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: [["Round", "Date", "Home/Away", "Opponent team", "Score", "Scorers"], ["32", "May 16, 2009", "Away", "Dinamo Tirana", "2–3", "Ansi Agolli 12', Sabien Lila 40', Ergys Sorra 73'"], ["14", "December 7, 2008", "Away", "KF Partizani Tirana", "2–2", "Jetmir Sefa 2', Migen Memelli 82'"], ["18", "January 31, 2009", "Away", "KS Dinamo Tirana", "2–4", "Migen Memelli 8' 77', Ansi Agolli 58', Daniel Xhafa 88'"], ["28", "April 18, 2009", "Away", "Partizani Tirana", "2–2", "Daniel Xhafa 56' 87'"], ["7", "October 19, 2008", "Home", "KS Dinamo Tirana", "2–1", "Migen Memelli 32', Gjergji Muzaka 51'"], ["3", "September 14, 2008", "Home", "KF Partizani Tirana", "2–1", "Daniel Xhafa 20', Andi Lila 90'"], ["16", "December 21, 2008", "Away", "KS Flamurtari Vlorë", "2–0", ""], ["25", "March 21, 2009", "Home", "Apolonia Fier", "2–0", "Bledar Devolli 32', Devis Mukaj 75'"], ["2", "August 30, 2008", "Away", "KS Teuta Durrës", "0–1", "Migen Memelli 42',"], ["19", "February 5, 2009", "Home", "KS Shkumbini Peqin", "2–0", "Andi Lila 27', Ansi Agolli 70'"], ["26", "April 5, 2009", "Away", "Flamurtari Vlore", "1–2", "Migen Memelli 1' 37'"], ["5", "September 27, 2008", "Home", "KS Flamurtari Vlorë", "3–1", "Migen Memelli 17' 57' 61'"], ["17", "December 27, 2008", "Home", "KS Bylis Ballsh", "6–2", "Pedro Neves (O.G) 2', Migen Memelli 4' 35' 57', Gjergji Muzaka 13', Daniel Xhafa 32'"], ["27", "April 11, 2009", "Home", "KF Elbasani", "3–0", "Daniel Xhafa 51', Devis Mukaj 77', Migen Memelli 86'"], ["11", "November 15, 2008", "Home", "KS Lushnja", "1–0", "Laert Ndoni (O.G) 13'"], ["24", "March 15, 2009", "Away", "KS Bylis Ballsh", "0–0", ""], ["4", "September 20, 2008", "Away", "KS Apolonia Fier", "0–2", "Andi Lila 28', Migen Memelli 32'"], ["10", "November 9, 2008", "Away", "KS Elbasani", "1–0", ""], ["20", "February 15, 2009", "Away", "KS Besa Kavaje", "1–3", "Daniel Xhafa 29', Ansi Agolli 53', Migen Memelli 73'"], ["8", "October 25, 2008", "Away", "KS Shkumbini Peqin", "0–0", ""], ["6", "October 4, 2008", "Away", "KS Bylis Ballsh", "0–0", ""], ["30", "May 2, 2009", "Away", "KS Besa Kavaje", "1–1", "Migen Memelli 20'"], ["22", "March 1, 2009", "Away", "KS Lushnja", "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:in how many games did albanian superliga score at least 2 goals? | 17 | 128 | Answer: |
Table InputTable: [["Date", "Opponents", "Venue", "Result", "Scorers", "Attendance"], ["16 Sep 1950", "Colchester United", "H", "2–0", "Parker 2", "16,021"], ["11 Nov 1950", "Southend United", "A", "0–3", "", "9,882"], ["7 Sep 1950", "Watford", "A", "2–0", "Parker, Moore", "9,451"], ["23 Sep 1950", "Bristol Rovers", "A", "0–1", "", "19,816"], ["19 Aug 1950", "Nottingham Forest", "H", "0–2", "", "16,595"], ["9 Sep 1950", "Swindon Town", "A", "0–2", "", "14,021"], ["28 Oct 1950", "Bournemouth & Boscombe Athletic", "A", "0–2", "", "13,466"], ["18 Apr 1951", "Brighton & Hove Albion", "A", "1–9", "Parker", "12,114"], ["5 May 1951", "Brighton & Hove Albion", "H", "3–0", "Parker, Moore, Birch", "9,274"], ["3 Mar 1951", "Bristol City", "H", "0–1", "", "11,494"], ["14 Apr 1951", "Plymouth Argyle", "H", "2–0", "Parker, Moore", "11,962"], ["10 Mar 1951", "Gillingham", "A", "1–0", "Birch", "9,040"], ["2 Sep 1950", "Aldershot", "H", "7–0", "Roffi 4, Parker 2, M.Haines", "13,696"], ["23 Dec 1950", "Torquay United", "H", "2–1", "Parker, Shergold", "8,369"], ["2 May 1951", "Nottingham Forest", "A", "1–2", "Parker", "21,468"], ["26 Dec 1950", "Walsall", "H", "3–0", "Parker, Moore, Birch", "13,160"], ["30 Apr 1951", "Bournemouth & Boscombe Athletic", "H", "1–0", "Shergold", "5,563"], ["25 Apr 1951", "Norwich City", "H", "1–1", "Moore", "13,862"], ["12 Apr 1951", "Leyton Orient", "A", "3–0", "Parker, Moore, Shergold", "8,270"], ["31 Mar 1951", "Southend United", "H", "6–1", "Moore 2, Shergold 2, Parker, Birch", "9,544"], ["25 Dec 1950", "Walsall", "A", "0–0", "", "7,832"], ["21 Apr 1951", "Ipswich Town", "A", "1–2", "Moore", "10,294"], ["14 Sep 1950", "Watford", "H", "2–2", "Newall, M.Haines", "12,116"], ["28 Apr 1951", "Leyton Orient", "H", "0–0", "", "7,564"], ["26 Aug 1950", "Torquay United", "A", "4–3", "Cowley, Parker, Roffi, Shergold", "10,276"], ["2 Dec 1950", "Ipswich Town", "H", "1–2", "Hayward", "11,496"], ["20 Jan 1951", "Colchester United", "A", "1–1", "Birch", "8,230"], ["21 Oct 1950", "Gillingham", "H", "1–0", "Shergold", "9,828"], ["4 Nov 1950", "Exeter City", "H", "0–3", "", "10,653"], ["26 Mar 1951", "Norwich City", "A", "1–2", "Birch", "35,267"], ["13 Jan 1951", "Swindon Town", "H", "2–1", "Shergold, Birch", "12,485"], ["30 Sep 1950", "Crystal Palace", "H", "2–4", "Cowley, Moore", "10,114"], ["3 Feb 1951", "Bristol Rovers", "H", "2–1", "Birch 2", "11,802"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did they play before they won a game? | 2 games | 128 | Answer: |
Table InputTable: [["Goal", "Date", "Venue", "Opponent", "Score", "Result", "Competition"], ["6", "2012-2-29", "Tsirion Stadium, Limassol, Cyprus", "Canada", "1-1", "1-3", "Friendly match"], ["7", "2012-2-29", "Tsirion Stadium, Limassol, Cyprus", "Canada", "1-2", "1-3", "Friendly match"], ["1", "2008-5-28", "Sheriff Stadium, Tiraspol, Moldova", "Moldova", "0-1", "2–2", "Friendly match"], ["3", "2011-6-4", "Petrovsky Stadium, Saint Petersburg, Russia", "Russia", "0-1", "3–1", "Euro 2012 Q"], ["2", "2010-10-12", "Hanrapetakan Stadium, Yerevan, Armenia", "Andorra", "4–0", "4–0", "Euro 2012 Q"], ["5", "2011-10-7", "Hanrapetakan Stadium, Yerevan, Armenia", "Macedonia", "1-0", "4-1", "Euro 2012 Q"], ["4", "2011-9-2", "Estadi Comunal d'Aixovall, Andorra la Vella, Andorra", "Andorra", "0-1", "0-3", "Euro 2012 Q"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what international stadium did marcos pizzelli score consecutive goals at? | Tsirion Stadium | 128 | Answer: |
Table InputTable: [["Conference", "# of Bids", "Record", "Win %", "Round\\nof 32", "Sweet\\nSixteen", "Elite\\nEight", "Final\\nFour", "Championship\\nGame"], ["Southeastern", "6", "10–6", ".625", "5", "3", "1", "1", "–"], ["Big Ten", "5", "9–5", ".643", "4", "2", "2", "1", "–"], ["Western Athletic", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["West Coast", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Big East", "2", "5–2", ".714", "2", "2", "1", "–", "–"], ["Mid-Continent", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Great Midwest", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Big Eight", "4", "3–4", ".429", "2", "1", "–", "–", "–"], ["Atlantic Coast", "3", "9–2", ".818", "3", "2", "1", "1", "1"], ["Missouri Valley", "2", "2–2", ".500", "2", "–", "–", "–", "–"], ["Sun Belt", "2", "6–2", ".750", "2", "1", "1", "1", "1"], ["Big West", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Southwest", "4", "5–4", ".556", "3", "2", "–", "–", "–"], ["Atlantic 10", "3", "1–3", ".250", "1", "–", "–", "–", "–"], ["Colonial", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["Big Sky", "2", "1–2", ".333", "1", "–", "–", "–", "–"], ["Pacific-10", "5", "8–5", ".615", "4", "2", "2", "–", "–"], ["Metro", "2", "2–2", ".500", "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 were the total number of times the southeastern conference went to the sweet sixteen? | 3 | 128 | Answer: |
