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alun jones ( tennis ) | https://en.wikipedia.org/wiki/Alun_Jones_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12762499-2.html.csv | unique | the 20 march 2007 tournament was the only one in which alun jones faced vasilis mazarakis in the final . | {'scope': 'all', 'row': '8', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'vasilis mazarakis', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent in the final', 'vasilis mazarakis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent in the final record fuzzily matches to vasilis mazarakis .', 'tostr': 'filter_eq { all_rows ; opponent in the final ; vasilis mazarakis }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } }', 'tointer': 'select the rows whose opponent in the final record fuzzily matches to vasilis mazarakis . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent in the final', 'vasilis mazarakis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent in the final record fuzzily matches to vasilis mazarakis .', 'tostr': 'filter_eq { all_rows ; opponent in the final ; vasilis mazarakis }'}, 'date'], 'result': '20 march 2007', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } ; date }'}, '20 march 2007'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } ; date } ; 20 march 2007 }', 'tointer': 'the date record of this unqiue row is 20 march 2007 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } ; date } ; 20 march 2007 } } = true', 'tointer': 'select the rows whose opponent in the final record fuzzily matches to vasilis mazarakis . there is only one such row in the table . the date record of this unqiue row is 20 march 2007 .'} | and { only { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; vasilis mazarakis } ; date } ; 20 march 2007 } } = true | select the rows whose opponent in the final record fuzzily matches to vasilis mazarakis . there is only one such row in the table . the date record of this unqiue row is 20 march 2007 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent in the final_7': 7, 'vasilis mazarakis_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '20 march 2007_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent in the final_7': 'opponent in the final', 'vasilis mazarakis_8': 'vasilis mazarakis', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '20 march 2007_10': '20 march 2007'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent in the final_7': [0], 'vasilis mazarakis_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '20 march 2007_10': [3]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['19 november 2002', 'berri', 'grass', 'paul baccanello', '6 - 2 , 6 - 2'], ['2 may 2005', 'phuket', 'hard', 'patrick schmolzer', '6 - 1 , 6 - 1'], ['16 may 2005', 'phuket', 'hard', 'phillip king', '6 - 3 , 6 - 1'], ['30 may 2005', 'maspalomas', 'clay', 'ignasi villacampa', '6 - 1 , 6 - 2'], ['12 september 2006', 'hope island', 'hard', 'robert smeets', '6 - 3 , 7 - 6'], ['24 october 2006', 'mildura', 'grass', 'samuel groth', '3 - 6 , 7 - 5 , 6 - 4'], ['31 october 2006', 'berri', 'grass', 'shannon nettle', '6 - 4 , 6 - 3'], ['20 march 2007', 'lyneham', 'clay', 'vasilis mazarakis', '3 - 6 , 6 - 1 , 6 - 3'], ['10 july 2007', 'felixstowe', 'grass', 'nicolas tourte', '6 - 3 , 6 - 4'], ['23 july 2007', 'nottingham', 'grass', 'aisam - ul - haq qureshi', '6 - 3 , 4 - 6 , 6 - 4'], ['9 december 2007', 'burnie', 'hard', 'rameez junaid', '6 - 0 , 6 - 1']] |
1960 american football league season | https://en.wikipedia.org/wiki/1960_American_Football_League_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11379937-4.html.csv | aggregation | the average amount of touchdowns scored was about 15 touchdowns . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '15', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', "td 's"], 'result': '15', 'ind': 0, 'tostr': "avg { all_rows ; td 's }"}, '15'], 'result': True, 'ind': 1, 'tostr': "round_eq { avg { all_rows ; td 's } ; 15 } = true", 'tointer': "the average of the td 's record of all rows is 15 ."} | round_eq { avg { all_rows ; td 's } ; 15 } = true | the average of the td 's record of all rows is 15 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, "td 's_4": 4, '15_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', "td 's_4": "td 's", '15_5': '15'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], "td 's_4": [0], '15_5': [1]} | ['player', 'comp', 'att', 'comp %', 'yards', "td 's", "int 's"] | [['frank tripucka ( den )', '248', '478', '51.8', '3038', '24', '34'], ['jack kemp ( la )', '211', '406', '52', '3018', '20', '25'], ['al dorow ( nyt )', '201', '396', '50.8', '2748', '26', '26'], ['butch songin ( bos )', '187', '392', '47.7', '2476', '22', '15'], ['cotton davidson ( dal )', '179', '379', '47.2', '2474', '15', '16'], ['george blanda ( hou )', '169', '363', '46.6', '2413', '24', '22'], ['tom flores ( oak )', '136', '252', '54', '1738', '12', '12'], ['johnny green ( buf )', '89', '228', '39', '1267', '10', '10'], ['babe parilli ( oak )', '87', '187', '46.5', '1003', '5', '11'], ["tommy o'connell ( buf )", '65', '145', '44.8', '1033', '7', '13'], ['dick jamieson ( nyt )', '35', '70', '50', '586', '6', '2']] |
1929 vfl season | https://en.wikipedia.org/wiki/1929_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10767118-14.html.csv | count | in the 1929 vfl season , among the games where home team scored above 9.0 , 2 of them had attendance over 10000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '10000', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '9.0'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '9.0'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; home team score ; 9.0 }', 'tointer': 'select the rows whose home team score record is greater than 9.0 .'}, 'crowd', '10000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team score record is greater than 9.0 . among these rows , select the rows whose crowd record is greater than 10000 .', 'tostr': 'filter_greater { filter_greater { all_rows ; home team score ; 9.0 } ; crowd ; 10000 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_greater { all_rows ; home team score ; 9.0 } ; crowd ; 10000 } }', 'tointer': 'select the rows whose home team score record is greater than 9.0 . among these rows , select the rows whose crowd record is greater than 10000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_greater { all_rows ; home team score ; 9.0 } ; crowd ; 10000 } } ; 2 } = true', 'tointer': 'select the rows whose home team score record is greater than 9.0 . among these rows , select the rows whose crowd record is greater than 10000 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_greater { all_rows ; home team score ; 9.0 } ; crowd ; 10000 } } ; 2 } = true | select the rows whose home team score record is greater than 9.0 . among these rows , select the rows whose crowd record is greater than 10000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'home team score_6': 6, '9.0_7': 7, 'crowd_8': 8, '10000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'home team score_6': 'home team score', '9.0_7': '9.0', 'crowd_8': 'crowd', '10000_9': '10000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'home team score_6': [0], '9.0_7': [0], 'crowd_8': [1], '10000_9': [1], '2_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '9.6 ( 60 )', 'st kilda', '11.5 ( 71 )', 'corio oval', '10500', '3 august 1929'], ['fitzroy', '5.11 ( 41 )', 'melbourne', '11.11 ( 77 )', 'brunswick street oval', '8000', '3 august 1929'], ['north melbourne', '9.8 ( 62 )', 'footscray', '7.7 ( 49 )', 'arden street oval', '7000', '3 august 1929'], ['richmond', '10.14 ( 74 )', 'essendon', '10.14 ( 74 )', 'punt road oval', '22000', '3 august 1929'], ['south melbourne', '6.7 ( 43 )', 'collingwood', '10.10 ( 70 )', 'lake oval', '20000', '3 august 1929'], ['hawthorn', '5.7 ( 37 )', 'carlton', '7.8 ( 50 )', 'glenferrie oval', '6000', '3 august 1929']] |
vasek pospisil | https://en.wikipedia.org/wiki/Vasek_Pospisil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13181492-2.html.csv | unique | vasek pospisil won only once on clay surface . | {'scope': 'subset', 'row': '5', 'col': '1', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'winner', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'clay'}} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; clay }', 'tointer': 'select the rows whose surface record fuzzily matches to clay .'}, 'outcome', 'winner'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to clay . among these rows , select the rows whose outcome record fuzzily matches to winner .', 'tostr': 'filter_eq { filter_eq { all_rows ; surface ; clay } ; outcome ; winner }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; surface ; clay } ; outcome ; winner } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to clay . among these rows , select the rows whose outcome record fuzzily matches to winner . there is only one such row in the table .'} | only { filter_eq { filter_eq { all_rows ; surface ; clay } ; outcome ; winner } } = true | select the rows whose surface record fuzzily matches to clay . among these rows , select the rows whose outcome record fuzzily matches to winner . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'surface_5': 5, 'clay_6': 6, 'outcome_7': 7, 'winner_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'surface_5': 'surface', 'clay_6': 'clay', 'outcome_7': 'outcome', 'winner_8': 'winner'} | {'only_2': [3], 'result_3': [], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'clay_6': [0], 'outcome_7': [1], 'winner_8': [1]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', 'july 13 , 2009', 'usa f17 , peoria', 'clay', 'michael venus', '7 - 6 ( 7 - 4 ) , 4 - 6 , 4 - 6'], ['winner', 'september 26 , 2009', 'italy f29 , alghero', 'hard', 'francesco piccari', '6 - 3 , 6 - 7 ( 5 - 7 ) , 6 - 3'], ['winner', 'october 3 , 2009', "italy f30 , quartu sant ' elena", 'hard', 'matteo viola', '6 - 1 , 6 - 2'], ['winner', 'november 1 , 2009', 'mexico f12 , obregón', 'hard', 'daniel garza', '7 - 6 ( 7 - 0 ) , 6 - 3'], ['winner', 'november 8 , 2009', 'mexico f14 , guadalajara', 'clay', 'césar ramírez', '6 - 2 , 6 - 2'], ['runner - up', 'february 22 , 2010', 'usa f5 , brownsville', 'hard', 'víctor estrella', '4 - 6 , 3 - 6'], ['winner', 'march 21 , 2010', 'canada f3 , sherbrooke', 'hard ( i )', 'milos raonic', '6 - 4 , 4 - 6 , 6 - 3'], ['winner', 'september 5 , 2010', 'mexico f6 , león', 'hard', 'david rice', '6 - 1 , 6 - 2'], ['winner', 'september 12 , 2010', 'mexico f7 , guadalajara', 'hard', 'adam el mihdawy', '6 - 0 , 6 - 1'], ['winner', 'october 3 , 2010', 'canada f5 , markham', 'hard ( i )', 'nicholas monroe', '6 - 3 , 6 - 2'], ['winner', 'may 29 , 2011', 'korea f2 , changwon', 'hard', 'lim yong - kyu', '7 - 5 , 6 - 4'], ['winner', 'july 31 , 2011', 'canada f4 , saskatoon', 'hard', 'érik chvojka', '7 - 5 , 6 - 2'], ['winner', 'march 25 , 2012', 'rimouski , canada', 'hard ( i )', 'maxime authom', '7 - 6 ( 8 - 6 ) , 6 - 4'], ['winner', 'july 22 , 2012', 'granby , canada', 'hard', 'igor sijsling', '7 - 6 ( 7 - 2 ) , 6 - 4'], ['runner - up', 'march 18 , 2013', 'rimouski , canada', 'hard ( i )', 'rik de voest', '6 - 7 ( 6 - 8 ) , 4 - 6'], ['winner', 'may 4 , 2013', 'johannesburg , south africa', 'hard', 'michał przysiężny', '6 - 7 ( 7 - 9 ) , 6 - 0 , 4 - 1 ret'], ['winner', 'august 4 , 2013', 'vancouver , canada', 'hard', 'daniel evans', '6 - 0 , 1 - 6 , 7 - 5']] |
mañana es para siempre | https://en.wikipedia.org/wiki/Ma%C3%B1ana_es_para_siempre | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18498743-1.html.csv | unique | bosnia and herzegovina is the only country that shows their version of mañana es para siempre on monday to saturday . | {'scope': 'all', 'row': '3', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'monday to saturday', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'monday to friday', 'monday to saturday'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose monday to friday record fuzzily matches to monday to saturday .', 'tostr': 'filter_eq { all_rows ; monday to friday ; monday to saturday }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; monday to friday ; monday to saturday } }', 'tointer': 'select the rows whose monday to friday record fuzzily matches to monday to saturday . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'monday to friday', 'monday to saturday'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose monday to friday record fuzzily matches to monday to saturday .', 'tostr': 'filter_eq { all_rows ; monday to friday ; monday to saturday }'}, 'mexico'], 'result': 'bosnia and herzegovina', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; monday to friday ; monday to saturday } ; mexico }'}, 'bosnia and herzegovina'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; monday to friday ; monday to saturday } ; mexico } ; bosnia and herzegovina }', 'tointer': 'the mexico record of this unqiue row is bosnia and herzegovina .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; monday to friday ; monday to saturday } } ; eq { hop { filter_eq { all_rows ; monday to friday ; monday to saturday } ; mexico } ; bosnia and herzegovina } } = true', 'tointer': 'select the rows whose monday to friday record fuzzily matches to monday to saturday . there is only one such row in the table . the mexico record of this unqiue row is bosnia and herzegovina .'} | and { only { filter_eq { all_rows ; monday to friday ; monday to saturday } } ; eq { hop { filter_eq { all_rows ; monday to friday ; monday to saturday } ; mexico } ; bosnia and herzegovina } } = true | select the rows whose monday to friday record fuzzily matches to monday to saturday . there is only one such row in the table . the mexico record of this unqiue row is bosnia and herzegovina . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'monday to friday_7': 7, 'monday to saturday_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'mexico_9': 9, 'bosnia and herzegovina_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'monday to friday_7': 'monday to friday', 'monday to saturday_8': 'monday to saturday', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'mexico_9': 'mexico', 'bosnia and herzegovina_10': 'bosnia and herzegovina'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'monday to friday_7': [0], 'monday to saturday_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'mexico_9': [2], 'bosnia and herzegovina_10': [3]} | ['mexico', 'mañana es para siempre', 'el canal de las estrellas', 'october 20 , 2008', 'june 14 , 2009', 'monday to friday'] | [['argentina', 'mañana es para siempre', 'canal 9', 'november 10 , 2011', 'march 16 , 2012', 'monday to friday'], ['bulgaria', 'утре и завинаги', 'diema family', 'january 11 , 2010', 'april 30 , 2010', 'monday to friday'], ['bosnia and herzegovina', 'ljubav je večna', 'pink bh', 'december 3 , 2009', 'may 29 , 2010', 'monday to saturday'], ['croatia', 'odavde do vječnosti', 'nova tv', 'february 1 , 2010', 'june 10 , 2010', 'monday to friday'], ['croatia', 'odavde do vječnosti', 'doma tv', 'june 16 , 2011', 'october 30 , 2011', 'monday to friday'], ['estonia', 'igavene homne', 'tv3', 'march 30 , 2010', 'november 8 , 2010', 'monday to friday'], ['hungary', 'mindörökké szerelem', 'rtl klub', 'november 15 , 2010', 'july 8 , 2011', 'monday to friday'], ['macedonia', 'љубовта е вечна', 'sitel tv', '2009', '2009', 'monday to friday'], ['lithuania', 'amžinai tavo', 'lnk', 'march , 2009', 'october 30 , 2009', 'monday to friday'], ['montenegro', 'ljubav je večna', 'pink m', 'august 10 , 2009', 'february 23 , 2010', 'monday to friday'], ['romania', 'impreuna pentru totdeauna', 'acasă', 'march 29 , 2010', 'september 4 , 2010', 'monday to friday'], ['serbia', 'ljubav je večna', 'rtv pink', 'june 5 , 2009', 'january 29 , 2010', 'monday to friday'], ['slovakia', 'love never dies', 'joj plus', 'december 21 , 2009', 'april , 2010', 'monday to friday'], ['slovenia', 'jutri je za večno', 'pop tv', 'september 25 , 2009', 'may 10 , 2010', 'monday to friday'], ['usa', 'mañana es para siempre', 'univision', 'february 23 , 2009', 'october 5 , 2009', 'monday to friday']] |
list of vancouver canucks draft picks | https://en.wikipedia.org/wiki/List_of_Vancouver_Canucks_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11636955-17.html.csv | comparative | of the vancouver canucks draft picks , curtis hunt was selected one round earlier than carl valimont . | {'row_1': '9', 'row_2': '10', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'curtis hunt'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to curtis hunt .', 'tostr': 'filter_eq { all_rows ; player ; curtis hunt }'}, 'rd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; curtis hunt } ; rd }', 'tointer': 'select the rows whose player record fuzzily matches to curtis hunt . take the rd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'carl valimont'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to carl valimont .', 'tostr': 'filter_eq { all_rows ; player ; carl valimont }'}, 'rd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; carl valimont } ; rd }', 'tointer': 'select the rows whose player record fuzzily matches to carl valimont . take the rd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; curtis hunt } ; rd } ; hop { filter_eq { all_rows ; player ; carl valimont } ; rd } } = true', 'tointer': 'select the rows whose player record fuzzily matches to curtis hunt . take the rd record of this row . select the rows whose player record fuzzily matches to carl valimont . take the rd record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; curtis hunt } ; rd } ; hop { filter_eq { all_rows ; player ; carl valimont } ; rd } } = true | select the rows whose player record fuzzily matches to curtis hunt . take the rd record of this row . select the rows whose player record fuzzily matches to carl valimont . take the rd record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'curtis hunt_8': 8, 'rd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'carl valimont_12': 12, 'rd_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'curtis hunt_8': 'curtis hunt', 'rd_9': 'rd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'carl valimont_12': 'carl valimont', 'rd_13': 'rd'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'curtis hunt_8': [0], 'rd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'carl valimont_12': [1], 'rd_13': [3]} | ['rd', 'pick', 'player', 'team ( league )', 'reg gp', 'pl gp'] | [['1', '4', 'jim sandlak', 'london knights ( ohl )', '509', '33'], ['2', '25', 'troy gamble', 'medicine hat tigers ( whl )', '72', '4'], ['3', '46', 'shane doyle', 'belleville bulls ( ohl )', '0', '0'], ['4', '67', 'randy siska', 'medicine hat tigers ( whl )', '0', '0'], ['5', '88', 'robert kron', 'brno zkl ( czech )', '144', '11'], ['6', '109', 'martin hrstka', 'hc dukla trenčín ( slovak )', '0', '0'], ['7', '130', 'brian mcfarlane', 'seattle breakers ( whl )', '0', '0'], ['8', '151', 'hakan ahlund', 'malmö if ( swe )', '0', '0'], ['9', '172', 'curtis hunt', 'prince albert raiders ( whl )', '0', '0'], ['10', '193', 'carl valimont', 'university of lowell ( ncaa )', '0', '0'], ['11', '214', 'igor larionov', 'hc cska moscow ( rus )', '210', '19'], ['12', '235', 'darren taylor', 'calgary wranglers ( whl )', '0', '0']] |
united states army air forces | https://en.wikipedia.org/wiki/United_States_Army_Air_Forces | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23508196-5.html.csv | ordinal | of the united states army air forces , the troop carrier group had the 2nd most number of crews . | {'row': '7', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'number of crews', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; number of crews ; 2 }'}, 'type of unit'], 'result': 'troop carrier group', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; number of crews ; 2 } ; type of unit }'}, 'troop carrier group'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; number of crews ; 2 } ; type of unit } ; troop carrier group } = true', 'tointer': 'select the row whose number of crews record of all rows is 2nd maximum . the type of unit record of this row is troop carrier group .'} | eq { hop { nth_argmax { all_rows ; number of crews ; 2 } ; type of unit } ; troop carrier group } = true | select the row whose number of crews record of all rows is 2nd maximum . the type of unit record of this row is troop carrier group . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'number of crews_5': 5, '2_6': 6, 'type of unit_7': 7, 'troop carrier group_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'number of crews_5': 'number of crews', '2_6': '2', 'type of unit_7': 'type of unit', 'troop carrier group_8': 'troop carrier group'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'number of crews_5': [0], '2_6': [0], 'type of unit_7': [1], 'troop carrier group_8': [2]} | ['type of unit', 'type of aircraft', 'number of aircraft', 'number of crews', 'men per crew', 'total personnel', 'officers', 'enlisted'] | [['very heavy bombardment group', 'b - 29', '45', '60', '11', '2078', '462', '1816'], ['heavy bombardment group', 'b - 17 , b - 24', '72', '96', '9 to 11', '2261', '465', '1796'], ['medium bombardment group', 'b - 25 , b - 26', '96', '96', '5 or 6', '1759', '393', '1386'], ['light bombardment group', 'a - 20 , a - 26', '96', '96', '3 or 4', '1304', '211', '1093'], ['single - engine fighter group', 'p - 40 , p - 47 p - 51', '111 to 126', '108 to 126', '1', '994', '183', '811'], ['twin - engine fighter group', 'p - 38', '111 to 126', '108 to 126', '1', '1081', '183', '838'], ['troop carrier group', 'c - 47', '80 - 110', '128', '4 or 5', '1837', '514', '1323'], ['combat cargo group', 'c - 46 , c - 47', '125', '150', '4', '883', '350', '533'], ['night fighter squadron', 'p - 61 , p - 70', '18', '16', '2 or 3', '288', '50', '238'], ['tactical reconnaissance squadron', 'f - 6 , p - 40 l - 4 , l - 5', '27', '23', '1', '233', '39', '194'], ['photo reconnaissance squadron', 'f - 5', '24', '21', '1', '347', '50', '297']] |
2008 issf world cup final ( rifle and pistol ) | https://en.wikipedia.org/wiki/2008_ISSF_World_Cup_Final_%28rifle_and_pistol%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18191407-10.html.csv | unique | of the shooters that had 8 rank points , the only one that had a total of 17 was iulian raicea . | {'scope': 'subset', 'row': '6', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '17', 'subset': {'col': '3', 'criterion': 'equal', 'value': '8'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rank points', '8'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; rank points ; 8 }', 'tointer': 'select the rows whose rank points record is equal to 8 .'}, 'total', '17'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rank points record is equal to 8 . among these rows , select the rows whose total record is equal to 17 .', 'tostr': 'filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 } }', 'tointer': 'select the rows whose rank points record is equal to 8 . among these rows , select the rows whose total record is equal to 17 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'rank points', '8'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; rank points ; 8 }', 'tointer': 'select the rows whose rank points record is equal to 8 .'}, 'total', '17'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rank points record is equal to 8 . among these rows , select the rows whose total record is equal to 17 .', 'tostr': 'filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 }'}, 'shooter'], 'result': 'iulian raicea ( rou )', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 } ; shooter }'}, 'iulian raicea ( rou )'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 } ; shooter } ; iulian raicea ( rou ) }', 'tointer': 'the shooter record of this unqiue row is iulian raicea ( rou ) .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 } } ; eq { hop { filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 } ; shooter } ; iulian raicea ( rou ) } } = true', 'tointer': 'select the rows whose rank points record is equal to 8 . among these rows , select the rows whose total record is equal to 17 . there is only one such row in the table . the shooter record of this unqiue row is iulian raicea ( rou ) .'} | and { only { filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 } } ; eq { hop { filter_eq { filter_eq { all_rows ; rank points ; 8 } ; total ; 17 } ; shooter } ; iulian raicea ( rou ) } } = true | select the rows whose rank points record is equal to 8 . among these rows , select the rows whose total record is equal to 17 . there is only one such row in the table . the shooter record of this unqiue row is iulian raicea ( rou ) . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'rank points_8': 8, '8_9': 9, 'total_10': 10, '17_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'shooter_12': 12, 'iulian raicea ( rou )_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'rank points_8': 'rank points', '8_9': '8', 'total_10': 'total', '17_11': '17', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'shooter_12': 'shooter', 'iulian raicea ( rou )_13': 'iulian raicea ( rou )'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'rank points_8': [0], '8_9': [0], 'total_10': [1], '17_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'shooter_12': [3], 'iulian raicea ( rou )_13': [4]} | ['shooter', 'event', 'rank points', 'score points', 'total'] | [['ralf schumann ( ger )', 'wcf 2007', 'defending champion', 'defending champion', 'defending champion'], ['oleksandr petriv ( ukr )', 'og beijing', 'olympic gold medalist', 'olympic gold medalist', 'olympic gold medalist'], ['christian reitz ( ger )', 'og beijing', 'olympic bronze medalist', 'olympic bronze medalist', 'olympic bronze medalist'], ['sergei alifirenko ( rus )', 'wc beijing', '15', '10', '25'], ['leuris pupo ( cub )', 'wc rio de janeiro', '10', '11', '21'], ['iulian raicea ( rou )', 'wc rio de janeiro', '8', '9', '17'], ['ivan stoukachev ( rus )', 'wc milan', '8', '7', '15'], ['zhang penghui ( chn )', 'wc beijing', '8', '6', '14'], ['renã vogn ( den )', 'wc munich', '4', '7', '11'], ['jorge llames ( esp )', 'wc milan', '5', '6', '11'], ['josef fiala ( cze )', 'wc munich', '5', '6', '11']] |
1996 - 97 european challenge cup | https://en.wikipedia.org/wiki/1996%E2%80%9397_European_Challenge_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16770037-5.html.csv | ordinal | borgoin scored the second highest points for in the 1996-97 european challenge cup . | {'row': '1', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points for', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points for ; 2 }'}, 'team'], 'result': 'bourgoin', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points for ; 2 } ; team }'}, 'bourgoin'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points for ; 2 } ; team } ; bourgoin } = true', 'tointer': 'select the row whose points for record of all rows is 2nd maximum . the team record of this row is bourgoin .'} | eq { hop { nth_argmax { all_rows ; points for ; 2 } ; team } ; bourgoin } = true | select the row whose points for record of all rows is 2nd maximum . the team record of this row is bourgoin . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points for_5': 5, '2_6': 6, 'team_7': 7, 'bourgoin_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'points for_5': 'points for', '2_6': '2', 'team_7': 'team', 'bourgoin_8': 'bourgoin'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points for_5': [0], '2_6': [0], 'team_7': [1], 'bourgoin_8': [2]} | ['team', 'tries for', 'tries against', 'try diff', 'points for', 'points against', 'points diff'] | [['bourgoin', '27', '4', '+ 23', '196', '66', '+ 130'], ['bordeaux - bègles', '29', '13', '+ 16', '195', '99', '+ 96'], ['swansea', '28', '19', '+ 9', '207', '138', '+ 69'], ['gloucester', '17', '17', '0', '119', '123', '4'], ['ebbw vale', '6', '36', '30', '48', '243', '195'], ['london irish', '12', '30', '18', '90', '186', '96']] |
ningde | https://en.wikipedia.org/wiki/Ningde | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2013618-1.html.csv | unique | pingnan county is the only administrative region in ningde with less than 100 population density . | {'scope': 'all', 'row': '6', 'col': '8', 'col_other': '1', 'criterion': 'less_than', 'value': '100', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'density', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose density record is less than 100 .', 'tostr': 'filter_less { all_rows ; density ; 100 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; density ; 100 } }', 'tointer': 'select the rows whose density record is less than 100 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'density', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose density record is less than 100 .', 'tostr': 'filter_less { all_rows ; density ; 100 }'}, 'english name'], 'result': 'pingnan county', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; density ; 100 } ; english name }'}, 'pingnan county'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; density ; 100 } ; english name } ; pingnan county }', 'tointer': 'the english name record of this unqiue row is pingnan county .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; density ; 100 } } ; eq { hop { filter_less { all_rows ; density ; 100 } ; english name } ; pingnan county } } = true', 'tointer': 'select the rows whose density record is less than 100 . there is only one such row in the table . the english name record of this unqiue row is pingnan county .'} | and { only { filter_less { all_rows ; density ; 100 } } ; eq { hop { filter_less { all_rows ; density ; 100 } ; english name } ; pingnan county } } = true | select the rows whose density record is less than 100 . there is only one such row in the table . the english name record of this unqiue row is pingnan county . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'density_7': 7, '100_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'english name_9': 9, 'pingnan county_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'density_7': 'density', '100_8': '100', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'english name_9': 'english name', 'pingnan county_10': 'pingnan county'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'density_7': [0], '100_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'english name_9': [2], 'pingnan county_10': [3]} | ['english name', 'simplified', 'traditional', 'pinyin', 'foochow', 'area', 'population', 'density'] | [['jiaocheng district', '蕉城区', '蕉城區', 'jiāochéng qū', 'ciĕu - siàng - kṳ̆', '1537', '429260', '279'], ["fu'an city", '福安市', '福安市', "fú ' ān shì", 'hók - ăng - chê', '1795', '563640', '314'], ['fuding city', '福鼎市', '福鼎市', 'fúdǐng shì', 'hók - tīng - chê', '1526', '529534', '347'], ['xiapu county', '霞浦县', '霞蒲縣', 'xiápǔ xiàn', 'hà - puō - ging', '1716', '461176', '269'], ['gutian county', '古田县', '古田縣', 'gǔtián xiàn', 'kŭ - chèng - ging', '2377', '323700', '136'], ['pingnan county', '屏南县', '屏南縣', 'píngnán xiàn', 'bìng - nàng - ging', '1485', '137724', '93'], ['shouning county', '寿宁县', '壽寧縣', 'shòuníng xiàn', 'sêu - nìng - ging', '1425', '175874', '123'], ['zherong county', '柘荣县', '柘榮縣', 'zhèróng xiàn', 'ciá - ìng - ging', '544', '88387', '162']] |
