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jonas l.a | https://en.wikipedia.org/wiki/Jonas_L.A. | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12441518-1.html.csv | comparative | the chacratcer macy misa appeared in less epsiodes of jonas l.a than the character stella malone . | {'row_1': '5', 'row_2': '4', 'col': '5', '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', 'character', 'macy misa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose character record fuzzily matches to macy misa .', 'tostr': 'filter_eq { all_rows ; character ; macy misa }'}, 'of episodes'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; character ; macy misa } ; of episodes }', 'tointer': 'select the rows whose character record fuzzily matches to macy misa . take the of episodes record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'character', 'stella malone'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose character record fuzzily matches to stella malone .', 'tostr': 'filter_eq { all_rows ; character ; stella malone }'}, 'of episodes'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; character ; stella malone } ; of episodes }', 'tointer': 'select the rows whose character record fuzzily matches to stella malone . take the of episodes record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; character ; macy misa } ; of episodes } ; hop { filter_eq { all_rows ; character ; stella malone } ; of episodes } } = true', 'tointer': 'select the rows whose character record fuzzily matches to macy misa . take the of episodes record of this row . select the rows whose character record fuzzily matches to stella malone . take the of episodes record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; character ; macy misa } ; of episodes } ; hop { filter_eq { all_rows ; character ; stella malone } ; of episodes } } = true | select the rows whose character record fuzzily matches to macy misa . take the of episodes record of this row . select the rows whose character record fuzzily matches to stella malone . take the of episodes 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, 'character_7': 7, 'macy misa_8': 8, 'of episodes_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'character_11': 11, 'stella malone_12': 12, 'of episodes_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', 'character_7': 'character', 'macy misa_8': 'macy misa', 'of episodes_9': 'of episodes', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'character_11': 'character', 'stella malone_12': 'stella malone', 'of episodes_13': 'of episodes'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'character_7': [0], 'macy misa_8': [0], 'of episodes_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'character_11': [1], 'stella malone_12': [1], 'of episodes_13': [3]} | ['character', 'portrayed by', 'main cast seasons', 'recurring cast seasons', 'of episodes'] | [['nick lucas', 'nick jonas', 'seasons 1 - 2', 'appears in all seasons', '34'], ['joe lucas', 'joe jonas', 'seasons 1 - 2', 'appears in all seasons', '34'], ['kevin lucas', 'kevin jonas', 'seasons 1 - 2', 'appears in all seasons', '34'], ['stella malone', 'chelsea kane', 'seasons 1 - 2', 'appears in all seasons', '34'], ['macy misa', 'nicole anderson', 'seasons 1 - 2', 'appears in all seasons', '30']] |
lost ( season 5 ) | https://en.wikipedia.org/wiki/Lost_%28season_5%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11562143-1.html.csv | majority | most of the april episodes of the fifth season of lost had at least 9 million viewers . | {'scope': 'subset', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '9', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'april'}} | {'func': 'most_greater_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'april'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; april }', 'tointer': 'select the rows whose original air date record fuzzily matches to april .'}, 'us viewers ( million )', '9'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose original air date record fuzzily matches to april . for the us viewers ( million ) records of these rows , most of them are greater than or equal to 9 .', 'tostr': 'most_greater_eq { filter_eq { all_rows ; original air date ; april } ; us viewers ( million ) ; 9 } = true'} | most_greater_eq { filter_eq { all_rows ; original air date ; april } ; us viewers ( million ) ; 9 } = true | select the rows whose original air date record fuzzily matches to april . for the us viewers ( million ) records of these rows , most of them are greater than or equal to 9 . | 2 | 2 | {'most_greater_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'original air date_4': 4, 'april_5': 5, 'us viewers (million)_6': 6, '9_7': 7} | {'most_greater_eq_1': 'most_greater_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'original air date_4': 'original air date', 'april_5': 'april', 'us viewers (million)_6': 'us viewers ( million )', '9_7': '9'} | {'most_greater_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'original air date_4': [0], 'april_5': [0], 'us viewers (million)_6': [1], '9_7': [1]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'featured character ( s )', 'original air date', 'us viewers ( million )'] | [['87', '1', 'because you left', 'stephen williams', 'damon lindelof & carlton cuse', 'none', 'january 21 , 2009', '11.66'], ['88', '2', 'the lie', 'jack bender', 'edward kitsis & adam horowitz', 'hurley', 'january 21 , 2009', '11.08'], ['89', '3', 'jughead', 'rod holcomb', 'elizabeth sarnoff & paul zbyszewski', 'desmond', 'january 28 , 2009', '11.07'], ['90', '4', 'the little prince', 'stephen williams', 'brian k vaughan & melinda hsu taylor', 'kate', 'february 4 , 2009', '10.98'], ['91', '5', 'this place is death', 'paul edwards', 'edward kitsis & adam horowitz', 'sun & jin', 'february 11 , 2009', '9.77'], ['92', '6', '316', 'stephen williams', 'damon lindelof & carlton cuse', 'jack', 'february 18 , 2009', '11.27'], ['93', '7', 'the life and death of jeremy bentham', 'jack bender', 'carlton cuse & damon lindelof', 'locke', 'february 25 , 2009', '9.82'], ['94', '8', 'lafleur', 'mark goldman', 'elizabeth sarnoff & kyle pennington', 'sawyer', 'march 4 , 2009', '10.61'], ['95', '9', 'namaste', 'jack bender', 'paul zbyszewski & brian k vaughan', 'none', 'march 18 , 2009', '9.08'], ['96', '10', "he 's our you", 'greg yaitanes', 'edward kitsis & adam horowitz', 'sayid', 'march 25 , 2009', '8.82'], ['97', '11', 'whatever happened , happened', 'bobby roth', 'carlton cuse & damon lindelof', 'kate', 'april 1 , 2009', '9.35'], ['98', '12', 'dead is dead', 'stephen williams', 'brian k vaughan & elizabeth sarnoff', 'ben', 'april 8 , 2009', '8.29'], ['99', '13', 'some like it hoth', 'jack bender', 'melinda hsu taylor & greggory nations', 'miles', 'april 15 , 2009', '9.23'], ['100', '14', 'the variable', 'paul edwards', 'edward kitsis & adam horowitz', 'faraday', 'april 29 , 2009', '9.04'], ['101', '15', 'follow the leader', 'stephen williams', 'paul zbyszewski & elizabeth sarnoff', 'none', 'may 6 , 2009', '8.70']] |
joão roque | https://en.wikipedia.org/wiki/Jo%C3%A3o_Roque | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445820-2.html.csv | aggregation | for joao roque had an average 2.3 rounds per match . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '2.3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'round'], 'result': '2.3', 'ind': 0, 'tostr': 'avg { all_rows ; round }'}, '2.3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; round } ; 2.3 } = true', 'tointer': 'the average of the round record of all rows is 2.3 .'} | round_eq { avg { all_rows ; round } ; 2.3 } = true | the average of the round record of all rows is 2.3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'round_4': 4, '2.3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'round_4': 'round', '2.3_5': '2.3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'round_4': [0], '2.3_5': [1]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '7 - 2 - 4', 'alexandre franca nogueira', 'decision ( unanimous )', 'shooto 2005 - 3 / 11 in korakuen hall', '3', '5:00', 'tokyo korakuen hall'], ['draw', '7 - 1 - 4', 'hiroyuki takaya', 'draw', 'shooto 2004 - 1 / 24 in korakuen hall', '3', '5:00', 'tokyo , japan'], ['win', '7 - 1 - 3', 'hiroyuki abe', 'submission ( armbar )', 'shooto - gig central 4', '2', '4:59', 'nagoya , japan'], ['win', '6 - 1 - 3', 'naoya uematsu', 'decision ( unanimous )', 'shooto 2003 - 1 / 24 in korakuen hall', '3', '5:00', 'tokyo , japan'], ['win', '5 - 1 - 3', 'ryan bow', 'decision ( majority )', 'deep - 6th impact', '3', '5:00', 'tokyo , japan'], ['win', '4 - 1 - 3', 'takehiro murahama', 'submission ( armbar )', 'deep - 4th impact', '1', '2:13', 'nagoya , japan'], ['win', '3 - 1 - 3', 'stephen palling', 'submission ( armbar )', 'world fighting alliance 1', '1', '1:29', 'nevada , united states'], ['win', '2 - 1 - 3', 'takehiro murahama', 'submission ( armbar )', 'deep - 2nd impact', '1', '4:29', 'yokohama , japan'], ['loss', '1 - 1 - 3', 'jens pulver', 'decision', 'ufc 26', '3', '5:00', 'iowa , united states'], ['draw', '1 - 0 - 3', 'hisao ikeda', 'draw', 'vtj 1999 - vale tudo japan 1999', '3', '8:00', 'tokyo , japan'], ['draw', '1 - 0 - 2', 'noboru asahi', 'draw', 'vtj 1998 - vale tudo japan 1998', '3', '8:00', 'tokyo , japan'], ['draw', '1 - 0 - 1', 'uchu tatsumi', 'draw', 'vtj 1997 - vale tudo japan 1997', '3', '8:00', 'tokyo , japan'], ['win', '1 - 0', 'abdelaziz cherigui', 'submission ( armbar )', 'ef 3 - extreme fighting 3', '1', '4:02', 'oklahoma , united states']] |
kuba giermaziak | https://en.wikipedia.org/wiki/Kuba_Giermaziak | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26473176-1.html.csv | majority | kuba giermaziak drove with the motopark academy in the majority of series during his career . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'motopark academy', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'team', 'motopark academy'], 'result': True, 'ind': 0, 'tointer': 'for the team records of all rows , most of them fuzzily match to motopark academy .', 'tostr': 'most_eq { all_rows ; team ; motopark academy } = true'} | most_eq { all_rows ; team ; motopark academy } = true | for the team records of all rows , most of them fuzzily match to motopark academy . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team_3': 3, 'motopark academy_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team_3': 'team', 'motopark academy_4': 'motopark academy'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team_3': [0], 'motopark academy_4': [0]} | ['season', 'series', 'team', 'races', 'wins', 'f / laps', 'podiums', 'points', 'position'] | [['2007', 'formula renault 2.0 nec', 'motopark academy', '15', '0', '0', '0', '97', '10th'], ['2007', 'formula renault 2.0 eurocup', 'motopark academy', '2', '0', '0', '0', '0', 'nc'], ['2008', 'formula renault 2.0 eurocup', 'motopark academy', '14', '0', '0', '0', '10', '18th'], ['2008', 'formula renault 2.0 nec', 'motopark academy', '14', '0', '0', '5', '206', '6th'], ['2008', 'portuguese formula renault 2.0 winter series', 'motopark academy', '2', '0', '0', '0', '4', '18th'], ['2009', 'formula renault 2.0 eurocup', 'motopark academy', '8', '0', '0', '1', '32', '9th'], ['2009', 'formula renault 2.0 nec', 'motopark academy', '10', '0', '0', '1', '115', '14th'], ['2009', 'adac gt masters', 'argo racing', '10', '0', '1', '3', '35', '11th'], ['2010', 'porsche supercup', 'verva racing team', '10', '0', '0', '0', '56', '10th'], ['2010', 'adac gt masters', 'abt sportsline', '10', '2', '0', '4', '42', '8th'], ['2011', 'formula 3 euroseries', 'star racing team', '18', '0', '0', '0', '29', '12th']] |
