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Table InputTable: [["PrecededΒ by\\nAlfred Scott", "Member of Parliament for Ashton-under-Lyne\\n1910–1916", "SucceededΒ by\\nAlbert Stanley"], ["PrecededΒ by\\nSir Frederick Cawley", "Chancellor of the Duchy of Lancaster\\n1918", "SucceededΒ by\\nThe Lord Downham"], ["New creation", "Baron Beaverbrook\\n1917–1964", "SucceededΒ by\\nJohn William Maxwell Aitken"], ["New creation", "Baronet(of Cherkley)Β \\n1916–1964", "SucceededΒ by\\nJohn William Maxwell Aitken"], ["PrecededΒ by\\nViscount Cranborne", "Lord Privy Seal\\n1943–1945", "SucceededΒ by\\nArthur Greenwood"], ["PrecededΒ by\\nSir Andrew Duncan", "Minister of Supply\\n1941–1942", "SucceededΒ by\\nSir Andrew Duncan"], ["New office", "Minister of Information\\n1918", "SucceededΒ by\\nThe Lord Downham"], ["New office", "Minister of War Production\\n1942", "SucceededΒ by\\nOliver Lyttelton\\nas Minister of Production"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 what year was lord beaverbrook chancellor of the duchy of lancaster?
1918
Answer:
128
Table InputTable: [["Year", "Film", "Role", "Notes"], ["1972", "Eagle in a Cage", "Betty Balcombe", ""], ["2011", "Cockneys vs Zombies", "Doreen", ""], ["1978", "Sweeney 2", "Switchboard Girl", ""], ["1971", "The Boy Friend", "Fay", ""], ["1980", "The Watcher in the Woods", "Young Mrs Aylwood", ""], ["2013", "Still Waters", "Grandma", "In Production"], ["1994", "Beyond Bedlam", "Sister Romulus", ""], ["1976", "Voyage of the Damned", "Lotte Schulman", ""], ["1973", "The Love Ban", "Joyce", ""], ["1986", "Castaway", "Sister Saint Margaret", ""], ["1971", "The Devils", "Phillippe", ""], ["1995", "Jackson: My Life... Your Fault", "Josephine", ""], ["2005", "Mrs Palfrey at the Claremont", "Shirley Burton", ""], ["1997", "Preaching to the Perverted", "Miss Wilderspin", ""]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:when did the movie "eagle in a cage," starring georgina hale, get released in the usa?
1972
Answer:
128
Table InputTable: [["#", "Date", "Venue", "Opponent", "Score", "Result", "Competition"], ["8", "March 14, 1993", "Tokyo, Japan", "Japan", "1–0", "1–3", "Friendly"], ["12", "March 26, 1994", "Dallas, Texas", "Bolivia", "1–1", "2–2", "Friendly"], ["11", "February 20, 1994", "Miami, Florida", "Sweden", "1–3", "1–0", "Friendly"], ["6", "April 4, 1992", "Palo Alto, California", "China PR", "1–0", "1-0", "Friendly"], ["5", "March 18, 1992", "Casablanca, Morocco", "Morocco", "1–2", "1–3", "Friendly"], ["7", "April 4, 1992", "Palo Alto, California", "China PR", "5–0", "1-0", "Friendly"], ["10", "December 5, 1993", "Los Angeles, California", "El Salvador", "5–0", "7–0", "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:what venue was immediately after tokyo, japan?
High Point, North Carolina
Answer:
128
Table InputTable: [["Olympics", "Athlete", "Judge (Official)", "Coach", "Language"], ["1976 Summer Olympics", "Pierre St.-Jean", "Maurice Fauget", "-", "French (St.-Jean)/English (Fauget)"], ["1984 Summer Olympics", "Edwin Moses", "Sharon Weber", "-", "English"], ["1956 Summer Olympics", "John Landy (Melbourne)\\nHenri Saint Cyr (Stockholm)", "-", "-", "English/Swedish"], ["1936 Summer Olympics", "Rudolf Ismayr", "-", "-", "-"], ["1972 Summer Olympics", "Heidi SchΓΌller", "Heinz Pollay", "-", "German"], ["1948 Summer Olympics", "Donald Finlay", "-", "-", "English"], ["2012 Summer Olympics", "Sarah Stevenson", "Mik Basi", "Eric Farrell", "English"], ["1996 Summer Olympics", "Teresa Edwards", "Hobie Billingsley", "-", "English"], ["2000 Summer Olympics", "Rechelle Hawkes", "Peter Kerr", "-", "English"], ["1992 Summer Olympics", "Luis Doreste Blanco", "Eugeni Asensio", "-", "Spanish/Catalan"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the name of the last speaker?
Ruslan Zakharov
Answer:
128
Table InputTable: [["Series Number", "Season Number", "Episode Title", "Premiere Date", "Production Code"], ["5", "5", "Hurricane Jules", "November 22, 1998", "105"], ["1", "1", "Going Up!", "October 25, 1998", "101"], ["4", "4", "Close Encounters", "November 15, 1998", "104"], ["12", "12", "Bottom's Up", "March 7, 1999", "112"], ["2", "2", "Who's The Man", "November 1, 1998", "102"], ["3", "3", "Vootle-Muck-A-Heev", "November 8, 1998", "103"], ["13", "13", "Hot Dog", "March 14, 1999", "113"], ["7", "7", "Front Page", "January 17, 1999", "107"], ["11", "11", "JB's Big Break", "February 21, 1999", "111"], ["6", "6", "Switcheroo", "November 29, 1998", "106"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the name of the next title after hurricane jules?
Switcheroo
Answer:
128
Table InputTable: [["Year", "Division", "League", "Regular Season", "Playoffs", "Open Cup"], ["2009", "4", "USL PDL", "6th, Heartland", "Did not qualify", "Did not qualify"], ["2004", "4", "USL PDL", "6th, Heartland", "Did not qualify", "Did not qualify"], ["2008", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["2012", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["2006", "4", "USL PDL", "3rd, Heartland", "Did not qualify", "Did not qualify"], ["2007", "4", "USL PDL", "3rd, Heartland", "Did not qualify", "1st Round"], ["2010", "4", "USL PDL", "7th, Heartland", "Did not qualify", "Did not qualify"], ["1999", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:when did they get 6th place in the regular season before their 6th place finish in 2009?
2004
Answer:
128
Table InputTable: [["Wrestler:", "Reigns:", "Date:", "Place:", "Notes:"], ["Randy Savage", "3", "1982", "Unknown", ""], ["Randy Savage", "2", "1981", "Unknown", ""], ["Randy Savage", "1", "March 13, 1979", "Halifax, Nova Scotia", ""], ["Paul Christy", "1", "November 13, 1983", "Springfield, Illinois", ""], ["Lanny Poffo", "4", "January 1, 1984", "Springfield, Illinois", ""], ["Lanny Poffo", "1", "May 10, 1978", "San Francisco, California", "Defeated Joe Banek to become the first champion"], ["Lanny Poffo", "3", "1981", "Unknown", ""], ["Lanny Poffo", "2", "July 21, 1979", "Lexington, Kentucky", ""]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 reigns for randy savage?
6
Answer:
128
Table InputTable: [["No.", "Score", "Player", "Team", "Balls", "Inns.", "Opposing team", "Date", "Result"], ["9", "107", "Virat Kohli", "India", "114", "2", "Sri Lanka", "24 December 2009", "Won"], ["6", "134*", "Graeme Smith", "South Africa", "124", "2", "India", "25 November 2005", "Won"], ["11", "101", "Paul Stirling", "Ireland", "72", "2", "Netherlands", "18 March 2011", "Won"], ["12", "106", "Nasir Jamshed", "Pakistan", "124", "1", "India", "3 January 2013", "Won"], ["2", "107*", "Desmond Haynes", "West Indies", "137", "1", "Pakistan", "1 November 1989", "Lost"], ["3", "100*", "Sachin Tendulkar", "India", "103", "2", "Kenya", "31 May 1998", "Won"], ["5", "108*", "Salman Butt", "Pakistan", "130", "2", "India", "13 November 2004", "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:how many teams are there that are not also opposing teams?
3
Answer:
128
Table InputTable: [["Rank", "Name", "Club", "Nationality", "Points"], ["8", "Alessandro Mazzola", "Internazionale", "Italy", "9"], ["15", "Mario Corso", "Internazionale", "Italy", "3"], ["7", "Gianni Rivera", "Milan", "Italy", "10"], ["2", "Giacinto Facchetti", "Internazionale", "Italy", "59"], ["17", "Milan Galić", "Partizan Beograd", "Yugoslavia", "2"], ["3", "Luis SuÑrez", "Internazionale", "Spain", "45"], ["17", "Amancio Amaro", "Real Madrid", "Spain", "2"], ["1", "Eusébio", "Benfica", "Portugal", "67"], ["17", "MÑrio Coluna", "Benfica", "Portugal", "2"], ["13", "Ferenc PuskÑs", "Real Madrid", "Spain", "5"], ["25", "Sigfried Held", "Borussia Dortmund", "West Germany", "1"], ["12", "Karl-Heinz Schnellinger", "Milan", "West Germany", "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:what was the average number of points scored by italians?
20.25
Answer:
128
Table InputTable: [["Hull", "Type", "Original Name", "Original Operator", "Delivery", "Disposition (2012)", "2nd name", "2nd operator", "3rd Name", "3rd operator"], ["β„– 9", "929-117", "Venus", "Kyushu Yusen", "Mar 1991", "Active", "", "", "", ""], ["β„– 12", "929-117", "Toppy 2", "Tane Yaku Jetfoils", "Apr 1992", "Active", "", "", "", ""], ["β„– 11", "929-117", "Princess Teguise", "Trasmediterranea", "Jun 1991", "Active", "2007 Toppy 5", "Tane Yaku Jetfoils", "", ""], ["β„– 10", "929-117", "Suisei", "Sado Kisen", "Apr 1991", "Active", "", "", "", ""], ["β„– 13", "929-117", "Toppy 3", "Tane Yaku Jetfoils", "Mar 1995", "Active", "", "", "", ""], ["β„– 4", "929-117", "Princess Dacil", "Trasmediterranea", "Mar 1990", "Active", "Pegasus", "Kyusyu Shosen Co. Ltd.", "", ""]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 original name is after venus in apr 1991?
Suisei
Answer:
128
Table InputTable: [["#", "Date", "Location", "Winner", "Score\\nJSU", "Score\\nTU", "Series"], ["2", "October 28, 1927", "?", "Jacksonville State", "26", "12", "JSU 2–0"], ["8", "November 11, 1938", "Jacksonville, AL", "Tied", "6", "6", "TSU 4–3–1"], ["1", "November 27, 1924", "Jacksonville, AL", "Jacksonville State", "14", "9", "JSU 1–0"], ["14", "December 18, 1948", "Pensacola, FL", "Jacksonville State", "19", "0", "TSU 7–6–1"], ["9", "November 11, 1939", "Troy, AL", "Troy State", "0", "27", "TSU 5–3–1"], ["3", "November 16, 1928", "Troy, AL", "Jacksonville State", "20", "0", "JSU 3–0"]]
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:in years, how long has it been since the first game listed?
70
Answer:
128
Table InputTable: [["Chord", "Root", "Minor Third", "Perfect Fifth", "Major Seventh"], ["DmM7", "D", "F", "A", "Cβ™―"], ["GmM7", "G", "Bβ™­", "D", "Fβ™―"], ["EmM7", "E", "G", "B", "Dβ™―"], ["Dβ™­mM7", "Dβ™­", "Fβ™­ (E)", "Aβ™­", "C"], ["CmM7", "C", "Eβ™­", "G", "B"], ["AmM7", "A", "C", "E", "Gβ™―"], ["BmM7", "B", "D", "Fβ™―", "Aβ™―"], ["FmM7", "F", "Aβ™­", "C", "E"], ["Bβ™­mM7", "Bβ™­", "Dβ™­", "F", "A"], ["Eβ™­mM7", "Eβ™­", "Gβ™­", "Bβ™­", "D"], ["Dβ™―mM7", "Dβ™―", "Fβ™―", "Aβ™―", "C (D)"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:is dm above or below am?
above
Answer:
128
Table InputTable: [["Date", "Venue", "Opponent", "Result", "Scoreline", "China scorers"], ["Dec 17", "Muscat", "Oman", "Lost", "1-3", "Qu Bo 58'"], ["Dec 19", "Muscat", "Iran", "Lost", "0-2", ""], ["April 23", "Los Angeles", "El Salvador", "Drawn", "2-2", "Xiao Zhanbo 62' pen\\nQu Bo 63'"], ["January 20", "Zhongshan", "Lebanon", "Drawn", "0-0", "β€”"], ["March 15", "Kunming", "Thailand", "Drawn", "3-3", "Qu Bo 34'\\nHan Peng 67'\\nZhu Ting 90'"], ["April 16", "Seattle", "Mexico", "Lost", "0-1", "β€”"], ["Dec 21", "Amman", "Jordan", "Won", "1-0", "Cao Yang 77'"], ["January 27", "Zhongshan", "Syria", "Won", "2-1", "Qu Bo 64'\\nZhu Ting 90'"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the last date?