pavlina nola | https://en.wikipedia.org/wiki/Pavlina_Nola | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12878201-8.html.csv | majority | majority of tournaments won by pavlina nola were played on clay surface . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'winners'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome', 'winners'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; outcome ; winners }', 'tointer': 'select the rows whose outcome record fuzzily matches to winners .'}, 'surface', 'clay'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose outcome record fuzzily matches to winners . for the surface records of these rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { filter_eq { all_rows ; outcome ; winners } ; surface ; clay } = true'} | most_eq { filter_eq { all_rows ; outcome ; winners } ; surface ; clay } = true | select the rows whose outcome record fuzzily matches to winners . for the surface records of these rows , most of them fuzzily match to clay . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'outcome_4': 4, 'winners_5': 5, 'surface_6': 6, 'clay_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'outcome_4': 'outcome', 'winners_5': 'winners', 'surface_6': 'surface', 'clay_7': 'clay'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'outcome_4': [0], 'winners_5': [0], 'surface_6': [1], 'clay_7': [1]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['runner - ups', 'august 7 , 1995', 'horb , germany itf 10000', 'clay', 'anna linkova', 'ivana havrliková monika kratochvílová', '2 - 6 , 5 - 7'], ['winners', 'september 3 , 1995', 'bad nauheim , germany itf 10000', 'clay', 'renata kochta', 'dominika górecka petra plačkova', '7 - 6 , 6 - 2'], ['winners', 'september 17 , 1995', 'varna , bulgaria itf 10000', 'clay', 'dora djilianova', 'galina dimitrova dessislava topalova', '4 - 6 , 6 - 4 , 7 - 5'], ['runner - ups', 'october 1 , 1995', 'bucharest , romania itf 25000', 'clay', 'dora djilianova', 'angela kerek maja zivec - skulj', '6 - 2 , 6 - 7 ( 5 - 7 ) , 6 - 3'], ['winners', 'august 25 , 1996', 'bad nauheim , germany itf 10000', 'clay', 'meike froehlich', 'simona galikova patrícia marková', '7 - 6 ( 7 - 4 ) , 7 - 6 ( 12 - 10 )'], ['winners', 'september 15 , 1996', 'varna , bulgaria itf 10000', 'clay', 'antoaneta pandjerova', 'galina dimitrova dessislava topalova', '6 - 4 , 6 - 2'], ['winners', 'june 1 , 1997', 'bourgas , bulgaria itf 10000', 'hard', 'teodora nedeva', 'meike froehlich kristina pojatina', '6 - 1 , 6 - 2'], ['winners', 'july 20 , 1997', 'darmstadt , germany itf 25000', 'clay', 'svetlana krivencheva', 'olga ivanova magdalena feistel', '6 - 0 , 2 - 6 , 6 - 3'], ['winners', 'july 27 , 1997', 'rostock , germany itf 25000', 'clay', 'svetlana krivencheva', 'renée reid réka vidáts', 'w / o'], ['runner - ups', 'august 17 , 1997', 'bratislava , slovakia itf 75000', 'clay', 'svetlana krivencheva', 'laurence courtois henrieta nagyová', '1 - 6 , 0 - 6'], ['winners', 'october 18 , 1998', 'indian wells , ca , usa itf 25000', 'hard', 'lindsay lee - waters', 'erika de lone katie schlukebir', '6 - 0 , 6 - 7 ( 4 - 7 ) , 6 - 1']] |
members of the 9th seanad | https://en.wikipedia.org/wiki/Members_of_the_9th_Seanad | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15547445-1.html.csv | superlative | the party fine gael had the highest number of members in the administrative panel among parties in the 9th seanad . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'administrative panel'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; administrative panel }'}, 'party'], 'result': 'fine gael', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; administrative panel } ; party }'}, 'fine gael'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; administrative panel } ; party } ; fine gael } = true', 'tointer': 'select the row whose administrative panel record of all rows is maximum . the party record of this row is fine gael .'} | eq { hop { argmax { all_rows ; administrative panel } ; party } ; fine gael } = true | select the row whose administrative panel record of all rows is maximum . the party record of this row is fine gael . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'administrative panel_5': 5, 'party_6': 6, 'fine gael_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'administrative panel_5': 'administrative panel', 'party_6': 'party', 'fine gael_7': 'fine gael'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'administrative panel_5': [0], 'party_6': [1], 'fine gael_7': [2]} | ['party', 'administrative panel', 'agricultural panel', 'cultural and educational panel', 'industrial and commercial panel', 'labour panel', 'national university of ireland', 'university of dublin', 'nominated by the taoiseach', 'total'] | [['fianna fáil', '2', '4', '2', '3', '5', '0', '0', '9', '25'], ['fine gael', '3', '4', '3', '3', '2', '1', '0', '0', '16'], ['labour party', '1', '1', '0', '1', '2', '0', '0', '0', '5'], ['clann na talmhan', '0', '1', '0', '0', '0', '0', '0', '0', '1'], ['independent', '1', '0', '0', '1', '1', '2', '3', '1', '9'], ['total', '7', '11', '5', '9', '11', '3', '3', '11', '60']] |
united states house of representatives elections in georgia , 1996 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Georgia%2C_1996 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27487712-1.html.csv | majority | republicans won most of the seats in the 1996 elections for united states house of representatives in georgia . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'} | most_eq { all_rows ; party ; republican } = true | for the party records of all rows , most of them fuzzily match to republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]} | ['district', 'incumbent', 'party', 'elected', 'status', 'result'] | [["georgia 's 2nd", 'sanford bishop', 'democratic', '1992', 're - elected', 'sanford bishop ( d ) 53.97 % darrel ealum ( r ) 46.03 %'], ["georgia 's 3rd", 'mac collins', 'republican', '1992', 're - elected', 'mac collins ( r ) 61.11 % jim chafin ( d ) 38.89 %'], ["georgia 's 5th", 'john lewis', 'democratic', '1986', 're - elected', 'john lewis ( d ) unopposed'], ["georgia 's 6th", 'newt gingrich', 'republican', '1978', 're - elected', 'newt gingrich ( r ) 57.80 % michael coles ( d ) 42.20 %'], ["georgia 's 7th", 'bob barr', 'republican', '1994', 're - elected', 'bob barr ( r ) 57.80 % charlie watts ( d ) 42.20 %'], ["georgia 's 8th", 'saxby chambliss', 'republican', '1994', 're - elected', 'saxby chambliss ( r ) 52.56 % jim wiggins ( d ) 47.44 %'], ["georgia 's 9th", 'nathan deal', 'republican', '1992', 're - elected', 'nathan deal ( r ) 65.55 % ken poston ( d ) 34.45 %'], ["georgia 's 10th", 'charlie norwood', 'republican', '1994', 're - elected', 'charlie norwood ( r ) 52.34 % david bell ( d ) 47.65 %']] |
elena pampoulova | https://en.wikipedia.org/wiki/Elena_Pampoulova | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18330817-11.html.csv | count | elena pampoulova has a career record of 3 - 5 at two different gland slam tournaments . | {'scope': 'all', 'criterion': 'equal', 'value': '3 - 5', 'result': '2', 'col': '15', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'career win - loss', '3 - 5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose career win - loss record fuzzily matches to 3 - 5 .', 'tostr': 'filter_eq { all_rows ; career win - loss ; 3 - 5 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; career win - loss ; 3 - 5 } }', 'tointer': 'select the rows whose career win - loss record fuzzily matches to 3 - 5 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; career win - loss ; 3 - 5 } } ; 2 } = true', 'tointer': 'select the rows whose career win - loss record fuzzily matches to 3 - 5 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; career win - loss ; 3 - 5 } } ; 2 } = true | select the rows whose career win - loss record fuzzily matches to 3 - 5 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'career win - loss_5': 5, '3 - 5_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'career win - loss_5': 'career win - loss', '3 - 5_6': '3 - 5', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'career win - loss_5': [0], '3 - 5_6': [0], '2_7': [2]} | ['tournament', '1988', '1990', '1991', '1992', '1993', '1995', '1996', '1997', '1998', '1999', '2000', '2001', 'career sr', 'career win - loss'] | [['australian open', 'a', '2r', 'a', 'a', 'a', '1r', 'a', '1r', '2r', '2r', 'a', 'a', '0 / 5', '3 - 5'], ['french open', 'a', '2r', '1r', 'a', 'q1', '1r', '1r', '1r', '2r', '2r', 'q3', 'a', '0 / 7', '3 - 7'], ['wimbledon', 'a', 'a', '2r', 'a', 'a', '1r', '1r', 'a', '1r', '3r', 'a', 'a', '0 / 5', '3 - 5'], ['us open', 'a', '1r', 'a', 'a', 'a', '1r', '2r', '3r', '1r', '1r', 'a', 'a', '0 / 6', '3 - 6'], ['sr', '0 / 0', '0 / 3', '0 / 2', '0 / 0', '0 / 0', '0 / 4', '0 / 3', '0 / 3', '0 / 4', '0 / 4', '0 / 0', '0 / 0', '0 / 23', '12 - 23']] |
1935 masters tournament | https://en.wikipedia.org/wiki/1935_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12586224-4.html.csv | aggregation | in the 1935 masters tournament , for players who were under par , their average score was 284.2 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '284.2', 'subset': {'col': '5', 'criterion': 'less_than_eq', 'value': '-1'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'to par', '-1'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; to par ; -1 }', 'tointer': 'select the rows whose to par record is less than or equal to -1 .'}, 'score'], 'result': '284.2', 'ind': 1, 'tostr': 'avg { filter_less_eq { all_rows ; to par ; -1 } ; score }'}, '284.2'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less_eq { all_rows ; to par ; -1 } ; score } ; 284.2 } = true', 'tointer': 'select the rows whose to par record is less than or equal to -1 . the average of the score record of these rows is 284.2 .'} | round_eq { avg { filter_less_eq { all_rows ; to par ; -1 } ; score } ; 284.2 } = true | select the rows whose to par record is less than or equal to -1 . the average of the score record of these rows is 284.2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'to par_5': 5, '-1_6': 6, 'score_7': 7, '284.2_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'to par_5': 'to par', '-1_6': '-1', 'score_7': 'score', '284.2_8': '284.2'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'to par_5': [0], '-1_6': [0], 'score_7': [1], '284.2_8': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'gene sarazen', 'united states', '68 + 71 + 73 + 70 = 282', '- 6', 'playoff'], ['t1', 'craig wood', 'united states', '69 + 72 + 68 + 73 = 282', '- 6', 'playoff'], ['3', 'olin dutra', 'united states', '70 + 70 + 70 + 74 = 284', '- 4', '600'], ['4', 'henry picard', 'united states', '67 + 68 + 76 + 75 = 286', '- 2', '500'], ['5', 'denny shute', 'united states', '73 + 71 + 70 + 73 = 287', '- 1', '400'], ['6', 'lawson little ( a )', 'united states', '74 + 72 + 70 + 72 = 288', 'e', '0'], ['7', 'paul runyan', 'united states', '70 + 72 + 75 + 72 = 289', '+ 1', '300'], ['8', 'vic ghezzi', 'united states', '73 + 71 + 73 + 73 = 290', '+ 2', '250'], ['t9', 'bobby cruickshank', 'scotland', '76 + 70 + 73 + 72 = 291', '+ 3', '138'], ['t9', 'jimmy hines', 'united states', '70 + 70 + 77 + 74 = 291', '+ 3', '138'], ['t9', 'byron nelson', 'united states', '71 + 74 + 72 + 74 = 291', '+ 3', '138'], ['t9', 'joe turnesa', 'united states', '73 + 71 + 74 + 73 = 291', '+ 3', '138']] |
2004 úrvalsdeild | https://en.wikipedia.org/wiki/2004_%C3%9Arvalsdeild | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11179106-1.html.csv | aggregation | all teams in the 2004 season of úrvalsdeild had an average point score of around 24 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '24', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'goals against'], 'result': '24', 'ind': 0, 'tostr': 'avg { all_rows ; goals against }'}, '24'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; goals against } ; 24 } = true', 'tointer': 'the average of the goals against record of all rows is 24 .'} | round_eq { avg { all_rows ; goals against } ; 24 } = true | the average of the goals against record of all rows is 24 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'goals against_4': 4, '24_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'goals against_4': 'goals against', '24_5': '24'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'goals against_4': [0], '24_5': [1]} | ['team', 'played', 'draw', 'lost', 'goals for', 'goals against', 'goal difference', 'points'] | [['fh', '18', '7', '1', '33', '16', '+ 17', '37'], ['íbv', '18', '4', '5', '35', '20', '+ 15', '31'], ['ía', '18', '7', '3', '28', '19', '+ 9', '31'], ['fylkir', '18', '5', '5', '26', '20', '+ 6', '29'], ['keflavík', '18', '3', '8', '31', '33', '- 2', '24'], ['kr', '18', '7', '6', '21', '22', '- 1', '22'], ['grindavík', '18', '7', '6', '24', '31', '- 7', '22'], ['fram', '18', '5', '9', '19', '28', '- 9', '17'], ['víkingur', '18', '4', '10', '19', '30', '- 11', '16'], ['ka', '18', '3', '11', '13', '30', '- 17', '15']] |
california 's great america | https://en.wikipedia.org/wiki/California%27s_Great_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1680162-1.html.csv | comparative | the flight deck achieved a higher rating than the woodstock express . | {'row_1': '2', 'row_2': '8', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ride', 'flight deck'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ride record fuzzily matches to flight deck .', 'tostr': 'filter_eq { all_rows ; ride ; flight deck }'}, 'rating'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; ride ; flight deck } ; rating }', 'tointer': 'select the rows whose ride record fuzzily matches to flight deck . take the rating record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ride', 'woodstock express'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose ride record fuzzily matches to woodstock express .', 'tostr': 'filter_eq { all_rows ; ride ; woodstock express }'}, 'rating'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; ride ; woodstock express } ; rating }', 'tointer': 'select the rows whose ride record fuzzily matches to woodstock express . take the rating record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; ride ; flight deck } ; rating } ; hop { filter_eq { all_rows ; ride ; woodstock express } ; rating } } = true', 'tointer': 'select the rows whose ride record fuzzily matches to flight deck . take the rating record of this row . select the rows whose ride record fuzzily matches to woodstock express . take the rating record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; ride ; flight deck } ; rating } ; hop { filter_eq { all_rows ; ride ; woodstock express } ; rating } } = true | select the rows whose ride record fuzzily matches to flight deck . take the rating record of this row . select the rows whose ride record fuzzily matches to woodstock express . take the rating record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'ride_7': 7, 'flight deck_8': 8, 'rating_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'ride_11': 11, 'woodstock express_12': 12, 'rating_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'ride_7': 'ride', 'flight deck_8': 'flight deck', 'rating_9': 'rating', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'ride_11': 'ride', 'woodstock express_12': 'woodstock express', 'rating_13': 'rating'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'ride_7': [0], 'flight deck_8': [0], 'rating_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'ride_11': [1], 'woodstock express_12': [1], 'rating_13': [3]} | ['ride', 'year opened', 'ride manufacturer and type', 'minimum height', 'rating'] | [['the demon', '1980', 'arrow dynamics', '48', '5'], ['flight deck', '1993', 'bolliger & mabillard inverted roller coaster', '54', '5'], ['gold striker', '2013', 'great coasters international wooden roller coaster', '48', '4'], ['grizzly', '1986', 'wooden roller coaster', '48', '4'], ['psycho mouse', '2001', 'arrow dynamics wild mouse roller coaster', '44', '4'], ['taxi jam', '1999', 'e & f miller industries kiddie coaster', '36', '2'], ['vortex', '1991', 'bolliger & mabillard stand - up roller coaster', '54', '5'], ['woodstock express', '1987', 'intamin family roller coaster', '40', '3']] |
1980 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1980_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11406866-2.html.csv | count | in the 1980 tampa bay buccaneers season , among the games played in november , 1980 , 5 of them were played in tampa stadium . | {'scope': 'subset', 'criterion': 'equal', 'value': 'tampa stadium', 'result': '3', 'col': '6', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'november'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; november }', 'tointer': 'select the rows whose date record fuzzily matches to november .'}, 'game site', 'tampa stadium'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose game site record fuzzily matches to tampa stadium .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; november } ; game site ; tampa stadium }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; date ; november } ; game site ; tampa stadium } }', 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose game site record fuzzily matches to tampa stadium . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; date ; november } ; game site ; tampa stadium } } ; 3 } = true', 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose game site record fuzzily matches to tampa stadium . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; date ; november } ; game site ; tampa stadium } } ; 3 } = true | select the rows whose date record fuzzily matches to november . among these rows , select the rows whose game site record fuzzily matches to tampa stadium . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'november_7': 7, 'game site_8': 8, 'tampa stadium_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'november_7': 'november', 'game site_8': 'game site', 'tampa stadium_9': 'tampa stadium', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'november_7': [0], 'game site_8': [1], 'tampa stadium_9': [1], '3_10': [3]} | ['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'] | [['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'], ['1', 'september 7 , 1980', 'cincinnati bengals', 'w 17 - 12', '1:00', 'riverfront stadium', '35551', '1 - 0'], ['2', 'september 11 , 1980', 'los angeles rams', 'w 10 - 9', '9:00', 'tampa stadium', '66576', '2 - 0'], ['3', 'september 21 , 1980', 'dallas cowboys', 'l 28 - 17', '4:00', 'texas stadium', '62750', '2 - 1'], ['4', 'september 28 , 1980', 'cleveland browns', 'l 34 - 27', '1:00', 'tampa stadium', '65540', '2 - 2'], ['5', 'october 6 , 1980', 'chicago bears', 'l 23 - 0', '9:00', 'soldier field', '61350', '2 - 3'], ['6', 'october 12 , 1980', 'green bay packers', 't 14 - 14 ot', '1:00', 'tampa stadium', '64854', '2 - 3 - 1'], ['7', 'october 19 , 1980', 'houston oilers', 'l 20 - 14', '4:00', 'houston astrodome', '48167', '2 - 4 - 1'], ['8', 'october 26 , 1980', 'san francisco 49ers', 'w 24 - 23', '4:00', 'candlestick park', '51925', '3 - 4 - 1'], ['9', 'november 2 , 1980', 'new york giants', 'w 30 - 13', '1:00', 'tampa stadium', '68256', '4 - 4 - 1'], ['10', 'november 9 , 1980', 'pittsburgh steelers', 'l 24 - 21', '1:00', 'tampa stadium', '71636', '4 - 5 - 1'], ['11', 'november 16 , 1980', 'minnesota vikings', 'l 38 - 30', '2:00', 'metropolitan stadium', '46032', '4 - 6 - 1'], ['12', 'november 23 , 1980', 'detroit lions', 'l 24 - 10', '1:00', 'tampa stadium', '64976', '4 - 7 - 1'], ['13', 'november 30 , 1980', 'green bay packers', 'w 20 - 17', '2:00', 'milwaukee county stadium', '54225', '5 - 7 - 1'], ['14', 'december 7 , 1980', 'minnesota vikings', 'l 21 - 10', '1:00', 'tampa stadium', '65649', '5 - 8 - 1'], ['15', 'december 14 , 1980', 'detroit lions', 'l 27 - 14', '4:00', 'pontiac silverdome', '77098', '5 - 9 - 1'], ['16', 'december 20 , 1980', 'chicago bears', 'l 14 - 13', '4:00', 'tampa stadium', '55298', '5 - 10 - 1']] |
1987 - 88 bradford city a.f.c. season | https://en.wikipedia.org/wiki/1987%E2%80%9388_Bradford_City_A.F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18998832-5.html.csv | superlative | in the 1987 - 88 bradford city a.f.c. season , their game with luton town was the away game that drew the highest attendance . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3,4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'away'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'away'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; away }', 'tointer': 'select the rows whose venue record fuzzily matches to away .'}, 'attendance'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; venue ; away } ; attendance }'}, 'opponent'], 'result': 'luton town', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; venue ; away } ; attendance } ; opponent }'}, 'luton town'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; venue ; away } ; attendance } ; opponent } ; luton town } = true', 'tointer': 'select the rows whose venue record fuzzily matches to away . select the row whose attendance record of these rows is maximum . the opponent record of this row is luton town .'} | eq { hop { argmax { filter_eq { all_rows ; venue ; away } ; attendance } ; opponent } ; luton town } = true | select the rows whose venue record fuzzily matches to away . select the row whose attendance record of these rows is maximum . the opponent record of this row is luton town . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'venue_6': 6, 'away_7': 7, 'attendance_8': 8, 'opponent_9': 9, 'luton town_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'venue_6': 'venue', 'away_7': 'away', 'attendance_8': 'attendance', 'opponent_9': 'opponent', 'luton town_10': 'luton town'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'venue_6': [0], 'away_7': [0], 'attendance_8': [1], 'opponent_9': [2], 'luton town_10': [3]} | ['round ( leg )', 'date', 'opponent', 'venue', 'result', 'attendance'] | [['2 ( 1 )', '22 september 1987', 'fulham', 'away', '5 - 1', '4357'], ['2 ( 2 )', '7 october 1987', 'fulham', 'home', '2 - 1', '6408'], ['3', '27 october 1987', 'charlton athletic', 'away', '1 - 0', '3629'], ['4', '18 november 1987', 'reading', 'away', '0 - 0', '6784'], ['4r', '24 november 1987', 'reading', 'home', '1 - 0', '10448'], ['5', '19 january 1988', 'luton town', 'away', '0 - 2', '11022']] |
list of virginia covered bridges | https://en.wikipedia.org/wiki/List_of_Virginia_covered_bridges | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14218015-1.html.csv | aggregation | the average length of the covered bridges in virginia is 86.25 feet . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '86.25', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'length ( ft )'], 'result': '86.25', 'ind': 0, 'tostr': 'avg { all_rows ; length ( ft ) }'}, '86.25'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; length ( ft ) } ; 86.25 } = true', 'tointer': 'the average of the length ( ft ) record of all rows is 86.25 .'} | round_eq { avg { all_rows ; length ( ft ) } ; 86.25 } = true | the average of the length ( ft ) record of all rows is 86.25 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'length (ft)_4': 4, '86.25_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'length (ft)_4': 'length ( ft )', '86.25_5': '86.25'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'length (ft)_4': [0], '86.25_5': [1]} | ['name', 'county', 'location', 'built', 'length ( ft )', 'spans'] | [['biedler farm', 'rockingham', 'broadway', '1896', '93', 'smith creek'], ['bob white', 'patrick', 'woolwine', '1921', '80', 'smith river'], ['ck reynolds', 'giles', 'newport', '1919', '36', 'sinking creek'], ['humpback', 'alleghany', 'covington', '1857', '109', 'dunlap creek'], ["jack 's creek", 'patrick', 'woolwine', '1914', '48', 'smith river'], ['link farm', 'giles', 'newport', '1912', '49', 'sinking creek'], ["meem 's bottom", 'shenandoah', 'mount jackson', '1894', '204', 'north fork of the shenandoah river'], ['sinking creek', 'giles', 'newport', 'ca 1916', '71', 'sinking creek']] |
list of townships in north dakota | https://en.wikipedia.org/wiki/List_of_townships_in_North_Dakota | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18600760-24.html.csv | ordinal | ypsilanti is the township in north dakota that had the second highest population in 2010 . | {'row': '5', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'pop ( 2010 )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; pop ( 2010 ) ; 2 }'}, 'township'], 'result': 'ypsilanti', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pop ( 2010 ) ; 2 } ; township }'}, 'ypsilanti'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; pop ( 2010 ) ; 2 } ; township } ; ypsilanti } = true', 'tointer': 'select the row whose pop ( 2010 ) record of all rows is 2nd maximum . the township record of this row is ypsilanti .'} | eq { hop { nth_argmax { all_rows ; pop ( 2010 ) ; 2 } ; township } ; ypsilanti } = true | select the row whose pop ( 2010 ) record of all rows is 2nd maximum . the township record of this row is ypsilanti . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'pop (2010)_5': 5, '2_6': 6, 'township_7': 7, 'ypsilanti_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'pop (2010)_5': 'pop ( 2010 )', '2_6': '2', 'township_7': 'township', 'ypsilanti_8': 'ypsilanti'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'pop (2010)_5': [0], '2_6': [0], 'township_7': [1], 'ypsilanti_8': [2]} | ['township', 'county', 'pop ( 2010 )', 'land ( sqmi )', 'water ( sqmi )', 'latitude', 'longitude', 'geo id', 'ansi code'] | [['yellowstone', 'mckenzie', '417', '40.198', '2.136', '47.895843', '- 103.997037', '3805387820', '01759523'], ['york', 'benson', '27', '36.028', '0.273', '48.324845', '- 99.533482', '3800587900', '02397901'], ['yorktown', 'dickey', '50', '35.804', '0.000', '46.153339', '- 98.316833', '3802187940', '01036768'], ['young', 'dickey', '35', '34.347', '0.074', '46.230278', '- 98.834821', '3802187980', '01036780'], ['ypsilanti', 'stutsman', '128', '36.026', '0.000', '46.761455', '- 98.502295', '3809388060', '01036451']] |
great rivers athletic conference | https://en.wikipedia.org/wiki/Great_Rivers_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22319599-1.html.csv | majority | most of the schools in the great rivers athletic conference include black among their school colors . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'black', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'colors', 'black'], 'result': True, 'ind': 0, 'tointer': 'for the colors records of all rows , most of them fuzzily match to black .', 'tostr': 'most_eq { all_rows ; colors ; black } = true'} | most_eq { all_rows ; colors ; black } = true | for the colors records of all rows , most of them fuzzily match to black . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'colors_3': 3, 'black_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'colors_3': 'colors', 'black_4': 'black'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'colors_3': [0], 'black_4': [0]} | ['school', 'location', 'team name', 'colors', 'varsity teams', 'njcaa championships'] | [['john a logan college', 'carterville , il 62918', 'vols', 'black & white', '7', '0'], ['kaskaskia college', 'centralia , il 62801', 'blue devils & blue angels', 'navy & white', '12', '0'], ['lake land college', 'mattoon , il 61938', 'lakers', 'red & black', '6', '0'], ['lincoln trail college', 'robinson , il 62454', 'statesmen', 'green , orange , & black', '5', '0'], ['olney central college', 'olney , il 62450', 'blue knights', 'navy & white', '4', '0'], ['rend lake college', 'ina , il 62846', 'warriors', 'red , black , & white', '17', '5'], ['southeastern illinois college', 'harrisburg , il 62946', 'falcons', 'blue & gold', '4', '0'], ['southwestern illinois college', 'belleville , il 62221', 'blue storm', 'blue , black , & white', '8', '0']] |
atp bordeaux | https://en.wikipedia.org/wiki/ATP_Bordeaux | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16028631-1.html.csv | ordinal | the 2nd to last year for the atp bordeaux was when wayne ferreira was the champion . | {'row': '16', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year ; 2 }'}, 'champions'], 'result': 'wayne ferreira', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year ; 2 } ; champions }'}, 'wayne ferreira'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; year ; 2 } ; champions } ; wayne ferreira } = true', 'tointer': 'select the row whose year record of all rows is 2nd maximum . the champions record of this row is wayne ferreira .'} | eq { hop { nth_argmax { all_rows ; year ; 2 } ; champions } ; wayne ferreira } = true | select the row whose year record of all rows is 2nd maximum . the champions record of this row is wayne ferreira . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'champions_7': 7, 'wayne ferreira_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'year_5': 'year', '2_6': '2', 'champions_7': 'champions', 'wayne ferreira_8': 'wayne ferreira'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'champions_7': [1], 'wayne ferreira_8': [2]} | ['year', 'tournament name', 'champions', 'runners - up', 'score'] | [['1979', 'grand prix passing shot', 'yannick noah', 'harold solomon', '6 - 0 , 6 - 7 , 6 - 1 , 1 - 6 , 6 - 4'], ['1980', 'grand prix de passing shot', 'mario martinez', 'gianni ocleppo', '6 - 0 , 7 - 5 , 7 - 5'], ['1981', 'grand prix passing shot', 'andrés gómez', 'thierry tulasne', '7 - 6 , 7 - 6 , 6 - 1'], ['1982', 'grand prix passing shot', 'hans gildemeister', 'pablo arraya', '7 - 5 , 6 - 1'], ['1983', 'grand prix passing shot', 'pablo arraya', 'juan aguilera', '7 - 5 , 7 - 5'], ['1984', 'grand prix passing shot', 'josé higueras', 'francesco cancellotti', '7 - 6 , 6 - 1'], ['1985', 'nabisco grand prix passing shot', 'diego pérez', 'jimmy brown', '6 - 4 , 7 - 6'], ['1986', 'nabisco grand prix passing shot', 'paolo canè', 'kent carlsson', '6 - 4 , 1 - 6 , 7 - 5'], ['1987', 'nabisco grand prix passing shot', 'emilio sánchez', 'ronald agénor', '5 - 7 , 6 - 4 , 6 - 4'], ['1988', 'ngp passing shot de bordeaux', 'thomas muster', 'ronald agénor', '6 - 3 , 6 - 3'], ['1989', 'grand prix passing shot de bordeaux', 'ivan lendl', 'emilio sánchez', '6 - 2 , 6 - 2'], ['1990', 'grand prix passing shot', 'guy forget', 'goran ivanišević', '6 - 4 , 6 - 3'], ['1991', 'grand prix passing shot', 'guy forget', 'olivier delaître', '6 - 1 , 6 - 3'], ['1992', 'grand prix passing shot', 'andrei medvedev', 'sergi bruguera', '6 - 3 , 1 - 6 , 6 - 2'], ['1993', 'grand prix passing shot bordeaux', 'sergi bruguera', 'diego nargiso', '7 - 5 , 6 - 2'], ['1994', 'grand prix passing shot', 'wayne ferreira', 'jeff tarango', '6 - 0 , 7 - 5'], ['1995', 'grand prix passing shot bordeaux', 'yahiya doumbia', 'jakob hlasek', '6 - 4 , 6 - 4']] |