Table InputTable: [["School Name", "Low grade", "High grade", "Students (K-12)", "FTE Teachers", "Student/teacher ratio"], ["St Thomas Aquinas Elementary School", "K", "8", "403", "25", "16.12"], ["Sheridan Road Christian School", "K", "12", "42", "5.9", "7.12"], ["St Helen Elementary School", "K", "8", "182", "10.9", "16.7"], ["Nouvel Catholic Central High School", "9", "12", "505", "37", "13.65"], ["St Stephen Elementary School", "PK", "8", "364", "23.1", "15.76"], ["Grace Christian School", "PK", "12", "117", "13", "9"], ["Tri-City Seventh-Day Adventist School", "1", "8", "18", "2.1", "8.57"], ["Valley Lutheran High School", "9", "12", "344", "21", "16.38"], ["St Pauls Lutheran School", "PK", "8", "155", "9.6", "16.15"], ["Bethany Lutheran School", "PK", "8", "28", "3.6", "7.78"], ["St John's Evangelical Lutheran School", "K", "8", "32", "3", "10.67"], ["Bethlehem Lutheran School", "PK", "8", "182", "10", "18.2"], ["Holy Cross Lutheran School", "PK", "8", "135", "7.9", "17.09"], ["Community Baptist Christian School", "PK", "12", "120", "9.8", "12.24"], ["Immanuel Lutheran School", "PK", "8", "82", "5.6", "14.64"], ["Christ Lutheran School", "K", "8", "12", "2", "6"], ["Peace Lutheran School", "PK", "8", "229", "", ""], ["Good Shepherd Early Childhood", "PK", "K", "20", "1", "20"], ["Michigan Lutheran Seminary", "9", "12", "313", "31", "10.1"], ["Notes", "", "", "", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:does st.thomas aquinas elementary have more or less grades than sheridan road elementary school? | Less | 128 | Answer: |
Table InputTable: [["Rank", "Athlete", "Nationality", "2.15", "2.20", "2.24", "2.27", "Result", "Notes"], ["9.", "Ramsay Carelse", "South Africa", "xo", "xo", "o", "xxx", "2.24", ""], ["13.", "Tomáš Janku", "Czech Republic", "o", "o", "xxo", "xxx", "2.24", ""], ["1.", "Yaroslav Rybakov", "Russia", "o", "o", "o", "o", "2.27", "q"], ["15.", "Svatoslav Ton", "Czech Republic", "o", "xo", "xxx", "", "2.20", ""], ["13.", "Mustapha Raifak", "France", "o", "o", "xxo", "xxx", "2.24", ""], ["1.", "Linus Thörnblad", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["10.", "Nicola Ciotti", "Italy", "o", "o", "xo", "xxx", "2.24", ""], ["16.", "Roman Fricke", "Germany", "o", "xxx", "", "2.15", "", ""], ["10.", "Wojciech Theiner", "Poland", "o", "o", "xo", "xxx", "2.24", ""], ["8.", "Robert Wolski", "Poland", "xo", "o", "o", "xxx", "2.24", "q"], ["1.", "Stefan Holm", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["1.", "Andriy Sokolovskyy", "Ukraine", "o", "o", "o", "o", "2.27", "q"], ["7.", "Giulio Ciotti", "Italy", "o", "o", "o", "xxx", "2.24", "q"], ["1.", "Víctor Moya", "Cuba", "o", "o", "o", "o", "2.27", "q, PB"], ["16.", "Adam Shunk", "United States", "o", "xxx", "", "2.15", "", ""], ["1.", "Andrey Tereshin", "Russia", "o", "o", "o", "o", "2.27", "q"], ["10.", "Tora Harris", "United States", "o", "o", "xo", "xxx", "2.24", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the only athlete from south africa? | Ramsay Carelse | 128 | Answer: |
Table InputTable: [["Single / EP", "Tracks", "Label", "Year", "Album"], ["Hot & Cold", "Overdose", "Burn The Fire", "2010", "—"], ["Los Angeles", "Los Angeles\\nLos Angeles feat. Whiskey Pete (Clean Mix)\\nLos Angeles feat. Whiskey Pete (Dirty Mix)", "Burn The Fire", "2010", "The Agenda"], ["Your Love Is Electric", "Your Love Is Electric", "Burn The Fire", "2009", "—"], ["2012 – Remix Contest EP", "2012 (Remastered)", "Burn The Fire", "2012", "The Agenda"], ["Doin' It Right", "Doin' It Right", "Burn The Fire", "2009", "—"], ["Fresh Attire Vol. 3", "Crush Groovin'", "Wearhouse Music", "2009", "—"], ["Rave To The Grave", "Raver Booty\\nShuffle", "Burn The Fire", "2010", "—"], ["Still Smoking", "Nasty & Gaspar Still Smoking", "Burn The Fire", "2010", "—"], ["Louder Than Bombs", "Louder Than Bombs", "Burn The Fire", "2012", "The Agenda"], ["Drop Bears", "Drop Bears", "Burn The Fire", "2013", "—"], ["Ghetto Ass Bitches", "Ghetto Ass Bitches", "Burn The Fire", "2010", "—"], ["Hyped", "Hyped", "Vicious", "2014", "—"], ["Die Famous", "Die Famous", "Burn The Fire", "2011", "—"], ["Breakdown", "Breakdown", "Burn The Fire", "2009", "—"], ["Dutchie", "Dutchie", "Burn The Fire", "2010", "—"], ["Onslaught", "Onslaught", "Burn The Fire", "2012", "The Agenda"], ["Redroid", "Redroid", "Temple Music Group", "2011", "—"], ["Deception", "Deception", "Burn The Fire", "2012", "The Agenda"], ["Those Who From Heaven To Earth Came", "The Lizard King\\nAnnunaki", "Burn The Fire", "2010", "—"], ["Ancient Psychic Tandem War Elephant", "Ancient Psychic Tandem War Elephant", "Burn The Fire", "2011", "—"], ["Left To Right", "Left To Right", "Destination?", "2009", "—"], ["The Thirteenth Skull", "The Thirteenth Skull", "Burn The Fire", "2010", "—"], ["The Flying Cat", "The Flying Cat", "Burn The Fire", "2010", "—"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which is the newest cold blank single currently available? | Hyped | 128 | Answer: |
Table InputTable: [["#", "Player", "Goals", "Caps", "Career"], ["3", "Eric Wynalda", "34", "106", "1990–2000"], ["9T", "DaMarcus Beasley", "17", "114", "2001–present"], ["8", "Eddie Johnson", "19", "62", "2004–present"], ["1", "Landon Donovan", "57", "155", "2000–present"], ["2", "Clint Dempsey", "36", "103", "2004–present"], ["6T", "Bruce Murray", "21", "86", "1985–1993"], ["5", "Joe-Max Moore", "24", "100", "1992–2002"], ["9T", "Earnie Stewart", "17", "101", "1990–2004"], ["6T", "Jozy Altidore", "21", "67", "2007–present"], ["4", "Brian McBride", "30", "95", "1993–2006"]] | 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:does eric wynalda have more or less caps than damarcus beasley? | less | 128 | Answer: |
Table InputTable: [["Location", "Reactor type", "Status", "Net\\nCapacity\\n(MWe)", "Gross\\nCapacity\\n(MWe)"], ["Chernobyl-4", "RBMK-1000", "destroyed in the 1986 accident", "925", "1,000"], ["Chernobyl-6", "RBMK-1000", "construction cancelled in 1988", "950", "1,000"], ["Chernobyl-1", "RBMK-1000", "shut down in 1996", "740", "800"], ["Chernobyl-5", "RBMK-1000", "construction cancelled in 1988", "950", "1,000"], ["Chernobyl-2", "RBMK-1000", "shut down in 1991", "925", "1,000"], ["Chernobyl-3", "RBMK-1000", "shut down in 2000", "925", "1,000"], ["Kursk-6", "RBMK-1000", "construction cancelled in 1993", "925", "1,000"], ["Kostroma-1", "RBMK-1500", "construction cancelled in 1980s", "1,380", "1,500"], ["Kostroma-2", "RBMK-1500", "construction cancelled in 1980s", "1,380", "1,500"], ["Ignalina-3", "RBMK-1500", "construction cancelled in 1988", "1,380", "1,500"], ["Smolensk-4", "RBMK-1000", "construction cancelled in 1993", "925", "1,000"], ["Ignalina-1", "RBMK-1500", "shut down in 2004", "1,185", "1,300"], ["Ignalina-2", "RBMK-1500", "shut down in 2009", "1,185", "1,300"], ["Ignalina-4", "RBMK-1500", "plan cancelled in 1988", "1,380", "1,500"], ["Leningrad-1", "RBMK-1000", "operational", "925", "1,000"], ["Kursk-5", "MKER-1000", "construction begin was 1985, since then shelved", "925", "1,000"], ["Kursk-2", "RBMK-1000", "operational until 2024", "925", "1,000"], ["Kursk-3", "RBMK-1000", "operational until March 2014", "925", "1,000"], ["Kursk-1", "RBMK-1000", "operational until 2021", "925", "1,000"], ["Leningrad-3", "RBMK-1000", "operational until June 2025", "925", "1,000"], ["Smolensk-1", "RBMK-1000", "operational until December 2022", "925", "1,000"], ["Leningrad-4", "RBMK-1000", "operational until August 2026", "925", "1,000"], ["Leningrad-2", "RBMK-1000", "operational until 2021", "925", "1,000"], ["Kursk-4", "RBMK-1000", "operational until February 2016", "925", "1,000"], ["Smolensk-3", "RBMK-1000", "operational until July 2023", "925", "1,000"], ["Smolensk-2", "RBMK-1000", "operational until July 2015", "925", "1,000"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which reactor is the only one to have been destroyed in an accident? | Chernobyl-4 | 128 | Answer: |
Table InputTable: [["DATE", "OPPONENT", "SCORE", "TOP SCORER (Total points)", "VENUE"], ["September 23 Governor's Cup", "TANDUAY", "108-93", "", "PHILSPORTS ARENA"], ["October 24", "BRGY.GINEBRA", "93-72", "", "PHILSPORTS ARENA"], ["June 10 Commissioner's Cup", "MOBILINE", "97-92", "Tony Lang (29)", "ARANETA COLISEUM"], ["June 15", "BRGY.GINEBRA", "111-98", "", "PHILSPORTS ARENA"], ["March 9", "SHELL", "65-58", "", "PHILSPORTS ARENA"], ["July 13", "TANDUAY", "104-98", "", "PHILSPORTS ARENA"], ["June 24", "SHELL", "94-82", "", "ARANETA COLISEUM"], ["February 16", "ALASKA", "73-72", "Davonn Harp (20)", "PHILSPORTS ARENA"], ["April 4", "STA.LUCIA", "87-84", "", "PHILSPORTS ARENA"], ["November 7", "SAN MIGUEL", "86-81", "", "ARANETA COLISEUM"], ["February 7 All-Filipino Cup", "SHELL", "76-60", "", "PHILSPORTS ARENA"], ["February 28", "SAN MIGUEL", "78-76", "Lowell Briones (21)", "PHILSPORTS ARENA"], ["July 8", "STA.LUCIA", "95-88", "", "ARANETA COLISEUM"], ["February 11", "MOBILINE", "80-68", "", "ARANETA COLISEUM"], ["July 1", "POP COLA", "95-79", "", "ARANETA COLISEUM"], ["October 14", "SHELL", "68-62", "", "YNARES CENTER"], ["October 19", "STA.LUCIA", "101-94", "", "CUNETA ASTRODOME"], ["March 3", "BRGY.GINEBRA", "79-72", "", "ILOILO CITY"], ["September 29", "TALK 'N TEXT", "99-85", "", "DUMAGUETE CITY"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 were played? | 19 | 128 | Answer: |