1951 in brazilian football | https://en.wikipedia.org/wiki/1951_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15303773-1.html.csv | count | 4 teams had a negative point differential in 1951 brazilian football . | {'scope': 'all', 'criterion': 'less_than', 'value': '0', 'result': '4', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'difference', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose difference record is less than 0 .', 'tostr': 'filter_less { all_rows ; difference ; 0 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; difference ; 0 } }', 'tointer': 'select the rows whose difference record is less than 0 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; difference ; 0 } } ; 4 } = true', 'tointer': 'select the rows whose difference record is less than 0 . the number of such rows is 4 .'} | eq { count { filter_less { all_rows ; difference ; 0 } } ; 4 } = true | select the rows whose difference record is less than 0 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'difference_5': 5, '0_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'difference_5': 'difference', '0_6': '0', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'difference_5': [0], '0_6': [0], '4_7': [2]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'palmeiras', '10', '7', '0', '2', '14', '11'], ['2', 'corinthians', '10', '7', '2', '1', '12', '8'], ['3', 'bangu', '7', '7', '1', '3', '18', '4'], ['4', 'flamengo', '7', '7', '1', '3', '19', '- 4'], ['5', 'américa', '7', '7', '3', '2', '19', '0'], ['6', 'portuguesa', '7', '7', '1', '3', '23', '- 6'], ['7', 'vasco da gama', '6', '7', '4', '2', '18', '- 3'], ['8', 'são paulo', '2', '7', '2', '5', '18', '- 10']] |
2007 japanese television dramas | https://en.wikipedia.org/wiki/2007_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539861-1.html.csv | superlative | the highest ratings for 2007 japanese television dramas was for karei - naru ichizoku . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', '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', 'average ratings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; average ratings }'}, 'romaji title'], 'result': 'karei - naru ichizoku', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; average ratings } ; romaji title }'}, 'karei - naru ichizoku'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; average ratings } ; romaji title } ; karei - naru ichizoku } = true', 'tointer': 'select the row whose average ratings record of all rows is maximum . the romaji title record of this row is karei - naru ichizoku .'} | eq { hop { argmax { all_rows ; average ratings } ; romaji title } ; karei - naru ichizoku } = true | select the row whose average ratings record of all rows is maximum . the romaji title record of this row is karei - naru ichizoku . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'average ratings_5': 5, 'romaji title_6': 6, 'karei - naru ichizoku_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'average ratings_5': 'average ratings', 'romaji title_6': 'romaji title', 'karei - naru ichizoku_7': 'karei - naru ichizoku'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'average ratings_5': [0], 'romaji title_6': [1], 'karei - naru ichizoku_7': [2]} | ['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings'] | [['エラいところに嫁いでしまった !', 'erai tokoro ni totsuide shimatta !', 'tv asahi', '9', '12.8 %'], ['演歌の女王', 'enka no joou', 'ntv', '10', '9.1 %'], ['華麗なる一族', 'karei - naru ichizoku', 'tbs', '10', '27.15 %'], ['きらきら研修医', 'kirakira kenshuui', 'tbs', '11', '9.38 %'], ['花より男子2 （ リターンズ ）', 'hana yori dango 2 ( returns )', 'tbs', '11', '21.7 %'], ['今週 、 妻が浮気します', 'konshu , tsuma ga uwakishimasu', 'fuji tv', '11', '10.15 %'], ['東京タワー ～ オカンとボクと 、 時々 、 オトン ～', 'tokyo tower ~ okan to boku to , tokidoki , oton ~', 'fuji tv', '11', '14.9 %'], ['拝啓 、 父上様', 'haikei , chichiue - sama', 'fuji tv', '11', '13.19 %'], ['ハケンの品格', 'haken no hinkaku', 'ntv', '10', '20.1 %'], ['ヒミツの花園', 'himitsu no hanazono', 'fuji tv', '11', '12.41 %'], ['わるいやつら', 'waruiyatsura', 'tv asahi', '8', '9.4 %']] |
the rob brydon show | https://en.wikipedia.org/wiki/The_Rob_Brydon_Show | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29135051-2.html.csv | superlative | the rob brydon show had the highest ratings when the guest was matt lucas . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', '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', 'ratings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; ratings }'}, 'guest ( s )'], 'result': 'matt lucas', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; ratings } ; guest ( s ) }'}, 'matt lucas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; ratings } ; guest ( s ) } ; matt lucas } = true', 'tointer': 'select the row whose ratings record of all rows is maximum . the guest ( s ) record of this row is matt lucas .'} | eq { hop { argmax { all_rows ; ratings } ; guest ( s ) } ; matt lucas } = true | select the row whose ratings record of all rows is maximum . the guest ( s ) record of this row is matt lucas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'ratings_5': 5, 'guest (s)_6': 6, 'matt lucas_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'ratings_5': 'ratings', 'guest (s)_6': 'guest ( s )', 'matt lucas_7': 'matt lucas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'ratings_5': [0], 'guest (s)_6': [1], 'matt lucas_7': [2]} | ['episode', 'broadcast date', 'guest ( s )', 'singer ( s )', 'comedian', 'ratings'] | [['1', '22 july 2011', 'matt lucas', 'the script', 'nina conti', '2.08 m'], ['2', '29 july 2011', 'bill bailey', 'beverley knight', 'celia pacquola', '1.45 m'], ['3', '5 august 2011', 'bruce forsyth', 'sophie ellis - bextor', 'elis james', 'under 1.41 m'], ['4', '12 august 2011', "chris o'dowd", 'the faces', 'josh widdicombe', 'under 1.32 m'], ['5', '19 august 2011', 'dame edna everage', 'will young', 'phil wang', '1.57 m'], ['6', '26 august 2011', 'frank skinner', 'hurts', 'joe wilkinson', '1.64 m']] |
polona hercog | https://en.wikipedia.org/wiki/Polona_Hercog | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17717526-9.html.csv | unique | the 11 february 2008 tournament was the only tournament that polona hercog played in spain . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'spain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; tournament ; spain }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; tournament ; spain } }', 'tointer': 'select the rows whose tournament record fuzzily matches to spain . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; tournament ; spain }'}, 'date'], 'result': '11 february 2008', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; spain } ; date }'}, '11 february 2008'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; spain } ; date } ; 11 february 2008 }', 'tointer': 'the date record of this unqiue row is 11 february 2008 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; tournament ; spain } } ; eq { hop { filter_eq { all_rows ; tournament ; spain } ; date } ; 11 february 2008 } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to spain . there is only one such row in the table . the date record of this unqiue row is 11 february 2008 .'} | and { only { filter_eq { all_rows ; tournament ; spain } } ; eq { hop { filter_eq { all_rows ; tournament ; spain } ; date } ; 11 february 2008 } } = true | select the rows whose tournament record fuzzily matches to spain . there is only one such row in the table . the date record of this unqiue row is 11 february 2008 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'spain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '11 february 2008_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'spain_8': 'spain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '11 february 2008_10': '11 february 2008'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'tournament_7': [0], 'spain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '11 february 2008_10': [3]} | ['date', 'tournament', 'surface', 'partner', 'opponents', 'score'] | [['15 january 2007', 'algiers 2 , algeria', 'clay', 'rushmi chakravarthi', 'barbora matusova anna savitskaya', '6 - 2 , 6 - 0'], ['11 february 2008', 'mallorca 2 , spain', 'clay', 'stephanie vogt', 'leticia costas - moreira maite gabarrus alonso', '7 - 6 ( 7 - 2 ) , 6 - 3'], ['28 april 2008', 'makarska , croatia', 'clay', 'stephanie vogt', 'tadeja majerić maša zec peškirič', '7 - 5 , 6 - 2'], ['8 september 2008', 'sarajevo 2 , bosnia - herzegovina', 'clay', 'alberta brianti', 'çağla büyükakçay julia glushko', '6 - 4 , 7 - 5'], ['8 february 2010', 'cali , colombia', 'clay', 'edina gallovits', 'estrella cabeza candella laura pous tió', '3 - 6 , 6 - 3 ,']] |
amino acid | https://en.wikipedia.org/wiki/Amino_acid | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1207-4.html.csv | comparative | the amino acid valine has a higher hydropathy index than glycine . | {'row_1': '20', 'row_2': '8', 'col': '6', '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', 'amino acid', 'valine'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose amino acid record fuzzily matches to valine .', 'tostr': 'filter_eq { all_rows ; amino acid ; valine }'}, 'hydropathy index'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; amino acid ; valine } ; hydropathy index }', 'tointer': 'select the rows whose amino acid record fuzzily matches to valine . take the hydropathy index record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'amino acid', 'glycine'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose amino acid record fuzzily matches to glycine .', 'tostr': 'filter_eq { all_rows ; amino acid ; glycine }'}, 'hydropathy index'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; amino acid ; glycine } ; hydropathy index }', 'tointer': 'select the rows whose amino acid record fuzzily matches to glycine . take the hydropathy index record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; amino acid ; valine } ; hydropathy index } ; hop { filter_eq { all_rows ; amino acid ; glycine } ; hydropathy index } } = true', 'tointer': 'select the rows whose amino acid record fuzzily matches to valine . take the hydropathy index record of this row . select the rows whose amino acid record fuzzily matches to glycine . take the hydropathy index record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; amino acid ; valine } ; hydropathy index } ; hop { filter_eq { all_rows ; amino acid ; glycine } ; hydropathy index } } = true | select the rows whose amino acid record fuzzily matches to valine . take the hydropathy index record of this row . select the rows whose amino acid record fuzzily matches to glycine . take the hydropathy index 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, 'amino acid_7': 7, 'valine_8': 8, 'hydropathy index_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'amino acid_11': 11, 'glycine_12': 12, 'hydropathy index_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', 'amino acid_7': 'amino acid', 'valine_8': 'valine', 'hydropathy index_9': 'hydropathy index', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'amino acid_11': 'amino acid', 'glycine_12': 'glycine', 'hydropathy index_13': 'hydropathy index'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'amino acid_7': [0], 'valine_8': [0], 'hydropathy index_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'amino acid_11': [1], 'glycine_12': [1], 'hydropathy index_13': [3]} | ['amino acid', '3 - letter', '1 - letter', 'side - chain polarity', 'side - chain charge ( ph 7.4 )', 'hydropathy index'] | [['alanine', 'ala', 'a', 'nonpolar', 'neutral', '1.8'], ['arginine', 'arg', 'r', 'basic polar', 'positive', '4.5'], ['asparagine', 'asn', 'n', 'polar', 'neutral', '3.5'], ['aspartic acid', 'asp', 'd', 'acidic polar', 'negative', '3.5'], ['cysteine', 'cys', 'c', 'nonpolar', 'neutral', '2.5'], ['glutamic acid', 'glu', 'e', 'acidic polar', 'negative', '3.5'], ['glutamine', 'gln', 'q', 'polar', 'neutral', '3.5'], ['glycine', 'gly', 'g', 'nonpolar', 'neutral', '0.4'], ['histidine', 'his', 'h', 'basic polar', 'positive ( 10 % ) neutral ( 90 % )', '3.2'], ['isoleucine', 'ile', 'i', 'nonpolar', 'neutral', '4.5'], ['leucine', 'leu', 'l', 'nonpolar', 'neutral', '3.8'], ['lysine', 'lys', 'k', 'basic polar', 'positive', '3.9'], ['methionine', 'met', 'm', 'nonpolar', 'neutral', '1.9'], ['phenylalanine', 'phe', 'f', 'nonpolar', 'neutral', '2.8'], ['proline', 'pro', 'p', 'nonpolar', 'neutral', '1.6'], ['serine', 'ser', 's', 'polar', 'neutral', '0.8'], ['threonine', 'thr', 't', 'polar', 'neutral', '0.7'], ['tryptophan', 'trp', 'w', 'nonpolar', 'neutral', '0.9'], ['tyrosine', 'tyr', 'y', 'polar', 'neutral', '1.3'], ['valine', 'val', 'v', 'nonpolar', 'neutral', '4.2']] |