cultural interest fraternities and sororities | https://en.wikipedia.org/wiki/Cultural_interest_fraternities_and_sororities | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2538117-12.html.csv | ordinal | delta episilon sigma iota has the second earliest founding date of any of these organiations . | {'row': '8', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'founding date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; founding date ; 2 }'}, 'organization'], 'result': 'delta epsilon sigma iota', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; founding date ; 2 } ; organization }'}, 'delta epsilon sigma iota'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; founding date ; 2 } ; organization } ; delta epsilon sigma iota } = true', 'tointer': 'select the row whose founding date record of all rows is 2nd minimum . the organization record of this row is delta epsilon sigma iota .'} | eq { hop { nth_argmin { all_rows ; founding date ; 2 } ; organization } ; delta epsilon sigma iota } = true | select the row whose founding date record of all rows is 2nd minimum . the organization record of this row is delta epsilon sigma iota . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'founding date_5': 5, '2_6': 6, 'organization_7': 7, 'delta epsilon sigma iota_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'founding date_5': 'founding date', '2_6': '2', 'organization_7': 'organization', 'delta epsilon sigma iota_8': 'delta epsilon sigma iota'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'founding date_5': [0], '2_6': [0], 'organization_7': [1], 'delta epsilon sigma iota_8': [2]} | ['letters', 'organization', 'nickname', 'founding date', 'founding university', 'type'] | [['αιο', 'alpha iota omicron', 'aio', '1998 - 10 - 16', 'university of michigan', 'fraternity'], ['βχθ', 'beta chi theta 2', 'beta chi / bct', '1999 - 06 - 02', 'university of california , los angeles', 'fraternity'], ['βκγ', 'beta kappa gamma', 'bkg', '1999 - 05 - 06', 'university of texas at austin', 'fraternity'], ['δσι', 'delta sigma iota', 'dsi', '2000 - 08 - 15', 'pennsylvania state university', 'fraternity'], ['δεψ', 'delta epsilon psi', 'depsi / depsi', '1998 - 10 - 01', 'university of texas at austin', 'fraternity'], ['δθψ', 'delta theta psi', 'dtpsi', '2002 - 01 - 14', 'university of michigan', 'sorority'], ['δκδ', 'delta kappa delta 1', 'dkd', '2000 - 08 - 15', 'texas a & m university', 'sorority'], ['δeσι', 'delta epsilon sigma iota', 'desi', '1997 - 12 - 12', 'university at buffalo , suny', 'fraternity'], ['δφω', 'delta phi omega', 'dpo', '1998 - 12 - 06', 'university of houston', 'sorority'], ['ινδ', 'iota nu delta', 'ind', '1994 - 02 - 07', 'binghamton university', 'fraternity'], ['κφγ', 'kappa phi gamma', 'kphig', '1998 - 11 - 08', 'university of texas at austin', 'sorority']] |
washington redskins draft history | https://en.wikipedia.org/wiki/Washington_Redskins_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-57.html.csv | aggregation | the average pick for the washington redskins draft history is 15 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '15', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pick'], 'result': '15', 'ind': 0, 'tostr': 'avg { all_rows ; pick }'}, '15'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pick } ; 15 } = true', 'tointer': 'the average of the pick record of all rows is 15 .'} | round_eq { avg { all_rows ; pick } ; 15 } = true | the average of the pick record of all rows is 15 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pick_4': 4, '15_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pick_4': 'pick', '15_5': '15'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pick_4': [0], '15_5': [1]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['2', '3', '30', 'markus koch', 'de', 'boise state'], ['2', '18', '45', 'walter murray', 'wr', 'hawaii'], ['3', '20', '75', 'alvin walton', 'db', 'kansas'], ['5', '3', '113', 'ravin caldwell', 'lb', 'arkansas'], ['6', '8', '146', 'mark rypien', 'qb', 'washington state'], ['6', '18', '156', 'jim huddleston', 'g', 'virginia'], ['7', '20', '186', 'rick badanjek', 'rb', 'maryland'], ['8', '19', '213', 'kurt gouveia', 'lb', 'brigham young'], ['9', '18', '239', 'wayne asberry', 'db', 'texas a & m'], ['11', '20', '297', 'kenny fells', 'rb', 'henderson state'], ['12', '18', '323', 'eric yarber', 'wr', 'idaho']] |
comparison of top chess players throughout history | https://en.wikipedia.org/wiki/Comparison_of_top_chess_players_throughout_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1710426-1.html.csv | aggregation | the top chess players in history have an average 1-year elo peak rating of 2869 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '2869', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', '1 - year peak'], 'result': '2869', 'ind': 0, 'tostr': 'avg { all_rows ; 1 - year peak }'}, '2869'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; 1 - year peak } ; 2869 } = true', 'tointer': 'the average of the 1 - year peak record of all rows is 2869 .'} | round_eq { avg { all_rows ; 1 - year peak } ; 2869 } = true | the average of the 1 - year peak record of all rows is 2869 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, '1 - year peak_4': 4, '2869_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', '1 - year peak_4': '1 - year peak', '2869_5': '2869'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], '1 - year peak_4': [0], '2869_5': [1]} | ['rank', '1 - year peak', '5 - year peak', '10 - year peak', '15 - year peak', '20 - year peak'] | [['1', 'bobby fischer , 2881', 'garry kasparov , 2875', 'garry kasparov , 2863', 'garry kasparov , 2862', 'garry kasparov , 2856'], ['2', 'garry kasparov , 2879', 'emanuel lasker , 2854', 'emanuel lasker , 2847', 'anatoly karpov , 2820', 'anatoly karpov , 2818'], ['3', 'mikhail botvinnik , 2871', 'josé capablanca , 2843', 'anatoly karpov , 2821', 'emanuel lasker , 2816', 'emanuel lasker , 2809'], ['4', 'josé capablanca , 2866', 'mikhail botvinnik , 2843', 'josé capablanca , 2813', 'josé capablanca , 2798', 'alexander alekhine , 2781'], ['5', 'emanuel lasker , 2863', 'bobby fischer , 2841', 'bobby fischer , 2810', 'alexander alekhine , 2794', 'viktor korchnoi , 2766'], ['6', 'alexander alekhine , 2851', 'anatoly karpov , 2829', 'mikhail botvinnik , 2810', 'mikhail botvinnik , 2789', 'vasily smyslov , 2759']] |
sammy mcilroy | https://en.wikipedia.org/wiki/Sammy_McIlroy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1699550-1.html.csv | count | sammy mcilroy had 2 world cup qualifications in his career . | {'scope': 'all', 'criterion': 'equal', 'value': 'world cup qualification', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'world cup qualification'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to world cup qualification .', 'tostr': 'filter_eq { all_rows ; competition ; world cup qualification }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; competition ; world cup qualification } }', 'tointer': 'select the rows whose competition record fuzzily matches to world cup qualification . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; competition ; world cup qualification } } ; 2 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to world cup qualification . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; competition ; world cup qualification } } ; 2 } = true | select the rows whose competition record fuzzily matches to world cup qualification . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, 'world cup qualification_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', 'world cup qualification_6': 'world cup qualification', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'world cup qualification_6': [0], '2_7': [2]} | ['goal', 'date', 'venue', 'score', 'result', 'competition'] | [['1', '29 october 1975', 'belfast , northern ireland', '2 - 0', '3 - 0', 'euro 1976 qualification'], ['2', '21 september 1977', 'belfast , northern ireland', '2 - 0', '2 - 0', '1978 world cup qualification'], ['3', '15 october 1980', 'belfast , northern ireland', '2 - 0', '3 - 0', '1982 world cup qualification'], ['4', '28 april 1982', 'belfast , northern ireland', '1 - 1', '1 - 1', '1982 british home championship'], ['5', '13 december 1983', 'belfast , northern ireland', '2 - 0', '2 - 0', '1984 british home championship']] |
2007 - 08 washington capitals season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Washington_Capitals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11772462-6.html.csv | majority | all games of the washington capitals ' in the 2007 - 08 season were scheduled for the month of january . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'january', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'january'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to january .', 'tostr': 'all_eq { all_rows ; date ; january } = true'} | all_eq { all_rows ; date ; january } = true | for the date records of all rows , all of them fuzzily match to january . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'january_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'january_4': 'january'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'january_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['january 1', 'ottawa', '3 - 6', 'washington', 'kolzig', '14547', '16 - 19 - 5'], ['january 3', 'washington', '0 - 2', 'boston', 'kolzig', '12240', '16 - 20 - 5'], ['january 5', 'washington', '5 - 4', 'montreal', 'kolzig', '21273', '17 - 20 - 5'], ['january 9', 'colorado', '1 - 2', 'washington', 'kolzig', '16168', '18 - 20 - 5'], ['january 13', 'philadelphia', '6 - 4', 'washington', 'kolzig', '17713', '18 - 21 - 5'], ['january 15', 'ottawa', '2 - 4', 'washington', 'johnson', '15261', '19 - 21 - 5'], ['january 17', 'edmonton', '4 - 5', 'washington', 'kolzig', '13399', '20 - 21 - 5'], ['january 19', 'florida', '3 - 5', 'washington', 'johnson', '16973', '21 - 21 - 5'], ['january 21', 'washington', '6 - 5', 'pittsburgh', 'kolzig', '17050', '22 - 21 - 5'], ['january 23', 'washington', '2 - 3', 'toronto', 'kolzig', '19479', '22 - 22 - 5'], ['january 24', 'toronto', '1 - 2', 'washington', 'johnson', '14094', '23 - 22 - 5'], ['january 29', 'washington', '0 - 4', 'montreal', 'johnson', '21273', '23 - 23 - 5'], ['january 31', 'montreal', '4 - 5', 'washington', 'kolzig', '14930', '24 - 23 - 5']] |
houston dynamo records and statistics | https://en.wikipedia.org/wiki/Houston_Dynamo_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17984330-1.html.csv | aggregation | the houston dynamo players averaged around 3.3 goals in the concacaf . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '3.3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'concacaf'], 'result': '3.3', 'ind': 0, 'tostr': 'avg { all_rows ; concacaf }'}, '3.3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; concacaf } ; 3.3 } = true', 'tointer': 'the average of the concacaf record of all rows is 3.3 .'} | round_eq { avg { all_rows ; concacaf } ; 3.3 } = true | the average of the concacaf record of all rows is 3.3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'concacaf_4': 4, '3.3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'concacaf_4': 'concacaf', '3.3_5': '3.3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'concacaf_4': [0], '3.3_5': [1]} | ['name', 'years', 'mls cup', 'us open cup', 'concacaf', 'other', 'total'] | [['wade barrett', '2006 - present', '8', '2', '5', '9', '86'], ['pat onstad', '2006 - present', '9', '2', '4', '8', '82'], ['brian mullan', '2006 - present', '8', '2', '4', '7', '80'], ['dwayne de rosario', '2006 - present', '8', '2', '5', '9', '78'], ['eddie robinson', '2006 - present', '8', '3', '4', '7', '72'], ['craig waibel', '2006 - present', '8', '1', '4', '10', '72'], ['ryan cochrane', '2006 - 2007', '7', '3', '0', '6', '68'], ['ricardo clark', '2006 - present', '3', '1', '5', '6', '65'], ['brian ching', '2006 - present', '7', '1', '5', '8', '62'], ['brad davis', '2006 - present', '8', '1', '2', '6', '62'], ['stuart holden', '2006 - present', '6', '3', '0', '7', '51'], ['alejandro moreno', '2006', '4', '2', '1', '6', '47'], ['richard mulrooney', '2007 - present', '4', '0', '4', '5', '41']] |
german armed forces casualties in afghanistan | https://en.wikipedia.org/wiki/German_Armed_Forces_casualties_in_Afghanistan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12378453-8.html.csv | superlative | the incident on 2009 - 09 - 16 resulted in the most soldiers wounded in action for the german armed forces in afghanistan . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'casualties'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; casualties }'}, 'date'], 'result': '2009 - 09 - 16', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; casualties } ; date }'}, '2009 - 09 - 16'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; casualties } ; date } ; 2009 - 09 - 16 } = true', 'tointer': 'select the row whose casualties record of all rows is maximum . the date record of this row is 2009 - 09 - 16 .'} | eq { hop { argmax { all_rows ; casualties } ; date } ; 2009 - 09 - 16 } = true | select the row whose casualties record of all rows is maximum . the date record of this row is 2009 - 09 - 16 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'casualties_5': 5, 'date_6': 6, '2009 - 09 - 16_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'casualties_5': 'casualties', 'date_6': 'date', '2009 - 09 - 16_7': '2009 - 09 - 16'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'casualties_5': [0], 'date_6': [1], '2009 - 09 - 16_7': [2]} | ['date', 'location', 'nature of incident', 'circumstances', 'casualties'] | [['2009 - 02 - 11', 'mazar - i - sharif', 'unknown', 'unknown', '1 killed'], ['2009 - 03 - 14', 'fayzabad', 'non - hostile', 'traffic accident', '1 dead , 2 injured'], ['2009 - 04 - 29', 'kunduz area', 'hostile', 'suicide bomber attack', '5 wia'], ['2009 - 04 - 29', 'kunduz area', 'hostile', 'direct fire', '1 kia , 10 wia'], ['2009 - 05 - 06 to 2009 - 05 - 07', 'fayzabad area', 'hostile', 'combat', '1 wia'], ['2009 - 06 - 07', 'kunduz', 'hostile', 'direct fire', '2 wia'], ['2009 - 06 - 23', 'kunduz', 'hostile', 'combat', '3 kia , 3 wia'], ['2009 - 08 - 03', 'sheberghan', 'non - hostile', 'traffic accident', '6 wia'], ['2009 - 08 - 07', 'kunduz', 'hostile', 'direct fire', '1 wia'], ['2009 - 08 - 15', 'kunduz', 'hostile', 'direct fire', '1 wia'], ['2009 - 09 - 03', 'kunduz', 'hostile', 'combat', '4 wia'], ['2009 - 09 - 05', 'kunduz', 'hostile', 'svbied attack', '5 wia'], ['2009 - 09 - 16', 'kunduz', 'hostile', 'combat', '8 wia'], ['2009 - 11 - 11', 'kunduz', 'hostile', 'direct fire', '1 wia'], ['2009 - 12 - 05', 'mazar - i - sharif', 'non - hostile', 'accidental explosion', '3 injured'], ['2009 - 12 - 14', 'eshkashem', 'non - hostile', 'accident', '5 injured'], ['2009 - 12 - 16', 'kunduz', 'hostile', 'combat', '2 wia']] |
1975 - 76 boston celtics season | https://en.wikipedia.org/wiki/1975%E2%80%9376_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17342278-4.html.csv | majority | all games of the 1975 - 76 boston celtics season were scheduled for november . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'november', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to november .', 'tostr': 'all_eq { all_rows ; date ; november } = true'} | all_eq { all_rows ; date ; november } = true | for the date records of all rows , all of them fuzzily match to november . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'november_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'november_4': 'november'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'november_4': [0]} | ['game', 'date', 'team', 'score', 'location attendance', 'record'] | [['4', 'november 1', 'chicago', 'l 82 - 84', 'chicago stadium', '3 - 1'], ['5', 'november 5', 'buffalo', 'w 105 - 95', 'boston garden', '4 - 1'], ['6', 'november 7', 'milwaukee', 'l 101 - 104', 'mecca arena', '4 - 2'], ['7', 'november 8', 'detroit', 'w 118 - 104', 'cobo arena', '5 - 2'], ['8', 'november 11', 'atlanta', 'l 91 - 100', 'hartford civic center', '5 - 3'], ['9', 'november 13', 'washington', 'l 107 - 110', 'capital centre', '5 - 4'], ['10', 'november 14', 'philadelphia', 'l 109 - 119', 'boston garden', '5 - 5'], ['11', 'november 15', 'buffalo', 'w 112 - 110', 'buffalo memorial auditorium', '6 - 5'], ['12', 'november 21', 'new york', 'w 110 - 101', 'boston garden', '7 - 5'], ['13', 'november 23', 'cleveland', 'w 105 - 90', 'richfield coliseum', '8 - 5'], ['14', 'november 26', 'seattle', 'l 109 - 110', 'boston garden', '8 - 6'], ['15', 'november 28', 'atlanta', 'w 114 - 107', 'boston garden', '9 - 6']] |
2001 wta tier i series | https://en.wikipedia.org/wiki/2001_WTA_Tier_I_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16851172-1.html.csv | superlative | the last game in may of the 2001 wta tier i series was played on a clay surface . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'may'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'week', 'may'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; week ; may }', 'tointer': 'select the rows whose week record fuzzily matches to may .'}, 'week'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; week ; may } ; week }'}, 'surface'], 'result': 'clay', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; week ; may } ; week } ; surface }'}, 'clay'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; week ; may } ; week } ; surface } ; clay } = true', 'tointer': 'select the rows whose week record fuzzily matches to may . select the row whose week record of these rows is maximum . the surface record of this row is clay .'} | eq { hop { argmax { filter_eq { all_rows ; week ; may } ; week } ; surface } ; clay } = true | select the rows whose week record fuzzily matches to may . select the row whose week record of these rows is maximum . the surface record of this row is clay . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'week_6': 6, 'may_7': 7, 'week_8': 8, 'surface_9': 9, 'clay_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'week_6': 'week', 'may_7': 'may', 'week_8': 'week', 'surface_9': 'surface', 'clay_10': 'clay'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'week_6': [0], 'may_7': [0], 'week_8': [1], 'surface_9': [2], 'clay_10': [3]} | ['tournament', 'surface', 'week', 'winners', 'finalists', 'semifinalists'] | [['tokyo', 'carpet ( i )', 'january 29', 'lindsay davenport 6 - 7 ( 4 ) , 6 - 4 , 6 - 2', 'martina hingis', 'magdalena maleeva anna kournikova'], ['indian wells', 'hard', 'march 5', 'serena williams 4 - 6 , 6 - 4 , 6 - 2', 'kim clijsters', 'martina hingis venus williams'], ['miami', 'hard', 'march 19', 'venus williams 4 - 6 , 6 - 1 , 7 - 6 ( 4 )', 'jennifer capriati', 'martina hingis elena dementieva'], ['charleston', 'clay', 'april 16', 'jennifer capriati 6 - 0 , 4 - 6 , 6 - 4', 'martina hingis', 'conchita martínez marlene weingärtner'], ['berlin', 'clay', 'may 7', 'amélie mauresmo 6 - 4 , 2 - 6 , 6 - 3', 'jennifer capriati', 'martina hingis justine henin'], ['rome', 'clay', 'may 14', 'jelena dokić 7 - 6 ( 3 ) , 6 - 1', 'amélie mauresmo', 'martina hingis conchita martínez'], ['canada ( toronto )', 'hard', 'august 13', 'serena williams 6 - 1 , 6 - 7 ( 7 ) , 6 - 3', 'jennifer capriati', 'anke huber monica seles'], ['moscow', 'carpet ( i )', 'october 1', 'jelena dokić 6 - 3 , 6 - 3', 'elena dementieva', 'anastasia myskina silvia farina elia'], ['zurich', 'carpet ( i )', 'october 15', 'lindsay davenport 6 - 3 , 6 - 1', 'jelena dokić', 'nathalie tauziat jennifer capriati']] |
wake forest demon deacons football , 1980 - 89 | https://en.wikipedia.org/wiki/Wake_Forest_Demon_Deacons_football%2C_1980%E2%80%9389 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15531181-15.html.csv | superlative | the game played at memorial stadium clemson was the highest attended game . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'location'], 'result': 'memorial stadium clemson , sc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; location }'}, 'memorial stadium clemson , sc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; location } ; memorial stadium clemson , sc } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the location record of this row is memorial stadium clemson , sc .'} | eq { hop { argmax { all_rows ; attendance } ; location } ; memorial stadium clemson , sc } = true | select the row whose attendance record of all rows is maximum . the location record of this row is memorial stadium clemson , sc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'location_6': 6, 'memorial stadium clemson , sc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'location_6': 'location', 'memorial stadium clemson , sc_7': 'memorial stadium clemson , sc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'location_6': [1], 'memorial stadium clemson , sc_7': [2]} | ['date', 'opponent', 'location', 'result', 'attendance'] | [['09 / 12 / 1987', 'richmond', 'groves stadium winston - salem , nc', 'w 24 - 0', '14250'], ['09 / 19 / 1987', 'north carolina state', 'groves stadium winston - salem , nc', 'w 21 - 3', '23600'], ['09 / 26 / 1987', 'appalachian state', 'groves stadium winston - salem , nc', 'w 16 - 12', '33400'], ['10 / 01 / 1987', 'army', 'michie stadium west point , ny', 'w 17 - 13', '36690'], ['10 / 10 / 1987', 'north carolina', 'kenan memorial stadium chapel hill , nc', 'w 22 - 14', '50000'], ['10 / 17 / 1987', 'maryland', 'groves stadium winston - salem , nc', 'l 0 - 14', '25175'], ['10 / 24 / 1987', 'virginia', 'scott stadium charlottesville , va', 'l 21 - 35', '32500'], ['10 / 31 / 1987', '14 clemson', 'memorial stadium clemson , sc', 'l 17 - 31', '69711'], ['11 / 07 / 1987', 'duke', 'groves stadium winston - salem , nc', 'w 30 - 27', '23500'], ['11 / 14 / 1987', '14 south carolina', 'groves stadium winston - salem , nc', 'l 0 - 30', '34720'], ['11 / 21 / 1987', 'georgia tech', 'grant field atlanta , ga', 'w 33 - 6', '21114']] |
pemra \ xc3 \ xb6zgen | https://en.wikipedia.org/wiki/Pemra_%C3%96zgen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17373032-2.html.csv | count | in the list of final matches given pemra özgen won seven . | {'scope': 'all', 'criterion': 'equal', 'value': 'winner', 'result': '7', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose outcome record fuzzily matches to winner .', 'tostr': 'filter_eq { all_rows ; outcome ; winner }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; outcome ; winner } }', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; outcome ; winner } } ; 7 } = true', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; outcome ; winner } } ; 7 } = true | select the rows whose outcome record fuzzily matches to winner . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'outcome_5': 5, 'winner_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'outcome_5': 'outcome', 'winner_6': 'winner', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'outcome_5': [0], 'winner_6': [0], '7_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['winner', '11 july 2005', 'istanbul , turkey', 'hard', 'radana holušová', '6 - 4 6 - 3'], ['runner - up', '21 nov 2005', 'ashkelon , israel', 'hard', 'sharon fichman', '1 - 6 1 - 6'], ['runner - up', '26 may 2008', 'gaziantep , turkey', 'hard', 'cagla buyukakcay', '5 - 7 4 - 6'], ['winner', '02 june 2008', 'izmir , turkey', 'hard', 'vivian segnini', '6 - 2 7 - 6 ( 5 )'], ['winner', '09 june 2008', 'istanbul , turkey', 'hard', 'ekaterine gorgodze', '6 - 4 7 - 6 ( 1 )'], ['winner', '13 july 2009', 'izmir , turkey', 'hard', 'sandra zaniewska', '6 - 0 6 - 4'], ['winner', '02 aug 2010', 'gaziantep , turkey', 'hard', 'jade hopper', '6 - 4 6 - 4'], ['winner', '09 aug 2010', 'istanbul , turkey', 'hard', 'magali de lattre', '6 - 2 5 - 0 ret'], ['runner - up', '11 feb 2013', 'leimen , germany', 'hard ( i )', 'julia kimmelmann', '4 - 6 3 - 6'], ['winner', '15 july 2013', 'woking , great britain', 'hard', 'tara moore', '3 - 6 7 - 5 7 - 6 ( 10 )']] |
2003 - 04 toronto raptors season | https://en.wikipedia.org/wiki/2003%E2%80%9304_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15869204-7.html.csv | count | during this period of the 2003-04 toronto raptors season , the toronto raptors won four games . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; score ; w }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; w } }', 'tointer': 'select the rows whose score record fuzzily matches to w . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; w } } ; 4 } = true', 'tointer': 'select the rows whose score record fuzzily matches to w . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; score ; w } } ; 4 } = true | select the rows whose score record fuzzily matches to w . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'score_5': 5, 'w_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'score_5': 'score', 'w_6': 'w', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], 'w_6': [0], '4_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['45', 'february 1', 'la lakers', 'l 83 - 84 ( ot )', 'vince carter ( 27 )', 'chris bosh ( 14 )', 'morris peterson ( 4 )', 'air canada centre 20116', '21 - 24'], ['46', 'february 3', 'philadelphia', 'w 93 - 80 ( ot )', 'vince carter ( 33 )', 'donyell marshall ( 14 )', 'jalen rose ( 5 )', 'wachovia center 19049', '22 - 24'], ['47', 'february 4', 'orlando', 'w 110 - 90 ( ot )', 'donyell marshall ( 32 )', 'jérôme moïso ( 12 )', 'vince carter ( 9 )', 'air canada centre 16228', '23 - 24'], ['48', 'february 6', 'indiana', 'l 77 - 83 ( ot )', 'donyell marshall ( 24 )', 'jérôme moïso ( 11 )', 'vince carter ( 6 )', 'air canada centre 19311', '23 - 25'], ['49', 'february 8', 'golden state', 'w 84 - 81 ( ot )', 'vince carter ( 22 )', 'donyell marshall ( 13 )', 'vince carter ( 4 )', 'the arena in oakland 16873', '24 - 25'], ['50', 'february 10', 'phoenix', 'w 101 - 94 ( ot )', 'vince carter ( 29 )', 'donyell marshall ( 11 )', 'vince carter ( 6 )', 'america west arena 14138', '25 - 25'], ['51', 'february 12', 'seattle', 'l 74 - 94 ( ot )', 'alvin williams ( 20 )', 'donyell marshall ( 17 )', 'vince carter ( 7 )', 'keyarena 14239', '25 - 26'], ['52', 'february 17', 'chicago', 'l 73 - 75 ( ot )', 'vince carter ( 21 )', 'donyell marshall ( 24 )', 'alvin williams ( 6 )', 'united center 17822', '25 - 27'], ['53', 'february 18', 'san antonio', 'l 82 - 86 ( ot )', 'vince carter ( 22 )', 'donyell marshall ( 11 )', 'vince carter ( 6 )', 'air canada centre 17119', '25 - 28'], ['54', 'february 20', 'new jersey', 'l 72 - 91 ( ot )', 'donyell marshall ( 17 )', 'donyell marshall ( 13 )', 'alvin williams ( 6 )', 'air canada centre 19301', '25 - 29'], ['55', 'february 22', 'sacramento', 'l 81 - 96 ( ot )', 'chris bosh ( 20 )', 'donyell marshall ( 13 )', 'alvin williams ( 9 )', 'air canada centre 19800', '25 - 30'], ['56', 'february 24', 'new jersey', 'l 74 - 86 ( ot )', 'roger mason ( 18 )', 'jérôme moïso , morris peterson ( 6 )', 'milt palacio ( 5 )', 'continental airlines arena 12829', '25 - 31'], ['57', 'february 25', 'washington', 'l 74 - 76 ( ot )', 'donyell marshall ( 20 )', 'chris bosh ( 9 )', 'roger mason ( 6 )', 'air canada centre 17291', '25 - 32'], ['58', 'february 27', 'boston', 'l 75 - 88 ( ot )', 'donyell marshall ( 19 )', 'donyell marshall ( 13 )', 'roger mason , milt palacio ( 4 )', 'fleetcenter 16681', '25 - 33']] |
list of vancouver canucks draft picks | https://en.wikipedia.org/wiki/List_of_Vancouver_Canucks_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11636955-20.html.csv | majority | most of the players had a reg gp of 0 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'reg gp', '0'], 'result': True, 'ind': 0, 'tointer': 'for the reg gp records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; reg gp ; 0 } = true'} | most_eq { all_rows ; reg gp ; 0 } = true | for the reg gp records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'reg gp_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'reg gp_3': 'reg gp', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'reg gp_3': [0], '0_4': [0]} | ['rd', 'pick', 'player', 'team ( league )', 'reg gp', 'pl gp'] | [['1', '2', 'trevor linden', 'medicine hat tigers ( whl )', '1140', '118'], ['2', '33', 'leif rohlin', 'vik v채ster책s hk ( swe )', '95', '5'], ['3', '44', 'dane jackson', 'vernon lakers ( bcjhl )', '15', '6'], ['6', '107', "corrie d'alessio", 'cornell university ( ncaa )', '0', '0'], ['6', '122', 'phil von stefenelli', 'boston university ( ncaa )', '0', '0'], ['7', '128', 'dixon ward', 'university of north dakota ( ncaa )', '103', '9'], ['8', '149', 'greg geldart', 'st albert saints ( ajhl )', '0', '0'], ['9', '170', 'roger akerstrom', 'lule책 hf ( swe )', '0', '0'], ['10', '191', 'paul constantin', 'lake superior state university ( ncaa )', '0', '0'], ['11', '212', 'chris wolanin', 'university of illinois ( ncaa )', '0', '0'], ['12', '233', 'stefan nilsson', 'f채rjestad bk ( swe )', '0', '0']] |
bo ' ness and kinneil railway | https://en.wikipedia.org/wiki/Bo%27ness_and_Kinneil_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1174877-18.html.csv | unique | only one of the original tanker wagons from the bo ' ness and kinneil railway are currently operational . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'operational', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current status', 'operational'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current status record fuzzily matches to operational .', 'tostr': 'filter_eq { all_rows ; current status ; operational }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; current status ; operational } } = true', 'tointer': 'select the rows whose current status record fuzzily matches to operational . there is only one such row in the table .'} | only { filter_eq { all_rows ; current status ; operational } } = true | select the rows whose current status record fuzzily matches to operational . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'current status_4': 4, 'operational_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'current status_4': 'current status', 'operational_5': 'operational'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'current status_4': [0], 'operational_5': [0]} | ['number & name', 'description', 'current status', 'livery', 'date'] | [['scottish tar distillers no 78', 'rectangular tanker', 'static display in the museum', 'black', '1877'], ['oakbank oil company no 13', '10t tanker', 'static display in the museum', 'black', '1894'], ['no a43', 'shell bp tanker', 'static display in the museum', 'black', '1897'], ['naval store no 161', '14t tanker', 'static display in the museum', 'black', '1918'], ['briggs , dundee no 20', '14t tanker', 'operational', 'black', '1918'], ['briggs no 17', '14t tanker', 'stored', 'black', '1927'], ['no 206', '20t tanker', 'stored', 'silver dcl', '1930'], ['no 241', '20t tanker', 'stored', 'silver dcl', '1940'], ['no 4', '20t tanker', 'stored', 'bp chemicals', '1941'], ['no 14', '14t nitric acid tanker', 'static display in the museum', 'grey', '1941'], ['no 252', '20t tanker', 'stored', "distiller 's co ltd silver", '1951'], ['no 261', '20t tanker', 'stored', 'british hydrocarbon chemicals silver', '1956'], ['no bpo67496', '45t tta tanker', 'stored', 'bp green', '1966']] |
