context stringlengths 362 4.81k | question stringlengths 2.11k 2.25k | answer stringlengths 1 260 | max_new_tokens int64 128 128 | answer_prefix stringclasses 1
value |
|---|---|---|---|---|
Table InputTable: [["Clerk", "Started", "Finished", "School (year)", "Previous clerkship"], ["Heywood H. Davis", "1958", "1959", "Kansas (1958)", "none"], ["Alan C. Kohn", "1957", "1958", "Wash U (1955)", "none"], ["Kenneth W. Dam", "1957", "1958", "Chicago (1957)", "none"], ["Jerome B. Libin", "1959", "1960", "Michigan (1959)", "none"], ["D. Lawrence Gunnels", "1961", "1962", "Wash U (1960)", "none"], ["William C. Canby, Jr.", "1958", "1959", "Minnesota (1956)", "none"], ["Patrick F. McCartan", "1959", "1960", "Notre Dame (1959)", "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:what year did the first washington university clerk start working? | 1957 | 128 | Answer: |
Table InputTable: [["Character", "Real name", "Home world", "Membership notes", "Powers"], ["Earth-Man", "Kirt Niedrigh", "Earth", "Pre-Crisis version first appeared (as \"Absorbency Boy\") in Superboy and the Legion of Super-Heroes #218 (July 1976).\\nJoined in Legion of Super-Heroes vol. 6, #2 (August 2010).\\nDied battling the Adversary in Legion of Super-Heroes vol. 6, #16 (October 2011).", "Super-power absorption and duplication."], ["Night Girl", "Lydda Jath", "Kathoon", "Pre-Crisis version first appeared in Adventure Comics #306 (March 1963).\\nLegion membership first mentioned by Starman in Justice Society of America vol. 3, #6 (July 2007) and confirmed in Action Comics #860 (February 2008).", "Super-strength when not in direct sunlight."], ["Chameleon Girl", "Yera Allon", "Durla", "Pre-Crisis version first appeared (impersonating Shrinking Violet) in Legion of Super-Heroes vol. 2, #286 (April 1982).\\nTrue form and identity revealed in Legion of Super-Heroes vol. 2, #305 (November 1983).\\nLegion membership first revealed in Action Comics #861 (March 2008).", "Shapeshifting."], ["XS", "Jenni Ognats", "Aarok", "First appeared in Legionnaires #0 (October 1994); granddaughter of Barry Allen and first cousin of Bart Allen.\\nNative of the same universe as the post-Infinite Crisis team, as revealed in Final Crisis: Legion of 3 Worlds #3 (April 2009).\\nJoined the Earth-247 team in Legion of Super-Heroes vol. 4, #62 (November 1994).\\nJoined the post-Infinite Crisis team in Final Crisis: Legion of 3 Worlds #5 (September 2009).\\nPost-Flashpoint no longer listed as a member of the Legion.", "Superspeed."], ["Karate Kid II", "Myg", "Lythyl", "Joined as a replacement for Val Armorr, as revealed in Final Crisis: Legion of 3 Worlds #1 (October 2008), unlike his counterpart who did not join the original team prior to Crisis on Infinite Earths.\\nKilled by Radiation Roy in Final Crisis: Legion of 3 Worlds #3 (April 2009).", "Mastery of all known martial arts."], ["Comet Queen", "Grava", "Extal Colony", "Pre-Crisis version first appeared in Legion of Super-Heroes vol. 2, #304 (October 1983) as a student at the Legion Academy.\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Space flight, comet gas extrusion."], ["Chemical Kid", "Hadru Jamik", "Phlon", "First appeared in Legion of Super-Heroes vol. 6, #6 (December 2010) as a student at the Legion Academy.\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Catalyze chemical reactions."], ["Dragonwing", "Marya Pai", "Earth", "First appeared in Legion of Super-Heroes vol. 6, #6 (December 2010) as a student at the Legion Academy.\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Fire breath and acid absorption."], ["Green Lantern", "Rond Vidar", "Earth", "Pre-Crisis version first appeared in Adventure Comics #349 (October 1966); granted honorary membership in Adventure Comics #360 (September 1967).\\nLast remaining member of the Green Lantern Corps, as revealed in Final Crisis: Legion of 3 Worlds #2 (November 2008).\\nKilled in the same issue by Superboy-Prime.", "Possesses a Green Lantern power ring."], ["Glorith II", "Glorith", "Unknown", "First appeared in Adventure Comics #523 (April 2011) as a student at the Legion Academy.\\nJoined between Legion of Super-Heroes vol. 6, #16 (October 2011) and Legion of Super-Heroes vol. 7, #1 (November 2011).", "Manipulation of mystical energies."]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 pre-crisis superhero first appeared as "absorbency boy," but then became someone else? | Earth-Man | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Partner", "Opponents", "Score"], ["Winner", "1.", "13 February 2011", "Rancho Mirage, United States", "Hard", "Karolína Plíšková", "Nadejda Guskova\\n Sandra Zaniewska", "6–7(6–8), 6–1, 6–4"], ["Runner-up", "4.", "17 September 2012", "Shrewsbury, United Kingdom", "Hard (i)", "Karolína Plíšková", "Vesna Dolonc\\n Stefanie Vögele", "1–6, 7–6(7–3), [13–15]"], ["Runner-up", "3.", "20 November 2011", "Bratislava, Slovakia", "Hard", "Karolína Plíšková", "Naomi Broady\\n Kristina Mladenovic", "7–5, 4–6, [2–10]"], ["Winner", "4.", "30 January 2012", "Grenoble, France", "Hard (i)", "Karolína Plíšková", "Valentyna Ivakhnenko\\n Maryna Zanevska", "6–1, 6–3"], ["Winner", "5.", "12 November 2012", "Zawada, Poland", "Carpet (i)", "Karolína Plíšková", "Kristina Barrois\\n Sandra Klemenschits", "6–3, 6–1"], ["Winner", "2.", "7 August 2011", "Vancouver, Canada", "Hard", "Karolína Plíšková", "Jamie Hampton\\n N. Lertcheewakarn", "5–7, 6–2, 6–4"], ["Winner", "3.", "23 January 2012", "Andrézieux-Bouthéon, France", "Hard (i)", "Karolína Plíšková", "Julie Coin\\n Eva Hrdinová", "6–4, 4–6, [10–5]"], ["Runner-up", "2.", "6 November 2011", "Taipei 5, Taiwan", "Hard", "Karolína Plíšková", "Chan Yung-jan\\n Zheng Jie", "6–7(5–7), 7–5, 3–6"], ["Runner-up", "1.", "16 May 2010", "Kurume, Japan", "Clay", "Karolína Plíšková", "Sun Shengnan\\n Xu Yifan", "0–6, 3–6"], ["Winner", "6.", "28 October 2013", "Barnstaple, United Kingdom", "Hard (i)", "Naomi Broady", "Raluca Olaru\\n Tamira Paszek", "6–3, 3–6, [10–5]"]] | 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:in what year did kristyna pliskova win her first doubles tournament? | 13 February 2011 | 128 | Answer: |
Table InputTable: [["#", "Date", "Location", "Winner", "Score\\nJSU", "Score\\nTU", "Series"], ["8", "November 11, 1938", "Jacksonville, AL", "Tied", "6", "6", "TSU 4–3–1"], ["6", "November 10, 1933", "Jacksonville, AL", "Troy State", "7", "18", "Tied 3–3"], ["38", "November 11, 1972", "Jacksonville, AL", "Tied", "14", "14", "JSU 22–14–2"], ["21", "October 15, 1955", "Troy, AL", "Jacksonville State", "12", "0", "Tied 10–10–1"], ["17", "October 13, 1951", "Troy, AL", "Jacksonville State", "13", "7", "Tied 8–8–1"], ["1", "November 27, 1924", "Jacksonville, AL", "Jacksonville State", "14", "9", "JSU 1–0"], ["2", "October 28, 1927", "?", "Jacksonville State", "26", "12", "JSU 2–0"], ["9", "November 11, 1939", "Troy, AL", "Troy State", "0", "27", "TSU 5–3–1"], ["7", "October 26, 1934", "Troy, AL", "Troy State", "0", "32", "TSU 4–3"], ["14", "December 18, 1948", "Pensacola, FL", "Jacksonville State", "19", "0", "TSU 7–6–1"], ["3", "November 16, 1928", "Troy, AL", "Jacksonville State", "20", "0", "JSU 3–0"], ["20", "October 16, 1954", "Jacksonville, AL", "Jacksonville State", "38", "7", "TSU 10–9–1"], ["10", "November 8, 1940", "Troy, AL", "Troy State", "0", "7", "TSU 6–3–1"], ["18", "October 18, 1952", "Jacksonville, AL", "Troy State", "6", "19", "TSU 9–8–1"], ["19", "October 17, 1953", "Troy, AL", "Troy State", "7", "13", "TSU 10–8–1"], ["59", "November 22, 1997", "Troy, AL", "Troy State", "0", "49", "JSU 32–25–2"], ["4", "October 3, 1931", "Jacksonville, AL", "Troy State", "6", "24", "JSU 3–1"], ["15", "October 15, 1949", "Troy, AL", "Troy State", "6", "27", "TSU 8–6–1"], ["5", "November 12, 1932", "Montgomery, AL", "Troy State", "0", "20", "JSU 3–2"], ["11", "October 17, 1946", "Anniston, AL", "Troy State", "0", "12", "TSU 7–3–1"], ["13", "October 14, 1948", "Jacksonville, AL", "Jacksonville State", "25", "13", "TSU 7–5–1"], ["34", "October 19, 1968", "Jacksonville, AL", "Troy State", "0", "31", "JSU 21–12–1"], ["30", "October 3, 1964", "Jacksonville, AL", "Jacksonville State", "38", "0", "JSU 19–10–1"], ["45", "November 10, 1979", "Troy, AL", "Troy State", "10", "12", "JSU 26–17–2"], ["49", "November 12, 1983", "Troy, AL", "Troy State", "3", "45", "JSU 29–18–2"], ["50", "November 10, 1984", "Jacksonville, AL", "Troy State", "39", "42", "JSU 29–19–2"]] | 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 date of the first tie game? | November 11, 1938 | 128 | Answer: |
Table InputTable: [["DATE", "OPPONENT", "SCORE", "TOP SCORER (Total points)", "VENUE"], ["February 11", "MOBILINE", "80-68", "", "ARANETA COLISEUM"], ["June 10 Commissioner's Cup", "MOBILINE", "97-92", "Tony Lang (29)", "ARANETA COLISEUM"], ["November 7", "SAN MIGUEL", "86-81", "", "ARANETA COLISEUM"], ["September 29", "TALK 'N TEXT", "99-85", "", "DUMAGUETE CITY"], ["June 15", "BRGY.GINEBRA", "111-98", "", "PHILSPORTS ARENA"], ["July 8", "STA.LUCIA", "95-88", "", "ARANETA COLISEUM"], ["April 4", "STA.LUCIA", "87-84", "", "PHILSPORTS ARENA"], ["October 24", "BRGY.GINEBRA", "93-72", "", "PHILSPORTS ARENA"], ["September 23 Governor's Cup", "TANDUAY", "108-93", "", "PHILSPORTS ARENA"], ["June 24", "SHELL", "94-82", "", "ARANETA COLISEUM"], ["March 9", "SHELL", "65-58", "", "PHILSPORTS ARENA"], ["July 13", "TANDUAY", "104-98", "", "PHILSPORTS ARENA"], ["February 16", "ALASKA", "73-72", "Davonn Harp (20)", "PHILSPORTS ARENA"], ["February 28", "SAN MIGUEL", "78-76", "Lowell Briones (21)", "PHILSPORTS ARENA"], ["February 7 All-Filipino Cup", "SHELL", "76-60", "", "PHILSPORTS ARENA"], ["March 3", "BRGY.GINEBRA", "79-72", "", "ILOILO CITY"], ["October 19", "STA.LUCIA", "101-94", "", "CUNETA ASTRODOME"], ["July 1", "POP COLA", "95-79", "", "ARANETA COLISEUM"], ["October 14", "SHELL", "68-62", "", "YNARES CENTER"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:after a game at dumaguete city, what venue comes next? | YNARES CENTER | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["7", "Hong Kong (HKG)", "2", "2", "9", "13"], ["3", "South Korea (KOR)", "32", "48", "65", "145"], ["1", "China (CHN)", "127", "63", "33", "223"], ["4", "Chinese Taipei (TPE)", "12", "34", "26", "72"], ["5", "Macau (MAC)", "11", "16", "17", "44"], ["Total", "Total", "237", "230", "254", "721"], ["8", "Mongolia (MGL)", "1", "1", "6", "8"], ["2", "Japan (JPN)", "46", "56", "77", "179"], ["6", "North Korea (PRK)", "6", "10", "20", "36"], ["9", "Guam (GUM)", "0", "0", "1", "1"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what are the number of bronze medals hong kong earned? | 9 | 128 | Answer: |
Table InputTable: [["Year", "Date", "Winner", "Result", "Loser", "Location"], ["2008", "November 9", "New York Giants", "36-31", "Philadelphia Eagles", "Lincoln Financial Field"], ["2006", "September 17", "New York Giants", "30-24 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2005", "December 11", "New York Giants", "26-23 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2003", "November 16", "Philadelphia Eagles", "28-10", "New York Giants", "Lincoln Financial Field"], ["2004", "September 12", "Philadelphia Eagles", "31-17", "New York Giants", "Lincoln Financial Field"], ["2006", "December 17", "Philadelphia Eagles", "36-22", "New York Giants", "Giants Stadium"], ["2007", "December 9", "New York Giants", "16-13", "Philadelphia Eagles", "Lincoln Financial Field"], ["2009", "November 1", "Philadelphia Eagles", "40-17", "New York Giants", "Lincoln Financial Field"], ["2009", "December 13", "Philadelphia Eagles", "45-38", "New York Giants", "Giants Stadium"], ["2004", "November 28", "Philadelphia Eagles", "27-6", "New York Giants", "Giants Stadium"], ["2008", "December 7", "Philadelphia Eagles", "20-14", "New York Giants", "Giants Stadium"], ["2007", "January 7", "Philadelphia Eagles", "23-20", "New York Giants", "Lincoln Financial Field"], ["2005", "November 20", "New York Giants", "27-17", "Philadelphia Eagles", "Giants Stadium"], ["2009", "January 11", "Philadelphia Eagles", "23-11", "New York Giants", "Giants Stadium"], ["2001", "October 22", "Philadelphia Eagles", "10-9", "New York Giants", "Giants Stadium"], ["2003", "October 19", "Philadelphia Eagles", "14-10", "New York Giants", "Giants Stadium"], ["2001", "December 30", "Philadelphia Eagles", "24-21", "New York Giants", "Veterans Stadium"], ["2002", "October 28", "Philadelphia Eagles", "17-3", "New York Giants", "Veterans Stadium"], ["2007", "September 30", "New York Giants", "16-3", "Philadelphia Eagles", "Giants Stadium"], ["2002", "December 28", "New York Giants", "10-7", "Philadelphia Eagles", "Giants Stadium"], ["2000", "September 10", "New York Giants", "33-18", "Philadelphia Eagles", "Veterans Stadium"], ["2001", "January 7", "New York Giants", "20-10", "Philadelphia Eagles", "Giants Stadium"], ["2000", "October 29", "New York Giants", "24-7", "Philadelphia Eagles", "Giants Stadium"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the winner of the last game on this chart? | Philadelphia Eagles | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2006", "African Championships", "Bambous, Mauritius", "4th", "400 m hurdles", "50.96"], ["2007", "All-Africa Games", "Algiers, Algeria", "8th", "4x400 m relay", "DNF"], ["2007", "All-Africa Games", "Algiers, Algeria", "2nd", "400 m hurdles", "48.91"], ["2006", "Commonwealth Games", "Melbourne, Australia", "7th", "400 m hurdles", "50.51"], ["2000", "World Junior Championships", "Santiago, Chile", "4th", "4x400 m relay", "3:07.66"], ["2000", "World Junior Championships", "Santiago, Chile", "2nd", "400 m hurdles", "50.52"], ["2007", "World Championships", "Osaka, Japan", "15th (sf)", "400 m hurdles", "49.37"], ["2008", "Olympic Games", "Beijing, China", "12th (sf)", "400 m hurdles", "49.44"], ["2005", "World Championships", "Helsinki, Finland", "13th (h)", "4x400 m relay", "3:04.64"], ["2005", "World Championships", "Helsinki, Finland", "17th (sf)", "400 m hurdles", "49.75"]] | 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:how many times did pieter de villiers get 4th place? | 2 | 128 | Answer: |
Table InputTable: [["Date", "Site", "Winning team", "Winning team", "Losing team", "Losing team", "Series"], ["September 29, 1984", "Colorado Springs", "Air Force", "52", "Colorado State", "10", "AFA 14–8–1"], ["September 27, 1986", "Colorado Springs", "Air Force", "24", "Colorado State", "7", "AFA 16–8–1"], ["October 16, 1982", "Colorado Springs", "Colorado State", "21", "Air Force", "11", "AFA 12–8–1"], ["October 3, 1981", "Colorado Springs", "Air Force", "28", "Colorado State", "14", "AFA 12–7–1"], ["October 17, 1992", "Colorado Springs", "Colorado State", "32", "Air Force", "28", "AFA 20–10–1"], ["September 17, 1998", "Colorado Springs", "Air Force", "30", "Colorado State", "27", "AFA 22–14–1"], ["November 11, 2000", "Colorado Springs", "Air Force", "44", "Colorado State", "40", "AFA 23–15–1"], ["October 31, 2002", "Colorado Springs", "Colorado State", "31", "Air Force", "12", "AFA 23–17–1"], ["September 30, 1989", "Fort Collins", "Air Force", "46", "Colorado State", "21", "AFA 19–8–1"], ["September 26, 1987", "Fort Collins", "Air Force", "27", "Colorado State", "19", "AFA 17–8–1"], ["October 19, 1985", "Fort Collins", "#10 Air Force", "35", "Colorado State", "19", "AFA 15–8–1"], ["September 1, 1990", "Colorado Springs", "Colorado State", "35", "Air Force", "33", "AFA 19–9–1"], ["November 8, 2008", "Colorado Springs", "Air Force", "38", "Colorado State", "17", "AFA 27–19–1"], ["September 6, 1980", "Fort Collins", "Colorado State", "21", "Air Force", "9", "AFA 11–7–1"], ["September 29, 2012", "Colorado Springs", "Air Force", "42", "Colorado State", "21", "AFA 31–19–1"], ["September 3, 1988", "Fort Collins", "Air Force", "29", "Colorado State", "23", "AFA 18–8–1"], ["November 2, 1996", "Colorado Springs", "Colorado State", "42", "Air Force", "41", "AFA 20–14–1"], ["September 3, 1994", "Colorado Springs", "Colorado State", "34", "Air Force", "21", "AFA 20–12–1"], ["September 16, 1995", "Colorado Springs", "Colorado State", "27", "Air Force", "20", "AFA 20–13–1"], ["October 12, 2006", "Colorado Springs", "Air Force", "24", "Colorado State", "21", "AFA 25–19–1"], ["September 11, 1993", "Fort Collins", "Colorado State", "8", "Air Force", "5", "AFA 20–11–1"], ["October 9, 2010", "Colorado Springs", "Air Force", "49", "Colorado State", "27", "AFA 29–19–1"], ["September 20, 1997", "Fort Collins", "Air Force", "24", "Colorado State", "0", "AFA 21–14–1"], ["September 7, 1991", "Fort Collins", "Air Force", "31", "Colorado State", "26", "AFA 20–9–1"], ["November 20, 2004", "Colorado Springs", "Air Force", "47", "Colorado State", "17", "AFA 24–18–1"], ["September 29, 2005", "Fort Collins", "Colorado State", "41", "Air Force", "23", "AFA 24–19–1"], ["November 8, 2001", "Fort Collins", "Colorado State", "28", "Air Force", "21", "AFA 23–16–1"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total games did the air force win during this era? | 20 | 128 | Answer: |
Table InputTable: [["Date", "Venue", "Opponents", "Score", "Competition"], ["20 March", "Fukuoka (A)", "China PR", "1–0", "Sanix Cup"], ["20 March", "Fukuoka (A)", "Japan", "2–0", "Sanix Cup"], ["18 October", "Tashkent (N)", "Iran", "1–2", "AFC U-16 Championship (Final)"], ["4 October", "Tashkent (N)", "India", "5–2", "AFC U-16 Championship (Group B)"], ["12 October", "Tashkent (A)", "Uzbekistan", "3–0", "AFC U-16 Championship (Quarterfinal)"], ["8 October", "Tashkent (N)", "Syria", "1–1", "AFC U-16 Championship (Group B)"], ["15 October", "Tashkent (N)", "Japan", "2–1", "AFC U-16 Championship (Semifinal)"], ["9 August", "Toyota (A)", "Japan", "2–2", "Toyota Cup"], ["8 August", "Toyota (N)", "Brazil", "0–0", "Toyota Cup"], ["6 October", "Tashkent (N)", "Indonesia", "9–0", "AFC U-16 Championship (Group B)"], ["10 August", "Toyota (N)", "United Arab Emirates", "6–0", "Toyota Cup"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which nation appears the most in the venue column? | Tashkent (N) | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["5", "Australia", "26", "38", "36", "100"], ["10", "Japan", "17", "16", "20", "53"], ["1", "China", "63", "46", "32", "141"], ["8", "Germany", "19", "28", "31", "78"], ["6", "Ukraine", "24", "12", "19", "55"], ["9", "France", "18", "26", "30", "74"], ["4", "United States", "27", "22", "39", "88"], ["7", "Spain", "20", "27", "24", "71"], ["2", "Great Britain", "35", "30", "29", "94"], ["3", "Canada", "28", "19", "25", "72"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the average number of gold medals in the top 5 ranked countries? | 35.8 | 128 | Answer: |
Table InputTable: [["Position", "Driver", "No.", "Car", "Entrant", "Lak.", "Ora.", "San.", "Phi.", "Total"], ["3", "James Phillip", "55", "Honda Prelude Chevrolet", "James Phillip", "26", "28", "28", "30", "112"], ["17", "Phil Crompton", "49", "Ford EA Falcon", "Phil Crompton", "17", "-", "-", "-", "17"], ["13", "Chris Fing", "", "Chevrolet Monza", "", "29", "-", "-", "-", "29"], ["4", "Mick Monterosso", "2", "Ford Escort RS2000", "Mick Monterosso", "-", "34", "36", "34", "104"], ["11", "Kevin Clark", "116", "Ford Mustang GT", "Kevin Clark", "-", "-", "23", "23", "46"], ["15", "Gary Rowe", "47", "Nissan Stanza", "Gary Rowe", "-", "-", "21", "-", "21"], ["6", "Danny Osborne", "", "Mazda RX-7", "", "26", "10", "30", "-", "66'"], ["21", "Brett Francis", "", "", "", "11", "-", "-", "-", "11"], ["18", "Allan McCarthy", "", "Alfa Romeo Alfetta", "", "14", "-", "-", "-", "14"], ["", "Paul Barrett", "", "", "", "-", "-", "-", "12", "12"], ["19", "Chris Donnelly", "", "", "", "12", "-", "-", "-", "12"], ["22", "Shane Eklund", "", "", "", "10", "-", "-", "-", "10"], ["5", "Bob Jolly", "3", "Holden VS Commodore", "Bob Jolly", "-", "28", "16", "32", "76"], ["8", "Mark Trenoweth", "", "Jaguar", "", "33", "24", "-", "-", "57"], ["12", "Peter O'Brien", "17", "Holden VL Commodore", "O'Brien Aluminium", "-", "11", "29", "-", "40"], ["2", "Kerry Baily", "18", "Toyota Supra Chevrolet", "Kerry Baily", "38", "38", "36", "38", "150"], ["14", "Brian Smith", "", "Alfa Romeo GTV Chevrolet", "", "-", "28", "-", "-", "28"], ["9", "Ivan Mikac", "42", "Mazda RX-7", "Ivan Mikac", "-", "-", "25", "26", "51"], ["1", "John Briggs", "9", "Honda Prelude Chevrolet", "John Briggs", "42", "42", "42", "42", "168"], ["7", "Mike Imrie", "4", "Saab", "Imrie Motor Sport", "23", "11", "-", "28", "62"], ["", "Craig Wildridge", "", "", "", "-", "10", "-", "-", "10"], ["10", "Des Wall", "", "Toyota Supra", "", "15", "32", "-", "-", "47"], ["", "Ron O'Brien", "", "", "", "-", "-", "-", "10", "10"], ["", "Domenic Beninca", "", "", "", "-", "-", "-", "21", "21"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:name a driver than has more total points than phillip. | Kerry Baily | 128 | Answer: |