wqln - fm | https://en.wikipedia.org/wiki/WQLN-FM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14163566-1.html.csv | aggregation | wqln - fm 's average erp w on this chart is 16 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '16', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'erp w'], 'result': '16', 'ind': 0, 'tostr': 'avg { all_rows ; erp w }'}, '16'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; erp w } ; 16 } = true', 'tointer': 'the average of the erp w record of all rows is 16 .'} | round_eq { avg { all_rows ; erp w } ; 16 } = true | the average of the erp w record of all rows is 16 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'erp w_4': 4, '16_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'erp w_4': 'erp w', '16_5': '16'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'erp w_4': [0], '16_5': [1]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'fcc info'] | [['w207af', '89.3 fm', 'meadville , pa', '4', 'fcc'], ['w211ae', '90.1 fm', 'mayville , ny', '3', 'fcc'], ['w218ap', '91.5 fm', 'titusville , pa', '13', 'fcc'], ['w220ba', '91.9 fm', 'oil city , pa', '10', 'fcc'], ['w255ae', '98.9 fm', 'warren , pa', '50', 'fcc']] |
giorgio mazza | https://en.wikipedia.org/wiki/Giorgio_Mazza | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11881236-1.html.csv | count | giorgio mazza finished in 5th place two times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '5', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 5 .', 'tostr': 'filter_eq { all_rows ; result ; 5 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; 5 } }', 'tointer': 'select the rows whose result record fuzzily matches to 5 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; 5 } } ; 2 } = true', 'tointer': 'select the rows whose result record fuzzily matches to 5 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; result ; 5 } } ; 2 } = true | select the rows whose result record fuzzily matches to 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, 'result_5': 5, '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', 'result_5': 'result', '5_6': '5', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], '5_6': [0], '2_7': [2]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['1958', 'european championships', 'stockholm , sweden', '5th', '110 m hurdles'], ['1959', 'universiade', 'turin , italy', '3rd', '110 m hurdles'], ['1962', 'european championships', 'belgrade , yugoslavia', '5th', '110 m hurdles'], ['1963', 'universiade', 'pãrto alegre , brazil', '2nd', '110 m hurdles'], ['1963', 'mediterranean games', 'naples , italy', '3rd', '110 m hurdles'], ['1964', 'olympic games', 'tokyo , japan', '8th', '110 m hurdles']] |
algeria at the 2008 summer olympics | https://en.wikipedia.org/wiki/Algeria_at_the_2008_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17427004-7.html.csv | count | algeria at the 2008 summer olympics did not advance two times to the round of 16 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'did not advance', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'round of 16', 'did not advance'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round of 16 record fuzzily matches to did not advance .', 'tostr': 'filter_eq { all_rows ; round of 16 ; did not advance }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; round of 16 ; did not advance } }', 'tointer': 'select the rows whose round of 16 record fuzzily matches to did not advance . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; round of 16 ; did not advance } } ; 2 } = true', 'tointer': 'select the rows whose round of 16 record fuzzily matches to did not advance . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; round of 16 ; did not advance } } ; 2 } = true | select the rows whose round of 16 record fuzzily matches to did not advance . 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, 'round of 16_5': 5, 'did not advance_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', 'round of 16_5': 'round of 16', 'did not advance_6': 'did not advance', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'round of 16_5': [0], 'did not advance_6': [0], '2_7': [2]} | ['athlete', 'event', 'round of 32', 'round of 16', 'quarterfinals', 'semifinals'] | [['abdelhalim ouradi', 'bantamweight', 'nevin ( irl ) l 4 - 9', 'did not advance', 'did not advance', 'did not advance'], ['abdelkader chadi', 'featherweight', 'bye', 'adi ( tha ) w 7 - 6', 'kılıç ( tur ) l 6 - 13', 'did not advance'], ['hamza kramou', 'lightweight', 'ugás ( cub ) l 3 - 21', 'did not advance', 'did not advance', 'did not advance'], ['nabil kassel', 'middleweight', 'bye', 'sutherland ( irl ) l 14 - 21', 'did not advance', 'did not advance'], ['abdelhafid benchebla', 'light heavyweight', 'kumar ( ind ) w 23 - 3', 'yasser ( egy ) w 13 - 6', 'zhang xp ( chn ) l 7 - 12', 'did not advance'], ['abdelaziz touilbini', 'heavyweight', 'n / a', 'wilder ( usa ) l 4 - 10', 'did not advance', 'did not advance']] |
1989 - 90 illinois fighting illini men 's basketball team | https://en.wikipedia.org/wiki/1989%E2%80%9390_Illinois_Fighting_Illini_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22824324-2.html.csv | aggregation | all the players in the 1989 - 90 illinois fighting illini men 's basketball team had average field goals of around 113 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '113', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'field goals'], 'result': '113', 'ind': 0, 'tostr': 'avg { all_rows ; field goals }'}, '113'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; field goals } ; 113 } = true', 'tointer': 'the average of the field goals record of all rows is 113 .'} | round_eq { avg { all_rows ; field goals } ; 113 } = true | the average of the field goals record of all rows is 113 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'field goals_4': 4, '113_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'field goals_4': 'field goals', '113_5': '113'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'field goals_4': [0], '113_5': [1]} | ['player', 'games played', 'field goals', 'three pointers', 'free throws', 'rebounds', 'assists', 'blocks', 'steals', 'points'] | [['kendall gill', '29', '211', '23', '136', '143', '96', '16', '63', '581'], ['andy kaufmann', '29', '91', '22', '81', '93', '54', '5', '27', '285'], ['steve bardo', '29', '99', '28', '55', '178', '137', '14', '37', '281'], ['rodney jones', '29', '88', '0', '40', '126', '9', '18', '17', '216'], ['ervin small', '29', '75', '1', '49', '151', '12', '5', '23', '200']] |
burma | https://en.wikipedia.org/wiki/Burma | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19457-1.html.csv | unique | kachin state is the only state in burma that has 18 town ships . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '18', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'town ships', '18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose town ships record is equal to 18 .', 'tostr': 'filter_eq { all_rows ; town ships ; 18 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; town ships ; 18 } }', 'tointer': 'select the rows whose town ships record is equal to 18 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'town ships', '18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose town ships record is equal to 18 .', 'tostr': 'filter_eq { all_rows ; town ships ; 18 }'}, 'state / region'], 'result': 'kachin state', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; town ships ; 18 } ; state / region }'}, 'kachin state'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; town ships ; 18 } ; state / region } ; kachin state }', 'tointer': 'the state / region record of this unqiue row is kachin state .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; town ships ; 18 } } ; eq { hop { filter_eq { all_rows ; town ships ; 18 } ; state / region } ; kachin state } } = true', 'tointer': 'select the rows whose town ships record is equal to 18 . there is only one such row in the table . the state / region record of this unqiue row is kachin state .'} | and { only { filter_eq { all_rows ; town ships ; 18 } } ; eq { hop { filter_eq { all_rows ; town ships ; 18 } ; state / region } ; kachin state } } = true | select the rows whose town ships record is equal to 18 . there is only one such row in the table . the state / region record of this unqiue row is kachin state . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'town ships_7': 7, '18_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'state / region_9': 9, 'kachin state_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'town ships_7': 'town ships', '18_8': '18', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'state / region_9': 'state / region', 'kachin state_10': 'kachin state'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'town ships_7': [0], '18_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'state / region_9': [2], 'kachin state_10': [3]} | ['no', 'state / region', 'districts', 'town ships', 'cities / towns', 'wards', 'village groups', 'villages'] | [['1', 'kachin state', '3', '18', '20', '116', '606', '2630'], ['2', 'kayah state', '2', '7', '7', '29', '79', '624'], ['3', 'kayin state', '3', '7', '10', '46', '376', '2092'], ['4', 'chin state', '2', '9', '9', '29', '475', '1355'], ['5', 'sagaing region', '8', '37', '37', '171', '1769', '6095'], ['6', 'tanintharyi region', '3', '10', '10', '63', '265', '1255'], ['7', 'bago region', '4', '28', '33', '246', '1424', '6498'], ['8', 'magway region', '5', '25', '26', '160', '1543', '4774'], ['9', 'mandalay region', '7', '31', '29', '259', '1611', '5472'], ['10', 'mon state', '2', '10', '11', '69', '381', '1199'], ['11', 'rakhine state', '4', '17', '17', '120', '1041', '3871'], ['12', 'yangon region', '4', '45', '20', '685', '634', '2119'], ['13', 'shan state', '11', '54', '54', '336', '1626', '15513'], ['14', 'ayeyarwady region', '6', '26', '29', '219', '1912', '11651']] |
loongson | https://en.wikipedia.org/wiki/Loongson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1764207-1.html.csv | unique | the l3b model processor is the only loongson processor that has 8 cores . | {'scope': 'all', 'row': '11', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': '8', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'cores', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cores record is equal to 8 .', 'tostr': 'filter_eq { all_rows ; cores ; 8 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; cores ; 8 } }', 'tointer': 'select the rows whose cores record is equal to 8 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'cores', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cores record is equal to 8 .', 'tostr': 'filter_eq { all_rows ; cores ; 8 }'}, 'model'], 'result': 'l3b', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; cores ; 8 } ; model }'}, 'l3b'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; cores ; 8 } ; model } ; l3b }', 'tointer': 'the model record of this unqiue row is l3b .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; cores ; 8 } } ; eq { hop { filter_eq { all_rows ; cores ; 8 } ; model } ; l3b } } = true', 'tointer': 'select the rows whose cores record is equal to 8 . there is only one such row in the table . the model record of this unqiue row is l3b .'} | and { only { filter_eq { all_rows ; cores ; 8 } } ; eq { hop { filter_eq { all_rows ; cores ; 8 } ; model } ; l3b } } = true | select the rows whose cores record is equal to 8 . there is only one such row in the table . the model record of this unqiue row is l3b . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'cores_7': 7, '8_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'model_9': 9, 'l3b_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'cores_7': 'cores', '8_8': '8', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'model_9': 'model', 'l3b_10': 'l3b'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'cores_7': [0], '8_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'model_9': [2], 'l3b_10': [3]} | ['name / generation', 'model', 'frequency', 'architecture version', 'cores', 'process'] | [['godson - 1 ( embedded cpu )', '1', '266', 'mips32', '1', '180'], ['godson - 1 ( embedded cpu )', '1a', '300', 'mips32', '1', '130'], ['godson - 1 ( embedded cpu )', '1b', '200', 'mips32', '1', '130'], ['godson - 2 ( singlecore )', '2b', '250', 'mips - iii 64 - bit', '1', '180'], ['godson - 2 ( singlecore )', '2c', '450', 'mips - iii 64 - bit', '1', '180'], ['godson - 2 ( singlecore )', 'stls2e', '1000', 'mips - iii 64 - bit', '1', '90'], ['godson - 2 ( singlecore )', 'stls2f', '1200', 'mips - iii 64 - bit', '1', '90'], ['godson - 2 ( singlecore )', 'l2 g', '9001000', 'mips64', '1', '65'], ['godson - 2 ( singlecore )', 'l2h', '1000', 'mips64', '1', '65'], ['godson - 3 ( multicore )', 'l3a / l2 gq', '1000', 'mips64', '4', '65'], ['godson - 3 ( multicore )', 'l3b', '1050', 'mips64', '8', '65'], ['godson - 3 ( multicore )', 'l3c', '1500 +', 'mips64', '16', '28'], ['godson - t ( manycore )', 'godson - t', '1000', 'mips32', '64', '28'], ['name / generation', 'model', 'frequency', 'architecture version', 'cores', 'process']] |