administrative divisions of lithuania | https://en.wikipedia.org/wiki/Administrative_divisions_of_Lithuania | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1784514-1.html.csv | comparative | samogitian eldership was established two years before trakai voivodeship . | {'row_1': '6', 'row_2': '7', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '2 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'voivodeship after 1569', 'samogitian eldership'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose voivodeship after 1569 record fuzzily matches to samogitian eldership .', 'tostr': 'filter_eq { all_rows ; voivodeship after 1569 ; samogitian eldership }'}, 'year established'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; voivodeship after 1569 ; samogitian eldership } ; year established }', 'tointer': 'select the rows whose voivodeship after 1569 record fuzzily matches to samogitian eldership . take the year established record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'voivodeship after 1569', 'trakai voivodeship'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose voivodeship after 1569 record fuzzily matches to trakai voivodeship .', 'tostr': 'filter_eq { all_rows ; voivodeship after 1569 ; trakai voivodeship }'}, 'year established'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; voivodeship after 1569 ; trakai voivodeship } ; year established }', 'tointer': 'select the rows whose voivodeship after 1569 record fuzzily matches to trakai voivodeship . take the year established record of this row .'}], 'result': '-2 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; voivodeship after 1569 ; samogitian eldership } ; year established } ; hop { filter_eq { all_rows ; voivodeship after 1569 ; trakai voivodeship } ; year established } }'}, '-2 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; voivodeship after 1569 ; samogitian eldership } ; year established } ; hop { filter_eq { all_rows ; voivodeship after 1569 ; trakai voivodeship } ; year established } } ; -2 years } = true', 'tointer': 'select the rows whose voivodeship after 1569 record fuzzily matches to samogitian eldership . take the year established record of this row . select the rows whose voivodeship after 1569 record fuzzily matches to trakai voivodeship . take the year established record of this row . the second record is 2 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; voivodeship after 1569 ; samogitian eldership } ; year established } ; hop { filter_eq { all_rows ; voivodeship after 1569 ; trakai voivodeship } ; year established } } ; -2 years } = true | select the rows whose voivodeship after 1569 record fuzzily matches to samogitian eldership . take the year established record of this row . select the rows whose voivodeship after 1569 record fuzzily matches to trakai voivodeship . take the year established record of this row . the second record is 2 years larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'voivodeship after 1569_8': 8, 'samogitian eldership_9': 9, 'year established_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'voivodeship after 1569_12': 12, 'trakai voivodeship_13': 13, 'year established_14': 14, '-2 years_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'voivodeship after 1569_8': 'voivodeship after 1569', 'samogitian eldership_9': 'samogitian eldership', 'year established_10': 'year established', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'voivodeship after 1569_12': 'voivodeship after 1569', 'trakai voivodeship_13': 'trakai voivodeship', 'year established_14': 'year established', '-2 years_15': '-2 years'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'voivodeship after 1569_8': [0], 'samogitian eldership_9': [0], 'year established_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'voivodeship after 1569_12': [1], 'trakai voivodeship_13': [1], 'year established_14': [3], '-2 years_15': [5]} | ['voivodeship after 1569', 'capital', 'year established', 'number of powiats', 'area ( km square ) in 1590 ( lithuanian ) category : articles with lithuanian - language external links'] | [['brest litovsk voivodeship', 'brest', '1566', '2 powiats', '40600'], ['minsk voivodeship', 'minsk', '1566', '3 powiats', '55500'], ['mstsislaw voivodeship', 'mstsislaw', '1566', '1 powiat', '22600'], ['nowogródek voivodeship', 'navahrudak', '1507', '3 powiats', '33200'], ['polotsk voivodeship', 'polotsk', '1504', '1 powiat', '21800'], ['samogitian eldership', 'raseiniai', '1411', '1 powiat', '23300'], ['trakai voivodeship', 'trakai', '1413', '4 powiats', '31100'], ['vilnius voivodeship', 'vilnius', '1413', '5 powiats', '44200']] |
2008 - 09 phoenix suns season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-8.html.csv | majority | during this period of the 2008-09 phoenix suns season , steve nash led the phoenix suns in assist in most of the games played . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'steve nash', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high assists', 'steve nash'], 'result': True, 'ind': 0, 'tointer': 'for the high assists records of all rows , most of them fuzzily match to steve nash .', 'tostr': 'most_eq { all_rows ; high assists ; steve nash } = true'} | most_eq { all_rows ; high assists ; steve nash } = true | for the high assists records of all rows , most of them fuzzily match to steve nash . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high assists_3': 3, 'steve nash_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high assists_3': 'high assists', 'steve nash_4': 'steve nash'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high assists_3': [0], 'steve nash_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['46', 'february 2', 'sacramento', 'w 129 - 81 ( ot )', "amar ' e stoudemire ( 25 )", 'steve nash ( 9 )', 'us airways center 18422', '26 - 20'], ['47', 'february 4', 'golden state', 'l 112 - 124 ( ot )', 'jason richardson ( 24 )', 'steve nash ( 9 )', 'oracle arena 19596', '26 - 21'], ['48', 'february 6', 'golden state', 'w 115 - 105 ( ot )', 'grant hill ( 27 )', 'steve nash ( 8 )', 'us airways center 18422', '27 - 21'], ['49', 'february 8', 'detroit', 'w 107 - 97 ( ot )', 'jason richardson ( 21 )', 'steve nash ( 21 )', 'the palace of auburn hills 22076', '28 - 21'], ['50', 'february 9', 'philadelphia', 'l 91 - 108 ( ot )', "amar ' e stoudemire ( 19 )", 'steve nash ( 8 )', 'wachovia center 16797', '28 - 22'], ['51', 'february 11', 'cleveland', 'l 92 - 109 ( ot )', "amar ' e stoudemire ( 27 )", 'leandro barbosa ( 7 )', 'quicken loans arena 20562', '28 - 23'], ['52', 'february 17', 'la clippers', 'w 140 - 100 ( ot )', 'leandro barbosa ( 24 )', 'steve nash ( 10 )', 'us airways center 18422', '29 - 23'], ['53', 'february 18', 'la clippers', 'w 142 - 119 ( ot )', "amar ' e stoudemire ( 42 )", 'steve nash ( 12 )', 'staples center 18169', '30 - 23'], ['54', 'february 20', 'oklahoma city', 'w 140 - 118 ( ot )', 'leandro barbosa ( 41 )', 'matt barnes ( 9 )', 'us airways center 18422', '31 - 23'], ['55', 'february 22', 'boston', 'l 108 - 128 ( ot )', 'jason richardson ( 21 )', 'steve nash ( 11 )', 'us airways center 18422', '31 - 24'], ['56', 'february 24', 'charlotte', 'w 112 - 102 ( ot )', 'steve nash ( 22 )', 'steve nash ( 5 )', 'us airways center 18422', '32 - 24'], ['57', 'february 26', 'la lakers', 'l 106 - 132 ( ot )', 'leandro barbosa ( 18 )', 'leandro barbosa ( 7 )', 'staples center 18997', '32 - 25'], ['58', 'february 27', 'toronto', 'w 133 - 113 ( ot )', "shaquille o'neal ( 45 )", 'grant hill ( 12 )', 'us airways center 18422', '33 - 25']] |
2006 latvian first league | https://en.wikipedia.org/wiki/2006_Latvian_First_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18017936-2.html.csv | comparative | the fk valmiera had a better position on the latvian first league of 2006 season compared to the fk auda kekava team . | {'row_1': '7', 'row_2': '14', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'fk valmiera'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to fk valmiera .', 'tostr': 'filter_eq { all_rows ; club ; fk valmiera }'}, 'position'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; fk valmiera } ; position }', 'tointer': 'select the rows whose club record fuzzily matches to fk valmiera . take the position record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'fk auda kekava'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to fk auda kekava .', 'tostr': 'filter_eq { all_rows ; club ; fk auda kekava }'}, 'position'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; fk auda kekava } ; position }', 'tointer': 'select the rows whose club record fuzzily matches to fk auda kekava . take the position record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; club ; fk valmiera } ; position } ; hop { filter_eq { all_rows ; club ; fk auda kekava } ; position } } = true', 'tointer': 'select the rows whose club record fuzzily matches to fk valmiera . take the position record of this row . select the rows whose club record fuzzily matches to fk auda kekava . take the position record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; club ; fk valmiera } ; position } ; hop { filter_eq { all_rows ; club ; fk auda kekava } ; position } } = true | select the rows whose club record fuzzily matches to fk valmiera . take the position record of this row . select the rows whose club record fuzzily matches to fk auda kekava . take the position record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'club_7': 7, 'fk valmiera_8': 8, 'position_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'fk auda kekava_12': 12, 'position_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'club_7': 'club', 'fk valmiera_8': 'fk valmiera', 'position_9': 'position', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'fk auda kekava_12': 'fk auda kekava', 'position_13': 'position'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'fk valmiera_8': [0], 'position_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'fk auda kekava_12': [1], 'position_13': [3]} | ['position', 'club', 'played', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'points', 'goal difference'] | [['1', 'jfk olimps r카ga', '30', '26', '2', '2', '111', '15', '80', '+ 96'], ['2', 'fc ditton - 2 daugavpils', '30', '21', '7', '2', '88', '24', '70', '+ 64'], ['3', 'skonto - 2 riga', '30', '20', '5', '5', '78', '23', '65', '+ 55'], ['4', 'ventspils - 2', '30', '20', '4', '6', '108', '25', '64', '+ 83'], ['5', 'r카ga - 2', '30', '17', '3', '10', '74', '44', '54', '+ 30'], ['6', 'dinaburg - zemessardze daugavpils', '30', '16', '3', '17', '60', '51', '51', '+ 9'], ['7', 'fk valmiera', '30', '13', '7', '10', '50', '53', '46', '- 3'], ['8', 'liepajas metalurgs - 2', '30', '13', '6', '11', '68', '47', '45', '+ 21'], ['9', 'fk jelgava', '30', '12', '6', '12', '53', '49', '42', '+ 4'], ['10', 'eirobaltija riga', '30', '11', '7', '12', '50', '40', '40', '+ 10'], ['11', 'j큰rmala - 2', '30', '10', '5', '15', '86', '74', '35', '+ 12'], ['12', 'tranz카ts ventspils', '30', '8', '4', '18', '37', '88', '28', '- 51'], ['13', 'multibanka riga', '30', '7', '6', '17', '34', '58', '27', '- 24'], ['14', 'fk auda kekava', '30', '5', '2', '23', '28', '79', '17', '- 51'], ['15', 'alberts riga', '30', '4', '4', '22', '32', '114', '16', '- 82'], ['16', 'abuls smiltene', '30', '1', '1', '28', '18', '191', '4', '- 173']] |
1981 vfl season | https://en.wikipedia.org/wiki/1981_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-3.html.csv | majority | all of the games were played on 11 april 1981 . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '11 april 1981', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '11 april 1981'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 11 april 1981 .', 'tostr': 'all_eq { all_rows ; date ; 11 april 1981 } = true'} | all_eq { all_rows ; date ; 11 april 1981 } = true | for the date records of all rows , all of them fuzzily match to 11 april 1981 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '11 april 1981_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '11 april 1981_4': '11 april 1981'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '11 april 1981_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '18.11 ( 119 )', 'melbourne', '18.12 ( 120 )', 'western oval', '13256', '11 april 1981'], ['carlton', '14.24 ( 108 )', 'fitzroy', '12.20 ( 92 )', 'princes park', '24780', '11 april 1981'], ['north melbourne', '15.26 ( 116 )', 'geelong', '14.5 ( 89 )', 'arden street oval', '17744', '11 april 1981'], ['richmond', '17.16 ( 118 )', 'essendon', '16.18 ( 114 )', 'mcg', '61908', '11 april 1981'], ['st kilda', '19.21 ( 135 )', 'collingwood', '23.19 ( 157 )', 'moorabbin oval', '33882', '11 april 1981'], ['south melbourne', '21.13 ( 139 )', 'hawthorn', '18.9 ( 117 )', 'vfl park', '21977', '11 april 1981']] |
1982 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1982_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12819742-2.html.csv | count | during the 1982 u.s. open , two players from the united states had a total score greater than 153 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '153', 'result': '2', 'col': '4', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'total', '153'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose total record is greater than 153 .', 'tostr': 'filter_greater { filter_eq { all_rows ; country ; united states } ; total ; 153 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; country ; united states } ; total ; 153 } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose total record is greater than 153 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; country ; united states } ; total ; 153 } } ; 2 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose total record is greater than 153 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_eq { all_rows ; country ; united states } ; total ; 153 } } ; 2 } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose total record is greater than 153 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'total_8': 8, '153_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'total_8': 'total', '153_9': '153', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'total_8': [1], '153_9': [1], '2_10': [3]} | ['player', 'country', 'year ( s ) won', 'total', 'to par'] | [['hubert green', 'united states', '1977', '152', '+ 8'], ['jerry pate', 'united states', '1976', '153', '+ 9'], ['lee trevino', 'united states', '1968 , 1971', '154', '+ 10'], ['arnold palmer', 'united states', '1960', '156', '+ 12'], ['gary player', 'south africa', '1965', '156', '+ 12']] |
phoenix suns all - time roster | https://en.wikipedia.org/wiki/Phoenix_Suns_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482079-12.html.csv | count | a total of seventeen players are listed in the phoenix suns all-time roster . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '17', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '17', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 17 .'}, '17'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 17 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 17 .'} | eq { count { filter_all { all_rows ; player } } ; 17 } = true | select the rows whose player record is arbitrary . the number of such rows is 17 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '17_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '17_6': '17'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '17_6': [2]} | ['player', 'pos', 'from', 'school / country', 'rebs', 'asts'] | [['maciej lampe', 'pf', '2004', 'poland', '76', '10'], ['andrew lang', 'c', '1988', 'arkansas', '1267', '100'], ['antonio lang', 'sf', '1994', 'duke', '4', '1'], ['dan langhi', 'pf', '2002', 'vanderbilt', '87', '21'], ['dave lattin', 'f / c', '1968', 'utep', '323', '48'], ['gani lawal', 'pf', '2010', 'georgia tech', '0', '0'], ['mo layton', 'pg', '1971', 'usc', '241', '386'], ['ron lee', 'pg', '1976', 'oregon', '666', '700'], ['tim legler', 'sg', '1990', 'la salle', '8', '6'], ['olexsiy alex len', 'c', '2013', 'maryland', '3', '0'], ['randy livingston', 'pg', '1999', 'lsu', '132', '173'], ['horacio llamas', 'c', '1997', 'grand canyon', '36', '5'], ['ian lockhart', 'pf', '1990', 'tennessee', '0', '0'], ['luc longley', 'c', '1999', 'new mexico', '544', '122'], ['robin lopez', 'c', '2008', 'stanford', '791', '43'], ['maurice lucas', 'pf', '1982', 'marquette', '2081', '567'], ['phil lumpkin', 'pg', '1975', 'miami ( ohio )', '23', '48']] |
united states house of representatives elections , 1968 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1968 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341738-19.html.csv | majority | all of the louisiana incumbents in the 1968 united states house of representatives elections were with the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'} | all_eq { all_rows ; party ; democratic } = true | for the party records of all rows , all of them fuzzily match to democratic . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', 'f edward hebert', 'democratic', '1940', 're - elected', 'f edward hebert ( d ) unopposed'], ['louisiana 2', 'hale boggs', 'democratic', '1946', 're - elected', 'hale boggs ( d ) 51.2 % david c treen ( r ) 48.8 %'], ['louisiana 3', 'edwin e willis', 'democratic', '1948', 'lost renomination democratic hold', 'patrick t caffery ( d ) unopposed'], ['louisiana 4', 'joe waggonner', 'democratic', '1961', 're - elected', 'joe waggonner ( d ) unopposed'], ['louisiana 5', 'otto passman', 'democratic', '1946', 're - elected', 'otto passman ( d ) unopposed'], ['louisiana 6', 'john rarick', 'democratic', '1966', 're - elected', 'john rarick ( d ) 79.3 % loyd j rockhold ( r ) 20.7 %'], ['louisiana 7', 'edwin edwards', 'democratic', '1965', 're - elected', 'edwin edwards ( d ) 84.9 % vance w plauche ( r ) 15.1 %']] |
best wnba player espy award | https://en.wikipedia.org/wiki/Best_WNBA_Player_ESPY_Award | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10525601-1.html.csv | majority | for the best wnba player espy award , most of the winners were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['year', 'player', 'nationality', 'position played', 'team represented'] | [['1998', 'cynthia cooper', 'united states', 'point guard', 'houston comets'], ['1999', 'cynthia cooper ( 2 )', 'united states', 'point guard', 'houston comets'], ['2000', 'cynthia cooper ( 3 )', 'united states', 'point guard', 'houston comets'], ['2001', 'sheryl swoopes', 'united states', 'small forward', 'houston comets'], ['2002', 'lisa leslie', 'united states', 'center', 'los angeles sparks'], ['2003', 'lisa leslie ( 2 )', 'united states', 'center', 'los angeles sparks'], ['2004', 'lauren jackson', 'australia', 'power forward', 'seattle storm'], ['2005', 'lauren jackson ( 2 )', 'australia', 'power forward', 'seattle storm'], ['2006', 'sheryl swoopes ( 2 )', 'united states', 'small forward', 'houston comets'], ['2007', 'lisa leslie ( 3 )', 'united states', 'center', 'los angeles sparks'], ['2008', 'lauren jackson ( 3 )', 'australia', 'power forward', 'seattle storm'], ['2009', 'candace parker', 'united states', 'power forward', 'los angeles sparks'], ['2010', 'diana taurasi', 'united states', 'shooting guard', 'phoenix mercury'], ['2011', 'diana taurasi ( 2 )', 'united states', 'shooting guard', 'phoenix mercury'], ['2012', 'diana taurasi ( 3 )', 'united states', 'shooting guard', 'phoenix mercury']] |
cho kwang - rae | https://en.wikipedia.org/wiki/Cho_Kwang-Rae | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12513368-1.html.csv | aggregation | choe kwang-rae scored a total of four goals in the 1979 president 's cup . | {'scope': 'subset', 'col': '3', 'type': 'sum', 'result': '4', 'subset': {'col': '5', 'criterion': 'equal', 'value': "1979 president 's cup"}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', "1979 president 's cup"], 'result': None, 'ind': 0, 'tostr': "filter_eq { all_rows ; competition ; 1979 president 's cup }", 'tointer': "select the rows whose competition record fuzzily matches to 1979 president 's cup ."}, 'score'], 'result': '4', 'ind': 1, 'tostr': "sum { filter_eq { all_rows ; competition ; 1979 president 's cup } ; score }"}, '4'], 'result': True, 'ind': 2, 'tostr': "round_eq { sum { filter_eq { all_rows ; competition ; 1979 president 's cup } ; score } ; 4 } = true", 'tointer': "select the rows whose competition record fuzzily matches to 1979 president 's cup . the sum of the score record of these rows is 4 ."} | round_eq { sum { filter_eq { all_rows ; competition ; 1979 president 's cup } ; score } ; 4 } = true | select the rows whose competition record fuzzily matches to 1979 president 's cup . the sum of the score record of these rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, "1979 president's cup_6": 6, 'score_7': 7, '4_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', "1979 president's cup_6": "1979 president 's cup", 'score_7': 'score', '4_8': '4'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], "1979 president's cup_6": [0], 'score_7': [1], '4_8': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['july 22 , 1977', 'kuala lumpur', '1 goal', '5 - 1', '1977 merdeka cup'], ['july 26 , 1977', 'kuala lumpur', '1 goal', '4 - 0', '1977 merdeka cup'], ['july 12 , 1978', 'kuala lumpur', '1 goal', '4 - 0', '1978 merdeka cup'], ['december 10 , 1978', 'bangkok', '2 goals', '5 - 1', '1978 asian games'], ['september 8 , 1979', 'seoul', '1 goal', '8 - 0', "1979 president 's cup"], ['september 16 , 1979', 'incheon', '3 goals', '9 - 0', "1979 president 's cup"], ['august 29 , 1980', 'gwangju', '1 goal', '5 - 0', "1980 president 's cup"], ['june 10 , 1986', 'puebla', '1 goal ( og )', '2 - 3', '1986 fifa world cup'], ['october 3 , 1986', 'seoul', '1 goal', '4 - 0', '1986 asian games'], ['october 5 , 1986', 'seoul', '1 goal', '2 - 0', '1986 asian games']] |
list of england national rugby union team results 1970 - 79 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1970%E2%80%9379 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178924-3.html.csv | aggregation | for the england national rugby union team results in 1970 - 79 , when the venue was london , the average against was 14 . | {'scope': 'subset', 'col': '2', 'type': 'average', 'result': '14', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'twickenham , london'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'twickenham , london'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; twickenham , london }', 'tointer': 'select the rows whose venue record fuzzily matches to twickenham , london .'}, 'against'], 'result': '14', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; venue ; twickenham , london } ; against }'}, '14'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; venue ; twickenham , london } ; against } ; 14 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to twickenham , london . the average of the against record of these rows is 14 .'} | round_eq { avg { filter_eq { all_rows ; venue ; twickenham , london } ; against } ; 14 } = true | select the rows whose venue record fuzzily matches to twickenham , london . the average of the against record of these rows is 14 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'twickenham, london_6': 6, 'against_7': 7, '14_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'twickenham, london_6': 'twickenham , london', 'against_7': 'against', '14_8': '14'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'twickenham, london_6': [0], 'against_7': [1], '14_8': [2]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['wales', '12', '15 / 01 / 1972', 'twickenham , london', 'five nations'], ['ireland', '16', '12 / 02 / 1972', 'twickenham , london', 'five nations'], ['france', '37', '26 / 02 / 1972', 'stade colombes , paris', 'five nations'], ['scotland', '23', '18 / 03 / 1972', 'murrayfield , edinburgh', 'five nations'], ['south africa', '9', '03 / 06 / 1972', 'ellis park , johannesburg', 'test match']] |
swimming at the 2008 summer olympics - men 's 100 metre backstroke | https://en.wikipedia.org/wiki/Swimming_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_100_metre_backstroke | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18624696-4.html.csv | majority | a majority of those swimming at the 2008 summer olympics cleared 54 seconds . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '54.0', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'time', '54.0'], 'result': True, 'ind': 0, 'tointer': 'for the time records of all rows , most of them are less than 54.0 .', 'tostr': 'most_less { all_rows ; time ; 54.0 } = true'} | most_less { all_rows ; time ; 54.0 } = true | for the time records of all rows , most of them are less than 54.0 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'time_3': 3, '54.0_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'time_3': 'time', '54.0_4': '54.0'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'time_3': [0], '54.0_4': [0]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'arkady vyatchanin', 'russia', '53.06'], ['2', '5', 'aschwin wildeboer faber', 'spain', '53.51'], ['3', '3', 'liam tancock', 'great britain', '53.61'], ['4', '2', 'junichi miyashita', 'japan', '53.69'], ['5', '7', 'tomomi morita', 'japan', '53.95'], ['6', '8', 'gregor tait', 'great britain', '54.37'], ['7', '6', 'ľuboš križko', 'slovakia', '54.38'], ['8', '1', 'mirco di tora', 'italy', '54.92']] |
missouri tigers men 's basketball | https://en.wikipedia.org/wiki/Missouri_Tigers_men%27s_basketball | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16201038-4.html.csv | majority | in their overall record , the missouri tigers hold a winning record against most of their opponents . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'current streak', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the current streak records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; current streak ; w } = true'} | most_eq { all_rows ; current streak ; w } = true | for the current streak records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'current streak_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'current streak_3': 'current streak', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'current streak_3': [0], 'w_4': [0]} | ['missouri vs', 'overall record', 'columbia', "opponent 's venue", 'neutral site', 'last 5 meetings', 'last 10 meetings', 'current streak'] | [['colorado', 'mu , 99 - 53', 'mu , 57 - 11', 'cu , 34 - 30', 'mu , 12 - 8', 'mu , 4 - 1', 'mu , 9 - 1', 'w 1'], ['creighton', 'mu , 9 - 7', 'mu , 3 - 2', 'tied , 4 - 4', 'mu , 2 - 1', 'mu , 3 - 2', 'cu , 6 - 4', 'l 1'], ['drake', 'mu , 27 - 7', 'mu , 17 - 3', 'mu , 10 - 4', 'tied , 0 - 0', 'mu , 4 - 1', 'mu , 8 - 2', 'w 4'], ['illinois', 'ui , 27 - 16', 'ui , 3 - 2', 'ui , 4 - 1', 'ui , 20 - 13', 'mu , 4 - 1', 'ui , 6 - 4', 'w 4'], ['indiana', 'tied , 9 - 9', 'mu , 5 - 3', 'iu , 6 - 3', 'mu , 1 - 0', 'mu , 4 - 1', 'tied , 5 - 5', 'w 3'], ['iowa', 'ui , 10 - 7', 'mu , 4 - 2', 'ui , 7 - 2', 'tied , 1 - 1', 'mu , 3 - 2', 'tied , 5 - 5', 'w 2'], ['nebraska', 'mu , 126 - 93', 'mu , 70 - 25', 'nu , 56 - 42', 'mu , 14 - 12', 'mu , 3 - 2', 'tied , 5 - 5', 'l 1'], ['saint louis', 'mu , 21 - 19', 'slu , 12 - 10', 'mu , 11 - 7', 'tied , 0 - 0', 'mu , 3 - 2', 'tied , 5 - 5', 'w 2'], ['washington u of stl', 'mu , 71 - 29', 'mu , 42 - 8', 'mu , 29 - 21', 'tied , 0 - 0', 'mu , 5 - 0', 'mu , 8 - 2', 'w 7']] |
2009 masters tournament | https://en.wikipedia.org/wiki/2009_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18812411-7.html.csv | count | at the 2009 masters tournament , 10 of the players were from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '10', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 10 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 10 .'} | eq { count { filter_eq { all_rows ; country ; united states } } ; 10 } = true | select the rows whose country record fuzzily matches to united states . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '10_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '10_7': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '10_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'ángel cabrera', 'argentina', '68 + 68 + 69 = 205', '- 11'], ['t1', 'kenny perry', 'united states', '68 + 67 + 70 = 205', '- 11'], ['3', 'chad campbell', 'united states', '65 + 70 + 72 = 207', '- 9'], ['4', 'jim furyk', 'united states', '66 + 74 + 68 = 208', '- 8'], ['5', 'steve stricker', 'united states', '72 + 69 + 68 = 209', '- 7'], ['t6', 'todd hamilton', 'united states', '68 + 70 + 72 = 210', '- 6'], ['t6', 'shingo katayama', 'japan', '67 + 73 + 70 = 210', '- 6'], ['t6', 'rory sabbatini', 'south africa', '73 + 67 + 70 = 210', '- 6'], ['9', 'tim clark', 'south africa', '68 + 71 + 72 = 211', '- 5'], ['t10', 'stephen ames', 'canada', '73 + 68 + 71 = 212', '- 4'], ['t10', 'anthony kim', 'united states', '75 + 65 + 72 = 212', '- 4'], ['t10', 'hunter mahan', 'united states', '66 + 75 + 71 = 212', '- 4'], ['t10', 'phil mickelson', 'united states', '73 + 68 + 71 = 212', '- 4'], ['t10', "sean o'hair", 'united states', '68 + 76 + 68 = 212', '- 4'], ['t10', 'ian poulter', 'england', '71 + 73 + 68 = 212', '- 4'], ['t10', 'lee westwood', 'england', '70 + 72 + 70 = 212', '- 4'], ['t10', 'tiger woods', 'united states', '70 + 72 + 70 = 212', '- 4']] |
1963 vfl season | https://en.wikipedia.org/wiki/1963_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10783853-9.html.csv | unique | in the 1963 vfl season , when the crowd is over 20000 , the only time the venue is mcg is when the home team is melbourne . | {'scope': 'subset', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'mcg', 'subset': {'col': '6', 'criterion': 'greater_than', 'value': '20000'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '20000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; crowd ; 20000 }', 'tointer': 'select the rows whose crowd record is greater than 20000 .'}, 'venue', 'mcg'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to mcg .', 'tostr': 'filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg } }', 'tointer': 'select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to mcg . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '20000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; crowd ; 20000 }', 'tointer': 'select the rows whose crowd record is greater than 20000 .'}, 'venue', 'mcg'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to mcg .', 'tostr': 'filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg }'}, 'home team score'], 'result': '18.6 ( 114 )', 'ind': 3, 'tostr': 'hop { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg } ; home team score }'}, '18.6 ( 114 )'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg } ; home team score } ; 18.6 ( 114 ) }', 'tointer': 'the home team score record of this unqiue row is 18.6 ( 114 ) .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg } } ; eq { hop { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg } ; home team score } ; 18.6 ( 114 ) } } = true', 'tointer': 'select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to mcg . there is only one such row in the table . the home team score record of this unqiue row is 18.6 ( 114 ) .'} | and { only { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg } } ; eq { hop { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; mcg } ; home team score } ; 18.6 ( 114 ) } } = true | select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to mcg . there is only one such row in the table . the home team score record of this unqiue row is 18.6 ( 114 ) . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '20000_9': 9, 'venue_10': 10, 'mcg_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'home team score_12': 12, '18.6 (114)_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '20000_9': '20000', 'venue_10': 'venue', 'mcg_11': 'mcg', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'home team score_12': 'home team score', '18.6 (114)_13': '18.6 ( 114 )'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_greater_0': [1], 'all_rows_7': [0], 'crowd_8': [0], '20000_9': [0], 'venue_10': [1], 'mcg_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'home team score_12': [3], '18.6 (114)_13': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '18.6 ( 114 )', 'north melbourne', '9.10 ( 64 )', 'mcg', '23971', '22 june 1963'], ['geelong', '16.13 ( 109 )', 'richmond', '10.11 ( 71 )', 'kardinia park', '20681', '22 june 1963'], ['essendon', '4.16 ( 40 )', 'st kilda', '8.8 ( 56 )', 'windy hill', '24725', '22 june 1963'], ['collingwood', '11.6 ( 72 )', 'footscray', '6.4 ( 40 )', 'victoria park', '26173', '22 june 1963'], ['south melbourne', '8.10 ( 58 )', 'fitzroy', '5.9 ( 39 )', 'lake oval', '12850', '22 june 1963'], ['hawthorn', '9.6 ( 60 )', 'carlton', '7.12 ( 54 )', 'glenferrie oval', '25300', '22 june 1963']] |