Table InputTable: [["Name", "City", "State/Country", "Designed", "Completed", "Other Information"], ["Eero Saarinen & Associates Building", "Bloomfield Hills", "Michigan", "1953", "1953", ""], ["Saarinen House furnishings", "Bloomfield Hills", "Michigan", "1928", "1930", ""], ["Center Line Defense Housing", "Center Line", "Michigan", "1941", "1942", "With Eliel Saarinen and J. Robert F. Swanson. 477 housing units"], ["Eero Saarinen House", "Bloomfield Hills", "Michigan", "1947", "1959", "Renovation of a Victorian house"], ["J. F. Spencer House", "Huntington Woods", "Michigan", "1937", "1938", "First building designed independently"], ["UAW–CIO Cooperative", "Flint", "Michigan", "1948", "1948", "Renovation. Demolished."], ["Willow Lodge", "Willow Run", "Michigan", "1942", "1943", "Demolished"], ["Fenton Community Center", "Fenton", "Michigan", "1937", "1938", "With Eliel Saarinen"], ["Kingswood School for Girls furnishings", "Bloomfield Hills", "Michigan", "1929", "1931", ""], ["Brandeis University plan and buildings", "Waltham", "Massachusetts", "1949", "1952", "With Matthew Nowicki. Ridgewood Quadrangle Dormitories (1950), Hamilton Quadrangle Dormitory & Student Center (1952), Sherman Student Center (1952)"], ["General Motors Technical Center", "Warren", "Michigan", "1948", "1956", "Listed on the National Register of Historic Places in 2000"], ["University of Michigan School of Music", "Ann Arbor", "Michigan", "1951", "1956", ""], ["Christ Church Lutheran", "Minneapolis", "Minnesota", "1947", "1949", "With Eliel Saarinen; solo addition in 1962. Designated a National Historic Landmark in 2009."], ["Case Study House #9", "Los Angeles", "California", "1945", "1949", "With Charles Eames. Saarinen also provided an original plan for House #8, but Eames completely redesigned it. Listed on the National Register of Historic Places in 2013"], ["Concordia Senior College", "Fort Wayne", "Indiana", "1953", "1958", ""], ["IBM Manufacturing & Training Facility", "Rochester", "Minnesota", "1956", "1958", ""], ["Loja Saarinen House", "Bloomfield Hills", "Michigan", "1950", "1950", "House for Saarinen's widowed mother"], ["United States Chancellery Building", "London", "England", "1955", "1960", ""], ["United States Chancellery Building", "Oslo", "Norway", "1955", "1959", ""], ["University of Chicago plan and buildings", "Chicago", "Illinois", "1955", "1960", "Women's Dormitory & Dining Hall (1958; demolished 2001), Law School (1960)"], ["Albert and Muriel Wermuth House", "Fort Wayne", "Indiana", "1941", "1942", ""], ["Des Moines Art Center", "Des Moines", "Iowa", "1944", "1948", "With Eliel Saarinen and J. Robert F. Swanson. Listed on the National Register of Historic Places in 2004"], ["Saarinen House", "New Haven", "Connecticut", "1960", "1961", "Renovation of a Tudor Revival house"], ["Hill Hall", "Philadelphia", "Pennsylvania", "1957", "1960", ""], ["Cranbrook School for Boys furnishings", "Bloomfield Hills", "Michigan", "1925", "1931", "With Eliel Saarinen"], ["David S. Ingalls Rink", "New Haven", "Connecticut", "1956", "1958", ""], ["Hamden Office", "Hamden", "Connecticut", "1960", "1961", "Became new headquarters"], ["Massachusetts Institute of Technology buildings", "Cambridge", "Massachusetts", "1950", "1955", "Kresge Chapel and Kresge Auditorium"], ["Milwaukee County War Memorial", "Milwaukee", "Wisconsin", "1952", "1957", ""], ["Kleinhans Music Hall", "Buffalo", "New York", "1938", "1940", "With Eliel Saarinen. Designated a National Historic Landmark in 1989"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 buildings completed in michigan? | 15 | 128 | Answer: |
Table InputTable: [["Date", "Opponents", "Venue", "Result", "Scorers", "Attendance"], ["16 Sep 1950", "Colchester United", "H", "2–0", "Parker 2", "16,021"], ["20 Jan 1951", "Colchester United", "A", "1–1", "Birch", "8,230"], ["11 Nov 1950", "Southend United", "A", "0–3", "", "9,882"], ["31 Mar 1951", "Southend United", "H", "6–1", "Moore 2, Shergold 2, Parker, Birch", "9,544"], ["23 Sep 1950", "Bristol Rovers", "A", "0–1", "", "19,816"], ["2 Dec 1950", "Ipswich Town", "H", "1–2", "Hayward", "11,496"], ["21 Apr 1951", "Ipswich Town", "A", "1–2", "Moore", "10,294"], ["23 Dec 1950", "Torquay United", "H", "2–1", "Parker, Shergold", "8,369"], ["3 Feb 1951", "Bristol Rovers", "H", "2–1", "Birch 2", "11,802"], ["7 Sep 1950", "Watford", "A", "2–0", "Parker, Moore", "9,451"], ["14 Apr 1951", "Plymouth Argyle", "H", "2–0", "Parker, Moore", "11,962"], ["3 Mar 1951", "Bristol City", "H", "0–1", "", "11,494"], ["19 Aug 1950", "Nottingham Forest", "H", "0–2", "", "16,595"], ["28 Oct 1950", "Bournemouth & Boscombe Athletic", "A", "0–2", "", "13,466"], ["25 Apr 1951", "Norwich City", "H", "1–1", "Moore", "13,862"], ["10 Mar 1951", "Gillingham", "A", "1–0", "Birch", "9,040"], ["26 Mar 1951", "Norwich City", "A", "1–2", "Birch", "35,267"], ["14 Sep 1950", "Watford", "H", "2–2", "Newall, M.Haines", "12,116"], ["5 May 1951", "Brighton & Hove Albion", "H", "3–0", "Parker, Moore, Birch", "9,274"], ["21 Oct 1950", "Gillingham", "H", "1–0", "Shergold", "9,828"], ["30 Apr 1951", "Bournemouth & Boscombe Athletic", "H", "1–0", "Shergold", "5,563"], ["12 Apr 1951", "Leyton Orient", "A", "3–0", "Parker, Moore, Shergold", "8,270"], ["26 Aug 1950", "Torquay United", "A", "4–3", "Cowley, Parker, Roffi, Shergold", "10,276"], ["28 Apr 1951", "Leyton Orient", "H", "0–0", "", "7,564"], ["2 May 1951", "Nottingham Forest", "A", "1–2", "Parker", "21,468"], ["18 Apr 1951", "Brighton & Hove Albion", "A", "1–9", "Parker", "12,114"], ["9 Sep 1950", "Swindon Town", "A", "0–2", "", "14,021"], ["2 Sep 1950", "Aldershot", "H", "7–0", "Roffi 4, Parker 2, M.Haines", "13,696"], ["4 Nov 1950", "Exeter City", "H", "0–3", "", "10,653"], ["13 Jan 1951", "Swindon Town", "H", "2–1", "Shergold, Birch", "12,485"], ["26 Dec 1950", "Walsall", "H", "3–0", "Parker, Moore, Birch", "13,160"], ["24 Aug 1950", "Port Vale", "A", "0–1", "", "30,196"], ["25 Dec 1950", "Walsall", "A", "0–0", "", "7,832"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 other games had the same result as the colchester united game that ended 2-0? | 2 | 128 | Answer: |
Table InputTable: [["Year", "MVP", "Defensive Player of the Year", "Unsung Hero", "Newcomer of the Year"], ["2006", "Mauricio Vincello", "Gabriel Gervais", "Andrew Weber", "Leonardo Di Lorenzo"], ["2002", "Eduardo Sebrango", "Gabriel Gervais", "Jason DiTullio", "Zé Roberto"], ["2007", "Leonardo Di Lorenzo", "Mauricio Vincello", "Simon Gatti", "Matt Jordan"], ["2004", "Gabriel Gervais", "Greg Sutton", "Zé Roberto", "Sandro Grande"], ["2005", "Mauro Biello", "Nevio Pizzolitto", "Mauricio Vincello", "Masahiro Fukazawa"], ["2008", "Matt Jordan", "Nevio Pizzolitto", "Joey Gjertsen", "Stefano Pesoli"], ["2003", "Greg Sutton", "Gabriel Gervais", "David Fronimadis", "Martin Nash"], ["2010", "Philippe Billy", "Philippe Billy", "Tony Donatelli", "Ali Gerba"], ["1996", "Paolo Ceccarelli", "–", "–", "–"], ["2009", "David Testo", "Nevio Pizzolitto", "Adam Braz", "Stephen deRoux"], ["2001", "Mauro Biello", "–", "–", "–"], ["1997", "Mauro Biello", "–", "–", "–"], ["1998", "Mauro Biello", "–", "–", "–"], ["2011", "Hassoun Camara", "Evan Bush", "Simon Gatti", "Ian Westlake / Sinisa Ubiparipovic"], ["1993", "Patrice Ferri", "–", "–", "–"], ["1995", "Lloyd Barker", "–", "–", "–"], ["1994", "Jean Harbor", "–", "–", "–"], ["2000", "Jim Larkin", "–", "–", "–"], ["1999", "N/A", "–", "–", "–"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the difference in number of defensive player of the year awards received by gabriel gervais and mauricio vincello? | 2 | 128 | Answer: |
Table InputTable: [["Thread\\nnominal size", "Outer diameter\\n[mm (in)]", "Threads per inch\\n(TPI)", "Pitch\\n[in (mm)]", "Inner diameter\\n[mm (in)]", "Cable diameter\\n[mm (in)]"], ["PG11", "18.6 (0.732)", "18", "0.05556 (1.4112)", "17.26 (0.680)", "5 to 10 (0.197 to 0.394)"], ["PG9", "15.5 (0.610)", "18", "0.05556 (1.4112)", "13.86 (0.546)", "4 to 8 (0.157 to 0.315)"], ["PG13.5", "20.4 (0.803)", "18", "0.05556 (1.4112)", "19.06 (0.750)", "6 to 12 (0.236 to 0.472)"], ["PG16", "22.5 (0.886)", "18", "0.05556 (1.4112)", "21.16 (0.833)", "10 to 14 (0.394 to 0.551)"], ["PG21", "28.3 (1.114)", "16", "0.0625 (1.5875)", "26.78 (1.054)", "13 to 18 (0.512 to 0.709)"], ["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)"], ["PG29", "37.0 (1.457)", "16", "0.0625 (1.5875)", "35.48 (1.397)", "18 to 25 (0.709 to 0.984)"], ["PG48", "59.3 (2.335)", "16", "0.0625 (1.5875)", "57.78 (2.275)", ""], ["PG36", "47.0 (1.850)", "16", "0.0625 (1.5875)", "45.48 (1.791)", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 screws have 18 threads per inch? | 4 | 128 | Answer: |
Table InputTable: [["Pos", "Rider", "Manufactuer", "Time/Retired", "Points"], ["22", "Massimo Pennacchioli", "Honda", "+1:59.498", ""], ["21", "Adrian Bosshard", "Honda", "+1:47.492", ""], ["20", "Gabriele Debbia", "Honda", "+1:40.049", ""], ["24", "Alessandro Gramigni", "Gilera", "+1 Lap", ""], ["11", "Alberto Puig", "Honda", "+25.136", "5"], ["3", "Helmut Bradl", "Honda", "+0.384", "16"], ["17", "Adi Stadler", "Honda", "+1:16.349", ""], ["4", "Max Biaggi", "Honda", "+2.346", "13"], ["12", "John Kocinski", "Suzuki", "+25.463", "4"], ["9", "Carlos Cardús", "Honda", "+4.893", "7"], ["2", "Loris Capirossi", "Honda", "+0.090", "20"], ["10", "Luis d'Antin", "Honda", "+25.044", "6"], ["1", "Doriano Romboni", "Honda", "33:53.776", "25"], ["13", "Jochen Schmid", "Yamaha", "+47.065", "3"], ["Ret", "Volker Bähr", "Honda", "Retirement", ""], ["15", "Juan Borja", "Honda", "+1:15.769", "1"], ["19", "Paolo Casoli", "Gilera", "+1:26.061", ""], ["16", "Frédéric Protat", "Aprilia", "+1:15.858", ""], ["8", "Jean-Philippe Ruggia", "Aprilia", "+3.985", "8"], ["Ret", "Patrick van den Goorbergh", "Aprilia", "Retirement", ""], ["Ret", "Jean-Pierre Jeandat", "Aprilia", "Retirement", ""], ["14", "Jean-Michel Bayle", "Aprilia", "+1:15.546", "2"], ["Ret", "Wilco Zeelenberg", "Aprilia", "Retirement", ""], ["Ret", "Luis Maurel", "Aprilia", "Retirement", ""], ["6", "Tetsuya Harada", "Yamaha", "+2.537", "10"], ["Ret", "Jurgen van den Goorbergh", "Aprilia", "Retirement", ""], ["Ret", "Andreas Preining", "Aprilia", "Retirement", ""], ["5", "Loris Reggiani", "Aprilia", "+2.411", "11"], ["23", "Bernard Haenggeli", "Aprilia", "+2:41.806", ""], ["18", "Bernd Kassner", "Aprilia", "+1:16:464", ""], ["7", "Pierfrancesco Chili", "Yamaha", "+3.845", "9"], ["Ret", "Eskil Suter", "Aprilia", "Retirement", ""], ["DNS", "Nobuatsu Aoki", "Honda", "Did not start", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 rider on this chart? | Nobuatsu Aoki | 128 | Answer: |
Table InputTable: [["Name", "Nation", "Position", "League Apps", "League Goals", "FA Cup Apps", "FA Cup Goals", "Total Apps", "Total Goals"], ["Jimmy Glazzard", "England", "FW", "21", "5", "1", "0", "22", "5"], ["John Battye", "England", "DF", "22", "0", "0", "0", "22", "0"], ["Johnny McKenna", "Northern Ireland", "MF", "40", "3", "1", "0", "41", "3"], ["George Hepplewhite", "England", "DF", "36", "0", "1", "0", "37", "0"], ["Vic Metcalfe", "England", "MF", "41", "11", "1", "0", "42", "11"], ["Bill Whittaker", "England", "DF", "16", "0", "0", "0", "16", "0"], ["Harry Mills", "England", "GK", "34", "0", "1", "0", "35", "0"], ["Charlie Gallogly", "Northern Ireland", "DF", "15", "0", "0", "0", "15", "0"], ["Harold Hassall", "England", "FW", "10", "4", "1", "0", "11", "4"], ["Harry Yates", "England", "MF", "1", "0", "0", "0", "1", "0"], ["Eddie Boot", "England", "DF", "38", "0", "1", "0", "39", "0"], ["Jack Howe", "England", "DF", "20", "1", "1", "0", "21", "1"], ["Bob Hesford", "England", "GK", "6", "0", "0", "0", "6", "0"], ["Donald Hunter", "England", "DF", "7", "0", "0", "0", "7", "0"], ["Joe Lynn", "England", "MF", "5", "0", "0", "0", "5", "0"], ["Don McEvoy", "England", "DF", "5", "2", "0", "0", "5", "2"], ["George Howe", "England", "DF", "5", "0", "0", "0", "5", "0"], ["Ian Duthie", "Scotland", "MF", "1", "0", "0", "0", "1", "0"], ["Jack Percival", "England", "DF", "7", "0", "0", "0", "7", "0"], ["Jack Wheeler", "England", "GK", "2", "0", "0", "0", "2", "0"], ["Jeff Taylor", "England", "FW", "21", "11", "0", "0", "21", "11"], ["Ronnie Burke", "England", "FW", "12", "5", "0", "0", "12", "5"], ["Ray Taylor", "England", "MF", "2", "0", "0", "0", "2", "0"], ["Albert Nightingale", "England", "MF", "39", "7", "1", "0", "40", "7"], ["Arnold Rodgers", "England", "FW", "4", "2", "0", "0", "4", "2"], ["Conway Smith", "England", "MF", "10", "0", "0", "0", "10", "0"], ["Henry Stewart", "England", "DF", "15", "0", "0", "0", "15", "0"], ["Lol Morgan", "England", "DF", "6", "0", "0", "0", "6", "0"], ["Tom Briggs", "England", "DF", "4", "0", "0", "0", "4", "0"], ["Bill Hayes", "Republic of Ireland", "DF", "17", "0", "1", "0", "18", "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:who has a larger amount of league appearance john battye or jimmy glazzard? | John Battye | 128 | Answer: |
Table InputTable: [["Nr.", "Name", "Area (km²)", "Population (2006)", "Capital", "Club(s)"], ["3", "Cairo", "3,435", "7,786,640", "Cairo", "Al-Ahly - Al Mokawloon - ENPPI - El-Jaish - El-Shorta - Itesalat"], ["1", "Alexandria", "2,900", "4,110,015", "Alexandria", "Al Itthad Al Sakandary - El-Olympi - Haras El Hodood"], ["4", "Gharbia", "25,400", "3,790,670", "Tanta", "Ghazl El-Mehalla"], ["6", "Ismailia", "1,442", "942,832", "Ismailia", "Ismaily"], ["6", "Suez", "17,840", "510,935", "Suez", "Petrojet"], ["5", "Giza", "85,153", "6,272,571", "Giza", "Zamalek- Tersana"], ["7", "Port Said", "72", "570,768", "Port Said", "Al Masry"], ["2", "Asyut", "25,926", "3,441,597", "Asyut", "Petrol Asyout"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 governorate has the most area recorded? | Giza | 128 | Answer: |
Table InputTable: [["School", "Season", "Record", "Conference Record", "Place", "Postseason"], ["Illinois", "1913–14", "9–4", "7–3", "3rd", ""], ["Illinois", "1919–20", "9–4", "8–4", "3rd", ""], ["Illinois", "1915–16", "13–3", "9–3", "T2nd", ""], ["Illinois", "1912–13", "10–6", "7–6", "5th", ""], ["Illinois", "1914–15", "16–0", "12–0", "T1st", "National Champions"], ["Illinois", "1918–19", "6–8", "5–7", "5th", ""], ["Illinois", "1912–20", "85–34", "64–31", "–", ""], ["Illinois", "1917–18", "9–6", "6–6", "T4th", ""], ["Illinois", "1916–17", "13–3", "10–2", "T1st", "Big Ten Champions"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times did he place not in the top 3? | 3 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event"], ["1996", "World Junior Championships", "Sydney, Australia", "2nd", "3000 m st."], ["", "Commonwealth Games", "Kuala Lumpur, Malaysia", "3rd", "3000 m st."], ["1999", "All-Africa Games", "Johannesburg, South Africa", "1st", "3000 m st."], ["1998", "World Cross Country Championships", "Marrakech, Morocco", "8th", "Short race"], ["2001", "IAAF Grand Prix Final", "Melbourne, Australia", "4th", "3000 m st."], ["2005", "World Athletics Final", "Monte Carlo, Monaco", "8th", "3000 m st."], ["2004", "World Athletics Final", "Monte Carlo, Monaco", "4th", "3000 m st."], ["", "IAAF Grand Prix Final", "Munich, Germany", "4th", "3000 m st."]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 competition did kipkurui misoi compete in after the commonwealth games? | All-Africa Games | 128 | Answer: |
Table InputTable: [["Season", "League\\nPos.", "League\\nCompetition", "League\\nTop scorer", "Danish Cup", "Europe", "Others"], ["1995-96", "1", "1995-96 Superliga", "Peter Møller (15)", "Finalist", "EC3 3rd round", ""], ["2008-09", "3", "2008-09 Superliga", "Morten Rasmussen (9)\\nAlexander Farnerud (9)\\nOusman Jallow (9)", "Semi-final", "EC3 1st round", ""], ["1981-82", "4", "1982 1st Division", "Michael Laudrup (15)", "4th round", "", ""], ["1993-94", "3", "1993-94 Superliga", "Mark Strudal (13)", "Winner", "EC3 3rd round", ""], ["2001-02", "1", "2001-02 Superliga", "Peter Madsen (22)", "5th round", "EC3 3rd round", ""], ["1991-92", "7", "1991-92 Superliga", "Kim Vilfort (9)", "4th round", "EC1 2nd round", ""], ["1982-83", "4", "1983 1st Division", "Brian Chrøis (12)", "4th round", "", ""], ["2007-08", "8", "2007-08 Superliga", "Morten Rasmussen (7)\\nMartin Ericsson (7)", "Winner", "", ""], ["2003-04", "2", "2003-04 Superliga", "Thomas Kahlenberg (11)", "Semi-final", "EC3 3rd round", ""], ["1987-88", "1", "1988 1st Division", "Bent Christensen (21)", "Finalist", "EC3 2nd round", ""], ["2004-05", "1", "2004-05 Superliga", "Thomas Kahlenberg (13)", "Winner", "EC3 qual 2nd round", "Royal League group stage"], ["1983-84", "4", "1984 1st Division", "Jens Kolding (11)", "3rd round", "", ""], ["2011-12", "9", "2011-12 Superliga", "Simon Makienok Christoffersen (10)", "", "", ""], ["1999-00", "2", "1999-00 Superliga", "Bent Christensen (13)", "Semi-final", "EC1 qual 3rd round\\nEC3 1st round", ""], ["1984-85", "1", "1985 1st Division", "Claus Nielsen (17)", "3rd round", "", ""], ["2006-07", "6", "2006-07 Superliga", "Morten Rasmussen (15)", "4th round", "EC3 1st round", "Royal League winner\\nDanish League Cup winner"], ["2005-06", "2", "2005-06 Superliga", "Johan Elmander (13)", "Semi-final", "EC1 qual 3rd round\\nEC3 group stage", "Royal League group stage\\nDanish League Cup winner"], ["1992-93", "3", "1992-93 Superliga", "Kim Vilfort (10)", "5th round", "", ""], ["2010-11", "3", "2010-11 Superliga", "Michael Krohn-Dehli (11)", "", "", ""], ["1988-89", "2", "1989 1st Division", "Bent Christensen (10)", "Winner", "EC1 1st round", ""], ["2000-01", "2", "2000-01 Superliga", "Peter Graulund (21)", "Quarter-final", "EC1 qual 3rd round\\nEC3 1st round", ""], ["1990-91", "1", "1991 Superliga", "Bent Christensen (11)", "Semi-final", "EC3 semi-final", ""], ["1985-86", "2", "1986 1st Division", "Claus Nielsen (16)", "Quarter-final", "", ""], ["1994-95", "2", "1994-95 Superliga", "Mark Strudal (12)", "Quarter-final", "EC2 2nd round", "Danish Supercup winner"], ["1996-97", "1", "1996-97 Superliga", "Peter Møller (22)", "Semi-final", "EC1 qualification round\\nEC3 quarter-final", "Danish Supercup winner"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in total how many top scorers have scored more than 15 goals? | 10 | 128 | Answer: |
Table InputTable: [["Rank", "Diver", "Nationality", "Preliminary\\nPoints", "Preliminary\\nRank", "Final\\nPoints", "Final\\nRank"], ["", "Wang Han", "China", "306.60", "1", "310.20", "2"], ["26", "Choi Sut Ian", "Macau", "224.50", "26", "", ""], ["", "Shi Tingmao", "China", "294.65", "2", "318.65", "1"], ["17", "Sharon Chan", "Hong Kong", "245.10", "17", "", ""], ["36", "Lei Sio I", "Macau", "192.00", "36", "", ""], ["40", "Hsu Shi-Han", "Chinese Taipei", "146.15", "40", "", ""], ["20", "Sayaka Shibusawa", "Japan", "240.80", "20", "", ""], ["29", "Yuka Mabuchi", "Japan", "219.50", "29", "", ""], ["19", "Jun Hoong Cheong", "Malaysia", "241.95", "18", "", ""], ["38", "Huang En-Tien", "Chinese Taipei", "187.25", "38", "", ""], ["6", "Abby Johnston", "United States", "282.40", "4", "282.85", "6"], ["35", "Sari Ambarwati", "Indonesia", "200.05", "35", "", ""], ["7", "Sharleen Stratton", "Australia", "282.45", "3", "281.65", "7"], ["30", "Alicia Blagg", "Great Britain", "212.50", "30", "", ""], ["12", "Anastasia Pozdniakova", "Russia", "260.00", "8", "251.70", "12"], ["13", "Hanna Pysmenska", "Ukraine", "251.40", "13", "", ""], ["39", "Carolina Murillo", "Colombia", "181.85", "39", "", ""], ["28", "Julia Loennegren", "Sweden", "221.05", "28", "", ""], ["5", "Nadezhda Bazhina", "Russia", "262.75", "7", "286.20", "5"], ["9", "Kelci Bryant", "United States", "257.00", "11", "274.25", "9"], ["25", "Hannah Starling", "Great Britain", "226.40", "25", "", ""], ["8", "Anna Lindberg", "Sweden", "276.05", "5", "279.55", "8"], ["15", "Sophie Somloi", "Austria", "249.45", "15", "", ""], ["18", "Inge Jansen", "Netherlands", "241.95", "18", "", ""], ["10", "Olena Fedorova", "Ukraine", "258.30", "9", "274.15", "10"], ["16", "Uschi Freitag", "Germany", "247.70", "16", "", ""], ["14", "Jennifer Abel", "Canada", "250.95", "14", "", ""], ["27", "Marion Farissier", "France", "221.65", "27", "", ""], ["11", "Brittany Broben", "Australia", "257.10", "10", "267.20", "11"], ["21", "Jennifer Benitez", "Spain", "232.50", "21", "", ""], ["23", "Vianey Hernandez", "Mexico", "227.85", "23", "", ""], ["32", "Diana Pineda", "Colombia", "209.60", "32", "", ""], ["33", "Tina Punzel", "Germany", "206.05", "33", "", ""], ["4", "Maria Marconi", "Italy", "264.25", "6", "290.15", "4"], ["34", "Maria Florencia Betancourt", "Venezuela", "204.90", "34", "", ""], ["", "Tania Cagnotto", "Italy", "253.15", "12", "295.45", "3"], ["24", "Fanny Bouvet", "France", "227.10", "24", "", ""], ["37", "Leyre Eizaguirre", "Spain", "189.95", "37", "", ""], ["22", "Arantxa Chavez", "Mexico", "232.35", "22", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 wang han lose by? | 8.45 | 128 | Answer: |