Table InputTable: [["Date", "Location", "Opponent", "Result", "Competition"], ["July 8, 2013", "Harrison, United States", "Honduras", "0–2", "GC"], ["July 15, 2013", "Houston, United States", "El Salvador", "0-1", "GC"], ["July 12, 2013", "Miami Gardens, United States", "Trinidad and Tobago", "2-0", "GC"], ["March 20, 2013", "Muscat, Oman", "Oman", "0–3", "F"], ["March 5, 2014", "Mitrovica, Kosovo", "Kosovo", "0–0", "F"], ["January 19, 2013", "Concepción, Chile", "Chile", "0–3", "F"], ["June 11, 2013", "Rio de Janeiro, Brazil", "Italy", "2–2", "F"], ["September 6, 2013", "Incheon, South Korea", "South Korea", "1-4", "F"], ["June 8, 2013", "Miami, United States", "Spain", "1–2", "F"], ["March 24, 2013", "Santo Domingo, Dominican Republic", "Dominican Republic", "1–3", "F"], ["February 6, 2013", "Santa Cruz de la Sierra, Bolivia", "Bolivia", "1–2", "F"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who did this team play in the last game of this season? | Kosovo | 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"], ["2006", "6", "Pakistan win", "3 - 1", "Mohammad Saqlain", "Asif Bajwa", "Ignace Tirkey", "Rajinder Singh Jr."], ["1998", "8", "Pakistan win", "4 - 3", "Tahir Zaman", "Islahuddin Siddique", "Dhanraj Pillay", "V Bhaskaran"], ["1978", "4", "Pakistan win", "3 - 1", "Islahuddin Siddique", "Sayad A. Hussain", "V. J. Philips", "R. S. Gentle"], ["1988", "6", "Draw", "2 - 2", "Nasir Ali", "Manzoor-ul-Hasan", "M. M. Somaya", "M. P. Ganesh"], ["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"], ["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 is the total number of points india has scored throughout the rivalry? | 16 | 128 | Answer: |
Table InputTable: [["Rank", "Diver", "Nationality", "Preliminary\\nPoints", "Preliminary\\nRank", "Final\\nPoints", "Final\\nRank"], ["7", "Sharleen Stratton", "Australia", "282.45", "3", "281.65", "7"], ["11", "Brittany Broben", "Australia", "257.10", "10", "267.20", "11"], ["27", "Marion Farissier", "France", "221.65", "27", "", ""], ["25", "Hannah Starling", "Great Britain", "226.40", "25", "", ""], ["30", "Alicia Blagg", "Great Britain", "212.50", "30", "", ""], ["15", "Sophie Somloi", "Austria", "249.45", "15", "", ""], ["28", "Julia Loennegren", "Sweden", "221.05", "28", "", ""], ["12", "Anastasia Pozdniakova", "Russia", "260.00", "8", "251.70", "12"], ["14", "Jennifer Abel", "Canada", "250.95", "14", "", ""], ["21", "Jennifer Benitez", "Spain", "232.50", "21", "", ""], ["26", "Choi Sut Ian", "Macau", "224.50", "26", "", ""], ["8", "Anna Lindberg", "Sweden", "276.05", "5", "279.55", "8"], ["29", "Yuka Mabuchi", "Japan", "219.50", "29", "", ""], ["35", "Sari Ambarwati", "Indonesia", "200.05", "35", "", ""], ["4", "Maria Marconi", "Italy", "264.25", "6", "290.15", "4"], ["24", "Fanny Bouvet", "France", "227.10", "24", "", ""], ["18", "Inge Jansen", "Netherlands", "241.95", "18", "", ""], ["22", "Arantxa Chavez", "Mexico", "232.35", "22", "", ""], ["5", "Nadezhda Bazhina", "Russia", "262.75", "7", "286.20", "5"], ["6", "Abby Johnston", "United States", "282.40", "4", "282.85", "6"], ["16", "Uschi Freitag", "Germany", "247.70", "16", "", ""], ["9", "Kelci Bryant", "United States", "257.00", "11", "274.25", "9"], ["17", "Sharon Chan", "Hong Kong", "245.10", "17", "", ""], ["20", "Sayaka Shibusawa", "Japan", "240.80", "20", "", ""], ["", "Tania Cagnotto", "Italy", "253.15", "12", "295.45", "3"], ["36", "Lei Sio I", "Macau", "192.00", "36", "", ""], ["34", "Maria Florencia Betancourt", "Venezuela", "204.90", "34", "", ""], ["33", "Tina Punzel", "Germany", "206.05", "33", "", ""], ["23", "Vianey Hernandez", "Mexico", "227.85", "23", "", ""], ["13", "Hanna Pysmenska", "Ukraine", "251.40", "13", "", ""], ["19", "Jun Hoong Cheong", "Malaysia", "241.95", "18", "", ""], ["39", "Carolina Murillo", "Colombia", "181.85", "39", "", ""], ["37", "Leyre Eizaguirre", "Spain", "189.95", "37", "", ""], ["10", "Olena Fedorova", "Ukraine", "258.30", "9", "274.15", "10"], ["", "Shi Tingmao", "China", "294.65", "2", "318.65", "1"], ["32", "Diana Pineda", "Colombia", "209.60", "32", "", ""], ["38", "Huang En-Tien", "Chinese Taipei", "187.25", "38", "", ""], ["40", "Hsu Shi-Han", "Chinese Taipei", "146.15", "40", "", ""], ["", "Wang Han", "China", "306.60", "1", "310.20", "2"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many finalists did australia have? | 2 | 128 | Answer: |
Table InputTable: [["Pos", "No.", "Driver", "Team", "Engine", "Laps", "Time/Retired", "Grid", "Laps Led", "Points"], ["26", "27", "James Hinchcliffe", "Andretti Autosport", "Chevrolet", "35", "Mechanical", "10", "0", "10"], ["1", "2", "Ryan Briscoe", "Team Penske", "Chevrolet", "85", "2:07:02.8248", "2", "27", "50"], ["13", "9", "Scott Dixon", "Chip Ganassi Racing", "Honda", "84", "+ 1 lap", "5", "0", "17"], ["18", "28", "Ryan Hunter-Reay", "Andretti Autosport", "Chevrolet", "84", "+ 1 lap", "7", "1", "12"], ["21", "83", "Charlie Kimball", "Chip Ganassi Racing", "Honda", "82", "+ 3 laps", "21", "0", "12"], ["23", "67", "Josef Newgarden (R)", "Sarah Fisher Hartman Racing", "Honda", "62", "Contact", "22", "0", "12"], ["11", "18", "Justin Wilson", "Dale Coyne Racing", "Honda", "84", "+ 1 lap", "20", "0", "19"], ["5", "38", "Graham Rahal", "Chip Ganassi Racing", "Honda", "85", "+ 9.4667", "13", "0", "30"], ["7", "77", "Simon Pagenaud (R)", "Schmidt Hamilton Motorsports", "Honda", "85", "+ 12.3087", "9", "0", "26"], ["20", "20", "Ed Carpenter", "Ed Carpenter Racing", "Chevrolet", "84", "+ 1 lap", "25", "0", "12"], ["8", "4", "J.R. Hildebrand", "Panther Racing", "Chevrolet", "85", "+ 22.8121", "15", "0", "24"], ["12", "19", "James Jakes", "Dale Coyne Racing", "Honda", "84", "+ 1 lap", "24", "0", "18"], ["15", "17", "Sebastián Saavedra", "Andretti Autosport", "Chevrolet", "84", "+ 1 lap", "23", "0", "15"], ["14", "14", "Mike Conway", "A.J. Foyt Enterprises", "Honda", "84", "+ 1 lap", "14", "0", "16"], ["3", "10", "Dario Franchitti", "Chip Ganassi Racing", "Honda", "85", "+ 1.0497", "6", "0", "35"], ["10", "11", "Tony Kanaan", "KV Racing Technology", "Chevrolet", "84", "+ 1 lap", "16", "0", "20"], ["24", "6", "Katherine Legge (R)", "Dragon Racing", "Chevrolet", "48", "Mechanical", "19", "0", "12"], ["25", "26", "Marco Andretti", "Andretti Autosport", "Chevrolet", "46", "Mechanical", "12", "0", "10"], ["4", "8", "Rubens Barrichello", "KV Racing Technology", "Chevrolet", "85", "+ 8.8529", "11", "0", "32"], ["16", "5", "E.J. Viso", "KV Racing Technology", "Chevrolet", "84", "+ 1 lap", "17", "0", "14"], ["22", "7", "Sebastien Bourdais", "Dragon Racing", "Chevrolet", "63", "Contact", "3", "0", "12"], ["2", "12", "Will Power", "Team Penske", "Chevrolet", "85", "+ 0.4408", "1", "57", "43"], ["6", "3", "Hélio Castroneves", "Team Penske", "Chevrolet", "85", "+ 11.2575", "4", "0", "28"], ["19", "22", "Oriol Servià", "Panther/Dreyer & Reinbold Racing", "Chevrolet", "84", "+ 1 lap", "18", "0", "12"], ["9", "98", "Alex Tagliani", "Team Barracuda – BHA", "Honda", "85", "+ 39.6868", "8", "0", "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 was the top position american driver? | Graham Rahal | 128 | Answer: |