peseta | https://en.wikipedia.org/wiki/Peseta | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-158806-3.html.csv | superlative | the peseta with the highest weight is the one with a diameter of 28 mm . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'weight'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; weight }'}, 'diameter'], 'result': '28 mm', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; weight } ; diameter }'}, '28 mm'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; weight } ; diameter } ; 28 mm } = true', 'tointer': 'select the row whose weight record of all rows is maximum . the diameter record of this row is 28 mm .'} | eq { hop { argmax { all_rows ; weight } ; diameter } ; 28 mm } = true | select the row whose weight record of all rows is maximum . the diameter record of this row is 28 mm . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'weight_5': 5, 'diameter_6': 6, '28 mm_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'weight_5': 'weight', 'diameter_6': 'diameter', '28 mm_7': '28 mm'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'weight_5': [0], 'diameter_6': [1], '28 mm_7': [2]} | ['value', 'equiv', 'diameter', 'weight', 'composition'] | [['1', '0.006 ( 0.01 )', '14 mm', '0.55 g', 'aluminium'], ['5', '0.03', '17.5 mm', '3 g', 'aluminium bronze'], ['10', '0.06', '18.5 mm', '4 g', 'cupronickel'], ['25', '0.15', '19.5 mm', '4.25 g', 'aluminium bronze'], ['50', '0.30', '20.5 mm', '5.60 g', 'cupronickel'], ['100', '0.60', '24.5 mm', '9.25 g', 'aluminium bronze'], ['200', '1.20', '25.5 mm', '10.5 g', 'cupronickel'], ['500', '3.01', '28 mm', '12 gr', 'aluminium bronze']] |
list of top association football goal scorers | https://en.wikipedia.org/wiki/List_of_top_association_football_goal_scorers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11336844-1.html.csv | superlative | josef bican had the highest number of goals with 1468 scored during his time playing for the austria czech republic . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'goals'], 'result': '1468', 'ind': 0, 'tostr': 'max { all_rows ; goals }', 'tointer': 'the maximum goals record of all rows is 1468 .'}, '1468'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; goals } ; 1468 }', 'tointer': 'the maximum goals record of all rows is 1468 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'goals'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; goals }'}, 'country'], 'result': 'austria czech republic', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; goals } ; country }'}, 'austria czech republic'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; goals } ; country } ; austria czech republic }', 'tointer': 'the country record of the row with superlative goals record is austria czech republic .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; goals } ; 1468 } ; eq { hop { argmax { all_rows ; goals } ; country } ; austria czech republic } } = true', 'tointer': 'the maximum goals record of all rows is 1468 . the country record of the row with superlative goals record is austria czech republic .'} | and { eq { max { all_rows ; goals } ; 1468 } ; eq { hop { argmax { all_rows ; goals } ; country } ; austria czech republic } } = true | the maximum goals record of all rows is 1468 . the country record of the row with superlative goals record is austria czech republic . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'goals_8': 8, '1468_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'goals_11': 11, 'country_12': 12, 'austria czech republic_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'goals_8': 'goals', '1468_9': '1468', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'goals_11': 'goals', 'country_12': 'country', 'austria czech republic_13': 'austria czech republic'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'goals_8': [0], '1468_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'goals_11': [2], 'country_12': [3], 'austria czech republic_13': [4]} | ['rank', 'name', 'country', 'years', 'matches', 'goals'] | [['1', 'josef bican', 'austria czech republic', '1931 - 1956', '918', '1468'], ['2', 'gerd mã ¼ ller', 'germany', '1962 - 1983', '1216', '1461'], ['3', 'arthur friedenreich', 'brazil', '1909 - 1935', '1239', '1329'], ['4', 'pele', 'brazil', '1956 - 1990', '1375', '1284'], ['5', 'franz binder', 'austria germany', '1930 - 1949', '756', '1006'], ['6', 'romario', 'brazil', '1985 - 2007', '1188', '968'], ['7', 'ferenc puskas', 'hungary spain', '1943 - 1966', '754', '746']] |
liberty league | https://en.wikipedia.org/wiki/Liberty_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974482-1.html.csv | superlative | rochester institute of technology has the highest student enrollment of schools in the liberty league . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'institution'], 'result': 'rochester institute of technology', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; institution }'}, 'rochester institute of technology'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; institution } ; rochester institute of technology } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the institution record of this row is rochester institute of technology .'} | eq { hop { argmax { all_rows ; enrollment } ; institution } ; rochester institute of technology } = true | select the row whose enrollment record of all rows is maximum . the institution record of this row is rochester institute of technology . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'institution_6': 6, 'rochester institute of technology_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'institution_6': 'institution', 'rochester institute of technology_7': 'rochester institute of technology'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'institution_6': [1], 'rochester institute of technology_7': [2]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'joined'] | [['bard college', 'raptors', 'annandale - on - hudson , new york', '1860', 'private', '1958', '2011'], ['clarkson university', 'golden knights', 'potsdam , new york', '1896', 'private', '2848', '1995'], ['hobart college', 'statesmen', 'geneva , new york', '1822', 'private', '905', '1995'], ['rensselaer polytechnic institute', 'engineers', 'troy , new york', '1824', 'private', '5431', '1995'], ['rochester institute of technology', 'tigers', 'henrietta , new york', '1829', 'private', '14224', '2011'], ['university of rochester', 'yellowjackets', 'rochester , new york', '1850', 'private', '5601', '1995'], ['st lawrence university', 'saints', 'canton , new york', '1856', 'private', '2327', '1995'], ['skidmore college', 'thoroughbreds', 'saratoga springs , new york', '1903', 'private', '2734', '1995'], ['union college', 'dutchmen', 'schenectady , new york', '1795', 'private', '2197', '1995'], ['vassar college', 'brewers', 'poughkeepsie , new york', '1861', 'private', '2446', '2001']] |
1970 detroit lions season | https://en.wikipedia.org/wiki/1970_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18733362-2.html.csv | majority | the 1970 detroit lions won the majority of their games . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 20 , 1970', 'green bay packers', 'w 40 - 0', '56263'], ['2', 'september 27 , 1970', 'cincinnati bengals', 'w 38 - 3', '58202'], ['3', 'october 5 , 1970', 'chicago bears', 'w 28 - 14', '58210'], ['4', 'october 11 , 1970', 'washington redskins', 'l 31 - 10', '50414'], ['5', 'october 18 , 1970', 'cleveland browns', 'w 41 - 24', '83577'], ['6', 'october 25 , 1970', 'chicago bears', 'w 16 - 10', '45632'], ['7', 'november 1 , 1970', 'minnesota vikings', 'l 30 - 17', '58210'], ['8', 'november 8 , 1970', 'new orleans saints', 'l 19 - 17', '66910'], ['9', 'november 15 , 1970', 'minnesota vikings', 'l 24 - 20', '47900'], ['10', 'november 22 , 1970', 'san francisco 49ers', 'w 28 - 7', '56232'], ['11', 'november 26 , 1970', 'oakland raiders', 'w 28 - 14', '56597'], ['12', 'december 6 , 1970', 'st louis cardinals', 'w 16 - 3', '56362'], ['13', 'december 14 , 1970', 'los angeles rams', 'w 28 - 23', '79441'], ['14', 'december 20 , 1970', 'green bay packers', 'w 20 - 0', '57387']] |
united states house of representatives elections , 1976 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1976 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341672-6.html.csv | unique | the only democratic candidate to be elected in the united states house of representatives elections in 1976 that was first elected before 1960 . | {'scope': 'subset', 'row': '2', 'col': '4', 'col_other': 'n/a', 'criterion': 'less_than', 'value': '1960', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'democratic'}} | {'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; democratic }', 'tointer': 'select the rows whose party record fuzzily matches to democratic .'}, 'first elected', '1960'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose party record fuzzily matches to democratic . among these rows , select the rows whose first elected record is less than 1960 .', 'tostr': 'filter_less { filter_eq { all_rows ; party ; democratic } ; first elected ; 1960 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_eq { all_rows ; party ; democratic } ; first elected ; 1960 } } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . among these rows , select the rows whose first elected record is less than 1960 . there is only one such row in the table .'} | only { filter_less { filter_eq { all_rows ; party ; democratic } ; first elected ; 1960 } } = true | select the rows whose party record fuzzily matches to democratic . among these rows , select the rows whose first elected record is less than 1960 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'democratic_6': 6, 'first elected_7': 7, '1960_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'democratic_6': 'democratic', 'first elected_7': 'first elected', '1960_8': '1960'} | {'only_2': [3], 'result_3': [], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], 'first elected_7': [1], '1960_8': [1]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['california 4', 'robert l leggett', 'democratic', '1962', 're - elected', 'robert l leggett ( d ) 50.2 % albert dehr ( r ) 49.8 %'], ['california 14', 'john j mcfall', 'democratic', '1956', 're - elected', 'john j mcfall ( d ) 72.5 % roger a blain ( r ) 27.5 %'], ['california 16', 'burt l talcott', 'republican', '1962', 'lost re - election democratic gain', 'leon panetta ( d ) 53.4 % burt l talcott ( r ) 46.6 %'], ['california 18', 'william m ketchum', 'republican', '1972', 're - elected', 'william m ketchum ( r ) 64.2 % dean close ( d ) 35.8 %'], ['california 26', 'john h rousselot', 'republican', '1970', 're - elected', 'john h rousselot ( r ) 65.6 % bruce latta ( d ) 34.4 %'], ['california 27', 'alphonzo e bell , jr', 'republican', '1960', 'retired to run for u s senate republican hold', 'bob dornan ( r ) 54.7 % gary familian ( d ) 45.3 %'], ['california 31', 'charles h wilson', 'democratic', '1962', 're - elected', 'charles h wilson ( d ) unopposed'], ['california 33', 'del m clawson', 'republican', '1963', 're - elected', 'del m clawson ( r ) 55.1 % ted snyder ( d ) 44.9 %'], ['california 34', 'mark w hannaford', 'democratic', '1974', 're - elected', 'mark w hannaford ( d ) 50.7 % dan lungren ( r ) 49.3 %'], ['california 35', 'james f lloyd', 'democratic', '1974', 're - elected', 'james f lloyd ( d ) 53.3 % louis brutocao ( r ) 46.7 %'], ['california 40', 'andrew j hinshaw', 'republican', '1972', 'lost renomination republican hold', 'robert badham ( r ) 59.3 % vivian hall ( d ) 40.7 %'], ['california 41', 'bob wilson', 'republican', '1952', 're - elected', 'bob wilson ( r ) 57.7 % king golden , jr ( d ) 42.3 %'], ['california 42', 'lionel van deerlin', 'democratic', '1962', 're - elected', 'lionel van deerlin ( d ) 76.0 % wes marden ( r ) 24.0 %']] |
european film award for best short film | https://en.wikipedia.org/wiki/European_Film_Award_for_Best_Short_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12152327-4.html.csv | unique | prva plata was the only film nominated from bosnia and herzegovina country . | {'scope': 'all', 'row': '11', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'bosnia and herzegovina', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'bosnia and herzegovina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to bosnia and herzegovina .', 'tostr': 'filter_eq { all_rows ; country ; bosnia and herzegovina }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; bosnia and herzegovina } }', 'tointer': 'select the rows whose country record fuzzily matches to bosnia and herzegovina . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'bosnia and herzegovina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to bosnia and herzegovina .', 'tostr': 'filter_eq { all_rows ; country ; bosnia and herzegovina }'}, 'film'], 'result': 'prva plata', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; bosnia and herzegovina } ; film }'}, 'prva plata'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; bosnia and herzegovina } ; film } ; prva plata }', 'tointer': 'the film record of this unqiue row is prva plata .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; bosnia and herzegovina } } ; eq { hop { filter_eq { all_rows ; country ; bosnia and herzegovina } ; film } ; prva plata } } = true', 'tointer': 'select the rows whose country record fuzzily matches to bosnia and herzegovina . there is only one such row in the table . the film record of this unqiue row is prva plata .'} | and { only { filter_eq { all_rows ; country ; bosnia and herzegovina } } ; eq { hop { filter_eq { all_rows ; country ; bosnia and herzegovina } ; film } ; prva plata } } = true | select the rows whose country record fuzzily matches to bosnia and herzegovina . there is only one such row in the table . the film record of this unqiue row is prva plata . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'bosnia and herzegovina_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'film_9': 9, 'prva plata_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'bosnia and herzegovina_8': 'bosnia and herzegovina', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'film_9': 'film', 'prva plata_10': 'prva plata'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'bosnia and herzegovina_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'film_9': [2], 'prva plata_10': [3]} | ['category', 'film', 'director ( s )', 'country', 'nominating festival'] | [['short film 2005 prix uip', 'undressing my mother', 'ken wardrop', 'ireland', 'prix uip tampere'], ['short film 2005 prix uip', 'little terrorist', 'ashvin kumar', 'united kingdom', 'prix uip ghent'], ['short film 2005 prix uip', 'rendevú', 'ferenc cakó', 'hungary', 'prix uip valladolid'], ['short film 2005 prix uip', 'rain is falling', 'holger ernst', 'germany', 'prix uip valladolid'], ['short film 2005 prix uip', 'flatlife', 'jonas geirnaert', 'belgium', 'prix uip angers'], ['short film 2005 prix uip', 'hoi maya', 'claudia lorenz', 'switzerland', 'prix uip berlin'], ['short film 2005 prix uip', 'toz ( dust )', 'halit fatih kizilgok', 'turkey', 'prix uip cracow'], ['short film 2005 prix uip', 'bawke', 'hisham zaman', 'norway', 'prix uip grimstad'], ['short film 2005 prix uip', 'a serpente', 'sandro aguilar', 'portugal', 'prix uip vila do conde'], ['short film 2005 prix uip', 'scen nr 6882 ur mitt liv', 'ruben östlund', 'sweden', 'prix uip edinburgh'], ['short film 2005 prix uip', 'prva plata', 'alen drljević', 'bosnia and herzegovina', 'prix uip sarajevo'], ['short film 2005 prix uip', 'butterflies', 'max jacoby', 'luxembourg', 'prix uip venezia'], ['short film 2005 prix uip', 'minotauromaquia , pablo en el laberinto', 'juan pablo etcheverry', 'spain', 'prix uip drama']] |
united states district court for the northern district of iowa | https://en.wikipedia.org/wiki/United_States_District_Court_for_the_Northern_District_of_Iowa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11088781-2.html.csv | majority | the majority of the judges ' appointments were terminated because of death . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'death', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'reason for termination', 'death'], 'result': True, 'ind': 0, 'tointer': 'for the reason for termination records of all rows , most of them fuzzily match to death .', 'tostr': 'most_eq { all_rows ; reason for termination ; death } = true'} | most_eq { all_rows ; reason for termination ; death } = true | for the reason for termination records of all rows , most of them fuzzily match to death . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'reason for termination_3': 3, 'death_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'reason for termination_3': 'reason for termination', 'death_4': 'death'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'reason for termination_3': [0], 'death_4': [0]} | ['state', 'born / died', 'active service', 'chief judge', 'senior status', 'appointed by', 'reason for termination'] | [['ia', '1833 - 1916', '1882 - 1903', '-', '-', 'arthur', 'retirement'], ['ia', '1846 - 1924', '1904 - 1921', '-', '1921 - 1924', 't roosevelt', 'death'], ['ia', '1864 - 1948', '1922 - 1943', '-', '1943 - 1948', 'harding', 'death'], ['ia', '1893 - 1970', '1944 - 1961', '1961', '1961 - 1970', 'f roosevelt', 'death'], ['ia', '1909 - 1995', '1962 - 1977', '-', '1977 - 1995', 'kennedy', 'death'], ['ia', '1939 - present', '1986 - 1991', '-', '-', 'reagan', 'reappointment'], ['ia', '1948 - present', '1992 - 2002', '1992 - 1999', '-', 'ghw bush', 'reappointment']] |
athletics at the 1956 summer olympics - men 's long jump | https://en.wikipedia.org/wiki/Athletics_at_the_1956_Summer_Olympics_%E2%80%93_Men%27s_long_jump | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10676139-2.html.csv | majority | the majority of contestants in the 1956 summer olympics - men 's long jump recorded a best jump of over 7 meters . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': 'over 7 meters', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'best jump', 'over 7 meters'], 'result': True, 'ind': 0, 'tointer': 'for the best jump records of all rows , most of them are greater than over 7 meters .', 'tostr': 'most_greater { all_rows ; best jump ; over 7 meters } = true'} | most_greater { all_rows ; best jump ; over 7 meters } = true | for the best jump records of all rows , most of them are greater than over 7 meters . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'best jump_3': 3, 'over 7 meters_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'best jump_3': 'best jump', 'over 7 meters_4': 'over 7 meters'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'best jump_3': [0], 'over 7 meters_4': [0]} | ['athlete name', 'jump 1', 'jump 2', 'jump 3', 'best jump'] | [['gregory bell ( usa )', '6.98', '7.83', '7.77', '7.83 m'], ['john bennett ( usa )', '7.68', '7.61', 'x', '7.68 m'], ['jorma valkama ( fin )', '7.11', 'x', '7.48', '7.48 m'], ['dmitriy bondarenko ( urs )', '7.44', 'x', '7.13', '7.44 m'], ['karim olowu ( ngr )', '7.28', '6.77', '7.36', '7.36 m'], ['kazimierz kropidlowski ( pol )', '7.27', '6.92', '7.30', '7.30 m'], ['neville price ( rsa )', 'x', '7.28', 'x', '7.28 m'], ['oleg fyodoseyev ( urs )', 'x', '7.25', '7.27', '7.27 m'], ['arthur gruttenden ( gbr )', '7.15', 'x', '6.96', '7.15 m'], ['henryk grabowski ( pol )', 'x', 'x', '7.15', '7.15 m'], ['ken wilmshurst ( gbr )', '7.14', '7.06', '7.05', '7.14 m'], ['fermã\xadn donazar ( uru )', 'x', 'x', '6.57', '6.57 m'], ['igor ter - ovanesian ( urs )', 'x', 'x', 'x', 'no mark']] |
provinces of korea | https://en.wikipedia.org/wiki/Provinces_of_Korea | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-160510-3.html.csv | count | in the provinces of korea , chungcheong dialect is one of the korean dialects in haeso region . | {'scope': 'subset', 'criterion': 'equal', 'value': 'chungcheong dialect', 'result': '1', 'col': '8', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'hoseo'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'hoseo'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; region ; hoseo }', 'tointer': 'select the rows whose region record fuzzily matches to hoseo .'}, 'korean dialect', 'chungcheong dialect'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose region record fuzzily matches to hoseo . among these rows , select the rows whose korean dialect record fuzzily matches to chungcheong dialect .', 'tostr': 'filter_eq { filter_eq { all_rows ; region ; hoseo } ; korean dialect ; chungcheong dialect }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; region ; hoseo } ; korean dialect ; chungcheong dialect } }', 'tointer': 'select the rows whose region record fuzzily matches to hoseo . among these rows , select the rows whose korean dialect record fuzzily matches to chungcheong dialect . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; region ; hoseo } ; korean dialect ; chungcheong dialect } } ; 1 } = true', 'tointer': 'select the rows whose region record fuzzily matches to hoseo . among these rows , select the rows whose korean dialect record fuzzily matches to chungcheong dialect . the number of such rows is 1 .'} | eq { count { filter_eq { filter_eq { all_rows ; region ; hoseo } ; korean dialect ; chungcheong dialect } } ; 1 } = true | select the rows whose region record fuzzily matches to hoseo . among these rows , select the rows whose korean dialect record fuzzily matches to chungcheong dialect . the number of such rows is 1 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'region_6': 6, 'hoseo_7': 7, 'korean dialect_8': 8, 'chungcheong dialect_9': 9, '1_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'region_6': 'region', 'hoseo_7': 'hoseo', 'korean dialect_8': 'korean dialect', 'chungcheong dialect_9': 'chungcheong dialect', '1_10': '1'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'region_6': [0], 'hoseo_7': [0], 'korean dialect_8': [1], 'chungcheong dialect_9': [1], '1_10': [3]} | ['rr romaja', 'm - r romaja', 'hangul', 'hanja', 'name origin', 'capital', 'region', 'korean dialect', 'post - 1896 provinces'] | [['chungcheong', "ch ' ungch ' ŏng", '충청도', '忠淸道', 'chungju ( 충주 忠州 ) , cheongju ( 청주 淸州 )', 'gongju', 'hoseo', 'chungcheong dialect', 'chungcheongbuk chungcheongnam'], ['gangwon', 'kangwŏn', '강원도', '江原道', 'gangneung ( 강릉 江陵 ) , wonju ( 원주 原州 )', 'wonju', 'gwandong ( yeongseo , yeongdong ( 1 ) )', 'gangwon dialect', 'gangwon'], ['gyeonggi', 'kyŏnggi', '경기도', '京畿道', '( see note )', 'hanseong ( seoul )', 'gijeon ( 2 )', 'seoul dialect', 'gyeonggi'], ['gyeongsang', 'kyŏngsang', '경상도', '慶尙道', 'gyeongju ( 경주 慶州 ) , sangju ( 상주 尙州 )', 'daegu', 'yeongnam', 'gyeongsang dialect', 'gyeongsangbuk gyeongsangnam'], ['hamgyeong', 'hamgyŏng', '함경도', '咸鏡道', 'hamhung ( 함흥 咸興 ) , kyongsong ( 경성 鏡城 )', 'hamhung', 'kwanbuk , kwannam ( 3 )', 'hamgyŏng dialect', 'hamgyŏngbuk hamgyŏngnam'], ['hwanghae', 'hwanghae', '황해도', '黃海道', 'hwangju ( 황주 黃州 ) , haeju ( 해주 海州 )', 'haeju', 'haeso', 'hwanghae dialect', 'hwanghae ( 4 )'], ['jeolla', 'chŏlla', '전라도', '全羅道', 'jeonju ( 전주 全州 ) , naju ( 나주 羅州 ) ( 5 )', 'jeonju', 'honam', 'jeolla dialect , jeju language ( 6 )', 'jeollabuk jeollanam'], ['pyeongan', "p ' yŏngan", '평안도', '平安道', 'pyongyang ( 평양 平壤 ) , anju ( 안주 安州 )', 'pyongyang', 'kwanso', 'pyongan dialect', "p ' yŏnganbuk p ' yŏngannam"]] |
montenegro at the 2008 summer olympics | https://en.wikipedia.org/wiki/Montenegro_at_the_2008_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15170808-7.html.csv | unique | the only player from pro recco is predrag jokić . | {'scope': 'all', 'row': '12', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'pro recco', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'pro recco'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to pro recco .', 'tostr': 'filter_eq { all_rows ; club ; pro recco }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; club ; pro recco } }', 'tointer': 'select the rows whose club record fuzzily matches to pro recco . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'pro recco'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to pro recco .', 'tostr': 'filter_eq { all_rows ; club ; pro recco }'}, 'name v t e'], 'result': 'predrag jokić', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; pro recco } ; name v t e }'}, 'predrag jokić'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; club ; pro recco } ; name v t e } ; predrag jokić }', 'tointer': 'the name v t e record of this unqiue row is predrag jokić .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; club ; pro recco } } ; eq { hop { filter_eq { all_rows ; club ; pro recco } ; name v t e } ; predrag jokić } } = true', 'tointer': 'select the rows whose club record fuzzily matches to pro recco . there is only one such row in the table . the name v t e record of this unqiue row is predrag jokić .'} | and { only { filter_eq { all_rows ; club ; pro recco } } ; eq { hop { filter_eq { all_rows ; club ; pro recco } ; name v t e } ; predrag jokić } } = true | select the rows whose club record fuzzily matches to pro recco . there is only one such row in the table . the name v t e record of this unqiue row is predrag jokić . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'club_7': 7, 'pro recco_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name v t e_9': 9, 'predrag jokić_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'club_7': 'club', 'pro recco_8': 'pro recco', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name v t e_9': 'name v t e', 'predrag jokić_10': 'predrag jokić'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'club_7': [0], 'pro recco_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name v t e_9': [2], 'predrag jokić_10': [3]} | ['name v t e', 'pos', 'height', 'weight', 'club'] | [['zdravko radić', 'gk', 'm', '-', 'vk primorac kotor'], ['draško brguljan', 'd', 'm', '-', 'vk primorac kotor'], ['vjekoslav pasković', 'd', 'm', '-', 'vk primorac kotor'], ['nikola vukčević', 'cf', 'm', '-', 'pvk jadran'], ['nikola janović', 'd', 'm', '-', 'posillipo naples'], ['milan tičić', 'cb', 'm', '-', 'pvk budvanska rivijera'], ['mlađan janović', 'd', 'm', '-', 'vk primorac kotor'], ['veljko uskoković', 'd', 'm', '-', 'pvk budvanska rivijera'], ['aleksandar ivović', 'cb', 'm', '-', 'pvk jadran'], ['boris zloković', 'cf', 'm', '-', 'posillipo naples'], ['vladimir gojković', 'd', 'm', '-', 'pvk jadran'], ['predrag jokić', 'cb', 'm', '-', 'pro recco'], ['miloš šćepanović', 'gk', 'm', '-', 'pvk jadran']] |
sunline | https://en.wikipedia.org/wiki/Sunline | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2581397-4.html.csv | aggregation | on average , sunline raced with a weight of 55.6 kg between august 19 , 2000 , and march 24 , 2001 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '55.6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weight ( kg )'], 'result': '55.6', 'ind': 0, 'tostr': 'avg { all_rows ; weight ( kg ) }'}, '55.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weight ( kg ) } ; 55.6 } = true', 'tointer': 'the average of the weight ( kg ) record of all rows is 55.6 .'} | round_eq { avg { all_rows ; weight ( kg ) } ; 55.6 } = true | the average of the weight ( kg ) record of all rows is 55.6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weight (kg)_4': 4, '55.6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weight (kg)_4': 'weight ( kg )', '55.6_5': '55.6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weight (kg)_4': [0], '55.6_5': [1]} | ['result', 'date', 'race', 'venue', 'group', 'distance', 'weight ( kg )', 'jockey', 'winner / 2nd'] | [['won', '19 august 2000', 'manikato stakes', 'moonee valley', 'g1', '1200 m', '55', 'g childs', '2nd - honour the name'], ['won', '3 september 2000', 'memsie stakes', 'caulfield', 'g2', '1400 m', '55.5', 'g childs', '2nd - umrum'], ['won', '16 september 2000', 'j f feehan stakes', 'moonee valley', 'g2', '1600 m', '55.5', 'g childs', '2nd - le zagaletta'], ['2nd', '7 october 2000', 'turnbull stakes', 'flemington', 'g2', '2000 m', '56.5', 'g childs', '1st - fairway'], ['won', '28 october 2000', 'cox plate', 'moonee valley', 'g1', '2040 m', '55.5', 'g childs', '2nd - diatribe'], ['won', '25 november 2000', 'breeders stakes', 'pukekohe', 'g2', '1400 m', '55.5', 'g childs', '2nd - amnesia'], ['won', '17 december 2000', 'hong kong mile', 'sha tin', 'g1', '1600 m', '56', 'g childs', '2nd - fairy king prawn'], ['won', '10 february 2001', 'waikato sprint', 'te rapa', 'g1', '1400 m', '56', 'g childs', '2nd - fritz'], ['won', '3 march 2001', 'apollo stakes', 'warwick farm', 'g2', '1400 m', '55.5', 'g childs', '2nd - celestial choir'], ['3rd', '24 march 2001', 'dubai duty free stakes', 'nad al sheba', 'g2', '1777 m', '55', 'g childs', '1st - jim and tonic']] |
