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: [["Year", "Name", "Label", "Hot Black Singles", "Club Play Singles"], ["1983", "\"I Need You Now\"", "Jive", "―", "―"], ["1982", "\"Thanks to You\"", "Becket", "#44", "#1"], ["1987", "\"Send It C.O.D.\"", "New Image", "―", "―"], ["1982", "\"He's Gonna Take You Home\"", "Becket", "―", "―"], ["1984", "\"Thin Line\"", "Power House", "―", "―"], ["1986", "\"Say It Again\"", "Spring", "―", "―"], ["1986", "\"Say It Again\"", "Spring", "―", "―"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 sinnamon's first label? | Becket | 128 | Answer: |
Table InputTable: [["Name", "Type", "R.A. (J2000)", "Dec. (J2000)", "Redshift (km/s)", "Apparent Magnitude"], ["IC 342", "SAB(rs)cd", "03h 46m 48.5s", "+68° 05′ 46″", "31 ± 3", "9.1"], ["NGC 1560", "SA(s)d", "04h 32m 49.1s", "+71° 52′ 59″", "-36 ± 5", "12.2"], ["NGC 1569", "Sbrst", "04h 30m 49.1s", "+64° 50′ 52,6″", "-104 ± 4", "11,2"], ["KK 35", "Irr", "03h 45m 12.6s", "+67° 51′ 51″", "105 ± 1", "17.2"], ["Cassiopeia 1", "dIrr", "02h 06m 02.8s", "+68° 59′ 59″", "35", "16.4"], ["Camelopardalis B", "Irr", "04h 53m 07.1s", "+67° 05′ 57″", "77", "16.1"], ["UGCA 92", "Im", "04h 32m 04.9s", "+63° 36′ 49.0″", "-99 ± 5", "13.8"], ["Camelopardalis A", "Irr", "04h 26m 16.3s", "+72° 48′ 21″", "-46 ± 1", "14.8"], ["UGCA 105", "Im", "05h 14m 15.3s", "+62° 34′ 48″", "111 ± 5", "13.9"], ["UGCA 86", "Im", "03h 59m 50.5s", "+67° 08′ 37″", "67 ± 4", "13.5"]] | 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 member of ic 342 subgroup has the most redshift? | UGCA 105 | 128 | Answer: |
Table InputTable: [["Client", "Years of Operation", "Area of Operation", "Country", "Services"], ["Agoco", "1991-current", "Sarir field", "Libya", "Drilling, workover"], ["Perenco Oil Co.", "2000-01", "EchiraX Concession", "Gabon", "Drilling"], ["IPC-Dublin", "1997-97", "Kilwa", "Tanzania", "Drilling"], ["SOC", "2000-current", "SOC fields", "Libya", "Drilling"], ["Zueitina", "2001-current", "Field 103", "Libya", "Drilling, workover"], ["Veba", "2000", "Different fields", "Libya", "Drilling, workover"], ["Total", "1999-current", "El Mabrouk", "Libya", "Drilling"], ["Khalda/Repsol", "1998-99", "West Desert", "Egypt", "Drilling"], ["IPLL", "1999-current", "El Naka field", "Libya", "Drilling"], ["Lasmo", "1993-94", "Wadi Borjuj", "Libya", "Drilling, workover"], ["OMV", "1997", "Field 103", "Libya", "Drilling, workover"], ["Marathon", "1998", "Manzala field", "Egypt", "Drilling"], ["Fina", "1997", "El Hamada", "Libya", "Drilling, workover"], ["Agiba-Agip", "1999", "West Desert", "Egypt", "Drilling"], ["Waha", "1994", "El Zahra", "Libya", "Drilling, workover"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 services are utilized by agoco? | 2 | 128 | Answer: |
Table InputTable: [["#", "Title", "Performer(s)", "Film", "Length"], ["14", "\"A Dream Is a Wish Your Heart Makes\"", "Disney Channel Stars", "Cinderella", "3:46"], ["2", "\"That's How You Know\"", "Demi Lovato", "Enchanted", "3:12"], ["12", "\"Happy Working Song\"", "Amy Adams", "Enchanted", "2:09"], ["6", "\"So This Is Love\"", "The Cheetah Girls", "Cinderella", "3:40"], ["7", "\"Kiss the Girl\"", "Colbie Caillat", "The Little Mermaid", "3:16"], ["13", "\"Part of Your World\"", "Original Broadway Cast", "The Little Mermaid", "3:23"], ["4", "\"Colors of the Wind\"", "Vanessa Hudgens", "Pocahontas", "3:58"], ["8", "\"It's Not Just Make Believe\"", "Kari Kimmel", "Ella Enchanted", "3:06"], ["3", "\"Some Day My Prince Will Come\"", "Ashley Tisdale", "Snow White and the Seven Dwarfs", "3:30"], ["1", "\"Once Upon a Dream\"", "Emily Osment", "Sleeping Beauty", "3:32"], ["9", "\"Under the Sea\"", "Raven-Symoné", "The Little Mermaid", "3:15"], ["10", "\"Ever Ever After\"", "Jordan Pruitt", "Enchanted", "3:12"], ["5", "\"Reflection\"", "Christina Aguilera", "Mulan", "3:33"], ["11", "\"True to Your Heart\"", "Keke Palmer", "Mulan", "3:22"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many artists were featured on the 2008 "princess disneymania". | 14 | 128 | Answer: |
Table InputTable: [["Chart Year", "Artist", "Album", "Song", "Billboard Hot 100", "Billboard Hot R&B/Hip Hop", ""], ["2014", "Rick Ross f/Jay Z", "Mastermind", "War Ready", "New Single", "", ""], ["2007", "Sean Paul", "The Trinity", "(When You Gonna) Give It Up To Me", "3", "5", ""], ["2012", "Tank", "This Is How I Feel", "Next Breath", "New Single", "", ""], ["2009", "Trey Songz", "Ready", "I Invented Sex", "42", "1", ""], ["2013", "T.I.", "Trouble Man", "Trap Back Jumpin", "New Single", "", ""], ["2011", "Lloyd", "King of Hearts", "Lloyd ft. Trey Songz & Young Jeezy", "New Single", "", ""], ["2014", "Future", "Honest", "Move That Dope", "New Single", "", ""], ["2011", "T.I. f/ B.o.B", "We Don't Get Down Like Y'all", "Forthcoming Album", "New Single", "", ""], ["2013", "T.I.", "Trouble Man", "Sorry f Andre 3000 Trouble Man", "New Single", "", ""], ["2008", "Usher", "Here I Stand", "Trading Places", "45", "4", ""], ["2008", "Usher", "Here I Stand", "Moving Mountains", "67", "18", ""], ["2009", "Lupe Fiasco", "Lasers", "Shining Down ft. Matthew Santos", "93", "", ""], ["2008", "The-Dream", "Love Hate", "I Luv Your Girl", "20", "3", ""], ["2010", "Trey Songz", "Passion, Pain & Pleasure", "Bottoms Up", "6", "2", ""], ["2009", "Jamie Foxx", "Intuition", "Digital Girl ft. The-Dream & Kanye West", "92", "38", ""], ["2014", "Future", "Honest", "Covered In Money", "New Single", "", ""], ["2010", "Trey Songz", "Passion, Pain & Pleasure", "Can't Be Friends", "43", "1", ""], ["2013", "The-Dream", "IV Play", "IV Play", "New Single", "", ""], ["2009", "Jamie Foxx", "Intuition", "Just Like Me ft. T.I.", "49", "8", ""], ["2012", "Ne-Yo", "Forthcoming Album", "Don't Make Em Like You", "New Single", "", ""], ["2009", "Mary J. Blige", "Stronger with Each Tear", "The One ft. Drake", "63", "32", ""], ["2011", "Marsha Ambrosius", "Late Nights & Early Mornings", "Late Nights & Early Mornings", "New Single", "30", ""], ["2008", "LL Cool J", "Exit 13", "Baby ft. The-Dream", "52", "22", ""], ["2009", "The-Dream", "Love vs. Money", "Rockin' That Shit", "22", "2", ""], ["2010", "The-Dream", "Love vs. Money", "Walkin' on the Moon ft. Kanye West", "87", "38", ""], ["2011", "Trey Songz", "Passion, Pain & Pleasure", "Love Faces", "", "3", ""], ["2007", "The-Dream", "Love Hate", "Falsetto", "30", "3", ""], ["2013", "Trevor Jackson", "Forthcoming Album", "Drop It", "New Single", "", ""], ["2008", "Jesse McCartney", "Departure", "Leavin'", "10", "", ""], ["2012", "Future", "Pluto", "Neva End f/Kelly Rowland", "21", "", ""], ["2012", "Future", "Pluto", "Turn On The Lights", "New Single", "5", ""], ["2012", "Karmin", "Forthcoming Album", "Crash Your Party", "New Single", "", ""], ["2013", "Omarion", "Self Made 3", "Know You Better f/ Fab", "New Single", "", ""], ["2008", "Jamie Foxx", "Intuition", "Blame It", "2", "1", "3"], ["2012", "John Legend", "Think Like A Man Soundtrack", "Tonight (Best You Ever Had)", "New Single", "12", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 song is previous to war ready | I Know f Rich Homie Quan | 128 | Answer: |
Table InputTable: [["Sr. No.", "Train No.", "Name of the Train", "Arrival", "Departure", "Day"], ["25.", "12722", "Dakshin Express", "16:00", "16:02", "Daily"], ["1.", "18238", "Chhatisgarh Express", "01:23", "01:25", "Daily"], ["14.", "12721", "Dakshin Express", "10:43", "10:44", "Daily"], ["26.", "51183", "Bhusaval-Narkhed Pass", "16:00", "N/a", "Daily"], ["34.", "51152", "Narkhed-New Amravati Pass", "N/a", "18:00", "Daily"], ["29.", "51830", "Agra-Nagpur Pass", "18:04", "18:05", "Daily"], ["33.", "18237", "Chhatisgarh Express", "23:09", "23:10", "Daily"], ["30.", "51293", "Nagpur-Amla Pass", "19:55", "20:00", "Daily"], ["12.", "51829", "Nagpur-Agra Pass", "09:41", "09:42", "Daily"], ["35.", "51184", "Bhusaval-Narkhed Pass", "N/a", "09:00", "Daily"], ["8.", "51151", "New Amravati-Narkhed Pass", "08:30", "N/a", "Daily"], ["3.", "51294", "Amla-Nagpur Pass", "06:39", "06:40", "Daily"], ["18.", "12615", "Grand Trunk(GT) Exp", "13:30", "13:32", "Daily"], ["31.", "12914", "Nagpur-Indore Tri. Exp", "20:08", "20:10", "M"], ["15.", "12616", "Grand Trunk(GT) Exp", "10:49", "10:51", "Daily"], ["21.", "16360", "Patna-Ernakulam Exp", "14:08", "14:10", "W"], ["32.", "12159", "Amravati-Jabalpur SF", "22:30", "22:32", "Daily"], ["11.", "16359", "Ernakulam-Patna Exp", "08:53", "08:55", "M"], ["2.", "12160", "Jabalpur-Amravati SF", "04:51", "04:53", "Daily"], ["27.", "11204", "Jaipur-Nagpur Exp", "17:24", "17:25", "St"], ["5.", "19301", "Indore-Yashwantpur Exp", "07:20", "07:25", "M"], ["13.", "12861", "Visakapatnam-Nizamuddin", "10:43", "10:44", "Daily"], ["24.", "19713", "Jaipur-Sec Exp", "15:48", "15:50", "Tu"], ["4.", "12913", "Indore-Nag Tri. Exp", "06:49", "06:51", "M"], ["10.", "11045", "Dikshsabhoomi Exp", "08:53", "08:55", "St"], ["22.", "11046", "Dikshsabhoomi Exp", "14:09", "14:10", "Tu"], ["16.", "19714", "Sec-Jaipur Exp", "11:58", "12:00", "Tu"], ["17.", "11203", "Nagpur-Jaipur Weekly Express", "13:03", "13:05", "T"], ["9.", "22112", "Nagpur-Bhusaval SF", "08:37", "08:39", "M,T,St"], ["23.", "22111", "Bhusaval_Nagpur SF", "14:36", "14:38", "S,W,F"], ["20.", "12409", "Raigarh-H.Nizamuddin- Gondwana Exp", "14:08", "14:10", "M,W,T,F,St"], ["28.", "19302", "Yashwantpur-Indore Exp", "17:35", "17:40", "W"], ["7.", "12410", "Nizamuddin-Raigarh Gondwana Exp", "07:25", "07:27", "S,M,Tu,W,T,F"], ["6.", "12406", "Nizamuddin-Bhusaval Gondwana Exp", "07:25", "07:27", "M,St"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many trains depart after 20:00 daily? | 3 | 128 | Answer: |
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2006", "Spartak Nizhny Novgorod", "Russia", "2", "36", "1"], ["2005", "CSKA Moscow", "Russia", "1", "0", "0"], ["2004", "CSKA Moscow", "Russia", "1", "0", "0"], ["2013/14", "Lokomotiv Moscow", "Russia", "1", "14", "1"], ["2012/13", "Lokomotiv Moscow", "Russia", "1", "8", "0"], ["2010/11", "Dnipro Dnipropetrovsk", "Ukraine", "1", "23", "0"], ["2011/12", "Dnipro Dnipropetrovsk", "Ukraine", "1", "16", "0"], ["2012/13", "Dnipro Dnipropetrovsk", "Ukraine", "1", "10", "1"], ["2008/09", "Dnipro Dnipropetrovsk", "Ukraine", "1", "22", "1"], ["2006/07", "Dnipro Dnipropetrovsk", "Ukraine", "1", "12", "0"], ["2009/10", "Dnipro Dnipropetrovsk", "Ukraine", "1", "28", "0"], ["2007/08", "Dnipro Dnipropetrovsk", "Ukraine", "1", "24", "0"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which team is not listed more than once? | Spartak Nizhny Novgorod | 128 | Answer: |
Table InputTable: [["Chart Year", "Artist", "Album", "Song", "Billboard Hot 100", "Billboard Hot R&B/Hip Hop", ""], ["2014", "Chris Brown", "X", "Loyal", "New Single", "", ""], ["2012", "Chris Brown f/ Big Sean & Wiz Khalifa", "Fortune", "Till I Die", "New Single", "12", ""], ["2009", "Jamie Foxx", "Intuition", "Digital Girl ft. The-Dream & Kanye West", "92", "38", ""], ["2007", "Sean Paul", "The Trinity", "(When You Gonna) Give It Up To Me", "3", "5", ""], ["2014", "Future", "Honest", "Move That Dope", "New Single", "", ""], ["2012", "Future", "Pluto", "Neva End f/Kelly Rowland", "21", "", ""], ["2009", "Justin Bieber", "My World", "Love Me", "37", "", ""], ["2008", "The-Dream", "Love Hate", "I Luv Your Girl", "20", "3", ""], ["2010", "Rihanna", "Loud", "Skin", "", "", ""], ["2013", "T.I.", "Trouble Man", "Sorry f Andre 3000 Trouble Man", "New Single", "", ""], ["2009", "Justin Bieber", "My World", "Favorite Girl", "26", "", ""], ["2013", "The-Dream", "IV Play", "IV Play", "New Single", "", ""], ["2009", "Justin Bieber", "My World", "Bigger", "94", "", ""], ["2013", "Tyler The Creator", "Wolf", "Domo 23 & Rusty", "New Single", "", ""], ["2012", "Future", "Pluto", "Turn On The Lights", "New Single", "5", ""], ["2011", "Big Sean", "Finally Famous", "Dance (A$$)", "10", "3", ""], ["2013", "Chris Brown", "X", "Fine China", "31", "", ""], ["2013", "Ciara", "Ciara", "Overdose", "New Single", "", ""], ["2013", "T.I.", "Trouble Man", "Trap Back Jumpin", "New Single", "", ""], ["2014", "Future", "Honest", "Covered In Money", "New Single", "", ""], ["2009", "Whitney Houston", "I Look to You", "I Look To You", "70", "19", ""], ["2010", "Justin Bieber", "My World 2.0", "Somebody to Love", "15", "20", ""], ["2014", "Kid Ink", "My Own Lane", "Show Me", "New Single", "", ""], ["2013", "Trevor Jackson", "Forthcoming Album", "Drop It", "New Single", "", ""], ["2012", "Tank", "This Is How I Feel", "Next Breath", "New Single", "", ""], ["2014", "Marsha Ambrosius", "FVCK&LOVE", "Friends & Lovers", "New Single", "", ""], ["2014", "Yo Gotti", "I Am", "I Know f Rich Homie Quan", "New Single", "", ""], ["2013", "Chris Brown", "X", "Love More f/Nikki Minaj", "31", "", ""], ["2014", "Kid Ink", "My Own Lane", "Main Chick", "New Single", "", ""], ["2009", "Justin Bieber", "My World", "Down To Earth", "79", "", ""], ["2008", "Mariah Carey", "E=MC²", "Touch My Body", "1", "2", ""], ["2013", "Yo Gotti", "I Am", "Don't Come Around", "New Single", "", ""], ["2013", "Omarion", "Self Made 3", "Know You Better f/ Fab", "New Single", "", ""], ["2013", "Yo Gotti", "I Am", "King Shit f/TI", "New Single", "", ""], ["2012", "Chris Brown f/Kevin McCall", "Fortune", "Strip", "42", "3", ""], ["2012", "Chris Brown", "Fortune", "Don't Judge Me", "18", "", ""], ["2013", "Jhene Aiko", "Sail Out", "Bed Peace f/Childish Gambino", "New Single", "", ""], ["2011", "Lloyd", "King of Hearts", "Lloyd ft. Trey Songz & Young Jeezy", "New Single", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the last artist and it song on this chart | Ayumi Hamasaki, Like a doll | 128 | Answer: |
Table InputTable: [["Wrestler:", "Times:", "Date:", "Location:", "Notes:"], ["Tigers Mask", "4", "May 19, 2013", "Osaka, Japan", "Defeated Billyken Kid in the finals of a four-man tournament to win the vacant title."], ["Tigers Mask", "2", "July 29, 2010", "Osaka, Japan", ""], ["Tigers Mask", "1", "February 12, 2007", "Osaka, Japan", ""], ["Tigers Mask", "3", "April 29, 2011", "Osaka, Japan", ""], ["Billyken Kid", "2", "August 26, 2006", "Osaka, Japan", ""], ["Billyken Kid", "1", "August 8, 2004", "Osaka, Japan", ""], ["Billyken Kid", "5", "August 14, 2011", "Osaka, Japan", ""], ["Billyken Kid", "3", "February 15, 2009", "Osaka, Japan", ""], ["Billyken Kid", "4", "February 11, 2010", "Osaka, Japan", ""], ["Super Delfin", "1", "January 4, 2000", "Tokyo, Japan", "Beat Dick Togo for the championship"], ["Asian Cougar / Kuuga", "1", "August 28, 2010", "Osaka, Japan", "Asian Cougar renamed himself Kuuga during his reign."], ["Black Buffalo", "1", "March 25, 2012", "Osaka, Japan", ""], ["Daisuke Harada", "2", "July 22, 2012", "Osaka, Japan", ""], ["“Big Boss” MA-G-MA", "1", "October 2, 2004", "Osaka, Japan", ""], ["Quiet Storm", "1", "July 21, 2013", "Osaka, Japan", ""], ["Vacated", "N/A", "March 30, 2013", "Osaka, Japan", "Title vacated, after Harada announced that he was not re-signing with Osaka Pro after his contract ran out on April 29, 2013."], ["Dick Togo", "1", "July 25, 2009", "Osaka, Japan", ""], ["Super Delfin", "2", "June 18, 2000", "Osaka, Japan", ""], ["Daisuke Harada", "1", "February 26, 2012", "Osaka, Japan", ""], ["Hideyoshi", "1", "July 26, 2008", "Osaka, Japan", ""], ["Super Delfin", "4", "February 26, 2006", "Osaka, Japan", ""], ["Takehiro Murahama", "1", "May 7, 2000", "Tokyo, Japan", ""], ["Super Delfin", "3", "January 3, 2002", "Osaka, Japan", ""], ["Takehiro Murahama", "2", "July 6, 2003", "Osaka, Japan", ""], ["Super Dolphin", "1", "February 13, 2005", "Osaka, Japan", ""], ["Zeus", "1", "January 19, 2014", "Osaka, Japan", ""], ["Gamma", "1", "June 24, 2001", "Osaka, Japan", ""], ["CIMA", "1", "June 18, 2010", "Osaka, Japan", ""], ["Daio QUALLT", "1", "April 17, 2004", "Osaka, Japan", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who won more titles, billyken kid or tigers mask? | Billyken Kid | 128 | Answer: |
Table InputTable: [["Team", "No", "Driver", "Class", "Rounds"], ["Josef Kaufmann Racing", "6", "Petri Suvanto", "R", "All"], ["Josef Kaufmann Racing", "4", "Robin Frijns", "", "All"], ["Josef Kaufmann Racing", "5", "Hannes van Asseldonk", "R", "All"], ["Fortec Motorsport", "26", "Christof von Grünigen", "", "All"], ["Mücke Motorsport", "7", "Maciej Bernacik", "R", "All"], ["Fortec Motorsport", "25", "George Katsinis", "", "All"], ["Mücke Motorsport", "8", "Timmy Hansen", "", "All"], ["Fortec Motorsport", "24", "Jack Harvey", "", "All"], ["Eifelland Racing", "20", "Marc Coleselli", "R", "All"], ["Eifelland Racing", "19", "Côme Ledogar", "", "All"], ["Eifelland Racing", "18", "Facundo Regalia", "", "All"], ["EuroInternational", "12", "Carlos Sainz, Jr.", "R", "All"], ["EuroInternational", "11", "Daniil Kvyat", "R", "All"], ["DAMS", "17", "Dustin Sofyan", "", "8"], ["DAMS", "15", "Javier Tarancón", "", "All"], ["DAMS", "16", "Dustin Sofyan", "", "5"], ["DAMS", "16", "Luciano Bacheta", "", "7–8"], ["EuroInternational", "14", "Michael Lewis", "", "All"], ["DAMS", "17", "Fahmi Ilyas", "", "1–6"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:the total number of josef kaufmann racing drivers? | 3 | 128 | Answer: |
Table InputTable: [["State\\n(linked to\\nsummaries below)", "Incumbent\\nSenator", "Incumbent\\nParty", "Incumbent\\nElectoral\\nhistory", "Most recent election results", "2018 intent", "Candidates"], ["Texas", "Ted Cruz", "Republican", "Ted Cruz (R) 56.5%\\nPaul Sadler (D) 40.7%\\nJohn Jay Myers (L) 2.1%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["California", "Dianne Feinstein", "Democratic", "Dianne Feinstein (D) 62.5%\\nElizabeth Emken (R) 37.5%", "1992 (special)\\n1994\\n2000\\n2006\\n2012", "Running", "[Data unknown/missing. You can help!]"], ["Arizona", "Jeff Flake", "Republican", "Jeff Flake (R) 49.2%\\nRichard Carmona (D) 46.1%\\nMarc Victor (L) 4.6%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Indiana", "Joe Donnelly", "Democratic", "Joe Donnelly (D) 50.0%\\nRichard Mourdock (R) 44.2%\\nAndrew Horning (L) 5.7%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Florida", "Bill Nelson", "Democratic", "Bill Nelson (D) 55.2%\\nConnie Mack IV (R) 42.2%", "2000\\n2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Nebraska", "Deb Fischer", "Republican", "Deb Fischer (R) 57.8%\\nBob Kerrey (D) 42.2%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Virginia", "Tim Kaine", "Democratic", "Tim Kaine (D) 52.9%\\nGeorge Allen (R) 47%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Delaware", "Tom Carper", "Democratic", "Tom Carper (D) 66.4%\\nKevin L. Wade (R) 29.0%\\nAlex Pires (I) 3.8%", "2000\\n2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Montana", "Jon Tester", "Democratic", "Jon Tester (D) 48.6%\\nDenny Rehberg (R) 44.9%\\nDan Cox (L) 6.6%", "2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Wyoming", "John Barrasso", "Republican", "John Barrasso (R) 75.7%\\nTim Chestnut (D) 21.7%\\nJoel Otto (Wyoming Country) 2.6%", "2008 (special)\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Nevada", "Dean Heller", "Republican", "Dean Heller (R) 45.9%\\nShelley Berkley (D) 44.7%\\nDavid Lory VanderBeek (C) 4.9%\\nNone of These Candidates 4.5%", "2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Maryland", "Ben Cardin", "Democratic", "Ben Cardin (D) 56.0%\\nDan Bongino (R) 26.3%\\nS. Rob Sobhani (I) 16.4%", "2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"], ["Rhode Island", "Sheldon Whitehouse", "Democratic", "Sheldon Whitehouse (D) 64.8%\\nBarry Hinckley (R) 35.0%", "2006\\n2012", "[Data unknown/missing. You can help!]", "[Data unknown/missing. You can help!]"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 republicans vs. democrats are involved in the race? | 8 | 128 | Answer: |
Table InputTable: [["Position", "Driver", "No.", "Car", "Entrant", "Lak.", "Ora.", "San.", "Phi.", "Total"], ["7", "Mike Imrie", "4", "Saab", "Imrie Motor Sport", "23", "11", "-", "28", "62"], ["17", "Phil Crompton", "49", "Ford EA Falcon", "Phil Crompton", "17", "-", "-", "-", "17"], ["4", "Mick Monterosso", "2", "Ford Escort RS2000", "Mick Monterosso", "-", "34", "36", "34", "104"], ["18", "Allan McCarthy", "", "Alfa Romeo Alfetta", "", "14", "-", "-", "-", "14"], ["14", "Brian Smith", "", "Alfa Romeo GTV Chevrolet", "", "-", "28", "-", "-", "28"], ["9", "Ivan Mikac", "42", "Mazda RX-7", "Ivan Mikac", "-", "-", "25", "26", "51"], ["11", "Kevin Clark", "116", "Ford Mustang GT", "Kevin Clark", "-", "-", "23", "23", "46"], ["6", "Danny Osborne", "", "Mazda RX-7", "", "26", "10", "30", "-", "66'"], ["1", "John Briggs", "9", "Honda Prelude Chevrolet", "John Briggs", "42", "42", "42", "42", "168"], ["13", "Chris Fing", "", "Chevrolet Monza", "", "29", "-", "-", "-", "29"], ["10", "Des Wall", "", "Toyota Supra", "", "15", "32", "-", "-", "47"], ["15", "Gary Rowe", "47", "Nissan Stanza", "Gary Rowe", "-", "-", "21", "-", "21"], ["3", "James Phillip", "55", "Honda Prelude Chevrolet", "James Phillip", "26", "28", "28", "30", "112"], ["12", "Peter O'Brien", "17", "Holden VL Commodore", "O'Brien Aluminium", "-", "11", "29", "-", "40"], ["2", "Kerry Baily", "18", "Toyota Supra Chevrolet", "Kerry Baily", "38", "38", "36", "38", "150"], ["8", "Mark Trenoweth", "", "Jaguar", "", "33", "24", "-", "-", "57"], ["5", "Bob Jolly", "3", "Holden VS Commodore", "Bob Jolly", "-", "28", "16", "32", "76"], ["19", "Chris Donnelly", "", "", "", "12", "-", "-", "-", "12"], ["22", "Shane Eklund", "", "", "", "10", "-", "-", "-", "10"], ["21", "Brett Francis", "", "", "", "11", "-", "-", "-", "11"], ["", "Paul Barrett", "", "", "", "-", "-", "-", "12", "12"], ["", "Domenic Beninca", "", "", "", "-", "-", "-", "21", "21"], ["", "Craig Wildridge", "", "", "", "-", "10", "-", "-", "10"], ["", "Ron O'Brien", "", "", "", "-", "-", "-", "10", "10"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of drivers listed under the entrant column? | 11 | 128 | Answer: |