Table InputTable: [["Rank", "City", "Passengers", "Ranking", "Airline"], ["6", "Baja California Sur, Los Cabos", "37,526", "1", "Interjet"], ["2", "Nuevo León, Monterrey", "106,513", "", "Aeroméxico Connect, Interjet"], ["3", "Guerrero, Acapulco", "56,069", "", "Aeroméxico Connect, Interjet"], ["8", "Baja California, Tijuana", "14,906", "", "Interjet"], ["7", "Guerrero, Ixtapa/Zihuatanejo", "35,507", "", "Interjet"], ["1", "Quintana Roo, Cancún", "132,046", "", "Aeroméxico Connect, Interjet, Volaris"], ["5", "Jalisco, Puerto Vallarta", "43,419", "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:what were the number of routes that had at least 50,000 passengers? | 4 | 128 | Answer: |
Table InputTable: [["Date", "Team", "Competition", "Round", "Leg", "Opponent", "Location", "Score"], ["August 16", "Standard Liège", "UEFA Cup", "Qual. Round 2", "Leg 1, Away", "Käerjeng", "Stade Josy Barthel, Luxembourg", "3-0"], ["August 30", "Standard Liège", "UEFA Cup", "Qual. Round 2", "Leg 2, Home", "Käerjeng", "Stade Maurice Dufrasne, Liège", "1-0"], ["October 4", "Standard Liège", "UEFA Cup", "Round 1", "Leg 2, Home", "Zenit St. Petersburg", "Stade Maurice Dufrasne, Liège", "1-1"], ["August 29", "Anderlecht", "Champions League", "Qual. Round 3", "Leg 2, Home", "Fenerbahçe", "Constant Vanden Stock Stadium, Anderlecht", "0-2"], ["February 13", "Anderlecht", "UEFA Cup", "Round of 32", "Leg 1, Home", "Bordeaux", "Constant Vanden Stock Stadium, Anderlecht", "2-1"], ["November 8", "Anderlecht", "UEFA Cup", "Group Stage", "Match 2, Away", "Aalborg", "Energi Nord Arena, Aalborg", "1-1"], ["December 6", "Anderlecht", "UEFA Cup", "Group Stage", "Match 3, Home", "Tottenham Hotspur", "Constant Vanden Stock Stadium, Anderlecht", "1-1"], ["August 15", "Anderlecht", "Champions League", "Qual. Round 3", "Leg 1, Away", "Fenerbahçe", "Şükrü Saracoğlu Stadium, Istanbul", "0-1"], ["July 7", "Gent", "Intertoto Cup", "Round 2", "Leg 1, Home", "Cliftonville", "Jules Ottenstadion, Ghent", "2-0"], ["October 4", "Club Brugge", "UEFA Cup", "Round 1", "Leg 2, Home", "Brann", "Jan Breydel Stadium, Bruges", "1-2"], ["September 20", "Standard Liège", "UEFA Cup", "Round 1", "Leg 1, Away", "Zenit St. Petersburg", "Petrovsky Stadium, Saint Petersburg", "0-3"], ["October 25", "Anderlecht", "UEFA Cup", "Group Stage", "Match 1, Home", "Hapoel Tel Aviv", "Constant Vanden Stock Stadium, Anderlecht", "2-0"], ["August 8", "Genk", "Champions League", "Qual. Round 2", "Leg 2, Away", "Sarajevo", "Asim Ferhatović Hase Stadium, Sarajevo", "1-0"], ["September 20", "Club Brugge", "UEFA Cup", "Round 1", "Leg 1, Away", "Brann", "Brann Stadion, Bergen", "1-0"], ["July 31", "Genk", "Champions League", "Qual. Round 2", "Leg 1, Home", "Sarajevo", "Cristal Arena, Genk", "1-2"], ["March 6", "Anderlecht", "UEFA Cup", "Round of 16", "Leg 1, Home", "Bayern Munich", "Constant Vanden Stock Stadium, Anderlecht", "0-5"], ["February 21", "Anderlecht", "UEFA Cup", "Round of 32", "Leg 2, Away", "Bordeaux", "Stade Chaban-Delmas, Bordeaux", "1-1"], ["July 21", "Gent", "Intertoto Cup", "Round 3", "Leg 1, Home", "Aalborg", "Jules Ottenstadion, Ghent", "1-1"], ["December 19", "Anderlecht", "UEFA Cup", "Group Stage", "Match 4, Away", "Getafe", "Coliseum Alfonso Pérez, Getafe", "1-2"], ["September 20", "Anderlecht", "UEFA Cup", "Round 1", "Leg 1, Home", "Rapid Wien", "Constant Vanden Stock Stadium, Anderlecht", "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:how many european club games did belgian football teams play in the 2007-08 season? | 24 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "China", "13", "9", "13", "35"], ["2", "Japan", "7", "10", "7", "24"], ["6", "South Korea", "0", "0", "2", "2"], ["5", "North Korea", "1", "0", "1", "2"], ["3", "Uzbekistan", "1", "2", "3", "6"], ["Total", "Total", "24", "23", "26", "73"], ["4", "Kazakhstan", "2", "2", "0", "4"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many total medals did china receive? | 35 | 128 | Answer: |
Table InputTable: [["Association", "Joining year", "Men's team", "Women's team", "League"], ["Guam", "2002", "Guam", "Guam", "Guam League"], ["Macau", "2002", "Macau", "Macau", "Campeonato da 1ª Divisão do Futebol"], ["Northern Mariana Islands", "2008 1", "Northern Mariana Islands", "Northern Mariana Islands", "Northern Mariana Championship"], ["Japan", "2002", "Japan", "Japan", "J. League"], ["China PR", "2002", "China", "China", "Chinese Super League"], ["Korea Republic", "2002", "Korea Republic", "Korea Republic", "K-League"], ["Mongolia", "2002", "Mongolia", "Mongolia", "Mongolia Premier League"], ["Korea DPR", "2002", "Korea DPR", "Korea DPR", "DPR Korea League"], ["Hong Kong", "2002", "Hong Kong", "Hong Kong", "Hong Kong First Division League"], ["Chinese Taipei", "2002", "Chinese Taipei", "Chinese Taipei", "Intercity Football League"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 association entered last? | Northern Mariana Islands | 128 | Answer: |
Table InputTable: [["Rank", "Island", "Area\\n(km²)", "Area\\n(sq mi)", "Country/Countries/Region"], ["263", "Kasos", "66", "26", "Greece"], ["247", "Tiree", "78", "30", "United Kingdom"], ["265", "Alonissos", "64", "25", "Greece"], ["273", "Graciosa Island", "62", "24", "Portugal"], ["213", "Santa Maria Island", "97", "37", "Portugal"], ["217", "Borðoy", "95", "37", "Faroe Islands, an autonomous region of Denmark"], ["226", "Öja (island)", "90", "35", "Finland"], ["219", "Skopelos", "95", "37", "Greece"], ["260", "Finnøya (in Nordland)", "68", "26", "Norway"], ["258", "Ålön (in Pargas/Parainen)", "70", "27", "Finland"], ["221", "Gräsö", "93", "36", "Sweden"], ["251", "Santorini", "76", "29", "Greece"], ["297", "Hydra", "50", "19", "Greece"], ["302", "Wahlbergøya", "50", "19", "Svalbard, Norway"], ["248", "Uløya", "78", "30", "Norway"], ["295", "San Pietro Island", "51", "20", "Italy"], ["291", "Leros", "53", "20", "Greece"], ["218", "Salamis", "95", "37", "Greece"], ["243", "Ytre Vikna (outer island of Vikna archipelago)", "83", "32", "Norway"], ["275", "Bolshoy Berezovy (in Beryozovye Islands, Gulf of Finland)", "60", "23", "Russia"], ["210", "Kythnos", "99", "38", "Greece"], ["214", "Astypalaia", "97", "38", "Greece"], ["238", "Nordkvaløya", "84", "33", "Norway"], ["259", "Engeløya", "68", "26", "Norway"], ["236", "Kågen", "86", "33", "Norway"], ["255", "Sifnos", "73", "29", "Greece"], ["254", "Serifos", "73", "29", "Greece"], ["290", "Dyrøya", "53", "20", "Norway"], ["223", "Vormsi", "92", "36", "Estonia"], ["239", "Syros", "84", "33", "Greece"], ["271", "Tilos", "63", "24", "Greece"], ["250", "Otrøy (in Møre og Romsdal)", "76", "29", "Norway"], ["269", "Ingarö", "63", "24", "Sweden"], ["235", "Mykonos", "86", "34", "Greece"], ["252", "Lošinj", "75", "29", "Croatia"], ["301", "Storøya", "50", "19", "Svalbard, Norway"], ["274", "Ljusterö", "62", "24", "Sweden"], ["293", "Vessölandet (in Borgå/Porvoo)", "52", "20", "Finland"], ["296", "Asinara", "51", "20", "Italy"], ["300", "Huftarøy", "50", "19", "Norway"], ["242", "Pantelleria", "83", "32", "Italy"], ["283", "Kivimaa (in Gustavs/Kustavi)", "57", "22", "Finland"], ["298", "Sanday, Orkney", "50", "19", "United Kingdom"], ["294", "Mörkön", "52", "20", "Sweden"], ["229", "Tustna", "89", "34", "Norway"], ["288", "Inner-Vikna (inner island of Vikna archipelago)", "55", "21", "Norway"], ["216", "Ithaki", "96", "37", "Greece"], ["286", "Île de Noirmoutier", "55.5", "21.5", "France"], ["212", "Askøy", "99", "38", "Norway"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 island has the most area, tiree or kasos? | Tiree | 128 | Answer: |
Table InputTable: [["No.", "Date/time", "Aircraft", "Foe", "Result", "Location", "Notes"], ["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"], ["5", "11 May 1917 @ 1950 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Set afire in midair; destroyed", "Douai, France", ""], ["6", "23 May 1917 @ 1800 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Douai, France", ""], ["7", "24 July 1917 @ 0635 hours", "Sopwith Triplane s/n N5462", "German two-seater aircraft", "Driven down out of control", "Leffinghe", ""], ["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"], ["2", "24 April 1917 @ 0840 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Sailly, France", ""], ["4", "11 May 1917 @ 1950 hours", "Sopwith Triplane s/n N5460", "Albatros D.III", "Driven down out of control", "Douai, France", ""], ["3", "2 May 1917 @ 0945 hours", "Sopwith Triplane s/n N5460", "German two-seater aircraft", "Driven down out of control", "Douai, France", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 aircraft was used before the 7th aerial victory? | Sopwith Triplane s/n N5460 | 128 | Answer: |