Dec 21
Answer:
128
Table InputTable: [["Country", "Amphibians", "Birds", "Mammals", "Reptile", "Total terrestrial vertebrates", "Vascular plants", "Biodiversity"], ["Guatemala", "133", "684", "193", "236", "1246", "8681", "9927"], ["Belize", "46", "544", "147", "140", "877", "2894", "3771"], ["Costa Rica", "183", "838", "232", "258", "1511", "12119", "13630"], ["Honduras", "101", "699", "201", "213", "1214", "5680", "6894"], ["El Salvador", "30", "434", "137", "106", "707", "2911", "3618"], ["Nicaragua", "61", "632", "181", "178", "1052", "7590", "8642"], ["Panama", "182", "904", "241", "242", "1569", "9915", "11484"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 species of birds are there in guatemala?
684
Answer:
128
Table InputTable: [["Model", "1991", "1995", "1996", "1997", "1998", "1999", "2000", "2001", "2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013"], ["Ε koda Superb", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "177", "16,867", "23,135", "22,392", "22,091", "20,989", "20,530", "25,645", "44,548", "98,873", "116,700", "106,847", "94,400"], ["Ε koda Rapid", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "1,700", "9,292", "103,800"], ["Ε koda Felicia", "172,000", "210,000", "", "288,458", "261,127", "241,256", "148,028", "44,963", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’", "βˆ’"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what year did skoda begin selling more than 300,000 cars?
1997
Answer:
128
Table InputTable: [["Week", "Date", "Opponent", "Score", "Result", "Record"], ["5", "Sept 25", "vs. Hamilton Tiger-Cats", "38–12", "Loss", "1–5"], ["10", "Oct 30", "vs. Hamilton Tiger-Cats", "30–9", "Loss", "1–11"], ["3", "Sept 11", "at Toronto Argonauts", "12–5", "Win", "1–3"], ["12", "Nov 13", "vs. Montreal Alouettes", "14–12", "Win", "2–12"], ["6", "Oct 2", "at Hamilton Tiger-Cats", "45–0", "Loss", "1–6"], ["9", "Oct 23", "at Hamilton Tiger-Cats", "25–17", "Loss", "1–10"], ["4", "Sept 18", "vs. Toronto Argonauts", "34–6", "Loss", "1–4"], ["8", "Oct 16", "vs. Toronto Argonauts", "27–11", "Loss", "1–9"], ["7", "Oct 9", "vs. Montreal Alouettes", "25–11", "Loss", "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:what is the total number of wins?
2
Answer:
128
Table InputTable: [["Sl no", "Name of the prabandham", "Starting from", "Ending with", "Number of pasurams", "Sung by"], ["", "Total number of pasurams", "", "", "3776", ""], ["18", "Thiruvasiriyam", "2578", "2584", "7", "Nammalvar"], ["16", "Naanmugan Thiruvandhadhi", "2382", "2477", "96", "Thirumalisai alvar"], ["11", "Kurun Thandagam", "2032", "2051", "20", "Thirumangai alvar"], ["12", "Nedum Thandagam", "2052", "2081", "30", "Thirumangai alvar"], ["4", "Perumal Thirumozhi", "647", "751", "105", "Kulasekara alvar"], ["8", "Amalanadhi piran", "927", "936", "10", "Thiruppaan alvar"], ["17", "Thiruviruththam", "2478", "2577", "100", "Nammalvar"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "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 pasurams are in naanmugan
96
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)"], ["3", "Air Commodore K. M. Ahmad", "1979", "1980", "Pakistan Air Force Academy", "Flight Instructor", "Certificated Flight Instructor (CFI)"], ["7", "Dr Abdul Majid", "1997", "2001", "University of Wales", "Astrophysics", "Ph.D"], ["8", "Major General Raza Hussain", "2001", "2010", "Pakistan Army Corps of Electrical and Mechanical Engineers", "Electrical Engineering", "B.S."], ["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 WΕ‚adysΕ‚aw Turowicz", "1967", "1979", "Warsaw University of Technology", "Aeronautical Engineering", "Ph.D"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:who was the last administrator of suparco?
Major General Ahmed Bilal
Answer:
128
Table InputTable: [["District", "Location", "Communities served"], ["Solon/Bainbridge Montessori School of Languages", "Bainbridge Township, Ohio", "nonsectarian Montessori School: quarterly enrollment periods"], ["Hershey Montessori Farm School", "Huntsburg Township, Ohio", "parent-owned, and chartered by Ohio Department of Education: application deadline January each year"], ["Saint Anselm School", "Chester Township, Ohio", "Roman Catholic Diocese of Cleveland K - 8th grade; preschool"], ["Hawken School", "Gates Mills, Ohio", "College preparatory day school: online application, site visit and testing"], ["Notre Dame-Cathedral Latin", "Munson Township, Ohio", "Roman Catholic Diocese of Cleveland: open to 8th grade students who have attended a Catholic elementary school and others who have not"], ["Saint Mary's School", "Chardon, Ohio", "Roman Catholic Diocese of Cleveland preschool - 8th grade; parishioners and non-parishioners"], ["Agape Christian Academy", "Burton Township, Ohio and Troy Township, Ohio", "Accepts applications prior to the start of each school year"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many of the schools are montessori schools?
1
Answer:
128
Table InputTable: [["Year", "Winner", "Age", "Jockey", "Trainer", "Owner", "Distance\\n(Miles)", "Time", "Purse", "Gr"], ["1966", "Williamston Kid †", "3", "Robert Stevenson", "James Bartlett", "Ternes & Bartlett", "1-1/8", "1:50.60", "", ""], ["1969", "Top Knight", "3", "Manuel Ycaza", "Ray Metcalf", "Steven B. Wilson", "1-1/8", "1:48.40", "", ""], ["1959", "Easy Spur", "3", "Bill Hartack", "Paul L. Kelley", "Spring Hill Farm", "1-1/8", "1:47.20", "", ""], ["1956", "Needles", "3", "David Erb", "Hugh L. Fontaine", "D & H Stable", "1-1/8", "1:48.60", "", ""], ["1981", "Lord Avie", "3", "Chris McCarron", "Daniel Perlsweig", "David Simon", "1-1/8", "1:50.40", "$250,000", "I"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 their main age listed?
3
Answer:
128
Table InputTable: [["No.", "Date", "Tournament", "Winning score", "Margin of\\nvictory", "Runner(s)-up"], ["3", "25 Apr 2004", "Tsuruya Open", "βˆ’9 (64-73-69-69=275)", "2 strokes", "Keiichiro Fukabori, Scott Laycock,\\n Tatsuya Mitsuhashi, Taichi Teshima,\\n Shinichi Yokota"], ["9", "26 Sep 2010", "Asia-Pacific Panasonic Open\\n(co-sanctioned by the Asian Tour)", "βˆ’6 (71-70-66=207)", "1 stroke", "Ryuichi Oda"], ["6", "22 Apr 2007", "Tsuruya Open", "βˆ’16 (67-65-68-68=268)", "2 strokes", "Masahiro Kuramoto, Hirofumi Miyase,\\n Takuya Taniguchi"], ["5", "23 Apr 2006", "Tsuruya Open", "βˆ’11 (70-68-66-69=273)", "2 strokes", "Mamo Osanai"], ["11", "15 Apr 2012", "Token Homemate Cup", "βˆ’15 (68-69-70-62=269)", "2 strokes", "Ryuichi Oda"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 the only tournament with a british runner-up?
Tsuruya Open
Answer:
128
Table InputTable: [["Year", "Car", "Start", "Qual", "Rank", "Finish", "Laps", "Led", "Retired"], ["1928", "8", "4", "117.031", "4", "10", "200", "33", "Running"], ["1939", "62", "27", "121.749", "24", "11", "200", "0", "Running"], ["1937", "38", "7", "118.788", "16", "8", "200", "0", "Running"], ["1927", "27", "27", "107.765", "22", "3", "200", "0", "Running"], ["1933", "34", "12", "113.578", "15", "7", "200", "0", "Running"], ["1929", "23", "11", "112.146", "15", "17", "91", "0", "Supercharger"], ["1931", "37", "19", "111.725", "6", "18", "167", "0", "Crash T4"], ["1932", "25", "20", "108.896", "34", "13", "184", "0", "Flagged"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 most laps run before being retired?
200
Answer:
128
Table InputTable: [["#", "Player", "Goals", "Caps", "Career"], ["8", "Eddie Johnson", "19", "62", "2004–present"], ["1", "Landon Donovan", "57", "155", "2000–present"], ["9T", "Earnie Stewart", "17", "101", "1990–2004"], ["2", "Clint Dempsey", "36", "103", "2004–present"], ["4", "Brian McBride", "30", "95", "1993–2006"], ["6T", "Bruce Murray", "21", "86", "1985–1993"], ["9T", "DaMarcus Beasley", "17", "114", "2001–present"], ["3", "Eric Wynalda", "34", "106", "1990–2000"], ["5", "Joe-Max Moore", "24", "100", "1992–2002"], ["6T", "Jozy Altidore", "21", "67", "2007–present"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what was the total number of goals scored by johnson and stewart?
36
Answer:
128
Table InputTable: [["Year", "Film", "Rotten Tomatoes", "Metacritic", "IMDb"], ["2006", "The Boss of It All", "74%", "71%", "6.7/10"], ["2000", "Dancer in the Dark", "68%", "61%", "8.0/10"], ["1996", "Breaking the Waves", "86%", "76%", "7.9/10"], ["1998", "The Idiots", "70%", "47%", "6.9/10"], ["2003", "The Five Obstructions", "88%", "79%", "7.5/10"], ["2009", "Antichrist", "48%", "49%", "6.6/10"], ["2003", "Dogville", "70%", "59%", "8.0/10"], ["1984", "The Element of Crime", "77%", "N/A", "6.9/10"], ["2013", "Nymphomaniac: Volume I", "77%", "63%", "7.5/10"], ["1982", "Images of Liberation", "N/A", "N/A", "5.1/10"]]
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 he has made?
15
Answer:
128
Table InputTable: [["Representative", "Party", "Home Town/City", "District"], ["Jose Menendez", "D", "San Antonio", "124"], ["Roland Gutierrez", "D", "San Antonio", "119"], ["Philip Cortez", "D", "San Antonio", "117"], ["Mike Villarreal", "D", "San Antonio", "123"], ["Joe Farias", "D", "San Antonio", "118"], ["Trey Martinez Fischer", "D", "San Antonio", "116"], ["Justin Rodriguez", "D", "San Antonio", "125"], ["Joe Straus", "R", "San Antonio", "121"], ["Lyle Larson", "R", "San Antonio", "122"], ["Ruth McClendon", "D", "San Antonio", "120"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 last representative on the table?
Justin Rodriguez
Answer:
128
Table InputTable: [["Rank", "Island", "Area\\n(kmΒ²)", "Area\\n(sq mi)", "Country/Countries/Region"], ["220", "Sheppey", "94", "36", "United Kingdom"], ["243", "Ytre Vikna (outer island of Vikna archipelago)", "83", "32", "Norway"], ["268", "Guernsey", "63", "24", "Guernsey, British Crown dependency"], ["226", "Γ–ja (island)", "90", "35", "Finland"], ["298", "Sanday, Orkney", "50", "19", "United Kingdom"], ["217", "BorΓ°oy", "95", "37", "Faroe Islands, an autonomous region of Denmark"], ["275", "Bolshoy Berezovy (in Beryozovye Islands, Gulf of Finland)", "60", "23", "Russia"], ["273", "Graciosa Island", "62", "24", "Portugal"], ["247", "Tiree", "78", "30", "United Kingdom"], ["272", "Raasay", "62", "24", "United Kingdom"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 island of sheppey is 36 sq miles, what is the name of their country?