Table InputTable: [["Locomotive", "Name", "Serial No", "Entered Service", "Livery"], ["9007", "Dunc Gray", "1379/918266-7", "May 94", "FreightCorp"], ["9006", "Murray Rose", "1378/918266-6", "May 94", "FreightCorp"], ["9028", "-", "1400/918266/28", "Aug 94", "FreightCorp"], ["9015", "Duncan Armstrong", "1387/918266-15", "Jul 94", "FreightCorp"], ["9029", "-", "1401/918266/29", "Aug 94", "FreightCorp"], ["9001", "Ernest Henry", "1373/918266-3", "May 94", "FreightCorp"], ["9008", "Ralph Doubell", "1380/918266-8", "Aug 94", "FreightCorp"], ["9024", "John Winter", "1396/918266-24", "Aug 94", "FreightCorp"], ["9009", "Lionel Cox", "1381/918266-9", "Jul 94", "FreightCorp"], ["9020", "Russell Mark", "1392/918266-20", "Jun 94", "FreightCorp"], ["9031", "-", "1403/918266/31", "Aug 94", "FreightCorp"], ["9023", "Robert Windle", "1395/918266-23", "Oct 94", "FreightCorp"], ["9010", "John Devitt", "1382/918266-10", "Jul 94", "FreightCorp"], ["9027", "-", "1399/918266-27", "Aug 94", "FreightCorp"], ["9002", "Michael Wendon", "1374/918266-2", "May 94", "FreightCorp"], ["9018", "John Konrads", "1390/918266-18", "Jul 94", "FreightCorp"], ["9021", "Ian O'Brien", "1393/918266-21", "Aug 94", "FreightCorp"], ["9026", "David Theile", "1398/918266-26", "Oct 94", "FreightCorp"], ["9019", "Dean Lukin", "1391/918266-19", "Jul 94", "FreightCorp"], ["9014", "Peter Antonie/Stephen Hawkins", "1386/918266-14", "Jul 94", "FreightCorp"], ["9004", "Kevin Nichols", "1376/918266-4", "May 94", "FreightCorp"], ["9022", "Clint Robinson", "1394/918266-22", "Aug 94", "FreightCorp"], ["9017", "Andrew Cooper/Nicholas Green/\\nMichael McKay/James Tomkins", "1389/918266-17", "Jun 94", "FreightCorp"], ["9016", "Herb Elliott", "1388/918266-16", "Jul 94", "FreightCorp"], ["9012", "Neil Brooks/Peter Evans/\\nMark Kerry/Mark Tonelli", "1384/918266-12", "Jun 94", "FreightCorp"], ["9005", "Kevin Barry", "1377/918266-5", "May 94", "FreightCorp"], ["9025", "Todd Woodbridge/Mark Woodforde", "1397/918266-25", "Aug 94", "FreightCorp"], ["9003", "Matthew Ryan", "1375/918266-1", "Aug 94", "FreightCorp"], ["9011", "Kevan Gosper", "1383/918266-11", "Jul 94", "FreightCorp"], ["9013", "Michael Diamond", "1385/918266-13", "Jun 94", "FreightCorp"], ["9035", "-", "05-1695", "Nov 05", "Pacific National"], ["9030", "Australian Men's Hockey Team", "1402/918266-30", "Aug 94", "FreightCorp"], ["9034", "-", "05-1694", "Nov 05", "Pacific National"], ["9032", "-", "05-1692", "Nov 05", "Pacific National"], ["9033", "-", "05-1693", "Nov 05", "Pacific National"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 locomotives listed? | 35 | 128 | Answer: |
Table InputTable: [["#", "Name", "Height", "Weight (lbs.)", "Position", "Class", "Hometown", "Previous Team(s)"], ["22", "Justin Holiday", "6'6\"", "170", "F", "Fr.", "Chatsworth, CA, U.S.", "Campbell Hall School"], ["44", "Darnell Gant", "6'8\"", "215", "F", "Fr.", "Los Angeles, CA, U.S.", "Crenshaw HS"], ["5", "Justin Dentmon", "5'11\"", "185", "G", "Jr.", "Carbondale, IL, U.S.", "Winchendon School"], ["20", "Ryan Appleby", "6'3\"", "170", "G", "Sr.", "Stanwood, WA, U.S.", "Florida"], ["4", "Tim Morris", "6'4\"", "210", "G", "Sr.", "Spokane Wa, U.S.", "Central Valley HS"], ["40", "Jon Brockman", "6'7\"", "255", "F", "Jr.", "Snohomish, WA, U.S.", "Snohomish Sr. HS"], ["11", "Matthew Bryan-Amaning", "6'9\"", "235", "F", "Fr.", "London, England, U.K.", "South Kent School"], ["24", "Quincy Pondexter", "6'6\"", "210", "F", "So.", "Fresno, CA, U.S.", "San Joaquin Memorial HS"], ["32", "Joe Wolfinger", "7'0\"", "255", "C", "RS So.", "Portland, OR, U.S.", "Northfield Mount Hermon School"], ["1", "Venoy Overton", "5'11\"", "180", "G", "Fr.", "Seattle, WA, U.S.", "Franklin HS"], ["0", "Joel Smith", "6'4\"", "210", "G", "RS Jr.", "Lompoc, CA, U.S.", "Brewster Academy"], ["21", "Artem Wallace", "6'8\"", "250", "C", "Jr.", "Toledo, WA, U.S.", "Toledo HS"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the difference between justin holiday and darnell gant? | 2 inches | 128 | Answer: |
Table InputTable: [["Game", "Date", "Opponent", "Location", "Score", "OT", "Attendance", "Record"], ["1", "December 30, 2007", "@ Portland LumberJax", "Rose Garden", "L 10–11", "OT", "8,437", "0–1"], ["4", "January 20, 2007", "Minnesota Swarm", "HSBC Arena", "W 22–13", "", "12,883", "2–2"], ["12", "March 24, 2007", "Colorado Mammoth", "HSBC Arena", "W 19–15", "", "15,156", "8–4"], ["2", "January 12, 2007", "New York Titans", "HSBC Arena", "W 16–14", "", "18,690", "1–1"], ["15", "April 13, 2007", "Rochester Knighthawks", "HSBC Arena", "L 10–14", "", "15,334", "10–5"], ["5", "February 2, 2007", "Toronto Rock", "HSBC Arena", "L 10–14", "", "13,659", "2–3"], ["3", "January 13, 2007", "@ Colorado Mammoth", "Pepsi Center", "L 10–11", "OT", "16,523", "1–2"], ["16", "April 14, 2007", "@ Rochester Knighthawks", "Blue Cross Arena", "L 8–14", "", "11,200", "10–6"], ["14", "April 7, 2007", "Arizona Sting", "HSBC Arena", "W 15–5", "", "13,492", "10–4"], ["13", "March 31, 2007", "Chicago Shamrox", "HSBC Arena", "W 15–10", "", "16,228", "9–4"], ["10", "March 4, 2007", "@ Minnesota Swarm", "Xcel Energy Center", "W 16–15", "", "7,504", "6–4"], ["9", "February 24, 2007", "Philadelphia Wings", "HSBC Arena", "W 13–12", "", "14,882", "5–4"], ["11", "March 17, 2007", "@ New York Titans", "Madison Square Garden", "W 11–8", "", "7,012", "7–4"], ["7", "February 11, 2007", "@ Chicago Shamrox", "Sears Centre", "W 12–11", "", "5,010", "3–4"], ["6", "February 3, 2007", "@ Toronto Rock", "Air Canada Centre", "L 8–13", "", "15,471", "2–4"], ["8", "February 17, 2007", "@ Philadelphia Wings", "Wachovia Center", "W 12–8", "", "12,688", "4–4"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which location had the least attendance? | Sears Centre | 128 | Answer: |
Table InputTable: [["#", "Office", "Current Officer"], ["4", "Attorney General of New Mexico", "Gary King"], ["1", "Lieutenant Governor of New Mexico", "John Sanchez"], ["", "Governor of New Mexico", "Susana Martinez"], ["2", "Secretary of State of New Mexico", "Dianna Duran"], ["4", "Speaker of the House of Representatives", "W. Ken Martinez"], ["3", "President Pro Tempore of the Senate", "Mary Kay Papen"], ["5", "State Auditor", "Hector Balderas"], ["7", "Commissioner of Public Lands", "Ray Powell"], ["12", "Public Regulation Commissioner", "Ben Hall"], ["6", "State Treasurer", "James B. Lewis"], ["11", "Public Regulation Commissioner", "Theresa Becenti–Aguilar"], ["10", "Public Regulation Commissioner", "Valerie Espinoza"], ["9", "Public Regulation Commissioner", "Karen Montoya"], ["8", "Public Regulation Commission, Chair", "Patrick Lyons"], ["", "May serve as Emergency Interim Successor", ""], ["", "May succeed to Governorship", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 attorney general of new mexico currently? | Gary King | 128 | Answer: |
Table InputTable: [["Match", "Date", "Venue", "Opponents", "Score"], ["Quarterfinals-2", "2008..", "[[]]", "[[]]", "-"], ["Quarterfinals-1", "2008..", "[[]]", "[[]]", "-"], ["GL-B-6", "2008..", "[[]]", "[[]]", "-"], ["GL-B-2", "2008..", "[[]]", "[[]]", "-"], ["GL-B-1", "2008..", "[[]]", "[[]]", "-"], ["GL-B-3", "2008..", "[[]]", "[[]]", "-"], ["GL-B-4", "2008..", "[[]]", "[[]]", "-"], ["GL-B-5", "2008..", "[[]]", "[[]]", "-"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many consecutive matches happened in 2008? | 8 | 128 | Answer: |
Table InputTable: [["Contestant", "Original Tribe", "Switched Tribe", "Merged Tribe", "Finish", "Total Votes"], ["Igor' Livanov\\n49.the actor", "Pelicans", "", "", "Eliminated\\nDay 11", "0"], ["Aleksandr Byalko\\n50.the physicist", "Pelicans", "Barracudas", "", "5th Voted Out\\nDay 15", "6"], ["Larisa Verbitskaya\\n43.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "12th Voted Out\\n7th Jury Member\\nDay 36", "11"], ["Aleksandr Lykov\\n41.the actor", "Barracudas", "Barracudas", "Crocodiles", "13th Voted Out\\n8th Jury Member\\nDay 37", "6"], ["Aleksandr Pashutin\\n60.the actor", "Barracudas", "", "", "3rd Voted Out\\nDay 9", "7"], ["Marina Aleksandrova\\n20.the actress", "Barracudas", "Pelicans", "Crocodiles", "9th Voted Out\\n4th Jury Member\\nDay 27", "6"], ["Ivan Demidov\\n39.the TV presenter", "Barracudas", "Pelicans", "Crocodiles", "Eliminated\\n2nd Jury Member\\nDay 23", "3"], ["Yelena Proklova\\n49.the TV presenter", "Pelicans", "Barracudas", "Crocodiles", "8th Voted Out\\n3rd Jury Member\\nDay 24", "4"], ["Vladimir Presnyakov, Jr.\\n34.the singer", "Pelicans", "Pelicans", "Crocodiles", "Sole Survivor", "6"], ["Vera Glagoleva\\n46.the actress", "", "", "Crocodiles", "11th Voted Out\\n6th Jury Member\\nDay 33", "4"], ["Tatyana Dogileva\\n45.the actress", "Pelicans", "Barracudas", "", "6th Voted Out\\nDay 18", "3"], ["Olga Orlova\\n25.the singer", "Barracudas", "Baracudas", "Crocodiles", "Eliminated\\n9th Jury Member\\nDay 38", "10"], ["Dana Borisova\\n26.the TV presenter", "Pelicans", "Barracudas", "", "4th Voted Out\\nDay 12", "5"], ["Yelena Kondulaynen\\n44.the actress", "Pelicans", "", "", "1st Voted Out\\nDay 3", "5"], ["Viktor Gusev\\n47.the sport commentator", "Pelicans", "Pelicans", "Crocodiles", "7th Voted Out\\n1st Jury Member\\nDay 21", "6"], ["Yelena Perova\\n26.the singer", "Pelicans", "Pelicans", "Crocodiles", "Runner-Up", "2"], ["Tat'yana Ovsiyenko\\n36.the singer", "Barracudas", "Pelicans", "", "Eliminated\\nDay 19", "1"], ["Kris Kelmi\\n47.the singer", "Barracudas", "", "", "2nd Voted Out\\nDay 6", "1"], ["Ivar Kalnynsh\\n54.the actor", "", "", "Crocodiles", "10th Voted Out\\n5th Jury Member\\nDay 30", "3"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who had more votes, byalko or livanov? | Aleksandr Byalko 50.the physicist | 128 | Answer: |
Table InputTable: [["Game", "Day", "Date", "Kickoff", "Opponent", "Results\\nScore", "Results\\nRecord", "Location", "Attendance"], ["2", "Sunday", "November 17", "1:05pm", "Monterrey Flash", "L 6–10", "0–2", "UniSantos Park", "363"], ["1", "Sunday", "November 10", "3:05pm", "at Las Vegas Legends", "L 3–7", "0–1", "Orleans Arena", "1,836"], ["12", "Sunday", "January 26", "1:05pm", "Sacramento Surge", "W 20–6", "7–5", "UniSantos Park", "224"], ["5", "Saturday", "December 14", "7:05pm", "at Sacramento Surge", "W 7–6 (OT)", "3–2", "Estadio Azteca Soccer Arena", "215"], ["14", "Friday", "February 7", "7:05pm", "at Turlock Express", "L 6–9", "7–7", "Turlock Soccer Complex", "673"], ["9", "Sunday", "January 5", "1:05pm", "San Diego Sockers", "L 7–12", "4–5", "UniSantos Park", "388"], ["7", "Sunday", "December 22", "1:05pm", "Turlock Express", "W 16–8", "4–3", "UniSantos Park", "218"], ["8", "Saturday", "January 4", "7:05pm", "at Ontario Fury", "L 5–12", "4–4", "Citizens Business Bank Arena", "2,653"], ["6", "Sunday", "December 15", "6:00pm", "at Bay Area Rosal", "L 8–9 (OT)", "3–3", "Cabernet Indoor Sports", "480"], ["15", "Saturday", "February 8", "7:05pm", "at Sacramento Surge", "W 10–6", "8–7", "Estadio Azteca Soccer Arena", "323"], ["4", "Sunday", "December 1", "1:05pm", "Ontario Fury", "W 18–4", "2–2", "UniSantos Park", "207"], ["10", "Sunday", "January 12", "1:05pm", "Las Vegas Legends", "W 10–7", "5–5", "UniSantos Park", "343"], ["11", "Sunday", "January 19", "1:05pm", "Bay Area Rosal", "W 17–7", "6–5", "UniSantos Park", "219"], ["16", "Saturday", "February 15♥", "5:05pm", "Bay Area Rosal", "W 27–2", "9–7", "UniSantos Park", "118"], ["3", "Saturday", "November 23", "7:05pm", "at Bay Area Rosal", "W 10–7", "1–2", "Cabernet Indoor Sports", "652"], ["13", "Saturday", "February 1", "7:05pm", "at San Diego Sockers", "L 5–6", "7–6", "Valley View Casino Center", "4,954"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many games did this team win during this season? | 9 | 128 | Answer: |
Table InputTable: [["Match no.", "Match Type", "Team Europe", "Score", "Team USA", "Progressive Total"], ["28", "Singles", "Tore Torgersen", "206 - 275", "Doug Kent", "15 - 13"], ["31", "Singles", "Tore Torgersen", "202 - 264", "Chris Barnes", "15 - 16"], ["32", "Singles", "Osku Palermaa", "196 - 235", "Tommy Jones", "15 - 17"], ["26", "Singles", "Osku Palermaa", "217 - 244", "Tommy Jones", "14 - 12"], ["25", "Singles", "Mika Koivuniemi", "217 - 279", "Chris Barnes", "14 - 11"], ["27", "Singles", "Paul Moor", "210 - 199", "Tim Mack", "15 - 12"], ["29", "Singles", "Tomas Leandersson", "176 - 258", "Bill Hoffman", "15 - 14"], ["30", "Baker", "Team Europe", "202 - 203", "Team USA", "15 - 15"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many singles matches was tore torgerson in during the evening session on day 3? | 2 | 128 | Answer: |
Table InputTable: [["Builder", "Works numbers", "Dates", "CN numbers", "GT numbers", "Notes"], ["ALCO", "49663-49674", "1911", "2616-2625\\n2677-2678", "766-777", "built at ALCO's Brooks Works"], ["MLW", "42331-42345\\n43150-43164", "1907", "2577-2605\\n2661-2662\\n2685", "721-750", ""], ["ALCO", "42046-42060\\n43540-43554", "1907", "2567-2576\\n2606-2615\\n2664-2665\\n2669-2676", "706-720\\n752\\n755\\n758\\n761\\n763", ""], ["ALCO", "50472-50481", "1911", "2626\\n2666-2668\\n2679-2684", "779-780\\n784\\n786-787", ""], ["MLW", "45163-45182", "1908", "2627-2646", "631-650", ""], ["MLW", "39548-39562\\n40583-40622", "1906", "2525-2566\\n2663", "651-705", ""], ["MLW", "46880-46894", "1910", "2647-2660\\n2686", "616-630", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:name a builder that had above 7 gt numbers. | ALCO | 128 | Answer: |
Table InputTable: [["Season", "Club", "Competition", "Games", "Goals"], ["2006/07", "KSV Roeselare", "Jupiler League", "29", "1"], ["2007/08", "KSV Roeselare", "Jupiler League", "25", "0"], ["2005/06", "KSV Roeselare", "Jupiler League", "26", "0"], ["2008/09", "Excelsior Mouscron", "Jupiler League", "31", "1"], ["2002/03", "RAEC Mons", "Jupiler League", "19", "0"], ["2009/10", "Excelsior Mouscron", "Jupiler League", "14", "1"], ["2003/04", "RAEC Mons", "Jupiler League", "23", "0"], ["2010/11", "Kortrijk", "Jupiler League", "0", "0"], ["2004/05", "KSV Roeselare", "Belgian Second Division", "29", "1"], ["2009/10", "Győri ETO FC", "Soproni Liga", "1", "0"], ["", "", "Totaal", "278", "4"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which competition had the same number of games as the jupiler league in the 2006/2007 season? | Belgian Second Division | 128 | Answer: |
Table InputTable: [["Band", "Disc/Song", "Released", "Disc Description", "Disk Size", "Image"], ["Men Without Hats", "I Got the Message", "1983", "", "", ""], ["Gary Numan", "Warriors", "1983", "Shaped like a Jet Fighter.", "7\"", ""], ["Men Without Hats", "The Safety Dance", "1982", "Oddly shaped picture disc of a man and a woman dancing", "", ""], ["Gary Numan", "Berserker", "1984", "Shaped like Numan's head.", "7\"", ""], ["The Enemy", "You're not alone", "2007", "Square shaped. Has the single cover art on the A-side and a black and white picture of the band on the B-side with track listing.", "7\"", ""], ["Guns N' Roses", "Paradise City", "1989", "Shape of a Colt \"Peacemaker\"", "7\"", ""], ["Barnes & Barnes", "Fish Heads: Barnes & Barnes' Greatest Hits", "1982", "Shaped as a fish head", "12\"", ""], ["Monster Magnet", "Dopes to Infinity", "1995", "Shaped like the lead singer Dave Wyndorf's head.", "12\"", ""], ["Red Box", "Lean On Me b/w Stinging Bee", "1985", "Hexagonal red vinyl. Looks like a red box in 2D; flipside is a band photo.", "7\"", ""], ["Joe Strummer", "Love Kills", "", "Shaped like a gun", "7\"", "A gun"], ["Guns N' Roses", "Nightrain", "1989", "Shape of a suitcase", "7\"", ""], ["The Coconuts (Side project of Kid Creole and the Coconuts)", "Did You Have To Love Me Like You Did", "1983", "In the shape of a coconut.", "7\"", ""], ["U2", "The Unforgettable Fire (single)", "1985", "Shaped as letter & number \"U2\" with various pictures of the band from the period.", "7\"", "U2"], ["Monster Magnet", "Negasonic Teenage Warhead", "", "Shaped like a mushroom cloud", "12\"", ""], ["Devo", "Beautiful World b/w Nu-Tra", "1981", "Shaped like an astronaut head", "", ""], ["Saxon", "Back on the Streets Again", "", "Shaped as an apple (as is printed on one side of the disk).", "7\"", ""], ["Guns N' Roses", "Sweet Child o' Mine", "1988", "Shape of the classic logo of the cross and skulls of the five band members", "7\"", ""], ["Kiss", "Lick It Up", "1983", "Shaped like an armored tank", "", ""], ["The Fat Boys", "Wipe Out", "", "Shaped like a Hamburger", "7\"", ""], ["Killing Joke", "Loose Cannon", "2003", "shaped yellow evil clown head image from the eponymous 2003 album sleeve", "", ""], ["Broken English", "Comin on Strong", "1987", "Shaped as the 3 band members wearing Ghostbusters outfits holding guitars.", "", ""], ["Gangrene", "Sawblade EP", "2010", "In the shape of a circular sawblade.", "", ""], ["OMD", "La Femme Accident", "1985", "", "", ""], ["The Mars Volta", "Mr. Muggs", "2008", "In the shape of a clear planchette.", "7\"", ""], ["Less Than Jake", "Cheese", "1998", "Shaped like a piece of swiss cheese. 1000 pressed in yellow. 500 pressed in green (\"Moldy Version\").", "7\"", ""], ["Yeah Yeah Yeahs", "Cheated Hearts", "2006", "Heart shaped.", "7\"", ""], ["Tangerine Dream", "Warsaw in the Sun", "1984", "The record is in the shape of Poland and has several images including Lech Wałęsa and Pope John Paul II.", "7\"", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what men without hats song/disc was released previous to gary numan's warriors? | The Safety Dance | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "1.", "2 October 2011", "Malaysian Open, Malaysia", "Hard (i)", "Marcos Baghdatis", "6–4, 7–5"], ["Runner-up", "4.", "18 June 2011", "Aegon International, United Kingdom", "Grass", "Andreas Seppi", "6–7(5–7), 6–3, 3–5 ret."], ["Winner", "2.", "23 October 2011", "Kremlin Cup, Russia", "Hard (i)", "Viktor Troicki", "6–4, 6–2"], ["Runner-up", "5.", "30 October 2011", "St. Petersburg Open, Russia", "Hard (i)", "Marin Čilić", "3–6, 6–3, 2–6"], ["Winner", "3.", "15 July 2012", "Stuttgart Open, Germany", "Clay", "Juan Mónaco", "6–4, 5–7, 6–3"], ["Runner-up", "3.", "27 February 2011", "International Tennis Championships, United States", "Hard", "Juan Martín del Potro", "4–6, 4–6"], ["Runner-up", "7.", "22 July 2012", "Swiss Open, Switzerland", "Clay", "Thomaz Bellucci", "7–6(8–6), 4–6, 2–6"], ["Runner-up", "6.", "8 January 2012", "Chennai Open, India", "Hard", "Milos Raonic", "7–6(7–4), 6–7(4–7), 6–7(4–7)"], ["Winner", "4.", "6 January 2013", "Chennai Open, India", "Hard", "Roberto Bautista-Agut", "3–6, 6–1, 6–3"], ["Runner-up", "1.", "25 October 2009", "Kremlin Cup, Russia", "Hard (i)", "Mikhail Youzhny", "7–6(7–5), 0–6, 4–6"], ["Runner-up", "2.", "19 June 2010", "UNICEF Open, Netherlands", "Grass", "Sergiy Stakhovsky", "3–6, 0–6"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many of these tournaments occurred after the year 2011? | 4 | 128 | Answer: |
Table InputTable: [["Represented", "Contestant", "Age", "Height", "Hometown"], ["Santo Domingo", "Yisney Lina Lagrange Méndez", "19", "1.82", "Pedro Brand"], ["Peravia", "Mariela Joselin Rosario Jiménez", "25", "1.86", "Santo Domingo"], ["La Romana", "Alina Charlin Espinal Luna", "19", "1.81", "La Romana"], ["Santiago", "Karina Luisa Betances Cabrera", "21", "1.80", "Santiago de los Caballeros"], ["Espaillat", "Angela María García Ruíz", "26", "1.77", "Moca"], ["Distrito Nacional", "Aimeé Elaine Melo Hernández", "23", "1.73", "Santo Domingo"], ["Azua", "Alicia Fernández de la Cruz", "23", "1.69", "Santo Domingo"], ["Com. Dom. EU", "Sandra Elisabeth Tavares Ruíz", "19", "1.80", "Newark"], ["San Cristóbal", "Daniela Teresa Peguero Brito", "24", "1.74", "Santo Domingo"], ["Monte Cristi", "Grace Stephany Mota Grisanty", "18", "1.75", "San Fernando de Monte Cristi"], ["Independencia", "Joany Marleny Sosa Peralta", "20", "1.82", "Jimaní"], ["Barahona", "Lucía Magdalena Alvarado Suarez", "20", "1.71", "Santo Domingo"], ["Salcedo", "Rossemely Cruz Logroño", "26", "1.76", "Salcedo"], ["Duarte", "Paola Saint-Hilaire Arias", "20", "1.79", "Santiago de los Caballeros"], ["Valverde", "Fania Miguelina Marte Lozada", "22", "1.73", "Mao"], ["La Vega", "Catherine Mabel Ramírez Rosario", "21", "1.83", "Santiago de los Caballeros"], ["La Altagracia", "Ana Carolina Viñas Machado", "22", "1.84", "Santiago de los Caballeros"], ["Puerto Plata", "Sheila Massiel Castíllo Domínguez", "18", "1.83", "Altamira"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 contestants are below 25 years of age? | 15 | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Championship", "Surface", "Opponent in the final", "Score in the final"], ["Runner-up", "8.", "December 18, 1995", "Grand Slam Cup, Munich, Germany", "Carpet", "Goran Ivanišević", "6–7(4–7), 3–6, 4–6"], ["Winner", "5.", "January 15, 1996", "Sydney, Australia", "Hard", "Goran Ivanišević", "5–7, 6–3, 6–4"], ["Runner-up", "10.", "August 22, 1996", "Stockholm, Sweden", "Hard (i)", "Thomas Enqvist", "5–7, 4–6, 6–7(0–7)"], ["Winner", "6.", "April 20, 1998", "Barcelona, Spain", "Clay", "Alberto Berasategui", "6–2, 1–6, 6–3, 6–2"], ["Runner-up", "11.", "April 12, 1999", "Estoril, Portugal", "Clay", "Albert Costa", "6–7(4–7), 6–2, 3–6"], ["Runner-up", "12.", "September 12, 1999", "US Open, New York City, USA", "Hard", "Andre Agassi", "4–6, 7–6(7–5), 7–6(7–2), 3–6, 2–6"], ["Runner-up", "5.", "January 31, 1994", "Australian Open, Melbourne, Australia", "Hard", "Pete Sampras", "6–7(4–7), 4–6, 4–6"], ["Winner", "8.", "January 18, 1999", "Sydney, Australia", "Hard", "Àlex Corretja", "6–3, 7–6(7–5)"], ["Winner", "4.", "February 20, 1995", "Memphis, Tennessee, USA", "Hard", "Paul Haarhuis", "7–6(7–2), 6–4"], ["Runner-up", "6.", "May 2, 1994", "Atlanta, Georgia, USA", "Clay", "Michael Chang", "7–6(7–4), 6–7(4–7), 0–6"], ["Winner", "7.", "November 16, 1998", "Stockholm, Sweden", "Hard", "Thomas Johansson", "6–3, 6–4, 6–4"], ["Runner-up", "3.", "August 2, 1993", "Montreal, Canada", "Hard", "Mikael Pernfors", "6–2, 2–6, 5–7"], ["Runner-up", "9.", "February 26, 1996", "Memphis, Tennessee, USA", "Hard (i)", "Pete Sampras", "4–6, 6–7(2–7)"], ["Runner-up", "4.", "October 18, 1993", "Tokyo, Japan", "Carpet", "Ivan Lendl", "4–6, 4–6"], ["Winner", "3.", "June 13, 1994", "London (Queen's Club), UK", "Grass", "Pete Sampras", "7–6(7–4), 7–6(7–4)"], ["Runner-up", "1.", "February 15, 1993", "Memphis, Tennessee, USA", "Hard (i)", "Jim Courier", "7–5, 6–7(4–7), 6–7(4–7)"], ["Runner-up", "7.", "May 9, 1994", "Pinehurst, USA", "Clay", "Jared Palmer", "4–6, 6–7(5–7)"], ["Winner", "2.", "February 14, 1994", "Memphis, Tennessee, USA", "Hard", "Brad Gilbert", "6–4, 7–5"], ["Runner-up", "2.", "July 26, 1993", "Washington D.C., USA", "Hard", "Amos Mansdorf", "6–7(3–7), 5–7"], ["Winner", "1.", "May 17, 1993", "Coral Springs, Florida, USA", "Clay", "David Wheaton", "6–3, 6–4"]] | 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 times did this player face goran ivanisevic in his career? | 2 | 128 | Answer: |