caroline vis | https://en.wikipedia.org/wiki/Caroline_Vis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15335011-3.html.csv | comparative | caroline vis ' tournament in the usa took place 7 days before the tournament in canada . | {'row_1': '4', 'row_2': '5', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'toronto , canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to toronto , canada .', 'tostr': 'filter_eq { all_rows ; tournament ; toronto , canada }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to toronto , canada . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'paris , france'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to paris , france .', 'tostr': 'filter_eq { all_rows ; tournament ; paris , france }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; paris , france } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to paris , france . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; hop { filter_eq { all_rows ; tournament ; paris , france } ; date } }', 'tointer': 'select the rows whose tournament record fuzzily matches to toronto , canada . take the date record of this row . select the rows whose tournament record fuzzily matches to paris , france . take the date record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'toronto , canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to toronto , canada .', 'tostr': 'filter_eq { all_rows ; tournament ; toronto , canada }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to toronto , canada . take the date record of this row .'}, '11 august 1997'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; 11 august 1997 }', 'tointer': 'the date record of the first row is 11 august 1997 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'paris , france'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to paris , france .', 'tostr': 'filter_eq { all_rows ; tournament ; paris , france }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; paris , france } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to paris , france . take the date record of this row .'}, '22 february 1999'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; paris , france } ; date } ; 22 february 1999 }', 'tointer': 'the date record of the second row is 22 february 1999 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; 11 august 1997 } ; eq { hop { filter_eq { all_rows ; tournament ; paris , france } ; date } ; 22 february 1999 } }', 'tointer': 'the date record of the first row is 11 august 1997 . the date record of the second row is 22 february 1999 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; hop { filter_eq { all_rows ; tournament ; paris , france } ; date } } ; and { eq { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; 11 august 1997 } ; eq { hop { filter_eq { all_rows ; tournament ; paris , france } ; date } ; 22 february 1999 } } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to toronto , canada . take the date record of this row . select the rows whose tournament record fuzzily matches to paris , france . take the date record of this row . the first record is less than the second record . the date record of the first row is 11 august 1997 . the date record of the second row is 22 february 1999 .'} | and { less { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; hop { filter_eq { all_rows ; tournament ; paris , france } ; date } } ; and { eq { hop { filter_eq { all_rows ; tournament ; toronto , canada } ; date } ; 11 august 1997 } ; eq { hop { filter_eq { all_rows ; tournament ; paris , france } ; date } ; 22 february 1999 } } } = true | select the rows whose tournament record fuzzily matches to toronto , canada . take the date record of this row . select the rows whose tournament record fuzzily matches to paris , france . take the date record of this row . the first record is less than the second record . the date record of the first row is 11 august 1997 . the date record of the second row is 22 february 1999 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'tournament_11': 11, 'toronto , canada_12': 12, 'date_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'tournament_15': 15, 'paris , france_16': 16, 'date_17': 17, 'and_7': 7, 'str_eq_5': 5, '11 august 1997_18': 18, 'str_eq_6': 6, '22 february 1999_19': 19} | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'toronto , canada_12': 'toronto , canada', 'date_13': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'tournament_15': 'tournament', 'paris , france_16': 'paris , france', 'date_17': 'date', 'and_7': 'and', 'str_eq_5': 'str_eq', '11 august 1997_18': '11 august 1997', 'str_eq_6': 'str_eq', '22 february 1999_19': '22 february 1999'} | {'and_8': [9], 'result_9': [], 'less_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'tournament_11': [0], 'toronto , canada_12': [0], 'date_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'tournament_15': [1], 'paris , france_16': [1], 'date_17': [3], 'and_7': [8], 'str_eq_5': [7], '11 august 1997_18': [5], 'str_eq_6': [7], '22 february 1999_19': [6]} | ['date', 'tournament', 'surface', 'partnering', 'opponent in the final', 'score'] | [['4 may 1992', 'waregem , belgium', 'clay', 'manon bollegraf', 'elena bryukhovets petra langrová', '6 - 4 , 6 - 3'], ['18 october 1993', 'budapest , hungary', 'carpet ( i )', 'inés gorrochategui', 'sandra cecchini patricia tarabini', '6 - 1 , 6 - 3'], ['4 august 1997', 'los angeles , usa', 'hard', 'yayuk basuki', 'larisa neiland helena suková', '7 - 6 ( 9 - 7 ) , 6 - 3'], ['11 august 1997', 'toronto , canada', 'hard', 'yayuk basuki', 'nicole arendt manon bollegraf', '3 - 6 , 7 - 5 , 6 - 4'], ['22 february 1999', 'paris , france', 'carpet ( i )', 'irina spîrlea', 'elena likhovtseva ai sugiyama', '7 - 5 , 3 - 6 , 6 - 3'], ['20 september 1999', 'luxembourg , luxembourg', 'carpet ( i )', 'irina spîrlea', 'tina križan katarina srebotnik', '6 - 1 , 6 - 2'], ['25 october 1999', 'linz , austria', 'carpet ( i )', 'irina spîrlea', 'tina križan larisa neiland', '6 - 4 , 6 - 3'], ['13 november 2000', 'pattaya , thailand', 'hard', 'yayuk basuki', 'tina križan katarina srebotnik', '6 - 3 , 6 - 3'], ['12 february 2001', 'dubai , uae', 'hard', 'yayuk basuki', 'åsa svensson karina habšudová', '6 - 0 , 4 - 6 , 6 - 2']] |
portland timbers ( 2001 - 10 ) | https://en.wikipedia.org/wiki/Portland_Timbers_%282001%E2%80%9310%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14240688-1.html.csv | count | the boston timbers failed to qualify for the open cup three times . | {'scope': 'all', 'criterion': 'equal', 'value': 'did not qualify', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'open cup', 'did not qualify'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose open cup record fuzzily matches to did not qualify .', 'tostr': 'filter_eq { all_rows ; open cup ; did not qualify }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; open cup ; did not qualify } }', 'tointer': 'select the rows whose open cup record fuzzily matches to did not qualify . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; open cup ; did not qualify } } ; 3 } = true', 'tointer': 'select the rows whose open cup record fuzzily matches to did not qualify . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; open cup ; did not qualify } } ; 3 } = true | select the rows whose open cup record fuzzily matches to did not qualify . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'open cup_5': 5, 'did not qualify_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'open cup_5': 'open cup', 'did not qualify_6': 'did not qualify', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'open cup_5': [0], 'did not qualify_6': [0], '3_7': [2]} | ['year', 'division', 'league', 'regular season', 'playoffs', 'open cup', 'avg attendance'] | [['2001', '2', 'usl a - league', '4th , western', 'quarterfinals', 'did not qualify', '7169'], ['2002', '2', 'usl a - league', '2nd , pacific', '1st round', 'did not qualify', '6260'], ['2003', '2', 'usl a - league', '3rd , pacific', 'did not qualify', 'did not qualify', '5871'], ['2004', '2', 'usl a - league', '1st , western', 'quarterfinals', '4th round', '5628'], ['2005', '2', 'usl first division', '5th', 'quarterfinals', '4th round', '6028'], ['2006', '2', 'usl first division', '11th', 'did not qualify', '3rd round', '5575'], ['2007', '2', 'usl first division', '2nd', 'semifinals', '2nd round', '6851'], ['2008', '2', 'usl first division', '11th', 'did not qualify', '1st round', '8567'], ['2009', '2', 'usl first division', '1st', 'semifinals', '3rd round', '9734']] |
1984 denver broncos season | https://en.wikipedia.org/wiki/1984_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16729063-2.html.csv | ordinal | during the 1984 season , denver broncos ' game against the los angeles raiders recorded the highest attendance . | {'row': '9', 'col': '7', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'opponent'], 'result': 'los angeles raiders', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent }'}, 'los angeles raiders'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent } ; los angeles raiders } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the opponent record of this row is los angeles raiders .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent } ; los angeles raiders } = true | select the row whose attendance record of all rows is 1st maximum . the opponent record of this row is los angeles raiders . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'opponent_7': 7, 'los angeles raiders_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'opponent_7': 'opponent', 'los angeles raiders_8': 'los angeles raiders'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'opponent_7': [1], 'los angeles raiders_8': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 2', 'cincinnati bengals', 'w 20 - 17', 'mile high stadium', '1 - 0', '74178'], ['2', 'september 9', 'chicago bears', 'l 0 - 27', 'soldier field', '1 - 1', '54335'], ['3', 'september 16', 'cleveland browns', 'w 24 - 14', 'cleveland stadium', '2 - 1', '61980'], ['4', 'september 23', 'kansas city chiefs', 'w 21 - 0', 'mile high stadium', '3 - 1', '74263'], ['5', 'september 30', 'los angeles raiders', 'w 16 - 13', 'mile high stadium', '4 - 1', '74833'], ['6', 'october 7', 'detroit lions', 'w 28 - 7', 'pontiac silverdome', '5 - 1', '55836'], ['7', 'october 15', 'green bay packers', 'w 17 - 14', 'mile high stadium', '6 - 1', '62546'], ['8', 'october 21', 'buffalo bills', 'w 37 - 7', 'rich stadium', '7 - 1', '31204'], ['9', 'october 28', 'los angeles raiders', 'w 22 - 19 ( ot )', 'los angeles memorial coliseum', '8 - 1', '91020'], ['10', 'november 4', 'new england patriots', 'w 26 - 19', 'mile high stadium', '9 - 1', '74908'], ['11', 'november 11', 'san diego chargers', 'w 16 - 13', 'jack murphy stadium', '10 - 1', '53162'], ['12', 'november 18', 'minnesota vikings', 'w 42 - 21', 'mile high stadium', '11 - 1', '74716'], ['13', 'november 25', 'seattle seahawks', 'l 24 - 27', 'mile high stadium', '11 - 2', '74922'], ['14', 'december 2', 'kansas city chiefs', 'l 13 - 16', 'arrowhead stadium', '11 - 3', '38494'], ['15', 'december 9', 'san diego chargers', 'w 16 - 13', 'mile high stadium', '12 - 3', '74867']] |
2007 - 08 russian volleyball super league | https://en.wikipedia.org/wiki/2007%E2%80%9308_Russian_Volleyball_Super_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14015965-1.html.csv | count | in the 2007 - 08 russian volleyball super league , among the arenas with capacity 5000 , 2 of them are home arenas for team that were ranked 5 or higher in the previous season . | {'scope': 'subset', 'criterion': 'less_than_eq', 'value': '5', 'result': '2', 'col': '1', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '5000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'arena ( capacity )', '5000'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; arena ( capacity ) ; 5000 }', 'tointer': 'select the rows whose arena ( capacity ) record fuzzily matches to 5000 .'}, 'previous season', '5'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose arena ( capacity ) record fuzzily matches to 5000 . among these rows , select the rows whose previous season record is less than or equal to 5 .', 'tostr': 'filter_less_eq { filter_eq { all_rows ; arena ( capacity ) ; 5000 } ; previous season ; 5 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_less_eq { filter_eq { all_rows ; arena ( capacity ) ; 5000 } ; previous season ; 5 } }', 'tointer': 'select the rows whose arena ( capacity ) record fuzzily matches to 5000 . among these rows , select the rows whose previous season record is less than or equal to 5 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less_eq { filter_eq { all_rows ; arena ( capacity ) ; 5000 } ; previous season ; 5 } } ; 2 } = true', 'tointer': 'select the rows whose arena ( capacity ) record fuzzily matches to 5000 . among these rows , select the rows whose previous season record is less than or equal to 5 . the number of such rows is 2 .'} | eq { count { filter_less_eq { filter_eq { all_rows ; arena ( capacity ) ; 5000 } ; previous season ; 5 } } ; 2 } = true | select the rows whose arena ( capacity ) record fuzzily matches to 5000 . among these rows , select the rows whose previous season record is less than or equal to 5 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'arena (capacity)_6': 6, '5000_7': 7, 'previous season_8': 8, '5_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_eq_1': 'filter_less_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'arena (capacity)_6': 'arena ( capacity )', '5000_7': '5000', 'previous season_8': 'previous season', '5_9': '5', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'arena (capacity)_6': [0], '5000_7': [0], 'previous season_8': [1], '5_9': [1], '2_10': [3]} | ['previous season', 'team', 'town', 'arena ( capacity )', 'website', 'head coach', 'foreign players ( max 2 )'] | [['1', 'dynamo - tattransgaz kazan', 'kazan', 'basket - hall arena ( 7 000 )', 'wwwdinamottgru', 'viktor sidelnikov', 'lloy ball clayton stanley'], ['2', 'dynamo moscow', 'moscow', 'dynamo sports palace ( 5 000 )', 'wwwvcdynamoru', 'daniele bagnoli', 'matej černič alan barbosa domingos'], ['3', 'iskra', 'odintsovo', 'volleyball sportiv complex ( 3 500 )', 'wwwvc - iskraru', 'zoran gajić', 'giba jochen schöps'], ['4', 'fakel', 'novy urengoy', 'csc gazodobytchik ( 800 )', 'wwwfakelvolleyru', 'boris kolchin', 'domotor meszaros thomas hoff'], ['5', 'lokomotiv - izumrud', 'ekaterinburg', 'divs uralochka ( 5 000 )', 'loko - izumrudurru', 'valeriy alferov', 'terence martin jason haldane'], ['6', 'dynamo - yantar', 'kaliningrad', 'sc yunost', 'wwwdinamoyantarru', 'yuriy panchenko', 'sean rooney tuomas sammelvuo'], ['7', 'gazprom - yugra', 'surgutsky district', 'sc tennis center', 'wwwzsk - gazpromru', 'rafael habibullin', 'sasa gadnik mahdi hachemi'], ['8', 'lokomotiv belogorie', 'belgorod', 'sports palace cosmos ( 5 000 )', 'wwwbelogorievolleyru', 'genadiy shipulin', 'frank depestel samuel fuchs'], ['9', 'ural', 'ufa', 'foc neftyanik bashkortostana', 'wwwvolleyufaru', 'yuriy marichev', 'loïc thiebaut de kegret renaud herpe'], ['10', 'lokomotiv', 'novosibirsk', 'skk sever ( 2 500 )', 'wwwlokovolleyru', 'pavel borsch', 'william priddy héctor soto'], ['promoted', 'yaroslavich', 'yaroslavl', 'sk atlant', 'wwwyarvolleyru', 'vladimir babakin', 'lukas chaves frederick winters']] |
football records in spain | https://en.wikipedia.org/wiki/Football_records_in_Spain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17937080-8.html.csv | aggregation | the average goals per match for football records in spain is 1.052 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '1.052', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'goals per match'], 'result': '1.052', 'ind': 0, 'tostr': 'avg { all_rows ; goals per match }'}, '1.052'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; goals per match } ; 1.052 } = true', 'tointer': 'the average of the goals per match record of all rows is 1.052 .'} | round_eq { avg { all_rows ; goals per match } ; 1.052 } = true | the average of the goals per match record of all rows is 1.052 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'goals per match_4': 4, '1.052_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'goals per match_4': 'goals per match', '1.052_5': '1.052'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'goals per match_4': [0], '1.052_5': [1]} | ['rank', 'name', 'season', 'club', 'goals', 'apps', 'goals per match'] | [['1', 'lionel messi', '2011 / 12', 'barcelona', '73', '60', '1.217'], ['2', 'lionel messi', '2012 / 13', 'barcelona', '60', '49', '1.224'], ['2', 'cristiano ronaldo', '2011 / 12', 'real madrid', '60', '55', '1.091'], ['4', 'cristiano ronaldo', '2012 / 13', 'real madrid', '55', '55', '1.000'], ['5', 'cristiano ronaldo', '2010 / 11', 'real madrid', '53', '54', '0.981'], ['5', 'lionel messi', '2010 / 11', 'barcelona', '53', '55', '0.964'], ['7', 'ferenc puskás', '1959 / 60', 'real madrid', '47', '38', '1.237'], ['7', 'ronaldo', '1996 / 97', 'barcelona', '47', '49', '0.964'], ['7', 'lionel messi', '2009 / 10', 'barcelona', '47', '53', '0.887'], ['10', 'telmo zarra', '1950 / 51', 'athletic bilbao', '46', '36', '1.278'], ['11', 'alfredo di stéfano', '1956 / 57', 'real madrid', '43', '43', '1.000'], ['12', 'mariano martín', '1942 / 43', 'barcelona', '42', '31', '1.355'], ['12', 'ferenc puskás', '1960 / 61', 'real madrid', '42', '39', '1.077'], ['12', 'hugo sánchez', '1989 / 90', 'real madrid', '42', '45', '0.933'], ['12', 'baltazar', '1988 / 89', 'atlético madrid', '42', '46', '0.913'], ['15', 'hugo sánchez', '1986 / 87', 'real madrid', '41', '54', '0.759'], ['16', 'ferenc puskás', '1961 / 62', 'real madrid', '40', '40', '1.000']] |
alien huang | https://en.wikipedia.org/wiki/Alien_Huang | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23379776-6.html.csv | unique | already famous was the only one of these movies to be released in 2011 . | {'scope': 'all', 'row': '6', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': '2011', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2011'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2011 .', 'tostr': 'filter_eq { all_rows ; year ; 2011 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; year ; 2011 } }', 'tointer': 'select the rows whose year record is equal to 2011 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2011'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2011 .', 'tostr': 'filter_eq { all_rows ; year ; 2011 }'}, 'title of movie'], 'result': 'already famous 《 一泡而紅 》', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 2011 } ; title of movie }'}, 'already famous 《 一泡而紅 》'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 2011 } ; title of movie } ; already famous 《 一泡而紅 》 }', 'tointer': 'the title of movie record of this unqiue row is already famous 《 一泡而紅 》 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; year ; 2011 } } ; eq { hop { filter_eq { all_rows ; year ; 2011 } ; title of movie } ; already famous 《 一泡而紅 》 } } = true', 'tointer': 'select the rows whose year record is equal to 2011 . there is only one such row in the table . the title of movie record of this unqiue row is already famous 《 一泡而紅 》 .'} | and { only { filter_eq { all_rows ; year ; 2011 } } ; eq { hop { filter_eq { all_rows ; year ; 2011 } ; title of movie } ; already famous 《 一泡而紅 》 } } = true | select the rows whose year record is equal to 2011 . there is only one such row in the table . the title of movie record of this unqiue row is already famous 《 一泡而紅 》 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '2011_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title of movie_9': 9, 'already famous 《一泡而紅》_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '2011_8': '2011', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title of movie_9': 'title of movie', 'already famous 《一泡而紅》_10': 'already famous 《 一泡而紅 》'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'year_7': [0], '2011_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title of movie_9': [2], 'already famous 《一泡而紅》_10': [3]} | ['year', 'title of movie', 'name of role', 'nature of role', 'co - artists', 'location'] | [['2002', 'wild 《 狂放 》', 'lin yi - jie 林益捷', 'male lead', 'junior han , josephine anan xu', 'taiwan'], ['2002', 'holiday dreaming 《 夢遊夏威夷 》', 'xiao gui 小鬼', 'second male lead', 'tony yang , janine chang', 'taiwan'], ['2006', 'a flight to yesterday 《 飛往昨天的ci006 》', 'li zheng - fei 李正非', 'male lead', 'yuchen zhang', 'taiwan'], ['2007', 'burn ! motorbike 《 燃燒吧 ！ 機車 》', 'hu di - ni 胡迪尼', 'male lead', 'megan lai', 'taiwan'], ['2009', 'black tide 《 黑潮 》', 'xiao gui 小鬼', 'male lead', 'shaoxiang li , jiaqing chu', 'taiwan'], ['2011', 'already famous 《 一泡而紅 》', 'christopher 阿盛', 'male lead', 'michelle chong', 'singapore']] |
sun sun | https://en.wikipedia.org/wiki/Sun_Sun | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15624634-2.html.csv | count | the album sun sun was released in cd format four times when the label was alfa records . | {'scope': 'subset', 'criterion': 'equal', 'value': 'cd', 'result': '4', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'alfa records'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'alfa records'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; label ; alfa records }', 'tointer': 'select the rows whose label record fuzzily matches to alfa records .'}, 'format', 'cd'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose label record fuzzily matches to alfa records . among these rows , select the rows whose format record fuzzily matches to cd .', 'tostr': 'filter_eq { filter_eq { all_rows ; label ; alfa records } ; format ; cd }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; label ; alfa records } ; format ; cd } }', 'tointer': 'select the rows whose label record fuzzily matches to alfa records . among these rows , select the rows whose format record fuzzily matches to cd . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; label ; alfa records } ; format ; cd } } ; 4 } = true', 'tointer': 'select the rows whose label record fuzzily matches to alfa records . among these rows , select the rows whose format record fuzzily matches to cd . the number of such rows is 4 .'} | eq { count { filter_eq { filter_eq { all_rows ; label ; alfa records } ; format ; cd } } ; 4 } = true | select the rows whose label record fuzzily matches to alfa records . among these rows , select the rows whose format record fuzzily matches to cd . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'label_6': 6, 'alfa records_7': 7, 'format_8': 8, 'cd_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'label_6': 'label', 'alfa records_7': 'alfa records', 'format_8': 'format', 'cd_9': 'cd', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'label_6': [0], 'alfa records_7': [0], 'format_8': [1], 'cd_9': [1], '4_10': [3]} | ['region', 'date', 'label', 'format', 'catalog'] | [['japan', 'september 10 , 1986', 'alfa records', 'stereo lp', 'alr - 28085'], ['japan', 'september 10 , 1986', 'alfa records', 'cd', '32xa - 90'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 285'], ['japan', 'august 31 , 1994', 'alfa records', 'cd', 'alca - 9015'], ['japan', 'august 29 , 1998', 'alfa records', 'cd', 'alca - 9210'], ['japan', 'february 20 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2215'], ['japan', 'march 13 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2235'], ['japan', 'may 27 , 2009', 'sony music direct', 'ed remaster cd', 'mhcl - 20017']] |
united states house of representatives elections , 1886 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1886 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431467-4.html.csv | count | 5 incumbents were re - elected during the 1886 house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; result ; re - elected }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re - elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re - elected } } ; 5 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 5 } = true | select the rows whose result record fuzzily matches to re - elected . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're - elected_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're - elected_6': 're - elected', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '5_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['south carolina 1', 'samuel dibble', 'democratic', '1882', 're - elected'], ['south carolina 2', 'george d tillman', 'democratic', '1878', 're - elected'], ['south carolina 3', 'd wyatt aiken', 'democratic', '1876', 'retired democratic hold'], ['south carolina 4', 'william h perry', 'democratic', '1884', 're - elected'], ['south carolina 5', 'john j hemphill', 'democratic', '1882', 're - elected'], ['south carolina 6', 'george w dargan', 'democratic', '1882', 're - elected'], ['south carolina 7', 'robert smalls', 'republican', '1884 ( special )', 'lost re - election democratic gain']] |
volleyball at the 2004 summer olympics - men 's team rosters | https://en.wikipedia.org/wiki/Volleyball_at_the_2004_Summer_Olympics_%E2%80%93_Men%27s_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15859432-12.html.csv | majority | the weight for most of the men 's volleyball team at the 2004 summer olympics is under 100 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '100', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'weight', '100'], 'result': True, 'ind': 0, 'tointer': 'for the weight records of all rows , most of them are less than 100 .', 'tostr': 'most_less { all_rows ; weight ; 100 } = true'} | most_less { all_rows ; weight ; 100 } = true | for the weight records of all rows , most of them are less than 100 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'weight_3': 3, '100_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'weight_3': 'weight', '100_4': '100'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'weight_3': [0], '100_4': [0]} | ['name', 'date of birth', 'height', 'weight', 'spike', 'block'] | [['lloy ball', '17.02.1972', '203', '95', '351', '316'], ['erik sullivan', '09.08.1972', '193', '86', '340', '320'], ['phillip eatherton', '02.01.1974', '206', '101', '356', '335'], ['donald suxho', '21.02.1976', '196', '98', '337', '319'], ['william priddy', '01.10.1977', '196', '89', '353', '330'], ['ryan millar', '22.01.1978', '204', '98', '354', '326'], ['riley salmon', '02.07.1976', '197', '89', '345', '331'], ['brook billings', '30.04.1980', '196', '95', '351', '331'], ['thomas hoff', '09.06.1973', '198', '94', '353', '333'], ['clayton stanley', '20.01.1978', '205', '104', '357', '332'], ['kevin barnett', '14.05.1974', '198', '94', '353', '340'], ['gabriel gardner', '18.03.1976', '209', '103', '353', '335']] |
united kingdom general election records | https://en.wikipedia.org/wiki/United_Kingdom_general_election_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10107334-3.html.csv | comparative | alfred dobbs was elected before thomas mitchell was elected . | {'row_1': '1', 'row_2': '5', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidate', 'alfred dobbs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidate record fuzzily matches to alfred dobbs .', 'tostr': 'filter_eq { all_rows ; candidate ; alfred dobbs }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; candidate ; alfred dobbs } ; year }', 'tointer': 'select the rows whose candidate record fuzzily matches to alfred dobbs . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidate', 'thomas mitchell'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose candidate record fuzzily matches to thomas mitchell .', 'tostr': 'filter_eq { all_rows ; candidate ; thomas mitchell }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; candidate ; thomas mitchell } ; year }', 'tointer': 'select the rows whose candidate record fuzzily matches to thomas mitchell . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; candidate ; alfred dobbs } ; year } ; hop { filter_eq { all_rows ; candidate ; thomas mitchell } ; year } } = true', 'tointer': 'select the rows whose candidate record fuzzily matches to alfred dobbs . take the year record of this row . select the rows whose candidate record fuzzily matches to thomas mitchell . take the year record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; candidate ; alfred dobbs } ; year } ; hop { filter_eq { all_rows ; candidate ; thomas mitchell } ; year } } = true | select the rows whose candidate record fuzzily matches to alfred dobbs . take the year record of this row . select the rows whose candidate record fuzzily matches to thomas mitchell . take the year record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'candidate_7': 7, 'alfred dobbs_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'candidate_11': 11, 'thomas mitchell_12': 12, 'year_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'candidate_7': 'candidate', 'alfred dobbs_8': 'alfred dobbs', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'candidate_11': 'candidate', 'thomas mitchell_12': 'thomas mitchell', 'year_13': 'year'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'candidate_7': [0], 'alfred dobbs_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'candidate_11': [1], 'thomas mitchell_12': [1], 'year_13': [3]} | ['candidate', 'party', 'constituency', 'year', 'days'] | [['alfred dobbs', 'labour', 'smethwick', '1945', '1 1'], ['john sunderland', 'labour', 'preston', '1945', '122 1'], ['john whittaker', 'labour', 'heywood and radcliffe', '1945', '137 1'], ['philip clarke', 'sinn féin', 'fermanagh and south tyrone', '1955', '152 3x'], ['thomas mitchell', 'sinn féin', 'mid - ulster', '1955', '152 3x'], ['harry west', 'ulster unionist', 'fermanagh and south tyrone', 'february 1974', '224 2'], ['michael ancram', 'conservative', 'berwick and east lothian', 'february 1974', '224 2a'], ['barry henderson', 'conservative', 'east dunbartonshire', 'february 1974', '224 2a'], ['paul tyler', 'liberal', 'bodmin', 'february 1974', '224 2a'], ['michael winstanley', 'liberal', 'hazel grove', 'february 1974', '224 2b'], ['james godfrey macmanaway', 'ulster unionist', 'belfast west', '1950', '238 3'], ['judith chaplin', 'conservative', 'newbury', '1992', '316 1'], ['peter law', 'independent', 'blaenau gwent', '2005', '355 1']] |
4th and long | https://en.wikipedia.org/wiki/4th_and_Long | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22603701-1.html.csv | aggregation | the average age for the people in 4th and long is 25.6 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '25.6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'age'], 'result': '25.6', 'ind': 0, 'tostr': 'avg { all_rows ; age }'}, '25.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; age } ; 25.6 } = true', 'tointer': 'the average of the age record of all rows is 25.6 .'} | round_eq { avg { all_rows ; age } ; 25.6 } = true | the average of the age record of all rows is 25.6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'age_4': 4, '25.6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'age_4': 'age', '25.6_5': '25.6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'age_4': [0], '25.6_5': [1]} | ['position', 'name', 'jersey number', 'age', 'height', 'weight', 'college', 'result'] | [['wr', 'jesse holley', '83', '25', "6 ' 3", '216', 'north carolina', 'winner in episode 10'], ['wr', 'andrew hawkins', '82', '22', "5 ' 7", '175', 'toledo', 'runners up in episode 10'], ['db', 'ahmaad smith', '25', '25', "6 ' 0", '196', 'tennessee state', 'runners up in episode 10'], ['db', 'eddie moten', '24', '27', "5 ' 10", '185', 'texas a & mkingsville', 'runners up in episode 10'], ['db', 'moses washington', '26', '28', "6 ' 0", '164', 'oklahoma', 'cut in episode 9'], ['wr', 'montrell jones', '84', '27', "6 ' 2", '205', 'tennessee / louisville', 'cut in episode 8'], ['db', 'donte gamble', '22', '30', "5 ' 8", '165', 'san diego state', 'cut in episode 7'], ['wr', 'steve gonzalez', '81', '24', "6 ' 2", '205', 'menlo college', 'cut in episode 5'], ['wr', 'luke swan', '86', '24', "6 ' 0", '193', 'wisconsin', 'cut in episode 4'], ['db', 'erick jackson', '23', '24', "6 ' 1", '195', 'texas', 'cut in episode 3'], ['wr', 'preston mcgann', '85', '25', "6 ' 3", '203', 'seminole community college', 'cut in episode 2']] |