United Kingdom
Answer:
128
Table InputTable: [["Year", "Network", "Race caller", "Color commentator", "Reporters", "Trophy Presentation"], ["1953", "CBS", "Bryan Field", "Mel Allen", "Phil Sutterfield", "Phil Sutterfield"], ["1952", "CBS", "Bryan Field", "Sam Renick", "", ""], ["1956", "CBS", "Fred Capossela", "Bryan Field", "", ""], ["1954", "CBS", "Bryan Field", "Mel Allen", "", "Bill Corum"], ["1959", "CBS", "Fred Capossela", "Bryan Field and Chris Schenkel", "", "Chris Schenkel"], ["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:what is the total number of times bryan field was the sole color commentator?
3
Answer:
128
Table InputTable: [["Year", "Song", "US Hot 100", "U.S. Modern Rock", "U.S. Mainstream Rock", "Album"], ["1998", "\"The Sick\"", "-", "-", "-", "An Audio Guide To Everyday Atrocity"], ["1997", "\"One Thing\"", "-", "-", "-", "Pacifier"], ["2003", "\"Ether\"", "-", "-", "-", "Skeletons"], ["1998", "\"Breathe Out\"", "-", "-", "-", "An Audio Guide To Everyday Atrocity"], ["2001", "\"Bleeder\"", "-", "-", "32", "Violence"], ["1997", "\"Defaced\"", "-", "-", "-", "Pacifier"], ["1997", "\"Pacifier\"", "-", "-", "-", "Pacifier"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:which song was on the us mainstream rock charts the most?--"one thing" or "the sick"?
"Bleeder"
Answer:
128
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2004", "17", "112", "–", "–", "51", "–", "β€”"], ["2005", "18", "37", "–", "27", "18", "49", "β€”"], ["2006", "19", "22", "–", "18", "37", "15", "β€”"], ["2011", "24", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete"], ["2007", "20", "33", "–", "50", "15", "23", "β€”"], ["2008", "21", "38", "–", "–", "35", "13", "β€”"], ["2013", "26", "37", "–", "17", "28", "30", "β€”"], ["2009", "22", "9", "–", "40", "2", "5", "50"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "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 highest overall standing that she achieved?
112
Answer:
128
Table InputTable: [["Year", "Film", "Role", "Language", "Notes"], ["2008", "Moggina Manasu", "Chanchala", "Kannada", "Filmfare Award for Best Actress - Kannada\\nKarnataka State Film Award for Best Actress"], ["2012", "Addhuri", "Poorna", "Kannada", "Udaya Award for Best Actress\\nNominated β€” SIIMA Award for Best Actress\\nNominated β€” Filmfare Award for Best Actress – Kannada"], ["2011", "Hudugaru", "Gayithri", "Kannada", "Nominated, Filmfare Award for Best Actress – Kannada"], ["2010", "Krishnan Love Story", "Geetha", "Kannada", "Filmfare Award for Best Actress - Kannada\\nUdaya Award for Best Actress"], ["2009", "Love Guru", "Kushi", "Kannada", "Filmfare Award for Best Actress - Kannada"], ["2009", "Olave Jeevana Lekkachaara", "Rukmini", "Kannada", "Innovative Film Award for Best Actress"], ["2013", "Bahaddoor", "Anjali", "Kannada", "Filming"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what was the first movie that won the filmfare award for best actress?
Moggina Manasu
Answer:
128
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["5", "July 8", "Watkins Glen‑", "Hal Shaw, Jr.\\n Monte Shelton", "Porsche 935", "Brian Fuerstenau\\n Bob Tullius", "Jaguar XJS"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["8", "September 4", "Road America", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["4", "June 25", "Mont-Tremblant", "Monte Sheldon", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["3", "June 11", "Portland", "Tuck Thomas", "Chevrolet Monza", "Bob Matkowitch", "Chevrolet Corvette"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:are there at least 11 rounds?
no
Answer:
128
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "Soviet Union", "*7*", "3", "6", "16"], ["7", "Norway", "2", "1", "1", "4"], ["5", "Sweden", "2", "4", "4", "10"], ["4", "Switzerland", "3", "2", "1", "6"], ["3", "Finland", "3", "3", "1", "7"], ["2", "Austria", "4", "3", "4", "11"], ["9", "Germany", "1", "0", "1", "2"], ["8", "Italy", "1", "2", "0", "3"], ["10", "Canada", "0", "1", "2", "3"], ["6", "United States", "2", "3", "2", "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:how many nations participated in the 1956 winter olympic games?
10
Answer:
128
Table InputTable: [["Year", "Competition", "Venue", "Position", "Notes"], ["1999", "World Youth Championships", "Bydgoszcz, Poland", "13th (q)", "4.60 m"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "13th (q)", "5.20 m"], ["2001", "European Junior Championships", "Grosseto, Italy", "7th", "5.15 m"], ["2005", "European U23 Championships", "Erfurt, Germany", "7th", "5.50 m"], ["2006", "European Championships", "Gothenburg, Sweden", "5th", "5.65 m"], ["2012", "European Championships", "Helsinki, Finland", "–", "NM"], ["2005", "Universiade", "Izmir, Turkey", "5th", "5.50 m"], ["2010", "European Championships", "Barcelona, Spain", "3rd", "5.75 m"], ["2006", "World Indoor Championships", "Moscow, Russia", "10th (q)", "5.65 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:what year did poland achieve its highest position?
2010
Answer:
128
Table InputTable: [["Speed", "Date", "Country", "Train", "Arr.", "Power", "State", "Comments"], ["202.6Β km/h (126Β mph)", "1938-07-03", "UK", "LNER Class A4 No. 4468 Mallard", "Loc", "Steam", "Unkn.", "Downhill grade. Data indicates peak speed 202.6Β km/h (126Β mph), mean speed (half-mile) 201.2Β km/h (125Β mph). Mallard suffered an overheated crankpin during the run, but was repaired and returned to traffic within 9Β days."], ["164Β km/h (102Β mph)", "1904-05-09", "UK", "GWR 3700 Class 3440 City of Truro", "Loc", "Steam", "Unmod.", "Claimed[by whom?] to be the first steam locomotive to reach100Β mph (161Β km/h).[citation needed]"], ["161Β km/h (100Β mph)", "1934-11-30", "UK", "LNER Class A3 4472 Flying Scotsman", "Loc", "Steam", "Unmod.", "In 1934, Flying Scotsman achieved the first authenticated 100Β mph (161Β km/h) by a steam locomotive."]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 km/h did the train lner class a4 no. 4468 mallard travel?
202.6 km/h
Answer:
128
Table InputTable: [["District", "Incumbent", "Party", "First\\nelected", "Result", "Candidates"], ["Maryland 7", "Elijah Cummings", "Democratic", "1996", "Re-elected", "Elijah Cummings (D) 73.53%\\nJoseph Ward (R) 26.38%"], ["Maryland 5", "Steny Hoyer", "Democratic", "1981", "Re-elected", "Steny Hoyer (D) 69.27%\\nJoseph Crawford (R) 30.52%"], ["Maryland 6", "Roscoe Bartlett", "Republican", "1992", "Re-elected", "Roscoe Bartlett (R) 66.11%\\nDonald DeArmon (D) 33.80%"], ["Maryland 3", "Ben Cardin", "Democratic", "1986", "Re-elected", "Ben Cardin (D) 65.72%\\nScott Conwell (R) 34.18%"], ["Maryland 1", "Wayne Gilchrest", "Republican", "1990", "Re-elected", "Wayne Gilchrest (R) 76.67%\\nAnn Tamlyn (D) 23.16%"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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:congressmen re-elected with at least 60% of the vote
Wayne Gilchrest, Ben Cardin, Albert Wynn, Steny Hoyer, Roscoe Bartlett, Elijah Cummings
Answer:
128
Table InputTable: [["Rank", "Name", "Nationality", "Time", "Notes", "Points"], ["2", "Jeff Lastennet", "France", "1:46.70", "", "11"], ["3", "Gareth Warburton", "Great Britain", "1:46.95", "SB", "10"], ["8", "Robin Schembera", "Germany", "1:47.79", "", "5"], ["4", "Mario Scapini", "Italy", "1:47.20", "PB", "9"], ["12", "Milan Kocourek", "Czech Republic", "1:59.28", "", "1"], ["9", "Ivan Tukhtachev", "Russia", "1:48.27", "SB", "4"], ["1", "Adam Kszczot", "Poland", "1:46.50", "", "12"], ["11", "AntΓ³nio Rodrigues", "Portugal", "1:50.45", "", "2"], ["10", "Antonio Manuel Reina", "Spain", "1:48.56", "", "3"], ["7", "Joni Jaako", "Sweden", "1:47.61", "SB", "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 long did it take jeff lastennet to finish?
1:46.70
Answer:
128
Table InputTable: [["Pos", "No.", "Driver", "Team", "Engine", "Laps", "Time/Retired", "Grid", "Laps Led", "Points"], ["1", "2", "Ryan Briscoe", "Team Penske", "Chevrolet", "85", "2:07:02.8248", "2", "27", "50"], ["18", "28", "Ryan Hunter-Reay", "Andretti Autosport", "Chevrolet", "84", "+ 1 lap", "7", "1", "12"], ["15", "17", "SebastiΓ‘n Saavedra", "Andretti Autosport", "Chevrolet", "84", "+ 1 lap", "23", "0", "15"], ["13", "9", "Scott Dixon", "Chip Ganassi Racing", "Honda", "84", "+ 1 lap", "5", "0", "17"], ["21", "83", "Charlie Kimball", "Chip Ganassi Racing", "Honda", "82", "+ 3 laps", "21", "0", "12"], ["25", "26", "Marco Andretti", "Andretti Autosport", "Chevrolet", "46", "Mechanical", "12", "0", "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:how long did it take ryan briscoe to finish the 2012 gopro indy grand prix of sonoma?
2:07:02.8248
Answer:
128
Table InputTable: [["Match Day", "Date", "Opponent", "H/A", "Score", "Aberdeen Scorer(s)", "Attendance"], ["34", "20 March", "Airdrieonians", "H", "3–0", "Brewster, Cail, Main", "5,500"], ["31", "27 February", "Third Lanark", "A", "1–0", "Walker", "5,000"], ["20", "19 December", "Kilmarnock", "H", "3–0", "MacLachlan, Cail, Main", "4,000"], ["5", "12 September", "Ayr United", "A", "0–1", "", "2,000"], ["2", "22 August", "Rangers", "H", "0–2", "", "15,000"], ["30", "20 February", "Hibernian", "H", "0–0", "", "8,500"], ["29", "13 February", "St. Mirren", "A", "2–0", "Cail, Walker", "3,000"], ["24", "9 January", "Ayr United", "H", "1–1", "Cail", "4,500"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:in how many games did the team score at least 3 goals?
4
Answer:
128
Table InputTable: [["Rank", "Diver", "Preliminary\\nPoints", "Preliminary\\nRank", "Final\\nPoints"], ["11", "Anita RossingΒ (SWE)", "464.58", "7", "424.98"], ["19", "Alison ChildsΒ (GBR)", "400.68", "19", ""], ["23", "Angela RibeiroΒ (BRA)", "370.68", "23", ""], ["24", "Rim HassanΒ (EGY)", "258.63", "24", ""], ["18", "Valerie McFarland-BeddoeΒ (AUS)", "401.13", "18", ""], ["", "Christina SeufertΒ (USA)", "481.41", "5", "517.62"], ["20", "Kerstin FinkeΒ (FRG)", "393.93", "20", ""], ["21", "Nicole KreilΒ (AUT)", "382.68", "21", ""], ["13", "Ann FargherΒ (NZL)", "421.65", "13", ""], ["15", "Antonette WilkenΒ (ZIM)", "414.66", "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:what was the average score of the gold, silver, and bronze medalists?