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2010/11", "Dnipro Dnipropetrovsk", "Ukraine", "1", "23", "0"], ["2007/08", "Dnipro Dnipropetrovsk", "Ukraine", "1", "24", "0"], ["2006/07", "Dnipro Dnipropetrovsk", "Ukraine", "1", "12", "0"], ["2009/10", "Dnipro Dnipropetrovsk", "Ukraine", "1", "28", "0"], ["2011/12", "Dnipro Dnipropetrovsk", "Ukraine", "1", "16", "0"], ["2008/09", "Dnipro Dnipropetrovsk", "Ukraine", "1", "22", "1"], ["2012/13", "Lokomotiv Moscow", "Russia", "1", "8", "0"], ["2012/13", "Dnipro Dnipropetrovsk", "Ukraine", "1", "10", "1"], ["2013/14", "Lokomotiv Moscow", "Russia", "1", "14", "1"], ["2005", "CSKA Moscow", "Russia", "1", "0", "0"], ["2004", "CSKA Moscow", "Russia", "1", "0", "0"], ["2006", "Spartak Nizhny Novgorod", "Russia", "2", "36", "1"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which country had the top number of apps? | Russia | 128 | Answer: |
Table InputTable: [["isn", "name", "arrival\\ndate", "departure\\ndate", "notes"], ["82", "Rasul Kudayev", "", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nAlso called \"Abdullah D. Kafkas\"."], ["209", "Almasm Rabilavich Sharipov", "2002-01-21", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nGranted asylum by the Netherlands."], ["203", "Ravil Shafeyavich Gumarov", "2002-01-21", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men.\\nAlleged to have played a role in a 2005 bombing.\\nDefense Intelligence Agency classifies him as a former detainee who \"returned to terrorism\"."], ["211", "Ruslan Anatoloivich Odijev", "2002-06-14", "2004-02-27", "Reported to have been repatriated on 24 February 2004, as \"Ruslan Anatolovich Odijev\", with six other Russian men.\\nCharged with a role in bombing a gas pipeline in 2005.\\nShot by police in 2007.\\nHuman Rights advocates argue he was falsely accused.\\nDefense Intelligence Agency classifies him as a former detainee who \"returned to terrorism\"."], ["674", "Timur Ravilich Ishmurat", "2002-06-14", "2004-02-27", "Repatriated to Russia.\\nReported to have been repatriated on 24 February 2004, as \"Timur Ravilich Ismurat\", with six other Russian men.\\nAlleged to have played a role in a 2005 bombing."], ["492", "Aiat Nasimovich Vahitov", "2002-06-14", "2004-02-27", "Repatriated to Russia on January 3, 2004.[citation needed]\\nReported to have been repatriated on 24 February 2004 with six other Russian men."], ["672", "Zakirjan Asam", "2002-06-08", "2006-11-17", "NLEC"], ["573", "Rustam Akhmyarov", "2002-05-01", "2004-02-27", "Reported to have been repatriated on 24 February 2004 with six other Russian men."], ["702", "Ravil Mingazov", "2002-10-28", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 not deported before 2006? | Ravil Mingazov | 128 | Answer: |
Table InputTable: [["Date", "Venue", "Opponents", "Score", "Competition"], ["20 March", "Fukuoka (A)", "Japan", "2–0", "Sanix Cup"], ["15 October", "Tashkent (N)", "Japan", "2–1", "AFC U-16 Championship (Semifinal)"], ["20 March", "Fukuoka (A)", "China PR", "1–0", "Sanix Cup"], ["18 October", "Tashkent (N)", "Iran", "1–2", "AFC U-16 Championship (Final)"], ["4 October", "Tashkent (N)", "India", "5–2", "AFC U-16 Championship (Group B)"], ["6 October", "Tashkent (N)", "Indonesia", "9–0", "AFC U-16 Championship (Group B)"], ["12 October", "Tashkent (A)", "Uzbekistan", "3–0", "AFC U-16 Championship (Quarterfinal)"], ["8 October", "Tashkent (N)", "Syria", "1–1", "AFC U-16 Championship (Group B)"], ["9 August", "Toyota (A)", "Japan", "2–2", "Toyota Cup"], ["10 August", "Toyota (N)", "United Arab Emirates", "6–0", "Toyota Cup"], ["8 August", "Toyota (N)", "Brazil", "0–0", "Toyota Cup"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of games played against japan? | 2 | 128 | Answer: |
Table InputTable: [["Position", "Driver", "No.", "Car", "Entrant", "Lak.", "Ora.", "San.", "Phi.", "Total"], ["14", "Brian Smith", "", "Alfa Romeo GTV Chevrolet", "", "-", "28", "-", "-", "28"], ["17", "Phil Crompton", "49", "Ford EA Falcon", "Phil Crompton", "17", "-", "-", "-", "17"], ["13", "Chris Fing", "", "Chevrolet Monza", "", "29", "-", "-", "-", "29"], ["4", "Mick Monterosso", "2", "Ford Escort RS2000", "Mick Monterosso", "-", "34", "36", "34", "104"], ["18", "Allan McCarthy", "", "Alfa Romeo Alfetta", "", "14", "-", "-", "-", "14"], ["11", "Kevin Clark", "116", "Ford Mustang GT", "Kevin Clark", "-", "-", "23", "23", "46"], ["2", "Kerry Baily", "18", "Toyota Supra Chevrolet", "Kerry Baily", "38", "38", "36", "38", "150"], ["1", "John Briggs", "9", "Honda Prelude Chevrolet", "John Briggs", "42", "42", "42", "42", "168"], ["9", "Ivan Mikac", "42", "Mazda RX-7", "Ivan Mikac", "-", "-", "25", "26", "51"], ["7", "Mike Imrie", "4", "Saab", "Imrie Motor Sport", "23", "11", "-", "28", "62"], ["15", "Gary Rowe", "47", "Nissan Stanza", "Gary Rowe", "-", "-", "21", "-", "21"], ["6", "Danny Osborne", "", "Mazda RX-7", "", "26", "10", "30", "-", "66'"], ["3", "James Phillip", "55", "Honda Prelude Chevrolet", "James Phillip", "26", "28", "28", "30", "112"], ["8", "Mark Trenoweth", "", "Jaguar", "", "33", "24", "-", "-", "57"], ["10", "Des Wall", "", "Toyota Supra", "", "15", "32", "-", "-", "47"], ["12", "Peter O'Brien", "17", "Holden VL Commodore", "O'Brien Aluminium", "-", "11", "29", "-", "40"], ["5", "Bob Jolly", "3", "Holden VS Commodore", "Bob Jolly", "-", "28", "16", "32", "76"], ["19", "Chris Donnelly", "", "", "", "12", "-", "-", "-", "12"], ["", "Paul Barrett", "", "", "", "-", "-", "-", "12", "12"], ["21", "Brett Francis", "", "", "", "11", "-", "-", "-", "11"], ["22", "Shane Eklund", "", "", "", "10", "-", "-", "-", "10"], ["", "Domenic Beninca", "", "", "", "-", "-", "-", "21", "21"], ["", "Ron O'Brien", "", "", "", "-", "-", "-", "10", "10"], ["", "Craig Wildridge", "", "", "", "-", "10", "-", "-", "10"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which driver got the most total points? | John Briggs | 128 | Answer: |
Table InputTable: [["Contestant", "Age", "Height", "Home City", "Rank"], ["Dzejlana \"Lana\" Baltić", "20", "179 cm (5 ft 10.5 in)", "Graz (originally from Bosnia)", "1st Eliminated in Episode 10"], ["Melisa Popanicić", "16", "175 cm (5 ft 9 in)", "Wörgl", "2nd Eliminated in Episode 10"], ["Christine Riener", "20", "181 cm (5 ft 11.25 in)", "Bludenz", "Eliminated in Episode 4"], ["Gina Zeneb Adamu", "17", "175 cm (5 ft 9 in)", "Bad Vöslau", "Runner-Up"], ["Nadine Trinker", "21", "183 cm (6 ft 0 in)", "Bodensdorf", "Eliminated in Episode 9"], ["Sabrina Angelika Rauch †", "21", "175 cm (5 ft 9 in)", "Graz", "Eliminated in Episode 2"], ["Bianca Ebelsberger", "24", "179 cm (5 ft 10.5 in)", "Aurach am Hongar", "Eliminated in Episode 9"], ["Isabelle Raisa", "16", "170 cm (5 ft 7 in)", "Vienna", "Eliminated in Episode 1"], ["Alina Chlebecek", "18", "170 cm (5 ft 7 in)", "Deutsch-Wagram", "Eliminated in Episode 1"], ["Katharina Mihalović", "23", "179 cm (5 ft 10.5 in)", "Vienna", "Eliminated in Episode 2"], ["Nataša Marić", "16", "175 cm (5 ft 9 in)", "Liefering (originally from Serbia)", "Eliminated in Episode 3"], ["Yemisi Rieger", "17", "177 cm (5 ft 9.5 in)", "Vienna", "Eliminated in Episode 7"], ["Antonia Maria Hausmair", "16", "175 cm (5 ft 9 in)", "Siegendorf", "Winner"], ["Izabela Pop Kostić", "20", "170 cm (5 ft 7 in)", "Vienna (originally from Bosnia)", "Eliminated in Episode 8"], ["Teodora-Mădălina Andreica", "17", "177 cm (5 ft 9.5 in)", "Romania", "Eliminated in Episode 6"], ["Michaela Schopf", "21", "172 cm (5 ft 7.5 in)", "Salzburg (originally from Germany)", "Quit in Episode 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 contestants were there? | 16 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Event", "Notes"], ["2002", "European Championships", "Munich, Germany", "8th", "4x400 m relay", "DQ"], ["2008", "Olympic Games", "Beijing, China", "6th", "400 m hurdles", "48.42"], ["2002", "European Championships", "Munich, Germany", "4th", "400 m", "45.40"], ["2004", "Olympic Games", "Athens, Greece", "6th", "400 m hurdles", "49.00"], ["2012", "European Championships", "Helsinki, Finland", "18th (sf)", "400 m hurdles", "50.77"], ["2003", "World Indoor Championships", "Birmingham, United Kingdom", "3rd", "4x400 m relay", "3:06.61"], ["2006", "European Championships", "Gothenburg, Sweden", "2nd", "400 m hurdles", "48.71"], ["2008", "Olympic Games", "Beijing, China", "7th", "4x400 m relay", "3:00.32"], ["2003", "World Indoor Championships", "Birmingham, United Kingdom", "7th (sf)", "400 m", "46.82"], ["2002", "European Indoor Championships", "Vienna, Austria", "1st", "4x400 m relay", "3:05.50 (CR)"], ["2002", "European Indoor Championships", "Vienna, Austria", "1st", "400 m", "45.39 (CR, NR)"], ["2007", "World Championships", "Osaka, Japan", "3rd", "400 m hurdles", "48.12 (NR)"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "1st", "400 m hurdles", "48.45"], ["2001", "World Championships", "Edmonton, Canada", "18th (sf)", "400 m hurdles", "49.80"], ["2001", "Universiade", "Beijing, China", "8th", "400 m hurdles", "49.68"], ["2004", "Olympic Games", "Athens, Greece", "10th (h)", "4x400 m relay", "3:03.69"], ["2007", "World Championships", "Osaka, Japan", "3rd", "4x400 m relay", "3:00.05"], ["1999", "European Junior Championships", "Riga, Latvia", "4th", "400 m hurdles", "52.17"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "1st", "4x400 m relay", "3:03.32"], ["2000", "World Junior Championships", "Santiago, Chile", "1st", "400 m hurdles", "49.23"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 competitions are listed? | 13 | 128 | Answer: |
Table InputTable: [["Year", "Film", "Role", "Language", "Notes"], ["2010", "Gaana Bajaana", "Radhey", "Kannada", ""], ["2013", "Dilwala", "Preethi", "Kannada", ""], ["2013", "Bahaddoor", "Anjali", "Kannada", "Filming"], ["2012", "Alemari", "Neeli", "Kannada", ""], ["2012", "Drama", "Nandini", "Kannada", ""], ["2012", "18th Cross", "Punya", "Kannada", ""], ["2012", "Sagar", "Kajal", "Kannada", ""], ["2012", "Breaking News", "Shraddha", "Kannada", ""], ["2012", "Addhuri", "Poorna", "Kannada", "Udaya Award for Best Actress\\nNominated — SIIMA Award for Best Actress\\nNominated — Filmfare Award for Best Actress – Kannada"], ["2013", "Kaddipudi", "Uma", "Kannada", ""], ["2010", "Krishnan Love Story", "Geetha", "Kannada", "Filmfare Award for Best Actress - Kannada\\nUdaya Award for Best Actress"], ["2011", "Hudugaru", "Gayithri", "Kannada", "Nominated, Filmfare Award for Best Actress – Kannada"], ["2008", "Moggina Manasu", "Chanchala", "Kannada", "Filmfare Award for Best Actress - Kannada\\nKarnataka State Film Award for Best Actress"], ["2009", "Love Guru", "Kushi", "Kannada", "Filmfare Award for Best Actress - Kannada"], ["2009", "Olave Jeevana Lekkachaara", "Rukmini", "Kannada", "Innovative Film Award for Best Actress"], ["2014", "Endendigu", "", "", "Filming"], ["2014", "Mr. & Mrs. Ramachari", "", "", "Announced"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 most number of films that radhika pandit has been in during one year? | 6 | 128 | Answer: |
Table InputTable: [["#", "Stadium", "Capacity", "City", "Region", "Home Team", "Opened"], ["16", "Grand Stade du Havre", "25,178", "Le Havre", "Upper Normandy", "Le Havre AC", "2012"], ["14", "Stade de la Meinau", "29,230", "Strasbourg", "Alsace", "RC Strasbourg", "1914"], ["22", "Stade Michel d'Ornano", "21,500", "Caen", "Lower Normandy", "Stade Malherbe Caen", "1993"], ["9", "Allianz Riviera", "35,624", "Nice", "Provence-Alpes-Côte d'Azur", "OGC Nice", "2013"], ["1", "Stade de France", "81,338", "Paris", "Île-de-France", "France national football team", "1998"], ["8", "Stade Geoffroy-Guichard", "37,587", "Saint-Étienne", "Rhône-Alpes", "AS Saint-Étienne", "1931"], ["12", "Stade de la Mosson", "32,939", "Montpellier", "Languedoc-Roussillon", "Montpellier HSC", "1972"], ["3", "Grand Stade Lille Métropole", "50,186", "Villeneuve-d'Ascq", "Nord-Pas-de-Calais", "Lille OSC", "2012"], ["13", "Stade de la Route de Lorient", "31,127", "Rennes", "Brittany", "Stade Rennais FC", "1912"], ["21", "Stade Auguste-Delaune", "21,684", "Reims", "Champagne-Ardenne", "Stade Reims", "1935"], ["6", "Stade Gerland", "41,044", "Lyon", "Rhône-Alpes", "Olympique Lyonnais", "1926"], ["17", "MMArena", "25,000", "Le Mans", "Pays de la Loire", "Le Mans UC", "2011"], ["2", "Stade Vélodrome", "60,013", "Marseille", "Provence-Alpes-Côte d'Azur", "Olympique de Marseille", "1937"], ["4", "Parc des Princes", "48,712", "Paris", "Île-de-France", "Paris Saint-Germain FC", "1897"], ["7", "Stade de la Beaujoire", "38,285", "Nantes", "Pays de la Loire", "FC Nantes Atlantique", "1984"], ["25", "Stade des Alpes", "20,068", "Grenoble", "Rhône-Alpes", "Grenoble Foot 38", "2008"], ["10", "Stadium Municipal", "35,575", "Toulouse", "Midi-Pyrénées", "Toulouse FC", "1937"], ["15", "Stade Municipal Saint-Symphorien", "26,700", "Metz", "Lorraine", "FC Metz", "1923"], ["5", "Stade Félix Bollaert", "41,233", "Lens", "Nord-Pas-de-Calais", "RC Lens", "1932"], ["27", "Stade Sébastien Charléty", "20,000", "Paris", "Île-de-France", "Paris FC", "1938"], ["26", "Stade Auguste Bonal", "20,025", "Montbéliard", "Franche-Comté", "FC Sochaux-Montbéliard", "2000"], ["11", "Stade Chaban-Delmas", "34,462", "Bordeaux", "Aquitaine", "FC Girondins de Bordeaux", "1938"], ["23", "Stade de l'Aube", "20,400", "Troyes", "Champagne-Ardenne", "Troyes AC", "1956"], ["18", "Stade du Hainaut", "24,926", "Valenciennes", "Nord-Pas-de-Calais", "Valenciennes FC", "2011"], ["24", "Stade Marcel Picot", "20,087", "Tomblaine", "Lorraine", "AS Nancy", "1926"], ["19", "Stade de l'Abbé-Deschamps", "23,467", "Auxerre", "Bourgogne", "AJ Auxerre", "1918"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 region listed before brittany? | Languedoc-Roussillon | 128 | Answer: |
Table InputTable: [["Season", "Series", "Team", "Races", "Wins", "Poles", "F/Laps", "Podiums", "Points", "Position"], ["2009", "Asian Formula Renault Challenge", "Asia Racing Team", "12", "6", "2", "4", "7", "287", "2nd"], ["2007", "Asian Formula Renault Challenge", "Champ Motorsports", "12", "0", "0", "0", "1", "64", "14th"], ["2008", "Asian Formula Renault Challenge", "Champ Motorsports", "13", "0", "0", "0", "3", "193", "4th"], ["2011", "Formula Pilota China", "Asia Racing Team", "12", "2", "0", "0", "3", "124", "2nd"], ["2009", "Formula Renault 2.0 Northern European Cup", "Krenek Motorsport", "14", "0", "0", "0", "0", "44", "21st"], ["2012", "British Formula 3 Championship", "Angola Racing Team", "5", "0", "0", "0", "0", "—", "—"], ["2012", "Formula 3 Euro Series", "Angola Racing Team", "21", "0", "0", "0", "0", "14", "14th"], ["2012", "Masters of Formula 3", "Angola Racing Team", "1", "0", "0", "0", "0", "—", "18th"], ["2010", "Austria Formula 3 Cup", "Sonangol Motopark", "4", "1", "2", "3", "2", "35", "9th"], ["2012", "59th Macau Grand Prix Formula 3", "Angola Racing Team", "2", "0", "0", "0", "0", "—", "23rd"], ["2013", "GP3 Series", "Carlin", "16", "0", "0", "0", "0", "0", "23rd"], ["2010", "ATS Formel 3 Cup", "China Sonangol", "5", "0", "0", "0", "0", "0", "19th"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what's the total number of points of all series but without the asian formula renault challenges? | 217 | 128 | Answer: |
Table InputTable: [["Stations", "Connections", "City/ Neighborhood", "Parking", "Date Opened"], ["Woodman", "Metro Local:154, 158", "Valley Glen", "None", "October 29, 2005"], ["Woodley", "Metro Local:164, 237", "Van Nuys", "None", "October 29, 2005"], ["Warner Center", "Metro Local: 150, 161, 164, 245, 645\\nMetro Rapid: 750\\nLADOT Commuter Express: 422\\nCity of Santa Clarita Transit: 791, 796\\nVentura Intercity Service Transit Authority: Conejo Connection", "Woodland Hills", "n/a", "October 29, 2005"], ["Tampa", "Metro Local: 242", "Tarzana", "n/a", "October 29, 2005"], ["Balboa", "Metro Local: 164, 236, 237\\nLADOT Commuter Express: 573, 574", "Lake Balboa", "270 Spaces", "October 29, 2005"], ["Reseda", "Metro Rapid: 741\\nMetro Local: 240", "Tarzana", "522 Spaces", "October 29, 2005"], ["Nordhoff", "Metro Local: 166, 364\\nLADOT DASH Northridge", "Chatsworth", "n/a", "June 30, 2012"], ["North Hollywood", "Metro Red Line \\nMetro Local: 152, 154, 156, 162, 183, 224, 353, 656\\nLADOT Commuter Express: 549\\nCity of Santa Clarita Transit: 757", "North Hollywood", "951 Spaces", "October 29, 2005"], ["Chatsworth", "Metro Local: 158, 166, 167, 244, 245, 364\\nLADOT Commuter Express: 419\\nSimi Valley Transit: C\\nSanta Clarita Transit: 791\\nMetrolink Ventura County Line\\nAmtrak Pacific Surfliner", "Chatsworth", "Parking Expanded", "June 30, 2012"], ["Valley College", "Metro Local: 156, 167, 656\\nLADOT Commuter Express: 549\\nLADOT DASH: Van Nuys/Studio City", "Valley Glen", "None", "October 29, 2005"], ["Sepulveda", "Metro Local: 234\\nMetro Rapid: 734", "Van Nuys", "1,205 Spaces", "October 29, 2005"], ["Van Nuys", "Metro Local:154, 156, 233, 237, 656\\nMetro Rapid: 761\\nLADOT DASH: Van Nuys/Studio City\\nCity of Santa Clarita Transit: 793, 798", "Van Nuys", "776 Spaces", "October 29, 2005"], ["Pierce College", "Metro Local: 164, 243", "Winnetka", "373 Spaces", "October 29, 2005"], ["De Soto", "Metro Local: 164, 244\\nCity of Santa Clarita Transit: 796", "Winnetka", "n/a", "October 29, 2005"], ["Canoga", "Metro Local:164, 165\\nCity of Santa Clarita Transit: 796", "Canoga Park", "612 Spaces", "December 27, 2006"], ["Sherman Way", "Metro Local: 162, 163", "Canoga Park", "Park & Ride Lot", "June 30, 2012"], ["Laurel Canyon", "Metro Local: 156, 230, 656", "Valley Village", "None", "October 29, 2005"], ["Roscoe", "Metro Local: 152, 353", "Canoga Park", "n/a", "June 30, 2012"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the next station after woodman? | Van Nuys | 128 | Answer: |
Table InputTable: [["Season", "Episodes", "Time slot (EST)", "Original airing\\nSeason premiere", "Original airing\\nSeason finale", "Original airing\\nTV season", "Rank", "Viewers\\n(in millions)"], ["13", "22", "Wednesday 10pm/9c", "September 26, 2012", "May 15, 2013", "2012–2013", "#25", "11.63"], ["3", "23", "Thursday 9pm/8c", "September 26, 2002", "May 15, 2003", "2002–2003", "#1", "26.20"], ["4", "23", "Thursday 9pm/8c", "September 25, 2003", "May 20, 2004", "2003–2004", "#2", "25.27"], ["8", "17", "Thursday 9pm/8c", "September 27, 2007", "May 15, 2008", "2007–2008", "#9", "16.62"], ["5", "25", "Thursday 9pm/8c", "September 23, 2004", "May 19, 2005", "2004–2005", "#2", "26.26"], ["9", "24", "Thursday 9pm/8c", "October 9, 2008", "May 14, 2009", "2008–2009", "#4", "18.52"], ["11", "22", "Thursday 9pm/8c", "September 23, 2010", "May 12, 2011", "2010–2011", "#12", "13.52"], ["12", "22", "Wednesday 10pm/9c", "September 21, 2011", "May 9, 2012", "2011–2012", "#21", "12.49"], ["6", "24", "Thursday 9pm/8c", "September 22, 2005", "May 18, 2006", "2005–2006", "#3", "24.86"], ["7", "24", "Thursday 9pm/8c", "September 21, 2006", "May 17, 2007", "2006–2007", "#4", "20.34"], ["10", "23", "Thursday 9pm/8c", "September 24, 2009", "May 20, 2010", "2009–2010", "#12", "14.92"], ["1", "23", "Friday 9pm/8c (October 6, 2000 – January 12, 2001)\\nThursday 9pm/8c (February 1, 2001 – May 17, 2001)", "October 6, 2000", "May 17, 2001", "2000–2001", "#10", "17.80"], ["2", "23", "Thursday 9pm/8c", "September 27, 2001", "May 16, 2002", "2001–2002", "#2", "23.69"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 of csi: crime scene investigation had at least 15 million viewers? | 9 | 128 | Answer: |
Table InputTable: [["Round", "Pick", "Player", "Position", "Nationality", "School/Club Team"], ["7", "153", "Allan Zahn", "", "United States", "Arkansas"], ["10", "209", "Steve Schall", "", "United States", "Arkansas"], ["3", "61", "Rich Yonakor", "", "United States", "North Carolina"], ["6", "129", "Dean Uthoff", "", "United States", "Iowa State"], ["4", "83", "Calvin Roberts", "", "United States", "California State-Fullerton"], ["8", "172", "Bill Bailey", "", "United States", "Texas Pan-American"], ["9", "192", "Al Williams", "", "United States", "North Texas State"], ["3", "60", "Lavon Mercer", "", "United States", "Georgia"], ["2", "39", "Michael Miley", "", "United States", "California State-Long Beach"], ["1", "15", "Reggie Johnson", "PF/C", "United States", "Tennessee"], ["5", "107", "Gib Hinz", "", "United States", "Wisconsin-Eau Claire"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:allan zahn and steve schall are each from which school? | Arkansas | 128 | Answer: |
Table InputTable: [["Pick #", "Player", "Position", "Nationality", "NHL team", "College/junior/club team"], ["152", "Sergei Starikov", "Defense", "Soviet Union", "New Jersey Devils", "CSKA Moscow (USSR)"], ["153", "Milan Tichy", "Defense", "Czechoslovakia", "Chicago Blackhawks", "Prince Albert Raiders (WHL)"], ["163", "David Shute", "Left Wing", "United States", "Pittsburgh Penguins", "Victoria Cougars (WHL)"], ["155", "Rob Sangster", "Left Wing", "Canada", "Vancouver Canucks", "Kitchener Rangers (OHL)"], ["167", "Patrick Lebeau", "Left Wing", "Canada", "Montreal Canadiens", "St-Jean Lynx (QMJHL)"], ["168", "Kevin Wortman", "Defense", "United States", "Calgary Flames", "American International College (NCAA)"], ["164", "Rick Allain", "Defense", "Canada", "Boston Bruins", "Kitchener Rangers (OHL)"], ["166", "Dean Holoien", "Right Wing", "Canada", "Washington Capitals", "Saskatoon Blades (WHL)"], ["158", "Andy Suhy", "Defense", "United States", "Detroit Red Wings", "Western Michigan University (NCAA)"], ["148", "Paul Krake", "Goalie", "Canada", "Quebec Nordiques", "University of Alaska Anchorage (NCAA)"], ["149", "Phil Huber", "Center", "Canada", "New York Islanders", "Kamloops Blazers (WHL)"], ["157", "Raymond Saumier", "Right Wing", "Canada", "Hartford Whalers", "Trois Rivieres Draveurs (QMJHL)"], ["160", "Greg Spenrath", "Defense", "Canada", "New York Rangers", "Tri-City Americans (WHL)"], ["159", "Sverre Sears", "Defense", "United States", "Philadelphia Flyers", "Princeton University (NCAA)"], ["165", "Sean Whyte", "Right Wing", "Canada", "Los Angeles Kings", "Guelph Platers (OHL)"], ["162", "Darcy Martini", "Defense", "Canada", "Edmonton Oilers", "Michigan Technological University (NCAA)"], ["151", "Jim Solly", "Left Wing", "Canada", "Winnipeg Jets", "Bowling Green State University (NCAA)"], ["150", "Derek Langille", "Defense", "Canada", "Toronto Maple Leafs", "North Bay Centennials (OHL)"], ["161", "Derek Plante", "Center", "United States", "Buffalo Sabres", "Cloquet High School (USHS-MN)"], ["156", "Kevin Plager", "Right Wing", "United States", "St. Louis Blues", "Parkway North High School (USHS-MO)"], ["154", "Jon Pratt", "Left Wing", "United States", "Minnesota North Stars", "Pingree High School (USHS-MA)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what are the number of players with a soviet union nationality? | 1 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["3", "Yugoslavia", "3", "2", "1", "6"], ["8", "Tunisia", "0", "1", "0", "1"], ["2", "Greece", "6", "7", "6", "19"], ["5", "Morocco", "1", "1", "0", "2"], ["7", "Egypt", "0", "1", "7", "8"], ["1", "France", "11", "5", "3", "19"], ["5", "Turkey", "1", "1", "0", "2"], ["4", "Spain", "1", "5", "5", "11"], ["Totaal", "Totaal", "23", "23", "22", "68"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which countries did not win any bronze medals? | Morocco, Turkey, Tunisia | 128 | Answer: |