Table InputTable: [["Week", "Date", "Opponent", "Result", "Record", "TV Time", "Attendance"], ["1", "September 9, 2001", "at Philadelphia Eagles", "W 20–17 (OT)", "1–0", "FOX 3:15pm", "66,243"], ["13", "December 9, 2001", "San Francisco 49ers", "W 27–14", "10–2", "FOX 12:00pm", "66,218"], ["2", "September 23, 2001", "at San Francisco 49ers", "W 30–26", "2–0", "FOX 3:15pm", "67,536"], ["3", "September 30, 2001", "Miami Dolphins", "W 42–10", "3–0", "CBS 12:00pm", "66,046"], ["16", "December 30, 2001", "Indianapolis Colts", "W 42–17", "13–2", "CBS 12:00pm", "66,084"], ["9", "November 11, 2001", "Carolina Panthers", "W 48–14", "7–1", "FOX 12:00pm", "66,069"], ["7", "October 28, 2001", "New Orleans Saints", "L 34–31", "6–1", "FOX 12:00pm", "66,189"], ["4", "October 8, 2001", "at Detroit Lions", "W 35–0", "4–0", "ABC 8:00pm", "77,765"], ["15", "December 23, 2001", "at Carolina Panthers", "W 38–32", "12–2", "FOX 12:00pm", "72,438"], ["6", "October 21, 2001", "at New York Jets", "W 34–14", "6–0", "FOX 12:00pm", "78,766"], ["12", "December 2, 2001", "at Atlanta Falcons", "W 35–6", "9–2", "FOX 3:15pm", "60,787"], ["11", "November 26, 2001", "Tampa Bay Buccaneers", "L 24–17", "8–2", "ABC 8:00pm", "66,198"], ["5", "October 14, 2001", "New York Giants", "W 15–14", "5–0", "FOX 12:00pm", "65,992"], ["17", "January 6, 2002", "Atlanta Falcons", "W 31–13", "14–2", "FOX 3:15pm", "66,033"], ["14", "December 17, 2001", "at New Orleans Saints", "W 34–21", "11–2", "ABC 8:00pm", "70,332"], ["10", "November 18, 2001", "at New England Patriots", "W 24–17", "8–1", "ESPN 7:30pm", "60,292"], ["8", "Bye", "Bye", "Bye", "Bye", "Bye", "Bye"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the first team to defeat the rams in the 2001 season? | New Orleans Saints | 128 | Answer: |
Table InputTable: [["Tablet", "Genealogy", "Narrative", "Colophon"], ["6", "Shem to Terah 11:10 - 26", "no narrative", "\"This is the account of Terah.\" 11:27"], ["11", "Descendants of Esau 36:10 to 37:1", "no narrative", "\"This is the account of Jacob.\" 37:2"], ["", "no genealogy", "37:2 to 50:26", "no colophon"], ["8", "Descendants of Ishmael 25:13 - 18", "no narrative", "\"This is the account of Abraham's son Isaac.\" 25:19"], ["10", "Descendants of Esau 36:2 - 5", "36:6 - 8", "\"This is the account of Esau.\" 36:9"], ["5", "Descendants of Shem, Ham, and Japeth 10:1 - 32", "11:1 - 9", "\"This is the account of Shem.\" 11:10"], ["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"], ["3", "Adam to Noah 5:1 - 32", "6:1 - 8", "\"This is the account of Noah.\" 6:9"], ["7", "Terah to Abraham 11:27", "11:28 to 25:11", "\"This is the account of Abraham's son Ishmael.\" 25:12 (eldest son)"], ["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"], ["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"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 have no narrative? | 3 | 128 | Answer: |
Table InputTable: [["Week", "Date", "Opponent", "Results\\nFinal score", "Results\\nTeam record", "Venue", "Attendance"], ["12", "December 3", "Chicago Bears", "W 23–10", "7–5", "Metropolitan Stadium", "49,784"], ["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"], ["1", "September 18", "Washington Redskins", "L 24–21", "0–1", "Metropolitan Stadium", "47,900"], ["3", "October 1", "Miami Dolphins", "L 16–14", "1–2", "Metropolitan Stadium", "47,900"], ["8", "November 5", "New Orleans Saints", "W 37–6", "4–4", "Metropolitan Stadium", "49,784"], ["6", "October 23", "at Chicago Bears", "L 13–10", "2–4", "Soldier Field", "55,701"], ["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"], ["10", "November 19", "at Los Angeles Rams", "W 45–41", "6–4", "Los Angeles Memorial Coliseum", "77,982"], ["4", "October 8", "St. Louis Cardinals", "L 19–17", "1–3", "Metropolitan Stadium", "49,687"], ["2", "September 24", "at Detroit Lions", "W 34–10", "1–1", "Tiger Stadium", "54,418"], ["7", "October 29", "at Green Bay Packers", "W 27–13", "3–4", "Lambeau Field", "56,263"], ["5", "October 15", "at Denver Broncos", "W 23–20", "2–3", "Mile High Stadium", "51,656"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total of attendees for the december games? | 160782 | 128 | Answer: |
Table InputTable: [["Season", "Age", "Overall", "Slalom", "Giant\\nSlalom", "Super G", "Downhill", "Combined"], ["2011", "24", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete", "Injured, did not compete"], ["2005", "18", "37", "–", "27", "18", "49", "—"], ["2006", "19", "22", "–", "18", "37", "15", "—"], ["2013", "26", "37", "–", "17", "28", "30", "—"], ["2008", "21", "38", "–", "–", "35", "13", "—"], ["2012", "25", "75", "–", "28", "–", "–", "—"], ["2004", "17", "112", "–", "–", "51", "–", "—"], ["2010", "23", "28", "–", "–", "13", "23", "—"], ["2007", "20", "33", "–", "50", "15", "23", "—"], ["2009", "22", "9", "–", "40", "2", "5", "50"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many seasons has nadia fanchini competed all together? | 10 | 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 21, 2031", "March 9, 2035", "December 26, 2038", "October 14, 2042", "August 2, 2046"], ["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"], ["138", "140", "142", "144", "146"], ["128", "130", "132", "134", "136"], ["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:when is the next solar eclipse? | March 9, 2016 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Notes"], ["2007", "World Student Games", "Bangkok, Thailand", "5th", "64.95 m"], ["2009", "World Student Games", "Belgrade, Serbia", "2nd", "72.85 m"], ["1999", "World Youth Championships", "Bydgoszcz, Poland", "12th", ""], ["2002", "European Championships", "Munich, Germany", "26th", "60.28 m"], ["2012", "European Championships", "Helsinki, Finland", "2nd", "73.34 m"], ["2000", "World Junior Championships", "Santiago, Chile", "5th", ""], ["2008", "Olympic Games", "Beijing, PR China", "8th", "71.00 m"], ["2009", "World Championships", "Berlin, Germany", "3rd", "74.79 m"], ["2008", "World Athletics Final", "Stuttgart, Germany", "2nd", "71.40 m"], ["2002", "World Junior Championships", "Kingston, Jamaica", "2nd", "63.91 m"], ["2007", "World Championships", "Osaka, Japan", "13th", "68.15 m"], ["2006", "European Championships", "Gothenburg, Sweden", "26th", "62.39 m"], ["2001", "World Championships", "Edmonton, Canada", "23rd", "61.26 m"], ["2009", "World Athletics Final", "Thessaloniki, Greece", "3rd", "70.45 m"], ["2001", "European Junior Championships", "Grosseto, Italy", "2nd", "61.97 m"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the least entry listed under notes? | 60.28 m | 128 | Answer: |
Table InputTable: [["Rank", "City", "Passengers", "Ranking", "Airline"], ["2", "Nuevo León, Monterrey", "106,513", "", "Aeroméxico Connect, Interjet"], ["8", "Baja California, Tijuana", "14,906", "", "Interjet"], ["6", "Baja California Sur, Los Cabos", "37,526", "1", "Interjet"], ["3", "Guerrero, Acapulco", "56,069", "", "Aeroméxico Connect, Interjet"], ["4", "Jalisco, Guadalajara", "52,584", "", "Aeroméxico Connect, Volaris"], ["7", "Guerrero, Ixtapa/Zihuatanejo", "35,507", "", "Interjet"], ["1", "Quintana Roo, Cancún", "132,046", "", "Aeroméxico Connect, Interjet, Volaris"], ["5", "Jalisco, Puerto Vallarta", "43,419", "1", "Interjet"], ["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:what city served the least number of passengers in 2013? | Tamaulipas, Tampico | 128 | Answer: |
