question stringlengths 2.28k 2.42k | context stringclasses 421
values | answer stringlengths 1 260 | answer_prefix stringclasses 1
value | max_new_tokens int64 128 128 |
|---|---|---|---|---|
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Rank","Cyclist","Team","Time","UCI ProTour\nPoints"]<header>["1","Alejandro Valverde (ESP)","Caisse d'Epargne","5h 29' 10"","40"]<tuple_end>["2","Alexandr Kolobnev (RUS)","Team CSC Saxo Bank","s.t.","30"]<tuple_end>["3","Davide Rebellin (ITA)","Gerolsteiner","s.t.","25"]<tuple_end>["4","Paolo Bettini (ITA)",... | Italy | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Description Losses","1939/40","1940/41","1941/42","1942/43","1943/44","1944/45","Total"]<header>["Direct War Losses","360,000","","","","","183,000","543,000"]<tuple_end>["Murdered","75,000","100,000","116,000","133,000","82,000","","506,000"]<tuple_end>["Deaths In Prisons & Camps","69,000","210,000","220,00... | 100,000 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Year","Division","League","Reg. Season","Playoffs","National Cup"]<header>["1931","1","ASL","6th (Fall)","No playoff","N/A"]<tuple_end>["Spring 1932","1","ASL","5th?","No playoff","1st Round"]<tuple_end>["Fall 1932","1","ASL","3rd","No playoff","N/A"]<tuple_end>["Spring 1933","1","ASL","?","?","Final"]<tuple... | 17 years | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Series #","Season #","Title","Notes","Original air date"]<header>["1","1",""The Charity"","Alfie, Dee Dee, and Melanie are supposed to be helping their parents at a carnival by working the dunking booth. When Goo arrives and announces their favorite basketball player, Kendall Gill, is at the Comic Book Store... | January 26, 1995 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Date","Competition","Location","Country","Event","Placing","Rider","Nationality"]<header>["31 October 2008","2008–09 World Cup","Manchester","United Kingdom","Sprint","1","Victoria Pendleton","GBR"]<tuple_end>["31 October 2008","2008–09 World Cup","Manchester","United Kingdom","Keirin","2","Jason Kenny","GBR... | 17 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Year","Competition","Venue","Position","Event","Notes"]<header>["2000","World Junior Championships","Santiago, Chile","1st","Discus throw","59.51 m"]<tuple_end>["2003","All-Africa Games","Abuja, Nigeria","5th","Shot put","17.76 m"]<tuple_end>["2003","All-Africa Games","Abuja, Nigeria","2nd","Discus throw","6... | World Junior Championships | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Year","Film","Role","Language","Notes"]<header>["2008","Moggina Manasu","Chanchala","Kannada","Filmfare Award for Best Actress - Kannada\nKarnataka State Film Award for Best Actress"]<tuple_end>["2009","Olave Jeevana Lekkachaara","Rukmini","Kannada","Innovative Film Award for Best Actress"]<tuple_end>["2009"... | 15 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Game","Day","Date","Kickoff","Opponent","Results\nScore","Results\nRecord","Location","Attendance"]<header>["1","Sunday","November 10","3:05pm","at Las Vegas Legends","L 3–7","0–1","Orleans Arena","1,836"]<tuple_end>["2","Sunday","November 17","1:05pm","Monterrey Flash","L 6–10","0–2","UniSantos Park","363"]... | 363 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Year","Kit Manufacturer","Shirt Sponsor","Back of Shirt Sponsor","Short Sponsor"]<header>["1977–1978","","National Express","",""]<tuple_end>["1982–1985","Umbro","","",""]<tuple_end>["1985–1986","Umbro","Whitbread","",""]<tuple_end>["1986–1988","Henson","Duraflex","",""]<tuple_end>["1988–1989","","Gulf Oil",... | 1982-1985 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Year","Competition","Venue","Position","Event","Notes"]<header>["1999","European Junior Championships","Riga, Latvia","4th","400 m hurdles","52.17"]<tuple_end>["2000","World Junior Championships","Santiago, Chile","1st","400 m hurdles","49.23"]<tuple_end>["2001","World Championships","Edmonton, Canada","18th... | 2000 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Season","Team","Record","Head Coach","Quarterback","Leading Rusher","Leading Receiver","All-Pros","Runner Up"]<header>["1970","Dallas Cowboys","10–4","Tom Landry*","Craig Morton","Duane Thomas","Bob