525.26
Answer:
128
Table InputTable: [["Year", "Kit Manufacturer", "Shirt Sponsor", "Back of Shirt Sponsor", "Short Sponsor"], ["1995–1996", "Matchwinner", "Empress", "", ""], ["1982–1985", "Umbro", "", "", ""], ["1986–1988", "Henson", "Duraflex", "", ""], ["1985–1986", "Umbro", "Whitbread", "", ""], ["1977–1978", "", "National Express", "", ""], ["2004–2008", "Errea", "Bence Building Merchants", "", ""], ["1991–1993", "Technik", "Gulf Oil", "", ""], ["1994–1995", "KlΕ«b Sport", "Empress", "", ""], ["1993–1994", "Club Sport", "Gulf Oil", "", ""], ["1988–1989", "", "Gulf Oil", "", ""], ["1999–2004", "Errea", "Towergate Insurance", "", ""], ["1997–1999", "Errea", "Endsleigh Insurance", "", ""], ["2009–2011", "Errea", "Mira Showers", "PSU Technology Group", ""]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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:during what time period was there no shirt sponsers?
1982-1985
Answer:
128
Table InputTable: [["Clerk", "Started", "Finished", "School (year)", "Previous clerkship"], ["Jerome B. Libin", "1959", "1960", "Michigan (1959)", "none"], ["Patrick F. McCartan", "1959", "1960", "Notre Dame (1959)", "none"], ["Heywood H. Davis", "1958", "1959", "Kansas (1958)", "none"], ["William C. Canby, Jr.", "1958", "1959", "Minnesota (1956)", "none"], ["Kenneth W. Dam", "1957", "1958", "Chicago (1957)", "none"], ["Alan C. Kohn", "1957", "1958", "Wash U (1955)", "none"], ["D. Lawrence Gunnels", "1961", "1962", "Wash U (1960)", "none"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 law clerk after jerome b. libin and patrick f. mccartan served as clerks?
D. Lawrence Gunnels
Answer:
128
Table InputTable: [["Hand", "Auto", "Wind", "Athlete", "Nationality", "Birthdate", "Location", "Date"], ["", "10.90", "", "Thaddeus Bell", "United States", "28.11.1942", "Raleigh", "01.05.1988"], ["10.7", "", "", "Klaus JΓΌrgen Schneider", "Germany", "02.03.1942", "Stuttgart", "07.07.1982"], ["", "10.95", "", "Karl Heinz SchrΓΆder", "Germany", "17.06.1939", "Hannover", "28.07.1979"], ["", "10.84", "1.8", "Erik Oostweegel", "Netherlands", "29.04.1960", "Tilburg", "10.06.2000"], ["", "10.93", "0.6", "Gilles Echevin", "France", "01.09.1948", "Grenoble", "07.05.1989"], ["10.7", "", "", "Walt Butler", "United States", "21.03.1941", "Northridge", "16.05.1981"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 older, thaddeus bell or klaus jΓΌrgen schneider?
Klaus JΓΌrgen Schneider
Answer:
128
Table InputTable: [["Competition", "Total spectatorship", "Average match attendance", "Year"], ["State of Origin series", "186,607", "62,202", "2011"], ["Rugby Championship", "133,532", "44,511", "2012"], ["Super Rugby", "773,940", "19,348", "2012"], ["National Rugby League", "3,345,248", "16,643", "2013"], ["Australian Football League", "6,931,085", "33,484", "2013"], ["Big Bash League", "550,262", "17,750", "2011/2012"], ["A-League", "1,772,133", "12,707", "2012/2013"], ["Women's National Basketball League", "77,944", "", "2010/2011"], ["National Basketball League", "547,021", "4,031", "2010/2011"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 had more spectators? rugby championship or state or origin series?
State of Origin series
Answer:
128
Table InputTable: [["Season", "Competition", "Round", "Club", "Home", "Away"], ["2012–13", "UEFA Europa League", "1QR", "Budapest HonvΓ©d", "0–1", "0–2"], ["", "", "2QR", "FK Jablonec 97", "0–2", "1–5"], ["2009–10", "UEFA Europa League", "2QR", "Motherwell", "1–0", "1–8"], ["1996–97", "UEFA Cup Winners' Cup", "QR", "HumennΓ©", "0–2", "0–1"], ["2011–12", "UEFA Europa League", "1QR", "FK BuduΔ‡nost", "1–2", "3–1"], ["1986–87", "UEFA Cup", "1R", "FC Barcelona", "1–1", "0–0"], ["1987–88", "UEFA Cup", "2R", "Wismut Aue", "2–0", "0–1"], ["1987–88", "UEFA Cup", "1/16", "FC Barcelona", "1–0", "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:what was the last season played?
2012-13
Answer:
128
Table InputTable: [["Date", "Festival", "Location", "Awards", "Link"], ["Sep 16", "Athens International Film Festival", "Athens, Attica\\nΒ Greece", "Best Director", "aiff.gr"], ["Sep 19", "Lund International Fantastic Film Festival", "Lund, SkΓ₯ne\\nΒ Sweden", "", "fff.se"], ["Oct 9", "London Int. Festival of Science Fiction Film", "London, England\\nΒ UK", "Closing Night Film", "Sci-Fi London"], ["Feb 2–5, Feb 11", "Santa Barbara International Film Festival", "Santa Barbara, California Β USA", "Top 11 \"Best of the Fest\" Selection", "sbiff.org"], ["Oct 9, Oct 11", "Sitges Film Festival", "Sitges, Catalonia\\nΒ Spain", "", "Sitges Festival"], ["May 21–22, Jun 11", "Seattle International Film Festival", "Seattle, Washington Β USA", "", "siff.net"], ["Nov 12, Nov 18", "Indonesia Fantastic Film Festival", "Jakarta, Bandung\\nΒ Indonesia", "", "inaff.com"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 awards this film won?
4
Answer:
128
Table InputTable: [["No.", "Date", "Tournament", "Surface", "Partnering", "Opponent in the final", "Score"], ["7.", "August 26, 2012", "Ecuador F3", "Clay", "Sergio GaldΓ³s", "Mauricio EchazΓΊ\\n Guillermo Rivera-ArΓ‘nguiz", "6-2, 6-1"], ["1.", "September 13, 2010", "Ecuador F2", "Hard", "Roberto Quiroz", "Peter Aarts\\n Christopher Racz", "6–4, 6–4"], ["6.", "August 20, 2012", "Colombia F2", "Clay", "Ariel Behar", "Nicolas Barrientos\\n Michael Quintero", "2-1 Ret."], ["2.", "April 4, 2011", "Chile F2", "Clay", "Sergio GaldΓ³s", "Guillermo HormazΓ‘bal\\n Rodrigo PΓ©rez", "5–7, 7–6(5), [10–5]"], ["10.", "May 27, 2013", "Argentina F8", "Clay", "Sergio GaldΓ³s", "Daniel Dutra da Silva\\n Pablo GaldΓ³n", "6-0, 7-5"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "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 tournament comes after ecuador f2?
Chile F2
Answer:
128
Table InputTable: [["Common name", "Binomial nomenclature", "Colour", "Density ΒΉ", "Location", "Characteristics, Usage and Status"], ["Deodar", "Cedrus deodara", "Yellowish brown", "560Β kg/mΒ³", "Himalayas, Punjab, Uttar Pradesh", "Deodar is the most important timber tree providing soft wood. It can be easily worked and it is moderately strong. It possesses distinct annual rings. It is used for making cheap furniture, railway carriages, railway sleepers, packing boxes, structural work and so forth."], ["Axlewood", "Anogeissus latifolia", "", "930Β kg/mΒ³", "Andhra Pradesh, Tamil Nadu, Maharashtra, Madhya Pradesh, Bihar, Uttar Pradesh", "It is very strong, hard and tough. It takes a smooth finish. It is subject to cracking."], ["Tamarind", "Tamarindus indica", "Dark brown", "1280Β kg/mΒ³[citation needed]", "All over India", "Tamarind is knotty and durable. It is a beautiful tree for avenue and gardens. Its development is very slow but it ultimately forms a massive appearance. Its fruit is also very useful. It is used for agricultural instruments, well curbs, sugar mills, carts and brick burning."]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 tree is the most dense in india?
Tamarind
Answer:
128
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["8", "China", "–", "–", "1", "1"], ["7", "Russia", "–", "1", "1", "2"], ["6", "Italy", "–", "2", "1", "3"], ["1", "Netherlands", "8", "3", "1", "12"], ["2", "Australia", "3", "3", "4", "10"], ["5", "Canada", "1", "–", "3", "4"], ["3", "United States", "2", "5", "1", "8"], ["4", "Hungary", "1", "1", "3", "5"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "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 at the top of the list?
Netherlands
Answer:
128
Table InputTable: [["Num", "Pod Color", "Nickname", "Short Description", "Episode"], ["071", "Yellow", "Penny", "Seen in pod form in Stitch! The Movie. Pod says 71 instead of 071. Function unknown.", "Leroy & Stitch"], ["078", "White", "Snozzle", "Seen in pod form in Stitch! The Movie. Pod says 78 instead of 078. Function unknown.", "Leroy & Stitch"], ["019", "White", "Clumsy", "Seen in pod form in Stitch! The Movie. Pod says 19 instead of 019. Function unknown.", "Leroy & Stitch"], ["070", "White", "Flapjack", "Seen in pod form in Stitch! The Movie. Function unknown. Pod says 70 instead of 070.", "Stitch! The Movie"], ["094", "White", "Louis B.", "Seen in pod form in Stitch! The Movie. Function unknown. Pod says 94 instead of 094.", "Stitch! The Movie"], ["082", "White", "Plunge", "Seen in pod form in Stitch! The Movie. Function unknown. Pod says 82 instead of 082.", "Stitch! The Movie"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what was the first pod color in the list of leroy & stitch episode?
Blue
Answer:
128
Table InputTable: [["Name", "Owner", "Location", "Notes", "Transmission", "Website"], ["Radio 24", "Il Sole 24 Ore", "Milan", "Commercial; News/Talk", "FM, DAB, DVB-S", "http://www.radio24.it"], ["RadioRadio", "", "Rome", "Local; News/Talk", "DAB, DVB-S", "http://www.radioradio.it"], ["Radio Monte Carlo", "Gruppo Finelco", "Milan", "Commercial; It is also called RMC", "FM, DVB-S", "http://www.radiomontecarlo.net"], ["Radio Italia Solo Musica Italiana", "Gruppo Radio Italia", "Milan", "Commercial; Italian Hits", "FM, DAB, DVB-S", "http://www.radioitalia.it"], ["Radio Radicale", "Radical Party", "Rome", "Community; News/Talk", "FM, DAB, DVB-S", "http://www.radioradicale.it"], ["Radio Dimensione Suono", "", "Rome", "Commercial; It is also called RDS", "FM, DAB, DAB+, DVB-S", "http://www.rds.it"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 radio stations are located in rome than in milan?
3
Answer:
128
Table InputTable: [["Contestant", "Original Tribe", "Switched Tribe", "Merged Tribe", "Finish", "Total Votes"], ["Aleksandr Pashutin\\n60.the actor", "Barracudas", "", "", "3rd Voted Out\\nDay 9", "7"], ["Kris Kelmi\\n47.the singer", "Barracudas", "", "", "2nd Voted Out\\nDay 6", "1"], ["Aleksandr Lykov\\n41.the actor", "Barracudas", "Barracudas", "Crocodiles", "13th Voted Out\\n8th Jury Member\\nDay 37", "6"], ["Aleksandr Byalko\\n50.the physicist", "Pelicans", "Barracudas", "", "5th Voted Out\\nDay 15", "6"], ["Ivar Kalnynsh\\n54.the actor", "", "", "Crocodiles", "10th Voted Out\\n5th Jury Member\\nDay 30", "3"], ["Larisa Verbitskaya\\n43.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "12th Voted Out\\n7th Jury Member\\nDay 36", "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:who had the most total votes?