Table InputTable: [["ZOOM", "Cast Member 1", "Cast Member 2", "Cast Member 3", "Cast Member 4", "Cast Member 5", "Cast Member 6", "Cast Member 7"], ["Season 1 (1999)", "Zoe Costello", "Jared Nathan", "Keiko Yoshida", "Pablo Velez, Jr.", "Alisa Besher", "David Toropov", "Lynese Browder"], ["Season 4 (2002)", "Aline Toupi", "Garrett DiBona", "Rachel Redd", "Matthew \"Matt\" Runyon", "Estuardo Alvizures", "Kaleigh Cronin", "Caroline Botelho"], ["Season 5 (2003)", "Caroline Botelho", "Aline Toupi", "Estuardo Alvizures", "Garrett DiBona", "Michael \"Mike\" Hansen", "Kortney Sumner", "Elena \"Shing Ying\" Shieh"], ["Season 2 (2000)", "Raymond \"Ray\" MacMore", "Caroline Botelho", "Claudio Schwartz", "Alisa Besher", "Jessica \"Jessie\" Ogungbadero", "Kenneth \"Kenny\" Yates", "Zoe Costello"], ["Season 7 (2005)", "W. Nick Henry", "Taylor Garron", "Francesco Tena", "Noreen Raja", "Emily Marshall", "Kyle Larrow", "Elena \"Shing Ying\" Shieh"], ["Season 3 (2001)", "Frances Domond", "Kenneth \"Kenny\" Yates", "Rachel Redd", "Eric Rollins", "Kaleigh Cronin", "Kevin \"Buzz\" Barrette", "Caroline Botelho"], ["Season 6 (2004)", "Michael \"Mike\" Hansen", "Kortney Sumner", "Francesco Tena", "Cara Harvey", "Kyle Larrow", "Maya Morales", "Elena \"Shing Ying\" Shieh"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 cast member 1 after aline toupi? | Caroline Botelho | 128 | Answer: |
Table InputTable: [["Stations", "Connections", "City/ Neighborhood", "Parking", "Date Opened"], ["Tampa", "Metro Local: 242", "Tarzana", "n/a", "October 29, 2005"], ["Reseda", "Metro Rapid: 741\\nMetro Local: 240", "Tarzana", "522 Spaces", "October 29, 2005"], ["Nordhoff", "Metro Local: 166, 364\\nLADOT DASH Northridge", "Chatsworth", "n/a", "June 30, 2012"], ["Warner Center", "Metro Local: 150, 161, 164, 245, 645\\nMetro Rapid: 750\\nLADOT Commuter Express: 422\\nCity of Santa Clarita Transit: 791, 796\\nVentura Intercity Service Transit Authority: Conejo Connection", "Woodland Hills", "n/a", "October 29, 2005"], ["Van Nuys", "Metro Local:154, 156, 233, 237, 656\\nMetro Rapid: 761\\nLADOT DASH: Van Nuys/Studio City\\nCity of Santa Clarita Transit: 793, 798", "Van Nuys", "776 Spaces", "October 29, 2005"], ["De Soto", "Metro Local: 164, 244\\nCity of Santa Clarita Transit: 796", "Winnetka", "n/a", "October 29, 2005"], ["Sepulveda", "Metro Local: 234\\nMetro Rapid: 734", "Van Nuys", "1,205 Spaces", "October 29, 2005"], ["Balboa", "Metro Local: 164, 236, 237\\nLADOT Commuter Express: 573, 574", "Lake Balboa", "270 Spaces", "October 29, 2005"], ["Canoga", "Metro Local:164, 165\\nCity of Santa Clarita Transit: 796", "Canoga Park", "612 Spaces", "December 27, 2006"], ["North Hollywood", "Metro Red Line \\nMetro Local: 152, 154, 156, 162, 183, 224, 353, 656\\nLADOT Commuter Express: 549\\nCity of Santa Clarita Transit: 757", "North Hollywood", "951 Spaces", "October 29, 2005"], ["Chatsworth", "Metro Local: 158, 166, 167, 244, 245, 364\\nLADOT Commuter Express: 419\\nSimi Valley Transit: C\\nSanta Clarita Transit: 791\\nMetrolink Ventura County Line\\nAmtrak Pacific Surfliner", "Chatsworth", "Parking Expanded", "June 30, 2012"], ["Roscoe", "Metro Local: 152, 353", "Canoga Park", "n/a", "June 30, 2012"], ["Woodley", "Metro Local:164, 237", "Van Nuys", "None", "October 29, 2005"], ["Valley College", "Metro Local: 156, 167, 656\\nLADOT Commuter Express: 549\\nLADOT DASH: Van Nuys/Studio City", "Valley Glen", "None", "October 29, 2005"], ["Pierce College", "Metro Local: 164, 243", "Winnetka", "373 Spaces", "October 29, 2005"], ["Laurel Canyon", "Metro Local: 156, 230, 656", "Valley Village", "None", "October 29, 2005"], ["Woodman", "Metro Local:154, 158", "Valley Glen", "None", "October 29, 2005"], ["Sherman Way", "Metro Local: 162, 163", "Canoga Park", "Park & Ride Lot", "June 30, 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:which station has a greater number of connetions, tampa or reseda? | Reseda | 128 | Answer: |
Table InputTable: [["Atomic\\nno.", "Name", "Symbol", "Group", "Period", "Block", "State at\\nSTP", "Occurrence", "Description"], ["38", "Strontium", "Sr", "2", "5", "s", "Solid", "Primordial", "Alkaline earth metal"], ["20", "Calcium", "Ca", "2", "4", "s", "Solid", "Primordial", "Alkaline earth metal"], ["12", "Magnesium", "Mg", "2", "3", "s", "Solid", "Primordial", "Alkaline earth metal"], ["99", "Einsteinium", "Es", "3", "7", "f", "Solid", "Synthetic", "Actinide"], ["56", "Barium", "Ba", "2", "6", "s", "Solid", "Primordial", "Alkaline earth metal"], ["55", "Caesium", "Cs", "1", "6", "s", "Solid", "Primordial", "Alkali metal"], ["4", "Beryllium", "Be", "2", "2", "s", "Solid", "Primordial", "Alkaline earth metal"], ["90", "Thorium", "Th", "3", "7", "f", "Solid", "Primordial", "Actinide"], ["92", "Uranium", "U", "3", "7", "f", "Solid", "Primordial", "Actinide"], ["98", "Californium", "Cf", "3", "7", "f", "Solid", "Transient", "Actinide"], ["95", "Americium", "Am", "3", "7", "f", "Solid", "Transient", "Actinide"], ["101", "Mendelevium", "Md", "3", "7", "f", "Solid", "Synthetic", "Actinide"], ["82", "Lead", "Pb", "14", "6", "p", "Solid", "Primordial", "Metal"], ["100", "Fermium", "Fm", "3", "7", "f", "Solid", "Synthetic", "Actinide"], ["88", "Radium", "Ra", "2", "7", "s", "Solid", "Transient", "Alkaline earth metal"], ["102", "Nobelium", "No", "3", "7", "f", "Solid", "Synthetic", "Actinide"], ["94", "Plutonium", "Pu", "3", "7", "f", "Solid", "Primordial", "Actinide"], ["34", "Selenium", "Se", "16", "4", "p", "Solid", "Primordial", "Non-metal"], ["87", "Francium", "Fr", "1", "7", "s", "Solid", "Transient", "Alkali metal"], ["75", "Rhenium", "Re", "7", "6", "d", "Solid", "Primordial", "Transition metal"], ["26", "Iron", "Fe", "8", "4", "d", "Solid", "Primordial", "Transition metal"], ["11", "Sodium", "Na", "1", "3", "s", "Solid", "Primordial", "Alkali metal"], ["5", "Boron", "B", "13", "2", "p", "Solid", "Primordial", "Metalloid"], ["32", "Germanium", "Ge", "14", "4", "p", "Solid", "Primordial", "Metalloid"], ["67", "Holmium", "Ho", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["103", "Lawrencium", "Lr", "3", "7", "d", "Solid", "Synthetic", "Actinide"], ["69", "Thulium", "Tm", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["19", "Potassium", "K", "1", "4", "s", "Solid", "Primordial", "Alkali metal"], ["52", "Tellurium", "Te", "16", "5", "p", "Solid", "Primordial", "Metalloid"], ["59", "Praseodymium", "Pr", "3", "6", "f", "Solid", "Primordial", "Lanthanide"], ["30", "Zinc", "Zn", "12", "4", "d", "Solid", "Primordial", "Transition metal"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 state are the most elements found in? | Solid | 128 | Answer: |
Table InputTable: [["Date", "Opponent", "Venue", "Result", "Attendance", "Scorers"], ["8 May 1993", "Southampton", "H", "4–3", "14,597", "Pointon, Olney, Ritchie, Halle"], ["15 August 1992", "Chelsea", "A", "1–1", "20,699", "Henry"], ["31 October 1992", "Southampton", "A", "0–1", "10,827", ""], ["6 February 1993", "Chelsea", "H", "3–1", "11,772", "Henry, Adams, Brennan"], ["7 April 1993", "Sheffield Wednesday", "H", "1–1", "12,312", "Pointon"], ["12 December 1992", "Wimbledon", "A", "2–5", "3,386", "Brennan, Milligan"], ["22 March 1993", "Middlesbrough", "A", "3–2", "12,290", "Bernard, Olney, Ritchie"], ["10 April 1993", "Liverpool", "A", "0–1", "36,129", ""], ["12 September 1992", "Crystal Palace", "A", "2–2", "11,224", "Olney, Sharp"], ["28 November 1992", "Middlesbrough", "H", "4–1", "12,401", "Halle, Pointon, Sharp, Adams"], ["20 March 1993", "Queens Park Rangers", "H", "2–2", "10,946", "Henry, Adams"], ["29 August 1992", "Manchester City", "A", "3–3", "27,288", "Jobson, Milligan, Halle"], ["17 October 1992", "Sheffield Wednesday", "A", "1–2", "24,485", "Milligan"], ["5 May 1993", "Liverpool", "H", "3–2", "15,381", "Beckford, Olney (2)"], ["20 February 1993", "Arsenal", "H", "0–1", "12,311", ""], ["9 November 1992", "Norwich City", "H", "2–3", "11,081", "Sharp, Marshall"], ["21 November 1992", "Manchester United", "A", "0–3", "33,497", ""], ["13 March 1993", "Norwich City", "A", "0–1", "19,597", ""], ["27 February 1993", "Everton", "A", "2–2", "18,025", "Adams (2, 1 pen)"], ["19 August 1992", "Crystal Palace", "H", "1–1", "11,063", "Sharp"], ["19 September 1992", "Ipswich Town", "H", "4–2", "11,150", "Marshall, Sharp, Halle, Henry"], ["23 January 1993", "Coventry City", "A", "0–3", "10,544", ""], ["26 August 1992", "Arsenal", "A", "0–2", "20,796", ""], ["5 December 1992", "Queens Park Rangers", "A", "2–3", "11,804", "Adams, Olney"], ["30 January 1993", "Nottingham Forest", "A", "0–2", "21,240", ""], ["22 February 1993", "Sheffield United", "A", "0–2", "14,628", ""], ["17 April 1993", "Tottenham Hotspur", "A", "1–4", "26,663", "Beckford"], ["9 March 1993", "Manchester United", "H", "1–0", "17,106", "Adams"], ["26 January 1993", "Manchester City", "H", "0–1", "14,903", ""], ["9 January 1993", "Ipswich Town", "A", "2–1", "15,025", "Brennan, Bernard"], ["22 August 1992", "Nottingham Forest", "H", "5–3", "11,632", "Adams, Sharp, Henry, Halle, Bernard"], ["13 April 1993", "Sheffield United", "H", "1–1", "14,795", "Ritchie"], ["19 December 1992", "Tottenham Hotspur", "H", "2–1", "11,735", "Sharp, Olney"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which date was attended by the least number of people? | 12 December 1992 | 128 | Answer: |
Table InputTable: [["Series", "Years", "Volumes", "Writer", "Editor", "Remarks"], ["Bruno Brazil", "1973–1977", "5", "Greg", "Magic-Strip", "William Vance drew the comics, Follet provided the page lay-out"], ["Harricana", "1992", "1", "Jean-Claude de la Royère", "Claude Lefrancq", "Drawn by Denis Mérezette, Follet did the page lay-out"], ["Marshall Blueberry", "1994", "1", "Jean Giraud", "Alpen", "Drawn by William Vance, Follet did the page lay-out"], ["Les autos de l'aventure", "1996–1998", "2", "De la Royère", "Citroën", "Promotional comics"], ["Ivan Zourine", "1979", "2", "Jacques Stoquart", "Magic-Strip", ""], ["Alain Brisant", "1985", "1", "Maurice Tillieux", "Dupuis", ""], ["Daddy", "1991-92", "2", "Loup Durand", "Cl. Lefrancq", ""], ["Bob Morane", "1991–2000", "3", "Henri Vernes", "Nautilus and Claude Lefrancq", "Follet drew one story in 2000, and made the cover art for two others (drawn by Gerald Forton)"], ["L'Iliade", "1982", "1", "Jacques Stoquart", "Glénat", "Adapted from the Ilias by Homer"], ["Ikar", "1995–1997", "2", "Pierre Makyo", "Glénat", ""], ["Jacques Le Gall", "1984–1985", "2", "Jean-Michel Charlier", "Dupuis", "A collaboration with MiTacq"], ["L'affaire Dominici", "2010", "1", "Pascal Bresson", "Glénat", ""], ["L'étoile du soldat", "2007", "1", "Christophe De Ponfilly", "Casterman", "Announced (28 August 2007)"], ["Shelena", "2005", "1", "Jéromine Pasteur", "Casterman", ""], ["Les zingari", "2004–2005", "2", "Yvan Delporte", "Hibou", ""], ["Terreur", "2002–2004", "2", "André-Paul Duchâteau", "Le Lombard", "Fictional biography of Madame Tussaud"], ["Edmund Bell", "1987–1990", "4", "Jacques Stoquart and Martin Lodewijk", "Cl. Lefrancq", "Based on the stories by John Flanders (Jean Ray)"], ["Valhardi", "1984–1986", "2", "Jacques Stoquart and André-Paul Duchâteau", "Dupuis", "Continuation of the series after Jijé and Eddy Paape"], ["Steve Severin", "1981–2003", "9", "Jacques Stoquart and Yvan Delporte", "Glénat", "3 in French - 6 additional in Dutch"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:the first comic to be published | Bruno Brazil | 128 | Answer: |
Table InputTable: [["Year", "Award", "Category", "Recipient", "Result"], ["2012", "Soompi Gayo Awards", "Top 50 Songs (#3)", "\"Heaven\"", "Won"], ["2013", "27th Golden Disk Awards", "Best New Artist", "Herself", "Won"], ["2012", "4th MelOn Music Awards", "Best New Artist", "Herself", "Won"], ["2014", "Soompi Music Awards", "Best Female Artist", "\"U&I\"", "Won"], ["2013", "5th MelOn Music Awards", "Top 10 Artists", "Herself", "Won"], ["2013", "15th Mnet Asian Music Awards", "Best Vocal Performance - Female", "\"U&I\"", "Won"], ["2012", "Asia Song Festival", "New Artist Award", "Herself", "Won"], ["2012", "Cyworld Digital Music Awards", "Rookie & Song of the Month (February)", "\"Heaven\"", "Won"], ["2013", "15th Mnet Asian Music Awards", "Artist of the Year", "Herself", "Nominated"], ["2013", "15th Mnet Asian Music Awards", "BC - UnionPay Song of the year", "\"U&I\"", "Nominated"], ["2012", "14th Mnet Asian Music Awards", "Best New Female Artist", "Herself", "Won"], ["2013", "15th Mnet Asian Music Awards", "Best Female Artist", "Herself", "Nominated"], ["2013", "2nd Gaon Chart K-Pop Awards", "New Female Solo Artist", "Herself", "Won"], ["2013", "23rd Seoul Music Awards", "Rookie Award", "Herself", "Won"], ["2014", "28th Golden Disk Awards", "Digital Bonsang", "\"U&I\"", "Won"], ["2012", "So-Loved Awards", "Best Female Newcomer", "Herself", "Won"], ["2013", "Mnet Pre-Grammy Awards", "Mnet Rising Star", "Herself", "Won"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of best f male artist won overall? | 2 | 128 | Answer: |
Table InputTable: [["Year", "Matches", "Winner", "Results", "Pakistan\\nCaptain", "Pakistan\\nCoach", "India\\nCaptain", "India\\nCoach"], ["1986", "7", "India win", "3 - 2", "Hassan Sardar", "Anwar Ahmad Khan", "Mohmmad Shaheed", "M. P. Ganesh"], ["1981", "4", "Pakistan win", "2 - 1", "Akhtar Rasool", "Zakauddin", "Surjeet Singh", "Harmeek Singh"], ["1978", "4", "Pakistan win", "3 - 1", "Islahuddin Siddique", "Sayad A. Hussain", "V. J. Philips", "R. S. Gentle"], ["1998", "8", "Pakistan win", "4 - 3", "Tahir Zaman", "Islahuddin Siddique", "Dhanraj Pillay", "V Bhaskaran"], ["2006", "6", "Pakistan win", "3 - 1", "Mohammad Saqlain", "Asif Bajwa", "Ignace Tirkey", "Rajinder Singh Jr."], ["1999", "9", "Pakistan win", "5 - 3", "Atif Bashir", "Shahnaz Shaikh", "Anil Aldrin", "V Bhaskaran"], ["2004", "8", "Pakistan win", "4 - 2", "Waseem Ahmad", "Roelant Oltmans", "Dileep Tirkey", "Gehard Rach"], ["1988", "6", "Draw", "2 - 2", "Nasir Ali", "Manzoor-ul-Hasan", "M. M. Somaya", "M. P. Ganesh"], ["2013", "TBA", "TBA", "TBA", "TBA", "TBA", "TBA", "TBA"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what year was the only time india has won in the rivalry? | 1986 | 128 | Answer: |
Table InputTable: [["Single / EP", "Tracks", "Label", "Year", "Album"], ["2012 – Remix Contest EP", "2012 (Remastered)", "Burn The Fire", "2012", "The Agenda"], ["Doin' It Right", "Doin' It Right", "Burn The Fire", "2009", "—"], ["Louder Than Bombs", "Louder Than Bombs", "Burn The Fire", "2012", "The Agenda"], ["Rave To The Grave", "Raver Booty\\nShuffle", "Burn The Fire", "2010", "—"], ["Hot & Cold", "Overdose", "Burn The Fire", "2010", "—"], ["Die Famous", "Die Famous", "Burn The Fire", "2011", "—"], ["Los Angeles", "Los Angeles\\nLos Angeles feat. Whiskey Pete (Clean Mix)\\nLos Angeles feat. Whiskey Pete (Dirty Mix)", "Burn The Fire", "2010", "The Agenda"], ["Drop Bears", "Drop Bears", "Burn The Fire", "2013", "—"], ["Still Smoking", "Nasty & Gaspar Still Smoking", "Burn The Fire", "2010", "—"], ["Onslaught", "Onslaught", "Burn The Fire", "2012", "The Agenda"], ["Fresh Attire Vol. 3", "Crush Groovin'", "Wearhouse Music", "2009", "—"], ["Those Who From Heaven To Earth Came", "The Lizard King\\nAnnunaki", "Burn The Fire", "2010", "—"], ["Hyped", "Hyped", "Vicious", "2014", "—"], ["Redroid", "Redroid", "Temple Music Group", "2011", "—"], ["Your Love Is Electric", "Your Love Is Electric", "Burn The Fire", "2009", "—"], ["Ghetto Ass Bitches", "Ghetto Ass Bitches", "Burn The Fire", "2010", "—"], ["Ancient Psychic Tandem War Elephant", "Ancient Psychic Tandem War Elephant", "Burn The Fire", "2011", "—"], ["Breakdown", "Breakdown", "Burn The Fire", "2009", "—"], ["Dutchie", "Dutchie", "Burn The Fire", "2010", "—"], ["Deception", "Deception", "Burn The Fire", "2012", "The Agenda"], ["The Thirteenth Skull", "The Thirteenth Skull", "Burn The Fire", "2010", "—"], ["The Flying Cat", "The Flying Cat", "Burn The Fire", "2010", "—"], ["Left To Right", "Left To Right", "Destination?", "2009", "—"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 year had the most releases? | 2010 | 128 | Answer: |
Table InputTable: [["Pos", "Rider", "Manufactuer", "Time/Retired", "Points"], ["22", "Massimo Pennacchioli", "Honda", "+1:59.498", ""], ["1", "Doriano Romboni", "Honda", "33:53.776", "25"], ["21", "Adrian Bosshard", "Honda", "+1:47.492", ""], ["11", "Alberto Puig", "Honda", "+25.136", "5"], ["17", "Adi Stadler", "Honda", "+1:16.349", ""], ["Ret", "Volker Bähr", "Honda", "Retirement", ""], ["2", "Loris Capirossi", "Honda", "+0.090", "20"], ["20", "Gabriele Debbia", "Honda", "+1:40.049", ""], ["3", "Helmut Bradl", "Honda", "+0.384", "16"], ["9", "Carlos Cardús", "Honda", "+4.893", "7"], ["10", "Luis d'Antin", "Honda", "+25.044", "6"], ["4", "Max Biaggi", "Honda", "+2.346", "13"], ["15", "Juan Borja", "Honda", "+1:15.769", "1"], ["DNS", "Nobuatsu Aoki", "Honda", "Did not start", ""], ["13", "Jochen Schmid", "Yamaha", "+47.065", "3"], ["6", "Tetsuya Harada", "Yamaha", "+2.537", "10"], ["12", "John Kocinski", "Suzuki", "+25.463", "4"], ["24", "Alessandro Gramigni", "Gilera", "+1 Lap", ""], ["19", "Paolo Casoli", "Gilera", "+1:26.061", ""], ["7", "Pierfrancesco Chili", "Yamaha", "+3.845", "9"], ["Ret", "Jean-Pierre Jeandat", "Aprilia", "Retirement", ""], ["8", "Jean-Philippe Ruggia", "Aprilia", "+3.985", "8"], ["16", "Frédéric Protat", "Aprilia", "+1:15.858", ""], ["23", "Bernard Haenggeli", "Aprilia", "+2:41.806", ""], ["Ret", "Jurgen van den Goorbergh", "Aprilia", "Retirement", ""], ["Ret", "Andreas Preining", "Aprilia", "Retirement", ""], ["Ret", "Luis Maurel", "Aprilia", "Retirement", ""], ["Ret", "Wilco Zeelenberg", "Aprilia", "Retirement", ""], ["Ret", "Patrick van den Goorbergh", "Aprilia", "Retirement", ""], ["14", "Jean-Michel Bayle", "Aprilia", "+1:15.546", "2"], ["5", "Loris Reggiani", "Aprilia", "+2.411", "11"], ["Ret", "Eskil Suter", "Aprilia", "Retirement", ""], ["18", "Bernd Kassner", "Aprilia", "+1:16:464", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what are the number of times honda is listed as the manufacturer? | 13 | 128 | Answer: |
Table InputTable: [["Date", "Time", "", "Score", "", "Set 1", "Set 2", "Set 3", "Set 4", "Set 5", "Total", "Report"], ["18 Nov", "14:00", "Russia", "3–0", "Tunisia", "25–15", "29–27", "25–20", "", "", "79–62", "P2 P3"], ["22 Nov", "14:00", "Kazakhstan", "0–3", "Tunisia", "19–25", "23–25", "24–26", "", "", "66–76", "P2 P3"], ["17 Nov", "18:00", "Tunisia", "3–2", "South Korea", "25–22", "24–26", "17–25", "28–26", "15–13", "109–112", "P2 P3"], ["21 Nov", "18:50", "Russia", "3–0", "Kazakhstan", "25–16", "25–18", "25–18", "", "", "75–52", "P2 P3"], ["19 Nov", "16:15", "Tunisia", "0–3", "Serbia and Montenegro", "21–25", "12–25", "23–25", "", "", "56–75", "P2 P3"], ["17 Nov", "16:00", "Russia", "0–3", "Serbia and Montenegro", "22–25", "18–25", "23–25", "", "", "63–75", "P2 P3"], ["22 Nov", "18:00", "South Korea", "0–3", "Russia", "13–25", "21–25", "13–25", "", "", "47–75", "P2 P3"], ["21 Nov", "14:00", "Tunisia", "2–3", "Canada", "15–25", "29–27", "25–21", "21–25", "13–15", "103–113", "P2 P3"], ["18 Nov", "16:00", "Serbia and Montenegro", "3–1", "Kazakhstan", "25–16", "22–25", "25–18", "25–22", "", "97–81", "P2 P3"], ["17 Nov", "14:00", "Canada", "3–0", "Kazakhstan", "25–21", "26–24", "25–21", "", "", "76–66", "P2 P3"], ["19 Nov", "18:00", "Canada", "0–3", "Russia", "19–25", "20–25", "21–25", "", "", "60–75", "P2 P3"], ["19 Nov", "14:00", "Kazakhstan", "1–3", "South Korea", "22–25", "25–23", "18–25", "21–25", "", "86–98", "P2 P3"], ["22 Nov", "16:00", "Canada", "0–3", "Serbia and Montenegro", "18–25", "18–25", "17–25", "", "", "53–75", "P2 P3"], ["21 Nov", "16:35", "Serbia and Montenegro", "3–1", "South Korea", "25–22", "23–25", "25–21", "25–18", "", "98–86", "P2 P3"], ["18 Nov", "18:10", "South Korea", "1–3", "Canada", "28–26", "23–25", "16–25", "23–25", "", "90–101", "P2 P3"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:did russia or tunisia win on the 18th of november? | Russia | 128 | Answer: |
Table InputTable: [["No. in\\nseries", "No. in\\nseason", "Title", "Directed by", "Written by", "Original air date", "Prod.\\ncode"], ["5", "2", "\"A Cup of Kindness\"", "Leo Penn", "Morton Fine & David Friedkin", "September 22, 1965", "102"], ["27", "26", "\"There was a Little Girl\"", "John Rich", "Teleplay by: Stephen Kandell Story by: Robert Bloch", "April 6, 1966", "126"], ["4", "7", "\"Danny was a Million Laughs\"", "Mark Rydell", "Arthur Dales", "October 27, 1965", "107"], ["8", "6", "\"The Loser\"", "Mark Rydell", "Robert Culp", "October 20, 1965", "106"], ["13", "13", "\"Tigers of Heaven\"", "Allen Reisner", "Morton Fine & David Friedkin", "December 15, 1965", "113"], ["25", "24", "\"Crusade to Limbo\"", "Richard Sarafian", "Teleplay by: Morton Fine & David Freidkin & Jack Turley Story by: Jack Turley", "March 23, 1966", "124"], ["18", "18", "\"Court of the Lion\"", "Robert Culp", "Robert Culp", "February 2, 1966", "118"], ["19", "19", "\"Turkish Delight\"", "Paul Wendkos", "Eric Bercovici", "February 9, 1966", "119"], ["17", "16", "\"The Barter\"", "Allen Reisner", "Harvey Bullock & P.S. Allen", "January 12, 1966", "116"], ["15", "17", "\"Always Say Goodbye\"", "Allen Reisner", "Robert C. Dennis & Earl Barrett", "January 26, 1966", "117"], ["21", "21", "\"Return to Glory\"", "Robert Sarafian", "David Friedkin & Morton Fine", "February 23, 1966", "121"], ["2", "3", "\"Carry Me Back to Old Tsing-Tao\"", "Mark Rydell", "David Karp", "September 29, 1965", "103"], ["16", "15", "\"The Tiger\"", "Paul Wendkos", "Robert Culp", "January 5, 1966", "115"], ["7", "5", "\"Dragon's Teeth\"", "Leo Penn", "Gilbert Ralston", "October 13, 1965", "105"], ["1", "14", "\"Affair in T'Sien Cha\"", "Sheldon Leonard", "Morton Fine & David Friedkin", "December 29, 1965", "114"], ["28", "27", "\"It's All Done with Mirrors\"", "Robert Butler", "Stephen Kandell", "April 13, 1966", "127"], ["3", "1", "\"So Long, Patrick Henry\"", "Leo Penn", "Robert Culp", "September 15, 1965", "101"], ["23", "23", "\"A Day Called 4 Jaguar\"", "Richard Sarafian", "Michael Zagar", "March 9, 1966", "123"], ["10", "8", "\"The Time of the Knife\"", "Paul Wendkos", "Gilbert Ralston", "November 3, 1965", "108"], ["26", "25", "\"My Mother, The Spy\"", "Richard Benedict", "Howard Gast", "March 30, 1966", "125"], ["22", "22", "\"The Conquest of Maude Murdock\"", "Paul Wendkos", "Robert C. Dennis & Earl Barrett", "March 2, 1966", "122"], ["11", "10", "\"Tatia\"", "David Friedkin", "Robert Lewin", "November 17, 1965", "110"], ["14", "12", "\"Three Hours on a Sunday\"", "Paul Wendkos", "Morton Fine & David Friedkin", "December 8, 1965", "112"], ["9", "9", "\"No Exchange on Damaged Merchandise\"", "Leo Penn", "Gary Marshall & Jerry Belson", "November 10, 1965", "109"], ["20", "20", "\"Bet Me a Dollar\"", "Richard Sarafian", "David Friedkin & Morton Fine", "February 16, 1966", "120"], ["12", "11", "\"Weight of the World\"", "Paul Wendkos", "Robert Lewin", "December 1, 1965", "111"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which episode was next after "a cup of kindness" in season? | "Carry Me Back to Old Tsing-Tao" | 128 | Answer: |