statues of the liberators | https://en.wikipedia.org/wiki/Statues_of_the_Liberators | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13846706-1.html.csv | superlative | the oldest statue of liberator on virginia avenue is the one of general josé gervasio artigas . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'year erected'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; year erected }'}, 'statue'], 'result': 'general josé gervasio artigas', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; year erected } ; statue }'}, 'general josé gervasio artigas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; year erected } ; statue } ; general josé gervasio artigas } = true', 'tointer': 'select the row whose year erected record of all rows is minimum . the statue record of this row is general josé gervasio artigas .'} | eq { hop { argmin { all_rows ; year erected } ; statue } ; general josé gervasio artigas } = true | select the row whose year erected record of all rows is minimum . the statue record of this row is general josé gervasio artigas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'year erected_5': 5, 'statue_6': 6, 'general josé gervasio artigas_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'year erected_5': 'year erected', 'statue_6': 'statue', 'general josé gervasio artigas_7': 'general josé gervasio artigas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'year erected_5': [0], 'statue_6': [1], 'general josé gervasio artigas_7': [2]} | ['statue', 'liberator', 'country', 'year erected', 'artist'] | [['general josé gervasio artigas', 'josé gervasio artigas', 'uruguay', '1950', 'juan manuel blanes ( 1830 - 1901 )'], ['equestrian of simón bolívar', 'simón bolívar', 'venezuela', '1958', 'felix de weldon ( 1907 - 2003 )'], ['general jose de san martin memorial', 'josé de san martín', 'argentina', '1970s', 'augustin - alexandre dumont ( 1801 - 1884 )'], ['bernardo de gálvez', 'bernardo de gálvez', 'spain', '1976', 'juan de ávalos ( 1911 - 2006 )'], ['benito juarez', 'benito juárez', 'mexico', '1969', 'enrique alciati']] |
jhalak dikhhla jaa ( indian dance series ) | https://en.wikipedia.org/wiki/Jhalak_Dikhhla_Jaa_%28Indian_Dance_Series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13133962-1.html.csv | unique | season four was the only season of the indian dance series where the finale date was in the month of march . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'march', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season finale date', 'march'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season finale date record fuzzily matches to march .', 'tostr': 'filter_eq { all_rows ; season finale date ; march }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; season finale date ; march } }', 'tointer': 'select the rows whose season finale date record fuzzily matches to march . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season finale date', 'march'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season finale date record fuzzily matches to march .', 'tostr': 'filter_eq { all_rows ; season finale date ; march }'}, 'season'], 'result': '4', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season finale date ; march } ; season }'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; season finale date ; march } ; season } ; 4 }', 'tointer': 'the season record of this unqiue row is 4 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; season finale date ; march } } ; eq { hop { filter_eq { all_rows ; season finale date ; march } ; season } ; 4 } } = true', 'tointer': 'select the rows whose season finale date record fuzzily matches to march . there is only one such row in the table . the season record of this unqiue row is 4 .'} | and { only { filter_eq { all_rows ; season finale date ; march } } ; eq { hop { filter_eq { all_rows ; season finale date ; march } ; season } ; 4 } } = true | select the rows whose season finale date record fuzzily matches to march . there is only one such row in the table . the season record of this unqiue row is 4 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'season finale date_7': 7, 'march_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '4_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'season finale date_7': 'season finale date', 'march_8': 'march', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '4_10': '4'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'season finale date_7': [0], 'march_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '4_10': [3]} | ['season', 'season premiere date', 'season finale date', 'winner', '1st runner up', '2nd runner up'] | [['1', '8 september 2006', '4 november 2006', 'mona singh', 'shweta salve', 'mahesh manjrekar'], ['2', '28 september 2007', '15 december 2007', 'prachi desai', 'sandhya mridul', 'jay bhanushali'], ['3', '27 february 2009', '31 may 2009', 'baichung bhutia', 'gauhar khan', 'karan singh grover'], ['4', '12 december 2010', '8 march 2011', 'meiyang chang', 'sushant singh rajput', 'yana gupta'], ['5', '16 june 2012', '30 september 2012', 'gurmeet choudhary', 'rashmi desai', 'rithvik dhanjani']] |
grand slam ( tennis ) | https://en.wikipedia.org/wiki/Grand_Slam_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-197638-6.html.csv | count | only two players won the grand slam under the age of 25 . | {'scope': 'all', 'criterion': 'less_than', 'value': '25', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'age', '25'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose age record is less than 25 .', 'tostr': 'filter_less { all_rows ; age ; 25 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; age ; 25 } }', 'tointer': 'select the rows whose age record is less than 25 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; age ; 25 } } ; 2 } = true', 'tointer': 'select the rows whose age record is less than 25 . the number of such rows is 2 .'} | eq { count { filter_less { all_rows ; age ; 25 } } ; 2 } = true | select the rows whose age record is less than 25 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'age_5': 5, '25_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'age_5': 'age', '25_6': '25', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'age_5': [0], '25_6': [0], '2_7': [2]} | ['', 'player', 'age', 'australian open', 'french open', 'wimbledon', 'us open'] | [['1', 'fred perry', '26', '1934', '1935', '1934', '1933'], ['2', 'don budge', '23', '1938', '1938', '1937', '1937'], ['3', 'rod laver', '24', '1960', '1962', '1961', '1962'], ['4', 'roy emerson', '27', '1961', '1963', '1964', '1961'], ['5', 'andre agassi', '29', '1995', '1999', '1992', '1994'], ['6', 'roger federer', '27', '2004', '2009', '2003', '2004']] |
con todo | https://en.wikipedia.org/wiki/Con_Todo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25614153-1.html.csv | majority | most of the songs on con todo are at least four minutes long . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '4:00', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'duration', '4:00'], 'result': True, 'ind': 0, 'tointer': 'for the duration records of all rows , most of them are greater than 4:00 .', 'tostr': 'most_greater { all_rows ; duration ; 4:00 } = true'} | most_greater { all_rows ; duration ; 4:00 } = true | for the duration records of all rows , most of them are greater than 4:00 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'duration_3': 3, '4:00_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'duration_3': 'duration', '4:00_4': '4:00'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'duration_3': [0], '4:00_4': [0]} | ['', 'song', 'english translation', 'original album', 'composer', 'worship leader', 'supporting vocal', 'duration'] | [['1', 'para exaltarte', 'your name high', 'this is our god', 'joel houston', 'joel houston', 'none', '4:02'], ['2', 'correré', 'run', 'this is our god', 'joel houston', 'toni romero', 'none', '3:22'], ['3', 'hosanna', 'hosanna', 'saviour king', 'brooke fraser', 'darlene zschech', 'none', '6:08'], ['4', 'desde mi interior', 'from the inside out', 'unidos permanecemos', 'joel houston', 'jad gillies', 'none', '6:13'], ['5', 'canción del desierto', 'desert song', 'this is our god', 'brooke fraser', 'annie garratt', 'none', '4:16'], ['6', 'en la cruz', 'the cross', 'mighty to save', 'darlene zschech & reuben morgan', 'darlene zschech', 'none', '6:20'], ['7', 'rey salvador', 'saviour king', 'saviour king', 'marty sampson & mia fields', 'dave ware', 'none', '8:02'], ['8', 'poderoso para salvar', 'mighty to save', 'mighty to save', 'reuben morgan & ben fielding', 'reuben morgan', 'darlene zschech', '5:34'], ['9', 'soy libre', 'break free', 'saviour king', 'joel houston , matt crocker & scott ligertwood', 'matt crocker', 'none', '3:59'], ['10', 'poderoso', 'stronger', 'this is our god', 'reuben morgan & ben fielding', 'jad gillies', 'darlene zschech', '4:37'], ['11', 'sólo cristo', 'none but jesus', 'unidos permanecemos', 'brooke fraser', 'brooke fraser', 'none', '7:07'], ['12', 'es nuestro dios', 'this is our god', 'this is our god', 'reuben morgan', 'reuben morgan & darlene zschech', 'none', '6:10'], ['13', 'eres mi fortaleza', 'you are my strength', 'saviour king', 'reuben morgan', 'reuben morgan', 'none', '4:53']] |
united states house of representatives elections , 1958 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1958 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341930-18.html.csv | unique | hale boggs was the only incumbent from louisiana in the 1958 united states house of representatives elections that was not unopposed . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '2', 'criterion': 'not_equal', 'value': 'unopposed', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record does not match to unopposed .', 'tostr': 'filter_not_eq { all_rows ; candidates ; unopposed }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; candidates ; unopposed } }', 'tointer': 'select the rows whose candidates record does not match to unopposed . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record does not match to unopposed .', 'tostr': 'filter_not_eq { all_rows ; candidates ; unopposed }'}, 'incumbent'], 'result': 'hale boggs', 'ind': 2, 'tostr': 'hop { filter_not_eq { all_rows ; candidates ; unopposed } ; incumbent }'}, 'hale boggs'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_not_eq { all_rows ; candidates ; unopposed } ; incumbent } ; hale boggs }', 'tointer': 'the incumbent record of this unqiue row is hale boggs .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_not_eq { all_rows ; candidates ; unopposed } } ; eq { hop { filter_not_eq { all_rows ; candidates ; unopposed } ; incumbent } ; hale boggs } } = true', 'tointer': 'select the rows whose candidates record does not match to unopposed . there is only one such row in the table . the incumbent record of this unqiue row is hale boggs .'} | and { only { filter_not_eq { all_rows ; candidates ; unopposed } } ; eq { hop { filter_not_eq { all_rows ; candidates ; unopposed } ; incumbent } ; hale boggs } } = true | select the rows whose candidates record does not match to unopposed . there is only one such row in the table . the incumbent record of this unqiue row is hale boggs . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'candidates_7': 7, 'unopposed_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'hale boggs_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_6': 'all_rows', 'candidates_7': 'candidates', 'unopposed_8': 'unopposed', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'hale boggs_10': 'hale boggs'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'candidates_7': [0], 'unopposed_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'hale boggs_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 2', 'hale boggs', 'democratic', '1946', 're - elected', 'hale boggs ( d ) 91.8 % john patrick conway ( r ) 8.2 %'], ['louisiana 3', 'edwin e willis', 'democratic', '1948', 're - elected', 'edwin e willis ( d ) unopposed'], ['louisiana 4', 'overton brooks', 'democratic', '1936', 're - elected', 'overton brooks ( d ) unopposed'], ['louisiana 5', 'otto passman', 'democratic', '1946', 're - elected', 'otto passman ( d ) unopposed'], ['louisiana 6', 'james h morrison', 'democratic', '1942', 're - elected', 'james h morrison ( d ) unopposed'], ['louisiana 7', 't ashton thompson', 'democratic', '1952', 're - elected', 't ashton thompson ( d ) unopposed']] |