Larisa Verbitskaya 43.the TV presenter
Answer:
128
Table InputTable: [["Date", "Rnd", "Race Name", "Circuit", "City/Location", "Pole position", "Winning driver", "Winning team", "Report"], ["10", "August 5", "Marlboro 500", "Michigan International Speedway", "Brooklyn, Michigan", "Emerson Fittipaldi", "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"], ["11", "August 26", "Texaco/Havoline Grand Prix of Denver", "Streets of Denver", "Denver, Colorado", "Teo Fabi", "Al Unser, Jr.", "Galles-Kraco Racing", "Report"], ["12", "September 2", "Molson Indy Vancouver", "Streets of Vancouver", "Vancouver, British Columbia", "Michael Andretti", "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"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 galles-kraco racing have more/less than 10 wins in the season?
less
Answer:
128
Table InputTable: [["Year", "Chassis", "Engine", "Start", "Finish", "Team"], ["2006", "Dallara", "Honda", "2", "25", "Team Penske"], ["2005", "Dallara", "Toyota", "5", "9", "Team Penske"], ["2007", "Dallara", "Honda", "1", "3", "Team Penske"], ["2009", "Dallara", "Honda", "1", "1", "Team Penske"], ["2008", "Dallara", "Honda", "4", "4", "Team Penske"], ["2003", "Dallara", "Toyota", "1", "2", "Team Penske"], ["2010", "Dallara", "Honda", "1", "9", "Team Penske"], ["2011", "Dallara", "Honda", "16", "17", "Team Penske"], ["2004", "Dallara", "Toyota", "8", "9", "Team Penske"], ["2001", "Dallara", "Oldsmobile", "11", "1", "Team Penske"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "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 was honda used in a row after 2005?
6
Answer:
128
Table InputTable: [["Ship", "Type of Vessel", "Lake", "Location", "Lives lost"], ["Leafield", "Steamer", "Lake Superior", "", "all hands"], ["Plymouth", "Barge", "Lake Michigan", "", "7 lost"], ["Henry B. Smith", "Steamer", "Lake Superior", "", "all hands"], ["Lightship No. 82", "Lightship", "Lake Erie", "Point Albino (near Buffalo)", "6 lost"], ["Hydrus", "Steamer", "Lake Huron", "near Lexington, Michigan", "28 lost"], ["Argus", "Steamer", "Lake Huron", "25 miles off Kincardine, Ontario", "25 lost"], ["Charles S. Price", "Steamer", "Lake Huron", "near Port Huron, Michigan", "28 lost"], ["Regina", "Steamer", "Lake Huron", "near Harbor Beach, Michigan", ""], ["James Carruthers", "Steamer", "Lake Huron", "near Kincardine", "18 lost"], ["Issac M. Scott", "Steamer", "Lake Huron", "near Port Elgin, Ontario", "28 lost"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 type of vessel is the last ship?
Lightship
Answer:
128
Table InputTable: [["Hull", "Type", "Original Name", "Original Operator", "Delivery", "Disposition (2012)", "2nd name", "2nd operator", "3rd Name", "3rd operator"], ["β„– 7", "929-117", "Unicorn", "Kyusyu Shosen Co. Ltd.", "Oct 1990", "Active", "Pegasus 2", "Kyusyu Shosen Co. Ltd.", "", ""], ["β„– 2", "929-117", "Pegasus", "Kyusyu Shosen Co. Ltd.", "Jun 1989", "Active", "Toppy 1", "Tane Yaku Jetfoils", "", ""], ["β„– 4", "929-117", "Princess Dacil", "Trasmediterranea", "Mar 1990", "Active", "Pegasus", "Kyusyu Shosen Co. Ltd.", "", ""], ["β„– 8", "929-117", "Beetle 2", "JR Kyushu Jet Ferries", "Feb 1991", "Active", "", "", "", ""], ["β„– 12", "929-117", "Toppy 2", "Tane Yaku Jetfoils", "Apr 1992", "Active", "", "", "", ""]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 second operator to work on the pegasus
Tane Yaku Jetfoils
Answer:
128
Table InputTable: [["Date", "Opponent#", "Rank#", "Site", "TV", "Result", "Attendance"], ["September 17", "atΒ Arkansas", "#12", "Razorback Stadium β€’ Fayetteville, AR", "ABC", "WΒ 13–6", "52,089"], ["November 19", "#6Β Auburn", "#4", "Legion Field β€’ Birmingham, AL (Iron Bowl)", "ABC", "WΒ 21–14", "83,091"], ["January 2, 1995", "vs.Β #13Β Ohio State*", "#6", "Citrus Bowl β€’ Orlando, FL (Florida Citrus Bowl)", "ABC", "WΒ 24–17", "71,195"], ["October 22", "Ole Miss", "#8", "Bryant–Denny Stadium β€’ Tuscaloosa, AL (Rivalry)", "ABC", "WΒ 21–10", "70,123"], ["November 12", "atΒ #20Β Mississippi State", "#6", "Scott Field β€’ Starkville, MS (Rivalry)", "ABC", "WΒ 29–25", "41,358"], ["December 3", "vs.Β #6Β Florida", "#3", "Georgia Dome β€’ Atlanta, GA (SEC Championship Game)", "ABC", "LΒ 23–24", "74,751"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 played on abc?
6
Answer:
128
Table InputTable: [["Competition", "Total spectatorship", "Average match attendance", "Year"], ["Super Rugby", "773,940", "19,348", "2012"], ["National Rugby League", "3,345,248", "16,643", "2013"], ["Rugby Championship", "133,532", "44,511", "2012"], ["Australian Football League", "6,931,085", "33,484", "2013"], ["Big Bash League", "550,262", "17,750", "2011/2012"], ["A-League", "1,772,133", "12,707", "2012/2013"], ["State of Origin series", "186,607", "62,202", "2011"], ["National Basketball League", "547,021", "4,031", "2010/2011"], ["Women's National Basketball League", "77,944", "", "2010/2011"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 has more average match attendance, super rugby or national rugby league?
Super Rugby
Answer:
128
Table InputTable: [["Pos", "Name", "Team", "Laps", "Time/Retired", "Grid", "Points"], ["11", "Dan Clarke", "Minardi Team USA", "69", "+38.903", "10", "11"], ["6", "Simon Pagenaud", "Team Australia", "69", "+22.698", "5", "19"], ["13", "Robert Doornbos", "Minardi Team USA", "69", "+1:00.638", "9", "8"], ["1", "Justin Wilson", "RuSPORT", "69", "1:46:02.236", "2", "32"], ["2", "Jan Heylen", "Conquest Racing", "69", "+7.227", "7", "27"], ["3", "Bruno Junqueira", "Dale Coyne Racing", "69", "+8.419", "11", "26"], ["14", "Will Power", "Team Australia", "69", "+1:01.204", "8", "7"], ["15", "Alex Tagliani", "Rocketsports", "68", "+ 1 Lap", "12", "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:who placed last?
Paul Tracy
Answer:
128
Table InputTable: [["Rank", "Player Name", "No. of Titles", "Runner-up", "Final Appearances"], ["9", "Thierry Lincou", "1", "1", "2"], ["12", "Rodney Martin", "1", "0", "1"], ["1", "Jansher Khan", "8", "1", "9"], ["17", "James Willstrop", "0", "1", "1"], ["3", "Geoff Hunt", "4", "1", "5"], ["8", "Peter Nicol", "1", "2", "3"], ["9", "Rodney Eyles", "1", "1", "2"], ["17", "Lee Beachill", "0", "1", "1"], ["17", "Mohamed El Shorbagy", "0", "1", "1"], ["17", "Ahmed Barada", "0", "1", "1"], ["17", "Peter Marshall", "0", "1", "1"], ["14", "Chris Dittmar", "0", "5", "5"], ["2", "Jahangir Khan", "6", "3", "9"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 player has the most titles?
Jansher Khan
Answer:
128
Table InputTable: [["Rank", "Pair", "Country", "Athletes", "Time", "Deficit"], ["5", "1", "Norway", "Sverre Lunde Pedersen\\nHΓ₯vard BΓΈkko\\nKristian Reistad Fredriksen", "3:46.33", "+4.90"], ["6", "3", "Germany", "Patrick Beckert\\nMarco Weber\\nRobert Lehmann", "3:46.48", "+5.05"], ["", "3", "Netherlands", "Sven Kramer\\nKoen Verweij\\nJan Blokhuijsen", "3:41.43", ""], ["", "2", "Russia", "Ivan Skobrev\\nDenis Yuskov\\nYevgeny Lalenkov", "3:43.62", "+2.19"], ["8", "2", "Poland", "Zbigniew BrΓ³dka\\nKonrad NiedΕΊwiedzki\\nJan SzymaΕ„ski", "3:47.72", "+6.29"], ["7", "4", "South Korea", "Lee Seung-hoon\\nJoo Hyong-jun\\nKo Byung-wook", "3:47.18", "+5.75"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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:norway finished 5th. who was the previous team that finished?
Canada
Answer:
128
Table InputTable: [["Date", "Venue", "Opponent", "Result", "Scoreline", "China scorers"], ["Dec 17", "Muscat", "Oman", "Lost", "1-3", "Qu Bo 58'"], ["Dec 19", "Muscat", "Iran", "Lost", "0-2", ""], ["March 15", "Kunming", "Thailand", "Drawn", "3-3", "Qu Bo 34'\\nHan Peng 67'\\nZhu Ting 90'"], ["April 23", "Los Angeles", "El Salvador", "Drawn", "2-2", "Xiao Zhanbo 62' pen\\nQu Bo 63'"], ["January 20", "Zhongshan", "Lebanon", "Drawn", "0-0", "β€”"], ["January 10", "Dubai", "United Arab Emirates", "Drawn", "0-0", "β€”"], ["January 27", "Zhongshan", "Syria", "Won", "2-1", "Qu Bo 64'\\nZhu Ting 90'"], ["April 16", "Seattle", "Mexico", "Lost", "0-1", "β€”"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 dates are there?
10
Answer:
128
Table InputTable: [["Pos", "Rider", "Manufacturer", "Time/Retired", "Points"], ["12", "Sebastian Porto", "Yamaha", "+27.054", "4"], ["11", "Alex Hofmann", "TSR-Honda", "+26.933", "5"], ["Ret", "Roberto Rolfo", "Aprilia", "Retirement", ""], ["23", "Arno Visscher", "Aprilia", "+1:40.635", ""], ["2", "Valentino Rossi", "Aprilia", "+0.180", "20"], ["7", "Franco Battaini", "Aprilia", "+20.889", "9"], ["22", "Rudie Markink", "Aprilia", "+1:40.280", ""], ["Ret", "Marcellino Lucchi", "Aprilia", "Retirement", ""], ["24", "Henk Van De Lagemaat", "Honda", "+1 Lap", ""], ["8", "Stefano Perugini", "Honda", "+20.891", "8"], ["6", "Ralf Waldmann", "Aprilia", "+7.019", "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:who finished sooner, hofmann or porto?
Alex Hofmann
Answer:
128
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2006", "Lusophony Games", "Macau", "1st", "800 m", "2:07.34"], ["2011", "All-Africa Games", "Maputo, Mozambique", "12th (h)", "800 m", "2:06.72"], ["2009", "Lusophony Games", "Lisbon, Portugal", "4th", "800 m", "2:07.48"], ["2007", "All-Africa Games", "Algiers, Algeria", "1st", "800 m", "2:02.83"], ["2003", "All-Africa Games", "Abuja, Nigeria", "11th (h)", "800 m", "2:05.19"], ["2009", "World Championships", "Berlin, Germany", "36th (h)", "800 m", "2:06.72"], ["2006", "Commonwealth Games", "Melbourne, Australia", "9th (sf)", "800 m", "2:01.84"], ["2006", "African Championships", "Bambous, Mauritius", "13th (h)", "800 m", "2:10.50"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:what is the first year?
2003
Answer:
128
Table InputTable: [["Represents", "Contestant", "Age", "Height", "Hometown"], ["DariΓ©n", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"], ["PanamΓ‘ Centro", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"], ["PanamΓ‘ Oeste", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"], ["ChiriquΓ­ Occidente", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"], ["Herrera", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"], ["PanamΓ‘ Este", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"], ["ChiriquΓ­", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"], ["Bocas del Toro", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"], ["Comarcas", "TBD", "TBD", "0.0Β m (0Β in)", "TBD"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 location is listed before darien?