Hayes*","Howley","San Francisco 49ers"]<tuple_end>["1971","Dallas Cowboys†","11–3","Tom Landry*","Roger Stauba... | 2004, 2005, 2006 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Name","League","FA Cup","League Cup","JP Trophy","Total"]<header>["Scot Bennett","5","0","0","0","5"]<tuple_end>["Danny Coles","3","0","0","0","3"]<tuple_end>["Liam Sercombe","1","0","0","0","1"]<tuple_end>["Alan Gow","4","0","0","0","4"]<tuple_end>["John O'Flynn","11","0","1","0","12"]<tuple_end>["Guillem B... | John | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Tournament","2004","2005","2006","2007","2008","2009","2010","2011","2012","2013","2014","W–L"]<header>["Australian Open","A","2R","2R","2R","3R","2R","1R","3R","1R","1R","2R","9–10"]<tuple_end>["French Open","2R","1R","1R","2R","2R","1R","2R","3R","1R","1R","","6–10"]<tuple_end>["Wimbledon","A","2R","2R","1... | 440 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Ship","Type of Vessel","Lake","Location","Lives lost"]<header>["Argus","Steamer","Lake Huron","25 miles off Kincardine, Ontario","25 lost"]<tuple_end>["James Carruthers","Steamer","Lake Huron","near Kincardine","18 lost"]<tuple_end>["Hydrus","Steamer","Lake Huron","near Lexington, Michigan","28 lost"]<tuple_... | 7 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["name","glyph","C string","Unicode","Unicode name"]<header>["NUL","","\\0","U+0000","NULL (NUL)"]<tuple_end>["alert","","\\a","U+0007","BELL (BEL)"]<tuple_end>["backspace","","\\b","U+0008","BACKSPACE (BS)"]<tuple_end>["tab","","\\t","U+0009","CHARACTER TABULATION (HT)"]<tuple_end>["carriage-return","","\\r",... | space | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Date","Opponent#","Rank#","Site","TV","Result","Attendance"]<header>["September 3","Tennessee–Chattanooga*","#11","Legion Field • Birmingham, AL","","W 42–13","82,109"]<tuple_end>["September 10","Vanderbilt","#11","Bryant–Denny Stadium • Tuscaloosa, AL","JPS","W 17–7","70,123"]<tuple_end>["September 17","at ... | 68 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Pos","Rider","Manufacturer","Time/Retired","Points"]<header>["1","Loris Capirossi","Honda","38:04.730","25"]<tuple_end>["2","Valentino Rossi","Aprilia","+0.180","20"]<tuple_end>["3","Jeremy McWilliams","Aprilia","+0.534","16"]<tuple_end>["4","Tohru Ukawa","Honda","+0.537","13"]<tuple_end>["5","Shinya Nakano"... | Tomomi Manako | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Date","Festival","Location","Awards","Link"]<header>["Feb 2–5, Feb 11","Santa Barbara International Film Festival","Santa Barbara, California USA","Top 11 "Best of the Fest" Selection","sbiff.org"]<tuple_end>["May 21–22, Jun 11","Seattle International Film Festival","Seattle, Washington USA","","siff.net"]... | 5 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Name","City","Hospital beds","Operating rooms","Total","Trauma designation","Affiliation","Notes"]<header>["Alamance Regional Medical Center","Burlington","238","15","253","-","Cone","-"]<tuple_end>["Albemarle Hospital","Elizabeth City","182","13","195","-","Vidant","-"]<tuple_end>["Alexander Hospital","Hick... | Vidant Bertie Hospital | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Model","1991","1995","1996","1997","1998","1999","2000","2001","2002","2003","2004","2005","2006","2007","2008","2009","2010","2011","2012","2013"]<header>["Škoda Felicia","172,000","210,000","","288,458","261,127","241,256","148,028","44,963","−","−","−","−","−","−","−","−","−","−","−","−"]<tuple_end>["Škod... | 492,111 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Outcome","No.","Date","Championship","Surface","Opponent in the final","Score in the final"]<header>["Runner-up","1.","February 15, 1993","Memphis, Tennessee, USA","Hard (i)","Jim Courier","7–5, 6–7(4–7), 6–7(4–7)"]<tuple_end>["Winner","1.","May 17, 1993","Coral Springs, Florida, USA","Clay","David Wheaton",... | 1 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Rank","Nation","Gold","Silver","Bronze","Total"]<header>["1","Brazil","7","5","3","15"]<tuple_end>["2","Venezuela","3","2","8","13"]<tuple_end>["3","Colombia","2","3","4","9"]<tuple_end>["4","Chile","2","0","2","4"]<tuple_end>["5","Argentina","1","2","5","8"]<tuple_end>["6","Peru","1","1","2","4"]<tuple_end>... | Brazil | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Place","Rider","Country","Team","Points","Wins"]<header>["1","Sylvain Geboers","Belgium","Suzuki","3066","3"]<tuple_end>["2","Adolf Weil","Germany","Maico","2331","2"]<tuple_end>["3","Torlief Hansen","Sweden","Husqvarna","2052","0"]<tuple_end>["4","Roger De Coster","Belgium","Suzuki","1865","3"]<tuple_end>["... | 7 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Position","Sail Number","Yacht","State/Country","Yacht Type","LOA\n(Metres)","Skipper","Elapsed Time\nd:hh:mm:ss"]<header>["1","US17","Sayonara","USA","Farr ILC Maxi","24.13","Larry Ellison","2:19:03:32"]<tuple_end>["2","C1","Brindabella","NSW","Jutson 79","24.07","George Snow","2:21:55:06"]<tuple_end>["3","... | Brindabella | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Match","Date","Venue","Opponents","Score"]<header>["GL-B-1","2008..","[[]]","[[]]","-"]<tuple_end>["GL-B-2","2008..","[[]]","[[]]","-"]<tuple_end>["GL-B-3","2008..","[[]]","[[]]","-"]<tuple_end>["GL-B-4","2008..","[[]]","[[]]","-"]<tuple_end>["GL-B-5","2008..","[[]]","[[]]","-"]<tuple_end>["GL-B-6","2008..",... | GL-B-6 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Series","Premiere","Finale","Winner","Runner-up","Third place","Host(s)","Judging panel","Guest judge(s)"]<header>["One","9 June 2007","17 June 2007","Paul Potts","Damon Scott","Connie Talbot","Ant & Dec","Simon Cowell\nAmanda Holden\nPiers Morgan","N/A"]<tuple_end>["Two","12 April 2008","31 May 2008","Georg... | 3 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Year","Award","Nominated work","Category","Result"]<header>["2007","Cosmopolitan Ultimate Woman of the Year","Leona Lewis","Newcomer of the Year","Won"]<tuple_end>["2007","The Record of the Year",""Bleeding Love"","The Record of the Year","Won"]<tuple_end>["2008","Capital Awards","Leona Lewis","Favourite UK ... | 20 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Season","League\nPos.","League\nCompetition","League\nTop scorer","Danish Cup","Europe","Others"]<header>["1981-82","4","1982 1st Division","Michael Laudrup (15)","4th round","",""]<tuple_end>["1982-83","4","1983 1st Division","Brian Chrøis (12)","4th round","",""]<tuple_end>["1983-84","4","1984 1st Division... | Simon Makienok Christoffersen | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Contestant","Original Tribe","Switched Tribe","Merged Tribe","Finish","Total Votes"]<header>["Yelena Kondulaynen\n44.the actress","Pelicans","","","1st Voted Out\nDay 3","5"]<tuple_end>["Kris Kelmi\n47.the singer","Barracudas","","","2nd Voted Out\nDay 6","1"]<tuple_end>["Aleksandr Pashutin\n60.the actor","B... | 9 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Season","Age","Overall","Slalom","Giant\nSlalom","Super G","Downhill","Combined"]<header>["2007","20","130","–","40","–","–","—"]<tuple_end>["2008","21","64","–","28","46","46","31"]<tuple_end>["2009","22","7","–","6","16","16","1"]<tuple_end>["2010","23","1","–","2","6","2","2"]<tuple_end>["2011","24","3","... | 1 | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Route","Name","Fare Type","Terminals","Terminals","Major streets","Notes","History"]<header>["31","Wisconsin Avenue Line","Local","Friendship Heights station","Potomac Park (Virginia Av & 21st St NW)","Wisconsin Avenue NW","","31 replaces the Wisconsin Avenue portion of the old 30 (see Pennsylvania Avenue Li... | Pennsylvania Avenue Metro Extra Line | Answer: | 128 |
You are a question-answering model specialized in tabular data.
I will provide you with a table in a list-of-lists format (where the first row is the header) and a single natural language question.
Your task is to extract the exact table cell value(s) that directly answer the provided question. Follow these guidelines:... | [<header>["Team","Stadium","Capacity","City/Area"]<header>["Bradford Bulls (2014 season)","Provident Stadium","27,000","Bradford, West Yorkshire"]<tuple_end>["Castleford Tigers (2014 season)","The Wish Communications Stadium","11,750","Castleford, West Yorkshire"]<tuple_end>["Catalans Dragons (2014 season)","Stade Gilb... | DW Stadium | Answer: | 128 |
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