Table InputTable: [["Site", "Municipality", "Comments", "Coordinates", "Type", "Ref."], ["*Itsukushima\\n厳島\\nItsukushima", "Hatsukaichi", "also a Special Historic Site; Itsukushima Jinja is inscribed on the UNESCO World Heritage List", "34°16′16″N 132°18′22″E / 34.27116774°N 132.30612348°E", "8", "[3]"], ["Kikkawa Motoharu Fortified Residence Gardens\\n吉川元春館跡庭園\\nKikkawa Motoharu yakata ato teien", "Kitahiroshima", "", "34°43′01″N 132°27′58″E / 34.71697004°N 132.46599393°E", "1", "[1]"], ["Peace Memorial Park\\n平和記念公園\\nHeiwa kinen kōen", "Hiroshima", "the Hiroshima Peace Memorial (Genbaku Dome) is inscribed on the UNESCO World Heritage List", "34°23′34″N 132°27′09″E / 34.39284707°N 132.45251203°E", "1", "[8]"], ["Jōdo-ji Gardens\\n浄土寺庭園\\nJōdoji teien", "Onomichi", "", "34°24′44″N 133°12′36″E / 34.41222952°N 133.21012266°E", "1", "[6]"], ["*Sandan-kyō\\n三段峡\\nSandan-kyō", "Akiōta/Kitahiroshima", "", "34°36′57″N 132°11′44″E / 34.61573328°N 132.19561853°E", "3, 5, 6", "[4]"], ["Shukkei-en\\n縮景園\\nShukukei-en", "Hiroshima", "", "34°24′02″N 132°28′04″E / 34.40050182°N 132.46770735°E", "1", "[5]"], ["Former Mantoku-in Gardens\\n旧万徳院庭園\\nkyū-Mantokuin teien", "Kitahiroshima", "", "34°43′27″N 132°28′22″E / 34.72423174°N 132.47265069°E", "1", "[2]"], ["Tomo Park\\n鞆公園\\nTomo kōen", "Fukuyama", "", "34°23′01″N 133°23′48″E / 34.3835209°N 133.39662133°E", "1, 8", "[9]"], ["Taishaku-kyō\\n帝釈川の谷 (帝釈峡)\\nTaishaku-gawa no tani (Taishaku-kyō)", "Shōbara/Jinsekikōgen", "", "34°50′58″N 133°13′23″E / 34.8493628°N 133.2231609°E", "5, 6", "[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:give the number of sites listed in the table? | 9 | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["1", "China (CHN)", "14", "14", "13", "41"], ["2", "India (IND)", "7", "6", "4", "17"], ["9", "Qatar (QAT)", "1", "4", "3", "8"], ["8", "Sri Lanka (SRI)", "2", "0", "2", "4"], ["5", "South Korea (KOR)", "3", "2", "1", "6"], ["6", "Japan (JPN)", "2", "13", "8", "23"], ["14", "Uzbekistan (UZB)", "0", "1", "3", "4"], ["11", "Kyrgyzstan (KGZ)", "1", "1", "0", "2"], ["10", "Thailand (THA)", "1", "1", "2", "4"], ["4", "Kazakhstan (KAZ)", "3", "4", "5", "12"], ["15", "Iran (IRI)", "0", "1", "0", "1"], ["7", "Bahrain (BRN)", "2", "1", "1", "4"], ["12", "Kuwait (KUW)", "1", "0", "0", "1"], ["3", "Saudi Arabia (KSA)", "7", "1", "0", "8"], ["12", "North Korea (PRK)", "1", "0", "0", "1"], ["Total", "Total", "45", "49", "42", "136"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 gold metals did china have than india | 7 | 128 | Answer: |
Table InputTable: [["Year", "Competition", "Venue", "Position", "Notes"], ["1999", "World Youth Championships", "Bydgoszcz, Poland", "13th (q)", "4.60 m"], ["2003", "European U23 Championships", "Bydgoszcz, Poland", "13th (q)", "5.20 m"], ["2012", "European Championships", "Helsinki, Finland", "–", "NM"], ["2006", "World Indoor Championships", "Moscow, Russia", "10th (q)", "5.65 m"], ["2005", "European U23 Championships", "Erfurt, Germany", "7th", "5.50 m"], ["2005", "Universiade", "Izmir, Turkey", "5th", "5.50 m"], ["2001", "European Junior Championships", "Grosseto, Italy", "7th", "5.15 m"], ["2006", "European Championships", "Gothenburg, Sweden", "5th", "5.65 m"], ["2008", "Olympic Games", "Beijing, China", "11th", "5.45 m"], ["2010", "European Championships", "Barcelona, Spain", "3rd", "5.75 m"], ["2007", "European Indoor Championships", "Birmingham, United Kingdom", "16th (q)", "5.40 m"], ["2002", "World Junior Championships", "Kingston, Jamaica", "8th", "5.30 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:how many times has przemysław czerwiński placed in the top ten? | 7 | 128 | Answer: |
Table InputTable: [["Aircraft", "Origin", "Type", "In service", "Notes"], ["Cessna 404 Titan", "USA", "Light transport", "0", "1 in service with the Air Wing from 1991 to 2008"], ["Cessna 208 Caravan", "USA", "Light transport", "1", "in service since 2007"], ["Cessna 421C Golden Eagle", "USA", "Light transport", "0", "1 in service with the Air Wing from 1988 to 2002"], ["Beechcraft Super King Air 350", "USA", "Light transport", "1", "in service since 2004"], ["Aero Commander 500", "USA", "Light utility transport", "0", "3 in service with the Air Wing from 1976 to 1990"], ["Partenvia P.68 Observer", "Italy", "Light transport aircraft", "1", "in service since 2009"], ["Piper PA-31 Navajo", "USA", "Light transport", "0", "in service since 1993"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the last aircraft in service? | Partenvia P.68 Observer | 128 | Answer: |
Table InputTable: [["Eps #", "Prod #", "Title", "Summary", "Air Date"], ["6", "9", "Prisoners Of Planet X", "A UFO has been sighted. The pilot abducts the Fantastic Four from the Science Center and is setting course for Planet X. There, their dictator Kurrgo requests the Fantastic Four save their planet from another planet knocked off its orbit. Reed manages to formulate a working plan to save the population. While the plan is in process, Kurrgo has other ideas. However, Reed tricks Kurrgo and leaves him on the exploding planet while the micro-sized population and the Fantastic Four get away to safety.", "10/14/1967"], ["13", "19", "Rama-Tut", "After coming back from vacation Reed tells Ben an interesting theory on attempting to restore him. They head to Dr. Doom’s deserted castle to use the time machine the doctor left behind. In 2000 B.C the four weaken during a fight and are taken by Pharaoh Rama-Tut, who is a lot more than he would seem at first sight. Susan is to be Rama-Tut’s queen while the other three are put to work with some mind control. Ben turns back to his former self. As he rescues Susan, he is once again the Thing. The four battle Rama-Tut to his sphinx. Finally, they destroy his sphinx and return to their own time.", "12/9/1967"], ["12", "13", "Return Of the Mole Man", "The Mole Man is creating earthquakes and causing buildings to sink deep into the Earth. In addition, he and his Moloids kidnap Susan. The Mole Man as usual has been expecting the other three and sends them back to the surface to tell the Army not to get involved. They manage to halt them and seek an alternate entrance in the underworld. Johnny rescues Susan, then they penetrate the laboratory. They all return the buildings to the surface and escape the exploding caves.", "11/25/1967"], ["18", "18", "The Terrible Tribunal", "The Fantastic Four are taken to another planet where they are regarded as criminals against evil, charged by three old enemies. Reed is forced to recall his memories on Klaw, Molecule, Man and Blastaar’s defeat. Meanwhile the other three escape and they rescue Reed just as the verdict is given. At the surface, they have to battle the court judge before they are able to leave the planet for Earth.", "9/14/1968"], ["9", "8", "Behold A Distant Star", "The Fantastic Four are testing their rocket when they are drawn into the Skrull Galaxy. After beating the first round of Skrulls, the Fantastic Four weaken and are taken prisoner. The cruel Skrull Warlord Morrat wishes to overthrow the Skrull Emperor. The Warlord gives the Fantastic Four the option to assist them or die. Reed tricks the Warlord into getting him and his friends' powers fully charged. They defeat the Warlord as the Emperor arrives and he allows the Fantastic 4 to go freely back to Earth.", "11/4/1967"], ["7", "14", "It Started On Yancy Street", "The Fantastic Four face a bunch of old rivals in Yancy Street, but their old enemy Red Ghost and his primates show up and capture them. During their voyage to the moon, the four turn the tables, but Red Ghost gets away and the four are dumped on the moon. They barely manage to get to a source of oxygen which is the Watcher’s laboratory. Using one of the Watcher’s machines, Reed brings down Red Ghost’s ship. Susan gets Dr. Kragoff banished into a trans-nitron machine. Reed uses that machine to get back to Earth.", "10/21/1967"], ["15", "16", "The Micro World Of Dr. Doom", "The Fantastic Four have been shrunken to small size. Dr. Doom is after them and takes them to the Micro World. Dr. Doom briefs them on his micro genius experiments involving a king and a princess from the micro world. The four battle the giant guards but Dr. Doom catches them and imprisons them with the King and Princess. They all escape and enlarge themselves. Ben puts a stop to the Lizard Men, then the four return to their own world.", "12/30/1967"], ["10", "12", "Demon in the Deep", "The Fantastic Four beat the criminal forces working for Dr. Gamma, and blow up the island with its secret weapons. While escaping, Dr. Gamma is infected by the radiation levels in the seabed and morphs into some creature. Johnny is flustered with being moved around and quits from the Fantastic Four. In the town Johnny goes to, there have been sightings of the Gamma Ray. Johnny defeats the Gamma Ray by himself, but he comes back with the hideous giant sea monster Giganto. Johnny rejoins the Fantastic Four. Ben succeeds in eliminating the sea monster. The Gamma Ray is defeated but not finished.", "11/11/1967"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 title of the last episode in 1968? | The Deadly Director | 128 | Answer: |
Table InputTable: [["Name", "Owner", "Location", "Notes", "Transmission", "Website"], ["Radio Capital", "Elemedia", "Cusano Milanino", "Commercial; Classic hits", "FM, DAB, DVB-T, DVB-S", "http://www.capital.it"], ["Radio DeeJay", "Elemedia", "Milan", "Commercial;", "FM, DAB, DAB+, DVB-T, DVB-S", "http://www.deejay.it"], ["m2o", "Elemedia", "Rome", "Commercial; Electronic dance music", "FM, DAB, DAB+, DVB-T, DVB-S", "http://www.m2o.it"], ["Radio Maria", "Associazione Radio Maria", "Erba, (CO)", "Community; Catholic", "FM, DAB, DVB-S", "http://www.radiomaria.it"], ["Multiradio", "Multiradio srl", "Massafra, (TA)", "Local; Adult Contemporary", "FM", "http://www.multiradio.it"], ["Radio Pianeta", "", "Cividate al piano. (BG)", "Local; News/Talk", "FM", "http://www.radiopianeta.it"], ["Radio Popolare", "cooperative", "Rome", "Community; News/Talk", "FM", "http://www.radiopopolare.it"], ["Radio Padania Libera", "Lega Nord", "Varese", "Community; News/Talk", "DAB, DVB-S", "http://www.radiopadania.info"], ["Radio 24", "Il Sole 24 Ore", "Milan", "Commercial; News/Talk", "FM, DAB, DVB-S", "http://www.radio24.it"], ["Radio 105 Network", "Gruppo Finelco", "Milan", "Commercial; Rock, Pop, Hip Hop", "FM, DVB-S", "http://www.105.net"], ["Radio Radicale", "Radical Party", "Rome", "Community; News/Talk", "FM, DAB, DVB-S", "http://www.radioradicale.it"], ["Rai Radio 1", "RAI", "Rome", "Public; News/Talk; Generalist", "FM, MW, DAB, DVB-T, DVB-S", "http://www.radio1.rai.it"], ["Radio Bruno", "Radio Bruno", "Carpi (MO)", "Local; Pop, Contemporary", "FM, streaming online, Dvb-T", "http://www.radiobruno.it"], ["Virgin Radio Italia", "Gruppo Finelco", "Milan", "Commercial; Rock", "FM, DAB, DAB+, DVB-S", "http://www.virginradioitaly.it"], ["Radio Dimensione Suono", "", "Rome", "Commercial; It is also called RDS", "FM, DAB, DAB+, DVB-S", "http://www.rds.it"], ["Rai Isoradio", "RAI", "", "Public; Traffic and weather news", "FM, DAB, DVB-S", "http://www.isoradio.rai.it"], ["Radio Monte Carlo", "Gruppo Finelco", "Milan", "Commercial; It is also called RMC", "FM, DVB-S", "http://www.radiomontecarlo.net"], ["Radio Italia Solo Musica Italiana", "Gruppo Radio Italia", "Milan", "Commercial; Italian Hits", "FM, DAB, DVB-S", "http://www.radioitalia.it"], ["Rai Radio 3", "RAI", "Rome", "Public; Culture; Classical music", "FM, DAB, DVB-T, DVB-S", "http://www.radio3.rai.it"], ["R101", "Monradio", "Milan", "Commercial; Classic hits", "FM, DAB, DAB+, DVB-S", "http://www.r101.it"], ["Rai Radio 2", "RAI", "Rome", "Public; Popular music; Entertainment", "FM, DAB, DVB-T, DVB-S", "http://www.radio2.rai.it"], ["RadioRadio", "", "Rome", "Local; News/Talk", "DAB, DVB-S", "http://www.radioradio.it"], ["Rai GR Parlamento", "RAI", "Rome", "Public; News/Talk", "FM, DVB-S", "http://www.grparlamento.rai.it"], ["Rai FD4 Leggera", "RAI", "Rome", "Public; Easy listening music", "DAB, Cable, DVB-T, DVB-S", "http://www.radio.rai.it/radiofd4"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 radio stations does elemedia own? | 3 | 128 | Answer: |
Table InputTable: [["Team", "City", "Years active", "Seasons played", "Win–loss record", "Win%", "Playoffs appearances"], ["Denver Nuggets", "Denver, Colorado", "1949–1950", "1", "11–51", ".177", "0"], ["Pittsburgh Ironmen", "Pittsburgh, Pennsylvania", "1946–1947", "1", "15–45", ".250", "0"], ["Indianapolis Olympians", "Indianapolis, Indiana", "1949–1953", "4", "132–137", ".491", "4"], ["Indianapolis Jets", "Indianapolis, Indiana", "1948–1949", "1", "18–42", ".300", "0"], ["Detroit Falcons", "Detroit, Michigan", "1946–1947", "1", "20–40", ".333", "0"], ["Toronto Huskies", "Toronto, Ontario", "1946–1947", "1", "22–38", ".367", "0"], ["Baltimore Bullets*", "Baltimore, Maryland", "1947–1954", "8", "158–292", ".351", "3"], ["Anderson Packers", "Anderson, Indiana", "1949–1950", "1", "37–27", ".578", "1"], ["Cleveland Rebels", "Cleveland, Ohio", "1946–1947", "1", "30–30", ".500", "1"], ["Chicago Stags", "Chicago, Illinois", "1946–1950", "4", "145–92", ".612", "4"], ["Waterloo Hawks", "Waterloo, Iowa", "1949–1950", "1", "19–43", ".306", "0"], ["St. Louis Bombers", "St. Louis, Missouri", "1946–1950", "4", "122–115", ".515", "3"], ["BAA Indianapolis", "Indianapolis, Indiana", "Never Played", "0", "0–0", "N/A", "0"], ["Providence Steamrollers", "Providence, Rhode Island", "1946–1949", "3", "46–122", ".274", "0"], ["BAA Buffalo", "Buffalo, New York", "Never Played", "0", "0–0", "N/A", "0"], ["Sheboygan Red Skins", "Sheboygan, Wisconsin", "1949–1950", "1", "22–40", ".355", "1"], ["Washington Capitols", "Washington, D.C.", "1946–1951", "5", "157–114", ".579", "4"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which defunct nba team had the highest win percentage? | Chicago Stags | 128 | Answer: |
Table InputTable: [["Rank", "Athlete", "Nationality", "2.15", "2.20", "2.24", "2.27", "Result", "Notes"], ["16.", "Adam Shunk", "United States", "o", "xxx", "", "2.15", "", ""], ["10.", "Tora Harris", "United States", "o", "o", "xo", "xxx", "2.24", ""], ["1.", "Yaroslav Rybakov", "Russia", "o", "o", "o", "o", "2.27", "q"], ["16.", "Roman Fricke", "Germany", "o", "xxx", "", "2.15", "", ""], ["10.", "Nicola Ciotti", "Italy", "o", "o", "xo", "xxx", "2.24", ""], ["13.", "Tomáš Janku", "Czech Republic", "o", "o", "xxo", "xxx", "2.24", ""], ["1.", "Stefan Holm", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["1.", "Linus Thörnblad", "Sweden", "o", "o", "o", "o", "2.27", "q"], ["1.", "Andrey Tereshin", "Russia", "o", "o", "o", "o", "2.27", "q"], ["1.", "Víctor Moya", "Cuba", "o", "o", "o", "o", "2.27", "q, PB"], ["1.", "Andriy Sokolovskyy", "Ukraine", "o", "o", "o", "o", "2.27", "q"], ["8.", "Robert Wolski", "Poland", "xo", "o", "o", "xxx", "2.24", "q"], ["9.", "Ramsay Carelse", "South Africa", "xo", "xo", "o", "xxx", "2.24", ""], ["7.", "Giulio Ciotti", "Italy", "o", "o", "o", "xxx", "2.24", "q"], ["15.", "Svatoslav Ton", "Czech Republic", "o", "xo", "xxx", "", "2.20", ""], ["13.", "Mustapha Raifak", "France", "o", "o", "xxo", "xxx", "2.24", ""], ["10.", "Wojciech Theiner", "Poland", "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:what other athlete from the united states ranked above adam shunk? | Tora Harris | 128 | Answer: |
Table InputTable: [["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"], ["8", "Tunisia", "0", "1", "0", "1"], ["3", "Yugoslavia", "3", "2", "1", "6"], ["7", "Egypt", "0", "1", "7", "8"], ["2", "Greece", "6", "7", "6", "19"], ["1", "France", "11", "5", "3", "19"], ["5", "Morocco", "1", "1", "0", "2"], ["Totaal", "Totaal", "23", "23", "22", "68"], ["4", "Spain", "1", "5", "5", "11"], ["5", "Turkey", "1", "1", "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:of the top 8 countries, which has the most number of bronze medals? | Egypt | 128 | Answer: |
Table InputTable: [["#", "Directed By", "Written By", "Original Air Date"], ["8", "Douglas Mackinnon", "Neil McKay", "November 16, 1997"], ["6", "John Reardon", "Neil McKay", "November 2, 1997"], ["9", "Douglas Mackinnon", "Neil McKay", "November 23, 1997"], ["16", "Douglas MacKinnon", "Neil McKay", "February 8, 1998"], ["5", "John Reardon", "Neil McKay", "October 26, 1997"], ["14", "Ken Horn", "Neil McKay", "January 25, 1998"], ["12", "Ken Horn", "David Humphries", "January 11, 1998"], ["10", "John Reardon", "Simon J. Sharkey", "November 30, 1997"], ["13", "John Reardon", "Simon J. Sharkey", "January 18, 1998"], ["4", "Gerry Poulson", "David Humphries", "October 12, 1997"], ["3", "Gerry Poulson", "David Humphries", "October 5, 1997"], ["11", "John Reardon", "Simon J. Sharkey", "January 4, 1998"], ["7", "Frank W. Smith", "Fran Carroll", "November 9, 1997"], ["17", "Graham Moore", "Simon J. Sharkey", "February 15, 1998"], ["18", "John Reardon", "Simon J. Sharkey", "February 22, 1998"], ["15", "Frank W. Smith", "Dave Humphries", "February 1, 1998"], ["2", "Frank W. Smith", "Simon J. Sharkey", "September 28, 1997"], ["1", "Frank W. Smith", "Simon J. Sharkey", "September 14, 1997"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:neil mckay wrote the episode on november 16. who wrote the previous one? | Fran Carroll | 128 | Answer: |
Table InputTable: [["Rank", "Lane", "Name", "Nationality", "Time", "Notes"], ["1", "5", "Eskender Mustafaiev", "Ukraine", "38.77", "Q"], ["4", "6", "Christoffer Lindhe", "Sweden", "41.52", "Q"], ["5", "7", "Arnost Petracek", "Czech Republic", "43.12", ""], ["6", "2", "Ronystony Cordeiro da Silva", "Brazil", "44.22", ""], ["8", "1", "Arnulfo Castorena", "Mexico", "1:03.49", ""], ["3", "3", "Kyunghyun Kim", "South Korea", "40.37", "Q"], ["2", "4", "David Smetanine", "France", "38.97", "Q"], ["7", "8", "Grant Patterson", "Australia", "55.49", ""]] | 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:did sweden or ukraine score the first rank? | Ukraine | 128 | Answer: |
Table InputTable: [["Date", "Venue", "Opponents", "Score", "Competition"], ["20 March", "Fukuoka (A)", "China PR", "1–0", "Sanix Cup"], ["15 October", "Tashkent (N)", "Japan", "2–1", "AFC U-16 Championship (Semifinal)"], ["12 October", "Tashkent (A)", "Uzbekistan", "3–0", "AFC U-16 Championship (Quarterfinal)"], ["20 March", "Fukuoka (A)", "Japan", "2–0", "Sanix Cup"], ["8 October", "Tashkent (N)", "Syria", "1–1", "AFC U-16 Championship (Group B)"], ["6 October", "Tashkent (N)", "Indonesia", "9–0", "AFC U-16 Championship (Group B)"], ["18 October", "Tashkent (N)", "Iran", "1–2", "AFC U-16 Championship (Final)"], ["4 October", "Tashkent (N)", "India", "5–2", "AFC U-16 Championship (Group B)"], ["8 August", "Toyota (N)", "Brazil", "0–0", "Toyota Cup"], ["10 August", "Toyota (N)", "United Arab Emirates", "6–0", "Toyota Cup"], ["9 August", "Toyota (A)", "Japan", "2–2", "Toyota Cup"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which team did the korean under-17 team play before they played china pr in 2008? | Japan | 128 | Answer: |
Table InputTable: [["Rank", "Pair", "Name", "Country", "Time", "Time behind"], ["", "20", "Joey Cheek", "United States", "1:09.16", "+0.27"], ["", "19", "Shani Davis", "United States", "1:08.89", ""], ["9", "18", "Casey FitzRandolph", "United States", "1:09.59", "+0.70"], ["16", "7", "François-Olivier Roberge", "Canada", "1:10.20", "+1.31"], ["6", "4", "Chad Hedrick", "United States", "1:09.45", "+0.56"], ["19", "17", "Denny Morrison", "Canada", "1:10.44", "+1.44"], ["20", "15", "Yusuke Imai", "Japan", "1:10.48", "+1.59"], ["29", "12", "Steven Elm", "Canada", "1:11.36", "+2.47"], ["17", "11", "Choi Jae-bong", "South Korea", "1:10.23", "+1.34"], ["–", "6", "Erik Zachrisson", "Sweden", "DQ", "–"], ["28", "3", "Takahiro Ushiyama", "Japan", "1:11.21", "+2.32"], ["8", "18", "Stefan Groothuis", "Netherlands", "1:09.57", "+0.68"], ["27", "14", "Takaharu Nakajima", "Japan", "1:11.10", "+2.21"], ["11", "19", "Jeremy Wotherspoon", "Canada", "1:09.76", "+0.87"], ["–", "2", "Ermanno Ioriatti", "Italy", "DQ", "–"], ["26", "2", "Mika Poutala", "Finland", "1:11.03", "+2.14"], ["4", "20", "Lee Kyou-hyuk", "South Korea", "1:09.37", "+0.48"], ["37", "9", "Risto Rosendahl", "Finland", "1:12.60", "+3.71"], ["35", "7", "Zhang Zhongqi", "China", "1:12.29", "+3.40"], ["32", "1", "Keiichiro Nagashima", "Japan", "1:11.78", "+2.89"], ["5", "21", "Jan Bos", "Netherlands", "1:09.42", "+0.53"], ["21", "15", "Aleksandr Kibalko", "Russia", "1:10.50", "+1.61"], ["–", "5", "Maciej Ustynowicz", "Poland", "DQ", "–"], ["30", "8", "Maurizio Carnino", "Italy", "1:11.44", "+2.55"], ["22", "10", "Lee Kang-seok", "South Korea", "1:10.52", "+1.63"], ["34", "1", "Yu Fengtong", "China", "1:11.90", "+3.01"], ["31", "1", "Pekka Koskela", "Finland", "1:11.45", "+2.56"], ["36", "8", "Aleksandr Zhigin", "Kazakhstan", "1:12.36", "+3.47"], ["18", "12", "Petter Andersen", "Norway", "1:10.38", "+1.38"], ["38", "5", "Lu Zhuo", "China", "1:12.69", "+3.80"], ["25", "10", "Janne Hänninen", "Finland", "1:10.83", "+1.94"], ["24", "17", "Mun Jun", "South Korea", "1:10.66", "+1.77"], ["15", "13", "Alexey Proshin", "Russia", "1:10.14", "+1.25"], ["10", "6", "Dmitry Dorofeyev", "Russia", "1:09.74", "+0.85"], ["23", "14", "Even Wetten", "Norway", "1:10.57", "+1.68"], ["14", "16", "Mikael Flygind Larsen", "Norway", "1:10.13", "+1.24"]] | 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:what is the previous name of joey cheek? | Shani Davis | 128 | Answer: |