ColΓ³n
Answer:
128
Table InputTable: [["No. in\\nseries", "No. in\\nseason", "Title", "Directed by", "Written by", "Original air date", "Prod.\\ncode"], ["26", "25", "\"My Mother, The Spy\"", "Richard Benedict", "Howard Gast", "MarchΒ 30,Β 1966", "125"], ["3", "1", "\"So Long, Patrick Henry\"", "Leo Penn", "Robert Culp", "SeptemberΒ 15,Β 1965", "101"], ["28", "27", "\"It's All Done with Mirrors\"", "Robert Butler", "Stephen Kandell", "AprilΒ 13,Β 1966", "127"], ["23", "23", "\"A Day Called 4 Jaguar\"", "Richard Sarafian", "Michael Zagar", "MarchΒ 9,Β 1966", "123"], ["4", "7", "\"Danny was a Million Laughs\"", "Mark Rydell", "Arthur Dales", "OctoberΒ 27,Β 1965", "107"], ["2", "3", "\"Carry Me Back to Old Tsing-Tao\"", "Mark Rydell", "David Karp", "SeptemberΒ 29,Β 1965", "103"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 writers wrote at least 3 "i spy" episodes?
3
Answer:
128
Table InputTable: [["Band", "Disc/Song", "Released", "Disc Description", "Disk Size", "Image"], ["Guns N' Roses", "Nightrain", "1989", "Shape of a suitcase", "7\"", ""], ["Guns N' Roses", "Paradise City", "1989", "Shape of a Colt \"Peacemaker\"", "7\"", ""], ["Guns N' Roses", "Sweet Child o' Mine", "1988", "Shape of the classic logo of the cross and skulls of the five band members", "7\"", ""], ["The Enemy", "You're not alone", "2007", "Square shaped. Has the single cover art on the A-side and a black and white picture of the band on the B-side with track listing.", "7\"", ""], ["Barnes & Barnes", "Fish Heads: Barnes & Barnes' Greatest Hits", "1982", "Shaped as a fish head", "12\"", ""], ["Monster Magnet", "Dopes to Infinity", "1995", "Shaped like the lead singer Dave Wyndorf's head.", "12\"", ""], ["The Coconuts (Side project of Kid Creole and the Coconuts)", "Did You Have To Love Me Like You Did", "1983", "In the shape of a coconut.", "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:how long was the time between the release of guns n' roses songs "sweet child o' mine" and "nightrain"?
1 year
Answer:
128
Table InputTable: [["Stage", "Date", "Route", "Terrain", "Length", "Winner", "Race leader"], ["2", "1 July", "Caen – Dinan", "Plain stage", "212Β km (132Β mi)", "Max BullaΒ (AUT)", "Max BullaΒ (AUT)"], ["9", "8 July", "Pau – Luchon", "Stage with mountain(s)", "231Β km (144Β mi)", "Antonin MagneΒ (FRA)", "Antonin MagneΒ (FRA)"], ["8", "7 July", "Bayonne – Pau", "Plain stage", "106Β km (66Β mi)", "Charles PΓ©lissierΒ (FRA)", "Charles PΓ©lissierΒ (FRA)"], ["5", "4 July", "Vannes – Les Sables d'Olonne", "Plain stage", "202Β km (126Β mi)", "Charles PΓ©lissierΒ (FRA)", "Charles PΓ©lissierΒ (FRA)\\nΒ Rafaele di PacoΒ (ITA)"], ["16", "18 July", "Gap – Grenoble", "Stage with mountain(s)", "102Β km (63Β mi)", "Charles PΓ©lissierΒ (FRA)", "Antonin MagneΒ (FRA)"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "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 caen-dinan route? (in miles)
132 mi
Answer:
128
Table InputTable: [["City", "County", "Population (2011)", "Population (2002)", "Altitude (m)", "Year status\\ngranted* or\\nfirst attested†"], ["Baia Mare", "MaramureΘ™", "123,738", "137,976", "225", "1329†"], ["Baia Sprie", "MaramureΘ™", "15,476", "15,735", "", ""], ["Bucharest", "-", "1,883,425", "1,926,334", "85", "1459†"], ["TopliΘ›a", "Harghita", "13,929", "16,839", "", "1956*"], ["Șomcuta Mare", "MaramureΘ™", "7,565", "7,708", "", "2004*"], ["BoldeΘ™ti-ScΔƒeni", "Prahova", "11,137", "11,505", "", ""], ["GΔƒeΘ™ti", "DΓ’mboviΘ›a", "13,317", "16,598", "", ""], ["Ungheni", "MureΘ™", "6,945", "6,554", "", "2004*"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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:city with the highest altitude with a population greater than 100,000
BraΘ™ov
Answer:
128
Table InputTable: [["Year", "Competition", "Venue", "Position", "Notes"], ["1999", "World Youth Championships", "Bydgoszcz, Poland", "12th", ""], ["2002", "World Junior Championships", "Kingston, Jamaica", "2nd", "63.91 m"], ["2009", "World Championships", "Berlin, Germany", "3rd", "74.79 m"], ["2001", "World Championships", "Edmonton, Canada", "23rd", "61.26 m"], ["2000", "World Junior Championships", "Santiago, Chile", "5th", ""], ["2001", "European Junior Championships", "Grosseto, Italy", "2nd", "61.97 m"], ["2007", "World Championships", "Osaka, Japan", "13th", "68.15 m"], ["2009", "World Athletics Final", "Thessaloniki, Greece", "3rd", "70.45 m"], ["2002", "European Championships", "Munich, Germany", "26th", "60.28 m"], ["2009", "World Student Games", "Belgrade, Serbia", "2nd", "72.85 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:what year did she receive her most recent highest rated position?
2012
Answer:
128
Table InputTable: [["Pos", "Name", "Team", "Laps", "Time/Retired", "Grid", "Points"], ["12", "Katherine Legge", "Dale Coyne Racing", "69", "+44.860", "14", "9"], ["3", "Bruno Junqueira", "Dale Coyne Racing", "69", "+8.419", "11", "26"], ["1", "Justin Wilson", "RuSPORT", "69", "1:46:02.236", "2", "32"], ["9", "Graham Rahal", "N/H/L Racing", "69", "+23.949", "6", "13"], ["7", "SΓ©bastien Bourdais", "N/H/L Racing", "69", "+22.955", "1", "18"], ["17", "Paul Tracy", "Forsythe Racing", "14", "Mechanical", "17", "4"], ["4", "Tristan Gommendy", "PKV Racing", "69", "+9.037", "3", "23"], ["10", "Ryan Dalziel", "Pacific Coast Motorsports", "69", "+29.554", "15", "11"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many drivers are from the united kingdom?
4
Answer:
128
Table InputTable: [["Place", "Player", "Country", "Score", "To par", "Money ($)"], ["T4", "Phil Mickelson", "United States", "68-70-72-74=284", "+4", "66,633"], ["1", "Corey Pavin", "United States", "72-69-71-68=280", "E", "350,000"], ["2", "Greg Norman", "Australia", "68-67-74-73=282", "+2", "207,000"], ["T10", "Frank Nobilo", "New Zealand", "72-72-70-71=285", "+5", "44,184"], ["T10", "Vijay Singh", "Fiji", "70-71-72-72=285", "+5", "44,184"], ["T10", "Bob Tway", "United States", "69-69-72-75=285", "+5", "44,184"], ["T4", "Jeff Maggert", "United States", "69-72-77-66=284", "+4", "66,633"], ["3", "Tom Lehman", "United States", "70-72-67-74=283", "+3", "131,974"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 number of players from the us and the number of players from every other country?
8
Answer:
128
Table InputTable: [["Hand", "Auto", "Wind", "Athlete", "Nationality", "Birthdate", "Location", "Date"], ["", "10.95", "", "George McNeill", "United Kingdom", "19.02.1947", "Melbourne", "31.11.1987"], ["", "10.90", "", "Thaddeus Bell", "United States", "28.11.1942", "Raleigh", "01.05.1988"], ["", "10.87", "", "Eddie Hart", "United States", "24.04.1949", "Eugene", "03.08.1989"], ["10.7", "", "", "Thane Baker", "United States", "04.10.1931", "Elkhart", "13.09.1972"], ["10.7", "", "", "Walt Butler", "United States", "21.03.1941", "Northridge", "16.05.1981"], ["", "10.60", "", "Bill Collins", "United States", "20.11.1950", "", "06.06.1992"], ["", "10.26", "2.3", "Troy Douglas", "Netherlands", "30.11.1962", "Utrecht", "10.07.2004"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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's auto score is the same as george mcneill?
Karl Heinz SchrΓΆder
Answer:
128
Table InputTable: [["Year", "Result", "Award", "Film"], ["2002", "Nominated", "ALMA Award Outstanding Actor in a Television Series", "Spin City"], ["2001", "Nominated", "ALMA Award Outstanding Actor in a Television Series", "Spin City"], ["2008", "Won", "ALMA Award Outstanding Actor in a Comedy Television Series", "Two and a Half Men"], ["2007", "Nominated", "Emmy Award for Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2008", "Nominated", "Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2006", "Nominated", "Emmy Award for Outstanding Lead Actor - Comedy Series", "Two and a Half Men"], ["2007", "Nominated", "Teen Choice Award Choice TV Actor: Comedy", "Two and a Half Men"], ["2002", "Nominated", "Kids' Choice Awards Favorite Television Actor", "Two and a Half Men"], ["2010", "Nominated", "SAG Award Outstanding Performance by a Male Actor in a Comedy Series", "Two and a Half Men"], ["2008", "Nominated", "Teen Choice Awards Choice TV Actor: Comedy", "Two and a Half Men"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 film had two consecutive nominations for the alma award outstanding actor in a television series?
Spin City
Answer:
128
Table InputTable: [["Match Day", "Date", "Opponent", "H/A", "Score", "Aberdeen Scorer(s)", "Attendance"], ["28", "6 February", "Morton", "H", "2–0", "Brewster, Archibald", "2,000"], ["4", "5 September", "Clyde", "H", "2–0", "MacLachlan, Archibald", "6,000"], ["2", "22 August", "Rangers", "H", "0–2", "", "15,000"], ["34", "20 March", "Airdrieonians", "H", "3–0", "Brewster, Cail, Main", "5,500"], ["30", "20 February", "Hibernian", "H", "0–0", "", "8,500"], ["32", "6 March", "Partick Thistle", "H", "0–0", "", "6,000"], ["19", "12 December", "Partick Thistle", "A", "0–3", "", "6,000"], ["31", "27 February", "Third Lanark", "A", "1–0", "Walker", "5,000"]]
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:how many games did archibald score a point this season?
3
Answer:
128
Table InputTable: [["Sl no", "Name of the prabandham", "Starting from", "Ending with", "Number of pasurams", "Sung by"], ["", "Total number of pasurams", "", "", "3776", ""], ["23", "Thiruvay Mozhi", "2674", "3776", "1102", "Nammalvar"], ["20", "Thiruvezhukkurrirukkai", "2672", "2672", "1", "Thirumangai alvar"], ["15", "Moonram Thiruvandhadhi", "2282", "2381", "100", "Peyalvar"], ["11", "Kurun Thandagam", "2032", "2051", "20", "Thirumangai alvar"], ["12", "Nedum Thandagam", "2052", "2081", "30", "Thirumangai alvar"], ["18", "Thiruvasiriyam", "2578", "2584", "7", "Nammalvar"], ["21", "Siriya Thirumadal", "2673", "2673", "1", "Thirumangai alvar"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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:thiruvay mozhi has the most pasurams at what number total?
1102
Answer:
128
Table InputTable: [["Date", "Time", "Opponent#", "Rank#", "Site", "TV", "Result", "Attendance"], ["September 8", "3:00 PM", "atΒ Oregon State*", "#13", "Reser Stadium β€’ Corvallis, OR", "FX", "LΒ 7–10", "42,189"], ["September 15", "7:00 PM", "Utah State*", "#22", "Camp Randall Stadium β€’ Madison, WI", "BTN", "WΒ 16–14", "79,332"], ["November 24", "2:30 PM", "atΒ Penn State", "", "Beaver Stadium β€’ University Park, PA", "ESPN2", "LΒ 21–24Β OT", "93,505"], ["December 1", "7:00 PM", "vs.Β #14Β Nebraska", "", "Lucas Oil Stadium β€’ Indianapolis, IN (Big Ten Championship Game)", "FOX", "WΒ 70–31", "41,260"], ["January 1, 2013", "4:10 PM", "vs.Β #8Β Stanford", "#23", "Rose Bowl β€’ Pasadena, CA (Rose Bowl)", "ESPN", "LΒ 14–20", "93,259"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 do they play before oregon state?