Table InputTable: [["Week", "Date", "Opponent", "Results\\nFinal score", "Results\\nTeam record", "Venue", "Attendance"], ["8", "November 5", "New Orleans Saints", "W 37–6", "4–4", "Metropolitan Stadium", "49,784"], ["1", "September 18", "Washington Redskins", "L 24–21", "0–1", "Metropolitan Stadium", "47,900"], ["5", "October 15", "at Denver Broncos", "W 23–20", "2–3", "Mile High Stadium", "51,656"], ["2", "September 24", "at Detroit Lions", "W 34–10", "1–1", "Tiger Stadium", "54,418"], ["9", "November 12", "Detroit Lions", "W 16–14", "5–4", "Metropolitan Stadium", "49,784"], ["11", "November 26", "at Pittsburgh Steelers", "L 23–10", "6–5", "Three Rivers Stadium", "50,348"], ["3", "October 1", "Miami Dolphins", "L 16–14", "1–2", "Metropolitan Stadium", "47,900"], ["7", "October 29", "at Green Bay Packers", "W 27–13", "3–4", "Lambeau Field", "56,263"], ["12", "December 3", "Chicago Bears", "W 23–10", "7–5", "Metropolitan Stadium", "49,784"], ["4", "October 8", "St. Louis Cardinals", "L 19–17", "1–3", "Metropolitan Stadium", "49,687"], ["13", "December 10", "Green Bay Packers", "L 23–7", "7–6", "Metropolitan Stadium", "49,784"], ["14", "December 16", "at San Francisco 49ers", "L 20–17", "7–7", "Candlestick Park", "61,214"], ["6", "October 23", "at Chicago Bears", "L 13–10", "2–4", "Soldier Field", "55,701"], ["10", "November 19", "at Los Angeles Rams", "W 45–41", "6–4", "Los Angeles Memorial Coliseum", "77,982"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 which venue did the vikings play after they played in mile high stadium? | Soldier Field | 128 | Answer: |
Table InputTable: [["Team 1", "Agg.", "Team 2", "1st leg", "2nd leg"], ["Jaén", "1–4", "Real Unión", "1–1", "0–3"], ["Figueres", "3–4", "Racing Santander", "1–2", "2–2"], ["Alcalá", "1–10", "Valencia", "1–3", "0–7"], ["Español Raspeig", "0–1", "Mirandés", "0–0", "0–1"], ["Europa", "3–8", "Málaga", "3–3", "0–5"], ["Algeciras", "2–10", "Real Madrid", "0–6", "2–4"], ["Langreo", "1–3", "Granada", "1–0", "0–3"], ["Tudelano", "3–6", "Sporting Gijón", "2–1", "1–5"], ["Ontinyent", "1–0", "Torrejón", "1–0", "0–0"], ["Orihuela", "0–3", "Alavés", "0–1", "0–2"], ["Reus", "0–5", "Zaragoza", "0–0", "0–5"], ["San Fernando", "5–1", "Nàstic Tarragona", "4–1", "1–0"], ["Talavera", "2–0", "Arosa", "2–0", "0–0"], ["Racing Ferrol", "3–5", "Real Murcia", "2–0", "1–5"], ["Peña Sport", "0–4", "Valladolid", "0–2", "0–2"], ["Fabril", "0–7", "Hércules", "0–3", "0–4"], ["Real Sociedad", "3–3 (8–7 p)", "Xerez", "1–1", "2–2"], ["Celta", "2–1", "Cartagena", "2–0", "0–1"], ["Atlético Baleares", "2–3", "Cádiz", "1–0", "1–3"], ["Almansa", "1–4", "Rayo Vallecano", "0–2", "1–2"], ["Real Madrid Castilla", "5–5 (3–4 p)", "Sabadell", "4–3", "1–2"], ["Valladolid Promesas", "1–3", "Elche", "0–2", "1–1"], ["Sariñena", "1–5", "Rayo Cantabria", "0–2", "1–3"], ["Oviedo", "4–1", "Cultural Leonesa", "2–0", "2–1"], ["Carabanchel", "5–2", "Calvo Sotelo", "4–1", "1–1"], ["Leganés", "1–5", "Eldense", "1–2", "0–3"], ["Levante", "9–2", "Moscardó", "5–0", "4–2"], ["Tenerife", "2–1", "Malgrat", "2–0", "0–1"], ["Marbella", "4–3", "Gimnástica Torrelavega", "4–1", "0–2"], ["Recreativo", "4–2", "Linense", "2–0", "2–2"], ["Burgos", "4–1", "Huesca", "2–0", "2–1"], ["Osasuna", "4–1", "Guadalajara", "2–0", "2–1"], ["Córdoba", "3–1", "Bilbao Athletic", "1–0", "2–1"], ["Ceuta", "1–6", "Espanyol", "1–1", "0–5"], ["Sevilla", "4–1", "Sant Andreu", "2–0", "2–1"], ["Valencia Mestalla", "4–2", "Sevilla Atlético", "3–0", "1–2"], ["Ciempozuelos", "3–2", "Lleida", "2–1", "1–1"], ["Girona", "5–1", "Alcoyano", "3–0", "2–1"], ["Toledo", "3–3 (4–3 p)", "Badajoz", "2–0", "1–3"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 teams listed? | 84 | 128 | Answer: |
Table InputTable: [["School", "2007", "2008", "2009", "2010", "2011"], ["Santee Education Complex", "", "502", "521", "552", "565"], ["Marc and Eva Stern Math and Science School", "718", "792", "788", "788", "809"], ["James A. Garfield High School", "553", "597", "593", "632", "705"], ["Francisco Bravo Medical Magnet High School", "807", "818", "815", "820", "832"], ["Woodrow Wilson High School", "582", "585", "600", "615", "636"], ["Abraham Lincoln High School", "594", "609", "588", "616", "643"], ["Thomas Jefferson High School", "457", "516", "514", "546", "546"], ["Oscar De La Hoya Animo Charter High School", "662", "726", "709", "710", "744"], ["Theodore Roosevelt High School", "557", "551", "576", "608", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many schools are in the following chart? | 9 | 128 | Answer: |
Table InputTable: [["Series", "Premiere", "Finale", "Winner", "Runner-up", "Third place", "Host(s)", "Judging panel", "Guest judge(s)"], ["Three", "11 April 2009", "30 May 2009", "Diversity", "Susan Boyle", "Julian Smith", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nPiers Morgan", "Kelly Brook"], ["One", "9 June 2007", "17 June 2007", "Paul Potts", "Damon Scott", "Connie Talbot", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nPiers Morgan", "N/A"], ["Eight", "12 April 2014", "31 May 2014", "TBA", "TBA", "TBA", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams", "Ant & Dec"], ["Two", "12 April 2008", "31 May 2008", "George Sampson", "Signature", "Andrew Johnston", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nPiers Morgan", "N/A"], ["Seven", "13 April 2013", "8 June 2013", "Attraction", "Jack Carroll", "Richard & Adam", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams", "N/A"], ["Four", "17 April 2010", "5 June 2010", "Spelbound", "Twist and Pulse", "Kieran Gaffney", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nPiers Morgan", "Louis Walsh"], ["Five", "16 April 2011", "4 June 2011", "Jai McDowall", "Ronan Parke", "New Bounce", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nDavid Hasselhoff\\nMichael McIntyre", "Louis Walsh"], ["Six", "24 March 2012", "12 May 2012", "Ashleigh and Pudsey", "Jonathan and Charlotte", "Only Boys Aloud", "Ant & Dec", "Simon Cowell\\nAmanda Holden\\nAlesha Dixon\\nDavid Walliams", "Carmen Electra"], ["Nine", "2015", "2015", "TBA", "TBA", "TBA", "Ant & Dec", "TBA", "TBA"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the first guest judge after kelly brook? | Louis Walsh | 128 | Answer: |
Table InputTable: [["Date", "Festival", "Location", "Awards", "Link"], ["Sep 28", "Fantastic Fest", "Austin, Texas\\n USA", "", "FantasticFest.com"], ["Oct 9, Oct 11", "Sitges Film Festival", "Sitges, Catalonia\\n Spain", "", "Sitges Festival"], ["Oct 1, Oct 15", "Gwacheon International SF Festival", "Gwacheon, Gyeonggi-do\\n South Korea", "", "gisf.org"], ["Nov 16–18", "AFF", "Wrocław, Lower Silesia\\n Poland", "", "AFF Poland"], ["Feb 2–5, Feb 11", "Santa Barbara International Film Festival", "Santa Barbara, California USA", "Top 11 \"Best of the Fest\" Selection", "sbiff.org"], ["Oct 9", "London Int. Festival of Science Fiction Film", "London, England\\n UK", "Closing Night Film", "Sci-Fi London"], ["Sep 19", "Lund International Fantastic Film Festival", "Lund, Skåne\\n Sweden", "", "fff.se"], ["Nov 12, Nov 18", "Indonesia Fantastic Film Festival", "Jakarta, Bandung\\n Indonesia", "", "inaff.com"], ["Nov 11", "Les Utopiales", "Nantes, Pays de la Loire\\n France", "", "utopiales.org"], ["Jul 18, Jul 25", "Fantasia Festival", "Montreal, Quebec Canada", "Special Mention\\n\"for the resourcefulness and unwavering determination by a director to realize his unique vision\"", "FanTasia"], ["Sep 16", "Athens International Film Festival", "Athens, Attica\\n Greece", "Best Director", "aiff.gr"], ["May 21–22, Jun 11", "Seattle International Film Festival", "Seattle, Washington USA", "", "siff.net"], ["Oct 17, Oct 20", "Icon TLV", "Tel Aviv, Central\\n Israel", "", "icon.org.il"], ["Oct 23", "Toronto After Dark", "Toronto, Ontario\\n Canada", "Best Special Effects\\nBest Musical Score", "torontoafterdark.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:name of the festivals that had at least 2 dates. | Santa Barbara International Film Festival, Seattle International Film Festival, Fantasia Festival, Sitges Film Festival, Gwacheon International SF Festival, Icon TLV, Indonesia Fantastic Film Festival, AFF | 128 | Answer: |
Table InputTable: [["Band", "Disc/Song", "Released", "Disc Description", "Disk Size", "Image"], ["Barnes & Barnes", "Fish Heads: Barnes & Barnes' Greatest Hits", "1982", "Shaped as a fish head", "12\"", ""], ["Guns N' Roses", "Paradise City", "1989", "Shape of a Colt \"Peacemaker\"", "7\"", ""], ["Guns N' Roses", "Nightrain", "1989", "Shape of a suitcase", "7\"", ""], ["Red Box", "Lean On Me b/w Stinging Bee", "1985", "Hexagonal red vinyl. Looks like a red box in 2D; flipside is a band photo.", "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\"", ""], ["Saxon", "Back on the Streets Again", "", "Shaped as an apple (as is printed on one side of the disk).", "7\"", ""], ["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\"", ""], ["Guns N' Roses", "Sweet Child o' Mine", "1988", "Shape of the classic logo of the cross and skulls of the five band members", "7\"", ""], ["Monster Magnet", "Dopes to Infinity", "1995", "Shaped like the lead singer Dave Wyndorf's head.", "12\"", ""], ["U2", "The Unforgettable Fire (single)", "1985", "Shaped as letter & number \"U2\" with various pictures of the band from the period.", "7\"", "U2"], ["Monster Magnet", "Negasonic Teenage Warhead", "", "Shaped like a mushroom cloud", "12\"", ""], ["Gary Numan", "Warriors", "1983", "Shaped like a Jet Fighter.", "7\"", ""], ["Joe Strummer", "Love Kills", "", "Shaped like a gun", "7\"", "A gun"], ["The Fat Boys", "Wipe Out", "", "Shaped like a Hamburger", "7\"", ""], ["Gary Numan", "Berserker", "1984", "Shaped like Numan's head.", "7\"", ""], ["The Mars Volta", "Mr. Muggs", "2008", "In the shape of a clear planchette.", "7\"", ""], ["Devo", "Beautiful World b/w Nu-Tra", "1981", "Shaped like an astronaut head", "", ""], ["Men Without Hats", "I Got the Message", "1983", "", "", ""], ["Killing Joke", "Loose Cannon", "2003", "shaped yellow evil clown head image from the eponymous 2003 album sleeve", "", ""], ["Yeah Yeah Yeahs", "Cheated Hearts", "2006", "Heart shaped.", "7\"", ""], ["Broken English", "Comin on Strong", "1987", "Shaped as the 3 band members wearing Ghostbusters outfits holding guitars.", "", ""], ["Kiss", "Lick It Up", "1983", "Shaped like an armored tank", "", ""], ["Gangrene", "Sawblade EP", "2010", "In the shape of a circular sawblade.", "", ""], ["Men Without Hats", "The Safety Dance", "1982", "Oddly shaped picture disc of a man and a woman dancing", "", ""], ["Less Than Jake", "Cheese", "1998", "Shaped like a piece of swiss cheese. 1000 pressed in yellow. 500 pressed in green (\"Moldy Version\").", "7\"", ""], ["OMD", "La Femme Accident", "1985", "", "", ""], ["Tangerine Dream", "Warsaw in the Sun", "1984", "The record is in the shape of Poland and has several images including Lech Wałęsa and Pope John Paul II.", "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:list the bands that had the same disk size as barnes & barnes. | Monster Magnet | 128 | Answer: |
Table InputTable: [["Number", "Name", "Service", "From", "To"], ["(Acting)", "COL George W. McIver", "USA", "September 18, 1916", "October 26, 1916"], ["(Acting)", "Maj Gen Winston P. Wilson", "USAF", "June 1, 1959", "July 19, 1959"], ["17", "Maj Gen Winston P. Wilson", "USAF", "August 31, 1963", "August 31, 1971"], ["24", "Lt Gen Russell C. Davis", "USAF", "August 4, 1998", "August 3, 2002"], ["26", "Gen Craig R. McKinley", "USAF", "November 17, 2008", "September 6, 2012"], ["(Acting)", "MG John R. D'Araujo, Jr.", "USA", "August 1, 1994", "September 30, 1994"], ["13", "MG Kenneth F. Cramer", "USA", "September 30, 1947", "September 4, 1950"], ["16", "MG Donald W. McGowan", "USA", "July 20, 1959", "August 30, 1963"], ["18", "MG Francis S. Greenlief", "USA", "September 1, 1971", "June 23, 1974"], ["(Acting)", "Maj Gen Earl T. Ricks", "USAF", "February 16, 1953", "June 21, 1953"], ["(Acting)", "MG Raymond F. Rees", "USA", "January 2, 1994", "July 31, 1994"], ["(Acting)", "Maj Gen Philip G. Killey", "USAF", "December 2, 1993", "January 1, 1994"], ["12", "MG Butler B. Miltonberger", "USA", "February 1, 1946", "September 29, 1947"], ["5", "MG Jesse McI. Carter", "USA", "November 26, 1917", "August 15, 1918"], ["(Acting)", "COL John F. Williams", "USA", "January 17, 1936", "January 30, 1936"], ["8", "MG William G. Everson", "USA", "October 1, 1929", "November 30, 1931"], ["(Acting)", "MG John F. Williams", "USA", "January 31, 1944", "January 31, 1946"], ["(Acting)", "BG John W. Heavey", "USA", "August 15, 1918", "February 5, 1919"], ["23", "LTG Edward D. Baca", "USA", "October 1, 1994", "July 31, 1998"], ["15", "MG Edgar C. Erickson", "USA", "June 22, 1953", "May 31, 1959"], ["11", "MG John F. Williams", "USA", "January 31, 1940", "January 30, 1944"], ["7", "MG Creed C. Hammond", "USA", "June 29, 1925", "June 28, 1929"], ["5", "MG Jesse McI. Carter", "USA", "February 5, 1919", "June 28, 1921"], ["25", "LTG H Steven Blum", "USA", "April 11, 2003", "November 17, 2008"], ["(Acting)", "MG Raymond F. Rees", "USA", "August 4, 2002", "April 10, 2003"], ["(Acting)", "COL Ernest R. Redmond", "USA", "June 29, 1929", "September 30, 1929"], ["27", "GEN Frank J. Grass", "USA", "September 7, 2012", "Present"], ["22", "Lt Gen John B. Conaway", "USAF", "February 1, 1990", "December 1, 1993"], ["3", "MG Albert L. Mills", "USA", "September 1, 1912", "September 18, 1916"], ["10", "MG Albert H. Blanding", "USA", "January 31, 1936", "January 30, 1940"], ["20", "LTG Emmett H. Walker, Jr.", "USA", "August 16, 1982", "August 15, 1986"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the number of the most consecutive (acting) chiefs? | 3 | 128 | Answer: |
Table InputTable: [["Representative", "Title", "Presentation\\nof Credentials", "Termination\\nof Mission", "Appointed by"], ["Mary Kramer", "Ambassador Extraordinary and Plenipotentiary", "February 5, 2004", "October 30, 2006", "George W. Bush"], ["Earl Norfleet Phillips", "Ambassador Extraordinary and Plenipotentiary", "March 26, 2002", "June 1, 2003", "George W. Bush"], ["Mary Martin Ourisman", "Ambassador Extraordinary and Plenipotentiary", "January 18, 2007", "2008", "George W. Bush"], ["Larry Leon Palmer", "Ambassador Extraordinary and Plenipotentiary", "2012", "incumbent", "Barack Obama"], ["Frank V. Ortiz, Jr.", "Ambassador Extraordinary and Plenipotentiary", "July 29, 1977", "May 15, 1979", "Jimmy Carter"], ["Sally Shelton-Colby", "Ambassador Extraordinary and Plenipotentiary", "July 23, 1979", "February 24, 1981", "Jimmy Carter"], ["Annette T. Veler", "Chargé d'Affaires", "July 1991", "July 1993", "George H. W. Bush"], ["Theodore R. Britton, Jr.", "Ambassador Extraordinary and Plenipotentiary", "February 25, 1975", "April 22, 1977", "Gerald Ford"], ["Jeanette W. Hyde", "Ambassador Extraordinary and Plenipotentiary", "April 4, 1995", "January 31, 1998", "Bill Clinton"], ["James A. Daley", "Ambassador Extraordinary and Plenipotentiary", "October 17, 2000", "March 1, 2001", "Bill Clinton"], ["Loren E. Lawrence", "Chargé d'Affaires ad interim", "March 1984", "December 1984", "Ronald Reagan"], ["Roy T. Haverkamp", "Chargé d'Affaires ad interim", "December 1984", "March 1986", "Ronald Reagan"], ["E. William Crotty", "Ambassador Extraordinary and Plenipotentiary", "January 30, 1999", "October 10, 1999", "Bill Clinton"], ["Charles A. Gillespie", "Chargé d'Affaires ad interim", "February 2, 1984", "March 1984", "Ronald Reagan"], ["Dennis F. Carter", "Chargé d'Affaires", "December 1994", "March 1995", "Bill Clinton"], ["Ollie P. Anderson, Jr.", "Chargé d'Affaires", "September 1993", "September 1994", "Bill Clinton"], ["James Ford Cooper", "Chargé d'Affaires", "June 1988", "January 1991", "Ronald Reagan"], ["John C. Leary", "Chargé d'Affaires ad interim", "March 1986", "January 9, 1987", "Ronald Reagan"], ["John C. Leary", "Chargé d'Affaires", "January 9, 1987", "May 1988", "Ronald Reagan"], ["Christopher Sandrolini", "Chargé d'Affaires ad interim", "June 19, 2011", "2012", ""], ["Brent Hardt", "Chargé d'Affaires ad interim", "January 1, 2009", "June 19, 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:who was the last ambassador under george w. bush? | Mary Martin Ourisman | 128 | Answer: |
Table InputTable: [["ZOOM", "Cast Member 1", "Cast Member 2", "Cast Member 3", "Cast Member 4", "Cast Member 5", "Cast Member 6", "Cast Member 7"], ["Season 3 (2001)", "Frances Domond", "Kenneth \"Kenny\" Yates", "Rachel Redd", "Eric Rollins", "Kaleigh Cronin", "Kevin \"Buzz\" Barrette", "Caroline Botelho"], ["Season 1 (1999)", "Zoe Costello", "Jared Nathan", "Keiko Yoshida", "Pablo Velez, Jr.", "Alisa Besher", "David Toropov", "Lynese Browder"], ["Season 7 (2005)", "W. Nick Henry", "Taylor Garron", "Francesco Tena", "Noreen Raja", "Emily Marshall", "Kyle Larrow", "Elena \"Shing Ying\" Shieh"], ["Season 2 (2000)", "Raymond \"Ray\" MacMore", "Caroline Botelho", "Claudio Schwartz", "Alisa Besher", "Jessica \"Jessie\" Ogungbadero", "Kenneth \"Kenny\" Yates", "Zoe Costello"], ["Season 5 (2003)", "Caroline Botelho", "Aline Toupi", "Estuardo Alvizures", "Garrett DiBona", "Michael \"Mike\" Hansen", "Kortney Sumner", "Elena \"Shing Ying\" Shieh"], ["Season 6 (2004)", "Michael \"Mike\" Hansen", "Kortney Sumner", "Francesco Tena", "Cara Harvey", "Kyle Larrow", "Maya Morales", "Elena \"Shing Ying\" Shieh"], ["Season 4 (2002)", "Aline Toupi", "Garrett DiBona", "Rachel Redd", "Matthew \"Matt\" Runyon", "Estuardo Alvizures", "Kaleigh Cronin", "Caroline Botelho"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many number of cast members were there on zoom season 1? | 7 | 128 | Answer: |
Table InputTable: [["Position", "Officer", "current officers", "superseded by", "Royal Household"], ["9", "Lord High Admiral", "HRH The Duke of Edinburgh", "", ""], ["2", "Lord High Chancellor", "The Rt Hon Chris Grayling, MP", "", ""], ["1", "Lord High Steward", "vacant", "Justiciar", "Lord Steward"], ["6", "Lord Great Chamberlain", "The Marquess of Cholmondeley", "Lord High Treasurer", "Lord Chamberlain"], ["3", "Lord High Treasurer", "in commission", "", ""], ["7", "Lord High Constable", "vacant", "Earl Marshal", "Master of the Horse"], ["5", "Lord Privy Seal", "The Rt Hon Andrew Lansley, CBE, MP", "", ""], ["4", "Lord President of the Council", "The Rt Hon Nick Clegg, MP", "", ""], ["8", "Earl Marshal", "The Duke of Norfolk", "", "Master of the Horse"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 lowest position, other than lord high admiral? | Earl Marshal | 128 | Answer: |
Table InputTable: [["Year", "Recipient", "Nationality", "Profession", "Speech"], ["2005", "William Safire", "United States", "Author, journalist and speechwriter\\n1978 Pulitzer Prize winner", ""], ["2006", "Daniel Pipes", "United States", "Author and historian", ""], ["1997", "Elie Wiesel", "United States", "Professional writer\\nWinner of the Nobel Peace Prize (1986)", ""], ["2007", "Norman Podhoretz", "United States", "Author, columnist", ""], ["2008", "David Be'eri, Mordechai Eliav, Rabbi Yehuda Maly", "Israel", "", ""], ["2010", "Malcolm Hoenlein", "United States", "Executive Vice Chairman of the Conference of Presidents of Major American Jewish Organizations", ""], ["2009", "Caroline Glick", "Israel", "Journalist", ""], ["2001", "Cynthia Ozick", "United States", "Professional writer", ""], ["1999", "A.M. Rosenthal", "United States", "Former New York Times editor\\nFormer New York Daily News columnist", ""], ["2003", "Ruth Roskies Wisse", "United States", "Yiddish professor of Harvard University", "[2]"], ["2002", "Charles Krauthammer", "United States", "The Washington Post columnist", "[1]"], ["2000", "Sir Martin Gilbert", "United Kingdom", "Historian and writer", ""], ["1998", "Herman Wouk", "United States", "Professional writer and 1952 Pulitzer Prize winner", ""], ["2004", "Arthur Cohn", "Switzerland", "Filmmaker and writer", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 guardian of zion awardees are from the united states? | 10 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["3", "Yugoslavia", "3", "2", "1", "6"], ["8", "Tunisia", "0", "1", "0", "1"], ["1", "France", "11", "5", "3", "19"], ["7", "Egypt", "0", "1", "7", "8"], ["5", "Morocco", "1", "1", "0", "2"], ["2", "Greece", "6", "7", "6", "19"], ["4", "Spain", "1", "5", "5", "11"], ["5", "Turkey", "1", "1", "0", "2"], ["Totaal", "Totaal", "23", "23", "22", "68"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:country that came in last place. | Tunisia | 128 | Answer: |