Table InputTable: [["Year", "Award", "Nominated work", "Category", "Result"], ["2008", "UK Music Video Awards", "\"Bleeding Love\"", "People's Choice Award", "Won"], ["2009", "HITO Pop Music Awards", "\"Bleeding Love\"", "Best Western Song", "Won"], ["2009", "APRA Awards", "\"Bleeding Love\"", "Most Played Foreign Work", "Won"], ["2007", "The Record of the Year", "\"Bleeding Love\"", "The Record of the Year", "Won"], ["2008", "Nickelodeon UK Kids Choice Awards", "\"Bleeding Love\"", "Favourite Song", "Won"], ["2008", "Vh1 Video of the Year", "\"Bleeding Love\"", "Best Video", "Won"], ["2008", "Bambi Award", "Leona Lewis", "Shooting Star", "Won"], ["2009", "Cosmopolitan Awards", "Leona Lewis", "Ultimate Music Star", "Won"], ["2008", "Britain's Best", "Leona Lewis", "Music Award", "Won"], ["2008", "PETA", "Leona Lewis", "Person Of The Year", "Won"], ["2008", "Capital Awards", "Leona Lewis", "Favourite UK Female Artist", "Won"], ["2008", "Billboard 2008 Year End Award", "Leona Lewis", "Best New Artist", "Won"], ["2008", "NewNowNext Awards", "Leona Lewis", "The Kylie Award: Next International Crossover", "Won"], ["2008", "NME Best Album", "\"Spirit\"", "Best Album", "Nominated"], ["2008", "New Music Weekly Awards", "Leona Lewis", "Top 40 New Artist of the Year", "Won"], ["2008", "Glamour Woman Of The Year Awards", "Leona Lewis", "UK Solo Artist", "Won"], ["2009", "BEFFTA Awards", "Leona Lewis", "Best Female Act", "Won"], ["2009", "Japan Gold Disc Awards", "Leona Lewis", "New Artist Of The Year", "Won"], ["2009", "NAACP Image Awards", "Leona Lewis", "Outstanding New Artist", "Nominated"], ["2007", "Cosmopolitan Ultimate Woman of the Year", "Leona Lewis", "Newcomer of the Year", "Won"], ["2009", "PETA - Sexiest Vegetarian Alive Awards", "Leona Lewis", "Sexiest Vegetarian Celebrity 2009", "Won"], ["2009", "Swiss Music Awards", "Leona Lewis", "Best International Newcomer", "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 times did "bleeding love" win? | 6 | 128 | Answer: |
Table InputTable: [["Release date", "Album Title", "Record Company", "Song Title", "Certification"], ["April 2009", "OPM Number 1's", "Star Records", "\"Can't Hurry Love\"", "PARI:"], ["March 5, 2011", "Kris Aquino: My Heart’s Journey", "Universal Records", "\"God Bless the Broken Road\"", "PARI: Platinum"], ["November 18, 2011", "Da Best ang Pasko ng Pilipino", "Star Records", "\"Ganyan ang Pasko\", \"Ngayong Pasko Magniningning ang Pilipino\" (Solo) & with Gary Valenciano", "PARI:"], ["June 24, 2009", "I Move, I Give, I Love", "Star Records", "\"Power of the Dream\", \"Bagong Umaga\" with Erik Santos & Yeng Constantino", "PARI: Gold"], ["February 2011", "I Love You", "Star Records", "\"Catch Me I'm Falling\"", "PARI:"], ["January 2011", "OPM Number 1's Vol. 2", "Star Records", "\"All Me (Remix)\"", "PARI:"], ["November 12, 2011", "Happy Yipee Yehey! Nananana!", "Star Records", "\"Mahalin Ka Ng Totoo\"", "PARI: Gold"], ["December 2007", "H.O.P.E. (Healing Of Pain and Enlightenment)", "Star Records", "\"Count On Me\"", "PARI: Gold"], ["June 2011", "Bida Best Hits Da Best", "Star Records", "\"Mahal Kita Kasi\", \"Catch Me I'm Falling\", \"You Are The One\" with Sam Milby", "PARI:"], ["November 2010", "Ngayong Pasko Magniningning ang Pilipino: Christmas Songs Compilation", "Star Records", "\"Ganyan ang Pasko\", \"Ngayong Pasko Magniningning ang Pilipino\" (Solo) & with Gary Valenciano", "PARI:"], ["January 17, 2013", "Himig Handog P-Pop Love Songs 2013", "Star Records", "\"Kahit Na\"", "PARI:"], ["July 25, 2007", "Nagmamahal, Kapamilya: Songs for Global Pinoys", "Star Records", "\"Super Pinoy\"", "PARI: 6X Platinum"], ["June 2010", "60 Taon ng Musika at Soap Opera", "Star Records", "\"Crazy For You\"", "PARI:"], ["October 8, 2006", "Hotsilog: The ASAP Hotdog Compilation", "ASAP Music", "\"Annie Batungbakal\"", "PARI: Platinum"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many times has toni gonzaga been a participating artist for an album released by star records? | 12 | 128 | Answer: |
Table InputTable: [["Round", "Pick", "Name", "Position", "College"], ["6", "170", "Frank Murphy", "WR", "Kansas State"], ["4", "125", "Reggie Austin", "DB", "Wake Forest"], ["3", "69", "Dez White", "WR", "Georgia Tech"], ["2", "39", "Mike Brown", "S", "Nebraska"], ["1", "9", "Brian Urlacher", "S", "New Mexico"], ["3", "87", "Dustin Lyman", "TE", "Wake Forest"], ["6", "174", "Paul Edinger", "K", "Michigan State"], ["7", "223", "James Cotton", "DE", "Ohio State"], ["7", "254", "Michael Green", "S", "Northwestern State"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 chicago bears' top draft pick in 2000? | Brian Urlacher | 128 | Answer: |
Table InputTable: [["Ship", "Hull No.", "Status", "Years Active", "NVR\\nPage"], ["Henry Eckford", "T-AO-192", "Cancelled when 84% complete,\\ntransferred to the Maritime Administration,\\nlaid up in the James River Reserve Fleet,\\nscrapped in 2011", "Launched 1989, never in service", "AO192"], ["Benjamin Isherwood", "T-AO-191", "Cancelled when 95.3% complete,\\ntransferred to the Maritime Administration,\\nlaid up in the James River Reserve Fleet,\\nscrapped in 2011", "Launched 1988, christened 1991, never in service", "AO191"], ["Andrew J. Higgins", "T-AO-190", "Inactivated May 1996. Sold to the Chilean Navy May 2009. Towed to Atlantic Marine Alabama shipyard, Mobile, Alabama, September 2009 for three-month refit. Commissioned in Chilean Navy on 10 February 2010 and renamed Almirante Montt.[1]", "1987-1996 (USA); 2010–present (Chile)", "AO190"], ["Yukon", "T-AO-202", "Active", "1994–present", "AO202"], ["Big Horn", "T-AO-198", "Active", "1992–present", "AO198"], ["John Lenthall", "T-AO-189", "Active", "1987-1996; 1998–present", "AO189"], ["Rappahannock", "T-AO-204", "Active", "1995–present", "AO204"], ["Tippecanoe", "T-AO-199", "Active", "1993–present", "AO199"], ["John Ericsson", "T-AO-194", "Active", "1991–present", "AO194"], ["Henry J. Kaiser", "T-AO-187", "Active—Southern California Duty Oiler", "1986–present", "AO187"], ["Patuxent", "T-AO-201", "Active", "1995–present", "AO201"], ["Kanawha", "T-AO-196", "Active", "1991–present", "AO196"], ["Guadalupe", "T-AO-200", "Active", "1992–present", "AO200"], ["Pecos", "T-AO-197", "Active", "1990–present", "AO197"], ["Laramie", "T-AO-203", "Active", "1996–present", "AO203"], ["Leroy Grumman", "T-AO-195", "Active", "1989–present", "AO195"], ["Joshua Humphreys", "T-AO-188", "Inactivated 1996, returned to service 2005", "1987-1996; 2005-2006; 2010-present", "AO188"], ["Walter S. Diehl", "T-AO-193", "Active", "1988–present", "AO193"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which ship is on the nvr page before henry eckford? | Benjamin Isherwood | 128 | Answer: |
Table InputTable: [["Name", "City", "State/Country", "Designed", "Completed", "Other Information"], ["Case Study House #9", "Los Angeles", "California", "1945", "1949", "With Charles Eames. Saarinen also provided an original plan for House #8, but Eames completely redesigned it. Listed on the National Register of Historic Places in 2013"], ["Brandeis University plan and buildings", "Waltham", "Massachusetts", "1949", "1952", "With Matthew Nowicki. Ridgewood Quadrangle Dormitories (1950), Hamilton Quadrangle Dormitory & Student Center (1952), Sherman Student Center (1952)"], ["J. F. Spencer House", "Huntington Woods", "Michigan", "1937", "1938", "First building designed independently"], ["United States Chancellery Building", "London", "England", "1955", "1960", ""], ["United States Chancellery Building", "Oslo", "Norway", "1955", "1959", ""], ["Christ Church Lutheran", "Minneapolis", "Minnesota", "1947", "1949", "With Eliel Saarinen; solo addition in 1962. Designated a National Historic Landmark in 2009."], ["Pedestal Series", "n/a", "n/a", "1954", "1957", "Furniture design for Knoll Associates. Includes the tulip chair"], ["Grasshopper Chair", "n/a", "n/a", "1943", "1946", "Chair design for Knoll Associates"], ["Womb Chair & Ottoman", "n/a", "n/a", "1946", "1948", "Chair design for Knoll Associates"], ["University of Chicago plan and buildings", "Chicago", "Illinois", "1955", "1960", "Women's Dormitory & Dining Hall (1958; demolished 2001), Law School (1960)"], ["Des Moines Art Center", "Des Moines", "Iowa", "1944", "1948", "With Eliel Saarinen and J. Robert F. Swanson. Listed on the National Register of Historic Places in 2004"], ["Eero Saarinen & Associates Building", "Bloomfield Hills", "Michigan", "1953", "1953", ""], ["Kleinhans Music Hall", "Buffalo", "New York", "1938", "1940", "With Eliel Saarinen. Designated a National Historic Landmark in 1989"], ["Saarinen House", "New Haven", "Connecticut", "1960", "1961", "Renovation of a Tudor Revival house"], ["CBS Building", "New York City", "New York", "1960", "1965", ""], ["Models 71 and 73", "n/a", "n/a", "1945", "1950", "Chair design for Knoll Associates"], ["Hvitträsk Studio and Home", "Kirkkonummi", "Finland", "1929", "1937", "Remodel"], ["Massachusetts Institute of Technology buildings", "Cambridge", "Massachusetts", "1950", "1955", "Kresge Chapel and Kresge Auditorium"], ["Eero Saarinen House", "Bloomfield Hills", "Michigan", "1947", "1959", "Renovation of a Victorian house"], ["UAW–CIO Cooperative", "Flint", "Michigan", "1948", "1948", "Renovation. Demolished."], ["Center Line Defense Housing", "Center Line", "Michigan", "1941", "1942", "With Eliel Saarinen and J. Robert F. Swanson. 477 housing units"], ["Hill Hall", "Philadelphia", "Pennsylvania", "1957", "1960", ""], ["Saarinen House furnishings", "Bloomfield Hills", "Michigan", "1928", "1930", ""], ["Crow Island School", "Winnetka", "Illinois", "1938", "1942", "With Eliel Saarinen and Perkins & Will. Designated a National Historic Landmark in 1990"], ["Aspen Music Center", "Aspen", "Colorado", "1949", "1949", "With Eliel Saarinen. Demolished in 1963."], ["Hamden Office", "Hamden", "Connecticut", "1960", "1961", "Became new headquarters"], ["Stephens College Chapel", "Columbia", "Missouri", "1953", "1956", ""], ["Drake University plan and buildings", "Des Moines", "Iowa", "1945", "1957", "Harvey Ingham Hall of Science, Fitch Hall of Pharmacy, Women's Dormitory & Dining Hall (all in 1945 with Eliel Saarinen and J. Robert F. Swanson), Bible School & Prayer Chapel in 1952, Women's Dormitory #4 in 1957, Jewett Union addition in 1957"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what was the name of the last building he designed? | Athens Airport | 128 | Answer: |
Table InputTable: [["Specifications", "Foundation", "Essentials", "Standard", "Datacenter"], ["Processor chip limit", "1", "2", "64", "64"], ["Licensing model", "Per server", "Per server", "Per CPU pair + CAL", "Per CPU pair + CAL"], ["Virtualization rights", "N/A", "Either in 1 VM or 1 physical server, but not both at once", "2 VMs", "Unlimited"], ["Memory limit", "32 GB", "64 GB", "4 TB", "4 TB"], ["File Services limits", "1 standalone DFS root", "1 standalone DFS root", "Unlimited", "Unlimited"], ["Remote Desktop Services limits", "50 Remote Desktop Services connections", "Gateway only", "Unlimited", "Unlimited"], ["Distribution", "OEM only", "Retail, volume licensing, OEM", "Retail, volume licensing, OEM", "Volume licensing and OEM"], ["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"], ["User limit", "15", "25", "Unlimited", "Unlimited"], ["Windows Deployment Services", "Yes", "Yes", "Yes", "Yes"], ["Server Core mode", "No", "No", "Yes", "Yes"], ["DHCP role", "Yes", "Yes", "Yes", "Yes"], ["Windows Server Update Services", "No", "Yes", "Yes", "Yes"], ["Server Manager", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Certificate Services", "Certificate Authorities only", "Certificate Authorities only", "Yes", "Yes"], ["Application server role", "Yes", "Yes", "Yes", "Yes"], ["Print and Document Services", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Federation Services", "Yes", "No", "Yes", "Yes"], ["Windows Powershell", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Domain Services", "Must be root of forest and domain", "Must be root of forest and domain", "Yes", "Yes"], ["Fax server role", "Yes", "Yes", "Yes", "Yes"], ["UDDI Services", "Yes", "Yes", "Yes", "Yes"], ["Web Services (Internet Information Services)", "Yes", "Yes", "Yes", "Yes"], ["Active Directory Rights Management Services", "Yes", "Yes", "Yes", "Yes"], ["Hyper-V", "No", "No", "Yes", "Yes"], ["Active Directory Lightweight Directory Services", "Yes", "Yes", "Yes", "Yes"], ["DNS server role", "Yes", "Yes", "Yes", "Yes"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many processor chips can the datacenter specification support? | 64 | 128 | Answer: |
Table InputTable: [["Rank", "Player", "Nation", "Club", "Goals"], ["9", "Chris Banks", "USA", "Wilmington Hammerheads", "7"], ["3", "Maxwell Griffin", "USA", "Orlando City", "9"], ["3", "José Angulo", "USA", "Harrisburg City Islanders", "9"], ["2", "Matthew Delicâte", "ENG", "Richmond Kickers", "10"], ["3", "Luke Mulholland", "ENG", "Wilmington Hammerheads", "9"], ["6", "Andriy Budnyy", "UKR", "Wilmington Hammerheads", "8"], ["9", "Sainey Touray", "GAM", "Harrisburg City Islanders", "7"], ["6", "Andrew Welker", "USA", "Harrisburg City Islanders", "8"], ["9", "George Davis IV", "USA", "Dayton Dutch Lions", "7"], ["1", "Jhonny Arteaga", "COL", "FC New York", "13"], ["6", "Jamie Watson", "USA", "Orlando City", "8"], ["9", "Sallieu Bundu", "SLE", "Charlotte Eagles", "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:who had more goals, griffin or banks? | Maxwell Griffin | 128 | Answer: |
Table InputTable: [["Departure", "Going to", "Calling at", "Arrival", "Operator"], ["11.01", "Skegness / Mablethorpe", "Boston, Firsby: Part to Skegness. Part to Willoughby, Sutton-on-Sea, Mablethorpe", "12.08 / 12.20", "GNR"], ["14.00", "York", "Lincoln, Gainsborough, Doncaster, Selby", "16.33", "GN&GE"], ["17.00", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "18.27", "GN&GE"], ["17.55", "Nottingham Victoria", "", "18.46", "GNR"], ["08.17", "Grantham", "Rauceby, Ancaster, Barkston", "08.45", "GNR"], ["12.43", "Lowestoft", "Spalding, March, Shippea Hill, Brandon, Thetford, Attleborough, Wymondham, Norwich, Oulton Broad", "16.10", "GN&GE"], ["09.50", "Grantham", "Rauceby, Ancaster, Honington", "10.20", "GNR"], ["19.46", "Doncaster", "Blankney & Metheringham, Lincoln, Gainsborough", "21.22", "GN&GE"], ["11.34", "Grantham", "Rauceby, Ancaster, Barkston, Honington", "12.05", "GNR"], ["07.00", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "07.32", "GNR"], ["13.48", "Grantham", "Rauceby, Ancaster, Honington", "14.21", "GNR"], ["18.51", "Grantham", "Rauceby, Ancaster, Honington, Barkston", "19.28", "GNR"], ["10.48", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "12.12", "GN&GE"], ["18.58", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "20.20", "GN&GE"], ["08.20", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "09.00", "GNR"], ["13.49", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "15.23", "GN&GE"], ["08.16", "March", "Helpringham, Donington Road, Gosberton, Pinckbeck, Spalding, Cowbit, Postland, French Drove, Murrow, Guyhirne", "09.38", "GN&GE"], ["19.22", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "19.55", "GNR"], ["16.25", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "17.00", "GNR"], ["22.04", "Grantham", "", "22.27", "GNR"], ["16.19", "Boston", "Heckington, Swineshead, Hubbert's Bridge", "16.51", "GNR"], ["11.37", "Doncaster", "Ruskington, Digby, Scopwick & Timberland, Blankney & Metheringham, Nocton & Dunston, Potterhanworth, Branston & Heighington, Lincoln, Saxilby, Stow Park, Lea, Gainsborough, Beckingham, Walkeringham, Misterton, Haxey & Epworth, Park Drain, Finningley", "09.05", "GN&GE"], ["10.05", "Bourne", "Aswarby & Scredington, Billingborough & Horbling, Rippingale, Morton Road", "10.41", "GNR"], ["21.54", "Doncaster", "Ruskington, Digby, Blankney & Metheringham, Nocton & Dunston, Potterhanworth, Branston & Heighington, Lincoln, Saxilby, Gainsborough, Misterton", "23.45", "GN&GE"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:a train going to where will take the least amount of time? | Grantham | 128 | Answer: |
Table InputTable: [["Season", "Series", "Team", "Races", "Wins", "Poles", "F/Laps", "Podiums", "Points", "Position"], ["2011", "Formula Pilota China", "Asia Racing Team", "12", "2", "0", "0", "3", "124", "2nd"], ["2008", "Asian Formula Renault Challenge", "Champ Motorsports", "13", "0", "0", "0", "3", "193", "4th"], ["2007", "Asian Formula Renault Challenge", "Champ Motorsports", "12", "0", "0", "0", "1", "64", "14th"], ["2012", "British Formula 3 Championship", "Angola Racing Team", "5", "0", "0", "0", "0", "—", "—"], ["2009", "Asian Formula Renault Challenge", "Asia Racing Team", "12", "6", "2", "4", "7", "287", "2nd"], ["2012", "Masters of Formula 3", "Angola Racing Team", "1", "0", "0", "0", "0", "—", "18th"], ["2012", "59th Macau Grand Prix Formula 3", "Angola Racing Team", "2", "0", "0", "0", "0", "—", "23rd"], ["2012", "Formula 3 Euro Series", "Angola Racing Team", "21", "0", "0", "0", "0", "14", "14th"], ["2009", "Formula Renault 2.0 Northern European Cup", "Krenek Motorsport", "14", "0", "0", "0", "0", "44", "21st"], ["2013", "GP3 Series", "Carlin", "16", "0", "0", "0", "0", "0", "23rd"], ["2010", "Austria Formula 3 Cup", "Sonangol Motopark", "4", "1", "2", "3", "2", "35", "9th"], ["2010", "ATS Formel 3 Cup", "China Sonangol", "5", "0", "0", "0", "0", "0", "19th"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:before 2011 how many races were there? | 6 | 128 | Answer: |
Table InputTable: [["Contestant", "Age", "Height", "Home City", "Rank"], ["Isabelle Raisa", "16", "170 cm (5 ft 7 in)", "Vienna", "Eliminated in Episode 1"], ["Michaela Schopf", "21", "172 cm (5 ft 7.5 in)", "Salzburg (originally from Germany)", "Quit in Episode 4"], ["Dzejlana \"Lana\" Baltić", "20", "179 cm (5 ft 10.5 in)", "Graz (originally from Bosnia)", "1st Eliminated in Episode 10"], ["Nadine Trinker", "21", "183 cm (6 ft 0 in)", "Bodensdorf", "Eliminated in Episode 9"], ["Melisa Popanicić", "16", "175 cm (5 ft 9 in)", "Wörgl", "2nd Eliminated in Episode 10"], ["Katharina Mihalović", "23", "179 cm (5 ft 10.5 in)", "Vienna", "Eliminated in Episode 2"], ["Yemisi Rieger", "17", "177 cm (5 ft 9.5 in)", "Vienna", "Eliminated in Episode 7"], ["Christine Riener", "20", "181 cm (5 ft 11.25 in)", "Bludenz", "Eliminated in Episode 4"], ["Gina Zeneb Adamu", "17", "175 cm (5 ft 9 in)", "Bad Vöslau", "Runner-Up"], ["Sabrina Angelika Rauch †", "21", "175 cm (5 ft 9 in)", "Graz", "Eliminated in Episode 2"], ["Izabela Pop Kostić", "20", "170 cm (5 ft 7 in)", "Vienna (originally from Bosnia)", "Eliminated in Episode 8"], ["Alina Chlebecek", "18", "170 cm (5 ft 7 in)", "Deutsch-Wagram", "Eliminated in Episode 1"], ["Bianca Ebelsberger", "24", "179 cm (5 ft 10.5 in)", "Aurach am Hongar", "Eliminated in Episode 9"], ["Nataša Marić", "16", "175 cm (5 ft 9 in)", "Liefering (originally from Serbia)", "Eliminated in Episode 3"], ["Teodora-Mădălina Andreica", "17", "177 cm (5 ft 9.5 in)", "Romania", "Eliminated in Episode 6"], ["Antonia Maria Hausmair", "16", "175 cm (5 ft 9 in)", "Siegendorf", "Winner"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 cycle 4 of austria's next top model, what is the average of all the contestants' ages? | 18 | 128 | Answer: |
Table InputTable: [["Name", "Route number(s)", "Length (mi)", "Location", "Notes"], ["Pilgrims Highway", "", "42.5", "Bourne to Braintree", "The Pilgrims Highway is the southern portion of Route 3, a 42-mile (68 km) long freeway which serves as a connector between Cape Cod (via U.S. Route 6) and the Boston metropolitan area (via I-93 and I-95).\\n- U.S. Route 44 runs along the highway between Exits 6 and 7."], ["Wilbur Cross Highway", "*", "8.0", "Sturbridge", "I-84 in Massachusetts is designated the Wilbur Cross Highway. It runs 8 miles (13 km) from the Connecticut state border to the Mass Pike at Exit 9."], ["Yankee Division Highway\\n(Circumferential Highway)", "*", "64.74", "Braintree to Gloucester", "The Yankee Division Highway consists of the Route 128 beltway before it was truncated to its southern terminus in Canton, and continues to span its entire length. It stretches from I-93's Exit 7 in Braintree to Route 128's northern terminus at Route 127A in Gloucester.\\n- I-95 runs along the highway between Exits 12 and 45 (concurrent with 128).\\n- I-93 runs along the highway between Exits 1 and 7.\\n- U.S. Route 1 runs along the highway between I-95 Exit 15B and I-93 Exit 7."], ["Lydia Taft Highway", "*", "3", "Uxbridge", "Route 146A in Massachusetts is designated as the Lydia Taft Highway, which runs from the Rhode Island state border to Route 122 in Uxbridge."], ["Grand Army of the Republic Highway", "*", "117.46", "Seekonk to Provincetown", "The cross-country U.S. Route 6 is designated Grand Army of the Republic Highway over its entire length, which spans 3,205 miles (5,158 km)."], ["Taunton-New Bedford Expressway\\n(Alfred M. Bessette Memorial Highway)", "", "19.3", "New Bedford to Taunton", "The New Bedford Expressway comprises the southern 19 miles (31 km) of Route 140, and serves as a freeway connection between U.S. Route 6 in New Bedford and Route 24 (Exit 12) in Taunton, near I-495."], ["Loop Connector", "*", "3.56", "Methuen", "Route 213 is designated \"Loop Connector.\" It serves as a freeway connection between Interstates 93 and 495 in Methuen."], ["Massachusetts Turnpike", "*", "138.1", "West Stockbridge\\nto Boston", "The Mass Pike is a toll road running from the New York state border to downtown Boston. It serves as the main cross-state freeway connecting the western and eastern portions of the state. The \"Pike\" carries the easternmost 138 miles (222 km) of cross-country Interstate 90."], ["East Boston Expressway", "", "1.2", "Boston", "The East Boston Expressway comprises the first 1.2 miles (1.9 km) of Route 1A's northern segment. It stretches from I-93 Exit 24 at the southern end of the Callahan Tunnel (northbound) and the Sumner Tunnel (southbound) to just northeast of the interchange with Route 145 in East Boston, near the eastern end of the Mass Pike."], ["Worcester-Providence Turnpike", "*", "20.99", "Millville to Worcester", "Route 146 is a freeway that, along with Rhode Island's Route 146, serves to connect the metropolitan areas of Providence and Worcester. The entire route starts from I-95 in Providence, with the Massachusetts section picking up at the state line in Millville. The highway runs 21 miles (34 km) northward, intersecting the Mass Pike (I-90) in Worcester, and terminating at I-290 shortly thereafter.\\n- Route 122A runs along the highway between Exits 9 and 12, concurrently with Route 146."], ["Mohawk Trail", "", "65", "Williamstown\\nto Orange", "The 65-mile (105 km) Mohawk Trail comprises the western section of Route 2, from the New York border east to Orange, and is regarded as one of the most scenic drives in the area."], ["Mid-Cape Highway", "", "36.6", "Bourne to Orleans", "The Mid-Cape Highway is the main highway on Cape Cod, a 36-mile (58 km) long freeway running from Route 3 and the Sagamore Bridge east to the Orleans Rotary."]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what road has the shortest length? | East Boston Expressway | 128 | Answer: |