list of street railways in canada | https://en.wikipedia.org/wiki/List_of_street_railways_in_Canada | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16927321-1.html.csv | count | two of the railways in canada run on petrol or gasoline . | {'scope': 'all', 'criterion': 'equal', 'value': 'petrol', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'traction type', 'petrol'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose traction type record fuzzily matches to petrol .', 'tostr': 'filter_eq { all_rows ; traction type ; petrol }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; traction type ; petrol } }', 'tointer': 'select the rows whose traction type record fuzzily matches to petrol . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; traction type ; petrol } } ; 2 } = true', 'tointer': 'select the rows whose traction type record fuzzily matches to petrol . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; traction type ; petrol } } ; 2 } = true | select the rows whose traction type record fuzzily matches to petrol . 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, 'traction type_5': 5, 'petrol_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', 'traction type_5': 'traction type', 'petrol_6': 'petrol', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'traction type_5': [0], 'petrol_6': [0], '2_7': [2]} | ['name of system', 'location', 'traction type', 'date ( from )', 'date ( to )'] | [['calgary municipal railway', 'calgary', 'electric', '5 jul 1909 25 may 1981', '29 dec 1950 -'], ['edmonton radial railway', 'edmonton', 'electric', '30 oct 1908 22 apr 1978', '1 sep 1951 -'], ['edmonton radial railway', 'edmonton', 'petrol ( gasoline )', '30 sep 1913', '1 apr 1914'], ['lake louise tramway', 'lake louise', 'petrol ( gasoline )', '1912', '1930'], ['lethbridge municipal railway', 'lethbridge', 'electric', 'sep 1912', '8 sep 1947']] |
1980 san francisco 49ers season | https://en.wikipedia.org/wiki/1980_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18680817-1.html.csv | comparative | the san francisco 49ers had a game against the dallas cowboys earlier than green bay packers . | {'row_1': '6', 'row_2': '10', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'dallas cowboys'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to dallas cowboys .', 'tostr': 'filter_eq { all_rows ; opponent ; dallas cowboys }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to dallas cowboys . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'green bay packers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers .', 'tostr': 'filter_eq { all_rows ; opponent ; green bay packers }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; green bay packers } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; date } ; hop { filter_eq { all_rows ; opponent ; green bay packers } ; date } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to dallas cowboys . take the date record of this row . select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; date } ; hop { filter_eq { all_rows ; opponent ; green bay packers } ; date } } = true | select the rows whose opponent record fuzzily matches to dallas cowboys . take the date record of this row . select the rows whose opponent record fuzzily matches to green bay packers . 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, 'opponent_7': 7, 'dallas cowboys_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'green bay packers_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', 'opponent_7': 'opponent', 'dallas cowboys_8': 'dallas cowboys', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'green bay packers_12': 'green bay packers', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'dallas cowboys_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'green bay packers_12': [1], 'date_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 7 , 1980', 'new orleans saints', 'w 26 - 23', '58621'], ['2', 'september 14 , 1980', 'st louis cardinals', 'w 24 - 21', '49999'], ['3', 'september 21 , 1980', 'new york jets', 'w 37 - 27', '50608'], ['4', 'september 28 , 1980', 'atlanta falcons', 'l 20 - 17', '56518'], ['5', 'october 5 , 1980', 'los angeles rams', 'l 48 - 26', '62188'], ['6', 'october 12 , 1980', 'dallas cowboys', 'l 59 - 14', '63399'], ['7', 'october 19 , 1980', 'los angeles rams', 'l 31 - 17', '55360'], ['8', 'october 26 , 1980', 'tampa bay buccaneers', 'l 24 - 23', '51925'], ['9', 'november 2 , 1980', 'detroit lions', 'l 17 - 13', '78845'], ['10', 'november 9 , 1980', 'green bay packers', 'l 23 - 16', '54475'], ['11', 'november 16 , 1980', 'miami dolphins', 'l 17 - 13', '45135'], ['12', 'november 23 , 1980', 'new york giants', 'w 12 - 0', '38574'], ['13', 'november 30 , 1980', 'new england patriots', 'w 21 - 17', '45254'], ['14', 'december 7 , 1980', 'new orleans saints', 'w 38 - 35', '37949'], ['15', 'december 14 , 1980', 'atlanta falcons', 'l 35 - 10', '55767'], ['16', 'december 21 , 1980', 'buffalo bills', 'l 18 - 13', '37476']] |
2000 ansett australia cup | https://en.wikipedia.org/wiki/2000_Ansett_Australia_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16388398-3.html.csv | unique | only one game of the 2000 ansett australia cup was held on a monday . | {'scope': 'all', 'row': '6', 'col': '7', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'monday', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'monday'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to monday .', 'tostr': 'filter_eq { all_rows ; date ; monday }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; monday } } = true', 'tointer': 'select the rows whose date record fuzzily matches to monday . there is only one such row in the table .'} | only { filter_eq { all_rows ; date ; monday } } = true | select the rows whose date record fuzzily matches to monday . 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, 'date_4': 4, 'monday_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'monday_5': 'monday'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'monday_5': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date'] | [['adelaide', '17.5 ( 107 )', 'melbourne', '19.11 ( 125 )', 'football park', '12239', 'sunday , 30 january'], ['geelong', '10.14 ( 74 )', 'st kilda', '11.12 ( 78 )', 'waverley park', '7394', 'sunday , 30 january'], ['st kilda', '9.12 ( 66 )', 'melbourne', '13.14 ( 92 )', 'waverley park', '10533', 'saturday , 5 february'], ['adelaide', '19.10 ( 124 )', 'geelong', '15.12 ( 102 )', 'football park', '11326', 'sunday , 6 february'], ['adelaide', '14.11 ( 95 )', 'st kilda', '15.12 ( 102 )', 'football park', '13086', 'sunday , 13 february'], ['geelong', '17.12 ( 114 )', 'melbourne', '11.16 ( 82 )', 'waverley park', '4952', 'monday , 14 february']] |
list of teachers ( uk tv series ) episodes | https://en.wikipedia.org/wiki/List_of_Teachers_%28UK_TV_series%29_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18335117-4.html.csv | count | brian kelly directed three of the episodes of teachers in 2003 . | {'scope': 'all', 'criterion': 'equal', 'value': 'brian kelly', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'brian kelly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to brian kelly .', 'tostr': 'filter_eq { all_rows ; director ; brian kelly }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; director ; brian kelly } }', 'tointer': 'select the rows whose director record fuzzily matches to brian kelly . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; director ; brian kelly } } ; 3 } = true', 'tointer': 'select the rows whose director record fuzzily matches to brian kelly . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; director ; brian kelly } } ; 3 } = true | select the rows whose director record fuzzily matches to brian kelly . 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, 'director_5': 5, 'brian kelly_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', 'director_5': 'director', 'brian kelly_6': 'brian kelly', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'director_5': [0], 'brian kelly_6': [0], '3_7': [2]} | ['no overall', 'no in series', 'title', 'director', 'writer', 'original air date', 'production code'] | [['19', '1', 'episode 1', 'brian kelly', 'ed roe', '6 august 2003', '301'], ['20', '2', 'episode 2', 'brian kelly', 'richard stoneman', '13 august 2003', '302'], ['21', '3', 'episode 3', 'brian kelly', 'andrew rattenburry', '20 august 2003', '303'], ['22', '4', 'episode 4', 'otto bathurst', 'richard stoneman', '27 august 2003', '304'], ['23', '5', 'episode 5', 'otto bathurst', 'charlie martin', '3 september 2003', '305'], ['24', '6', 'episode 6', 'otto bathurst', 'richard stoneman', '10 september 2003', '306'], ['25', '7', 'episode 7', 'jonathan fox bassett', 'ed roe', '17 september 2003', '307'], ['26', '8', 'episode 8', 'jonathan fox bassett', 'tony basgallop', '23 september 2003', '308'], ['27', '9', 'episode 9', 'jonathan fox bassett', 'ed roe', '30 september 2003', '309'], ['28', '10', 'episode 10', 'susanna white', 'andrew rattenbury', '7 october 2003', '310'], ['29', '11', 'episode 11', 'susanna white', 'jack lothian', '13 october 2003', '311'], ['30', '12', 'episode 12', 'andrew lincoln', 'richard stoneman', '20 october 2003', '312']] |