Table InputTable: [["No.", "Date/time", "Aircraft", "Foe", "Result", "Location", "Notes"], ["6", "23 May 1917 @ 1800 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Douai, France", ""], ["1", "4 December 1916 @ 1100 hours", "Nieuport serial number 3958", "Albatros D.I", "Driven down out of control", "Northeast of Bapaume, France", "Victory shared with another pilot"], ["4", "11 May 1917 @ 1950 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Douai, France", ""], ["2", "24 April 1917 @ 0840 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Sailly, France", ""], ["8", "28 July 1917 @ 1735 hours", "Sopwith Triplane s/n N5462", "German two-seater aircraft", "Driven down out of control", "Middelkerke, Belgium", "Victory shared with Francis Mellersh"], ["7", "24 July 1917 @ 0635 hours", "Sopwith Triplane s/n N5462", "German two-seater aircraft", "Driven down out of control", "Leffinghe", ""], ["3", "2 May 1917 @ 0945 hours", "Sopwith Triplane s/n N5460", "German two-seater aircraft", "Driven down out of control", "Douai, France", ""], ["5", "11 May 1917 @ 1950 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Set afire in midair; destroyed", "Douai, France", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 victories that had the result of driven down out of control? | 7 | 128 | Answer: |
Table InputTable: [["Ship", "Type of Vessel", "Lake", "Location", "Lives lost"], ["Plymouth", "Barge", "Lake Michigan", "", "7 lost"], ["Lightship No. 82", "Lightship", "Lake Erie", "Point Albino (near Buffalo)", "6 lost"], ["Argus", "Steamer", "Lake Huron", "25 miles off Kincardine, Ontario", "25 lost"], ["Charles S. Price", "Steamer", "Lake Huron", "near Port Huron, Michigan", "28 lost"], ["Hydrus", "Steamer", "Lake Huron", "near Lexington, Michigan", "28 lost"], ["James Carruthers", "Steamer", "Lake Huron", "near Kincardine", "18 lost"], ["Issac M. Scott", "Steamer", "Lake Huron", "near Port Elgin, Ontario", "28 lost"], ["John A. McGean", "Steamer", "Lake Huron", "near Goderich, Ontario", "28 lost"], ["Henry B. Smith", "Steamer", "Lake Superior", "", "all hands"], ["Regina", "Steamer", "Lake Huron", "near Harbor Beach, Michigan", ""], ["Leafield", "Steamer", "Lake Superior", "", "all hands"], ["Wexford", "Steamer", "Lake Huron", "north of Grand Bend, Ontario", "all hands"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 ship lost over 5 lives but was a barge? | Plymouth | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2011", "Asian Championships", "Kobe, Jpan", "3rd", "200 m", "20.97"], ["2009", "Asian Championships", "Guangzhou, China", "1st", "200 m", "21.07"], ["2011", "World Championships", "Daegu, South Korea", "48th (h)", "200 m", "21.45"], ["2008", "Asian Indoor Championships", "Doha, Qatar", "4th", "60 m", "6.81"], ["2010", "Asian Games", "Guangzhou, China", "3rd", "200 m", "20.83"], ["2009", "Asian Indoor Games", "Hanoi, Vietnam", "4th", "60 m", "6.72 (NR)"], ["2008", "World Indoor Championships", "Valencia, Spain", "28th (h)", "60 m", "6.88"], ["2009", "World Championships", "Berlin, Germany", "25th (qf)", "200 m", "20.97"], ["2008", "World Junior Championships", "Bydgoszcz, Poland", "7th", "200 m", "21.10"], ["2008", "Olympic Games", "Beijing, China", "40th (h)", "200 m", "21.00"], ["2007", "Pan Arab Games", "Cairo, Egypt", "4th", "200 m", "20.94 (NR)"], ["2011", "Pan Arab Games", "Doha, Qatar", "3rd", "4x100 m", "40.15"], ["2011", "Pan Arab Games", "Doha, Qatar", "5th", "100 m", "21.59"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many consecutive years did he participate in the asian championships? | 1 | 128 | Answer: |
Table InputTable: [["Season", "Episodes", "Season Premiere", "Season Finale"], ["7", "8", "October 29, 2013", "December 17, 2013"], ["4", "48", "October 13, 2008", "May 11, 2009"], ["3", "44", "October 15, 2007", "June 2, 2008"], ["2", "52", "October 7, 2006", "July 16, 2007"], ["5", "40", "October 12, 2009", "June 14, 2010"], ["6", "20", "September 6, 2010", "December 6, 2010"], ["1", "20", "March 4, 2006", "May 13, 2006"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which season only had eight episodes? | Season 7 | 128 | Answer: |
Table InputTable: [["Pick #", "Player", "Position", "Nationality", "NHL team", "College/junior/club team"], ["158", "Andy Suhy", "Defense", "United States", "Detroit Red Wings", "Western Michigan University (NCAA)"], ["168", "Kevin Wortman", "Defense", "United States", "Calgary Flames", "American International College (NCAA)"], ["153", "Milan Tichy", "Defense", "Czechoslovakia", "Chicago Blackhawks", "Prince Albert Raiders (WHL)"], ["164", "Rick Allain", "Defense", "Canada", "Boston Bruins", "Kitchener Rangers (OHL)"], ["160", "Greg Spenrath", "Defense", "Canada", "New York Rangers", "Tri-City Americans (WHL)"], ["152", "Sergei Starikov", "Defense", "Soviet Union", "New Jersey Devils", "CSKA Moscow (USSR)"], ["159", "Sverre Sears", "Defense", "United States", "Philadelphia Flyers", "Princeton University (NCAA)"], ["162", "Darcy Martini", "Defense", "Canada", "Edmonton Oilers", "Michigan Technological University (NCAA)"], ["163", "David Shute", "Left Wing", "United States", "Pittsburgh Penguins", "Victoria Cougars (WHL)"], ["149", "Phil Huber", "Center", "Canada", "New York Islanders", "Kamloops Blazers (WHL)"], ["166", "Dean Holoien", "Right Wing", "Canada", "Washington Capitals", "Saskatoon Blades (WHL)"], ["150", "Derek Langille", "Defense", "Canada", "Toronto Maple Leafs", "North Bay Centennials (OHL)"], ["161", "Derek Plante", "Center", "United States", "Buffalo Sabres", "Cloquet High School (USHS-MN)"], ["155", "Rob Sangster", "Left Wing", "Canada", "Vancouver Canucks", "Kitchener Rangers (OHL)"], ["157", "Raymond Saumier", "Right Wing", "Canada", "Hartford Whalers", "Trois Rivieres Draveurs (QMJHL)"], ["148", "Paul Krake", "Goalie", "Canada", "Quebec Nordiques", "University of Alaska Anchorage (NCAA)"], ["165", "Sean Whyte", "Right Wing", "Canada", "Los Angeles Kings", "Guelph Platers (OHL)"], ["151", "Jim Solly", "Left Wing", "Canada", "Winnipeg Jets", "Bowling Green State University (NCAA)"], ["167", "Patrick Lebeau", "Left Wing", "Canada", "Montreal Canadiens", "St-Jean Lynx (QMJHL)"], ["156", "Kevin Plager", "Right Wing", "United States", "St. Louis Blues", "Parkway North High School (USHS-MO)"], ["154", "Jon Pratt", "Left Wing", "United States", "Minnesota North Stars", "Pingree High School (USHS-MA)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many consecutive defense players were picked after andy suhy? | 5 | 128 | Answer: |
Table InputTable: [["Tablet", "Genealogy", "Narrative", "Colophon"], ["3", "Adam to Noah 5:1 - 32", "6:1 - 8", "\"This is the account of Noah.\" 6:9"], ["4", "Noah to Shem, Ham, and Japeth 6:9 - 10", "6:11 to 9:29", "\"This is the account of Shem, Ham, and Japheth, Noah's sons.\" 10:1"], ["9", "Abraham to Isaac 25:19", "25:20 to 35:29", "\"This is the account of Esau.\" 36:1 (eldest son)"], ["2", "Heavens and Earth 2:4", "2:5 to 4:26", "\"This is the written account of Adam.\" 5:1"], ["7", "Terah to Abraham 11:27", "11:28 to 25:11", "\"This is the account of Abraham's son Ishmael.\" 25:12 (eldest son)"], ["8", "Descendants of Ishmael 25:13 - 18", "no narrative", "\"This is the account of Abraham's son Isaac.\" 25:19"], ["1", "Creation of Universe 1:1", "1:2 to 2:3", "\"This is the account of the heavens and of the earth when they were created.\" 2:4"], ["11", "Descendants of Esau 36:10 to 37:1", "no narrative", "\"This is the account of Jacob.\" 37:2"], ["5", "Descendants of Shem, Ham, and Japeth 10:1 - 32", "11:1 - 9", "\"This is the account of Shem.\" 11:10"], ["10", "Descendants of Esau 36:2 - 5", "36:6 - 8", "\"This is the account of Esau.\" 36:9"], ["6", "Shem to Terah 11:10 - 26", "no narrative", "\"This is the account of Terah.\" 11:27"], ["", "no genealogy", "37:2 to 50:26", "no colophon"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 tablets are in genesis? | 11 | 128 | Answer: |
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)"], ["5", "Dr M. Shafi Ahmad", "1989", "1990", "University of London", "Astronomy", "Ph.D"], ["7", "Dr Abdul Majid", "1997", "2001", "University of Wales", "Astrophysics", "Ph.D"], ["4", "Dr Salim Mehmud", "1980", "1989", "Oak Ridge Institute for Science and Education and Oak Ridge National Laboratory", "Nuclear Engineering, Electrical engineering, Physics, Mathematics, Electronics engineering", "Ph.D"], ["2", "Air Commodore Dr Władysław Turowicz", "1967", "1979", "Warsaw University of Technology", "Aeronautical Engineering", "Ph.D"], ["8", "Major General Raza Hussain", "2001", "2010", "Pakistan Army Corps of Electrical and Mechanical Engineers", "Electrical Engineering", "B.S."], ["3", "Air Commodore K. M. Ahmad", "1979", "1980", "Pakistan Air Force Academy", "Flight Instructor", "Certificated Flight Instructor (CFI)"], ["6", "Engr.Sikandar Zaman", "1990", "1997", "University of Leeds", "Mechanical Engineering", "Bachelor of Science (B.S.)"], ["9", "Major General Ahmed Bilal", "2010", "Present", "Pakistan Army Corps of Signals Engineering", "Computer Engineering", "Master of Science (M.S)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many administrators did not possess a ph.d? | 4 | 128 | Answer: |
Table InputTable: [["No.", "Date", "Tournament", "Winning score", "Margin of\\nvictory", "Runner(s)-up"], ["5", "23 Apr 2006", "Tsuruya Open", "−11 (70-68-66-69=273)", "2 strokes", "Mamo Osanai"], ["7", "11 Nov 2007", "Mitsui Sumitomo VISA Taiheiyo Masters", "−13 (67-68-69-70=274)", "5 strokes", "Toru Taniguchi"], ["11", "15 Apr 2012", "Token Homemate Cup", "−15 (68-69-70-62=269)", "2 strokes", "Ryuichi Oda"], ["6", "22 Apr 2007", "Tsuruya Open", "−16 (67-65-68-68=268)", "2 strokes", "Masahiro Kuramoto, Hirofumi Miyase,\\n Takuya Taniguchi"], ["3", "25 Apr 2004", "Tsuruya Open", "−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)", "−6 (71-70-66=207)", "1 stroke", "Ryuichi Oda"], ["1", "3 Nov 2002", "Philip Morris K.K. Championship", "−19 (65-67-67-70=269)", "2 strokes", "Toshimitsu Izawa"], ["10", "1 May 2011", "The Crowns", "−9 (67-66-68-70=271)", "Playoff", "Jang Ik-jae"], ["12", "29 Jul 2012", "Sun Chlorella Classic", "−15 (69-66-68-70=273)", "2 strokes", "Lee Seong-ho, Hideki Matsuyama (am),\\n Yoshinobu Tsukada"], ["13", "30 Jun 2013", "Gateway to the Open Mizuno Open", "−19 (67-66-68-68=269)", "3 strokes", "Kim Kyung-tae"], ["4", "26 Jun 2004", "Gateway to the Open Mizuno Open", "−14 (67-68-70-69=274)", "Playoff", "Hiroaki Iijima"], ["8", "2 Dec 2007", "Golf Nippon Series JT Cup", "−11 (70-70-68-61=261)", "1 stroke", "Toru Taniguchi"], ["2", "10 Aug 2003", "Sun Chlorella Classic", "−8 (71-73-68-68=280)", "1 stroke", "Daisuke Maruyama, Taichi Teshima"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 runner-up places for mamo osanai? | 1 | 128 | Answer: |
Table InputTable: [["Tournament", "2004", "2005", "2006", "2007", "2008", "2009", "2010", "2011", "2012", "2013", "2014", "W–L"], ["French Open", "2R", "1R", "1R", "2R", "2R", "1R", "2R", "3R", "1R", "1R", "", "6–10"], ["Australian Open", "A", "2R", "2R", "2R", "3R", "2R", "1R", "3R", "1R", "1R", "2R", "9–10"], ["Madrid Masters", "A", "A", "A", "LQ", "LQ", "1R", "3R", "3R", "2R", "1R", "", "5–5"], ["Miami Masters", "A", "A", "A", "2R", "1R", "1R", "2R", "2R", "2R", "A", "", "3–6"], ["US Open", "A", "1R", "1R", "1R", "2R", "2R", "2R", "2R", "2R", "1R", "", "5–9"], ["Win–Loss", "1–1", "2–4", "2–4", "2–4", "6–4", "3–4", "2–4", "6–4", "2–4", "0–4", "1–1", "27–38"], ["Win–Loss", "0–0", "0–1", "1–1", "4–4", "1–2", "2–6", "11–6", "5–8", "5–5", "0–2", "", "29–35"], ["Paris Masters", "A", "A", "A", "LQ", "LQ", "A", "A", "2R", "1R", "1R", "", "1–3"], ["Canada Masters", "A", "A", "A", "A", "A", "1R", "A", "A", "A", "A", "", "0–1"], ["Hamburg Masters", "A", "A", "2R", "1R", "A", "Not Masters Series", "Not Masters Series", "Not Masters Series", "Not Masters Series", "Not Masters Series", "", "1–2"], ["Wimbledon", "A", "2R", "2R", "1R", "3R", "2R", "1R", "2R", "2R", "1R", "", "7–9"], ["Monte-Carlo Masters", "A", "1R", "A", "3R", "LQ", "A", "1R", "2R", "A", "A", "", "2–3"], ["Shanghai Masters", "Not Masters Series", "Not Masters Series", "Not Masters Series", "Not Masters Series", "Not Masters Series", "1R", "QF", "2R", "Q2", "A", "", "4–3"], ["Indian Wells Masters", "A", "A", "A", "3R", "2R", "1R", "4R", "2R", "3R", "A", "A", "8–6"], ["Titles–Finals", "0–0", "0–0", "0–0", "0–0", "0–0", "1–1", "1–2", "0–0", "0–0", "0–2", "", "2–5"], ["Cincinnati Masters", "A", "A", "A", "LQ", "A", "3R", "A", "1R", "A", "A", "", "2–2"], ["Rome Masters", "A", "A", "A", "A", "A", "LQ", "3R", "1R", "2R", "A", "", "3–3"], ["Year End Ranking", "129", "91", "68", "90", "62", "41", "33", "39", "76", "62", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 wins guillermo garcía-lópez had in the french open? | 6 | 128 | Answer: |
Table InputTable: [["Representative", "Party", "Home Town/City", "District"], ["Trey Martinez Fischer", "D", "San Antonio", "116"], ["Lyle Larson", "R", "San Antonio", "122"], ["Jose Menendez", "D", "San Antonio", "124"], ["Justin Rodriguez", "D", "San Antonio", "125"], ["Philip Cortez", "D", "San Antonio", "117"], ["Ruth McClendon", "D", "San Antonio", "120"], ["Roland Gutierrez", "D", "San Antonio", "119"], ["Joe Farias", "D", "San Antonio", "118"], ["Joe Straus", "R", "San Antonio", "121"], ["Mike Villarreal", "D", "San Antonio", "123"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 first representative from texas in district 116? | Trey Martinez Fischer | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["5", "Greece", "3", "4", "9", "16"], ["8", "Croatia", "0", "3", "3", "6"], ["2", "Italy", "12", "8", "10", "30"], ["9", "Egypt", "0", "1", "2", "3"], ["1", "France", "14", "7", "7", "28"], ["7", "Algeria", "2", "0", "2", "4"], ["3", "Slovenia", "5", "4", "3", "12"], ["6", "Tunisia", "3", "0", "0", "3"], ["4", "Spain", "4", "14", "6", "24"], ["Total", "Total", "43", "41", "42", "126"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 same number of gold medals as greece? | Tunisia | 128 | Answer: |
Table InputTable: [["Player", "No.", "Nationality", "Position", "Years for Jazz", "School/Club Team"], ["Terry Furlow", "25", "United States", "Guard/Forward", "1979-80", "Michigan State"], ["Bernie Fryer", "25", "United States", "Guard", "1975-76", "BYU"], ["Todd Fuller", "52", "United States", "Center", "1998-99", "North Carolina State"], ["Derrick Favors", "15", "United States", "Forward", "2011-present", "Georgia Tech"], ["Jim Farmer", "30", "United States", "Guard", "1988-89", "Alabama"], ["Greg Foster", "44", "United States", "Center/Forward", "1995-99", "UTEP"], ["Derek Fisher", "2", "United States", "Guard", "2006-2007", "Arkansas-Little Rock"], ["Kyrylo Fesenko", "44", "Ukraine", "Center", "2007-11", "Cherkasy Monkeys (Ukraine)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:in total, how many players with a last name starting with the letter f play on the jazz? | 8 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2009", "Lusophony Games", "Lisbon, Portugal", "4th", "800 m", "2:07.48"], ["2006", "Lusophony Games", "Macau", "1st", "800 m", "2:07.34"], ["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"], ["2008", "African Championships", "Addis Ababa, Ethiopia", "6th", "800 m", "2:05.95"], ["2011", "All-Africa Games", "Maputo, Mozambique", "12th (h)", "800 m", "2:06.72"], ["2006", "African Championships", "Bambous, Mauritius", "13th (h)", "800 m", "2:10.50"], ["2007", "All-Africa Games", "Algiers, Algeria", "1st", "800 m", "2:02.83"], ["2010", "African Championships", "Nairobi, Kenya", "7th", "800 m", "2:08.45"], ["2010", "Commonwealth Games", "Delhi, India", "–", "800 m", "DNF"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total years are there? | 7 | 128 | Answer: |
Table InputTable: [["Competition", "Total spectatorship", "Average match attendance", "Year"], ["Super Rugby", "773,940", "19,348", "2012"], ["Big Bash League", "550,262", "17,750", "2011/2012"], ["Rugby Championship", "133,532", "44,511", "2012"], ["National Rugby League", "3,345,248", "16,643", "2013"], ["State of Origin series", "186,607", "62,202", "2011"], ["Australian Football League", "6,931,085", "33,484", "2013"], ["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:what is the total of the 4 highest total spectatorships? | 12822406 | 128 | Answer: |
Table InputTable: [["Rd.", "Event", "Circuit", "Location", "Date", "Winner"], ["1", "Clipsal 500", "Adelaide Street Circuit", "Adelaide, South Australia", "19-22 Mar", "David Russell"], ["2", "Winton", "Winton Motor Raceway", "Benalla, Victoria", "1-3 May", "Jonathon Webb"], ["4", "Norton 360 Sandown Challenge", "Sandown Raceway", "Melbourne, Victoria", "31 Jul-Aug 2", "David Russell"], ["5", "Queensland House & Land 300", "Queensland Raceway", "Ipswich, Queensland", "21-23 Aug", "Jonathon Webb"], ["6", "Supercheap Auto Bathurst 1000", "Mount Panorama Circuit", "Bathurst, New South Wales", "8-11 Oct", "Jonathon Webb"], ["3", "Dunlop Townsville 400", "Townsville Street Circuit", "Townsville, Queensland", "10-12 Jul", "James Moffat"], ["7", "Sydney Telstra 500", "Homebush Street Circuit", "Sydney, New South Wales", "4-6 Dec", "Jonathon Webb"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who won the clipsal 500, webb or russell? | David Russell | 128 | Answer: |
Table InputTable: [["Year", "Date", "Winner", "Result", "Loser", "Location"], ["2000", "October 29", "New York Giants", "24-7", "Philadelphia Eagles", "Giants Stadium"], ["2005", "December 11", "New York Giants", "26-23 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2008", "November 9", "New York Giants", "36-31", "Philadelphia Eagles", "Lincoln Financial Field"], ["2007", "September 30", "New York Giants", "16-3", "Philadelphia Eagles", "Giants Stadium"], ["2006", "September 17", "New York Giants", "30-24 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2007", "December 9", "New York Giants", "16-13", "Philadelphia Eagles", "Lincoln Financial Field"], ["2002", "December 28", "New York Giants", "10-7", "Philadelphia Eagles", "Giants Stadium"], ["2007", "January 7", "Philadelphia Eagles", "23-20", "New York Giants", "Lincoln Financial Field"], ["2005", "November 20", "New York Giants", "27-17", "Philadelphia Eagles", "Giants Stadium"], ["2001", "January 7", "New York Giants", "20-10", "Philadelphia Eagles", "Giants Stadium"], ["2008", "December 7", "Philadelphia Eagles", "20-14", "New York Giants", "Giants Stadium"], ["2006", "December 17", "Philadelphia Eagles", "36-22", "New York Giants", "Giants Stadium"], ["2009", "January 11", "Philadelphia Eagles", "23-11", "New York Giants", "Giants Stadium"], ["2003", "November 16", "Philadelphia Eagles", "28-10", "New York Giants", "Lincoln Financial Field"], ["2000", "September 10", "New York Giants", "33-18", "Philadelphia Eagles", "Veterans Stadium"], ["2003", "October 19", "Philadelphia Eagles", "14-10", "New York Giants", "Giants Stadium"], ["2001", "October 22", "Philadelphia Eagles", "10-9", "New York Giants", "Giants Stadium"], ["2009", "December 13", "Philadelphia Eagles", "45-38", "New York Giants", "Giants Stadium"], ["2004", "November 28", "Philadelphia Eagles", "27-6", "New York Giants", "Giants Stadium"], ["2009", "November 1", "Philadelphia Eagles", "40-17", "New York Giants", "Lincoln Financial Field"], ["2004", "September 12", "Philadelphia Eagles", "31-17", "New York Giants", "Lincoln Financial Field"], ["2001", "December 30", "Philadelphia Eagles", "24-21", "New York Giants", "Veterans Stadium"], ["2002", "October 28", "Philadelphia Eagles", "17-3", "New York Giants", "Veterans Stadium"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what are the total number of times the new york giants is listed as the winner? | 10 | 128 | Answer: |
Table InputTable: [["Season", "Competition", "Round", "Club", "Home", "Away"], ["2012–13", "UEFA Europa League", "1QR", "Budapest Honvéd", "0–1", "0–2"], ["1990–91", "UEFA Cup Winners' Cup", "1R", "Olympiacos Piraeus", "0–2", "1–3"], ["1987–88", "UEFA Cup", "2R", "Wismut Aue", "2–0", "0–1"], ["1987–88", "UEFA Cup", "1R", "FK Partizan Beograd", "2–0", "1–2"], ["1985–86", "UEFA Cup Winners' Cup", "1R", "HJK Helsinki", "1–2", "2–3"], ["1996–97", "UEFA Cup Winners' Cup", "QR", "Humenné", "0–2", "0–1"], ["", "", "2QR", "FK Jablonec 97", "0–2", "1–5"], ["2011–12", "UEFA Europa League", "1QR", "FK Budućnost", "1–2", "3–1"], ["2009–10", "UEFA Europa League", "2QR", "Motherwell", "1–0", "1–8"], ["1988–89", "UEFA Cup Winners' Cup", "1R", "Lech Poznań", "2–3", "0–1"], ["1987–88", "UEFA Cup", "1/16", "FC Barcelona", "1–0", "1–4"], ["1986–87", "UEFA Cup", "1R", "FC Barcelona", "1–1", "0–0"], ["1991–92", "UEFA European Cup", "1R", "IFK Göteborg", "1–1", "0–0"]] | 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:which season did flamurtari vlorë win more home games than away? | 1986-87 | 128 | Answer: |