Table InputTable: [["Conference", "# of Bids", "Record", "Win %", "Round\\nof 32", "Sweet\\nSixteen", "Elite\\nEight", "Final\\nFour", "Championship\\nGame"], ["Southeastern", "6", "10–6", ".625", "5", "3", "1", "1", "–"], ["Southwest", "4", "5–4", ".556", "3", "2", "–", "–", "–"], ["Big East", "2", "5–2", ".714", "2", "2", "1", "–", "–"], ["Colonial", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["Big Eight", "4", "3–4", ".429", "2", "1", "–", "–", "–"], ["Western Athletic", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["West Coast", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Big Ten", "5", "9–5", ".643", "4", "2", "2", "1", "–"], ["Mid-Continent", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Atlantic 10", "3", "1–3", ".250", "1", "–", "–", "–", "–"], ["Pacific-10", "5", "8–5", ".615", "4", "2", "2", "–", "–"], ["Missouri Valley", "2", "2–2", ".500", "2", "–", "–", "–", "–"], ["Sun Belt", "2", "6–2", ".750", "2", "1", "1", "1", "1"], ["Great Midwest", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Atlantic Coast", "3", "9–2", ".818", "3", "2", "1", "1", "1"], ["Metro", "2", "2–2", ".500", "1", "1", "–", "–", "–"], ["Big Sky", "2", "1–2", ".333", "1", "–", "–", "–", "–"], ["Big West", "2", "0–2", "–", "–", "–", "–", "–", "–"]] | 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:which conference has had at least 6 bids? | Southeastern | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["8", "Croatia", "0", "3", "3", "6"], ["6", "Tunisia", "3", "0", "0", "3"], ["7", "Algeria", "2", "0", "2", "4"], ["3", "Slovenia", "5", "4", "3", "12"], ["2", "Italy", "12", "8", "10", "30"], ["9", "Egypt", "0", "1", "2", "3"], ["1", "France", "14", "7", "7", "28"], ["5", "Greece", "3", "4", "9", "16"], ["Total", "Total", "43", "41", "42", "126"], ["4", "Spain", "4", "14", "6", "24"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country has the top number of silver medals won? | Spain | 128 | Answer: |
Table InputTable: [["Season", "Class", "Moto", "Races", "Win", "Podiums", "Pole", "Pts", "Position"], ["2013", "Moto2", "Suter", "17", "3", "4", "1", "150", "7th"], ["2012", "Moto2", "Suter", "17", "0", "1", "0", "37", "17th"], ["2014", "Moto2", "Suter", "1", "0", "0", "0", "0*", "NC*"], ["2010", "125cc", "Aprilia", "16", "3", "14", "1", "296", "2nd"], ["2008", "125cc", "Aprilia", "17", "1", "5", "0", "176", "5th"], ["2004", "125cc", "Aprilia", "1", "0", "0", "0", "0", "NC"], ["2011", "125cc", "Aprilia", "16", "8", "11", "7", "302", "1st"], ["2009", "125cc", "Aprilia", "16", "1", "4", "0", "179.5", "3rd"], ["2005", "125cc", "Derbi", "13", "0", "0", "0", "1", "36th"], ["2007", "125cc", "Derbi", "17", "0", "0", "0", "19", "22nd"], ["2006", "125cc", "Derbi", "16", "0", "0", "0", "53", "14th"], ["Total", "", "", "147", "16", "39", "9", "1213.5", ""]] | 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:which is the last season that nicolás used an aprilia moto? | 2011 | 128 | Answer: |
Table InputTable: [["Celebrity", "Residence", "Famous for.../Occupation", "Age", "Status"], ["Bárbara Rey", "Totana, Murcia", "Actress, Vedette, TV Host", "61", "2nd Evicted"], ["Regina Do Santos", "Brazil", "Singer & Dancer", "58", "1st / 14th Evicted"], ["Brenda Cerdá", "Valencia", "Reality show star", "19", "4th Evicted"], ["Raúl Hidalgo", "Valladolid", "Reality show star", "29", "6th Evicted"], ["Leticia Sabater", "Barcelona", "TV Host", "45", "5th Evicted"], ["Pedro Reche, \"Reche\"", "Langreo, Asturias", "Reality show star", "27", "9th Evicted"], ["Antonio David Flores", "Madrid", "Ex-son-in-law of Rocío Jurado", "36", "7th Evicted"], ["Dionisio Rodríguez, \"Dioni\"", "Madrid", "Ex Security Guard, robbed a security van", "62", "Ejected"], ["Mª Ángeles Delgado", "Valladolid", "Mother of Reality-show star Aída Nízar", "57", "8th / 12th Evicted"], ["Sonia Baby", "Elche, Valencia", "Porn Actress", "30", "3rd Evicted"], ["Liberto López de la Franca", "Madrid", "Good manner teacher", "40", "13th Evicted"], ["Úrsula Aguilar", "Málaga", "Miss Málaga 2011", "24", "11th Evicted"], ["Álvaro Muñoz-Escassi", "Seville", "Horse rider & ex-boyfriend of Lara Dibildos", "42", "10th Evicted"], ["Nagore Robles", "Bilbao", "Gran Hermano 11 Housemate", "28", "Winner"], ["Blanca de Borbón", "Oviedo, Asturias", "Alfonso XIII's illegitimate granddaughter", "55", "3rd Finalist"], ["Raquel Bollo", "Seville", "TV Host & ex-wife of Chiquetete", "43", "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:who was the first person to get evicted? | Regina Do Santos | 128 | Answer: |
Table InputTable: [["Specifications", "Foundation", "Essentials", "Standard", "Datacenter"], ["Windows Server Update Services", "No", "Yes", "Yes", "Yes"], ["Windows Deployment Services", "Yes", "Yes", "Yes", "Yes"], ["Licensing model", "Per server", "Per server", "Per CPU pair + CAL", "Per CPU pair + CAL"], ["Server Manager", "Yes", "Yes", "Yes", "Yes"], ["File Services limits", "1 standalone DFS root", "1 standalone DFS root", "Unlimited", "Unlimited"], ["Server Core mode", "No", "No", "Yes", "Yes"], ["Application server role", "Yes", "Yes", "Yes", "Yes"], ["Remote Desktop Services limits", "50 Remote Desktop Services connections", "Gateway only", "Unlimited", "Unlimited"], ["Windows Powershell", "Yes", "Yes", "Yes", "Yes"], ["DNS server role", "Yes", "Yes", "Yes", "Yes"], ["Virtualization rights", "N/A", "Either in 1 VM or 1 physical server, but not both at once", "2 VMs", "Unlimited"], ["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"], ["Active Directory Certificate Services", "Certificate Authorities only", "Certificate Authorities only", "Yes", "Yes"], ["Active Directory Domain Services", "Must be root of forest and domain", "Must be root of forest and domain", "Yes", "Yes"], ["Active Directory Federation Services", "Yes", "No", "Yes", "Yes"], ["Fax server role", "Yes", "Yes", "Yes", "Yes"], ["DHCP role", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Rights Management Services", "Yes", "Yes", "Yes", "Yes"], ["Web Services (Internet Information Services)", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Lightweight Directory Services", "Yes", "Yes", "Yes", "Yes"], ["Distribution", "OEM only", "Retail, volume licensing, OEM", "Retail, volume licensing, OEM", "Volume licensing and OEM"], ["Memory limit", "32 GB", "64 GB", "4 TB", "4 TB"], ["Print and Document Services", "Yes", "Yes", "Yes", "Yes"], ["Processor chip limit", "1", "2", "64", "64"], ["User limit", "15", "25", "Unlimited", "Unlimited"], ["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:how many versions of windows server 2012 do not have windows server update services? | 1 | 128 | Answer: |
Table InputTable: [["Rank", "Athlete", "Nationality", "2.15", "2.20", "2.24", "2.27", "Result", "Notes"], ["1.", "Yaroslav Rybakov", "Russia", "o", "o", "o", "o", "2.27", "q"], ["13.", "Tomáš Janku", "Czech Republic", "o", "o", "xxo", "xxx", "2.24", ""], ["1.", "Andriy Sokolovskyy", "Ukraine", "o", "o", "o", "o", "2.27", "q"], ["1.", "Andrey Tereshin", "Russia", "o", "o", "o", "o", "2.27", "q"], ["1.", "Linus Thörnblad", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["1.", "Stefan Holm", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["10.", "Nicola Ciotti", "Italy", "o", "o", "xo", "xxx", "2.24", ""], ["15.", "Svatoslav Ton", "Czech Republic", "o", "xo", "xxx", "", "2.20", ""], ["7.", "Giulio Ciotti", "Italy", "o", "o", "o", "xxx", "2.24", "q"], ["1.", "Víctor Moya", "Cuba", "o", "o", "o", "o", "2.27", "q, PB"], ["8.", "Robert Wolski", "Poland", "xo", "o", "o", "xxx", "2.24", "q"], ["13.", "Mustapha Raifak", "France", "o", "o", "xxo", "xxx", "2.24", ""], ["16.", "Roman Fricke", "Germany", "o", "xxx", "", "2.15", "", ""], ["10.", "Wojciech Theiner", "Poland", "o", "o", "xo", "xxx", "2.24", ""], ["9.", "Ramsay Carelse", "South Africa", "xo", "xo", "o", "xxx", "2.24", ""], ["16.", "Adam Shunk", "United States", "o", "xxx", "", "2.15", "", ""], ["10.", "Tora Harris", "United States", "o", "o", "xo", "xxx", "2.24", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 athletes have the same score as rybakov? | 5 | 128 | Answer: |