list of natural gas pipelines in western australia | https://en.wikipedia.org/wiki/List_of_natural_gas_pipelines_in_Western_Australia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17918238-1.html.csv | superlative | the dampier to bunbury natural gas pipeline is the longest pipeline of those listed . | {'scope': 'all', 'col_superlative': '3', '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', 'length'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; length }'}, 'name ( year commissioned )'], 'result': 'dampier to bunbury natural gas pipeline ( 1984 )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; length } ; name ( year commissioned ) }'}, 'dampier to bunbury natural gas pipeline ( 1984 )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; length } ; name ( year commissioned ) } ; dampier to bunbury natural gas pipeline ( 1984 ) } = true', 'tointer': 'select the row whose length record of all rows is maximum . the name ( year commissioned ) record of this row is dampier to bunbury natural gas pipeline ( 1984 ) .'} | eq { hop { argmax { all_rows ; length } ; name ( year commissioned ) } ; dampier to bunbury natural gas pipeline ( 1984 ) } = true | select the row whose length record of all rows is maximum . the name ( year commissioned ) record of this row is dampier to bunbury natural gas pipeline ( 1984 ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, 'name (year commissioned)_6': 6, 'dampier to bunbury natural gas pipeline (1984)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'length_5': 'length', 'name (year commissioned)_6': 'name ( year commissioned )', 'dampier to bunbury natural gas pipeline (1984)_7': 'dampier to bunbury natural gas pipeline ( 1984 )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], 'name (year commissioned)_6': [1], 'dampier to bunbury natural gas pipeline (1984)_7': [2]} | ['name ( year commissioned )', 'owner / operator', 'length', 'maximum diameter', 'from / to', 'licence number'] | [['dampier to bunbury natural gas pipeline ( 1984 )', 'dampier bunbury pipeline', '1530 km', '660 mm', 'dampier to bunbury', 'pl 40'], ['goldfields gas transmission pipeline ( 1996 )', 'ggt joint venture ( apa group & others )', '1426 km', '400 mm', 'near compressor station 1 to kalgoorlie', 'pl 24'], ['parmelia pipeline ( 1971 )', 'apa group', '416 km', '356 mm', 'dongara to pinjarra', 'pl 1'], ['pilbara energy pipeline ( 1996 )', 'epic energy', '215 km', '450 mm', 'karratha to port hedland', 'pl 22'], ['mid west gas pipeline ( 1999 )', 'apa group and western power', '352 km', '219 mm', 'geraldton to windimurra', 'pl 43'], ['kambalda esperance pipeline ( 2003 )', 'esperance pipeline co', '340 km', '150 mm', 'kambalda to esperance', 'pl 59'], ['telfer pipeline ( 2003 )', 'apa group & eii', '443 km', '250 mm', 'port hedland to telfer', 'pl 60']] |
2002 fivb volleyball world league | https://en.wikipedia.org/wiki/2002_FIVB_Volleyball_World_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15945725-13.html.csv | majority | most matches during the 2002 volleyball world league took 17 minutes and 30 seconds . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '17:30', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'time', '17:30'], 'result': True, 'ind': 0, 'tointer': 'for the time records of all rows , most of them fuzzily match to 17:30 .', 'tostr': 'most_eq { all_rows ; time ; 17:30 } = true'} | most_eq { all_rows ; time ; 17:30 } = true | for the time records of all rows , most of them fuzzily match to 17:30 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'time_3': 3, '17:30_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'time_3': 'time', '17:30_4': '17:30'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'time_3': [0], '17:30_4': [0]} | ['date', 'time', 'score', 'set 1', 'set 2', 'set 3', 'total', 'report'] | [['13 aug', '17:30', '3 - 0', '25 - 14', '25 - 23', '25 - 21', '75 - 58', 'p2'], ['13 aug', '20:02', '3 - 0', '25 - 20', '25 - 22', '25 - 13', '75 - 55', 'p2'], ['14 aug', '17:30', '3 - 1', '22 - 25', '25 - 19', '25 - 15', '97 - 74', 'p2'], ['14 aug', '20:00', '3 - 0', '25 - 19', '25 - 20', '25 - 17', '75 - 56', 'p2'], ['15 aug', '17:30', '2 - 3', '25 - 22', '23 - 25', '18 - 25', '106 - 111', 'p2'], ['15 aug', '20:00', '0 - 3', '26 - 28', '23 - 25', '18 - 25', '67 - 78', 'p2']] |
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 | majority | the most method used by elena reid was tko ( punches ) against other opponents . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'tko ( punches )', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'method', 'tko ( punches )'], 'result': True, 'ind': 0, 'tointer': 'for the method records of all rows , most of them fuzzily match to tko ( punches ) .', 'tostr': 'most_eq { all_rows ; method ; tko ( punches ) } = true'} | most_eq { all_rows ; method ; tko ( punches ) } = true | for the method records of all rows , most of them fuzzily match to tko ( punches ) . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'method_3': 3, 'tko (punches)_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'method_3': 'method', 'tko (punches)_4': 'tko ( punches )'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'method_3': [0], 'tko (punches)_4': [0]} | ['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']] |
black swan - class sloop | https://en.wikipedia.org/wiki/Black_Swan-class_sloop | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1220125-3.html.csv | count | 2 sloops in the black swan - class sloop were launched in november 1942 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'november 1942', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'launched', 'november 1942'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose launched record fuzzily matches to november 1942 .', 'tostr': 'filter_eq { all_rows ; launched ; november 1942 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; launched ; november 1942 } }', 'tointer': 'select the rows whose launched record fuzzily matches to november 1942 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; launched ; november 1942 } } ; 2 } = true', 'tointer': 'select the rows whose launched record fuzzily matches to november 1942 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; launched ; november 1942 } } ; 2 } = true | select the rows whose launched record fuzzily matches to november 1942 . 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, 'launched_5': 5, 'november 1942_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', 'launched_5': 'launched', 'november 1942_6': 'november 1942', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'launched_5': [0], 'november 1942_6': [0], '2_7': [2]} | ['name', 'pennant', 'builder', 'laid down', 'launched', 'commissioned'] | [['chanticleer', 'u05', 'denny , dunbarton', '6 june 1941', '24 september 1942', '29 march 1943'], ['crane', 'u23', 'denny , dunbarton', '13 june 1941', '9 november 1942', '10 may 1943'], ['cygnet', 'u38', 'cammell laird , birkenhead', '30 august 1941', '28 july 1942', '1 december 1942'], ['kite', 'u87', 'cammell laird , birkenhead', '25 september 1941', '13 october 1942', '1 march 1943'], ['lapwing', 'u62', 'scotts , greenock', '17 december 1941', '16 july 1943', '21 march 1944'], ['lark', 'u11', 'scotts , greenock', '5 may 1942', '28 august 1943', '10 april 1944'], ['magpie', 'u82', 'thornycroft , woolston', '30 december 1941', '24 march 1943', '30 august 1943'], ['peacock', 'u96', 'thornycroft , woolston', '29 november 1942', '11 december 1943', '10 may 1944'], ['pheasant', 'u49', 'yarrow , scotstoun', '17 march 1942', '21 december 1942', '12 may 1943'], ['redpole', 'u69', 'yarrow , scotstoun', '18 may 1942', '25 february 1943', '24 june 1943'], ['snipe', 'u20', 'denny , dunbarton', '21 september 1944', '20 december 1945', '9 september 1946'], ['sparrow', 'u71', 'denny , dunbarton', '30 october 1944', '18 february 1946', '16 december 1946'], ['starling', 'u66', 'fairfield , govan', '21 october 1941', '14 october 1942', '1 april 1943'], ['woodcock', 'u90', 'fairfield , govan', '21 october 1941', '26 november 1942', '29 may 1943']] |
united states house of representatives elections , 1934 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1934 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342331-5.html.csv | count | for the united states house of representatives election in 1934 , for those that were re-elected , three were first elected in the 1930s . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '193', 'result': '3', 'col': '4', 'subset': {'col': '5', 'criterion': 'equal', 'value': 're-elected'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; re-elected }', 'tointer': 'select the rows whose result record fuzzily matches to re-elected .'}, 'first elected', '193'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose result record fuzzily matches to re-elected . among these rows , select the rows whose first elected record fuzzily matches to 193 .', 'tostr': 'filter_eq { filter_eq { all_rows ; result ; re-elected } ; first elected ; 193 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; result ; re-elected } ; first elected ; 193 } }', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . among these rows , select the rows whose first elected record fuzzily matches to 193 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; result ; re-elected } ; first elected ; 193 } } ; 3 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . among these rows , select the rows whose first elected record fuzzily matches to 193 . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; result ; re-elected } ; first elected ; 193 } } ; 3 } = true | select the rows whose result record fuzzily matches to re-elected . among these rows , select the rows whose first elected record fuzzily matches to 193 . 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, 'result_6': 6, 're-elected_7': 7, 'first elected_8': 8, '193_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', 'result_6': 'result', 're-elected_7': 're-elected', 'first elected_8': 'first elected', '193_9': '193', '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], 'result_6': [0], 're-elected_7': [0], 'first elected_8': [1], '193_9': [1], '3_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'william j driver', 'democratic', '1920', 're - elected', 'william j driver ( d ) unopposed'], ['arkansas 2', 'john e miller', 'democratic', '1930', 're - elected', 'john e miller ( d ) unopposed'], ['arkansas 3', 'claude fuller', 'democratic', '1928', 're - elected', 'claude fuller ( d ) 63.1 % pat murphy ( r ) 36.9 %'], ['arkansas 4', 'ben cravens', 'democratic', '1932', 're - elected', 'ben cravens ( d ) unopposed'], ['arkansas 5', 'david d terry', 'democratic', '1933', 're - elected', 'david d terry ( d ) unopposed'], ['arkansas 6', 'david delano glover', 'democratic', '1928', 'lost renomination democratic hold', 'john little mcclellan ( d ) unopposed']] |
1910 in brazilian football | https://en.wikipedia.org/wiki/1910_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15419242-1.html.csv | count | 5 teams participated in the 1910 brazilian football season games . | {'scope': 'all', 'criterion': 'not_equal', 'value': 'n/a', 'result': '6', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'team', 'n/a'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record does not match to n/a .', 'tostr': 'filter_not_eq { all_rows ; team ; n/a }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_not_eq { all_rows ; team ; n/a } }', 'tointer': 'select the rows whose team record does not match to n/a . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_not_eq { all_rows ; team ; n/a } } ; 6 } = true', 'tointer': 'select the rows whose team record does not match to n/a . the number of such rows is 6 .'} | eq { count { filter_not_eq { all_rows ; team ; n/a } } ; 6 } = true | select the rows whose team record does not match to n/a . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'n/a_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'n/a_6': 'n/a', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'n/a_6': [0], '6_7': [2]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'aa das palmeiras', '18', '10', '0', '1', '12', '31'], ['2', 'americano - sp', '16', '10', '0', '2', '18', '7'], ['3', 'são paulo athletic', '11', '10', '1', '4', '26', '- 2'], ['4', 'paulistano', '8', '10', '2', '5', '17', '2'], ['5', 'ypiranga - sp', '4', '10', '2', '7', '32', '- 21'], ['6', 'germnia', '3', '10', '1', '8', '31', '- 17']] |