jacksonville jaguars draft history | https://en.wikipedia.org/wiki/Jacksonville_Jaguars_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15100419-11.html.csv | ordinal | scott starks was the third player that the jacksonville jaguars drafted . | {'row': '3', 'col': '1', 'order': '3', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'round', '3'], 'result': '3', 'ind': 0, 'tostr': 'nth_min { all_rows ; round ; 3 }', 'tointer': 'the 3rd minimum round record of all rows is 3 .'}, '3'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; round ; 3 } ; 3 }', 'tointer': 'the 3rd minimum round record of all rows is 3 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'round', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; round ; 3 }'}, 'name'], 'result': 'scott starks', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; round ; 3 } ; name }'}, 'scott starks'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; round ; 3 } ; name } ; scott starks }', 'tointer': 'the name record of the row with 3rd minimum round record is scott starks .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; round ; 3 } ; 3 } ; eq { hop { nth_argmin { all_rows ; round ; 3 } ; name } ; scott starks } } = true', 'tointer': 'the 3rd minimum round record of all rows is 3 . the name record of the row with 3rd minimum round record is scott starks .'} | and { eq { nth_min { all_rows ; round ; 3 } ; 3 } ; eq { hop { nth_argmin { all_rows ; round ; 3 } ; name } ; scott starks } } = true | the 3rd minimum round record of all rows is 3 . the name record of the row with 3rd minimum round record is scott starks . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'round_8': 8, '3_9': 9, '3_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'round_12': 12, '3_13': 13, 'name_14': 14, 'scott starks_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'round_8': 'round', '3_9': '3', '3_10': '3', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'round_12': 'round', '3_13': '3', 'name_14': 'name', 'scott starks_15': 'scott starks'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'round_8': [0], '3_9': [0], '3_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'round_12': [2], '3_13': [2], 'name_14': [3], 'scott starks_15': [4]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '21', '21', 'matt jones', 'wide receiver', 'arkansas'], ['2', '20', '52', 'khalif barnes', 'offensive tackle', 'washington'], ['3', '23', '87', 'scott starks', 'cornerback', 'wisconsin'], ['4', '26', '127', 'alvin pearman', 'running back', 'virginia'], ['5', '21', '157', 'gerald sensabaugh', 'safety', 'north carolina'], ['6', '11', '185', 'chad owens', 'wide receiver', 'hawaii'], ['6', '20', '194', 'pat thomas', 'linebacker', 'north carolina state'], ['7', '23', '237', 'chris roberson', 'cornerback', 'eastern michigan']] |
pulp and paper industry | https://en.wikipedia.org/wiki/Pulp_and_paper_industry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-293465-1.html.csv | superlative | among the main countries that are in the pulp and paper industry , china produced the highest amount of material from raw wood in the year 2011 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'production in 2011 ( 1000 ton )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; production in 2011 ( 1000 ton ) }'}, 'country'], 'result': 'china', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; production in 2011 ( 1000 ton ) } ; country }'}, 'china'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; production in 2011 ( 1000 ton ) } ; country } ; china } = true', 'tointer': 'select the row whose production in 2011 ( 1000 ton ) record of all rows is maximum . the country record of this row is china .'} | eq { hop { argmax { all_rows ; production in 2011 ( 1000 ton ) } ; country } ; china } = true | select the row whose production in 2011 ( 1000 ton ) record of all rows is maximum . the country record of this row is china . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'production in 2011 (1000 ton)_5': 5, 'country_6': 6, 'china_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'production in 2011 (1000 ton)_5': 'production in 2011 ( 1000 ton )', 'country_6': 'country', 'china_7': 'china'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'production in 2011 (1000 ton)_5': [0], 'country_6': [1], 'china_7': [2]} | ['rank 2011', 'country', 'production in 2011 ( 1000 ton )', 'share 2011', 'rank 2010', 'production in 2010 ( 1000 ton )'] | [['1', 'china', '99300', '24.9 %', '1', '92599'], ['2', 'united states', '75083', '18.8 %', '2', '75849'], ['3', 'japan', '26627', '6.7 %', '3', '27288'], ['4', 'germany', '22698', '5.7 %', '4', '23122'], ['5', 'canada', '12112', '3.0 %', '5', '12787'], ['6', 'south korea', '11492', '2.9 %', '8', '11120'], ['7', 'finland', '11329', '2.8 %', '6', '11789'], ['8', 'sweden', '11298', '2.8 %', '7', '11410'], ['9', 'brazil', '10159', '2.5 %', '10', '9796'], ['10', 'indonesia', '10035', '2.5 %', '9', '9951']] |
indiana high school athletics conferences : mid - eastern - northwestern | https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Mid-Eastern_%E2%80%93_Northwestern | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18942405-13.html.csv | aggregation | the average enrollment of schools in the indiana high school atheltics conferences is 519 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '519', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '519', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '519'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 519 } = true', 'tointer': 'the average of the enrollment record of all rows is 519 .'} | round_eq { avg { all_rows ; enrollment } ; 519 } = true | the average of the enrollment record of all rows is 519 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '519_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '519_5': '519'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '519_5': [1]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'ihsaa football class', 'county'] | [['bremen', 'bremen', 'lions', '495', 'aa', 'aa', '50 marshall'], ['culver community', 'culver', 'cavaliers', '287', 'a', 'a', '50 marshall'], ['glenn', 'walkerton', 'falcons', '605', 'aaa', 'aaa', '71 st joseph'], ['jimtown', 'elkhart', 'jimmies', '601', 'aaa', 'aaa', '20 elkhart'], ['knox community', 'knox', 'redskins', '620', 'aaa', 'aaa', '75 starke'], ['laville', 'lakeville', 'lancers', '379', 'aa', 'a', '71 st joseph'], ['new prairie 1', 'new carlisle', 'cougars', '852', 'aaa', 'aaaa', '46 laporte 71 st joseph'], ['triton', 'bourbon', 'trojans', '316', 'a', 'a', '50 marshall']] |
french west african cup | https://en.wikipedia.org/wiki/French_West_African_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12444503-1.html.csv | superlative | in the french west african cup , 1947 was the first year when asc jeanne d'arc was a runner-up . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': "asc jeanne d'arc"}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner - up', "asc jeanne d'arc"], 'result': None, 'ind': 0, 'tostr': "filter_eq { all_rows ; runner - up ; asc jeanne d'arc }", 'tointer': "select the rows whose runner - up record fuzzily matches to asc jeanne d'arc ."}, 'season'], 'result': '1947', 'ind': 1, 'tostr': "min { filter_eq { all_rows ; runner - up ; asc jeanne d'arc } ; season }", 'tointer': "select the rows whose runner - up record fuzzily matches to asc jeanne d'arc . the minimum season record of these rows is 1947 ."}, '1947'], 'result': True, 'ind': 2, 'tostr': "eq { min { filter_eq { all_rows ; runner - up ; asc jeanne d'arc } ; season } ; 1947 } = true", 'tointer': "select the rows whose runner - up record fuzzily matches to asc jeanne d'arc . the minimum season record of these rows is 1947 ."} | eq { min { filter_eq { all_rows ; runner - up ; asc jeanne d'arc } ; season } ; 1947 } = true | select the rows whose runner - up record fuzzily matches to asc jeanne d'arc . the minimum season record of these rows is 1947 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'runner - up_5': 5, "asc jeanne d'arc_6": 6, 'season_7': 7, '1947_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'runner - up_5': 'runner - up', "asc jeanne d'arc_6": "asc jeanne d'arc", 'season_7': 'season', '1947_8': '1947'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'runner - up_5': [0], "asc jeanne d'arc_6": [0], 'season_7': [1], '1947_8': [2]} | ['season', 'winner', 'score', 'runner - up', 'lost to eventual winner', 'lost to eventual runner - up'] | [['1947', 'us gorée', '2 - 1', "asc jeanne d'arc", 'espoir saint - louis', 'espérance rufisque'], ['1948', 'foyer france sénégal', '4 - 0', "jeunesse club d'abidjan", 'saint - louisienne', 'racing club de conakry'], ['1949', 'racing club de dakar', '3 - 0', 'racing club de conakry', 'espoir saint - louis', 'usc bassam'], ['1949 / 50', 'racing club de conakry', '4 - 2', 'espoir saint - louis', 'usc bassam', "jeanne d'arc ( bamako )"], ['1950 / 51', "asc jeanne d'arc", '3 - 1', "jeanne d'arc ( bamako )", 'africa sports', 'us indigène'], ['1951 / 52', "asc jeanne d'arc", '2 - 0', 'etoile sportive porto novo', 'africa sports', 'foyer france sénégal'], ['1952 / 53', "jeanne d'arc ( bamako )", '3 - 1', 'racing club de conakry', 'us gorée', "jeunesse club d'abidjan"], ['1953 / 54', 'us gorée', '1 - 0', 'foyer du soudan', 'etoile sportive porto - novo', 'racing club de conakry'], ['1954 / 55', 'us gorée', '7 - 0', 'asec abidjan', 'as porto - novo', 'avenir saint - louis'], ['1955 / 56', "jeanne d'arc ( bamako )", '3 - 0', 'asec abidjan', 'foyer france sénégal', 'essor'], ['1956 / 57', 'réveil de saint - louis', '4 - 1', 'africa sports', 'etoile filante ( lomé )', "jeanne d'arc ( bamako )"], ['1957 / 58', 'africa sports', '5 - 0', 'asec abidjan', 'foyer france sénégal', 'société sportive de guinée'], ['1958 / 59', 'saint - louisienne', '2 - 1', 'modèle lomé', "stella d'abidjan", "asc jeanne d'arc"]] |
2007 - 08 utah jazz season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Utah_Jazz_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11964263-5.html.csv | count | all games of the utah jazz ' in the 2007 - 08 season were scheduled for the month of november . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'november', 'result': '16', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november .', 'tostr': 'filter_eq { all_rows ; date ; november }'}], 'result': '16', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; november } }', 'tointer': 'select the rows whose date record fuzzily matches to november . the number of such rows is 16 .'}, '16'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; november } } ; 16 } = true', 'tointer': 'select the rows whose date record fuzzily matches to november . the number of such rows is 16 .'} | eq { count { filter_eq { all_rows ; date ; november } } ; 16 } = true | select the rows whose date record fuzzily matches to november . the number of such rows is 16 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'november_6': 6, '16_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'november_6': 'november', '16_7': '16'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'november_6': [0], '16_7': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['november 1', 'rockets', 'l 95 - 106 ( ot )', 'jazz', 'boozer ( 30 )', '19911', '1 - 1'], ['november 3', 'warriors', 'w 133 - 110 ( ot )', 'jazz', 'williams ( 30 )', '19911', '2 - 1'], ['november 4', 'jazz', 'l 109 - 119 ( ot )', 'lakers', 'williams ( 26 )', '18997', '2 - 2'], ['november 7', 'cavaliers', 'w 103 - 101 ( ot )', 'jazz', 'millsap ( 24 )', '19911', '3 - 2'], ['november 9', 'jazz', 'w 103 - 101 ( ot )', 'supersonics', 'boozer ( 27 )', '15980', '4 - 2'], ['november 10', 'grizzlies', 'w 118 - 94 ( ot )', 'jazz', 'boozer ( 31 )', '19771', '5 - 2'], ['november 12', 'kings', 'w 117 - 93 ( ot )', 'jazz', 'boozer ( 32 )', '19911', '6 - 2'], ['november 14', 'jazz', 'w 92 - 88 ( ot )', 'raptors', 'boozer ( 23 )', '17337', '7 - 2'], ['november 16', 'jazz', 'l 94 - 99 ( ot )', 'cavaliers', 'boozer ( 26 )', '19862', '7 - 3'], ['november 17', 'jazz', 'l 97 - 117 ( ot )', 'pacers', 'boozer ( 19 )', '12447', '7 - 4'], ['november 19', 'nets', 'w 102 - 75 ( ot )', 'jazz', 'williams ( 20 )', '19911', '8 - 4'], ['november 23', 'hornets', 'w 99 - 71 ( ot )', 'jazz', 'boozer ( 19 )', '19911', '9 - 4'], ['november 25', 'jazz', 'w 103 - 93 ( ot )', 'pistons', 'boozer ( 36 )', '22076', '10 - 4'], ['november 26', 'jazz', 'l 109 - 113 ( ot )', 'knicks', 'boozer ( 30 )', '18816', '10 - 5'], ['november 28', 'jazz', 'w 106 - 95 ( ot )', '76ers', 'boozer ( 26 )', '11006', '11 - 5'], ['november 30', 'lakers', 'w 120 - 96 ( ot )', 'jazz', 'williams ( 35 )', '19911', '12 - 5']] |
list of solar car teams | https://en.wikipedia.org/wiki/List_of_solar_car_teams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1688640-4.html.csv | aggregation | 63 is the total number of cars in the list of solar car teams . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '63', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'number of cars'], 'result': '63', 'ind': 0, 'tostr': 'sum { all_rows ; number of cars }'}, '63'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; number of cars } ; 63 } = true', 'tointer': 'the sum of the number of cars record of all rows is 63 .'} | round_eq { sum { all_rows ; number of cars } ; 63 } = true | the sum of the number of cars record of all rows is 63 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'number of cars_4': 4, '63_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'number of cars_4': 'number of cars', '63_5': '63'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'number of cars_4': [0], '63_5': [1]} | ['year started', 'number of cars', 'current car', 'car', 'website'] | [['1998', '7', 'b - 7', '77', 'english'], ['1992', '7', 'ã ‰ clipse 7', '92', 'french english'], ['1998', '6', 'esteban vi', '55', 'french english'], ['1992', '3', 'isun', '66', 'french english'], ['1997', '4', 'phoenix ii', '116', 'english'], ['1990', '10', 'midnight sun x', '24', 'english'], ['2008', '1', 'arctic sun', 'none', 'english'], ['1988', '11', 'aurum', '100', 'english'], ['1991', '6', 'sunstang', '96', 'english'], ['2008', '1', 'raven', 'none', 'english'], ['2004', '4', 'schulich delta', '65', 'english'], ['1989', '2', 'ralos ii', '125', 'english'], ['1999', '1', 'xof1', '125', 'english french']] |
new zealand national football team | https://en.wikipedia.org/wiki/New_Zealand_national_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1023035-3.html.csv | aggregation | the average goals scored across all players on the new zealand national football team is about 15 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '15', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'goals'], 'result': '15', 'ind': 0, 'tostr': 'avg { all_rows ; goals }'}, '15'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; goals } ; 15 } = true', 'tointer': 'the average of the goals record of all rows is 15 .'} | round_eq { avg { all_rows ; goals } ; 15 } = true | the average of the goals record of all rows is 15 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'goals_4': 4, '15_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'goals_4': 'goals', '15_5': '15'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'goals_4': [0], '15_5': [1]} | ['name', 'career', 'goals', 'caps', 'first cap', 'most recent cap'] | [['vaughan coveny', '1992 - 2006', '28', '64', '7 june 1992', '4 june 2006'], ['shane smeltz', '2003 -', '23', '49', 'united states 9 june 2003', 'new caledonia 21 march 2013'], ['steve sumner', '1976 - 1988', '22', '58', 'burma 13 september 1976', '23 june 1988'], ['brian turner', '1967 - 1982', '21', '59', 'australia 5 november 1967', '23 june 1982'], ['jock newall', '1951 - 1952', '17', '10', 'new caledonia 19 september 1951', 'new caledonia 28 september 1952'], ['keith nelson', '1977 - 1983', '16', '20', 'new caledonia 5 march 1977', '7 june 1983'], ['chris killen', '2000 -', '16', '48', 'tahiti 19 june 2000', '5 september 2013'], ['grant turner', '1980 - 1988', '15', '42', '20 august 1980', '27 march 1988'], ['darren mcclennan', '1986 - 1997', '12', '43', '17 september 1986', '11 june 1997'], ['michael mcgarry', '1986 - 1997', '12', '54', '17 september 1986', 'australia 6 july 1997'], ['wynton rufer', '1980 - 1997', '12', '23', '16 october 1980', 'australia 28 june 1997'], ['steve wooddin', '1980 - 1984', '11', '24', '20 august 1980', '20 october 1984'], ['roy coxon', '1951 - 1952', '10', '8', 'new caledonia 19 september 1951', 'tahiti 28 september 1952'], ['chris jackson', '1995 - 2003', '10', '60', '21 february 1995', '22 june 2003'], ['dave taylor', '1967 - 1981', '10', '47', 'south vietnam 10 november 1967', '12 september 1981'], ['colin walker', '1984 - 1988', '10', '15', '18 october 1984', '23 june 1988'], ['chris wood', '2009 -', '10', '31', '3 june 2009', '5 september 2013']] |
1988 england rugby union tour of australia and fiji | https://en.wikipedia.org/wiki/1988_England_rugby_union_tour_of_Australia_and_Fiji | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058417-1.html.csv | superlative | the highest against was when the opposing team was australia . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'against'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; against }'}, 'opposing team'], 'result': 'australia', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; against } ; opposing team }'}, 'australia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; against } ; opposing team } ; australia } = true', 'tointer': 'select the row whose against record of all rows is maximum . the opposing team record of this row is australia .'} | eq { hop { argmax { all_rows ; against } ; opposing team } ; australia } = true | select the row whose against record of all rows is maximum . the opposing team record of this row is australia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'against_5': 5, 'opposing team_6': 6, 'australia_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'against_5': 'against', 'opposing team_6': 'opposing team', 'australia_7': 'australia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'against_5': [0], 'opposing team_6': [1], 'australia_7': [2]} | ['opposing team', 'against', 'date', 'venue', 'status'] | [['queensland country', '9', '17 may 1988', 'quarry hill rugby park , mackay', 'tour match'], ['queensland', '19', '22 may 1988', 'ballymore , brisbane', 'tour match'], ["queensland ' b '", '7', '25 may 1988', 'gold park , toowoomba', 'tour match'], ['australia', '22', '29 may 1988', 'ballymore , brisbane', 'first test'], ['south australia invitation xv', '10', '1 june 1988', 'hindmarsh stadium , adelaide', 'tour match'], ['new south wales', '23', '5 june 1988', 'waratah stadium , sydney', 'tour match'], ["new south wales ' b '", '9', '8 june 1988', 'brandon park , wollongong', 'tour match'], ['australia', '28', '12 june 1988', 'waratah stadium , sydney', 'second test'], ['fiji', '12', '16 june 1988', 'national stadium , suva', 'test match']] |
heartland collegiate athletic conference | https://en.wikipedia.org/wiki/Heartland_Collegiate_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-255205-1.html.csv | majority | in the heartland collegiate athletic conference , all of the institutions are private . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'private', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'type', 'private'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , all of them fuzzily match to private .', 'tostr': 'all_eq { all_rows ; type ; private } = true'} | all_eq { all_rows ; type ; private } = true | for the type records of all rows , all of them fuzzily match to private . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'private_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'private_4': 'private'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'private_4': [0]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined'] | [['anderson university', 'anderson , indiana', 'ravens', '1917', 'private / church of god', '3065', '1987'], ['bluffton university', 'bluffton , ohio', 'beavers', '1899', 'private / mennonite', '1191', '1998'], ['college of mount st joseph', 'cincinnati , ohio', 'lions', '1920', 'private / catholic', '2259', '1998'], ['defiance college', 'defiance , ohio', 'yellow jackets', '1850', 'private / united church of christ', '1000', '2000'], ['earlham college', 'richmond , indiana', 'quakers', '1847', 'private / quaker', '1194', '2010'], ['franklin college', 'franklin , indiana', 'grizzlies', '1834', 'private / baptist', '1000', '1987'], ['hanover college', 'hanover , indiana', 'panthers', '1827', 'private / presbyterian', '1062', '1987'], ['manchester university', 'north manchester , indiana', 'spartans', '1860', 'private / church of the brethren', '1250', '1987'], ['rose - hulman institute of technology', 'terre haute , indiana', "fightin ' engineers", '1874', 'private / non - sectarian', '1970', '1988 1']] |
vincenzo modica | https://en.wikipedia.org/wiki/Vincenzo_Modica | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14056562-1.html.csv | comparative | vincenzo modico 's time in 1998 was faster than the time in 1999 . | {'row_1': '3', 'row_2': '4', 'col': '6', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1998'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1998 .', 'tostr': 'filter_eq { all_rows ; year ; 1998 }'}, 'notes'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1998 } ; notes }', 'tointer': 'select the rows whose year record fuzzily matches to 1998 . take the notes record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1999'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1999 .', 'tostr': 'filter_eq { all_rows ; year ; 1999 }'}, 'notes'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1999 } ; notes }', 'tointer': 'select the rows whose year record fuzzily matches to 1999 . take the notes record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; year ; 1998 } ; notes } ; hop { filter_eq { all_rows ; year ; 1999 } ; notes } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1998 . take the notes record of this row . select the rows whose year record fuzzily matches to 1999 . take the notes record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; year ; 1998 } ; notes } ; hop { filter_eq { all_rows ; year ; 1999 } ; notes } } = true | select the rows whose year record fuzzily matches to 1998 . take the notes record of this row . select the rows whose year record fuzzily matches to 1999 . take the notes record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '1998_8': 8, 'notes_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1999_12': 12, 'notes_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '1998_8': '1998', 'notes_9': 'notes', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1999_12': '1999', 'notes_13': 'notes'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1998_8': [0], 'notes_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1999_12': [1], 'notes_13': [3]} | ['year', 'competition', 'venue', 'position', 'event', 'notes'] | [['1994', 'european championships', 'helsinki , finland', '11th', '10000 m', '28:17.24'], ['1997', 'world championships', 'athens , greece', '-', 'marathon', 'dnf'], ['1998', 'european championships', 'budapest , hungary', '3rd', 'marathon', '2:12:53'], ['1999', 'world championships', 'seville , spain', '2nd', 'marathon', '2:14:03'], ['2000', 'olympic games', 'sydney , australia', '-', 'marathon', 'dnf']] |
phil parsons | https://en.wikipedia.org/wiki/Phil_Parsons | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2597876-1.html.csv | count | phil parsons had a total of one win from 1983 to 1995 in over 100 starts . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '1', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; wins ; 1 }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; wins ; 1 } }', 'tointer': 'select the rows whose wins record is equal to 1 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; wins ; 1 } } ; 1 } = true', 'tointer': 'select the rows whose wins record is equal to 1 . the number of such rows is 1 .'} | eq { count { filter_eq { all_rows ; wins ; 1 } } ; 1 } = true | select the rows whose wins record is equal to 1 . the number of such rows is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'wins_5': 5, '1_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'wins_5': 'wins', '1_6': '1', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'wins_5': [0], '1_6': [0], '1_7': [2]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1983', '5', '0', '0', '0', '0', '15.4', '23.8', '23850', '43rd', '66 johnny hayes racing'], ['1984', '23', '0', '0', '3', '0', '21.0', '19.3', '90700', '24th', '66 johnny hayes racing'], ['1985', '28', '0', '0', '4', '0', '20.5', '21.9', '104840', '21st', '66 jackson bros motorsports 17 hamby racing'], ['1986', '17', '0', '1', '5', '0', '18.6', '20.5', '84680', '27th', '66 jackson bros motorsports 17 hamby racing'], ['1987', '29', '0', '1', '7', '0', '19.4', '16.5', '180261', '14th', '55 jackson bros motorsports'], ['1988', '29', '1', '6', '15', '0', '17.0', '14.3', '532043', '9th', '55 jackson bros motorsports'], ['1989', '29', '0', '2', '3', '0', '22.4', '21.1', '285012', '21st', '55 jackson bros motorsports 60 combs racing'], ['1992', '2', '0', '0', '1', '0', '26.0', '20.0', '58475', '53rd', '9 melling racing'], ['1994', '3', '0', '0', '0', '0', '32.3', '27.3', '21415', '50th', '9 melling racing'], ['1995', '2', '0', '0', '0', '0', '35.0', '41.5', '41450', '60th', '19 tristar motorsports']] |
thiago alves ( tennis ) | https://en.wikipedia.org/wiki/Thiago_Alves_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14924949-3.html.csv | majority | most of the games thiago alves played in the singles were on a hard surface . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['date', 'tournament', 'surface', 'opponent', 'score'] | [['august 15 , 2005', 'manta , ecuador', 'hard', 'lesley joseph', '6 - 4 , 6 - 1'], ['october 10 , 2005', 'quito , ecuador', 'clay', 'marcos daniel', '1 - 6 , 7 - 6 ( 7 - 1 ) , 6 - 2'], ['july 31 , 2006', 'belo horizonte , brazil', 'hard', 'andré sá', '6 - 3 , 0 - 6 , 6 - 4'], ['august 14 , 2006', 'manta , ecuador', 'hard', 'brian dabul', '6 - 2 , 6 - 2'], ['december 31 , 2007', 'são paulo , brazil', 'hard', 'carlos berlocq', '6 - 4 , 3 - 6 , 7 - 5'], ['january 8 , 2012', 'são paulo , brazil', 'hard', 'gastão elias', '7 - 6 ( 7 - 5 ) , 7 - 6 ( 7 - 1 )'], ['march 18 , 2012', 'guadalajara , mexico', 'hard', 'paolo lorenzi', '6 - 3 , 7 - 6 ( 6 - 4 )']] |
2007 - 08 dallas stars season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Dallas_Stars_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11801912-4.html.csv | comparative | the dallas stars had a game against the los angeles visitor earlier than toronto . | {'row_1': '8', 'row_2': '10', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'los angeles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose visitor record fuzzily matches to los angeles .', 'tostr': 'filter_eq { all_rows ; visitor ; los angeles }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; visitor ; los angeles } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to los angeles . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'toronto'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose visitor record fuzzily matches to toronto .', 'tostr': 'filter_eq { all_rows ; visitor ; toronto }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; visitor ; toronto } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to toronto . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; visitor ; los angeles } ; date } ; hop { filter_eq { all_rows ; visitor ; toronto } ; date } } = true', 'tointer': 'select the rows whose visitor record fuzzily matches to los angeles . take the date record of this row . select the rows whose visitor record fuzzily matches to toronto . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; visitor ; los angeles } ; date } ; hop { filter_eq { all_rows ; visitor ; toronto } ; date } } = true | select the rows whose visitor record fuzzily matches to los angeles . take the date record of this row . select the rows whose visitor record fuzzily matches to toronto . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'visitor_7': 7, 'los angeles_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'visitor_11': 11, 'toronto_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'visitor_7': 'visitor', 'los angeles_8': 'los angeles', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'visitor_11': 'visitor', 'toronto_12': 'toronto', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'visitor_7': [0], 'los angeles_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'visitor_11': [1], 'toronto_12': [1], 'date_13': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 2', 'phoenix', '5 - 0', 'dallas', 'smith', '18203', '5 - 6 - 2'], ['november 5', 'dallas', '5 - 0', 'anaheim', 'turco', '17174', '6 - 6 - 2'], ['november 7', 'dallas', '3 - 1', 'san jose', 'turco', '17496', '7 - 6 - 2'], ['november 8', 'dallas', '2 - 5', 'phoenix', 'turco', '12027', '7 - 7 - 2'], ['november 10', 'dallas', '5 - 6', 'los angeles', 'turco', '18118', '7 - 7 - 3'], ['november 14', 'san jose', '4 - 3', 'dallas', 'turco', '17682', '7 - 7 - 4'], ['november 16', 'colorado', '1 - 6', 'dallas', 'smith', '18019', '8 - 7 - 4'], ['november 19', 'los angeles', '0 - 3', 'dallas', 'smith', '17208', '9 - 7 - 4'], ['november 21', 'anaheim', '1 - 2', 'dallas', 'smith', '18584', '10 - 7 - 4'], ['november 23', 'toronto', '1 - 3', 'dallas', 'turco', '18409', '11 - 7 - 4'], ['november 25', 'dallas', '3 - 2', 'ny rangers', 'smith', '18200', '12 - 7 - 4'], ['november 26', 'dallas', '3 - 2', 'ny islanders', 'turco', '8161', '13 - 7 - 4'], ['november 28', 'dallas', '2 - 4', 'new jersey', 'turco', '13665', '13 - 8 - 4'], ['november 30', 'dallas', '1 - 4', 'pittsburgh', 'smith', '17132', '13 - 9 - 4']] |
