by Black Artists", "2005", "27"], ["The Recording Academy", "United States", "Grammy Hall of Fame Albums and Songs", "2004", "*"], ["Blender", "United States", "The 100 Greatest American Albums of All time", "2002", "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", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country held the most accolades? | United States | Answer: | 128 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.