#9 (FCS) Northern Iowa*
Answer:
128
Table InputTable: [["Name", "Pennant", "Namesake", "Builder", "Ordered", "Laid down", "Launched", "Commissioned", "Fate"], ["Achilles", "70", "Achilles", "Cammell Laird", "16 February 1931", "11 June 1931", "1 September 1932", "24 March 1936", "Transferred to Royal New Zealand Navy as HMNZS Achilles 1941-1946\\nSold to Indian Navy as HIMS Delhi 1948"], ["Leander", "75", "Leander of Abydos", "HM Dockyard, Devonport", "18 February 1928", "1 August 1928", "13 July 1929", "23 July 1931", "Transferred to Royal New Zealand Navy as HMNZS Leander 1941-1945\\nBroken up at Blyth 1950"], ["Amphion", "29", "Amphion of Thebes", "HM Dockyard, Portsmouth", "1 December 1932", "22 June 1933", "27 July 1934", "15 June 1936", "Sold to Royal Australian Navy as HMAS Perth, 1939\\nSunk in torpedo attack, 1 March 1942"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 builder?
5
Answer:
128
Table InputTable: [["Thread\\nnominal size", "Outer diameter\\n[mm (in)]", "Threads per inch\\n(TPI)", "Pitch\\n[in (mm)]", "Inner diameter\\n[mm (in)]", "Cable diameter\\n[mm (in)]"], ["PG42", "54.0 (2.126)", "16", "0.0625 (1.5875)", "52.48 (2.066)", ""], ["PG7", "12.5 (0.492)", "20", "0.05 (1.270)", "11.28 (0.444)", "3 to 6.5 (0.118 to 0.256)"], ["PG48", "59.3 (2.335)", "16", "0.0625 (1.5875)", "57.78 (2.275)", ""], ["PG29", "37.0 (1.457)", "16", "0.0625 (1.5875)", "35.48 (1.397)", "18 to 25 (0.709 to 0.984)"], ["PG16", "22.5 (0.886)", "18", "0.05556 (1.4112)", "21.16 (0.833)", "10 to 14 (0.394 to 0.551)"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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:does a pg7 screw have a larger pitch than a pg16 screw?
no
Answer:
128
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2007", "Universiade", "Bangkok, Thailand", "1st", "400 m", ""], ["2001", "World Youth Championships", "Debrecen, Hungary", "4th", "400 m", ""], ["2006", "World Cup", "Athens, Greece", "7th", "400 m", ""], ["2006", "Asian Games", "Doha, Qatar", "1st", "400 m", ""], ["2011", "Universiade", "Shenzhen, China", "–", "400 m", "DQ"], ["2006", "Asian Games", "Doha, Qatar", "2nd", "4x400 m relay", ""], ["2005", "Asian Championships", "Incheon, South Korea", "2nd", "4x400 m relay", ""], ["2005", "Universiade", "Izmir, Turkey", "6th", "4x400 m relay", ""], ["2002", "Asian Games", "Busan, South Korea", "2nd", "4x400 m relay", ""]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:number of consecutive years she finished in top 10
3
Answer:
128
Table InputTable: [["Week", "Date", "Opponent", "Score", "Result", "Record"], ["9", "Oct 23", "at Hamilton Tiger-Cats", "25–17", "Loss", "1–10"], ["6", "Oct 2", "at Hamilton Tiger-Cats", "45–0", "Loss", "1–6"], ["5", "Sept 25", "vs. Hamilton Tiger-Cats", "38–12", "Loss", "1–5"], ["10", "Oct 30", "vs. Hamilton Tiger-Cats", "30–9", "Loss", "1–11"], ["11", "Nov 6", "at Toronto Argonauts", "18–12", "Loss", "1–12"], ["7", "Oct 11", "at Montreal Alouettes", "24–6", "Loss", "1–8"], ["1", "Aug 28", "at Toronto Argonauts", "13–6", "Loss", "0–1"], ["2", "Sept 4", "at Montreal Alouettes", "21–2", "Loss", "0–2"], ["4", "Sept 18", "vs. Toronto Argonauts", "34–6", "Loss", "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:what was the number of losses on the road?
6
Answer:
128
Table InputTable: [["Round", "Round", "Race", "Date", "Pole Position", "Fastest Lap", "Winning Club", "Winning Team", "Report"], ["2", "R2", "NΓΌrburgring", "September 21", "", "SC Corinthians", "PSV Eindhoven", "Azerti Motorsport", "Report"], ["4", "R2", "Estoril", "October 19", "", "Borussia Dortmund", "Al Ain", "Azerti Motorsport", "Report"], ["2", "R1", "NΓΌrburgring", "September 21", "A.C. Milan", "PSV Eindhoven", "A.C. Milan", "Scuderia Playteam", "Report"], ["5", "R1", "Vallelunga", "November 2", "Liverpool F.C.", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "Report"], ["6", "R2", "Jerez", "November 23", "", "Beijing Guoan", "Borussia Dortmund", "Zakspeed", "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:which race came first?
Donington Park
Answer:
128
Table InputTable: [["District", "Incumbent", "2008 Status", "Democratic", "Republican"], ["7", "Ed Perlmutter", "Re-election", "Ed Perlmutter", "John W. Lerew"], ["4", "Marilyn Musgrave", "Re-election", "Betsy Markey", "Marilyn Musgrave"], ["5", "Doug Lamborn", "Re-election", "Hal Bidlack", "Doug Lamborn"], ["3", "John Salazar", "Re-election", "John Salazar", "Wayne Wolf"], ["1", "Diana DeGette", "Re-election", "Diana DeGette", "George Lilly"], ["2", "Mark Udall", "Open", "Jared Polis", "Scott Starin"], ["6", "Tom Tancredo", "Open", "Hank Eng", "Mike Coffman"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 incumbents are on the table
7
Answer:
128
Table InputTable: [["Date", "Date", "", "Rank", "Tournament name", "Venue", "City", "Winner", "Runner-up", "Score"], ["12–09", "12–15", "GER", "WR", "German Open", "NAAFI", "OsnabrΓΌck", "Ronnie O'Sullivan", "Alain Robidoux", "9–7"], ["05–??", "05–??", "WAL", "", "Pontins Professional", "Pontins", "Prestatyn", "Martin Clark", "Andy Hicks", "9–7"], ["10–29", "11–10", "THA", "", "World Cup", "Amari Watergate Hotel", "Bangkok", "Scotland", "Ireland", "10–7"], ["11–15", "12–01", "ENG", "WR", "UK Championship", "Guild Hall", "Preston", "Stephen Hendry", "John Higgins", "10–9"], ["03–27", "04–05", "ENG", "WR", "British Open", "Plymouth Pavilions", "Plymouth", "Mark Williams", "Stephen Hendry", "9–2"]]
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:what is the number of german flags on this table?
1
Answer:
128
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2006", "Chengdu Wuniu", "China", "2", "1", "0"], ["2008", "Jiangsu Sainty", "China", "2", "24", "0"], ["2003", "Shandong Luneng", "China", "1", "4", "0"], ["2013", "Jiangsu Sainty", "China", "1", "11", "0"], ["2004", "Shandong Luneng", "China", "1", "0", "0"], ["2009", "Jiangsu Sainty", "China", "1", "15", "0"], ["2012", "Jiangsu Sainty", "China", "1", "0", "0"], ["2010", "Jiangsu Sainty", "China", "1", "17", "0"], ["2005", "Shandong Luneng", "China", "1", "0", "0"], ["2007", "Shandong Luneng", "China", "1", "0", "0"], ["2011", "Jiangsu Sainty", "China", "1", "9", "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 seasons did team chengdu wuniu have?
1
Answer:
128
Table InputTable: [["Year", "Division", "League", "Regular Season", "Playoffs", "Open Cup"], ["2013", "4", "USL PDL", "4th, Heartland", "Did not qualify", "Did not qualify"], ["2007", "4", "USL PDL", "3rd, Heartland", "Did not qualify", "1st Round"], ["2008", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["2012", "4", "USL PDL", "5th, Heartland", "Did not qualify", "Did not qualify"], ["2009", "4", "USL PDL", "6th, Heartland", "Did not qualify", "Did not qualify"], ["2006", "4", "USL PDL", "3rd, Heartland", "Did not qualify", "Did not qualify"], ["2005", "4", "USL PDL", "3rd, Heartland", "Did not qualify", "Did not qualify"], ["2004", "4", "USL PDL", "6th, Heartland", "Did not qualify", "Did not qualify"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:when was the last time the kansas city brass placed 4th in the regular season standings?
2013
Answer:
128
Table InputTable: [["Rank", "Player", "County", "Tally", "Total", "Opposition"], ["6", "Gary Kirby", "Limerick", "0–9", "9", "Antrim"], ["3", "Gary Kirby", "Limerick", "0–10", "10", "Tipperary"], ["6", "SeΓ‘n McLoughlin", "Westmeath", "1–6", "9", "Carlow"], ["6", "David Martin", "Meath", "1–6", "9", "Offaly"], ["3", "Gary Kirby", "Limerick", "1–7", "10", "Tipperary"], ["9", "Paul Flynn", "Waterford", "1–5", "8", "Tipperary"], ["9", "John Leahy", "Tipperary", "2–2", "8", "Kerry"], ["9", "John Byrne", "Carlow", "2–2", "8", "Westmeath"], ["3", "Kevin Broderick", "Galway", "3–1", "10", "New York"], ["2", "Niall English", "Carlow", "1–9", "12", "Westmeath"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 top ranking player?
Francis Forde
Answer:
128
Table InputTable: [["Golfer", "Country", "Wins", "Match Play", "Championship", "Invitational", "Champions"], ["Ernie Els", "South Africa", "2", "β€”", "2: 2004, 2010", "β€”", "β€”"], ["Geoff Ogilvy", "Australia", "3", "2: 2006, 2009", "1: 2008", "β€”", "β€”"], ["Phil Mickelson", "United States", "2", "β€”", "1: 2009", "β€”", "1: 2009"], ["Ian Poulter", "England", "2", "1: 2010", "β€”", "β€”", "1: 2012"], ["Darren Clarke", "Northern Ireland", "2", "1: 2000", "β€”", "1: 2003", "β€”"], ["Hunter Mahan", "United States", "2", "1: 2012", "β€”", "1: 2010", "β€”"], ["Tiger Woods", "United States", "18", "3: 2003, 2004, 2008", "7: 1999, 2002, 2003,\\n2005, 2006, 2007, 2013", "8: 1999, 2000, 2001, 2005,\\n2006, 2007, 2009, 2013", "β€”"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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:whats the difference in win amounts between geoff ogilvy and ernie els?
1
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)", "OctoberΒ 6,Β 2000", "MayΒ 17,Β 2001", "2000–2001", "#10", "17.80"], ["9", "24", "Thursday 9pm/8c", "OctoberΒ 9,Β 2008", "May 14, 2009", "2008–2009", "#4", "18.52"], ["5", "25", "Thursday 9pm/8c", "SeptemberΒ 23,Β 2004", "May 19, 2005", "2004–2005", "#2", "26.26"], ["6", "24", "Thursday 9pm/8c", "SeptemberΒ 22,Β 2005", "May 18, 2006", "2005–2006", "#3", "24.86"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any explanations, reasoning, or repeat these instructions in your answer. Examples: Example 1 Table: [["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"], ["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"], ["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""], ["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"], ["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""], ["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"], ["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]] Question: which typ(s) had the longest construction times? Answer: K 5/13 PS Example 2 Table: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], [1, "Netherlands", 20, 9, 0, 29], [2, "Italy", 10, 15, 3, 28], [3, "Belgium", 1, 2, 6, 9], [4, "Spain", 1, 1, 13, 15], [5, "Great Britain", 0, 2, 0, 2], [6, "Germany", 0, 1, 7, 8], [7, "Greece", 0, 1, 0, 1], [7, "Russia", 0, 1, 0, 1], [9, "Sweden", 0, 0, 2, 2], [10, "France", 0, 0, 1, 1]] Question: name the countries that had at least 5 gold medals Answer: Netherlands, Italy Question:how many episodes were in the last season on this chart?