1980 toronto blue jays season | https://en.wikipedia.org/wiki/1980_Toronto_Blue_Jays_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12207900-2.html.csv | aggregation | the average attendance for games in the 1980 toronto blue jays season was 15720 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '15720', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '15720', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '15720'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 15720 } = true', 'tointer': 'the average of the attendance record of all rows is 15720 .'} | round_eq { avg { all_rows ; attendance } ; 15720 } = true | the average of the attendance record of all rows is 15720 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '15720_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '15720_5': '15720'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '15720_5': [1]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'record'] | [['april 9', 'mariners', '8 - 6', 'lemanczyk ( 0 - 1 )', '22588', '0 - 1'], ['april 11', 'mariners', '10 - 7 ( 11 )', 'dressler ( 0 - 1 )', '6104', '1 - 1'], ['april 12', 'mariners', '3 - 2 ( 10 )', 'garvin ( 0 - 1 )', '6773', '1 - 2'], ['april 13', 'mariners', '5 - 1', 'lemanczyk ( 0 - 2 )', '4567', '1 - 3'], ['april 14', 'brewers', 'postponed ( rain ) rescheduled for july 13', 'postponed ( rain ) rescheduled for july 13', 'postponed ( rain ) rescheduled for july 13', 'postponed ( rain ) rescheduled for july 13'], ['april 16', 'brewers', '11 - 2', 'slaton ( 0 - 1 )', '12688', '2 - 3'], ['april 17', 'brewers', '1 - 0', 'sorensen ( 1 - 1 )', '11235', '3 - 3'], ['april 19', 'indians', '8 - 1', 'clancy ( 0 - 1 )', '61753', '3 - 4'], ['april 20', 'indians', '5 - 3', 'denny ( 0 - 2 )', '11220', '4 - 4'], ['april 21', 'royals', '7 - 1', 'gale ( 0 - 2 )', '21117', '5 - 4'], ['april 22', 'royals', '7 - 2', 'mirabella ( 1 - 1 )', '16993', '5 - 5'], ['april 23', 'royals', '7 - 4', 'mclaughlin ( 0 - 1 )', '18855', '5 - 6'], ['april 25', 'brewers', '5 - 3', 'sorensen ( 1 - 2 )', '9902', '6 - 6'], ['april 26', 'brewers', '4 - 0', 'caldwell ( 2 - 1 )', '11038', '7 - 6'], ['april 27', 'brewers', '8 - 2', 'haas ( 1 - 3 )', '11099', '8 - 6'], ['april 28', 'royals', 'postponed ( rain ) rescheduled for august 8', 'postponed ( rain ) rescheduled for august 8', 'postponed ( rain ) rescheduled for august 8', 'postponed ( rain ) rescheduled for august 8'], ['april 29', 'royals', '3 - 1', 'leonard ( 0 - 3 )', '11553', '9 - 6'], ['april 30', 'royals', '3 - 0', 'jefferson ( 0 - 1 )', '14029', '9 - 7']] |
2006 hamburg sea devils season | https://en.wikipedia.org/wiki/2006_Hamburg_Sea_Devils_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24989925-2.html.csv | count | the 2006 hamburg sea devils played against the amsterdam admirals only once . | {'scope': 'all', 'criterion': 'equal', 'value': 'amsterdam admirals', 'result': '1', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'amsterdam admirals'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to amsterdam admirals .', 'tostr': 'filter_eq { all_rows ; opponent ; amsterdam admirals }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; amsterdam admirals } }', 'tointer': 'select the rows whose opponent record fuzzily matches to amsterdam admirals . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; amsterdam admirals } } ; 1 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to amsterdam admirals . the number of such rows is 1 .'} | eq { count { filter_eq { all_rows ; opponent ; amsterdam admirals } } ; 1 } = true | select the rows whose opponent record fuzzily matches to amsterdam admirals . the number of such rows is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'amsterdam admirals_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'amsterdam admirals_6': 'amsterdam admirals', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'amsterdam admirals_6': [0], '1_7': [2]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , march 18', '6:00 pm', 'cologne centurions', 'l 10 - 14', '0 - 1 - 0', 'aol arena', '15243'], ['2', 'saturday , march 25', '7:00 pm', 'frankfurt galaxy', 'l 14 - 31', '0 - 2 - 0', 'commerzbank - arena', '26713'], ['3', 'saturday , april 1', '6:00 pm', 'berlin thunder', 't 17 - 17 ot', '0 - 2 - 1', 'aol arena', '15837'], ['4', 'saturday , april 8', '7:00 pm', 'rhein fire', 'l 21 - 31', '0 - 3 - 1', 'ltu arena', '18224'], ['5', 'saturday , april 15', '6:00 pm', 'frankfurt galaxy', 'l 13 - 17', '0 - 4 - 1', 'aol arena', '12281'], ['6', 'sunday , april 23', '4:00 pm', 'cologne centurions', 'l 17 - 20', '0 - 5 - 1', 'rheinenergiestadion', '9238'], ['7', 'saturday , april 29', '6:00 pm', 'amsterdam admirals', 'l 17 - 18', '0 - 6 - 1', 'aol arena', '15224'], ['8', 'sunday , may 7', '4:00 pm', 'berlin thunder', 'w 38 - 14', '1 - 6 - 1', 'olympic stadium', '16762'], ['9', 'sunday , may 14', '4:00 pm', 'rhein fire', 'w 13 - 10', '2 - 6 - 1', 'aol arena', '16823']] |
carlos pace | https://en.wikipedia.org/wiki/Carlos_Pace | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219709-1.html.csv | comparative | carlos pace scored more points in the year 1974 than he did in the year 1976 . | {'row_1': '4', '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', 'year', '1974'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1974 .', 'tostr': 'filter_eq { all_rows ; year ; 1974 }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1974 } ; points }', 'tointer': 'select the rows whose year record fuzzily matches to 1974 . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1976'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1976 .', 'tostr': 'filter_eq { all_rows ; year ; 1976 }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1976 } ; points }', 'tointer': 'select the rows whose year record fuzzily matches to 1976 . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1974 } ; points } ; hop { filter_eq { all_rows ; year ; 1976 } ; points } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1974 . take the points record of this row . select the rows whose year record fuzzily matches to 1976 . take the points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 1974 } ; points } ; hop { filter_eq { all_rows ; year ; 1976 } ; points } } = true | select the rows whose year record fuzzily matches to 1974 . take the points record of this row . select the rows whose year record fuzzily matches to 1976 . take the points 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, 'year_7': 7, '1974_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1976_12': 12, 'points_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', 'year_7': 'year', '1974_8': '1974', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1976_12': '1976', 'points_13': 'points'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1974_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1976_12': [1], 'points_13': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1972', 'team williams - motul', 'march 711', 'cosworth v8', '3'], ['1973', 'brooke bond oxo team surtees', 'surtees ts14a', 'cosworth v8', '7'], ['1974', 'team surtees', 'surtees ts16', 'cosworth v8', '11'], ['1974', 'bang & olufsen team surtees', 'surtees ts16', 'cosworth v8', '11'], ['1974', 'goldie hexagon racing', 'brabham bt42', 'cosworth v8', '11'], ['1974', 'motor racing developments', 'brabham bt44', 'cosworth v8', '11'], ['1975', 'martini racing', 'brabham bt44b', 'cosworth v8', '24'], ['1976', 'martini racing', 'brabham bt45', 'alfa romeo flat - 12', '7'], ['1977', 'martini racing', 'brabham bt45', 'alfa romeo flat - 12', '6'], ['1977', 'martini racing', 'brabham bt45b', 'alfa romeo flat - 12', '6']] |
list of ngc objects ( 2001 - 3000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%282001%E2%80%933000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11097664-10.html.csv | majority | the majority of nbc objects are of the spiral galaxy object type . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'spiral galaxy', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'object type', 'spiral galaxy'], 'result': True, 'ind': 0, 'tointer': 'for the object type records of all rows , most of them fuzzily match to spiral galaxy .', 'tostr': 'most_eq { all_rows ; object type ; spiral galaxy } = true'} | most_eq { all_rows ; object type ; spiral galaxy } = true | for the object type records of all rows , most of them fuzzily match to spiral galaxy . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'object type_3': 3, 'spiral galaxy_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'object type_3': 'object type', 'spiral galaxy_4': 'spiral galaxy'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'object type_3': [0], 'spiral galaxy_4': [0]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )'] | [['2903', 'spiral galaxy', 'leo', '09h32 m09 .7 s', 'degree30 ′ 03 ″'], ['2915', 'irregular galaxy', 'chamaeleon', '09h26 m11 .5 s', 'degree37 ′ 35 ″'], ['2935', 'spiral galaxy', 'hydra', '09h36 m44 .6 s', 'degree07 ′ 41 ″'], ['2964', 'spiral galaxy', 'leo', '09h42 m54 .2 s', 'degree50 ′ 49 ″'], ['2968', 'irregular galaxy', 'leo', '09h43 m12 .1 s', 'degree55 ′ 42 ″'], ['2972', 'open cluster', 'vela', '09h40 m28 .5 s', 'degree20 ′ 10 ″'], ['2976', 'spiral galaxy', 'ursa major', '09h47 m15 .5 s', 'degree55 ′ 03 ″'], ['2997', 'spiral galaxy', 'antlia', '09h45 m38 .7 s', 'degree11 ′ 25 ″'], ['2998', 'spiral galaxy', 'ursa major', '09h48 m43 .6 s', 'degree04 ′ 51 ″'], ['2999', 'open cluster', 'vela', '09h40 m28 .5 s', 'degree20 ′ 10 ″'], ['3000', 'double star', 'ursa major', '09h49 m', 'degree08 ′']] |
2004 molson indy montreal | https://en.wikipedia.org/wiki/2004_Molson_Indy_Montreal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16838759-2.html.csv | unique | in the 2004 molson indy montreal , the only driver on the walker racing team was mario haberfeld . | {'scope': 'all', 'row': '13', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'walker racing', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'walker racing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to walker racing .', 'tostr': 'filter_eq { all_rows ; team ; walker racing }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; team ; walker racing } }', 'tointer': 'select the rows whose team record fuzzily matches to walker racing . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'walker racing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to walker racing .', 'tostr': 'filter_eq { all_rows ; team ; walker racing }'}, 'driver'], 'result': 'mario haberfeld', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; walker racing } ; driver }'}, 'mario haberfeld'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; walker racing } ; driver } ; mario haberfeld }', 'tointer': 'the driver record of this unqiue row is mario haberfeld .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; team ; walker racing } } ; eq { hop { filter_eq { all_rows ; team ; walker racing } ; driver } ; mario haberfeld } } = true', 'tointer': 'select the rows whose team record fuzzily matches to walker racing . there is only one such row in the table . the driver record of this unqiue row is mario haberfeld .'} | and { only { filter_eq { all_rows ; team ; walker racing } } ; eq { hop { filter_eq { all_rows ; team ; walker racing } ; driver } ; mario haberfeld } } = true | select the rows whose team record fuzzily matches to walker racing . there is only one such row in the table . the driver record of this unqiue row is mario haberfeld . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'walker racing_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'mario haberfeld_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'walker racing_8': 'walker racing', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'mario haberfeld_10': 'mario haberfeld'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'team_7': [0], 'walker racing_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'mario haberfeld_10': [3]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['bruno junqueira', 'newman / haas racing', '69', '1:39:12.432', '4', '32'], ['patrick carpentier', 'forsythe racing', '69', '+ 6.382 secs', '6', '27'], ['mario domínguez', 'herdez competition', '69', '+ 11.142 secs', '3', '26'], ['paul tracy', 'forsythe racing', '69', '+ 16.874 secs', '5', '23'], ['a j allmendinger', 'rusport', '69', '+ 17.561 secs', '2', '22'], ['michel jourdain , jr', 'rusport', '69', '+ 32.256 secs', '12', '20'], ['alex tagliani', 'rocketsports racing', '69', '+ 32.300 secs', '7', '17'], ['jimmy vasser', 'pkv racing', '69', '+ 34.097 secs', '11', '15'], ['oriol servià', 'dale coyne racing', '69', '+ 42.654 secs', '10', '13'], ['roberto gonzález', 'pkv racing', '69', '+ 1:09.190', '15', '11'], ['rodolfo lavín', 'forsythe racing', '69', '+ 1:18.083', '14', '10'], ['gastón mazzacane', 'dale coyne racing', '67', '+ 2 laps', '18', '9'], ['mario haberfeld', 'walker racing', '65', '+ 4 laps', '17', '8'], ['justin wilson', 'mi - jack conquest racing', '55', 'gearbox', '8', '7'], ['sébastien bourdais', 'newman / haas racing', '42', 'contact', '1', '10'], ['guy smith', 'rocketsports racing', '27', 'engine', '16', '5'], ['nelson philippe', 'mi - jack conquest racing', '21', 'lost wheel', '13', '4'], ['ryan hunter - reay', 'herdez competition', '5', 'contact', '9', '3']] |