Table InputTable: [["Country", "Amphibians", "Birds", "Mammals", "Reptile", "Total terrestrial vertebrates", "Vascular plants", "Biodiversity"], ["Costa Rica", "183", "838", "232", "258", "1511", "12119", "13630"], ["Panama", "182", "904", "241", "242", "1569", "9915", "11484"], ["Guatemala", "133", "684", "193", "236", "1246", "8681", "9927"], ["Nicaragua", "61", "632", "181", "178", "1052", "7590", "8642"], ["Belize", "46", "544", "147", "140", "877", "2894", "3771"], ["Honduras", "101", "699", "201", "213", "1214", "5680", "6894"], ["El Salvador", "30", "434", "137", "106", "707", "2911", "3618"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many more reptiles are there in costa rica then there are in panama? | 16 | 128 | Answer: |
Table InputTable: [["Year", "Network", "Race caller", "Color commentator", "Reporters", "Trophy Presentation"], ["1953", "CBS", "Bryan Field", "Mel Allen", "Phil Sutterfield", "Phil Sutterfield"], ["1956", "CBS", "Fred Capossela", "Bryan Field", "", ""], ["1952", "CBS", "Bryan Field", "Sam Renick", "", ""], ["1958", "CBS", "Fred Capossela", "Bryan Field", "", ""], ["1957", "CBS", "Fred Capossela", "Bryan Field", "", ""], ["1959", "CBS", "Fred Capossela", "Bryan Field and Chris Schenkel", "", "Chris Schenkel"], ["1954", "CBS", "Bryan Field", "Mel Allen", "", "Bill Corum"], ["1955", "CBS", "Fred Capossela", "Phil Sutterfield and Win Elliot", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many races in the 1950s were not called by bryan field? | 5 | 128 | Answer: |
Table InputTable: [["No. in\\nseries", "No. in\\nseason", "Title", "Directed by", "Written by", "Original air date", "Prod.\\ncode"], ["4", "7", "\"Danny was a Million Laughs\"", "Mark Rydell", "Arthur Dales", "October 27, 1965", "107"], ["11", "10", "\"Tatia\"", "David Friedkin", "Robert Lewin", "November 17, 1965", "110"], ["8", "6", "\"The Loser\"", "Mark Rydell", "Robert Culp", "October 20, 1965", "106"], ["12", "11", "\"Weight of the World\"", "Paul Wendkos", "Robert Lewin", "December 1, 1965", "111"], ["1", "14", "\"Affair in T'Sien Cha\"", "Sheldon Leonard", "Morton Fine & David Friedkin", "December 29, 1965", "114"], ["14", "12", "\"Three Hours on a Sunday\"", "Paul Wendkos", "Morton Fine & David Friedkin", "December 8, 1965", "112"], ["7", "5", "\"Dragon's Teeth\"", "Leo Penn", "Gilbert Ralston", "October 13, 1965", "105"], ["2", "3", "\"Carry Me Back to Old Tsing-Tao\"", "Mark Rydell", "David Karp", "September 29, 1965", "103"], ["26", "25", "\"My Mother, The Spy\"", "Richard Benedict", "Howard Gast", "March 30, 1966", "125"], ["10", "8", "\"The Time of the Knife\"", "Paul Wendkos", "Gilbert Ralston", "November 3, 1965", "108"], ["25", "24", "\"Crusade to Limbo\"", "Richard Sarafian", "Teleplay by: Morton Fine & David Freidkin & Jack Turley Story by: Jack Turley", "March 23, 1966", "124"], ["27", "26", "\"There was a Little Girl\"", "John Rich", "Teleplay by: Stephen Kandell Story by: Robert Bloch", "April 6, 1966", "126"], ["21", "21", "\"Return to Glory\"", "Robert Sarafian", "David Friedkin & Morton Fine", "February 23, 1966", "121"], ["13", "13", "\"Tigers of Heaven\"", "Allen Reisner", "Morton Fine & David Friedkin", "December 15, 1965", "113"], ["28", "27", "\"It's All Done with Mirrors\"", "Robert Butler", "Stephen Kandell", "April 13, 1966", "127"], ["16", "15", "\"The Tiger\"", "Paul Wendkos", "Robert Culp", "January 5, 1966", "115"], ["3", "1", "\"So Long, Patrick Henry\"", "Leo Penn", "Robert Culp", "September 15, 1965", "101"], ["9", "9", "\"No Exchange on Damaged Merchandise\"", "Leo Penn", "Gary Marshall & Jerry Belson", "November 10, 1965", "109"], ["15", "17", "\"Always Say Goodbye\"", "Allen Reisner", "Robert C. Dennis & Earl Barrett", "January 26, 1966", "117"], ["23", "23", "\"A Day Called 4 Jaguar\"", "Richard Sarafian", "Michael Zagar", "March 9, 1966", "123"], ["5", "2", "\"A Cup of Kindness\"", "Leo Penn", "Morton Fine & David Friedkin", "September 22, 1965", "102"], ["19", "19", "\"Turkish Delight\"", "Paul Wendkos", "Eric Bercovici", "February 9, 1966", "119"], ["22", "22", "\"The Conquest of Maude Murdock\"", "Paul Wendkos", "Robert C. Dennis & Earl Barrett", "March 2, 1966", "122"], ["18", "18", "\"Court of the Lion\"", "Robert Culp", "Robert Culp", "February 2, 1966", "118"], ["24", "28", "\"One Thousand Fine\"", "Paul Wendkos", "Eric Bercovici", "April 27, 1966", "128"], ["17", "16", "\"The Barter\"", "Allen Reisner", "Harvey Bullock & P.S. Allen", "January 12, 1966", "116"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many episodes were originally aired before december 1965? | 10 | 128 | Answer: |
Table InputTable: [["Player", "Friendlies", "FIFA Confederations Cup", "FIFA World Cup Qual.", "Total Goals"], ["Cahill", "-", "-", "1", "1"], ["Milicic", "2", "-", "-", "2"], ["Chipperfield", "1", "-", "1", "2"], ["Bresciano", "2", "-", "1", "3"], ["Elrich", "1", "-", "-", "1"], ["Griffiths", "1", "-", "-", "1"], ["Thompson", "1", "-", "2", "3"], ["Zdrilic", "1", "-", "-", "1"], ["Emerton", "-", "-", "2", "2"], ["Colosimo", "1", "-", "-", "1"], ["Viduka", "1", "-", "2", "3"], ["Aloisi", "1", "4", "-", "5"], ["Culina", "-", "-", "1", "1"], ["Skoko", "-", "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 player comes after cahill? | Colosimo | 128 | Answer: |
Table InputTable: [["County", "Brown", "Votes", "Nixon", "Votes", "Wyckoff", "Votes"], ["San Luis Obispo", "52.86%", "16,110", "45.36%", "13,825", "1.78%", "543"], ["Santa Barbara", "47.50%", "30,424", "51.24%", "32,821", "1.26%", "807"], ["San Joaquin", "49.40%", "43,276", "49.25%", "43,147", "1.34%", "1,178"], ["Sacramento", "60.69%", "115,462", "37.74%", "71,788", "1.57%", "2,988"], ["Siskiyou", "59.98%", "7,718", "38.41%", "4,942", "1.62%", "208"], ["Nevada", "51.02%", "4,818", "47.12%", "4,450", "1.85%", "175"], ["Riverside", "46.60%", "50,257", "51.86%", "55,926", "1.54%", "1,666"], ["Lake", "44.42%", "3,315", "54.15%", "4,041", "1.43%", "107"], ["Santa Clara", "51.20%", "121,149", "47.63%", "112,700", "1.18%", "2,783"], ["San Francisco", "62.19%", "180,298", "36.96%", "107,165", "0.85%", "2,455"], ["Sonoma", "49.19%", "29,373", "49.65%", "29,647", "1.17%", "696"], ["Fresno", "57.78%", "68,187", "40.85%", "48,211", "1.37%", "1,615"], ["Napa", "53.50%", "14,748", "44.72%", "12,326", "1.78%", "490"], ["San Bernardino", "51.68%", "88,437", "46.78%", "80,054", "1.54%", "2,634"], ["Los Angeles", "51.83%", "1,191,724", "46.98%", "1,080,113", "1.19%", "27,445"], ["Butte", "47.74%", "16,142", "50.79%", "17,172", "1.47%", "497"], ["El Dorado", "56.25%", "6,572", "41.44%", "4,842", "2.30%", "269"], ["San Diego", "42.40%", "153,389", "55.83%", "201,969", "1.77%", "6,416"], ["Mendocino", "51.50%", "8,704", "46.96%", "7,936", "1.54%", "261"], ["Santa Cruz", "44.93%", "17,354", "53.28%", "20,580", "1.79%", "690"], ["Kings", "59.03%", "9,141", "39.48%", "6,113", "1.49%", "231"], ["Alameda", "57.98%", "206,861", "40.88%", "145,851", "1.13%", "4,038"], ["Contra Costa", "55.49%", "91,150", "43.34%", "71,192", "1.18%", "1,935"], ["Merced", "57.62%", "14,105", "41.14%", "10,071", "1.23%", "302"], ["Sierra", "57.98%", "676", "39.54%", "461", "2.49%", "29"], ["Stanislaus", "53.64%", "30,431", "44.80%", "25,417", "1.57%", "888"], ["Kern", "52.10%", "48,737", "46.33%", "43,342", "1.57%", "1,471"], ["Shasta", "63.97%", "14,753", "34.07%", "7,858", "1.96%", "453"], ["Calaveras", "46.37%", "2,379", "51.75%", "2,655", "1.87%", "96"], ["Orange", "39.16%", "112,152", "59.35%", "169,962", "1.49%", "4,263"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 county did brown receive the most votes? | Plumas | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Runner-up", "1.", "6 October 2003", "Bari, Italy", "Clay", "Bettina Pirker", "6–2, 7–5"], ["Runner-up", "5.", "13 March 2007", "Orange, USA", "Hard", "Naomi Cavaday", "6–1, 6–1"], ["Runner-up", "8.", "9 July 2007", "Biella, Italy", "Clay", "Agnieszka Radwańska", "6–3, 6–3"], ["Runner-up", "11.", "14 June 2011", "Padova, Italy", "Clay", "Kristina Mladenovic", "3–6, 6–4, 6–0"], ["Runner-up", "12.", "27 August 2012", "Bagnatica, Italy", "Clay", "Maria-Elena