Table InputTable: [["Rank", "Diver", "Nationality", "Preliminary\\nPoints", "Preliminary\\nRank", "Final\\nPoints", "Final\\nRank"], ["11", "Brittany Broben", "Australia", "257.10", "10", "267.20", "11"], ["40", "Hsu Shi-Han", "Chinese Taipei", "146.15", "40", "", ""], ["26", "Choi Sut Ian", "Macau", "224.50", "26", "", ""], ["17", "Sharon Chan", "Hong Kong", "245.10", "17", "", ""], ["29", "Yuka Mabuchi", "Japan", "219.50", "29", "", ""], ["", "Wang Han", "China", "306.60", "1", "310.20", "2"], ["28", "Julia Loennegren", "Sweden", "221.05", "28", "", ""], ["15", "Sophie Somloi", "Austria", "249.45", "15", "", ""], ["36", "Lei Sio I", "Macau", "192.00", "36", "", ""], ["", "Shi Tingmao", "China", "294.65", "2", "318.65", "1"], ["25", "Hannah Starling", "Great Britain", "226.40", "25", "", ""], ["30", "Alicia Blagg", "Great Britain", "212.50", "30", "", ""], ["16", "Uschi Freitag", "Germany", "247.70", "16", "", ""], ["38", "Huang En-Tien", "Chinese Taipei", "187.25", "38", "", ""], ["27", "Marion Farissier", "France", "221.65", "27", "", ""], ["21", "Jennifer Benitez", "Spain", "232.50", "21", "", ""], ["20", "Sayaka Shibusawa", "Japan", "240.80", "20", "", ""], ["8", "Anna Lindberg", "Sweden", "276.05", "5", "279.55", "8"], ["18", "Inge Jansen", "Netherlands", "241.95", "18", "", ""], ["7", "Sharleen Stratton", "Australia", "282.45", "3", "281.65", "7"], ["33", "Tina Punzel", "Germany", "206.05", "33", "", ""], ["13", "Hanna Pysmenska", "Ukraine", "251.40", "13", "", ""], ["19", "Jun Hoong Cheong", "Malaysia", "241.95", "18", "", ""], ["9", "Kelci Bryant", "United States", "257.00", "11", "274.25", "9"], ["10", "Olena Fedorova", "Ukraine", "258.30", "9", "274.15", "10"], ["24", "Fanny Bouvet", "France", "227.10", "24", "", ""], ["32", "Diana Pineda", "Colombia", "209.60", "32", "", ""], ["39", "Carolina Murillo", "Colombia", "181.85", "39", "", ""], ["5", "Nadezhda Bazhina", "Russia", "262.75", "7", "286.20", "5"], ["6", "Abby Johnston", "United States", "282.40", "4", "282.85", "6"], ["35", "Sari Ambarwati", "Indonesia", "200.05", "35", "", ""], ["23", "Vianey Hernandez", "Mexico", "227.85", "23", "", ""], ["37", "Leyre Eizaguirre", "Spain", "189.95", "37", "", ""], ["14", "Jennifer Abel", "Canada", "250.95", "14", "", ""], ["4", "Maria Marconi", "Italy", "264.25", "6", "290.15", "4"], ["12", "Anastasia Pozdniakova", "Russia", "260.00", "8", "251.70", "12"], ["34", "Maria Florencia Betancourt", "Venezuela", "204.90", "34", "", ""], ["", "Tania Cagnotto", "Italy", "253.15", "12", "295.45", "3"], ["22", "Arantxa Chavez", "Mexico", "232.35", "22", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 higher, han or broben? | Han | 128 | Answer: |
Table InputTable: [["Round", "Pick", "Player", "Position", "Nationality", "School/Club Team"], ["9", "192", "Al Williams", "", "United States", "North Texas State"], ["1", "15", "Reggie Johnson", "PF/C", "United States", "Tennessee"], ["6", "129", "Dean Uthoff", "", "United States", "Iowa State"], ["8", "172", "Bill Bailey", "", "United States", "Texas Pan-American"], ["10", "209", "Steve Schall", "", "United States", "Arkansas"], ["4", "83", "Calvin Roberts", "", "United States", "California State-Fullerton"], ["7", "153", "Allan Zahn", "", "United States", "Arkansas"], ["3", "60", "Lavon Mercer", "", "United States", "Georgia"], ["5", "107", "Gib Hinz", "", "United States", "Wisconsin-Eau Claire"], ["3", "61", "Rich Yonakor", "", "United States", "North Carolina"], ["2", "39", "Michael Miley", "", "United States", "California State-Long Beach"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many players were from texas schools? | 2 | 128 | Answer: |
Table InputTable: [["#", "Massif", "Region", "Type of nature reserve", "Preserved area", "Buffer zone"], ["11", "Jasmund", "Mecklenburg-Vorpommern", "Jasmund National Park", "492.5 ha", "2510.5 ha"], ["4", "Maramoros", "Zakarpattia", "Carpathian Biosphere Reserve", "2243.6 ha", "6230.4 ha"], ["3", "Svydovets", "Zakarpattia", "Carpathian Biosphere Reserve", "3030.5 ha", "5639.5 ha"], ["5", "Kuziy / Trybushany", "Zakarpattia", "Carpathian Biosphere Reserve", "1369.6 ha", "3163.4 ha"], ["8", "Rožok", "Presov", "Presov Preserved areas", "67.1 ha", "41.4 ha"], ["14", "Hainich", "Thuringia", "Hainich National Park", "1573.4 ha", "4085.4 ha"], ["13", "Grumsiner Forest", "Brandenburg", "Grumsiner Forest Nature Reserve", "590.1 ha", "274.3 ha"], ["1", "Chornohora", "Zakarpattia", "Carpathian Biosphere Reserve", "2476.8 ha", "12925 ha"], ["10", "Havešová", "Presov", "Presov Preserved areas", "171.3 ha", "63.9 ha"], ["9", "Vihorlat", "Presov", "Presov Preserved areas", "2578 ha", "2413 ha"], ["2", "Uholka / Wide Meadow", "Zakarpattia", "Carpathian Biosphere Reserve", "11860 ha", "3301 ha"], ["15", "Kellerwald", "Hesse", "Kellerwald-Edersee National Park", "1467.1 ha", "4271.4 ha"], ["6", "Stuzhytsia / Uzhok", "Zakarpattia", "Uzh National Nature Park", "2532 ha", "3615 ha"], ["12", "Serrahn", "Mecklenburg-Vorpommern", "Müritz National Park", "268.1 ha", "2568 ha"], ["7", "Stužica / Bukovské vrchy", "Presov", "Poloniny National Park", "2950 ha", "11300 ha"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 maramoros larger or smaller than jasmund? | larger | 128 | Answer: |
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["9", "8", "Stefano Modena", "Brabham-Judd", "62", "+ 2 Laps", "20", ""], ["12", "24", "Paolo Barilla", "Minardi-Ford", "62", "+ 2 Laps", "24", ""], ["10", "25", "Nicola Larini", "Ligier-Ford", "62", "+ 2 Laps", "21", ""], ["13", "26", "Philippe Alliot", "Ligier-Ford", "61", "+ 3 Laps", "22", ""], ["DNQ", "7", "David Brabham", "Brabham-Judd", "", "", "", ""], ["11", "21", "Emanuele Pirro", "Dallara-Ford", "62", "+ 2 Laps", "19", ""], ["7", "10", "Alex Caffi", "Arrows-Ford", "63", "+ 1 Lap", "17", ""], ["8", "4", "Jean Alesi", "Tyrrell-Ford", "63", "+ 1 Lap", "6", ""], ["4", "29", "Éric Bernard", "Lola-Lamborghini", "64", "+ 1:15.302", "8", "3"], ["Ret", "12", "Martin Donnelly", "Lotus-Lamborghini", "48", "Engine", "14", ""], ["14", "28", "Gerhard Berger", "McLaren-Honda", "60", "Throttle", "3", ""], ["2", "5", "Thierry Boutsen", "Williams-Renault", "64", "+ 39.092", "4", "6"], ["1", "1", "Alain Prost", "Ferrari", "64", "1:18:30.999", "5", "9"], ["Ret", "11", "Derek Warwick", "Lotus-Lamborghini", "46", "Engine", "16", ""], ["DNPQ", "31", "Bertrand Gachot", "Coloni-Subaru", "", "", "", ""], ["Ret", "16", "Ivan Capelli", "Leyton House-Judd", "48", "Fuel Leak", "10", ""], ["Ret", "2", "Nigel Mansell", "Ferrari", "55", "Gearbox", "1", ""], ["3", "27", "Ayrton Senna", "McLaren-Honda", "64", "+ 43.088", "2", "4"], ["Ret", "6", "Riccardo Patrese", "Williams-Renault", "26", "Chassis", "7", ""], ["DNQ", "36", "JJ Lehto", "Onyx-Ford", "", "", "", ""], ["Ret", "9", "Michele Alboreto", "Arrows-Ford", "37", "Engine", "25", ""], ["Ret", "17", "Gabriele Tarquini", "AGS-Ford", "41", "Engine", "26", ""], ["6", "30", "Aguri Suzuki", "Lola-Lamborghini", "63", "+ 1 Lap", "9", "1"], ["DNPQ", "34", "Claudio Langes", "EuroBrun-Judd", "", "", "", ""], ["DNPQ", "33", "Roberto Moreno", "EuroBrun-Judd", "", "", "", ""], ["5", "20", "Nelson Piquet", "Benetton-Ford", "64", "+ 1:24.003", "11", "2"], ["Ret", "22", "Andrea de Cesaris", "Dallara-Ford", "12", "Fuel System", "23", ""], ["DNPQ", "39", "Bruno Giacomelli", "Life", "", "", "", ""], ["DNQ", "14", "Olivier Grouillard", "Osella-Ford", "", "", "", ""], ["DNPQ", "18", "Yannick Dalmas", "AGS-Ford", "", "", "", ""], ["Ret", "19", "Alessandro Nannini", "Benetton-Ford", "15", "Collision", "13", ""], ["Ret", "23", "Pierluigi Martini", "Minardi-Ford", "3", "Alternator", "18", ""], ["DNQ", "35", "Gregor Foitek", "Onyx-Ford", "", "", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 retired before finishing 4 laps? | Pierluigi Martini | 128 | Answer: |
Table InputTable: [["Year", "MVP", "Defensive Player of the Year", "Unsung Hero", "Newcomer of the Year"], ["2000", "Jim Larkin", "–", "–", "–"], ["2010", "Philippe Billy", "Philippe Billy", "Tony Donatelli", "Ali Gerba"], ["1994", "Jean Harbor", "–", "–", "–"], ["1999", "N/A", "–", "–", "–"], ["2001", "Mauro Biello", "–", "–", "–"], ["1995", "Lloyd Barker", "–", "–", "–"], ["2003", "Greg Sutton", "Gabriel Gervais", "David Fronimadis", "Martin Nash"], ["2008", "Matt Jordan", "Nevio Pizzolitto", "Joey Gjertsen", "Stefano Pesoli"], ["1998", "Mauro Biello", "–", "–", "–"], ["1993", "Patrice Ferri", "–", "–", "–"], ["1997", "Mauro Biello", "–", "–", "–"], ["1996", "Paolo Ceccarelli", "–", "–", "–"], ["2007", "Leonardo Di Lorenzo", "Mauricio Vincello", "Simon Gatti", "Matt Jordan"], ["2011", "Hassoun Camara", "Evan Bush", "Simon Gatti", "Ian Westlake / Sinisa Ubiparipovic"], ["2004", "Gabriel Gervais", "Greg Sutton", "Zé Roberto", "Sandro Grande"], ["2009", "David Testo", "Nevio Pizzolitto", "Adam Braz", "Stephen deRoux"], ["2006", "Mauricio Vincello", "Gabriel Gervais", "Andrew Weber", "Leonardo Di Lorenzo"], ["2002", "Eduardo Sebrango", "Gabriel Gervais", "Jason DiTullio", "Zé Roberto"], ["2005", "Mauro Biello", "Nevio Pizzolitto", "Mauricio Vincello", "Masahiro Fukazawa"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 county has the most mvp's? | Canada | 128 | Answer: |
Table InputTable: [["No.", "Date", "Tournament", "Surface", "Partnering", "Opponent in the final", "Score"], ["3.", "April 11, 2011", "Chile F3", "Clay", "Roberto Quiroz", "Luis David Martínez\\n Miguel Ángel Reyes-Varela", "6–4, 7–5"], ["2.", "April 4, 2011", "Chile F2", "Clay", "Sergio Galdós", "Guillermo Hormazábal\\n Rodrigo Pérez", "5–7, 7–6(5), [10–5]"], ["8.", "October 8, 2012", "Chile F8", "Clay", "Gustavo Sterin", "Cristóbal Saavedra-Corvalán\\n Guillermo Rivera-Aránguiz", "6-4, 7-5"], ["7.", "August 26, 2012", "Ecuador F3", "Clay", "Sergio Galdós", "Mauricio Echazú\\n Guillermo Rivera-Aránguiz", "6-2, 6-1"], ["10.", "May 27, 2013", "Argentina F8", "Clay", "Sergio Galdós", "Daniel Dutra da Silva\\n Pablo Galdón", "6-0, 7-5"], ["9.", "May 13, 2013", "Argentina F6", "Clay", "Sergio Galdós", "Franco Agamenone\\n Jose Angel Carrizo", "4-6, 6-4, [10–1]"], ["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."], ["4.", "August 8, 2011", "Peru F1", "Clay", "Sergio Galdós", "Martín Cuevas\\n Guido Pella", "6–4, 6–0"], ["5.", "August 5, 2012", "Manta", "Hard", "Renzo Olivo", "Víctor Estrella\\n João Souza", "6–3, 6–0"]] | 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 tournament comes before chile f3? | Chile F2 | 128 | Answer: |
Table InputTable: [["Name", "League", "FA Cup", "League Cup", "JP Trophy", "Total"], ["Danny Coles", "3", "0", "0", "0", "3"], ["Scot Bennett", "5", "0", "0", "0", "5"], ["Liam Sercombe", "1", "0", "0", "0", "1"], ["Jamie Cureton", "20", "0", "0", "0", "20"], ["Arron Davies", "3", "0", "0", "0", "3"], ["Pat Baldwin", "1", "0", "0", "0", "1"], ["OWN GOALS", "0", "0", "0", "0", "0"], ["Alan Gow", "4", "0", "0", "0", "4"], ["Jake Gosling", "1", "0", "0", "0", "1"], ["John O'Flynn", "11", "0", "1", "0", "12"], ["Jimmy Keohane", "3", "0", "0", "0", "3"], ["Guillem Bauza", "2", "0", "0", "0", "2"], ["Total", "0", "0", "0", "0", "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 people have the same amount of league cups are they do fa cups? | 10 | 128 | Answer: |
Table InputTable: [["Event", "Gold", "Time", "Silver", "Time", "Bronze", "Time"], ["K–2 200 m", "Hungary\\nKatalin Kovács\\nDanuta Kozák", "37.667", "Poland\\nKarolina Naja\\nMagdalena Krukowska", "38.165", "Australia\\nJoanne Brigden-Jones\\nHannah Davis", "38.369"], ["K–1 4x200 m Relay", "Germany\\nNicole Reinhardt\\nConny Wassmuth\\nTina Dietze\\nCarolin Leonhardt", "2:49.541", "Russia\\nNatalia Lobova\\nAnastasiya Sergeeva\\nNatalia Proskurina\\nSvetlana Kudinova", "2:50.207", "Poland\\nMarta Walczykiewicz\\nKarolina Naja\\nAneta Konieczna\\nEwelina Wojnarowska", "2:50.951"], ["K–2 500 m", "Austria\\nYvonne Schuring\\nViktoria Schwarz", "1:37.071 WB", "Germany\\nFranziska Weber\\nTina Dietze", "1:37.275", "Poland\\nBeata Mikołajczyk\\nAneta Konieczna", "1:37.803"], ["K–1 1000 m", "Tamara Csipes (HUN)", "4:11.388", "Krisztina Fazekas Zur (USA)", "4:13.470", "Naomi Flood (AUS)", "4:14.124"], ["K–4 500 m", "Hungary\\nGabriella Szabó\\nDanuta Kozák\\nKatalin Kovács\\nDalma Benedek", "1:36.339", "Germany\\nCarolin Leonhardt\\nSilke Hörmann\\nFranziska Weber\\nTina Dietze", "1:37.521", "Belarus\\nIryna Pamialova\\nNadzeya Papok\\nVolha Khudzenka\\nMaryna Paltaran", "1:37.887"], ["K–2 1000 m", "Germany\\nAnne Knorr\\nDebora Niche", "3:50.614", "Bulgaria\\nBerenike Faldum\\nDaniela Nedeva", "3:50.950", "Hungary\\nAlíz Sarudi\\nErika Medveczky", "3:53.416"], ["K–1 500 m", "Nicole Reinhardt (GER)", "1:47.066", "Danuta Kozák (HUN)", "1:47.396", "Inna Osypenko-Radomska (UKR)", "1:48.668"], ["K–1 200 m", "Lisa Carrington (NZL)", "39.998", "Marta Walczykiewicz (POL)", "40.472", "Inna Osypenko-Radomska (UKR)", "40.670"], ["K–1 5000 m", "Tamara Csipes (HUN)", "22:19.816", "Lani Belcher (GBR)", "22:26.572", "Maryna Paltaran (BLR)", "22:37.294"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who's number of individual gold medals was two. | Tamara Csipes (HUN) | 128 | Answer: |
Table InputTable: [["Season", "Date", "Location", "Discipline", "Place"], ["1995", "11 Dec 1994", "Tignes, France", "Super G", "2nd"], ["1994", "13 Mar 1994", "Whistler, BC, Canada", "Super G", "1st"], ["1993", "27 Feb 1993", "Whistler, BC, Canada", "Downhill", "2nd"], ["1994", "12 Mar 1994", "Whistler, BC, Canada", "Downhill", "3rd"], ["1994", "16 Mar 1994", "Vail, CO, USA", "Downhill", "3rd"], ["1994", "12 Dec 1993", "Val-d'Isère, France", "Super G", "3rd"], ["1994", "29 Dec 1993", "Bormio, Italy", "Downhill", "3rd"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which location is listed at the top of the table? | Whistler, BC, Canada | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["5", "Turkey", "1", "1", "0", "2"], ["8", "Tunisia", "0", "1", "0", "1"], ["7", "Egypt", "0", "1", "7", "8"], ["2", "Greece", "6", "7", "6", "19"], ["3", "Yugoslavia", "3", "2", "1", "6"], ["5", "Morocco", "1", "1", "0", "2"], ["1", "France", "11", "5", "3", "19"], ["Totaal", "Totaal", "23", "23", "22", "68"], ["4", "Spain", "1", "5", "5", "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:name a country that has the same medal record as turkey. | Morocco | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "3.", "7 June 2011", "Campobasso, Italy", "Clay", "Alizé Lim", "6–2, 6–4"], ["Runner-up", "7.", "9 April 2007", "Civitavecchia, Italy", "Clay", "Darya Kustova", "3–6, 6–4, 6–4"], ["Runner-up", "12.", "27 August 2012", "Bagnatica, Italy", "Clay", "Maria-Elena Camerin", "7–6(5), 6–4"], ["Runner-up", "11.", "14 June 2011", "Padova, Italy", "Clay", "Kristina Mladenovic", "3–6, 6–4, 6–0"], ["Winner", "4.", "20 June 2011", "Rome, Italy", "Clay", "Laura Thorpe", "6–3, 6–0"], ["Runner-up", "1.", "6 October 2003", "Bari, Italy", "Clay", "Bettina Pirker", "6–2, 7–5"], ["Runner-up", "8.", "9 July 2007", "Biella, Italy", "Clay", "Agnieszka Radwańska", "6–3, 6–3"], ["Runner-up", "4.", "31 July 2006", "Martina Franca, Italy", "Clay", "Margalita Chakhnashvili", "6–3, 7–5"], ["Winner", "5.", "4 September 2012", "Mestre, Italy", "Clay", "Estrella Cabeza Candela", "6–1, 3–6, 6–1"], ["Winner", "2.", "18 October 2010", "Seville, Spain", "Clay", "Andrea Gámiz", "6–0, 6–1"], ["Runner-up", "13.", "12 May 2013", "Trnava, Slovakia", "Clay", "Barbora Záhlavová-Strýcová", "6–2, 6–4"], ["Runner-up", "3.", "1 May 2006", "Catania, Italy", "Clay", "María José Martínez Sánchez", "6–3, 4–6, 6–4"], ["Runner-up", "2.", "14 June 2005", "Lenzerheide, Switzerland", "Clay", "Danica Krstajić", "6–2, 7–5"], ["Runner-up", "6.", "3 April 2007", "Dinan, France", "Clay (i)", "Maša Zec Peškirič", "6–4, 6–2"], ["Winner", "1.", "25 July 2006", "Monteroni D'Arbia, Italy", "Clay", "Edina Gallovits-Hall", "6–2, 6–1"], ["Runner-up", "10.", "16 November 2010", "Mallorca, Spain", "Clay", "Diana Enache", "6–4, 6–2"], ["Runner-up", "9.", "11 October 2010", "Settimo San Pietro, Italy", "Clay", "Anastasia Grymalska", "4–6, 6–2, 7–5"], ["Runner-up", "5.", "13 March 2007", "Orange, USA", "Hard", "Naomi Cavaday", "6–1, 6–1"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what country hosted the most tournaments? | Italy | 128 | Answer: |
Table InputTable: [["Pos", "No", "Driver", "Team", "Laps", "Time/Retired", "Grid", "Points"], ["1", "32", "Patrick Carpentier", "Team Player's", "87", "1:48:11.023", "1", "22"], ["7", "51", "Adrian Fernández", "Fernández Racing", "87", "+1:01.4", "5", "6"], ["15", "4", "Roberto Moreno", "Herdez Competition", "85", "+ 2 Laps", "9", "0"], ["11", "27", "Bryan Herta", "PK Racing", "86", "+ 1 Lap", "12", "2"], ["9", "7", "Tiago Monteiro", "Fittipaldi-Dingman Racing", "86", "+ 1 Lap", "15", "4"], ["10", "55", "Mario Domínguez", "Herdez Competition", "86", "+ 1 Lap", "11", "3"], ["6", "20", "Oriol Servià", "Patrick Racing", "87", "+1:00.2", "10", "8"], ["2", "1", "Bruno Junqueira", "Newman/Haas Racing", "87", "+0.8 secs", "2", "17"], ["14", "33", "Alex Tagliani", "Rocketsports Racing", "85", "+ 2 Laps", "14", "0"], ["16", "11", "Geoff Boss", "Dale Coyne Racing", "83", "Mechanical", "19", "0"], ["12", "31", "Ryan Hunter-Reay", "American Spirit Team Johansson", "86", "+ 1 Lap", "17", "1"], ["5", "34", "Mario Haberfeld", "Mi-Jack Conquest Racing", "87", "+42.1 secs", "6", "10"], ["17", "2", "Sébastien Bourdais", "Newman/Haas Racing", "77", "Mechanical", "4", "0"], ["13", "19", "Joël Camathias", "Dale Coyne Racing", "85", "+ 2 Laps", "18", "0"], ["19", "5", "Rodolfo Lavín", "Walker Racing", "10", "Mechanical", "16", "0"], ["18", "15", "Darren Manning", "Walker Racing", "12", "Mechanical", "7", "0"], ["4", "9", "Michel Jourdain, Jr.", "Team Rahal", "87", "+40.8 secs", "13", "12"], ["3", "3", "Paul Tracy", "Team Player's", "87", "+28.6 secs", "3", "14"], ["8", "12", "Jimmy Vasser", "American Spirit Team Johansson", "87", "+1:01.8", "8", "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 was the difference between patrick carpentier and adrian fernandez's times at the 2003 grand prix of montery? | +1:01.4 | 128 | Answer: |
Table InputTable: [["Tour", "Official title", "Venue", "City", "Date\\nStart", "Date\\nFinish", "Prize money\\nUSD", "Report"], ["13", "Super Series Finals", "Cancelled", "Cancelled", "Cancelled", "Cancelled", "500,000", "Report"], ["12", "Hong Kong Super Series", "Ma On Shan Sports Centre\\nQueen Elizabeth Stadium", "Ma On Shan\\nWan Chai", "November 26", "December 2", "200,000", "Report"], ["4", "Swiss Open Super Series", "St. Jakobshalle", "Basel", "March 12", "March 18", "200,000", "Report"], ["9", "Denmark Super Series", "Arena Fyn", "Odense", "October 23", "October 28", "200,000", "Report"], ["10", "French Super Series", "Stade Pierre de Coubertin", "Paris", "October 30", "November 4", "200,000", "Report"], ["11", "China Open Super Series", "Tianhe Gymnasium", "Guangzhou", "November 20", "November 25", "250,000", "Report"], ["8", "Japan Super Series", "Tokyo Metropolitan Gymnasium", "Tokyo", "September 11", "September 16", "200,000", "Report"], ["1", "Malaysia Super Series", "Stadium Badminton Kuala Lumpur", "Kuala Lumpur", "January 16", "January 21", "200,000", "Report"], ["3", "All England Super Series", "National Indoor Arena", "Birmingham", "March 6", "March 11", "200,000", "Report"], ["2", "Korea Open Super Series", "Seoul National University Gymnasium", "Seoul", "January 23", "January 28", "300,000", "Report"], ["5", "Singapore Super Series", "Singapore Indoor Stadium", "Singapore", "May 1", "May 6", "200,000", "Report"], ["7", "China Masters Super Series", "Sichuan Provincial Gymnasium", "Chengdu", "July 10", "July 15", "250,000", "Report"], ["6", "Indonesia Super Series", "Bung Karno Stadium", "Jakarta", "May 7", "May 13", "250,000", "Report"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 tour was the only one that was canceled? | Super Series Finals | 128 | Answer: |