22
Answer:
128
Table InputTable: [["Date", "Opponent#", "Rank#", "Site", "TV", "Result", "Attendance"], ["October 22", "Ole Miss", "#8", "Bryant–Denny Stadium β€’ Tuscaloosa, AL (Rivalry)", "ABC", "WΒ 21–10", "70,123"], ["October 8", "Southern Miss*", "#11", "Bryant–Denny Stadium β€’ Tuscaloosa, AL", "", "WΒ 14–6", "70,123"], ["October 1", "Georgia", "#11", "Bryant–Denny Stadium β€’ Tuscaloosa, AL", "ESPN", "WΒ 29–28", "70,123"], ["September 10", "Vanderbilt", "#11", "Bryant–Denny Stadium β€’ Tuscaloosa, AL", "JPS", "WΒ 17–7", "70,123"], ["December 3", "vs.Β #6Β Florida", "#3", "Georgia Dome β€’ Atlanta, GA (SEC Championship Game)", "ABC", "LΒ 23–24", "74,751"], ["November 5", "atΒ LSU", "#6", "Tiger Stadium β€’ Baton Rouge, LA (Rivalry)", "ESPN", "WΒ 35–17", "75,453"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 where there at least 70,000 people in attendance for the 1994 alabama crimson tide football team?
11
Answer:
128
Table InputTable: [["Client", "Years of Operation", "Area of Operation", "Country", "Services"], ["Lasmo", "1993-94", "Wadi Borjuj", "Libya", "Drilling, workover"], ["Agoco", "1991-current", "Sarir field", "Libya", "Drilling, workover"], ["Total", "1999-current", "El Mabrouk", "Libya", "Drilling"], ["Waha", "1994", "El Zahra", "Libya", "Drilling, workover"], ["Fina", "1997", "El Hamada", "Libya", "Drilling, workover"], ["SOC", "2000-current", "SOC fields", "Libya", "Drilling"], ["OMV", "1997", "Field 103", "Libya", "Drilling, workover"], ["Veba", "2000", "Different fields", "Libya", "Drilling, workover"], ["Perenco Oil Co.", "2000-01", "EchiraX Concession", "Gabon", "Drilling"], ["Khalda/Repsol", "1998-99", "West Desert", "Egypt", "Drilling"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 has the greatest number of challenger operations?
Libya
Answer:
128
Table InputTable: [["Team", "City", "Years active", "Seasons played", "Win–loss record", "Win%", "Playoffs appearances"], ["Chicago Stags", "Chicago, Illinois", "1946–1950", "4", "145–92", ".612", "4"], ["Baltimore Bullets*", "Baltimore, Maryland", "1947–1954", "8", "158–292", ".351", "3"], ["Indianapolis Jets", "Indianapolis, Indiana", "1948–1949", "1", "18–42", ".300", "0"], ["Pittsburgh Ironmen", "Pittsburgh, Pennsylvania", "1946–1947", "1", "15–45", ".250", "0"], ["Detroit Falcons", "Detroit, Michigan", "1946–1947", "1", "20–40", ".333", "0"], ["St. Louis Bombers", "St. Louis, Missouri", "1946–1950", "4", "122–115", ".515", "3"], ["Toronto Huskies", "Toronto, Ontario", "1946–1947", "1", "22–38", ".367", "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:what is the total of seasons played between baltimore bullets and chicago stags?
12
Answer:
128
Table InputTable: [["Binary", "Octal", "Decimal", "Hexadecimal", "Glyph"], ["0011Β 0111", "067", "55", "37", "7"], ["0011Β 0100", "064", "52", "34", "4"], ["0011Β 0010", "062", "50", "32", "2"], ["0011Β 0110", "066", "54", "36", "6"], ["0011Β 0101", "065", "53", "35", "5"], ["0011Β 0011", "063", "51", "33", "3"], ["0011Β 0001", "061", "49", "31", "1"], ["0011Β 0000", "060", "48", "30", "0"], ["0011Β 1000", "070", "56", "38", "8"], ["0011Β 1001", "071", "57", "39", "9"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 next octal number after 067?
070
Answer:
128
Table InputTable: [["Pick #", "Player", "Position", "Nationality", "NHL team", "College/junior/club team"], ["165", "Sean Whyte", "Right Wing", "Canada", "Los Angeles Kings", "Guelph Platers (OHL)"], ["157", "Raymond Saumier", "Right Wing", "Canada", "Hartford Whalers", "Trois Rivieres Draveurs (QMJHL)"], ["152", "Sergei Starikov", "Defense", "Soviet Union", "New Jersey Devils", "CSKA Moscow (USSR)"], ["166", "Dean Holoien", "Right Wing", "Canada", "Washington Capitals", "Saskatoon Blades (WHL)"], ["155", "Rob Sangster", "Left Wing", "Canada", "Vancouver Canucks", "Kitchener Rangers (OHL)"], ["163", "David Shute", "Left Wing", "United States", "Pittsburgh Penguins", "Victoria Cougars (WHL)"], ["159", "Sverre Sears", "Defense", "United States", "Philadelphia Flyers", "Princeton University (NCAA)"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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:total number of countries represented in round 8
4
Answer:
128
Table InputTable: [["Name", "Sport", "Event", "Placing", "Performance"], ["Mark Slavin", "Wrestling", "Greco-Roman β€” Middleweight <82 kg", "β€”", "(taken hostage before his scheduled event)"], ["Itzhak Nir", "Sailing", "Flying Dutchman", "23", "28-22-22-19-25-19-DNS = 171 pts\\n(left Kiel before 7th race)"], ["Gad Tsobari", "Wrestling", "Freestyle β€” Light Flyweight <48 kg", "Group stage", "0W–2L"], ["Esther Shahamorov", "Athletics", "Women's 100 m hurdles", "Semifinal", "Did not start (left Munich before the semifinal)"], ["Yehuda Weissenstein", "Fencing", "Men's foil", "Second round", "W2–L8 (1R 2-3, 2R 0-5)"], ["Shlomit Nir", "Swimming", "Women's 200 m breaststroke", "Heats (6th)", "2:53.60"], ["Shlomit Nir", "Swimming", "Women's 100 m breaststroke", "Heats (8th)", "1:20.90"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 mark slavin and itzhak nir both complete their events successfully?
no
Answer:
128
Table InputTable: [["Year", "Injuries (US $000)", "Deaths (age <15)", "CPSC toy safety funding\\n(US$ Millions)", "Toy sales\\n(US $ Billions)"], ["1996", "130", "", "", ""], ["1995", "139", "", "", ""], ["1997", "141", "", "", ""], ["2009", "no data", "12", "no data", ""], ["1998", "153", "14", "", ""], ["1994", "154", "", "", ""], ["2007", "no data", "22", "no data", ""], ["2008", "no data", "19", "no data", ""], ["2006", "no data", "22", "no data†", "22.3"], ["2005", "202 (estimate)", "20", "11.0", "22.2"], ["2001", "255", "25", "12.4", ""], ["1999", "152", "16", "13.6", ""], ["2003", "206", "11", "12.8", "20.7"], ["2000", "191", "17", "12.0", ""]]
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 injuries were reported in the year that toy safety funding was reported at its lowest?
202 (estimate)
Answer:
128
Table InputTable: [["Num", "Pod Color", "Nickname", "Short Description", "Episode"], ["090", "", "Fetchit", "This experiment was activated when Mrs. Hasagawa's cats were. Function unknown.", "220"], ["014", "White", "Kernel", "A tan gourd-shaped experiment with a large opening at the top of his head. Designed to pop popcorn. His one true place is in a movie theater. Was mentioned in \"Angel\" when Jumba said \"624 is harmless early experiment. Designed to...pop popcorn for Jumba's movie night.\"", "Leroy & Stitch"], ["049", "White", "Picker", "This experiment was seen in pod form in Stitch! The Movie. His pod says 49 instead of 049, possibly due to the angle. Function unknown.", "Stitch! The Movie"], ["054", "Blue", "Fudgy", "An experiment made of chocolate that looks like a blob. Designed to drown people in his sticky sweetness. When he was activated, he was called 119, and he was mistaken for experiment 611. The mistake with his number was due to Jumba's untidy database, although Jumba later corrected this mistake. Was rescued in \"Snafu.\"", "119, 226"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 experiments are there?
99
Answer:
128
Table InputTable: [["Type", "Construction period", "Cylinder", "Capacity", "Power", "Vmax"], ["C2 (10/28 PS)", "1913–1914", "straight-4", "2.412 cc", "28 PS (20,6 kW)", "75Β km/h (47Β mph)"], ["V 5 Sport", "1931–1932", "V4", "1.168 cc", "30 PS (22 kW)", "100Β km/h (62Β mph)"], ["V 5", "1931–1932", "V4", "1.168 cc", "25 PS (18,4 kW)", "80Β km/h (50Β mph)"], ["B6 (9/22 PS)", "1912–1914", "straight-4", "4.900 cc", "45 PS (33 kW)", "95Β km/h (59Β mph)"], ["D7 (42/120 PS)", "1919–1921", "straight-6", "11.160 cc", "120 PS (88 kW)", "160Β km/h (99Β mph)"], ["D12 (12/45 PS)", "1923–1924", "straight-6", "3.107 cc", "45 PS (33 kW)", "100Β km/h (62Β mph)"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 kilometers per hour is the vmax of the passenger car model constructed in 1913-1914?
75 km/h (47 mph)
Answer:
128
Table InputTable: [["Week", "Date", "Opponent", "Result", "Attendance"], ["5", "October 4, 1981", "Cincinnati Bengals", "W 17–10", "44,350"], ["9", "November 1, 1981", "at Cincinnati Bengals", "L 34–21", "54,736"], ["8", "October 26, 1981", "at Pittsburgh Steelers", "L 26–13", "52,732"], ["16", "December 20, 1981", "Pittsburgh Steelers", "W 21–20", "41,056"], ["6", "October 11, 1981", "Seattle Seahawks", "W 35–17", "42,671"], ["2", "September 13, 1981", "at Cleveland Browns", "W 9–3", "79,483"], ["14", "December 3, 1981", "Cleveland Browns", "W 17–13", "44,502"], ["15", "December 13, 1981", "at San Francisco 49ers", "L 28–6", "55,707"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 points did they beat the bengals by in week 5?
7
Answer:
128
Table InputTable: [["Rank", "Pair", "Name", "Country", "Time", "Time behind"], ["4", "20", "Lee Kyou-hyuk", "South Korea", "1:09.37", "+0.48"], ["", "21", "Erben Wennemars", "Netherlands", "1:09.32", "+0.43"], ["24", "17", "Mun Jun", "South Korea", "1:10.66", "+1.77"], ["–", "2", "Ermanno Ioriatti", "Italy", "DQ", "–"], ["33", "1", "An Weijiang", "China", "1:11.80", "+2.91"], ["8", "18", "Stefan Groothuis", "Netherlands", "1:09.57", "+0.68"], ["12", "9", "Beorn Nijenhuis", "Netherlands", "1:09.85", "+0.96"], ["10", "6", "Dmitry Dorofeyev", "Russia", "1:09.74", "+0.85"], ["36", "8", "Aleksandr Zhigin", "Kazakhstan", "1:12.36", "+3.47"]]
You are a question-answering model specialized in tabular data. I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question. Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines: - Output Format: Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy). - Direct Answers Only: Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text. - Aggregation Requirements: If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string. - No Explanations: Do NOT provide any 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 country is at the top?
United States
Answer:
128
Table InputTable: [["Rank", "Country", "Box Office", "Year", "Box office\\nfrom national films"], ["6", "South Korea", "$1.47 billion", "2013", "59.7% (2013)"], ["3", "Japan", "$1.88 billion", "2013", "61% (2013)"], ["5", "France", "$1.7 billion", "2012", "33.3% (2013)"], ["7", "India", "$1.4 billion", "2012", "–"], ["2", "China", "$3.6 billion", "2013", "59% (2013)"], ["12", "Brazil", "$0.72 billion", "2013", "17% (2013)"], ["8", "Germany", "$1.3 billion", "2012", "–"], ["11", "Italy", "$0.84 billion", "2013", "30% (2013)"], ["4", "United Kingdom", "$1.7 billion", "2012", "36.1% (2011)"], ["-", "World", "$34.7 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 asian countries received over 1.5 billion dollars in box office revenue in 2013?
2
Answer:
128