Camerin", "7–6(5), 6–4"], ["Runner-up", "7.", "9 April 2007", "Civitavecchia, Italy", "Clay", "Darya Kustova", "3–6, 6–4, 6–4"], ["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", "4.", "31 July 2006", "Martina Franca, Italy", "Clay", "Margalita Chakhnashvili", "6–3, 7–5"], ["Runner-up", "13.", "12 May 2013", "Trnava, Slovakia", "Clay", "Barbora Záhlavová-Strýcová", "6–2, 6–4"], ["Runner-up", "2.", "14 June 2005", "Lenzerheide, Switzerland", "Clay", "Danica Krstajić", "6–2, 7–5"], ["Runner-up", "3.", "1 May 2006", "Catania, Italy", "Clay", "María José Martínez Sánchez", "6–3, 4–6, 6–4"], ["Winner", "3.", "7 June 2011", "Campobasso, Italy", "Clay", "Alizé Lim", "6–2, 6–4"], ["Runner-up", "6.", "3 April 2007", "Dinan, France", "Clay (i)", "Maša Zec Peškirič", "6–4, 6–2"], ["Winner", "4.", "20 June 2011", "Rome, Italy", "Clay", "Laura Thorpe", "6–3, 6–0"], ["Winner", "2.", "18 October 2010", "Seville, Spain", "Clay", "Andrea Gámiz", "6–0, 6–1"], ["Winner", "5.", "4 September 2012", "Mestre, Italy", "Clay", "Estrella Cabeza Candela", "6–1, 3–6, 6–1"], ["Winner", "1.", "25 July 2006", "Monteroni D'Arbia, Italy", "Clay", "Edina Gallovits-Hall", "6–2, 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:is the number of wins higher than the number of runner-up? | no | 128 | Answer: |
Table InputTable: [["Iteration", "Dates", "Location", "Attendance", "Notes"], ["GameStorm 15", "March 21–24, 2013", "Hilton - Vancouver, WA", "1188", ""], ["GameStorm 10", "March 2008", "Red Lion - Vancouver, WA", "750", "-"], ["GameStorm 12", "March 25–28, 2010", "Hilton - Vancouver, WA", "802", "Board games Guest of Honor: Tom Lehmann"], ["GameStorm 13", "March 24–27, 2011", "Hilton - Vancouver, WA", "984", "Guests: Lisa Steenson, Michael A. Stackpole"], ["GameStorm 14", "March 22–25, 2012", "Hilton - Vancouver, WA", "1072", "Boardgame:Andrew Hackard and Sam Mitschke of Steve Jackson Games - RPG: Jason Bulmahn"], ["GameStorm 16", "March 20–23, 2014", "Hilton - Vancouver, WA", "tba", "Guests: Mike Selinker, Shane Lacy Hensley, Lisa Steenson, Zev Shlasinger of Z-Man Games"], ["GameStorm 11", "March 26–29, 2009", "Hilton - Vancouver, WA", "736", "debut of Video games, first-ever Artist Guest of Honor, Rob Alexander"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 amount of attendance from gamestorm 10-15? | 5532 | 128 | Answer: |
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["DNQ", "28", "Skip Barber", "March-Ford", "", "", "", ""], ["DNQ", "18", "Alex Soler-Roig", "March-Ford", "", "", "", ""], ["7", "22", "John Surtees", "Surtees-Ford", "79", "+ 1 Lap", "10", ""], ["10", "8", "Tim Schenken", "Brabham-Ford", "76", "+ 4 Laps", "18", ""], ["DNQ", "16", "Howden Ganley", "BRM", "", "", "", ""], ["8", "27", "Henri Pescarolo", "March-Ford", "77", "+ 3 Laps", "13", ""], ["DNQ", "6", "Mario Andretti", "Ferrari", "", "", "", ""], ["Ret", "10", "Peter Gethin", "McLaren-Ford", "22", "Accident", "14", ""], ["5", "1", "Emerson Fittipaldi", "Lotus-Ford", "79", "+ 1 Lap", "17", "2"], ["DNQ", "19", "Nanni Galli*", "March-Alfa-Romeo", "", "", "", ""], ["4", "9", "Denny Hulme", "McLaren-Ford", "80", "+ 1:06.7", "8", "3"], ["6", "24", "Rolf Stommelen", "Surtees-Ford", "79", "+ 1 Lap", "16", "1"], ["Ret", "2", "Reine Wisell", "Lotus-Ford", "21", "Wheel bearing", "12", ""], ["Ret", "7", "Graham Hill", "Brabham-Ford", "1", "Accident", "9", ""], ["Ret", "12", "François Cevert", "Tyrrell-Ford", "5", "Accident", "15", ""], ["1", "11", "Jackie Stewart", "Tyrrell-Ford", "80", "1:52:21.3", "1", "9"], ["Ret", "5", "Clay Regazzoni", "Ferrari", "24", "Accident", "11", ""], ["2", "17", "Ronnie Peterson", "March-Ford", "80", "+ 25.6", "6", "6"], ["9", "15", "Pedro Rodríguez", "BRM", "76", "+ 4 Laps", "5", ""], ["3", "4", "Jacky Ickx", "Ferrari", "80", "+ 53.3", "2", "4"], ["Ret", "20", "Chris Amon", "Matra", "45", "Differential", "4", ""], ["Ret", "14", "Jo Siffert", "BRM", "58", "Oil Pipe", "3", ""], ["Ret", "21", "Jean-Pierre Beltoise", "Matra", "47", "Differential", "7", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers are listed as "did not qualify" or dnq? | 5 | 128 | Answer: |
Table InputTable: [["Place", "Player", "Country", "Score", "To par", "Money ($)"], ["T4", "Jeff Maggert", "United States", "69-72-77-66=284", "+4", "66,633"], ["T10", "Bob Tway", "United States", "69-69-72-75=285", "+5", "44,184"], ["T4", "Phil Mickelson", "United States", "68-70-72-74=284", "+4", "66,633"], ["1", "Corey Pavin", "United States", "72-69-71-68=280", "E", "350,000"], ["T4", "Neal Lancaster", "United States", "70-72-77-65=284", "+4", "66,633"], ["3", "Tom Lehman", "United States", "70-72-67-74=283", "+3", "131,974"], ["T4", "Jay Haas", "United States", "70-73-72-69=284", "+4", "66,633"], ["T4", "Bill Glasson", "United States", "69-70-76-69=284", "+4", "66,633"], ["T10", "Frank Nobilo", "New Zealand", "72-72-70-71=285", "+5", "44,184"], ["2", "Greg Norman", "Australia", "68-67-74-73=282", "+2", "207,000"], ["T4", "Davis Love III", "United States", "72-68-73-71=284", "+4", "66,633"], ["T10", "Vijay Singh", "Fiji", "70-71-72-72=285", "+5", "44,184"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 person from the us to earn less than $65,000 on june 18, 1995? | Bob Tway | 128 | Answer: |
Table InputTable: [["Rank", "Lane", "Name", "Nationality", "Time", "Notes"], ["7", "8", "Grant Patterson", "Australia", "55.49", ""], ["1", "5", "Eskender Mustafaiev", "Ukraine", "38.77", "Q"], ["2", "4", "David Smetanine", "France", "38.97", "Q"], ["5", "7", "Arnost Petracek", "Czech Republic", "43.12", ""], ["4", "6", "Christoffer Lindhe", "Sweden", "41.52", "Q"], ["3", "3", "Kyunghyun Kim", "South Korea", "40.37", "Q"], ["6", "2", "Ronystony Cordeiro da Silva", "Brazil", "44.22", ""], ["8", "1", "Arnulfo Castorena", "Mexico", "1:03.49", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how long did it take the 5th place swimmer to finish? | 43.12 | 128 | Answer: |
Table InputTable: [["Year", "Award", "Nominated work", "Category", "Result"], ["2007", "Cosmopolitan Ultimate Woman of the Year", "Leona Lewis", "Newcomer of the Year", "Won"], ["2009", "BEFFTA Awards", "Leona Lewis", "Best Female Act", "Won"], ["2008", "Glamour Woman Of The Year Awards", "Leona Lewis", "UK Solo Artist", "Won"], ["2009", "Cosmopolitan Awards", "Leona Lewis", "Ultimate Music Star", "Won"], ["2009", "PETA - Sexiest Vegetarian Alive Awards", "Leona Lewis", "Sexiest Vegetarian Celebrity 2009", "Won"], ["2008", "PETA", "Leona Lewis", "Person Of The Year", "Won"], ["2009", "NAACP Image Awards", "Leona Lewis", "Outstanding New Artist", "Nominated"], ["2008", "Capital Awards", "Leona Lewis", "Favourite UK Female Artist", "Won"], ["2008", "NewNowNext Awards", "Leona Lewis", "The Kylie Award: Next International Crossover", "Won"], ["2009", "Japan Gold Disc Awards", "Leona Lewis", "New Artist Of The Year", "Won"], ["2008", "Britain's Best", "Leona Lewis", "Music Award", "Won"], ["2009", "APRA Awards", "\"Bleeding Love\"", "Most Played Foreign Work", "Won"], ["2008", "Billboard 2008 Year End Award", "Leona Lewis", "Best New Artist", "Won"], ["2009", "Swiss Music Awards", "Leona Lewis", "Best International Newcomer", "Won"], ["2008", "Bambi Award", "Leona Lewis", "Shooting Star", "Won"], ["2008", "New Music Weekly Awards", "Leona Lewis", "Top 40 New Artist of the Year", "Won"], ["2007", "The Record of the Year", "\"Bleeding Love\"", "The Record of the Year", "Won"], ["2008", "UK Music Video Awards", "\"Bleeding Love\"", "People's Choice Award", "Won"], ["2009", "HITO Pop Music Awards", "\"Bleeding Love\"", "Best Western Song", "Won"], ["2008", "Vh1 Video of the Year", "\"Bleeding Love\"", "Best Video", "Won"], ["2008", "NME Best Album", "\"Spirit\"", "Best Album", "Nominated"], ["2008", "Nickelodeon UK Kids Choice Awards", "\"Bleeding Love\"", "Favourite Song", "Won"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many more awards did she win in 2009 than in 2007? | 6 | 128 | Answer: |
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