Table InputTable: [["#", "Name", "Took office", "Left office", "Party", "Governor", "Notes"], ["14", "Oliver P. Morton", "January 14, 1861", "January 16, 1861", "Republican", "Henry Smith Lane", ""], ["—", "John R. Cravens", "January 16, 1861", "October 9, 1863", "Republican", "Oliver P. Morton", "acting"], ["29", "Edgar D. Bush", "January 8, 1917", "January 10, 1921", "Republican", "James P. Goodrich", ""], ["37", "Rue J. Alexander", "April 14, 1948", "January 2, 1949", "Republican", "Henry F. Schricker", ""], ["16", "William Cumback", "January 11, 1869", "January 13, 1873", "Republican", "Conrad Baker", ""], ["6", "David Wallace", "December 7, 1831", "December 6, 1837", "Whig", "Noah Noble", ""], ["32", "Edgar D. Bush", "January 14, 1929", "January 9, 1933", "Republican", "Harry G. Leslie", ""], ["31", "F. Harold Van Orman", "January 12, 1925", "January 14, 1929", "Republican", "Edward L. Jackson", ""], ["30", "Emmett Forrest Branch", "January 10, 1921", "April 30, 1924", "Republican", "Warren T. McCray", ""], ["24", "William S. Haggard", "January 11, 1897", "January 14, 1901", "Republican", "James A. Mount", ""], ["35", "Charles M. Dawson", "January 13, 1941", "January 8, 1945", "Democrat", "Henry F. Schricker", ""], ["26", "Hugh Thomas Miller", "January 9, 1905", "January 11, 1909", "Republican", "Frank Hanly", ""], ["44", "Robert D. Orr", "January 8, 1973", "January 12, 1981", "Republican", "Otis R. Bowen", ""], ["21", "Robert S. Robertson", "January 10, 1887", "January 13, 1889", "Republican", "Isaac P. Gray", ""], ["28", "William P. O'Neill", "January 13, 1913", "January 8, 1917", "Democrat", "Samuel M. Ralston", ""], ["25", "Newton W. Gilbert", "January 14, 1901", "January 9, 1905", "Republican", "Winfield T. Durbin", ""], ["15", "Conrad Baker", "January 9, 1865", "January 23, 1867", "Republican", "Oliver P. Morton", ""], ["7", "David Hillis", "December 6, 1837", "December 9, 1840", "Whig", "David Wallace", ""], ["11", "James Henry Lane", "December 5, 1849", "January 10, 1853", "Democrat", "Joseph A. Wright", ""], ["19", "Thomas Hanna", "January 10, 1881", "November 12, 1885", "Republican", "Albert G. Porter", ""], ["17", "Leonidas Sexton", "January 13, 1873", "January 13, 1877", "Republican", "Thomas A. Hendricks", ""], ["12", "Ashbel P. Willard", "January 10, 1853", "January 12, 1857", "Democrat", "Joseph A. Wright", ""], ["40", "Crawford F. Parker", "January 14, 1957", "January 9, 1961", "Republican", "Harold W. Handley", ""], ["18", "Isaac P. Gray", "January 13, 1877", "November 2, 1880", "Democrat", "James D. Williams", ""], ["2", "Ratliff Boon", "December 8, 1819", "September 12, 1822", "Democratic-Republican", "Jonathan Jennings", ""], ["5", "Milton Stapp", "December 3, 1828", "December 7, 1831", "Independent", "James B. Ray", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 took office in 1861 but left office just two days later? | Oliver P. Morton | 128 | Answer: |
Table InputTable: [["Year", "Date", "Winner", "Result", "Loser", "Location"], ["2000", "October 29", "New York Giants", "24-7", "Philadelphia Eagles", "Giants Stadium"], ["2000", "September 10", "New York Giants", "33-18", "Philadelphia Eagles", "Veterans Stadium"], ["2007", "January 7", "Philadelphia Eagles", "23-20", "New York Giants", "Lincoln Financial Field"], ["2005", "December 11", "New York Giants", "26-23 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2001", "January 7", "New York Giants", "20-10", "Philadelphia Eagles", "Giants Stadium"], ["2007", "December 9", "New York Giants", "16-13", "Philadelphia Eagles", "Lincoln Financial Field"], ["2005", "November 20", "New York Giants", "27-17", "Philadelphia Eagles", "Giants Stadium"], ["2004", "September 12", "Philadelphia Eagles", "31-17", "New York Giants", "Lincoln Financial Field"], ["2006", "September 17", "New York Giants", "30-24 (OT)", "Philadelphia Eagles", "Lincoln Financial Field"], ["2006", "December 17", "Philadelphia Eagles", "36-22", "New York Giants", "Giants Stadium"], ["2009", "November 1", "Philadelphia Eagles", "40-17", "New York Giants", "Lincoln Financial Field"], ["2003", "November 16", "Philadelphia Eagles", "28-10", "New York Giants", "Lincoln Financial Field"], ["2002", "December 28", "New York Giants", "10-7", "Philadelphia Eagles", "Giants Stadium"], ["2001", "December 30", "Philadelphia Eagles", "24-21", "New York Giants", "Veterans Stadium"], ["2001", "October 22", "Philadelphia Eagles", "10-9", "New York Giants", "Giants Stadium"], ["2008", "November 9", "New York Giants", "36-31", "Philadelphia Eagles", "Lincoln Financial Field"], ["2009", "January 11", "Philadelphia Eagles", "23-11", "New York Giants", "Giants Stadium"], ["2004", "November 28", "Philadelphia Eagles", "27-6", "New York Giants", "Giants Stadium"], ["2008", "December 7", "Philadelphia Eagles", "20-14", "New York Giants", "Giants Stadium"], ["2009", "December 13", "Philadelphia Eagles", "45-38", "New York Giants", "Giants Stadium"], ["2002", "October 28", "Philadelphia Eagles", "17-3", "New York Giants", "Veterans Stadium"], ["2003", "October 19", "Philadelphia Eagles", "14-10", "New York Giants", "Giants Stadium"], ["2007", "September 30", "New York Giants", "16-3", "Philadelphia Eagles", "Giants Stadium"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the only winner in the year 2000? | New York Giants | 128 | Answer: |
Table InputTable: [["Team", "City", "Venue", "Capacity", "Head Coach", "Team Captain", "Past Season"], ["Aboomoslem", "Mashhad", "Samen", "35,000", "Ali Hanteh", "Saeed Khani", "4th"], ["Persepolis", "Tehran", "Azadi", "90,000", "Nelo Vingada", "Karim Bagheri", "Champion"], ["Foolad", "Ahvaz", "Takhti Ahvaz", "15,000", "Majid Jalali", "Ali Badavi", "Qualifier"], ["Payam", "Mashhad", "Samen", "35,000", "Kazem Ghiyasiyan", "Mehdi Hasheminasab", "Qualifier"], ["Rah Ahan", "Rey, Iran", "Rah Ahan", "15,000", "Mehdi Tartar", "Ahmad Taghavi", "12th"], ["Pas Hamedan", "Hamedan", "Ghods", "5,000", "Vinko Begovic", "Omid Khouraj", "5th"], ["Damash Gilan", "Rasht", "Sardar Jangal", "15,000", "Stanko Poklepović", "Mohammad Reza Mahdavi", "15th"], ["Malavan", "Anzali", "Takhti Anzali", "8,000", "Mohammad Ahmadzadeh", "Masoud Gholamalizad", "16th"], ["Esteghlal", "Tehran", "Azadi", "90,000", "Amir Ghalenoei", "Farhad Majidi", "13th"], ["Saba Qom", "Qom", "Yadegar Emam", "15,000", "Firouz Karimi", "Yahya Golmohammadi", "3rd"], ["Paykan", "Qazvin", "Shahid Rajaei", "5,000", "Ali Asghar Modir Roosta", "Mohammad Reza Tahmasebi", "9th"], ["Moghavemat", "Shiraz", "Hafezieh", "20,000", "Gholam Hossein Peyrovani", "Mostafa Sabri", "14th"], ["Bargh Shiraz", "Shiraz", "Hafezieh", "20,000", "Rasoul Korbekandi", "Sattar Zare", "7th"], ["Saipa", "Karaj", "Enghelab Karaj", "15,000", "Mohammad Mayeli Kohan", "Ebrahim Sadeghi", "11th"], ["Mes Kerman", "Kerman", "Shahid Bahonar", "15,000", "Parviz Mazloomi", "Farzad Hosseinkhani", "10th"], ["Est. Ahvaz", "Ahvaz", "Takhti Ahvaz", "30,000", "Khodadad Azizi", "Afshin Komaei", "8th"], ["Zob Ahan", "Esfahan", "Foolad Shahr", "25,000", "Mansour Ebrahimzadeh", "Mohammad Salsali", "6th"], ["Sepahan", "Esfahan", "Foolad Shahr", "25,000", "Farhad Kazemi", "Moharram Navidkia", "2nd"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the head coach of the only team in 4th place? | Ali Hanteh | 128 | Answer: |
Table InputTable: [["Tour", "Official title", "Venue", "City", "Date\\nStart", "Date\\nFinish", "Prize money\\nUSD", "Report"], ["2", "Korea Open Super Series", "Seoul National University Gymnasium", "Seoul", "January 23", "January 28", "300,000", "Report"], ["6", "Indonesia Super Series", "Bung Karno Stadium", "Jakarta", "May 7", "May 13", "250,000", "Report"], ["1", "Malaysia Super Series", "Stadium Badminton Kuala Lumpur", "Kuala Lumpur", "January 16", "January 21", "200,000", "Report"], ["4", "Swiss Open Super Series", "St. Jakobshalle", "Basel", "March 12", "March 18", "200,000", "Report"], ["5", "Singapore Super Series", "Singapore Indoor Stadium", "Singapore", "May 1", "May 6", "200,000", "Report"], ["11", "China Open Super Series", "Tianhe Gymnasium", "Guangzhou", "November 20", "November 25", "250,000", "Report"], ["8", "Japan Super Series", "Tokyo Metropolitan Gymnasium", "Tokyo", "September 11", "September 16", "200,000", "Report"], ["9", "Denmark Super Series", "Arena Fyn", "Odense", "October 23", "October 28", "200,000", "Report"], ["13", "Super Series Finals", "Cancelled", "Cancelled", "Cancelled", "Cancelled", "500,000", "Report"], ["7", "China Masters Super Series", "Sichuan Provincial Gymnasium", "Chengdu", "July 10", "July 15", "250,000", "Report"], ["12", "Hong Kong Super Series", "Ma On Shan Sports Centre\\nQueen Elizabeth Stadium", "Ma On Shan\\nWan Chai", "November 26", "December 2", "200,000", "Report"], ["10", "French Super Series", "Stade Pierre de Coubertin", "Paris", "October 30", "November 4", "200,000", "Report"], ["3", "All England Super Series", "National Indoor Arena", "Birmingham", "March 6", "March 11", "200,000", "Report"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:was the prize money larger at the indonesia super series or korea open super series? | Korea Open Super Series | 128 | Answer: |
Table InputTable: [["Builder", "Works numbers", "Dates", "CN numbers", "GT numbers", "Notes"], ["MLW", "45163-45182", "1908", "2627-2646", "631-650", ""], ["ALCO", "49663-49674", "1911", "2616-2625\\n2677-2678", "766-777", "built at ALCO's Brooks Works"], ["ALCO", "42046-42060\\n43540-43554", "1907", "2567-2576\\n2606-2615\\n2664-2665\\n2669-2676", "706-720\\n752\\n755\\n758\\n761\\n763", ""], ["ALCO", "50472-50481", "1911", "2626\\n2666-2668\\n2679-2684", "779-780\\n784\\n786-787", ""], ["MLW", "42331-42345\\n43150-43164", "1907", "2577-2605\\n2661-2662\\n2685", "721-750", ""], ["MLW", "39548-39562\\n40583-40622", "1906", "2525-2566\\n2663", "651-705", ""], ["MLW", "46880-46894", "1910", "2647-2660\\n2686", "616-630", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the next year it was produced after 1908? | 1910 | 128 | Answer: |
Table InputTable: [["Series", "Years", "Volumes", "Writer", "Editor", "Remarks"], ["Shelena", "2005", "1", "Jéromine Pasteur", "Casterman", ""], ["Daddy", "1991-92", "2", "Loup Durand", "Cl. Lefrancq", ""], ["Ivan Zourine", "1979", "2", "Jacques Stoquart", "Magic-Strip", ""], ["Les zingari", "2004–2005", "2", "Yvan Delporte", "Hibou", ""], ["L'affaire Dominici", "2010", "1", "Pascal Bresson", "Glénat", ""], ["Ikar", "1995–1997", "2", "Pierre Makyo", "Glénat", ""], ["Valhardi", "1984–1986", "2", "Jacques Stoquart and André-Paul Duchâteau", "Dupuis", "Continuation of the series after Jijé and Eddy Paape"], ["Alain Brisant", "1985", "1", "Maurice Tillieux", "Dupuis", ""], ["Bruno Brazil", "1973–1977", "5", "Greg", "Magic-Strip", "William Vance drew the comics, Follet provided the page lay-out"], ["Terreur", "2002–2004", "2", "André-Paul Duchâteau", "Le Lombard", "Fictional biography of Madame Tussaud"], ["Les autos de l'aventure", "1996–1998", "2", "De la Royère", "Citroën", "Promotional comics"], ["L'étoile du soldat", "2007", "1", "Christophe De Ponfilly", "Casterman", "Announced (28 August 2007)"], ["Harricana", "1992", "1", "Jean-Claude de la Royère", "Claude Lefrancq", "Drawn by Denis Mérezette, Follet did the page lay-out"], ["Marshall Blueberry", "1994", "1", "Jean Giraud", "Alpen", "Drawn by William Vance, Follet did the page lay-out"], ["L'Iliade", "1982", "1", "Jacques Stoquart", "Glénat", "Adapted from the Ilias by Homer"], ["Jacques Le Gall", "1984–1985", "2", "Jean-Michel Charlier", "Dupuis", "A collaboration with MiTacq"], ["Steve Severin", "1981–2003", "9", "Jacques Stoquart and Yvan Delporte", "Glénat", "3 in French - 6 additional in Dutch"], ["Edmund Bell", "1987–1990", "4", "Jacques Stoquart and Martin Lodewijk", "Cl. Lefrancq", "Based on the stories by John Flanders (Jean Ray)"], ["Bob Morane", "1991–2000", "3", "Henri Vernes", "Nautilus and Claude Lefrancq", "Follet drew one story in 2000, and made the cover art for two others (drawn by Gerald Forton)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 series on the table? | L'affaire Dominici | 128 | Answer: |
Table InputTable: [["Political lieutenant", "District\\n(Area)", "Took Office", "Left Office", "Party leader"], ["Claude Wagner", "Saint-Hyacinthe\\n(Montérégie)", "1972", "1978", "Robert Stanfield\\nJoe Clark"], ["Lucien Bouchard", "Lac-Saint-Jean\\n(Saguenay-Lac-Saint-Jean)", "1988", "1990", "Brian Mulroney"], ["André Bachand", "Richmond—Arthabaska\\n(Centre-du-Québec &\\nEastern Townships)", "1998", "2004", "Joe Clark\\nPeter MacKay"], ["Benoît Bouchard", "Roberval\\n(Saguenay-Lac-Saint-Jean)", "1990", "1993", "Brian Mulroney"], ["Léon Balcer", "Trois-Rivières\\n(Mauricie)", "1957", "1965", "John George Diefenbaker"], ["Georges-Henri Héon", "Argenteuil\\n(Laurentides)", "1949", "1949", "George A. Drew"], ["Monique Landry", "Blainville—Deux-Montagnes\\n(Laurentides)", "1993", "1993", "Kim Campbell"], ["Marcel Faribault", "none", "1967", "1968", "Robert Stanfield"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 district was claude wagner over? lac-saint-jean or saint-hyacinthe | Saint-Hyacinthe (Montérégie) | 128 | Answer: |
Table InputTable: [["May 20-21\\n118", "March 9\\n120", "December 25-26\\n122", "October 13-14\\n124", "August 1-2\\n126"], ["May 20, 2012", "March 9, 2016", "December 26, 2019", "October 14, 2023", "August 2, 2027"], ["May 20, 2050", "March 9, 2054", "December 26, 2057", "October 13, 2061", "August 2, 2065"], ["May 21, 1993", "March 9, 1997", "December 25, 2000", "October 14, 2004", "August 1, 2008"], ["May 21, 2031", "March 9, 2035", "December 26, 2038", "October 14, 2042", "August 2, 2046"], ["128", "130", "132", "134", "136"], ["138", "140", "142", "144", "146"], ["148", "150", "152", "154", "156"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 year listed after 2012? | 2016 | 128 | Answer: |
Table InputTable: [["Series Number", "Season Number", "Episode Title", "Premiere Date", "Production Code"], ["4", "4", "Close Encounters", "November 15, 1998", "104"], ["11", "11", "JB's Big Break", "February 21, 1999", "111"], ["12", "12", "Bottom's Up", "March 7, 1999", "112"], ["1", "1", "Going Up!", "October 25, 1998", "101"], ["13", "13", "Hot Dog", "March 14, 1999", "113"], ["2", "2", "Who's The Man", "November 1, 1998", "102"], ["8", "8", "Special FX-Ation", "January 24, 1999", "108"], ["9", "9", "The Famous Stone Gold", "January 31, 1999", "109"], ["10", "10", "Kiss And Tell", "February 7, 1999", "110"], ["5", "5", "Hurricane Jules", "November 22, 1998", "105"], ["7", "7", "Front Page", "January 17, 1999", "107"], ["6", "6", "Switcheroo", "November 29, 1998", "106"], ["3", "3", "Vootle-Muck-A-Heev", "November 8, 1998", "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:what was the name of the last episode? | Hot Dog | 128 | Answer: |
Table InputTable: [["Year", "Title", "Role", "Notes"], ["2003", "Homem Objeto", "Eva", ""], ["2002", "O Beijo do Vampiro", "Lara", ""], ["2006", "Dança no Gelo", "Herself", "Reality show of Domingão do Faustão"], ["2013", "A Grande Família", "Bianca", "Cameo"], ["1997", "Zazá", "Dora Dumont", ""], ["2008", "Episódio Especial", "Herself", "Cameo"], ["2007", "Paraíso Tropical", "Betina Monteiro", "Cameo"], ["2008", "A Favorita", "Maria do Céu / Pâmela Queiroz", ""], ["1992", "Você Decide", "", "Ep: \"Mamãe Coragem\""], ["2009", "Decamerão - A Comédia do Sexo", "Monna", ""], ["2004", "Casseta & Planeta, Urgente!", "Darlene Sampaio", "Cameo"], ["1990", "Meu Bem, Meu Mal", "", "Cameo"], ["1999", "Você Decide", "Socorro", "Ep: \"A Filha de Maria\""], ["1999", "Mundo VIP", "Herself", "Cameo"], ["2002", "Os Normais", "Kátia", "Ep: \"É Nojento, Mas é Normal\""], ["1992", "Escolinha do Professor Raimundo", "Capituzinha", ""], ["2009", "Episódio Especial", "Herself", "Cameo"], ["2003", "Celebridade", "Darlene Sampaio", ""], ["1999", "Suave Veneno", "Marina Canhedo", ""], ["1990", "Mico Preto", "Denise Menezes Garcia", ""], ["1995", "A Próxima Vítima", "Carina Carvalho Rossi", ""], ["1998", "Era Uma Vez...", "Emilia Zanella", ""], ["2010", "As Cariocas", "Alice", "Ep: \"A Suicida da Lapa\""], ["1999", "Terra Nostra", "Hannah", "Cameo"], ["2001", "Sítio do Picapau Amarelo", "", "Ep: \"A Festa da Cuca\""], ["2000", "A Invenção do Brasil", "Moema", ""], ["1992", "Você Decide", "", "Ep: \"Tabu\""], ["2009", "Ó Paí, Ó", "Keila Cristina", "Ep: \"A Outra\""], ["1996", "Você Decide", "", "Ep: \"Justiça\""], ["1994", "Confissões de Adolescente", "Carol", ""], ["2002", "Festival de Desenhos", "Herself", "Hoster"], ["2001", "A Padroeira", "Cecília de Sá", ""], ["1996", "Vira-Lata", "Tatu / Bárbara", ""], ["2012", "Louco por Elas", "Giovanna Bianchi", ""], ["2011", "Insensato Coração", "Natalie Lamour", ""], ["2002", "Brava Gente", "Jane", "Ep: \"Loucos de Pedra\""], ["2005", "América", "Sol de Oliveira", ""], ["1993", "Contos de Verão", "Fabíola", ""], ["2000", "Laços de Família", "Íris Frank Lacerda", ""], ["2006", "Pé na Jaca", "Elizabeth Aparecida Barra", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 character did play in the show "homem objeto"? | Eva | 128 | Answer: |
Table InputTable: [["Round", "Date", "Circuit", "Winning driver (TA2)", "Winning vehicle (TA2)", "Winning driver (TA1)", "Winning vehicle (TA1)"], ["1", "May 21", "Sears Point", "Greg Pickett", "Chevrolet Corvette", "Gene Bothello", "Chevrolet Corvette"], ["7", "August 19", "Mosport", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["9", "October 8", "Laguna Seca", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["8", "September 4", "Road America", "Greg Pickett", "Chevrolet Corvette", "Bob Tullius", "Jaguar XJS"], ["3", "June 11", "Portland", "Tuck Thomas", "Chevrolet Monza", "Bob Matkowitch", "Chevrolet Corvette"], ["6", "August 13", "Brainerd", "Jerry Hansen", "Chevrolet Monza", "Bob Tullius", "Jaguar XJS"], ["2", "June 4", "Westwood", "Ludwig Heimrath", "Porsche 935", "Nick Engels", "Chevrolet Corvette"], ["5", "July 8", "Watkins Glen‡", "Hal Shaw, Jr.\\n Monte Shelton", "Porsche 935", "Brian Fuerstenau\\n Bob Tullius", "Jaguar XJS"], ["10", "November 5", "Mexico City", "Ludwig Heimrath", "Porsche 935", "Bob Tullius", "Jaguar XJS"], ["4", "June 25", "Mont-Tremblant", "Monte Sheldon", "Porsche 935", "Bob Tullius", "Jaguar XJS"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:on average how many times was chevrolet corvette listed as the winning vehicle(ta2). | 4 | 128 | Answer: |
Table InputTable: [["Political lieutenant", "District\\n(Area)", "Took Office", "Left Office", "Party leader"], ["André Bachand", "Richmond—Arthabaska\\n(Centre-du-Québec &\\nEastern Townships)", "1998", "2004", "Joe Clark\\nPeter MacKay"], ["Benoît Bouchard", "Roberval\\n(Saguenay-Lac-Saint-Jean)", "1990", "1993", "Brian Mulroney"], ["Lucien Bouchard", "Lac-Saint-Jean\\n(Saguenay-Lac-Saint-Jean)", "1988", "1990", "Brian Mulroney"], ["Georges-Henri Héon", "Argenteuil\\n(Laurentides)", "1949", "1949", "George A. Drew"], ["Léon Balcer", "Trois-Rivières\\n(Mauricie)", "1957", "1965", "John George Diefenbaker"], ["Marcel Faribault", "none", "1967", "1968", "Robert Stanfield"], ["Monique Landry", "Blainville—Deux-Montagnes\\n(Laurentides)", "1993", "1993", "Kim Campbell"], ["Claude Wagner", "Saint-Hyacinthe\\n(Montérégie)", "1972", "1978", "Robert Stanfield\\nJoe Clark"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:andre bachand was in office from 1998 to 2004 who was his party leader? | Joe Clark Peter MacKay | 128 | Answer: |
Table InputTable: [["Series", "Name", "Age", "Hometown", "Occupation", "Status"], ["BB1", "Anna Nolan", "29", "Dublin", "Office Manager", "2nd - Runner-up"], ["BB1", "Craig Phillips", "28", "Liverpool", "Builder", "1st - Winner"], ["BB:CH", "Emilia Arata", "18", "Birmingham", "Circus Performer", "2nd - Runner-up"], ["BB2", "Helen Adams", "22", "South Wales", "Hairdresser", "2nd - Runner-up"], ["BB8", "Amanda Marchant", "18", "Stoke-on-Trent", "Student", "2nd - Runner-up"], ["BB8", "Sam Marchant", "18", "Stoke-on-Trent", "Student", "2nd - Runner-up"], ["BB3", "Jonny Regan", "29", "County Durham", "Firefighter", "2nd - Runner-up"], ["TBB", "Caroline Cloke", "18", "Kent", "Student", "2nd - Runner-up"], ["UBB", "Josie Gibson", "25", "Bristol", "Participated in BB11", "14th - Walked"], ["BB4", "Justine Sellman", "27", "Leeds", "Sales assistant", "12th - Evicted"], ["BB13", "Adam Kelly", "27", "Dudley", "Unemployed", "2nd - Runner-up"], ["BB11", "Laura McAdam", "20", "Warwickshire", "Sales assistant", "13th - Walked"], ["UBB", "Chantelle Houghton", "27", "Essex", "Participated in CBB5", "3rd - Third Place"], ["BB11", "Josie Gibson", "25", "Bristol", "Financial sales rep", "1st - Winner"], ["BB12", "Jay McKray", "27", "Newcastle", "Plumber/Fitness Instructor/DJ/barber", "2nd - Runner-up"], ["BB5", "Emma Greenwood", "20", "Manchester", "Administrative Assistant", "12th - Ejected"], ["BB6", "Eugene Sully", "27", "Crawley", "Student", "2nd - Runner-up"], ["TBB", "Paul Brennan", "18", "Belfast", "Student", "1st - Winner"], ["BB8", "Lesley Brain", "60", "Gloucestershire", "Retired", "21st - Walked"], ["BB8", "Liam McGough", "22", "County Durham", "Tree Surgeon", "3rd - Third Place"], ["BB5", "Jason Cowan", "30", "South Lanarkshire", "Air Steward", "2nd - Runner-up"], ["BB3", "Alison Hammond", "27", "Birmingham", "Cinema Team Leader", "12th - Evicted"], ["BB14", "Dexter Koh", "28", "London", "Celebrity publicist", "2nd - Runner-up"], ["BB12", "Jem Palmer", "28", "Tamworth", "Professional Wrestler", "8th - Walked"], ["BB4", "Anouska Golebiewski", "20", "Manchester", "Nursery Assistant", "13th - Evicted"], ["BB9", "Rachel Rice", "24", "Torfaen", "Trainee Teacher/Actress", "1st - Winner"], ["BB12", "Aaron Allard-Morgan", "30", "Weston-super-Mare", "Contract manager", "1st - Winner"], ["BB9", "Rebecca Shiner", "21", "Coventry", "Nursery Nurse", "14th - Evicted"], ["BB13", "Luke Anderson", "31", "North Wales", "Development chef", "1st - Winner"], ["TBB", "Tracey Fowler", "18", "Cheshire", "Student", "3rd - Third Place"], ["BB12", "Louise Cliffe", "25", "Manchester", "Model/Actress", "4th - Evicted"], ["BB6", "Craig Coates", "20", "Norfolk", "Hair Stylist", "5th - Evicted"], ["BB6", "Anthony Hutton", "23", "Newcastle", "70s Dancer", "1st - Winner"], ["BB8", "Emily Parr", "19", "Bristol", "Student", "22nd - Ejected"], ["BB12", "Mark Henderson", "28", "London", "Sales", "12th - Walked"], ["BB11", "Dave (David) Vaughan", "39", "Torfaen", "Minister", "2nd - Runner-up"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the difference in age between craig phillips and anna nolan? | 1 year | 128 | Answer: |