Table InputTable: [["Round", "Round", "Race", "Date", "Pole Position", "Fastest Lap", "Winning Club", "Winning Team", "Report"], ["6", "R1", "Jerez", "November 23", "Liverpool F.C.", "R.S.C. Anderlecht", "A.C. Milan", "Scuderia Playteam", "Report"], ["2", "R1", "Nürburgring", "September 21", "A.C. Milan", "PSV Eindhoven", "A.C. Milan", "Scuderia Playteam", "Report"], ["4", "R1", "Estoril", "October 19", "A.S. Roma", "Atlético Madrid", "Liverpool F.C.", "Hitech Junior Team", "Report"], ["3", "R1", "Zolder", "October 5", "Borussia Dortmund", "Liverpool F.C.", "Liverpool F.C.", "Hitech Junior Team", "Report"], ["5", "R2", "Vallelunga", "November 2", "", "Atlético Madrid", "F.C. Porto", "Hitech Junior Team", "Report"], ["4", "R2", "Estoril", "October 19", "", "Borussia Dortmund", "Al Ain", "Azerti Motorsport", "Report"], ["5", "R1", "Vallelunga", "November 2", "Liverpool F.C.", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "Report"], ["3", "R2", "Zolder", "October 5", "", "Atlético Madrid", "Beijing Guoan", "Zakspeed", "Report"], ["2", "R2", "Nürburgring", "September 21", "", "SC Corinthians", "PSV Eindhoven", "Azerti Motorsport", "Report"], ["6", "R2", "Jerez", "November 23", "", "Beijing Guoan", "Borussia Dortmund", "Zakspeed", "Report"], ["1", "R2", "Donington Park", "August 31", "", "PSV Eindhoven", "Sevilla FC", "GTA Motor Competición", "Report"], ["1", "R1", "Donington Park", "August 31", "Beijing Guoan", "Beijing Guoan", "Beijing Guoan", "Zakspeed", "Report"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the total number of wins that a.c. milan had? | 2 | 128 | Answer: |
Table InputTable: [["Year", "Injuries (US $000)", "Deaths (age <15)", "CPSC toy safety funding\\n(US$ Millions)", "Toy sales\\n(US $ Billions)"], ["1998", "153", "14", "", ""], ["2008", "no data", "19", "no data", ""], ["1996", "130", "", "", ""], ["2009", "no data", "12", "no data", ""], ["1994", "154", "", "", ""], ["1995", "139", "", "", ""], ["2007", "no data", "22", "no data", ""], ["1997", "141", "", "", ""], ["2005", "202 (estimate)", "20", "11.0", "22.2"], ["1999", "152", "16", "13.6", ""], ["2006", "no data", "22", "no data†", "22.3"], ["2004", "210", "16", "11.5", "22.4"], ["2001", "255", "25", "12.4", ""], ["2003", "206", "11", "12.8", "20.7"], ["2000", "191", "17", "12.0", ""], ["2002", "212", "13", "12.2", "21.3"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the first year in which data was recorded for deaths under the age of 15? | 1998 | 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, 1993", "March 9, 1997", "December 25, 2000", "October 14, 2004", "August 1, 2008"], ["May 21, 2031", "March 9, 2035", "December 26, 2038", "October 14, 2042", "August 2, 2046"], ["May 20, 2050", "March 9, 2054", "December 26, 2057", "October 13, 2061", "August 2, 2065"], ["138", "140", "142", "144", "146"], ["148", "150", "152", "154", "156"], ["128", "130", "132", "134", "136"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 solar eclipses occurred previous to 2014? | 6 | 128 | Answer: |
Table InputTable: [["Rank", "Pair", "Country", "Athletes", "Time", "Deficit"], ["", "4", "United States", "Shani Davis\\nBrian Hansen\\nJonathan Kuck", "3:43.42", "+1.99"], ["5", "1", "Norway", "Sverre Lunde Pedersen\\nHåvard Bøkko\\nKristian Reistad Fredriksen", "3:46.33", "+4.90"], ["6", "3", "Germany", "Patrick Beckert\\nMarco Weber\\nRobert Lehmann", "3:46.48", "+5.05"], ["", "3", "Netherlands", "Sven Kramer\\nKoen Verweij\\nJan Blokhuijsen", "3:41.43", ""], ["4", "1", "Canada", "Denny Morrison\\nMathieu Giroux\\nLucas Makowsky", "3:44.38", "+2.95"], ["", "2", "Russia", "Ivan Skobrev\\nDenis Yuskov\\nYevgeny Lalenkov", "3:43.62", "+2.19"], ["7", "4", "South Korea", "Lee Seung-hoon\\nJoo Hyong-jun\\nKo Byung-wook", "3:47.18", "+5.75"], ["8", "2", "Poland", "Zbigniew Bródka\\nKonrad Niedźwiedzki\\nJan Szymański", "3:47.72", "+6.29"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what country did the athletes shani davis and brian hansen skate? | United States | 128 | Answer: |
Table InputTable: [["Name of place", "Number of counties", "Principal county", "Lower zip code", "Upper zip code"], ["Scott Township", "1", "Columbia County", "", ""], ["Scott Township", "1", "Lawrence County", "", ""], ["Scott Township", "1", "Wayne County", "", ""], ["Scott Township", "1", "Allegheny County", "15106", ""], ["Scott Township", "1", "Lackawanna County", "", ""], ["Scott Center", "1", "Wayne County", "18462", ""], ["Scottdale", "1", "Westmoreland County", "15683", ""], ["Scott Haven", "1", "Westmoreland County", "15083", ""], ["Scottsville", "1", "Beaver County", "15001", ""], ["Silver Spring Township", "1", "Cumberland County", "", ""], ["Scottsville", "1", "Wyoming County", "", ""], ["Saville Township", "1", "Perry County", "", ""], ["Scott", "1", "Lackawanna County", "", ""], ["St. Clair Township", "1", "Westmoreland County", "", ""], ["Sergeant Township", "1", "McKean County", "", ""], ["Sharon Township", "1", "Potter County", "", ""], ["Shade Township", "1", "Somerset County", "", ""], ["Shippen Township", "1", "Cameron County", "", ""], ["Salford Township", "1", "Montgomery County", "", ""], ["Sheffield Township", "1", "Warren County", "", ""], ["Shenango Township", "1", "Mercer County", "", ""], ["Sandy Lake Township", "1", "Mercer County", "", ""], ["Shenango Township", "1", "Lawrence County", "", ""], ["Shingletown", "1", "Centre County", "16801", ""], ["Schwenksville", "1", "Montgomery County", "19473", ""], ["Shazen", "1", "Cambria County", "", ""], ["Shippensburg Township", "1", "Cumberland County", "", ""], ["Schweibinzville", "1", "Somerset County", "", ""], ["Schuylkill Township", "1", "Chester County", "", ""], ["Sipes Mill", "1", "Fulton County", "17238", ""], ["Scrubgrass Township", "1", "Venango County", "", ""], ["Sandy Creek Township", "1", "Mercer County", "", ""], ["Saville", "1", "Perry County", "17074", ""], ["Shamrock", "1", "Somerset County", "", ""], ["Saltlick Township", "1", "Fayette County", "", ""], ["Sandy Township", "1", "Clearfield County", "", ""], ["Shimpstown", "1", "Franklin County", "17236", ""], ["Schaefferstown", "1", "Lebanon County", "17088", ""], ["Shadle", "1", "Snyder County", "15666", ""], ["Shamokin Township", "1", "Northumberland County", "", ""], ["Sconnelltown", "1", "Chester County", "19380", ""], ["Sandycreek Township", "1", "Venango County", "", ""], ["Silver Lake Township", "1", "Susquehanna County", "", ""], ["St. Joseph", "1", "Susquehanna County", "18818", ""], ["Shepherdstown", "1", "Cumberland County", "17055", ""], ["Scherersville", "1", "Lehigh County", "", ""], ["Shaytown", "1", "Potter County", "", ""], ["Shamrock", "1", "Fayette County", "15401", ""], ["St. Thomas Township", "1", "Franklin County", "", ""], ["Savage", "1", "Somerset County", "", ""], ["Sheshequin Township", "1", "Bradford County", "", ""], ["Sadsbury Township", "1", "Chester County", "", ""], ["Shimerville", "1", "Lehigh County", "18049", ""], ["Saverys Mill", "1", "Chester County", "", ""], ["Shinglehouse", "1", "Potter County", "16748", ""], ["Shippen Township", "1", "Tioga County", "", ""], ["Shrewsbury Township", "1", "Sullivan County", "", ""], ["Shirksville", "1", "Lebanon County", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 counties are each scott townships located in? | Allegheny County, Columbia County, Lackawanna County, Lawrence County, Wayne County | 128 | Answer: |
Table InputTable: [["Year", "MVP", "Defensive Player of the Year", "Unsung Hero", "Newcomer of the Year"], ["2008", "Matt Jordan", "Nevio Pizzolitto", "Joey Gjertsen", "Stefano Pesoli"], ["2010", "Philippe Billy", "Philippe Billy", "Tony Donatelli", "Ali Gerba"], ["2003", "Greg Sutton", "Gabriel Gervais", "David Fronimadis", "Martin Nash"], ["2007", "Leonardo Di Lorenzo", "Mauricio Vincello", "Simon Gatti", "Matt Jordan"], ["2011", "Hassoun Camara", "Evan Bush", "Simon Gatti", "Ian Westlake / Sinisa Ubiparipovic"], ["2000", "Jim Larkin", "–", "–", "–"], ["2001", "Mauro Biello", "–", "–", "–"], ["2009", "David Testo", "Nevio Pizzolitto", "Adam Braz", "Stephen deRoux"], ["1998", "Mauro Biello", "–", "–", "–"], ["2004", "Gabriel Gervais", "Greg Sutton", "Zé Roberto", "Sandro Grande"], ["2006", "Mauricio Vincello", "Gabriel Gervais", "Andrew Weber", "Leonardo Di Lorenzo"], ["2002", "Eduardo Sebrango", "Gabriel Gervais", "Jason DiTullio", "Zé Roberto"], ["1993", "Patrice Ferri", "–", "–", "–"], ["1996", "Paolo Ceccarelli", "–", "–", "–"], ["1995", "Lloyd Barker", "–", "–", "–"], ["1997", "Mauro Biello", "–", "–", "–"], ["1999", "N/A", "–", "–", "–"], ["1994", "Jean Harbor", "–", "–", "–"], ["2005", "Mauro Biello", "Nevio Pizzolitto", "Mauricio Vincello", "Masahiro Fukazawa"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who won the most mvp awards? | Mauro Biello | 128 | Answer: |
Table InputTable: [["Season", "Team", "Country", "Division", "Apps", "Goals"], ["2006", "Chengdu Wuniu", "China", "2", "1", "0"], ["2005", "Shandong Luneng", "China", "1", "0", "0"], ["2008", "Jiangsu Sainty", "China", "2", "24", "0"], ["2009", "Jiangsu Sainty", "China", "1", "15", "0"], ["2010", "Jiangsu Sainty", "China", "1", "17", "0"], ["2007", "Shandong Luneng", "China", "1", "0", "0"], ["2004", "Shandong Luneng", "China", "1", "0", "0"], ["2011", "Jiangsu Sainty", "China", "1", "9", "0"], ["2003", "Shandong Luneng", "China", "1", "4", "0"], ["2013", "Jiangsu Sainty", "China", "1", "11", "0"], ["2012", "Jiangsu Sainty", "China", "1", "0", "0"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which season had, at most, 1 app? | 2006 | 128 | Answer: |
Table InputTable: [["Rnd", "Circuit", "GTP Winning Team\\nGTP Winning Drivers", "GTO Winning Team\\nGTO Winning Drivers", "GTU Winning Team\\nGTU Winning Drivers", "Results"], ["4", "Road Atlanta", "#16 Marty Hinze Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["1", "Daytona", "#00 Kreepy Krauly Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["11", "Portland", "#56 Blue Thunder Racing", "#51 Corvette", "#76 Malibu Grand Prix", "Results"], ["8", "Lime Rock", "#00 Kreepy Krauly Racing", "#38 Mandeville Auto Tech", "#76 Malibu Grand Prix", "Results"], ["17", "Daytona", "#14 Holbert Racing", "#67 Roush Racing", "#87 Performance Motorsports", "Results"], ["14", "Pocono", "#14 Holbert Racing", "#65 English Enterprises", "#87 Performance Motorsports", "Results"], ["7", "Charlotte", "#56 Blue Thunder Racing", "#4 Stratagraph Inc.", "#99 All American Racers", "Results"], ["10", "Watkins Glen", "#14 Holbert Racing", "#91 Electrodyne", "#87 Performance Motorsports", "Results"], ["1", "Daytona", "Sarel van der Merwe\\n Graham Duxbury\\n Tony Martin", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Jim Cook\\n Ira Young\\n Bob Reed", "Results"], ["9", "Mid-Ohio", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["2", "Miami", "#04 Group 44", "#47 Dingman Bros. Racing", "#99 All American Racers", "Results"], ["13", "Road America", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["6", "Laguna Seca", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#99 All American Racers", "Results"], ["5", "Riverside", "#56 Blue Thunder Racing", "#38 Mandeville Auto Tech", "#87 Performance Motorsports", "Results"], ["12", "Sears Point", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#98 All American Racers", "Results"], ["15", "Michigan", "#56 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["6", "Laguna Seca", "Randy Lanier", "John Bauer", "Jim Adams", "Results"], ["16", "Watkins Glen", "Dale Whittington\\n Randy Lanier", "Chester Vincentz\\n Jim Mullen", "Clay Young", "Results"], ["3", "Sebring", "#48 DeNarvaez Enterprises", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["16", "Watkins Glen", "#57 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["17", "Daytona", "Al Holbert\\n Derek Bell", "Wally Dallenbach, Jr.\\n Willy T. Ribbs", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["3", "Sebring", "Mauricio DeNarvaez\\n Hans Heyer\\n Stefan Johansson", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed\\n Ira Young", "Results"], ["10", "Watkins Glen", "Al Holbert\\n Jim Adams\\n Derek Bell", "Chester Vincentz\\n Jim Mullen", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["7", "Charlotte", "Bill Whittington\\n Randy Lanier", "Billy Hagan\\n Gene Felton", "Chris Cord\\n Jim Adams", "Results"], ["12", "Sears Point", "Bill Whittington", "John Bauer", "Dennis Aase", "Results"], ["11", "Portland", "Bill Whittington\\n Randy Lanier", "David Schroeder\\n Tom Hendrickson", "Jack Baldwin", "Results"], ["5", "Riverside", "Don Whittington\\n Randy Lanier", "Roger Mandeville\\n Amos Johnson", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["2", "Miami", "Doc Bundy\\n Brian Redman", "Walt Bohren", "Chris Cord", "Results"], ["9", "Mid-Ohio", "Al Holbert\\n Derek Bell", "Chester Vincentz\\n Dave White", "Jack Dunham\\n Jeff Kline", "Results"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:what is the difference in racting number for malibu grand prix and marty hinze racing? | 60 | 128 | Answer: |
Table InputTable: [["Date", "Location", "Air/Ground", "Number", "Type", "Status"], ["13 April 1944", "West of Mannheim, Germany", "Air", "1", "FW-190", "Destroyed"], ["27 November 1944", "South of Magdeburg, Germany", "Air", "4", "FW-190", "Destroyed"], ["24 April 1944", "South of Munich, Germany", "Air", "3", "Me-110", "Destroyed"], ["13 September 1944", "South of Nordhausen, Germany", "Air", "2.5", "Me-109", "Destroyed"], ["8 March 1944", "Near Steinhuder Meer (Lake), Germany", "Air", "1", "Me-109", "Destroyed"], ["16 March 1944", "20 miles south of Stuttgart, Germany", "Air", "1", "Me-110", "Destroyed"], ["18 August 1944", "20 miles northeast of Paris, France", "Air", "0.5", "Me-109", "Destroyed"], ["25 January 1952", "Korea", "Air", "1", "Mig-15", "Damaged"], ["11 April 1944", "20 miles northeast of Magdeburg, Germany", "Air", "0.5", "Me-109", "Destroyed"], ["6 October 1944", "20 miles northwest of Berlin, Germany", "Air", "2", "Me-109", "Destroyed"], ["14 January 1945", "20 miles northwest of Berlin, Germany", "Air", "1", "Me-109", "Destroyed"], ["27 May 1944", "North of Strasbourg, France", "Air", "1", "Me-109", "Damaged"], ["6 October 1944", "20 miles northwest of Berlin, Germany", "Air", "1", "Me-109", "Damaged"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which year has the most destroyed aircrafts? | 1944 | 128 | Answer: |
Table InputTable: [["Round", "Pick", "Name", "Position", "College"], ["7", "223", "James Cotton", "DE", "Ohio State"], ["6", "170", "Frank Murphy", "WR", "Kansas State"], ["4", "125", "Reggie Austin", "DB", "Wake Forest"], ["3", "69", "Dez White", "WR", "Georgia Tech"], ["6", "174", "Paul Edinger", "K", "Michigan State"], ["2", "39", "Mike Brown", "S", "Nebraska"], ["3", "87", "Dustin Lyman", "TE", "Wake Forest"], ["7", "254", "Michael Green", "S", "Northwestern State"], ["1", "9", "Brian Urlacher", "S", "New Mexico"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 player picked after james cotton? | Michael Green | 128 | Answer: |
Table InputTable: [["Location", "Reactor type", "Status", "Net\\nCapacity\\n(MWe)", "Gross\\nCapacity\\n(MWe)"], ["Chernobyl-6", "RBMK-1000", "construction cancelled in 1988", "950", "1,000"], ["Chernobyl-5", "RBMK-1000", "construction cancelled in 1988", "950", "1,000"], ["Kostroma-2", "RBMK-1500", "construction cancelled in 1980s", "1,380", "1,500"], ["Kostroma-1", "RBMK-1500", "construction cancelled in 1980s", "1,380", "1,500"], ["Chernobyl-1", "RBMK-1000", "shut down in 1996", "740", "800"], ["Chernobyl-2", "RBMK-1000", "shut down in 1991", "925", "1,000"], ["Ignalina-4", "RBMK-1500", "plan cancelled in 1988", "1,380", "1,500"], ["Chernobyl-4", "RBMK-1000", "destroyed in the 1986 accident", "925", "1,000"], ["Chernobyl-3", "RBMK-1000", "shut down in 2000", "925", "1,000"], ["Ignalina-3", "RBMK-1500", "construction cancelled in 1988", "1,380", "1,500"], ["Kursk-6", "RBMK-1000", "construction cancelled in 1993", "925", "1,000"], ["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"], ["Leningrad-1", "RBMK-1000", "operational", "925", "1,000"], ["Kursk-2", "RBMK-1000", "operational until 2024", "925", "1,000"], ["Kursk-5", "MKER-1000", "construction begin was 1985, since then shelved", "925", "1,000"], ["Leningrad-4", "RBMK-1000", "operational until August 2026", "925", "1,000"], ["Kursk-4", "RBMK-1000", "operational until February 2016", "925", "1,000"], ["Leningrad-3", "RBMK-1000", "operational until June 2025", "925", "1,000"], ["Leningrad-2", "RBMK-1000", "operational until 2021", "925", "1,000"], ["Kursk-3", "RBMK-1000", "operational until March 2014", "925", "1,000"], ["Kursk-1", "RBMK-1000", "operational until 2021", "925", "1,000"], ["Smolensk-1", "RBMK-1000", "operational until December 2022", "925", "1,000"], ["Smolensk-2", "RBMK-1000", "operational until July 2015", "925", "1,000"], ["Smolensk-3", "RBMK-1000", "operational until July 2023", "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:how many reactors were cancelled in the 1980's? | 6 | 128 | Answer: |
Table InputTable: [["Game", "Day", "Date", "Kickoff", "Opponent", "Results\\nScore", "Results\\nRecord", "Location", "Attendance"], ["8", "Saturday", "January 4", "7:05pm", "at Ontario Fury", "L 5–12", "4–4", "Citizens Business Bank Arena", "2,653"], ["4", "Sunday", "December 1", "1:05pm", "Ontario Fury", "W 18–4", "2–2", "UniSantos Park", "207"], ["2", "Sunday", "November 17", "1:05pm", "Monterrey Flash", "L 6–10", "0–2", "UniSantos Park", "363"], ["5", "Saturday", "December 14", "7:05pm", "at Sacramento Surge", "W 7–6 (OT)", "3–2", "Estadio Azteca Soccer Arena", "215"], ["14", "Friday", "February 7", "7:05pm", "at Turlock Express", "L 6–9", "7–7", "Turlock Soccer Complex", "673"], ["1", "Sunday", "November 10", "3:05pm", "at Las Vegas Legends", "L 3–7", "0–1", "Orleans Arena", "1,836"], ["15", "Saturday", "February 8", "7:05pm", "at Sacramento Surge", "W 10–6", "8–7", "Estadio Azteca Soccer Arena", "323"], ["12", "Sunday", "January 26", "1:05pm", "Sacramento Surge", "W 20–6", "7–5", "UniSantos Park", "224"], ["7", "Sunday", "December 22", "1:05pm", "Turlock Express", "W 16–8", "4–3", "UniSantos Park", "218"], ["6", "Sunday", "December 15", "6:00pm", "at Bay Area Rosal", "L 8–9 (OT)", "3–3", "Cabernet Indoor Sports", "480"], ["13", "Saturday", "February 1", "7:05pm", "at San Diego Sockers", "L 5–6", "7–6", "Valley View Casino Center", "4,954"], ["16", "Saturday", "February 15♥", "5:05pm", "Bay Area Rosal", "W 27–2", "9–7", "UniSantos Park", "118"], ["9", "Sunday", "January 5", "1:05pm", "San Diego Sockers", "L 7–12", "4–5", "UniSantos Park", "388"], ["3", "Saturday", "November 23", "7:05pm", "at Bay Area Rosal", "W 10–7", "1–2", "Cabernet Indoor Sports", "652"], ["11", "Sunday", "January 19", "1:05pm", "Bay Area Rosal", "W 17–7", "6–5", "UniSantos Park", "219"], ["10", "Sunday", "January 12", "1:05pm", "Las Vegas Legends", "W 10–7", "5–5", "UniSantos Park", "343"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 opponent did this team play against after playing the ontario fury on december 1 of this season? | Sacramento Surge | 128 | Answer: |
Table InputTable: [["Season", "Episodes", "Season Premiere", "Season Finale"], ["4", "48", "October 13, 2008", "May 11, 2009"], ["3", "44", "October 15, 2007", "June 2, 2008"], ["2", "52", "October 7, 2006", "July 16, 2007"], ["7", "8", "October 29, 2013", "December 17, 2013"], ["5", "40", "October 12, 2009", "June 14, 2010"], ["1", "20", "March 4, 2006", "May 13, 2006"], ["6", "20", "September 6, 2010", "December 6, 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:what season had the least number of episodes? | 7 | 128 | Answer: |
Table InputTable: [["Position", "Player", "Transferred From", "Date"], ["DF", "Winston Yap", "Sengkang Punggol", "1 January 2010"], ["DF", "Kazuki Yoshino", "Albirex Niigata (S)", "1 January 2010"], ["MF", "Guntur Djafril", "SAFFC", "1 January 2010"], ["MF", "Syed Karim", "SAFFC", "1 January 2010"], ["DF", "Sahairi Ramri", "Balestier Khalsa", "1 January 2010"], ["MF", "Mohd Noor Ali", "Geylang United", "1 January 2010"], ["GK", "Fajar Sarib", "Geylang United", "1 January 2010"], ["FW", "Laakkad Abdelhadi", "Free Transfer", "1 January 2010"], ["FW", "Rizawan Abdullah", "Balestier Khalsa", "1 January 2010"], ["MF", "Sazali Salleh", "Sengkang Punggol", "1 January 2010"], ["MF", "Rachid Lajane", "Raja Al Hoceima", "26 February 2010"], ["GK", "Hafez Mawasi", "Balestier Khalsa", "1 January 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:what are the total number of times df is listed as the position? | 3 | 128 | Answer: |