list of game of the year awards | https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-24.html.csv | majority | the system with the games that won the gamestop game of the year award the highest number of times was the playstation 3 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'playstation 3', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'platform ( s )', 'playstation 3'], 'result': True, 'ind': 0, 'tointer': 'for the platform ( s ) records of all rows , most of them fuzzily match to playstation 3 .', 'tostr': 'most_eq { all_rows ; platform ( s ) ; playstation 3 } = true'} | most_eq { all_rows ; platform ( s ) ; playstation 3 } = true | for the platform ( s ) records of all rows , most of them fuzzily match to playstation 3 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'platform (s)_3': 3, 'playstation 3_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'platform (s)_3': 'platform ( s )', 'playstation 3_4': 'playstation 3'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'platform (s)_3': [0], 'playstation 3_4': [0]} | ['year', 'game', 'genre', 'platform ( s )', 'developer ( s )'] | [['2002', 'metroid prime', '( first - person ) action - adventure', 'gamecube', 'retro studios , nintendo'], ['2003', 'the legend of zelda : the wind waker', 'action - adventure', 'gamecube', 'nintendo'], ['2004', 'world of warcraft', 'mmorpg', 'windows , mac os x', 'blizzard'], ['2005', 'resident evil 4', 'survival horror : ( third - person ) shooter', 'gamecube , playstation 2 , wii , windows', 'capcom'], ['2006', 'gears of war', 'tactical shooter', 'xbox 360 , windows', 'epic games'], ['2007', 'super mario galaxy', 'platformer', 'wii', 'nintendo'], ['2008', 'metal gear solid 4 : guns of the patriots', 'stealth action', 'playstation 3', 'kojima productions'], ['2009', "demon 's souls", 'action rpg : hack & slash', 'playstation 3', 'from software'], ['2010', 'red dead redemption', 'open world : ( third - person ) shooter', 'playstation 3 , xbox 360', 'rockstar games'], ['2011', 'the elder scrolls v : skyrim', 'role - playing game', 'windows , playstation 3 , xbox 360', 'bethesda game studios'], ['2012', 'journey', 'adventure', 'playstation 3', 'thatgamecompany']] |
phoenix suns all - time roster | https://en.wikipedia.org/wiki/Phoenix_Suns_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482079-8.html.csv | count | two of the players had a total of 0 assists . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'asts', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose asts record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; asts ; 0 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; asts ; 0 } }', 'tointer': 'select the rows whose asts record is equal to 0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; asts ; 0 } } ; 2 } = true', 'tointer': 'select the rows whose asts record is equal to 0 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; asts ; 0 } } ; 2 } = true | select the rows whose asts record is equal to 0 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'asts_5': 5, '0_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'asts_5': 'asts', '0_6': '0', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'asts_5': [0], '0_6': [0], '2_7': [2]} | ['player', 'pos', 'from', 'school / country', 'rebs', 'asts'] | [['rubén garcés', 'pf', '2000', 'providence', '22', '4'], ['diante garrett', 'g', '2012', 'iowa state', '15', '31'], ['pat garrity', 'pf', '1998', 'notre dame', '75', '18'], ['kenny gattison', 'pf', '1986', 'old dominion', '271', '36'], ['armen gilliam', 'pf', '1987', 'unlv', '1045', '132'], ['gordan giriček', 'g / f', '2008', 'croatia', '51', '35'], ['georgi glouchkov', 'pf', '1985', 'bulgaria', '163', '32'], ['grant gondrezick', 'sg', '1986', 'pepperdine', '110', '81'], ['gail goodrich', 'pg', '1968', 'ucla', '777', '1123'], ['archie goodwin', 'g', '2013', 'kentucky', '1', '0'], ['marcin gortat', 'c', '2010', 'poland', '1688', '237'], ['brian grant', 'f / c', '2005', 'xavier', '57', '7'], ['greg grant', 'pg', '1989', 'trenton state', '59', '168'], ['a c green', 'f / c', '1993', 'oregon state', '2114', '353'], ['gerald green', 'g / f', '2013', 'gulf shores academy ( tx )', '2', '0'], ['lamar green', 'pf', '1969', 'morehead state', '2186', '247'], ['gary gregor', 'pf', '1968', 'south carolina', '711', '96'], ['greg griffin', 'f', '1977', 'idaho state', '103', '24'], ['taylor griffin', 'f', '2009', 'oklahoma', '2', '1'], ['tom gugliotta', 'pf', '1999', 'north carolina state', '1438', '353']] |
elena reid | https://en.wikipedia.org/wiki/Elena_Reid | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1433370-2.html.csv | count | elena reid recorded a win of 4 matches against other opponents . | {'scope': 'all', 'criterion': 'equal', 'value': 'win', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'res', 'win'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose res record fuzzily matches to win .', 'tostr': 'filter_eq { all_rows ; res ; win }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; res ; win } }', 'tointer': 'select the rows whose res record fuzzily matches to win . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; res ; win } } ; 4 } = true', 'tointer': 'select the rows whose res record fuzzily matches to win . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; res ; win } } ; 4 } = true | select the rows whose res record fuzzily matches to win . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'res_5': 5, 'win_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'res_5': 'res', 'win_6': 'win', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'res_5': [0], 'win_6': [0], '4_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '4 - 1', 'catia vitoria', 'tko ( punches )', 'playboy fight night 4', '3', '3:59', 'new town , north dakota , united states'], ['win', '4 - 0', 'masako yoshida', 'tko ( punches )', 'eb - beatdown at 4 bears 5', '3', '2:35', 'new town , north dakota , united states'], ['win', '3 - 0', 'michelle waterson', 'tko ( punches )', 'apache gold : extreme beatdown', '2', '1:50', 'phoenix , arizona , united states'], ['win', '2 - 0', 'stephanie palmer', 'tko ( liver punch )', 'superfights mma - night of combat 2', '1', '0:53', 'las vegas , nevada , united states'], ['win', '1 - 0', 'tammie schneider', 'tko ( punches )', 'ifo - fireworks in the cage iv', '2', '2:05', 'las vegas , nevada , united states']] |
1988 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1988_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17231125-6.html.csv | comparative | larry mize came in three places behind scott simpson . | {'row_1': '4', 'row_2': '5', 'col': '1', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '3', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'scott simpson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to scott simpson .', 'tostr': 'filter_eq { all_rows ; player ; scott simpson }'}, 'place'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; scott simpson } ; place }', 'tointer': 'select the rows whose player record fuzzily matches to scott simpson . take the place record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'larry mize'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to larry mize .', 'tostr': 'filter_eq { all_rows ; player ; larry mize }'}, 'place'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; larry mize } ; place }', 'tointer': 'select the rows whose player record fuzzily matches to larry mize . take the place record of this row .'}], 'result': '-3', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; scott simpson } ; place } ; hop { filter_eq { all_rows ; player ; larry mize } ; place } }'}, '-3'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; scott simpson } ; place } ; hop { filter_eq { all_rows ; player ; larry mize } ; place } } ; -3 } = true', 'tointer': 'select the rows whose player record fuzzily matches to scott simpson . take the place record of this row . select the rows whose player record fuzzily matches to larry mize . take the place record of this row . the second record is 3 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; player ; scott simpson } ; place } ; hop { filter_eq { all_rows ; player ; larry mize } ; place } } ; -3 } = true | select the rows whose player record fuzzily matches to scott simpson . take the place record of this row . select the rows whose player record fuzzily matches to larry mize . take the place record of this row . the second record is 3 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'scott simpson_9': 9, 'place_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'larry mize_13': 13, 'place_14': 14, '-3_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'scott simpson_9': 'scott simpson', 'place_10': 'place', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'larry mize_13': 'larry mize', 'place_14': 'place', '-3_15': '-3'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'scott simpson_9': [0], 'place_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'larry mize_13': [1], 'place_14': [3], '-3_15': [5]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'curtis strange', 'united states', '70 + 67 + 69 = 206', '- 7'], ['t2', 'nick faldo', 'england', '72 + 67 + 68 = 207', '- 6'], ['t2', 'bob gilder', 'united states', '68 + 69 + 70 = 207', '- 6'], ['t2', 'scott simpson', 'united states', '69 + 66 + 72 = 207', '- 6'], ['t5', 'larry mize', 'united states', '69 + 67 + 72 = 208', '- 5'], ['t5', 'd a weibring', 'united states', '71 + 69 + 68 = 208', '- 5'], ['7', "mark o'meara", 'united states', '71 + 72 + 66 = 209', '- 4'], ['8', 'fred couples', 'united states', '72 + 67 + 71 = 210', '- 3'], ['9', 'lanny wadkins', 'united states', '70 + 71 + 70 = 211', '- 2'], ['10', 'ken green', 'united states', '72 + 70 + 70 = 212', '- 1']] |
washington redskins draft history | https://en.wikipedia.org/wiki/Washington_Redskins_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-11.html.csv | majority | most of the players were the sixth pick in their round . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '6', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'pick', '6'], 'result': True, 'ind': 0, 'tointer': 'for the pick records of all rows , most of them are equal to 6 .', 'tostr': 'most_eq { all_rows ; pick ; 6 } = true'} | most_eq { all_rows ; pick ; 6 } = true | for the pick records of all rows , most of them are equal to 6 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'pick_3': 3, '6_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'pick_3': 'pick', '6_4': '6'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'pick_3': [0], '6_4': [0]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '6', '6', 'spec sanders', 'hb', 'texas'], ['3', '6', '21', 'rufus deal', 'rb', 'auburn'], ['5', '6', '36', 'joe zeno', 'g', 'holy cross'], ['6', '6', '46', 'harley mccollum', 'ot', 'tulane'], ['7', '6', '56', 'bob fitch', 'e', 'minnesota'], ['8', '6', '66', 'george peters', 'rb', 'oregon state'], ['9', '6', '76', 'frank swiger', 'rb', 'duke'], ['10', '6', '86', 'john goodyear', 'rb', 'marquette'], ['11', '6', '96', 'al demao', 'c', 'duquesne'], ['12', '6', '106', 'phil ahwesh', 'rb', 'duquesne'], ['13', '6', '116', 'john kovatch', 'e', 'notre dame'], ['14', '6', '126', 'bill decorrevont', 'rb', 'northwestern'], ['15', '6', '136', 'marvin whited', 'g', 'oklahoma'], ['16', '6', '146', 'dee chipman', 'rb', 'brigham young'], ['17', '6', '156', 'george watts', 'ot', 'appalachian state'], ['18', '6', '166', 'gene stewart', 'rb', 'willamette'], ['19', '6', '176', 'charlie timmons', 'fb', 'clemson'], ['20', '6', '186', 'tiny croft', 'ot', 'ripon'], ['21', '1', '191', 'steve juzwik', 'hb', 'notre dame'], ['22', '1', '196', 'al couppee', 'g', 'iowa']] |
bh11960 | https://en.wikipedia.org/wiki/BH11960 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27155678-2.html.csv | aggregation | the genus/species have an combined average sequence similarity with bh11960 of 70 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '70', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'sequence similarity'], 'result': '70', 'ind': 0, 'tostr': 'avg { all_rows ; sequence similarity }'}, '70'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; sequence similarity } ; 70 } = true', 'tointer': 'the average of the sequence similarity record of all rows is 70 .'} | round_eq { avg { all_rows ; sequence similarity } ; 70 } = true | the average of the sequence similarity record of all rows is 70 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'sequence similarity_4': 4, '70_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'sequence similarity_4': 'sequence similarity', '70_5': '70'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'sequence similarity_4': [0], '70_5': [1]} | ['genus / species', 'gene name', 'accession number', 'sequence length', 'sequence similarity'] | [['bartonella henselae', 'hypothetical protein', 'bx897699 .1', '2805nt / 934aa', '100'], ['bartonella quintana', 'hypothetical protein', 'bx897700 .1', '2805nt / 934aa', '91'], ['bartonella grahamii', 'transcription regulator', 'cp001562 .1', '2799nt / 932aa', '87'], ['bartonella tribocorum', 'alanyl - trna synthetase', 'am260525 .1', '2799nt / 932aa', '87'], ['methylobacterium nodulans', 'hypothetical protein', 'yp_002500318 .1', '2820nt / 939aa', '53'], ['nitrobacter hamburgensis', 'double transmembrane region like', 'yp_578448 .1', '2817nt / 938aa', '53'], ['hyphomicrobium denitrificans', 'conserved hypothetical protein', 'zp_05374729 .1', '2973nt / 990aa', '53'], ['rhodopseudomonas palustris', 'double transmembrane region like', 'yp_568432 .1', '2826nt / 941aa', '54'], ['hoeflea phototrophica', 'double transmembrane region like', 'yp_002289983 .1', '1832nt / 943aa', '55']] |
united states house of representatives elections , 1930 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1930 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342359-41.html.csv | majority | most of the candidates were elected to the house of representatives in the 1920s . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1920', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'first elected', '1920'], 'result': True, 'ind': 0, 'tointer': 'for the first elected records of all rows , most of them are greater than 1920 .', 'tostr': 'most_greater { all_rows ; first elected ; 1920 } = true'} | most_greater { all_rows ; first elected ; 1920 } = true | for the first elected records of all rows , most of them are greater than 1920 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'first elected_3': 3, '1920_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'first elected_3': 'first elected', '1920_4': '1920'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'first elected_3': [0], '1920_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['tennessee 3', 'sam d mcreynolds', 'democratic', '1922', 're - elected', 'sam d mcreynolds ( d ) unopposed'], ['tennessee 4', 'cordell hull', 'democratic', '1922', 'retired to run for u s senate democratic hold', 'john ridley mitchell ( d ) unopposed'], ['tennessee 5', 'ewin l davis', 'democratic', '1918', 're - elected', 'ewin l davis ( d ) 92.0 % george motlow ( r ) 8.0 %'], ['tennessee 7', 'edward everett eslick', 'democratic', '1924', 're - elected', 'edward everett eslick ( d ) unopposed'], ['tennessee 8', 'gordon browning', 'democratic', '1922', 're - elected', 'gordon browning ( d ) unopposed']] |
list of palatine locomotives and railbuses | https://en.wikipedia.org/wiki/List_of_Palatine_locomotives_and_railbuses | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18843924-5.html.csv | superlative | the largest number of palatine loctomotives and railbuses are class l 1 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'quantity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; quantity }'}, 'class'], 'result': 'l 1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; quantity } ; class }'}, 'l 1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; quantity } ; class } ; l 1 } = true', 'tointer': 'select the row whose quantity record of all rows is maximum . the class record of this row is l 1 .'} | eq { hop { argmax { all_rows ; quantity } ; class } ; l 1 } = true | select the row whose quantity record of all rows is maximum . the class record of this row is l 1 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'quantity_5': 5, 'class_6': 6, 'l 1_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'quantity_5': 'quantity', 'class_6': 'class', 'l 1_7': 'l 1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'quantity_5': [0], 'class_6': [1], 'l 1_7': [2]} | ['class', 'railway number ( s )', 'drg number ( s )', 'quantity', 'year ( s ) of manufacture', 'axle arrangement ( uic ) bauart'] | [['l 1', 'xi - xxii , xxviii', '99 081 - 99 092', '13', '1889 - 1907', 'c n2t'], ['l 2', 'xxiii - xxvii', '99 001 - 99 005', '5', '1903 - 1905', 'b n2t'], ['pts 2 / 2', 'xxx', '99 011', '1', '1910', 'b h2t'], ['pts 3 / 3 n', 'xxix', '99 093', '1', '1911', 'c n2t'], ['pts 3 / 3 h', 'xxxi - xxxiii', '99 101 - 99 103', '3', '1923', 'c h2t']] |
baltimore city delegation | https://en.wikipedia.org/wiki/Baltimore_City_Delegation | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11873520-1.html.csv | ordinal | brian k mchale is the fourth earliest baltimore city delegate to take office . | {'row': '18', 'col': '5', 'order': '4', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'took office', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; took office ; 4 }'}, 'delegate'], 'result': 'brian k mchale', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; took office ; 4 } ; delegate }'}, 'brian k mchale'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; took office ; 4 } ; delegate } ; brian k mchale } = true', 'tointer': 'select the row whose took office record of all rows is 4th minimum . the delegate record of this row is brian k mchale .'} | eq { hop { nth_argmin { all_rows ; took office ; 4 } ; delegate } ; brian k mchale } = true | select the row whose took office record of all rows is 4th minimum . the delegate record of this row is brian k mchale . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'took office_5': 5, '4_6': 6, 'delegate_7': 7, 'brian k mchale_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'took office_5': 'took office', '4_6': '4', 'delegate_7': 'delegate', 'brian k mchale_8': 'brian k mchale'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'took office_5': [0], '4_6': [0], 'delegate_7': [1], 'brian k mchale_8': [2]} | ['district', 'place of birth', 'delegate', 'party', 'took office', 'committee'] | [['40', 'baltimore city', 'frank conaway', 'democratic', '2006', 'judiciary'], ['40', 'alexandria city , alabama', 'barbara robinson', 'democratic', '2006', 'appropriations'], ['40', 'freeport , ny', 'shawn z tarrant', 'democratic', '2006', 'health and government operations'], ['41', 'baltimore city', 'jill p carter', 'democratic', '2002', 'judiciary'], ['41', 'baltimore city', 'nathaniel t oaks', 'democratic', '1982', 'health and government operations'], ['41', 'baltimore city', 'sandy rosenberg', 'democratic', '1982', 'ways and means ( vice - chair )'], ['43', 'chicago , illinois', 'curt anderson , chair', 'democratic', '1982', 'judiciary'], ['43', 'philadelphia , pennsylvania', 'mary l washington', 'democratic', '2011', 'appropriations'], ['43', 'quinter , kansas', 'maggie mcintosh', 'democratic', '1992', 'environmental matters ( chair )'], ['44', 'shelby , north carolina', 'keith e haynes', 'democratic', '2002', 'appropriations'], ['44', 'baltimore city', 'keiffer mitchell', 'democratic', '2011', 'judiciary'], ['44', 'baltimore city', 'melvin l stukes', 'democratic', '2006', 'ways and means'], ['45', 'northampton co , north carolina', 'talmadge branch', 'democratic', '1994', 'appropriations'], ['45', 'baltimore city', 'cheryl glenn', 'democratic', '2006', 'environmental matters'], ['45', 'baltimore city', 'nina r harper', 'democratic', '2013', 'ways and means'], ['46', 'baltimore city', 'peter a hammen', 'democratic', '1994', 'health and government operations ( chair )'], ['46', 'baltimore city', 'luke clippinger', 'democratic', '2011', 'judiciary'], ['46', 'baltimore city', 'brian k mchale', 'democratic', '1990', 'economic matters']] |
anthony kim | https://en.wikipedia.org/wiki/Anthony_Kim | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11106562-3.html.csv | majority | of the tournaments that anthony kim participated in , he always had 0 wins . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'wins', '0'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , all of them are equal to 0 .', 'tostr': 'all_eq { all_rows ; wins ; 0 } = true'} | all_eq { all_rows ; wins ; 0 } = true | for the wins records of all rows , all of them are equal to 0 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '0_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '0_4': '0'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '0_4': [0]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '1', '2', '3', '2'], ['us open', '0', '0', '0', '2', '4', '4'], ['the open championship', '0', '1', '2', '2', '3', '2'], ['pga championship', '0', '0', '0', '0', '5', '3'], ['totals', '0', '2', '3', '6', '15', '11']] |
atlantic coast collegiate hockey league | https://en.wikipedia.org/wiki/Atlantic_Coast_Collegiate_Hockey_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16403890-1.html.csv | ordinal | among the members of the atlantic coast collegiate hockey league , george washington university is the third oldest member institution . | {'row': '4', 'col': '3', 'order': '3', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'founded', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; founded ; 3 }'}, 'institution'], 'result': 'george washington university', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; founded ; 3 } ; institution }'}, 'george washington university'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; founded ; 3 } ; institution } ; george washington university } = true', 'tointer': 'select the row whose founded record of all rows is 3rd minimum . the institution record of this row is george washington university .'} | eq { hop { nth_argmin { all_rows ; founded ; 3 } ; institution } ; george washington university } = true | select the row whose founded record of all rows is 3rd minimum . the institution record of this row is george washington university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'founded_5': 5, '3_6': 6, 'institution_7': 7, 'george washington university_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'founded_5': 'founded', '3_6': '3', 'institution_7': 'institution', 'george washington university_8': 'george washington university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'founded_5': [0], '3_6': [0], 'institution_7': [1], 'george washington university_8': [2]} | ['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname', 'primary conference', 'home rink'] | [['duke university', 'durham , nc', '1838', 'private / non - sectarian', '6496', 'blue devils', 'atlantic coast conference ( d - i )', 'triangle sports plex'], ['elon university', 'elon , nc', '1889', 'private', '5225', 'phoenix', 'southern conference ( d - i )', 'triangle sports plex / greensboro ice house'], ['georgetown university', 'washington , dc', '1789', 'private / catholic', '13612', 'hoyas', 'big east conference ( d - i )', 'kettler capitals iceplex'], ['george washington university', 'washington , dc', '1821', 'private', '6655', 'colonials', 'atlantic 10 conference ( d - i )', 'fort dupont ice arena / kettler capitals iceplex'], ['university of north carolina', 'chapel hill , nc', '1789', 'public', '17895', 'tar heels', 'atlantic coast conference ( d - i )', 'triangle sports plex'], ['north carolina state university', 'raleigh , nc', '1887', 'public', '24741', 'wolfpack', 'atlantic coast conference ( d - i )', 'raleigh center ice']] |
2008 - 09 san antonio spurs season | https://en.wikipedia.org/wiki/2008%E2%80%9309_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17288845-9.html.csv | count | during this period of the 2008-09 san antonio spurs spurs season , tim duncan led the san antonio spurs in rebounds on eleven occasions . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'tim duncan', 'result': '11', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'tim duncan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high rebounds record fuzzily matches to tim duncan .', 'tostr': 'filter_eq { all_rows ; high rebounds ; tim duncan }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high rebounds ; tim duncan } }', 'tointer': 'select the rows whose high rebounds record fuzzily matches to tim duncan . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high rebounds ; tim duncan } } ; 11 } = true', 'tointer': 'select the rows whose high rebounds record fuzzily matches to tim duncan . the number of such rows is 11 .'} | eq { count { filter_eq { all_rows ; high rebounds ; tim duncan } } ; 11 } = true | select the rows whose high rebounds record fuzzily matches to tim duncan . the number of such rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high rebounds_5': 5, 'tim duncan_6': 6, '11_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high rebounds_5': 'high rebounds', 'tim duncan_6': 'tim duncan', '11_7': '11'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'tim duncan_6': [0], '11_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['58', 'march 1', 'portland', 'l 84 - 102 ( ot )', 'tony parker ( 15 )', 'fabricio oberto ( 6 )', 'george hill , tony parker ( 4 )', 'rose garden 20627', '39 - 19'], ['59', 'march 2', 'la clippers', 'w 106 - 78 ( ot )', 'tony parker ( 26 )', 'tim duncan ( 12 )', 'tony parker ( 10 )', 'staples center 17649', '40 - 19'], ['60', 'march 4', 'dallas', 'l 102 - 107 ( ot )', 'tony parker ( 37 )', 'tim duncan ( 12 )', 'tim duncan ( 5 )', 'american airlines center 20316', '40 - 20'], ['61', 'march 6', 'washington', 'w 100 - 78 ( ot )', 'tony parker ( 19 )', 'kurt thomas ( 7 )', 'tony parker ( 7 )', 'at & t center 18440', '41 - 20'], ['62', 'march 8', 'phoenix', 'w 103 - 98 ( ot )', 'tony parker ( 30 )', 'tim duncan ( 15 )', 'tony parker ( 9 )', 'at & t center 18797', '42 - 20'], ['63', 'march 10', 'charlotte', 'w 100 - 86 ( ot )', 'roger mason , tony parker ( 21 )', 'tim duncan ( 11 )', 'tony parker ( 7 )', 'at & t center 18254', '43 - 20'], ['64', 'march 12', 'la lakers', 'l 95 - 102 ( ot )', 'michael finley , tony parker ( 25 )', 'tim duncan ( 11 )', 'tony parker ( 9 )', 'at & t center 18797', '43 - 21'], ['65', 'march 14', 'houston', 'w 88 - 85 ( ot )', 'tony parker ( 28 )', 'tim duncan ( 12 )', 'tony parker ( 8 )', 'toyota center 18300', '44 - 21'], ['66', 'march 16', 'oklahoma city', 'l 76 - 78 ( ot )', 'tony parker ( 28 )', 'tim duncan ( 12 )', 'tony parker ( 7 )', 'ford center 19136', '44 - 22'], ['67', 'march 17', 'minnesota', 'w 93 - 86 ( ot )', 'tony parker ( 24 )', 'kurt thomas ( 10 )', 'tony parker , kurt thomas ( 6 )', 'at & t center 18797', '45 - 22'], ['68', 'march 20', 'boston', 'l 77 - 80 ( ot )', 'tony parker ( 25 )', 'tim duncan ( 9 )', 'tony parker ( 8 )', 'at & t center 18797', '45 - 23'], ['69', 'march 22', 'houston', 'l 85 - 87 ( ot )', 'tim duncan ( 23 )', 'kurt thomas ( 9 )', 'tony parker ( 12 )', 'at & t center 18797', '45 - 24'], ['70', 'march 24', 'golden state', 'w 107 - 106 ( ot )', 'tony parker ( 30 )', 'tim duncan ( 10 )', 'tony parker ( 10 )', 'at & t center 18797', '46 - 24'], ['71', 'march 25', 'atlanta', 'w 102 - 92 ( ot )', 'tony parker ( 42 )', 'kurt thomas ( 8 )', 'tony parker ( 10 )', 'philips arena 18529', '47 - 24'], ['72', 'march 27', 'la clippers', 'w 111 - 98 ( ot )', 'tony parker ( 18 )', 'roger mason ( 8 )', 'manu ginóbili ( 7 )', 'at & t center 18797', '48 - 24'], ['73', 'march 29', 'new orleans', 'l 86 - 90 ( ot )', 'tony parker ( 20 )', 'tim duncan ( 15 )', 'tony parker ( 7 )', 'new orleans arena 18204', '48 - 25'], ['74', 'march 31', 'oklahoma city', 'l 95 - 96 ( ot )', 'tim duncan ( 21 )', 'tim duncan ( 12 )', 'tim duncan , michael finley , tony parker ( 4 )', 'at & t center 18797', '48 - 26']] |
2000 belarusian premier league | https://en.wikipedia.org/wiki/2000_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14747235-1.html.csv | superlative | the stadium in the 2000 belarusian premier league that can hold the most people is the one that is located in minsk . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; capacity }'}, 'venue'], 'result': 'dinamo , minsk', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; capacity } ; venue }'}, 'dinamo , minsk'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; capacity } ; venue } ; dinamo , minsk } = true', 'tointer': 'select the row whose capacity record of all rows is maximum . the venue record of this row is dinamo , minsk .'} | eq { hop { argmax { all_rows ; capacity } ; venue } ; dinamo , minsk } = true | select the row whose capacity record of all rows is maximum . the venue record of this row is dinamo , minsk . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'venue_6': 6, 'dinamo , minsk_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'venue_6': 'venue', 'dinamo , minsk_7': 'dinamo , minsk'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'venue_6': [1], 'dinamo , minsk_7': [2]} | ['team', 'location', 'venue', 'capacity', 'position in 1999'] | [['bate', 'borisov', 'city stadium , borisov', '5500', '1'], ['slavia', 'mozyr', 'yunost , mozyr', '5500', '2'], ['gomel', 'gomel', 'central , gomel', '11800', '3'], ['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '6'], ['dinamo brest', 'brest', 'dinamo , brest', '10080', '7'], ['belshina', 'bobruisk', 'spartak , bobruisk', '3550', '8'], ['neman - belcard', 'grodno', 'neman', '6300', '9'], ['torpedo - maz', 'minsk', 'torpedo , minsk', '5200', '10'], ['lokomotiv - 96', 'vitebsk', 'central , vitebsk', '8300', '11'], ['naftan - devon', 'novopolotsk', 'atlant', '6500', '12'], ['lida', 'lida', 'city stadium , lida', '4000', '13'], ['torpedo - kadino', 'mogilev', 'torpedo , mogilev', '3500', '14'], ['kommunalnik', 'slonim', 'yunost , slonim', '3000', 'first league , 1'], ['vedrich - 97', 'rechytsa', 'central , rechytsa', '3550', 'first league , 2']] |
1965 baltimore colts season | https://en.wikipedia.org/wiki/1965_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14977592-1.html.csv | majority | the baltimore colts won most of the games they played in the 1965 season . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 19 , 1965', 'minnesota vikings', 'w 35 - 16', '1 - 0', 'memorial stadium', '56562'], ['2', 'september 26 , 1965', 'green bay packers', 'l 17 - 20', '1 - 1', 'milwaukee county stadium', '48130'], ['3', 'october 3 , 1965', 'san francisco 49ers', 'w 27 - 24', '2 - 1', 'memorial stadium', '58609'], ['4', 'october 10 , 1965', 'detroit lions', 'w 31 - 7', '3 - 1', 'memorial stadium', '60238'], ['5', 'october 17 , 1965', 'washington redskins', 'w 38 - 7', '4 - 1', 'rfk stadium', '50405'], ['6', 'october 24 , 1965', 'los angeles rams', 'w 35 - 20', '5 - 1', 'memorial stadium', '45827'], ['7', 'october 31 , 1966', 'san francisco 49ers', 'w 34 - 28', '6 - 1', 'kezar stadium', '45827'], ['8', 'november 7 , 1965', 'chicago bears', 'w 26 - 21', '7 - 1', 'wrigley field', '45656'], ['9', 'november 14 , 1965', 'minnesota vikings', 'w 41 - 21', '8 - 1', 'metropolitan stadium', '47426'], ['10', 'november 21 , 1965', 'philadelphia eagles', 'w 34 - 24', '9 - 1', 'memorial stadium', '60238'], ['11', 'november 25 , 1965', 'detroit lions', 't 24 - 24', '9 - 1 - 1', 'tiger stadium', '55036'], ['12', 'december 5 , 1966', 'chicago bears', 'l 0 - 13', '9 - 2 - 1', 'memorial stadium', '60238'], ['13', 'december 12 , 1965', 'green bay packers', 'l 27 - 42', '9 - 3 - 1', 'memorial stadium', '60238'], ['14', 'december 18 , 1965', 'los angeles rams', 'w 20 - 17', '10 - 3 - 1', 'la memorial coliseum', '46636']] |
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