Table InputTable: [["School", "Season", "Record", "Conference Record", "Place", "Postseason"], ["Illinois", "1919–20", "9–4", "8–4", "3rd", ""], ["Illinois", "1914–15", "16–0", "12–0", "T1st", "National Champions"], ["Illinois", "1915–16", "13–3", "9–3", "T2nd", ""], ["Illinois", "1918–19", "6–8", "5–7", "5th", ""], ["Illinois", "1912–20", "85–34", "64–31", "–", ""], ["Illinois", "1913–14", "9–4", "7–3", "3rd", ""], ["Illinois", "1917–18", "9–6", "6–6", "T4th", ""], ["Illinois", "1912–13", "10–6", "7–6", "5th", ""], ["Illinois", "1916–17", "13–3", "10–2", "T1st", "Big Ten Champions"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which season did illinois have a 16-0 record? 1918-1919 or 1914-1915? | 1914-15 | 128 | Answer: |
Table InputTable: [["Specifications", "Foundation", "Essentials", "Standard", "Datacenter"], ["Remote Desktop Services limits", "50 Remote Desktop Services connections", "Gateway only", "Unlimited", "Unlimited"], ["Windows Server Update Services", "No", "Yes", "Yes", "Yes"], ["Network Policy and Access Services limits", "50 RRAS connections and 10 IAS connections", "250 RRAS connections, 50 IAS connections, and 2 IAS Server Groups", "Unlimited", "Unlimited"], ["Windows Deployment Services", "Yes", "Yes", "Yes", "Yes"], ["Licensing model", "Per server", "Per server", "Per CPU pair + CAL", "Per CPU pair + CAL"], ["File Services limits", "1 standalone DFS root", "1 standalone DFS root", "Unlimited", "Unlimited"], ["Virtualization rights", "N/A", "Either in 1 VM or 1 physical server, but not both at once", "2 VMs", "Unlimited"], ["Application server role", "Yes", "Yes", "Yes", "Yes"], ["Server Manager", "Yes", "Yes", "Yes", "Yes"], ["Server Core mode", "No", "No", "Yes", "Yes"], ["DNS server role", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Certificate Services", "Certificate Authorities only", "Certificate Authorities only", "Yes", "Yes"], ["Windows Powershell", "Yes", "Yes", "Yes", "Yes"], ["DHCP role", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Rights Management Services", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Federation Services", "Yes", "No", "Yes", "Yes"], ["Fax server role", "Yes", "Yes", "Yes", "Yes"], ["User limit", "15", "25", "Unlimited", "Unlimited"], ["Active Directory Lightweight Directory Services", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Domain Services", "Must be root of forest and domain", "Must be root of forest and domain", "Yes", "Yes"], ["Web Services (Internet Information Services)", "Yes", "Yes", "Yes", "Yes"], ["Memory limit", "32 GB", "64 GB", "4 TB", "4 TB"], ["Distribution", "OEM only", "Retail, volume licensing, OEM", "Retail, volume licensing, OEM", "Volume licensing and OEM"], ["Print and Document Services", "Yes", "Yes", "Yes", "Yes"], ["Processor chip limit", "1", "2", "64", "64"], ["UDDI Services", "Yes", "Yes", "Yes", "Yes"], ["Hyper-V", "No", "No", "Yes", "Yes"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which editions of windows server 2012 have unlimited remote desktop services connections? | 2 | 128 | Answer: |
Table InputTable: [["No.", "Date", "Tournament", "Surface", "Partnering", "Opponent in the final", "Score"], ["2.", "April 4, 2011", "Chile F2", "Clay", "Sergio Galdós", "Guillermo Hormazábal\\n Rodrigo Pérez", "5–7, 7–6(5), [10–5]"], ["5.", "August 5, 2012", "Manta", "Hard", "Renzo Olivo", "Víctor Estrella\\n João Souza", "6–3, 6–0"], ["1.", "September 13, 2010", "Ecuador F2", "Hard", "Roberto Quiroz", "Peter Aarts\\n Christopher Racz", "6–4, 6–4"], ["3.", "April 11, 2011", "Chile F3", "Clay", "Roberto Quiroz", "Luis David Martínez\\n Miguel Ángel Reyes-Varela", "6–4, 7–5"], ["7.", "August 26, 2012", "Ecuador F3", "Clay", "Sergio Galdós", "Mauricio Echazú\\n Guillermo Rivera-Aránguiz", "6-2, 6-1"], ["4.", "August 8, 2011", "Peru F1", "Clay", "Sergio Galdós", "Martín Cuevas\\n Guido Pella", "6–4, 6–0"], ["10.", "May 27, 2013", "Argentina F8", "Clay", "Sergio Galdós", "Daniel Dutra da Silva\\n Pablo Galdón", "6-0, 7-5"], ["6.", "August 20, 2012", "Colombia F2", "Clay", "Ariel Behar", "Nicolas Barrientos\\n Michael Quintero", "2-1 Ret."], ["9.", "May 13, 2013", "Argentina F6", "Clay", "Sergio Galdós", "Franco Agamenone\\n Jose Angel Carrizo", "4-6, 6-4, [10–1]"], ["8.", "October 8, 2012", "Chile F8", "Clay", "Gustavo Sterin", "Cristóbal Saavedra-Corvalán\\n Guillermo Rivera-Aránguiz", "6-4, 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 is the total number of opponents listed in the table? | 20 | 128 | Answer: |
Table InputTable: [["No", "Name", "Code", "Formed", "Headquarters", "Administrative\\nDivision", "Area (km2)", "Population\\n(2001 census)", "% of State\\nPopulation", "Density\\n(per km2)", "Urban (%)", "Literacy (%)", "Sex Ratio", "Tehsils", "Source"], ["22", "Nashik", "NS", "1 May 1960", "Nashik", "Nashik", "15,530", "4,993,796", "5.15%", "321.56", "38.8", "74.4", "927", "15", "District website"], ["32", "Thane", "TH", "1 May 1960", "Thane", "Konkan", "9,558", "8,131,849", "8.39%", "850.71", "72.58", "80.67", "858", "15", "District website"], ["3", "Amravati", "AM", "1 May 1960", "Amravati", "Amravati", "12,626", "2,606,063", "2.69%", "206.40", "34.50", "82.5", "938", "14", "District website"], ["13", "Jalgaon", "JG", "1 May 1960", "Jalgaon", "Nashik", "11,765", "3,679,936", "3.8%", "312.79", "71.4", "76.06", "932", "15", "District website"], ["5", "Beed", "BI", "1 May 1960", "Beed", "Aurangabad", "10,439", "2,161,250", "2.23%", "207.04", "17.91", "68", "936", "11", "District website"], ["15", "Kolhapur", "KO", "1 May 1960", "Kolhapur", "Pune", "7,685", "3,515,413", "3.63%", "457.44", "29.65", "77.23", "949", "10", "District website"], ["9", "Dhule", "DH", "1 May 1960", "Dhule", "Nashik", "8,063", "1,707,947", "1.76%", "211.83", "26.11", "71.6", "944", "4", "District website"], ["2", "Akola", "AK", "1 May 1960", "Akola", "Amravati", "5,417", "1,818,617", "1.68%", "300.78", "38.49", "81.41", "938", "7", "District website"], ["33", "Wardha", "WR", "1 May 1960", "Wardha", "Nagpur", "6,310", "1,230,640", "1.27%", "195.03", "25.17", "80.5", "936", "8", "District website"], ["19", "Nagpur", "NG", "1 May 1960", "Nagpur", "Nagpur", "9,897", "4,051,444", "4.18%", "409.36", "64.33", "84.18", "933", "13", "District website"], ["30", "Sindhudurg", "SI", "1 May 1981", "Oros", "Konkan", "5,207", "868,825", "0.9%", "166.86", "9.5", "80.3", "1,079", "8", "District website"], ["7", "Buldhana", "BU", "1 May 1960", "Buldhana", "Amravati", "9,680", "2,232,480", "2.3%", "230.63", "21.2", "75.8", "946", "13", "District website"], ["34", "Washim", "WS", "1 July 1998", "Washim", "Amravati", "5,150", "1,020,216", "1.05%", "275.98", "17.49", "74.02", "939", "6", "District website"], ["35", "Yavatmal", "YA", "1 May 1960", "Yavatmal", "Amravati", "13,582", "2,077,144", "2.14%", "152.93", "18.6", "57.96", "951", "16", "District website"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 districts have a percentage of state population that is greater than 5%? | 4 | 128 | Answer: |
Table InputTable: [["Pos", "Rider", "Manufacturer", "Time/Retired", "Points"], ["21", "David Garcia", "Yamaha", "+1:33.867", ""], ["20", "Lucas Oliver Bulto", "Yamaha", "+1:25.758", ""], ["13", "Tomomi Manako", "Yamaha", "+27.903", "3"], ["18", "Julien Allemand", "TSR-Honda", "+1:16.347", ""], ["17", "Johann Stigefelt", "Yamaha", "+1:07.433", ""], ["19", "Fonsi Nieto", "Yamaha", "+1:25.622", ""], ["1", "Loris Capirossi", "Honda", "38:04.730", "25"], ["8", "Stefano Perugini", "Honda", "+20.891", "8"], ["15", "Jarno Janssen", "TSR-Honda", "+56.248", "1"], ["11", "Alex Hofmann", "TSR-Honda", "+26.933", "5"], ["16", "Luca Boscoscuro", "TSR-Honda", "+56.432", ""], ["24", "Henk Van De Lagemaat", "Honda", "+1 Lap", ""], ["12", "Sebastian Porto", "Yamaha", "+27.054", "4"], ["10", "Anthony West", "TSR-Honda", "+26.816", "6"], ["9", "Jason Vincent", "Honda", "+21.310", "7"], ["14", "Masaki Tokudome", "TSR-Honda", "+33.161", "2"], ["Ret", "Andre Romein", "Honda", "Retirement", ""], ["5", "Shinya Nakano", "Yamaha", "+0.742", "11"], ["4", "Tohru Ukawa", "Honda", "+0.537", "13"], ["Ret", "Maurice Bolwerk", "TSR-Honda", "Retirement", ""], ["2", "Valentino Rossi", "Aprilia", "+0.180", "20"], ["7", "Franco Battaini", "Aprilia", "+20.889", "9"], ["23", "Arno Visscher", "Aprilia", "+1:40.635", ""], ["Ret", "Roberto Rolfo", "Aprilia", "Retirement", ""], ["Ret", "Marcellino Lucchi", "Aprilia", "Retirement", ""], ["22", "Rudie Markink", "Aprilia", "+1:40.280", ""], ["3", "Jeremy McWilliams", "Aprilia", "+0.534", "16"], ["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:what is the number of drivers that drove a vehicle manufactored by yamaha? | 7 | 128 | Answer: |
Table InputTable: [["Chart Year", "Artist", "Album", "Song", "Billboard Hot 100", "Billboard Hot R&B/Hip Hop", ""], ["2012", "Ciara", "Forthcoming Album", "Got Me Good", "New Single", "", ""], ["2013", "Ciara", "Ciara", "Overdose", "New Single", "", ""], ["2013", "Ciara", "One Woman Army", "Body Party", "34", "", ""], ["2009", "Keyshia Cole", "A Different Me", "You Complete Me", "67", "", ""], ["2013", "Yo Gotti", "I Am", "Don't Come Around", "New Single", "", ""], ["2013", "Yo Gotti", "I Am", "King Shit f/TI", "New Single", "", ""], ["2013", "T.I.", "Trouble Man", "Trap Back Jumpin", "New Single", "", ""], ["2013", "Yo Gotti", "Forthcoming Album", "Act Right", "New Single", "", ""], ["2013", "Omarion", "Self Made 3", "Know You Better f/ Fab", "New Single", "", ""], ["2010", "Ciara", "Basic Instinct", "Ride ft. Ludacris", "45", "5", ""], ["2012", "Keyshia Cole", "Woman to Woman", "Enough of No Love f Lil Wayne", "", "", ""], ["2012", "Keyshia Cole", "Woman to Woman", "Trust and Believe", "32", "", ""], ["2013", "T.I.", "Trouble Man", "Sorry f Andre 3000 Trouble Man", "New Single", "", ""], ["2013", "Tyler The Creator", "Wolf", "Domo 23 & Rusty", "New Single", "", ""], ["2009", "Keyshia Cole", "Just Like You", "Remember", "24", "1", ""], ["2013", "Kelly Rowland", "Talk A Good Game", "Dirty Laundry", "New Single", "", ""], ["2013", "Chris Brown", "X", "Love More f/Nikki Minaj", "31", "", ""], ["2012", "Chris Brown", "Fortune", "Don't Judge Me", "18", "", ""], ["2013", "Iggy Azelea", "Forthcoming Album", "Change your Life f/ TI", "New Single", "", ""], ["2013", "Fantasia", "Side Effects of You", "Without Me f/ Kelly Rolland & Miss Elliot", "New Single", "", ""], ["2012", "Chris Brown f/Kevin McCall", "Fortune", "Strip", "42", "3", ""], ["2007", "Keyshia Cole", "Just Like You", "Shoulda Let You Go", "41", "6", ""], ["2013", "Chris Brown", "X", "Fine China", "31", "", ""], ["2013", "Aloe Blacc", "Wake Me Up", "Wake Me Up", "New Single", "", ""], ["2009", "Letoya Luckett", "Lady Love", "Regret ft. Ludacris", "78", "8", ""], ["2007", "Sean Paul", "The Trinity", "(When You Gonna) Give It Up To Me", "3", "5", ""], ["2012", "Rihanna", "Unapologetic", "Various Songs", "11", "14", ""], ["2012", "Chris Brown f/ Big Sean & Wiz Khalifa", "Fortune", "Till I Die", "New Single", "12", ""], ["2009", "Rihanna", "Rated R", "Hard ft. Young Jeezy", "11", "14", ""], ["2014", "Yo Gotti", "I Am", "I Know f Rich Homie Quan", "New Single", "", ""], ["2008", "Beyoncé", "I Am... Sasha Fierce", "Single Ladies", "1", "1", ""], ["2013", "Bryan J", "Forthcoming Album", "Caught Up", "New Single", "", ""], ["2009", "Jamie Foxx", "Intuition", "Just Like Me ft. T.I.", "49", "8", ""], ["2013", "Ariana Grande", "Forthcoming Album", "Right There f/ Big Sean", "9", "", ""], ["2013", "Jay-Z", "Magna Carta... Holy Grail", "F*uckwithmeyouknowigotit", "New Single", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:was it 2012 or 2013 that ciara released got me good? | 2012 | 128 | Answer: |
Table InputTable: [["Rank", "City", "Passengers", "Ranking", "Airline"], ["3", "Guerrero, Acapulco", "56,069", "", "Aeroméxico Connect, Interjet"], ["2", "Nuevo León, Monterrey", "106,513", "", "Aeroméxico Connect, Interjet"], ["1", "Quintana Roo, Cancún", "132,046", "", "Aeroméxico Connect, Interjet, Volaris"], ["5", "Jalisco, Puerto Vallarta", "43,419", "1", "Interjet"], ["7", "Guerrero, Ixtapa/Zihuatanejo", "35,507", "", "Interjet"], ["8", "Baja California, Tijuana", "14,906", "", "Interjet"], ["6", "Baja California Sur, Los Cabos", "37,526", "1", "Interjet"], ["4", "Jalisco, Guadalajara", "52,584", "", "Aeroméxico Connect, Volaris"], ["10", "Tamaulipas, Tampico", "3,619", "1", "VivaAerobus"], ["9", "Tabasco, Villahermosa", "6,928", "1", "VivaAerobus"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 interjet airline has the highest number of passenders? | Aeroméxico Connect, Interjet, Volaris | 128 | Answer: |
Table InputTable: [["Season", "Conference", "Head Coach", "Total Wins", "Total Losses", "Total Ties", "Conference Wins", "Conference Losses", "Conference Ties", "Conference Standing", "Postseason Result"], ["1992", "Southern", "Charlie Taaffe", "11", "2", "0", "6", "1", "0", "1", "Quarterfinals"], ["Totals:\\n105 Seasons", "2 Conferences", "23 Head Coaches", "Total\\nWins\\n473", "Total\\nLosses\\n536", "Total\\nTies\\n32", "239 Conference Wins\\n55 SIAA\\n184 SoCon", "379 Conference Losses\\n58 SIAA\\n321 SoCon", "13 Conference Ties\\n8 SIAA\\n5 SoCon", "Regular Season\\nChampions\\n2 times", "1–0 Bowl Record\\n1–3 Playoff Record"], ["1930", "Southern Intercollegiate", "Johnny Floyd", "4", "5", "2", "3", "0", "1", "—", "—"], ["1988", "Southern", "Charlie Taaffe", "8", "4", "0", "5", "2", "0", "3", "First Round"], ["1931", "Southern Intercollegiate", "Johnny Floyd", "5", "4", "1", "4", "1", "0", "—", "—"], ["1990", "Southern", "Charlie Taaffe", "7", "5", "0", "4", "3", "0", "3", "First Round"], ["1918", "Southern Intercollegiate", "Harvey O'Brien", "0", "2", "1", "0", "1", "1", "—", "—"], ["1920", "Southern Intercollegiate", "Harvey O'Brien", "2", "6", "0", "1", "5", "0", "—", "—"], ["1921", "Southern Intercollegiate", "Harvey O'Brien", "3", "3", "2", "2", "3", "1", "—", "—"], ["1925", "Southern Intercollegiate", "Carl Prause", "6", "4", "0", "4", "2", "0", "—", "—"], ["1929", "Southern Intercollegiate", "Carl Prause", "5", "4", "1", "4", "0", "1", "—", "—"], ["1905", "Independent", "Sidney Smith", "2", "3", "1", "—", "—", "—", "—", "—"], ["1924", "Southern Intercollegiate", "Carl Prause", "6", "4", "0", "4", "2", "0", "—", "—"], ["1928", "Southern Intercollegiate", "Carl Prause", "6", "3", "1", "3", "3", "0", "—", "—"], ["1916", "Southern Intercollegiate", "Harvey O'Brien", "6", "1", "1", "4", "1", "0", "—", "—"], ["1917", "Southern Intercollegiate", "Harvey O'Brien", "3", "3", "0", "1", "3", "0", "—", "—"], ["1927", "Southern Intercollegiate", "Carl Prause", "3", "6", "1", "2", "3", "1", "—", "—"], ["1923", "Southern Intercollegiate", "Carl Prause", "5", "3", "1", "2", "1", "1", "—", "—"], ["1908", "Southern Intercollegiate", "Ralph Foster", "4", "1", "1", "—", "—", "—", "—", "—"], ["1926", "Southern Intercollegiate", "Carl Prause", "7", "3", "0", "4", "3", "0", "—", "—"], ["1909", "Southern Intercollegiate", "Sam Costen", "4", "3", "2", "0", "1", "1", "—", "—"], ["1922", "Southern Intercollegiate", "Carl Prause", "3", "5", "0", "1", "2", "0", "—", "—"], ["1914", "Southern Intercollegiate", "George C. Rogers", "2", "5", "0", "0", "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:who was the next head coach after sidney smith? | Ralph Foster | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["5", "Canada", "1", "–", "3", "4"], ["1", "Netherlands", "8", "3", "1", "12"], ["7", "Russia", "–", "1", "1", "2"], ["8", "China", "–", "–", "1", "1"], ["2", "Australia", "3", "3", "4", "10"], ["6", "Italy", "–", "2", "1", "3"], ["4", "Hungary", "1", "1", "3", "5"], ["3", "United States", "2", "5", "1", "8"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what nation comes before canada? | Hungary | 128 | Answer: |
Table InputTable: [["Departure", "Going to", "Calling at", "Arrival", "Operator"], ["11.01", "Skegness / Mablethorpe", "Boston, Firsby: Part to Skegness. Part to Willoughby, Sutton-on-Sea, Mablethorpe", "12.08 / 12.20", "GNR"], ["19.22", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "19.55", "GNR"], ["07.00", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "07.32", "GNR"], ["16.19", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "16.51", "GNR"], ["10.02", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "10.33", "GNR"], ["11.34", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "12.07", "GNR"], ["08.17", "Grantham", "Rauceby, Ancaster, Barkston", "08.45", "GNR"], ["14.00", "York", "Lincoln, Gainsborough, Doncaster, Selby", "16.33", "GN&GE"], ["18.51", "Grantham", "Rauceby, Ancaster, Honington, Barkston", "19.28", "GNR"], ["11.34", "Grantham", "Rauceby, Ancaster, Barkston, Honington", "12.05", "GNR"], ["17.00", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "18.27", "GN&GE"], ["12.43", "Lowestoft", "Spalding, March, Shippea Hill, Brandon, Thetford, Attleborough, Wymondham, Norwich, Oulton Broad", "16.10", "GN&GE"], ["13.48", "Grantham", "Rauceby, Ancaster, Honington", "14.21", "GNR"], ["09.50", "Grantham", "Rauceby, Ancaster, Honington", "10.20", "GNR"], ["18.58", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "20.20", "GN&GE"], ["08.20", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "09.00", "GNR"], ["19.46", "Doncaster", "Blankney & Metheringham, Lincoln, Gainsborough", "21.22", "GN&GE"], ["10.48", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "12.12", "GN&GE"], ["08.16", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "09.38", "GN&GE"], ["16.25", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "17.00", "GNR"], ["17.55", "Nottingham Victoria", "", "18.46", "GNR"], ["13.49", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "15.23", "GN&GE"], ["22.04", "Grantham", "", "22.27", "GNR"], ["10.05", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "10.41", "GNR"], ["08.16", "Lincoln", "Ruskington, Digby, Scopwick & Timberland, Blankney & Metheringham, Nocton & Dunston, Potterhanworth, Branston & Heighington", "09.05", "GN&GE"], ["13.48", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "14.24", "GNR"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many trains are going to boston? | 5 | 128 | Answer: |
Table InputTable: [["Common name", "District", "Hebrew", "Arabic", "Population\\n(2009)", "Area\\n(km²)", "Mayor"], ["Migdal HaEmek", "North", "מגדל העמק", "مجدال هعيمق", "23,900", "7.637", "Eliyahu Barda"], ["Safed", "North", "צפת", "صفد", "29,500", "29.248", "Ilan Shohat"], ["Nazareth Illit", "North", "נצרת עילית", "الناصرة العليا", "40,800", "32.521", "Shimon Gapso"], ["Nazareth", "North", "נצרת", "الناصرة", "72,200", "14.123", "Ali Salam"], ["Sakhnin", "North", "סח'נין", "سخنين", "25,700", "9.816", "Mazen Ghnaim"], ["Nahariya", "North", "נהריה", "نهاريا", "51,200", "10.233", "Jacky Sabag"], ["Acre", "North", "עכו", "عكا", "46,300", "13.533", "Shimon Lancry"], ["Beit She'an", "North", "בית שאן", "بيسان", "16,900", "7.330", "Jacky Levi"], ["Afula", "North", "עפולה", "العفولة", "40,500", "26.909", "Avi Elkabetz"], ["Tiberias", "North", "טבריה", "طبريا", "41,300", "10.872", "Zohar Oved"], ["Yokneam", "North", "יקנעם", "يوقنعم", "19,100", "7.390", "Simon Alfasi"], ["Yehud-Monosson", "Center", "יהוד-מונוסון", "يهود مونوسون", "26,500", "5.014", "Yossi Ben-David"], ["Karmiel", "North", "כרמיאל", "كرميئيل", "44,100", "19.188", "Adi Eldar"], ["Netivot", "South", "נתיבות", "نتيفوت", "26,700", "5.626", "Yehiel Zohar"], ["Netanya", "Center", "נתניה", "نتانيا", "183,200", "28.954", "Miriam Feirberg"], ["Ma'alot-Tarshiha", "North", "מעלות-תרשיחא", "معالوت ترشيحا", "20,600", "6.832", "Shlomo Bohbot"], ["Arad", "South", "ערד", "عراد", "23,400", "93.140", "Tali Ploskov"], ["Ashdod", "South", "אשדוד", "أشدود", "206,400", "47.242", "Yehiel Lasri"], ["Kiryat Shmona", "North", "קריית שמונה", "كريات شمونة", "23,100", "14.228", "Nissim Malka"], ["Nesher", "Haifa", "נשר", "نيشر", "23,600", "12.790", "David Amar"], ["Sderot", "South", "שדרות", "سديروت", "23,700", "4.472", "David Buskila"], ["Tamra", "North", "טמרה", "طمرة", "28,700", "29.259", "Abu el-Hija Adel"], ["Hod HaSharon", "Center", "הוד השרון", "هود هشارون", "47,200", "21.585", "Hai Adiv"], ["Shefa-'Amr (Shfar'am)", "North", "שפרעם", "شفا عمرو", "36,200", "19.766", "Nahed Khazem"], ["Lod", "Center", "לוד", "اللد", "69,800", "12.226", "Yair Revivo"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 were in the north district? | 16 | 128 | Answer: |
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