Table InputTable: [["No", "Name", "Code", "Formed", "Headquarters", "Administrative\\nDivision", "Area (km2)", "Population\\n(2001 census)", "% of State\\nPopulation", "Density\\n(per km2)", "Urban (%)", "Literacy (%)", "Sex Ratio", "Tehsils", "Source"], ["22", "Nashik", "NS", "1 May 1960", "Nashik", "Nashik", "15,530", "4,993,796", "5.15%", "321.56", "38.8", "74.4", "927", "15", "District website"], ["32", "Thane", "TH", "1 May 1960", "Thane", "Konkan", "9,558", "8,131,849", "8.39%", "850.71", "72.58", "80.67", "858", "15", "District website"], ["34", "Washim", "WS", "1 July 1998", "Washim", "Amravati", "5,150", "1,020,216", "1.05%", "275.98", "17.49", "74.02", "939", "6", "District website"], ["3", "Amravati", "AM", "1 May 1960", "Amravati", "Amravati", "12,626", "2,606,063", "2.69%", "206.40", "34.50", "82.5", "938", "14", "District website"], ["9", "Dhule", "DH", "1 May 1960", "Dhule", "Nashik", "8,063", "1,707,947", "1.76%", "211.83", "26.11", "71.6", "944", "4", "District website"], ["7", "Buldhana", "BU", "1 May 1960", "Buldhana", "Amravati", "9,680", "2,232,480", "2.3%", "230.63", "21.2", "75.8", "946", "13", "District website"], ["5", "Beed", "BI", "1 May 1960", "Beed", "Aurangabad", "10,439", "2,161,250", "2.23%", "207.04", "17.91", "68", "936", "11", "District website"], ["13", "Jalgaon", "JG", "1 May 1960", "Jalgaon", "Nashik", "11,765", "3,679,936", "3.8%", "312.79", "71.4", "76.06", "932", "15", "District website"], ["33", "Wardha", "WR", "1 May 1960", "Wardha", "Nagpur", "6,310", "1,230,640", "1.27%", "195.03", "25.17", "80.5", "936", "8", "District website"], ["35", "Yavatmal", "YA", "1 May 1960", "Yavatmal", "Amravati", "13,582", "2,077,144", "2.14%", "152.93", "18.6", "57.96", "951", "16", "District website"], ["1", "Ahmednagar", "AH", "1 May 1960", "Ahmednagar", "Nashik", "17,413", "4,088,077", "4.22%", "234.77", "19.67", "75.82", "941", "14", "District website"], ["24", "Parbhani", "PA", "1 May 1960", "Parbhani", "Aurangabad", "6,251", "1,527,715", "1.58%", "244.4", "31.8", "55.15", "958", "9", "District website"], ["2", "Akola", "AK", "1 May 1960", "Akola", "Amravati", "5,417", "1,818,617", "1.68%", "300.78", "38.49", "81.41", "938", "7", "District website"], ["25", "Pune", "PU", "1 May 1960", "Pune", "Pune", "15,642", "7,224,224", "7.46%", "461.85", "58.1", "80.78", "919", "14", "District website"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many districts have more than 75% literacy? | 15 | 128 | Answer: |
Table InputTable: [["Round", "Pick", "Name", "Position", "College"], ["6", "170", "Frank Murphy", "WR", "Kansas State"], ["4", "125", "Reggie Austin", "DB", "Wake Forest"], ["3", "87", "Dustin Lyman", "TE", "Wake Forest"], ["6", "174", "Paul Edinger", "K", "Michigan State"], ["7", "223", "James Cotton", "DE", "Ohio State"], ["3", "69", "Dez White", "WR", "Georgia Tech"], ["7", "254", "Michael Green", "S", "Northwestern State"], ["2", "39", "Mike Brown", "S", "Nebraska"], ["1", "9", "Brian Urlacher", "S", "New Mexico"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many players were drafted from wake forest college according to this chart? | 2 | 128 | Answer: |
Table InputTable: [["Language", "2001 census[1]\\n(total population 1,004.59 million)", "1991 censusIndian Census [2]\\n(total population 838.14 million)", "1991 censusIndian Census [2]\\n(total population 838.14 million)", ""], ["Hindi", "422,048,642", "337,272,114", "40.0%", "336 M"], ["Bengali", "230,000,000", "200,595,738", "28.30%", "320 M"], ["Assamese", "13,168,484", "13,079,696", "1.56%", "15.4 M"], ["Urdu", "51,536,111", "43,406,932", "5.18%", "60.3 M"], ["Punjabi", "130,000,000", "100,017,615", "20.87%", "113 M"], ["Nepali", "23,017,446", "28,061,313", "3.35%", "32.3 M"], ["Marathi", "71,936,894", "62,481,681", "7.45%", "68.0 M"], ["Kannada", "37,924,011", "32,753,676", "3.91%", "40.3 M"], ["Telugu", "70,002,856", "65,595,738", "8.30%", "70 M"], ["Gujarati", "46,091,617", "40,673,814", "4.85%", "46.1 M"], ["Tamil", "60,793,814", "53,006,368", "6.32%", "66.0 M"], ["Malayalam", "33,066,392", "30,377,176", "3.62%", "35.7 M"], ["Maithili", "12,179,122", "1.18%", "", ""], ["Sindhi", "25,535,485", "25,122,848", "0.248%", "32.3 M"], ["Kashmiri", "5,527,698", "0.54%", "", ""], ["Oriya", "33,017,446", "28,061,313", "3.35%", "32.3 M"], ["Meitei (Manipuri)", "1,466,705*", "0.14%", "1,270,216", "0.151%"], ["Sinhalese", "19,017,446", "28,061,313", "3.35%", "32.3 M"], ["Mundari", "1,061,352", "0.105%", "", ""], ["Khandeshi", "2,075,258", "0.21%", "", ""], ["Kurukh", "1,751,489", "0.17%", "1,426,618", "0.170%"], ["Bhili/Bhilodi", "9,582,957", "5,572,308", "0.665%", ""], ["Khasi", "1,128,575", "0.112%", "", ""], ["Konkani", "2,489,015", "1,760,607", "0.210%", ""], ["", "Speakers", "Speakers", "Percentage", ""], ["Tulu", "1,722,768", "0.17%", "1,552,259", "0.185%"], ["Santali", "6,469,600", "5,216,325", "0.622%", ""], ["Bodo", "1,350,478", "0.13%", "1,221,881", "0.146%"], ["Ho", "1,042,724", "0.103%", "", ""], ["Dogri", "2,282,589[dubious – discuss]", "0.22%", "", ""], ["Gondi", "2,713,790", "2,124,852", "0.253%", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 language has the most speakers after hindi? | Bengali | 128 | Answer: |
Table InputTable: [["Season", "Club", "Competition", "Games", "Goals"], ["2008/09", "Excelsior Mouscron", "Jupiler League", "31", "1"], ["2009/10", "Győri ETO FC", "Soproni Liga", "1", "0"], ["2009/10", "Excelsior Mouscron", "Jupiler League", "14", "1"], ["2005/06", "KSV Roeselare", "Jupiler League", "26", "0"], ["2004/05", "KSV Roeselare", "Belgian Second Division", "29", "1"], ["2007/08", "KSV Roeselare", "Jupiler League", "25", "0"], ["2002/03", "RAEC Mons", "Jupiler League", "19", "0"], ["2006/07", "KSV Roeselare", "Jupiler League", "29", "1"], ["2003/04", "RAEC Mons", "Jupiler League", "23", "0"], ["2010/11", "Kortrijk", "Jupiler League", "0", "0"], ["", "", "Totaal", "278", "4"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 club did chemcedine el araichi play for before excelsior mouscron? | KSV Roeselare | 128 | Answer: |
Table InputTable: [["Rank", "Cyclist", "Team", "Time", "UCI ProTour\\nPoints"], ["1", "Alejandro Valverde (ESP)", "Caisse d'Epargne", "5h 29' 10\"", "40"], ["5", "Franco Pellizotti (ITA)", "Liquigas", "s.t.", "15"], ["4", "Paolo Bettini (ITA)", "Quick Step", "s.t.", "20"], ["8", "Stéphane Goubert (FRA)", "Ag2r-La Mondiale", "+ 2\"", "5"], ["2", "Alexandr Kolobnev (RUS)", "Team CSC Saxo Bank", "s.t.", "30"], ["10", "David Moncoutié (FRA)", "Cofidis", "+ 2\"", "1"], ["7", "Samuel Sánchez (ESP)", "Euskaltel-Euskadi", "s.t.", "7"], ["9", "Haimar Zubeldia (ESP)", "Euskaltel-Euskadi", "+ 2\"", "3"], ["6", "Denis Menchov (RUS)", "Rabobank", "s.t.", "11"], ["3", "Davide Rebellin (ITA)", "Gerolsteiner", "s.t.", "25"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 uci pro tour points scored by an italian cyclist? | 60 | 128 | Answer: |
Table InputTable: [["Year", "Class", "No", "Tyres", "Car", "Team", "Co-Drivers", "Laps", "Pos.", "Class\\nPos."], ["1978", "S\\n+2.0", "10", "", "Mirage M9\\nRenault 2.0L Turbo V6", "Grand Touring Cars Inc.", "Vern Schuppan\\n Sam Posey", "293", "10th", "5th"], ["1974", "S\\n3.0", "15", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Alain Serpaggi", "310", "8th", "5th"], ["1994", "GT2", "49", "P", "Porsche 911 Carrera RSR\\nPorsche 3.8 L Flat-6", "Larbre Compétition", "Jacques Alméras\\n Jean-Marie Alméras", "94", "DNF", "DNF"], ["1977", "S\\n+2.0", "8", "", "Renault Alpine A442\\nRenault 2.0L Turbo V6", "Renault Sport", "Patrick Depailler", "289", "DNF", "DNF"], ["1972", "S\\n3.0", "22", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Pierre Maublanc", "195", "DNF", "DNF"], ["1996", "GT1", "38", "M", "McLaren F1 GTR\\nBMW S70 6.1L V12", "Team Bigazzi SRL", "Steve Soper\\n Marc Duez", "318", "11th", "9th"], ["1993", "GT", "71", "D", "Venturi 500LM\\nRenault PRV 3.0 L Turbo V6", "Jacadi Racing", "Michel Maisonneuve\\n Christophe Dechavanne", "210", "DNF", "DNF"], ["1990", "C1", "6", "G", "Porsche 962C\\nPorsche Type-935 3.0L Turbo Flat-6", "Joest Porsche Racing", "Henri Pescarolo\\n Jean-Louis Ricci", "328", "14th", "14th"], ["1973", "S\\n3.0", "62", "", "Ligier JS2\\nMaserati 3.0L V6", "Automobiles Ligier", "Guy Ligier", "24", "DSQ", "DSQ"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many of each type of car are there? | 13 | 128 | Answer: |
Table InputTable: [["Conference", "# of Bids", "Record", "Win %", "Round\\nof 32", "Sweet\\nSixteen", "Elite\\nEight", "Final\\nFour", "Championship\\nGame"], ["Western Athletic", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["West Coast", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Mid-Continent", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Big East", "2", "5–2", ".714", "2", "2", "1", "–", "–"], ["Big Ten", "5", "9–5", ".643", "4", "2", "2", "1", "–"], ["Great Midwest", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Southeastern", "6", "10–6", ".625", "5", "3", "1", "1", "–"], ["Big Eight", "4", "3–4", ".429", "2", "1", "–", "–", "–"], ["Big West", "2", "0–2", "–", "–", "–", "–", "–", "–"], ["Southwest", "4", "5–4", ".556", "3", "2", "–", "–", "–"], ["Sun Belt", "2", "6–2", ".750", "2", "1", "1", "1", "1"], ["Atlantic Coast", "3", "9–2", ".818", "3", "2", "1", "1", "1"], ["Missouri Valley", "2", "2–2", ".500", "2", "–", "–", "–", "–"], ["Metro", "2", "2–2", ".500", "1", "1", "–", "–", "–"], ["Atlantic 10", "3", "1–3", ".250", "1", "–", "–", "–", "–"], ["Colonial", "1", "1–1", ".500", "1", "–", "–", "–", "–"], ["Pacific-10", "5", "8–5", ".615", "4", "2", "2", "–", "–"], ["Big Sky", "2", "1–2", ".333", "1", "–", "–", "–", "–"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:which team had the top win % out of the group? | Atlantic Coast | 128 | Answer: |
Table InputTable: [["Series", "Name", "Age", "Hometown", "Occupation", "Status"], ["BB1", "Anna Nolan", "29", "Dublin", "Office Manager", "2nd - Runner-up"], ["BB8", "Amanda Marchant", "18", "Stoke-on-Trent", "Student", "2nd - Runner-up"], ["UBB", "Chantelle Houghton", "27", "Essex", "Participated in CBB5", "3rd - Third Place"], ["BB8", "Sam Marchant", "18", "Stoke-on-Trent", "Student", "2nd - Runner-up"], ["TBB", "Paul Brennan", "18", "Belfast", "Student", "1st - Winner"], ["UBB", "Nikki Grahame", "28", "London", "Participated in BB7", "2nd - Runner-up"], ["BB2", "Helen Adams", "22", "South Wales", "Hairdresser", "2nd - Runner-up"], ["TBB", "Caroline Cloke", "18", "Kent", "Student", "2nd - Runner-up"], ["BB9", "Rachel Rice", "24", "Torfaen", "Trainee Teacher/Actress", "1st - Winner"], ["BB13", "Adam Kelly", "27", "Dudley", "Unemployed", "2nd - Runner-up"], ["BB6", "Anthony Hutton", "23", "Newcastle", "70s Dancer", "1st - Winner"], ["UBB", "Brian Dowling", "32", "County Kildare", "Participated in BB2", "1st - Winner"], ["BB3", "Jonny Regan", "29", "County Durham", "Firefighter", "2nd - Runner-up"], ["BB2", "Brian Dowling", "22", "County Kildare", "Air Steward", "1st - Winner"], ["BB9", "Mikey (Michael) Hughes", "33", "Glasgow", "Radio Producer", "2nd - Runner-up"], ["BB7", "Aisleyne Horgan-Wallace", "27", "London", "Model/Promotions Girl", "3rd - Third Place"], ["BB:CH", "Emilia Arata", "18", "Birmingham", "Circus Performer", "2nd - Runner-up"], ["BB10", "Sophie (Dogface) Reade", "20", "Cheshire", "Model", "1st - Winner"], ["BB11", "Josie Gibson", "25", "Bristol", "Financial sales rep", "1st - Winner"], ["BBP", "Jade Goody", "23", "London", "Participated in BB3", "Not competing"], ["UBB", "Josie Gibson", "25", "Bristol", "Participated in BB11", "14th - Walked"], ["TBB", "Tracey Fowler", "18", "Cheshire", "Student", "3rd - Third Place"], ["BB7", "Glyn Wise", "18", "North Wales", "Student/Lifeguard", "2nd - Runner-up"], ["BB13", "Luke Anderson", "31", "North Wales", "Development chef", "1st - Winner"], ["BB14", "Hazel O'Sullivan", "24", "Dublin", "Glamour Model", "7th - Evicted"], ["BB3", "Kate Lawler", "22", "London", "Technical support administrator", "1st - Winner"], ["BB14", "Dexter Koh", "28", "London", "Celebrity publicist", "2nd - Runner-up"], ["BB6", "Eugene Sully", "27", "Crawley", "Student", "2nd - Runner-up"], ["BB3", "Alex Sibley", "23", "London", "Model", "3rd - Third Place"], ["BB4", "Ray Shah", "25", "Dublin", "IT Systems Administrator", "2nd - Runner-up"], ["BBP", "Anouska Golebiewski", "22", "Manchester", "Participated in BB4", "Not competing"], ["BBP", "Spencer Smith", "25", "Cambridge", "Participated in BB3", "Not competing"], ["BB5", "Jason Cowan", "30", "South Lanarkshire", "Air Steward", "2nd - Runner-up"], ["BB14", "Gina Rio", "24", "London", "Socialite", "3rd - Third Place"], ["BB8", "Liam McGough", "22", "County Durham", "Tree Surgeon", "3rd - Third Place"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who was the next contestant to come from ireland after anna nolan? | Brian Dowling | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "3.", "21 May 2006", "Hamburg Masters, Hamburg, Germany", "Clay", "Radek Štěpánek", "6–1, 6–3, 6–3"], ["Winner", "1.", "29 July 2001", "Orange Warsaw Open, Sopot, Poland", "Clay", "Albert Portas", "1–6, 7–5, 7–6(7–2)"], ["Winner", "10.", "6 February 2011", "Chile Open, Santiago, Chile", "Clay", "Santiago Giraldo", "6–2, 2–6, 7–6(7–5)"], ["Winner", "4.", "16 July 2006", "Swedish Open, Båstad, Sweden", "Clay", "Nikolay Davydenko", "6–2, 6–1"], ["Runner-up", "3.", "1 May 2005", "Estoril Open, Estoril, Portugal", "Clay", "Gastón Gaudio", "1–6, 6–2, 1–6"], ["Winner", "2.", "2 May 2004", "Torneo Godó, Barcelona, Spain", "Clay", "Gastón Gaudio", "6–3, 4–6, 6–2, 3–6, 6–3"], ["Winner", "11.", "14 April 2013", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Kevin Anderson", "7–6(8–6), 4–6, 6–3"], ["Runner-up", "7.", "15 June 2008", "Orange Warsaw Open, Warsaw, Poland", "Clay", "Nikolay Davydenko", "3–6, 3–6"], ["Winner", "5.", "5 August 2007", "Orange Warsaw Open, Sopot, Poland (2)", "Clay", "José Acasuso", "7–5, 6–0"], ["Runner-up", "1.", "15 April 2001", "Grand Prix Hassan II, Casablanca, Morocco", "Clay", "Guillermo Cañas", "5–7, 2–6"], ["Runner-up", "4.", "30 April 2006", "Torneo Godó, Barcelona, Spain", "Clay", "Rafael Nadal", "4–6, 4–6, 0–6"], ["Winner", "7.", "13 July 2008", "Swedish Open, Båstad, Sweden (2)", "Clay", "Tomáš Berdych", "6–4, 6–1"], ["Winner", "12.", "28 July 2013", "ATP Vegeta Croatia Open Umag, Umag, Croatia", "Clay", "Fabio Fognini", "6–0, 6–3"], ["Runner-up", "5.", "14 January 2007", "Heineken Open, Auckland, New Zealand", "Hard", "David Ferrer", "4–6, 2–6"], ["Winner", "6.", "7 October 2007", "Open de Moselle, Metz, France", "Hard (i)", "Andy Murray", "0–6, 6–2, 6–3"], ["Winner", "8.", "14 February 2009", "Brasil Open, Costa do Sauípe, Brazil", "Clay", "Thomaz Bellucci", "6–3, 3–6, 6–4"], ["Runner-up", "2.", "20 July 2003", "Mercedes Cup, Stuttgart, Germany", "Clay", "Guillermo Coria", "2–6, 2–6, 1–6"], ["Runner-up", "6.", "16 September 2007", "China Open, Beijing, China", "Hard (i)", "Fernando González", "1–6, 6–3, 1–6"], ["Winner", "9.", "22 February 2009", "Copa Telmex, Buenos Aires, Argentina", "Clay", "Juan Mónaco", "7–5, 2–6, 7–6(7–5)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:were the number of clay surfaces above or below the number of hard surfaces? | above | 128 | Answer: |
Table InputTable: [["Year", "Single", "Peak chart positions\\nAUS", "Peak chart positions\\nAUT", "Peak chart positions\\nBEL\\n(Fl)", "Peak chart positions\\nBEL\\n(Wa)", "Peak chart positions\\nFIN", "Peak chart positions\\nFRA", "Peak chart positions\\nGER", "Peak chart positions\\nNED", "Peak chart positions\\nSWE", "Peak chart positions\\nSUI", "Certifications\\n(sales thresholds)", "Album"], ["2000", "\"Around the World (La La La La La)\"", "11", "1", "10", "10", "7", "12", "1", "5", "8", "1", "GER: Platinum\\nAUT: Gold\\nSWI: Gold\\nFRA: Silver", "Planet Pop"], ["2000", "\"My Heart Beats Like a Drum (Dam Dam Dam)\"", "76", "6", "11", "3", "12", "39", "3", "37", "38", "21", "GER: Gold", "Planet Pop"], ["2000", "\"Why Oh Why\"", "—", "16", "39", "15", "—", "—", "16", "—", "—", "—", "", "Planet Pop"], ["2000", "\"Thinking of You\"", "—", "—", "—", "—", "—", "—", "46", "—", "—", "51", "", "Planet Pop"], ["2001", "\"I'm In Heaven (When You Kiss Me)\"", "—", "27", "—", "—", "—", "—", "22", "—", "—", "31", "", "Touch the Sky"], ["2001", "\"New York City\"", "—", "—", "—", "—", "—", "—", "—", "—", "—", "—", "", "Touch the Sky"], ["2001", "\"Set Me Free\"", "—", "—", "—", "—", "—", "—", "44", "—", "—", "—", "", "Touch the Sky"], ["2001", "\"Call on Me\"", "—", "—", "—", "—", "—", "—", "—", "—", "—", "—", "", "Touch the Sky"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 singles had a gold certification? | 2 | 128 | Answer: |
Table InputTable: [["Fence", "Name", "Jockey", "Age", "Handicap (st-lb)", "Starting price", "Fate"], ["22", "Ballygowan", "A Redmond", "11", "10-13", "66/1", "Refused"], ["?", "Fearless Cavalier", "R West", "14", "10-13", "100/1", "Refused"], ["22", "Kapeno", "David Dick", "8", "11-6", "100/8", "Fell"], ["06", "Forgotten Dreams", "R Coonan", "11", "11-0", "22/1", "Fell"], ["06", "Nedsmar", "John Hudson", "11", "10-13", "100/1", "Fell"], ["26", "Rondetto", "Jeff King", "9", "11-6", "100/8", "Fell"], ["?", "Black Spot", "J Gamble", "8", "10-13", "100/1", "Fell"], ["?", "French Cottage", "Mr WA Tellwright", "13", "10-13", "100/1", "Refused"], ["08", "Coleen Star", "Johnny Leech", "11", "10-13", "100/1", "Refused"], ["18", "Leedsy", "George Robinson", "7", "10-13", "18/1", "Fell"], ["24", "Pontin-Go", "Johnny Lehane", "13", "10-13", "50/1", "Fell"], ["01", "Ayala", "Stan Mellor", "11", "10-13", "50/1", "Fell"], ["?", "Solonace", "RW Jones", "13", "10-13", "100/1", "Pulled Up"], ["17", "Bold Biri", "Michael Scudamore", "9", "10-13", "100/1", "Fell"], ["06", "Barleycroft", "Phil Harvey", "10", "10-13", "100/1", "Brought Down"], ["?", "Leslie", "P Jones", "9", "10-13", "33/1", "Pulled Up"], ["09", "Groomsman", "Beltrán Osorio", "10", "10-13", "100/1", "Fell"], ["04", "Red Tide", "Johnny Haine", "8", "10-13", "33/1", "Fell"], ["?", "Vulcano", "Tommy Carberry", "7", "10-13", "50/1", "Pulled Up"], ["?", "Blonde Warrior", "Mr D Crossley-Cooke", "13", "10-13", "100/1", "Fell"], ["06", "Crobeg", "Mr Macer Gifford", "12", "10-13", "100/1", "Brought Down"], ["?", "Reproduction", "Robin Langley", "12", "10-13", "40/1", "Pulled-Up"], ["10", "Dark Venetian", "Jim Renfree", "10", "10-13", "100/1", "Fell"], ["?", "Quintin Bay", "Pat Taaffe", "9", "10-13", "25/1", "Pulled Up"], ["06", "Sizzle-On", "P Hurley", "9", "10/13", "100/1", "Brought Down"], ["04", "Cutlette", "M Roberts", "8", "10-13", "50/1", "Pulled Up"], ["?", "Sword Flash", "T Ryan", "12", "10-13", "100/1", "Pulled Up"], ["?", "Mr McTaffy", "T Jackson", "13", "10-13", "100/1", "Pulled Up"], ["?", "Time", "Mr Brough Scott", "10", "10-13", "40/1", "Fell"], ["13", "Phebu", "J Morrissey", "8", "10-13", "33/1", "Brought Down"], ["06", "Ruby Glen", "Stephen Davenport", "10", "10-13", "33/1", "Brought Down"], ["03", "Ronald's Boy", "Mr Gay Kindersley", "8", "11-1", "100/1", "Fell"], ["?", "Lizawake", "Mr George Hartigan", "12", "10-13", "100/1", "Pulled 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:how many more competitors fell than refused? | 11 | 128 | Answer: |
Table InputTable: [["Date of Incident", "Offender", "Team", "Offense", "Date of Action", "Length"], ["March 8, 2012", "Mike Green", "Washington Capitals", "Illegal hit to the head of Brett Connolly.", "March 9, 2012", "3 games"], ["May 6, 2012", "Claude Giroux", "Philadelphia Flyers", "Illegal hit to the head of Dainius Zubrus.", "May 7, 2012", "1 game‡ (1 post-season)"], ["January 14, 2012", "Dane Byers", "Columbus Blue Jackets", "Illegal hit to the head of Andrew Desjardins.", "January 16, 2012", "3 games"], ["April 17, 2012", "Raffi Torres", "Phoenix Coyotes", "Late charge to the head of Marian Hossa.", "April 21, 2012", "25 games\\nreduced to 21 games‡ (13 post-season)*"], ["January 8, 2012", "Jean-Francois Jacques", "Anaheim Ducks", "Illegal hit to the head of R.J. Umberger.", "January 9, 2012", "3 games"], ["April 1, 2012", "Kyle Quincey", "Detroit Red Wings", "Charging Tomas Kopecky.", "April 2, 2012", "1 game"], ["April 14, 2012", "Andrew Shaw", "Chicago Blackhawks", "Charging goaltender Mike Smith.", "April 17, 2012", "3 games‡ (3 post-season)"], ["December 31, 2011", "Ian Cole", "St. Louis Blues", "Illegal hit to the head of Justin Abdelkader.", "January 1, 2012", "3 games"], ["November 23, 2011", "Andre Deveaux", "New York Rangers", "Illegal hit to the head of Tomas Fleischmann.", "November 23, 2011", "3 games"], ["April 15, 2012", "Craig Adams", "Pittsburgh Penguins", "Instigator penalty in the last five minutes of a game.", "April 16, 2012", "1 game‡ (1 post-season)"], ["April 5, 2012", "Nate Prosser", "Minnesota Wild", "Head-butting Jamal Mayers.", "April 6, 2012", "1 game"], ["April 15, 2012", "James Neal", "Pittsburgh Penguins", "Charging Claude Giroux.", "April 17, 2012", "1 game‡ (1 post-season)"], ["April 14, 2012", "Carl Hagelin", "New York Rangers", "Elbowing Daniel Alfredsson.", "April 15, 2012", "3 games‡ (3 post-season)"], ["April 14, 2012", "Matt Carkner", "Ottawa Senators", "Aggressing an unwilling Brian Boyle.", "April 15, 2012", "1 game‡ (1 post-season)"], ["April 14, 2012", "Nicklas Backstrom", "Washington Capitals", "Cross-checking Rich Peverley.", "April 17, 2012", "1 game‡ (1 post-season)"], ["December 20, 2011", "Deryk Engelland", "Pittsburgh Penguins", "Illegal hit to the head of Marcus Kruger.", "December 22, 2011", "3 games"], ["April 15, 2012", "Arron Asham", "Pittsburgh Penguins", "Cross-checking Brayden Schenn.", "April 17, 2012", "4 games‡ (3 post-season)*"], ["April 11, 2012", "Byron Bitz", "Vancouver Canucks", "Boarding Kyle Clifford.", "April 12, 2012", "2 games‡ (2 post-season)"], ["September 23, 2011", "James Wisniewski", "Columbus Blue Jackets", "Illegal hit to the head of Cal Clutterbuck.", "September 24, 2011", "12 games† (4 pre-season, 8 regular season)"], ["March 20, 2012", "Shane Doan", "Phoenix Coyotes", "Elbowing Jamie Benn.", "March 21, 2012", "3 games"], ["November 26, 2011", "Max Pacioretty", "Montreal Canadiens", "Illegal hit to the head of Kris Letang.", "November 28, 2011", "3 games"], ["September 28, 2011", "Brendan Smith", "Detroit Red Wings", "Illegal hit to the head of Ben Smith.", "September 30, 2011", "8 games† (3 pre-season, 5 regular season)"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 offenses occurred after april 21, 2012? | 4 | 128 | Answer: |
Table InputTable: [["Rnd", "Circuit", "GTP Winning Team\\nGTP Winning Drivers", "GTO Winning Team\\nGTO Winning Drivers", "GTU Winning Team\\nGTU Winning Drivers", "Results"], ["14", "Pocono", "#14 Holbert Racing", "#65 English Enterprises", "#87 Performance Motorsports", "Results"], ["1", "Daytona", "Sarel van der Merwe\\n Graham Duxbury\\n Tony Martin", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Jim Cook\\n Ira Young\\n Bob Reed", "Results"], ["17", "Daytona", "#14 Holbert Racing", "#67 Roush Racing", "#87 Performance Motorsports", "Results"], ["10", "Watkins Glen", "#14 Holbert Racing", "#91 Electrodyne", "#87 Performance Motorsports", "Results"], ["16", "Watkins Glen", "Dale Whittington\\n Randy Lanier", "Chester Vincentz\\n Jim Mullen", "Clay Young", "Results"], ["5", "Riverside", "#56 Blue Thunder Racing", "#38 Mandeville Auto Tech", "#87 Performance Motorsports", "Results"], ["6", "Laguna Seca", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#99 All American Racers", "Results"], ["1", "Daytona", "#00 Kreepy Krauly Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["12", "Sears Point", "#56 Blue Thunder Racing", "#77 Brooks Racing", "#98 All American Racers", "Results"], ["2", "Miami", "#04 Group 44", "#47 Dingman Bros. Racing", "#99 All American Racers", "Results"], ["7", "Charlotte", "#56 Blue Thunder Racing", "#4 Stratagraph Inc.", "#99 All American Racers", "Results"], ["4", "Road Atlanta", "#16 Marty Hinze Racing", "#4 Stratagraph Inc.", "#76 Malibu Grand Prix", "Results"], ["16", "Watkins Glen", "#57 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["15", "Michigan", "#56 Blue Thunder Racing", "#91 Electrodyne", "#84 Dole Racing", "Results"], ["13", "Road America", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["3", "Sebring", "Mauricio DeNarvaez\\n Hans Heyer\\n Stefan Johansson", "Terry Labonte\\n Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed\\n Ira Young", "Results"], ["6", "Laguna Seca", "Randy Lanier", "John Bauer", "Jim Adams", "Results"], ["11", "Portland", "#56 Blue Thunder Racing", "#51 Corvette", "#76 Malibu Grand Prix", "Results"], ["9", "Mid-Ohio", "#14 Holbert Racing", "#91 Electrodyne", "#66 Mike Meyer Racing", "Results"], ["10", "Watkins Glen", "Al Holbert\\n Jim Adams\\n Derek Bell", "Chester Vincentz\\n Jim Mullen", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["17", "Daytona", "Al Holbert\\n Derek Bell", "Wally Dallenbach, Jr.\\n Willy T. Ribbs", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["8", "Lime Rock", "#00 Kreepy Krauly Racing", "#38 Mandeville Auto Tech", "#76 Malibu Grand Prix", "Results"], ["13", "Road America", "Al Holbert\\n Derek Bell", "Chester Vincentz\\n Jim Mullen", "Jack Dunham\\n Jeff Kline", "Results"], ["7", "Charlotte", "Bill Whittington\\n Randy Lanier", "Billy Hagan\\n Gene Felton", "Chris Cord\\n Jim Adams", "Results"], ["14", "Pocono", "Al Holbert\\n Derek Bell", "Gene Felton", "Elliot Forbes-Robinson\\n John Schneider", "Results"], ["11", "Portland", "Bill Whittington\\n Randy Lanier", "David Schroeder\\n Tom Hendrickson", "Jack Baldwin", "Results"], ["4", "Road Atlanta", "Don Whittington", "Billy Hagan\\n Gene Felton", "Jack Baldwin\\n Bob Reed", "Results"], ["9", "Mid-Ohio", "Al Holbert\\n Derek Bell", "Chester Vincentz\\n Dave White", "Jack Dunham\\n Jeff Kline", "Results"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who is the first driver listed for performance motorsports? | Elliot Forbes-Robinson | 128 | Answer: |
Table InputTable: [["", "Name on the Register", "Date listed", "Location", "City or town", "Summary"], ["32", "Strafford Union Academy", "September 22, 1983\\n(#83001155)", "NH 126 and NH 202A\\n43°16′07″N 71°07′23″W / 43.268611°N 71.123056°W", "Strafford", ""], ["33", "Gen. John Sullivan House", "November 28, 1972\\n(#72000089)", "23 Newmarket Rd.\\n43°07′48″N 70°55′05″W / 43.13°N 70.918056°W", "Durham", "Home of American Revolutionary War General John Sullivan, elected President of New Hampshire."], ["31", "Strafford County Farm", "February 25, 1981\\n(#81000100)", "County Farm Rd.\\n43°13′03″N 70°56′31″W / 43.2175°N 70.941944°W", "Dover", ""], ["18", "Plumer-Jones Farm", "March 23, 1979\\n(#79000212)", "North of Milton on NH 125\\n43°27′44″N 70°59′37″W / 43.462222°N 70.993611°W", "Milton", ""], ["27", "Salmon Falls Mill Historic District", "February 29, 1980\\n(#80000315)", "Front St.\\n43°14′10″N 70°49′05″W / 43.236111°N 70.818056°W", "Rollinsford", ""], ["7", "First Parish Church Site-Dover Point", "May 27, 1983\\n(#83001153)", "Dover Point Rd.\\n43°08′26″N 70°50′21″W / 43.140556°N 70.839167°W", "Dover", ""], ["6", "First Parish Church", "March 11, 1982\\n(#82001696)", "218 Central Ave.\\n43°10′56″N 70°52′27″W / 43.182222°N 70.874167°W", "Dover", ""], ["15", "Milton Town House", "November 26, 1980\\n(#80000311)", "NH 125 and Town House Rd.\\n43°26′27″N 70°59′05″W / 43.440833°N 70.984722°W", "Milton", ""], ["34", "Thompson Hall", "December 6, 1996\\n(#96001468)", "Off Main St., University of New Hampshire campus\\n43°08′09″N 70°55′59″W / 43.135833°N 70.933056°W", "Durham", ""], ["3", "County Farm Bridge", "May 21, 1975\\n(#75000237)", "Northwest of Dover on County Farm Rd.\\n43°13′14″N 70°56′38″W / 43.220556°N 70.943889°W", "Dover", "Over Cocheco River"], ["29", "Sawyer Woolen Mills", "September 13, 1989\\n(#89001208)", "1 Mill St.\\n43°10′44″N 70°52′35″W / 43.178889°N 70.876389°W", "Dover", ""], ["11", "William Hale House", "November 18, 1980\\n(#80000309)", "5 Hale St.\\n43°11′36″N 70°52′29″W / 43.193376°N 70.874858°W", "Dover", ""], ["26", "St. Thomas Episcopal Church", "June 7, 1984\\n(#84003241)", "5 Hale St.\\n43°11′37″N 70°52′30″W / 43.193611°N 70.875°W", "Dover", ""], ["38", "Woodbury Mill", "March 25, 2013\\n(#13000156)", "1 Dover St.\\n43°12′07″N 70°52′29″W / 43.201985°N 70.874587°W", "Dover", ""], ["25", "Rollinsford Town Hall", "March 5, 1999\\n(#99000268)", "667 Main St.\\n43°14′08″N 70°49′17″W / 43.235556°N 70.821389°W", "Rollinsford", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 listed historical place in strafford county, new hampshire? | Back River Farm | 128 | Answer: |
Table InputTable: [["Round", "Pick", "Player", "Position", "Nationality", "School/Club Team"], ["1", "15", "Reggie Johnson", "PF/C", "United States", "Tennessee"], ["3", "60", "Lavon Mercer", "", "United States", "Georgia"], ["9", "192", "Al Williams", "", "United States", "North Texas State"], ["5", "107", "Gib Hinz", "", "United States", "Wisconsin-Eau Claire"], ["8", "172", "Bill Bailey", "", "United States", "Texas Pan-American"], ["6", "129", "Dean Uthoff", "", "United States", "Iowa State"], ["3", "61", "Rich Yonakor", "", "United States", "North Carolina"], ["10", "209", "Steve Schall", "", "United States", "Arkansas"], ["4", "83", "Calvin Roberts", "", "United States", "California State-Fullerton"], ["2", "39", "Michael Miley", "", "United States", "California State-Long Beach"], ["7", "153", "Allan Zahn", "", "United States", "Arkansas"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:are their any draft picks that are not from the united states? | No | 128 | Answer: |
Table InputTable: [["Outcome", "No.", "Date", "Tournament", "Surface", "Opponent", "Score"], ["Winner", "5.", "4 September 2012", "Mestre, Italy", "Clay", "Estrella Cabeza Candela", "6–1, 3–6, 6–1"], ["Runner-up", "5.", "13 March 2007", "Orange, USA", "Hard", "Naomi Cavaday", "6–1, 6–1"], ["Winner", "1.", "25 July 2006", "Monteroni D'Arbia, Italy", "Clay", "Edina Gallovits-Hall", "6–2, 6–1"], ["Winner", "4.", "20 June 2011", "Rome, Italy", "Clay", "Laura Thorpe", "6–3, 6–0"], ["Runner-up", "10.", "16 November 2010", "Mallorca, Spain", "Clay", "Diana Enache", "6–4, 6–2"], ["Runner-up", "12.", "27 August 2012", "Bagnatica, Italy", "Clay", "Maria-Elena Camerin", "7–6(5), 6–4"], ["Winner", "3.", "7 June 2011", "Campobasso, Italy", "Clay", "Alizé Lim", "6–2, 6–4"], ["Runner-up", "1.", "6 October 2003", "Bari, Italy", "Clay", "Bettina Pirker", "6–2, 7–5"], ["Runner-up", "4.", "31 July 2006", "Martina Franca, Italy", "Clay", "Margalita Chakhnashvili", "6–3, 7–5"], ["Winner", "2.", "18 October 2010", "Seville, Spain", "Clay", "Andrea Gámiz", "6–0, 6–1"], ["Runner-up", "6.", "3 April 2007", "Dinan, France", "Clay (i)", "Maša Zec Peškirič", "6–4, 6–2"], ["Runner-up", "7.", "9 April 2007", "Civitavecchia, Italy", "Clay", "Darya Kustova", "3–6, 6–4, 6–4"], ["Runner-up", "11.", "14 June 2011", "Padova, Italy", "Clay", "Kristina Mladenovic", "3–6, 6–4, 6–0"], ["Runner-up", "8.", "9 July 2007", "Biella, Italy", "Clay", "Agnieszka Radwańska", "6–3, 6–3"], ["Runner-up", "9.", "11 October 2010", "Settimo San Pietro, Italy", "Clay", "Anastasia Grymalska", "4–6, 6–2, 7–5"], ["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"], ["Runner-up", "13.", "12 May 2013", "Trnava, Slovakia", "Clay", "Barbora Záhlavová-Strýcová", "6–2, 6–4"]] | 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 times was she a winner? | 5 | 128 | Answer: |
Table InputTable: [["Year", "Title", "Role", "Notes"], ["2006–2007", "Family Guy", "Esther", "Voice\\n3 episodes"], ["1997", "Smart Guy", "Roxanne", "1 episode"], ["2014", "Melissa and Joey", "Gillian", "Season 3 Episode 24 'To Tell the Truth'"], ["1994–1999", "Sister, Sister", "Tamera Campbell", "119 episodes"], ["2013", "The Real", "Herself", "Host"], ["1994", "The All-New Mickey Mouse (MMC)", "Herself", "1 episode"], ["2004–2006", "Strong Medicine", "Dr. Kayla Thorton", "37 episodes"], ["2009", "Roommates", "Hope", "13 episodes"], ["2009", "The Super Hero Squad Show", "Misty Knight", "1 episode"], ["1998", "Blues Clues", "Herself", "1 episode"], ["2011–2013", "Tia & Tamera", "Herself", "Executive producer"], ["1995–1996", "The Adventures of Hyperman", "Emma C. Squared", "8 episodes"], ["2011", "Access Hollywood Live", "Herself", "Co-host"], ["1996", "All That", "Herself", ""], ["2011", "CHRISJayify", "Herself", "Episode: \"Drugs Are Bad\""], ["1991", "Flesh'n Blood", "Penelope", "1 episode"], ["2012", "Christmas Angel", "Daphney", ""], ["2000", "How I Loved a Macho Boy", "Jamal Santos", "3 episodes"], ["1999", "Detention", "Orangejella LaBelle", "13 episodes"], ["2011", "Things We Do for Love", "Lourdes", "5 episodes"], ["1992", "True Colors", "Lorae", "1 episode"], ["1995", "Are You Afraid of the Dark?", "Evil Chameleon", "1 episode"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 family guy, what was the name of her role? | Esther | 128 | Answer: |
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["8", "27", "Henri Pescarolo", "March-Ford", "77", "+ 3 Laps", "13", ""], ["5", "1", "Emerson Fittipaldi", "Lotus-Ford", "79", "+ 1 Lap", "17", "2"], ["2", "17", "Ronnie Peterson", "March-Ford", "80", "+ 25.6", "6", "6"], ["DNQ", "19", "Nanni Galli*", "March-Alfa-Romeo", "", "", "", ""], ["Ret", "2", "Reine Wisell", "Lotus-Ford", "21", "Wheel bearing", "12", ""], ["4", "9", "Denny Hulme", "McLaren-Ford", "80", "+ 1:06.7", "8", "3"], ["6", "24", "Rolf Stommelen", "Surtees-Ford", "79", "+ 1 Lap", "16", "1"], ["DNQ", "18", "Alex Soler-Roig", "March-Ford", "", "", "", ""], ["7", "22", "John Surtees", "Surtees-Ford", "79", "+ 1 Lap", "10", ""], ["DNQ", "28", "Skip Barber", "March-Ford", "", "", "", ""], ["Ret", "10", "Peter Gethin", "McLaren-Ford", "22", "Accident", "14", ""], ["10", "8", "Tim Schenken", "Brabham-Ford", "76", "+ 4 Laps", "18", ""], ["1", "11", "Jackie Stewart", "Tyrrell-Ford", "80", "1:52:21.3", "1", "9"], ["Ret", "12", "François Cevert", "Tyrrell-Ford", "5", "Accident", "15", ""], ["Ret", "7", "Graham Hill", "Brabham-Ford", "1", "Accident", "9", ""], ["3", "4", "Jacky Ickx", "Ferrari", "80", "+ 53.3", "2", "4"], ["DNQ", "6", "Mario Andretti", "Ferrari", "", "", "", ""], ["Ret", "5", "Clay Regazzoni", "Ferrari", "24", "Accident", "11", ""], ["Ret", "14", "Jo Siffert", "BRM", "58", "Oil Pipe", "3", ""], ["9", "15", "Pedro Rodríguez", "BRM", "76", "+ 4 Laps", "5", ""], ["Ret", "20", "Chris Amon", "Matra", "45", "Differential", "4", ""], ["Ret", "21", "Jean-Pierre Beltoise", "Matra", "47", "Differential", "7", ""], ["DNQ", "16", "Howden Ganley", "BRM", "", "", "", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 cars were constructed by march-ford? | 4 | 128 | Answer: |
Table InputTable: [["Pos", "No", "Driver", "Constructor", "Laps", "Time/Retired", "Grid", "Points"], ["8", "26", "Philippe Alliot", "Ligier-Renault", "79", "+ 3 Laps", "8", ""], ["4", "3", "Martin Brundle", "Tyrrell-Renault", "81", "+ 1 Lap", "16", "3"], ["Ret", "8", "Derek Warwick", "Brabham-BMW", "57", "Brakes", "20", ""], ["7", "25", "René Arnoux", "Ligier-Renault", "79", "+ 3 Laps", "5", ""], ["Ret", "7", "Riccardo Patrese", "Brabham-BMW", "63", "Electrical", "19", ""], ["9", "14", "Jonathan Palmer", "Zakspeed", "77", "+ 5 Laps", "21", ""], ["6", "11", "Johnny Dumfries", "Lotus-Renault", "80", "+ 2 Laps", "14", "1"], ["3", "28", "Stefan Johansson", "Ferrari", "81", "+ 1 Lap", "12", "4"], ["1", "1", "Alain Prost", "McLaren-TAG", "82", "1:54:20.388", "4", "9"], ["Ret", "2", "Keke Rosberg", "McLaren-TAG", "62", "Tyre", "7", ""], ["Ret", "5", "Nigel Mansell", "Williams-Honda", "63", "Tyre", "1", ""], ["5", "4", "Philippe Streiff", "Tyrrell-Renault", "80", "Out of Fuel", "10", "2"], ["Ret", "15", "Alan Jones", "Lola-Ford", "16", "Engine", "15", ""], ["2", "6", "Nelson Piquet", "Williams-Honda", "82", "+ 4.205", "2", "6"], ["Ret", "12", "Ayrton Senna", "Lotus-Renault", "43", "Engine", "3", ""], ["Ret", "18", "Thierry Boutsen", "Arrows-BMW", "50", "Engine", "22", ""], ["10", "19", "Teo Fabi", "Benetton-BMW", "77", "+ 5 Laps", "13", ""], ["Ret", "27", "Michele Alboreto", "Ferrari", "0", "Collision", "9", ""], ["Ret", "20", "Gerhard Berger", "Benetton-BMW", "40", "Engine", "6", ""], ["Ret", "17", "Christian Danner", "Arrows-BMW", "52", "Engine", "24", ""], ["Ret", "29", "Huub Rothengatter", "Zakspeed", "29", "Suspension", "23", ""], ["NC", "16", "Patrick Tambay", "Lola-Ford", "70", "Not Classified", "17", ""], ["Ret", "24", "Alessandro Nannini", "Minardi-Motori Moderni", "10", "Accident", "18", ""], ["NC", "22", "Allen Berg", "Osella-Alfa Romeo", "61", "Not Classified", "26", ""], ["Ret", "21", "Piercarlo Ghinzani", "Osella-Alfa Romeo", "2", "Transmission", "25", ""], ["Ret", "23", "Andrea de Cesaris", "Minardi-Motori Moderni", "40", "Mechanical", "11", ""]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:how many drivers scored at leasst 4 points? | 3 | 128 | Answer: |
Table InputTable: [["Wrestler:", "Times:", "Date:", "Location:", "Notes:"], ["Super Delfin", "1", "January 4, 2000", "Tokyo, Japan", "Beat Dick Togo for the championship"], ["Super Delfin", "2", "June 18, 2000", "Osaka, Japan", ""], ["Gamma", "1", "June 24, 2001", "Osaka, Japan", ""], ["Dick Togo", "1", "July 25, 2009", "Osaka, Japan", ""], ["Takehiro Murahama", "1", "May 7, 2000", "Tokyo, Japan", ""], ["Zeus", "1", "January 19, 2014", "Osaka, Japan", ""], ["Tigers Mask", "1", "February 12, 2007", "Osaka, Japan", ""], ["Daisuke Harada", "1", "February 26, 2012", "Osaka, Japan", ""], ["Super Dolphin", "1", "February 13, 2005", "Osaka, Japan", ""], ["Super Delfin", "3", "January 3, 2002", "Osaka, Japan", ""], ["Hideyoshi", "1", "July 26, 2008", "Osaka, Japan", ""], ["Black Buffalo", "1", "March 25, 2012", "Osaka, Japan", ""], ["CIMA", "1", "June 18, 2010", "Osaka, Japan", ""], ["Super Delfin", "4", "February 26, 2006", "Osaka, Japan", ""], ["Daisuke Harada", "2", "July 22, 2012", "Osaka, Japan", ""], ["Tigers Mask", "3", "April 29, 2011", "Osaka, Japan", ""], ["Takehiro Murahama", "2", "July 6, 2003", "Osaka, Japan", ""], ["Tigers Mask", "2", "July 29, 2010", "Osaka, Japan", ""], ["Daio QUALLT", "1", "April 17, 2004", "Osaka, Japan", ""], ["“Big Boss” MA-G-MA", "1", "October 2, 2004", "Osaka, Japan", ""], ["Quiet Storm", "1", "July 21, 2013", "Osaka, Japan", ""], ["Billyken Kid", "4", "February 11, 2010", "Osaka, Japan", ""], ["Asian Cougar / Kuuga", "1", "August 28, 2010", "Osaka, Japan", "Asian Cougar renamed himself Kuuga during his reign."], ["Billyken Kid", "3", "February 15, 2009", "Osaka, Japan", ""], ["Billyken Kid", "1", "August 8, 2004", "Osaka, Japan", ""], ["Billyken Kid", "5", "August 14, 2011", "Osaka, Japan", ""], ["Tigers Mask", "4", "May 19, 2013", "Osaka, Japan", "Defeated Billyken Kid in the finals of a four-man tournament to win the vacant title."], ["Billyken Kid", "2", "August 26, 2006", "Osaka, Japan", ""], ["Vacated", "N/A", "March 30, 2013", "Osaka, Japan", "Title vacated, after Harada announced that he was not re-signing with Osaka Pro after his contract ran out on April 29, 2013."]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 0, 2, 2],
[10, "France", 0, 0, 1, 1]]
Question: name the countries that had at least 5 gold medals
Answer: Netherlands, Italy
Question:who has the top number of times? | Billyken Kid | 128 | Answer: |
Table InputTable: [["Represent", "Candidate", "in Russian", "Age", "Height", "Hometown"], ["Capital City", "Natalia Varnakova", "Наталиа Варнакова", "19", "1.80 m (5 ft 11 in)", "Moscow"], ["Chuvash Republic", "Martha Neosova", "Мартха Неосова", "19", "1.78 m (5 ft 10 in)", "Cheboksary"], ["Mordovian Republic", "Olga Stepančenko", "Олга Степанченко", "20", "1.75 m (5 ft 9 in)", "Saransk"], ["Chechen Republic", "Carmen Jenockova", "Цармен Йеноцкова", "24", "1.80 m (5 ft 11 in)", "Urus-Martan"], ["Adygean Republic", "Alissa Joanndova", "Алисса Йоанндова", "19", "1.83 m (6 ft 0 in)", "Tulsky"], ["Jewish Autonomous Oblast", "Natalia Melckenberger", "Наталиа Мелцкенбергер", "20", "1.75 m (5 ft 9 in)", "Birobidzhan"], ["Buryatian Republic", "Loise Egiazarjan", "Лоисе Егиазарян", "20", "1.85 m (6 ft 1 in)", "Ulan-Ude"], ["Udmurt Republic", "Monica Zaharova", "Моница Захарова", "24", "1.81 m (5 ft 11 1⁄2 in)", "Izhevsk"], ["Saint Petersburg", "Maria Hernasova", "Мариа Хернасова", "20", "1.78 m (5 ft 10 in)", "Saint Petersburg"], ["Bashkortostan Republic", "Aimee Neosaranova", "Аимее Неосаранова", "19", "1.77 m (5 ft 9 1⁄2 in)", "Ufa"], ["Mari El Republic", "Anna Il’ina", "Анна Ильина", "19", "1.88 m (6 ft 2 in)", "Medvedevo"], ["Nenets Okrug", "Sofia Meldemendev", "Софиа Мелдемендев", "25", "1.85 m (6 ft 1 in)", "Naryan-Mar"], ["Penza Oblast", "Anna Milinzova", "Анна Милинзова", "20", "1.86 m (6 ft 1 in)", "Penza"], ["Chukotka Okrug", "Mariesea Mnesiču", "Мариесеа Мнесичу", "19", "1.80 m (5 ft 11 in)", "Anadyr"], ["Tyumen Oblast", "Andrea Maksimova", "Андреа Максимова", "24", "1.84 m (6 ft 1⁄2 in)", "Tyumen"], ["Samara Oblast", "Nadia Gurina", "Надиа Гурина", "20", "1.78 m (5 ft 10 in)", "Samara"], ["Ryazan Oblast", "Julia Sandrova", "Юлиа Сандрова", "20", "1.74 m (5 ft 8 1⁄2 in)", "Ryazan"], ["Rostov Oblast", "Tatiana Kotova", "Татиана Котова", "21", "1.81 m (5 ft 11 1⁄2 in)", "Rostov-on-Don"], ["Krasnodar Krai", "Patricia Valiahmetova", "Патрициа Валиахметова", "20", "1.80 m (5 ft 11 in)", "Krasnodar"], ["Karachay-Cherkess Republic", "Stephanie Drjagina", "Степхание Дрягина", "24", "1.81 m (5 ft 11 1⁄2 in)", "Kaluga"], ["Chelyabinsk Oblast", "Tatiana Abramenko", "Татиана Абраменко", "21", "1.74 m (5 ft 8 1⁄2 in)", "Chelyabinsk"], ["Sakhalin Oblast", "Jeannette Menova", "Йеаннетте Менова", "18", "1.75 m (5 ft 9 in)", "Sakhalin"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 candidate from capital city? | Natalia Varnakova | 128 | Answer: |
Table InputTable: [["Week", "Date", "Opponent", "Result", "Game site", "NFL Recap", "Attendance"], ["13", "November 27, 1986", "Seattle Seahawks", "L 14–31", "Texas Stadium", "[13]", "58,020"], ["9", "November 2, 1986", "at New York Giants", "L 14–17", "Giants Stadium", "[9]", "74,871"], ["7", "October 19, 1986", "at Philadelphia Eagles", "W 17–14", "Veterans Stadium", "[7]", "68,572"], ["12", "November 23, 1986", "at Washington Redskins", "L 14–41", "RFK Stadium", "[12]", "55,642"], ["11", "November 16, 1986", "at San Diego Chargers", "W 24–21", "Jack Murphy Stadium", "[11]", "55,622"], ["1", "September 8, 1986", "New York Giants", "W 31–28", "Texas Stadium", "[1]", "59,804"], ["5", "October 5, 1986", "at Denver Broncos", "L 14–29", "Mile High Stadium", "[5]", "76,082"], ["14", "December 7, 1986", "at Los Angeles Rams", "L 10–29", "Anaheim Stadium", "[14]", "64,949"], ["16", "December 21, 1986", "Chicago Bears", "L 10–24", "Texas Stadium", "[16]", "57,256"], ["8", "October 26, 1986", "St. Louis Cardinals", "W 37–6", "Texas Stadium", "[8]", "60,756"], ["10", "November 9, 1986", "Los Angeles Raiders", "L 13–17", "Texas Stadium", "[10]", "61,706"], ["4", "September 29, 1986", "at St. Louis Cardinals", "W 31–7", "Busch Memorial Stadium", "[4]", "49,077"], ["15", "December 14, 1986", "Philadelphia Eagles", "L 21–23", "Texas Stadium", "[15]", "46,117"], ["2", "September 14, 1986", "at Detroit Lions", "W 31–7", "Pontiac Silverdome", "[2]", "73,812"], ["3", "September 21, 1986", "Atlanta Falcons", "L 35–37", "Texas Stadium", "[3]", "62,880"], ["6", "October 12, 1986", "Washington Redskins", "W 30–6", "Texas Stadium", "[6]", "63,264"]] | You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:
- Output Format:
Your response must be a plain text string. If the answer contains multiple values, separate them by a comma followed by a space (for example: Netherlands, Italy).
- Direct Answers Only:
Return ONLY the table cell value(s) that directly answer the question. Do not include headers, column names, or any additional text.
- Aggregation Requirements:
If the question requires an aggregation (e.g., average, sum, count, etc.), return only the aggregated value(s) as a plain text string.
- No Explanations:
Do NOT provide any explanations, reasoning, or repeat these instructions in your answer.
Examples:
Example 1
Table:
[["Model", "Production_Years", "Engine", "Displacement", "Power", "Top_Speed"],
["11/18 PS", "1907–1910", "4 inline", "2,799 cc", "13.2 kW (18 PS)", "55 km/h (34 mph)"],
["13/30 PS", "1909–1912", "4 inline", "3,180 cc", "25.7 kW (35 PS)", ""],
["K 5/13 PS", "1911–1920", "4 inline", "1,292 cc", "9.6–10.3 kW (13–14 PS)", "55 km/h (34 mph)"],
["10/28 PS", "1909–1912", "4 inline", "2,612 cc", "22 kW (30 PS)", ""],
["30/70 PS", "1911–1914", "4 inline", "7,853 cc", "51 kW (70 PS)", "115 km/h (71 mph)"],
["35/80 PS", "1911–1914", "4 inline", "9,081 cc", "62.5 kW (85 PS)", ""]]
Question: which typ(s) had the longest construction times?
Answer: K 5/13 PS
Example 2
Table:
[["Rank", "Nation", "Gold", "Silver", "Bronze", "Total"],
[1, "Netherlands", 20, 9, 0, 29],
[2, "Italy", 10, 15, 3, 28],
[3, "Belgium", 1, 2, 6, 9],
[4, "Spain", 1, 1, 13, 15],
[5, "Great Britain", 0, 2, 0, 2],
[6, "Germany", 0, 1, 7, 8],
[7, "Greece", 0, 1, 0, 1],
[7, "Russia", 0, 1, 0, 1],
[9, "Sweden", 0, 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 game date had the least people in attendance? | December 14, 1986 | 128 | Answer: |
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