list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-2.html.csv | comparative | the urban settlement sremska kamenica had a higher population in 2002 than sremski karlovci had . | {'row_1': '11', 'row_2': '12', 'col': '6', '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', 'urban settlement', 'sremska kamenica'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose urban settlement record fuzzily matches to sremska kamenica .', 'tostr': 'filter_eq { all_rows ; urban settlement ; sremska kamenica }'}, 'population ( 2002 )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; urban settlement ; sremska kamenica } ; population ( 2002 ) }', 'tointer': 'select the rows whose urban settlement record fuzzily matches to sremska kamenica . take the population ( 2002 ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'urban settlement', 'sremski karlovci'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose urban settlement record fuzzily matches to sremski karlovci .', 'tostr': 'filter_eq { all_rows ; urban settlement ; sremski karlovci }'}, 'population ( 2002 )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; urban settlement ; sremski karlovci } ; population ( 2002 ) }', 'tointer': 'select the rows whose urban settlement record fuzzily matches to sremski karlovci . take the population ( 2002 ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; urban settlement ; sremska kamenica } ; population ( 2002 ) } ; hop { filter_eq { all_rows ; urban settlement ; sremski karlovci } ; population ( 2002 ) } } = true', 'tointer': 'select the rows whose urban settlement record fuzzily matches to sremska kamenica . take the population ( 2002 ) record of this row . select the rows whose urban settlement record fuzzily matches to sremski karlovci . take the population ( 2002 ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; urban settlement ; sremska kamenica } ; population ( 2002 ) } ; hop { filter_eq { all_rows ; urban settlement ; sremski karlovci } ; population ( 2002 ) } } = true | select the rows whose urban settlement record fuzzily matches to sremska kamenica . take the population ( 2002 ) record of this row . select the rows whose urban settlement record fuzzily matches to sremski karlovci . take the population ( 2002 ) 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, 'urban settlement_7': 7, 'sremska kamenica_8': 8, 'population (2002)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'urban settlement_11': 11, 'sremski karlovci_12': 12, 'population (2002)_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', 'urban settlement_7': 'urban settlement', 'sremska kamenica_8': 'sremska kamenica', 'population (2002)_9': 'population ( 2002 )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'urban settlement_11': 'urban settlement', 'sremski karlovci_12': 'sremski karlovci', 'population (2002)_13': 'population ( 2002 )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'urban settlement_7': [0], 'sremska kamenica_8': [0], 'population (2002)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'urban settlement_11': [1], 'sremski karlovci_12': [1], 'population (2002)_13': [3]} | ['urban settlement', 'cyrillic name', 'city / municipality', 'district', 'population ( 1991 )', 'population ( 2002 )', 'population ( 2011 )'] | [['bač', 'бач', 'bač', 'south bačka', '6046', '6087', '5399'], ['bačka palanka', 'бачка паланка', 'bačka palanka', 'south bačka', '26780', '29449', '28239'], ['bački jarak', 'бачки јарак', 'temerin', 'south bačka', '5426', '6049', '5687'], ['bački petrovac', 'бачки петровац', 'bački petrovac', 'south bačka', '7236', '6727', '6155'], ['bečej', 'бечеј', 'bečej', 'south bačka', '26634', '25774', '23895'], ['beočin', 'беочин', 'beočin', 'south bačka', '7873', '8058', '7839'], ['futog', 'футог', 'novi sad', 'south bačka', '16048', '18582', '18641'], ['novi sad', 'нови сад', 'novi sad', 'south bačka', '179626', '191405', '250439'], ['petrovaradin', 'петроварадин', 'petrovaradin , novi sad', 'south bačka', '11285', '13973', '14810'], ['srbobran', 'србобран', 'srbobran', 'south bačka', '12798', '13091', '12009'], ['sremska kamenica', 'сремска каменица', 'petrovaradin , novi sad', 'south bačka', '7955', '11205', '12273'], ['sremski karlovci', 'сремски карловци', 'sremski karlovci', 'south bačka', '7534', '8839', '8750'], ['temerin', 'темерин', 'temerin', 'south bačka', '16971', '19216', '19661'], ['titel', 'тител', 'titel', 'south bačka', '6007', '5894', '5294'], ['vrbas', 'врбас', 'vrbas', 'south bačka', '25858', '25907', '24112']] |
margarita ponomaryova | https://en.wikipedia.org/wiki/Margarita_Ponomaryova | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15489384-1.html.csv | aggregation | margarita ponomaryova average time for 400mh in world championship races was 54.54 seconds . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '54.54 seconds', 'subset': {'col': '5', 'criterion': 'equal', 'value': '400 m h'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', '400 m h'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; event ; 400 m h }', 'tointer': 'select the rows whose event record fuzzily matches to 400 m h .'}, 'notes'], 'result': '54.54 seconds', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; event ; 400 m h } ; notes }'}, '54.54 seconds'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; event ; 400 m h } ; notes } ; 54.54 seconds } = true', 'tointer': 'select the rows whose event record fuzzily matches to 400 m h . the average of the notes record of these rows is 54.54 seconds .'} | round_eq { avg { filter_eq { all_rows ; event ; 400 m h } ; notes } ; 54.54 seconds } = true | select the rows whose event record fuzzily matches to 400 m h . the average of the notes record of these rows is 54.54 seconds . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'event_5': 5, '400 m h_6': 6, 'notes_7': 7, '54.54 seconds_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'event_5': 'event', '400 m h_6': '400 m h', 'notes_7': 'notes', '54.54 seconds_8': '54.54 seconds'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'event_5': [0], '400 m h_6': [0], 'notes_7': [1], '54.54 seconds_8': [2]} | ['year', 'competition', 'venue', 'position', 'event', 'notes'] | [['1981', 'european junior championships', 'utrecht , netherlands', '3rd', '400 m h', '57.45'], ['1981', 'european junior championships', 'utrecht , netherlands', '2nd', '4x400 m', '3:31.41'], ['1985', 'world cup', 'canberra , australia', '6th', '400 m h', '56.90'], ['1986', 'european championships', 'stuttgart , germany', '8th', '400 m h', '55.56'], ['1987', 'world championships', 'rome , italy', 'semi - final', '400 m h', '54.86'], ['1989', 'world student games ( universiade )', 'duisburg , germany', '1st', '400 m h', '57.03'], ['1990', 'european championships', 'split , yugoslavia', '5th', '400 m h', '55.22'], ['1991', 'world indoor championships', 'seville , spain', '2nd', '4x400 m', '3:27.95'], ['1991', 'european cup', 'frankfurt , germany', '1st', '400 m h', '54.42'], ['1991', 'world championships', 'tokyo , japan', '8th', '400 m h', '55.27'], ['1992', 'olympic games', 'barcelona , spain', '6th', '400 m h', '54.83'], ['1992', 'world cup', 'havana , cuba', '3rd', '400 m h', '56.46'], ['1993', 'world championships', 'stuttgart , germany', '3rd', '400 m h', '53.48'], ['1993', 'world championships', 'stuttgart , germany', '2nd', '4x400 m', '3:18.38']] |
1990 - 91 atlanta hawks season | https://en.wikipedia.org/wiki/1990%E2%80%9391_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27882867-6.html.csv | superlative | the largest attendance in the 1990-91 atlanta hawks season was on january 11 . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '5', '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', 'location attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; location attendance }'}, 'date'], 'result': 'january 11', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; location attendance } ; date }'}, 'january 11'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; location attendance } ; date } ; january 11 } = true', 'tointer': 'select the row whose location attendance record of all rows is maximum . the date record of this row is january 11 .'} | eq { hop { argmax { all_rows ; location attendance } ; date } ; january 11 } = true | select the row whose location attendance record of all rows is maximum . the date record of this row is january 11 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'date_6': 6, 'january 11_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'date_6': 'date', 'january 11_7': 'january 11'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'date_6': [1], 'january 11_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['29', 'january 2', 'la clippers', 'w 120 - 107', 'd wilkins ( 35 )', 'd wilkins ( 16 )', 'g rivers ( 11 )', 'omni coliseum 8733', '16 - 13'], ['30', 'january 4', 'indiana', 'w 111 - 96', 'd wilkins ( 36 )', 'm malone ( 11 )', 'g rivers , r robinson ( 5 )', 'omni coliseum 10124', '17 - 13'], ['31', 'january 5', 'minnesota', 'w 117 - 112 ( ot )', 'j battle ( 27 )', 'k willis ( 19 )', 'j koncak ( 7 )', 'omni coliseum 10988', '18 - 13'], ['32', 'january 8', 'san antonio', 'w 109 - 98', 'd wilkins ( 40 )', 'k willis ( 9 )', 'g rivers ( 10 )', 'omni coliseum 12608', '19 - 13'], ['33', 'january 11', 'chicago', 'l 96 - 99', 'd wilkins ( 23 )', 'd wilkins ( 12 )', 'j battle ( 7 )', 'chicago stadium 18676', '19 - 14'], ['34', 'january 12', 'new york', 'l 92 - 99', 'd wilkins ( 22 )', 'g rivers ( 8 )', 'g rivers , r robinson ( 6 )', 'madison square garden 17457', '19 - 15'], ['35', 'january 14', 'new york', 'w 96 - 82', 'd wilkins ( 26 )', 'd wilkins ( 16 )', 'j battle , s moncrief ( 4 )', 'omni coliseum 12612', '20 - 15'], ['36', 'january 15', 'indiana', 'w 117 - 106', 'd wilkins ( 28 )', 'd wilkins ( 12 )', 'j battle ( 8 )', 'market square arena 9531', '21 - 15'], ['37', 'january 18', 'chicago', 'w 114 - 105', 'd wilkins ( 34 )', 'm malone ( 12 )', 'g rivers ( 5 )', 'omni coliseum 16390', '22 - 15'], ['38', 'january 19', 'new jersey', 'w 114 - 84', 'k willis ( 24 )', 'k willis ( 17 )', 'a webb ( 6 )', 'omni coliseum 15758', '23 - 15'], ['39', 'january 22', 'miami', 'w 118 - 107', 'k willis ( 29 )', 'k willis ( 10 )', 'g rivers , a webb , d wilkins ( 7 )', 'omni coliseum 10440', '24 - 15'], ['40', 'january 23', 'washington', 'l 99 - 104', 'd wilkins ( 27 )', 'd wilkins ( 13 )', 'g rivers ( 7 )', 'capital centre 9830', '24 - 16'], ['41', 'january 26', 'seattle', 'l 102 - 103', 'd wilkins ( 43 )', 'd wilkins ( 10 )', 'a webb ( 9 )', 'seattle center coliseum 12792', '24 - 17'], ['42', 'january 28', 'portland', 'l 111 - 116', 'd wilkins ( 34 )', 'k willis ( 10 )', 'a webb ( 11 )', 'memorial coliseum 12884', '24 - 18'], ['43', 'january 29', 'utah', 'l 105 - 116', 'd wilkins ( 24 )', 'd wilkins ( 14 )', 'a webb ( 4 )', 'salt palace 12616', '24 - 19']] |
1996 grand national | https://en.wikipedia.org/wiki/1996_Grand_National | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29562161-1.html.csv | aggregation | the horses in the 1996 grand national race were an average age of 10 years old . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '10.06', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'age'], 'result': '10.06', 'ind': 0, 'tostr': 'avg { all_rows ; age }'}, '10.06'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; age } ; 10.06 } = true', 'tointer': 'the average of the age record of all rows is 10.06 .'} | round_eq { avg { all_rows ; age } ; 10.06 } = true | the average of the age record of all rows is 10.06 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'age_4': 4, '10.06_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'age_4': 'age', '10.06_5': '10.06'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'age_4': [0], '10.06_5': [1]} | ['position', 'name', 'jockey', 'age', 'weight ( st , lb )', 'starting price', 'distance'] | [['1st', 'rough quest', 'mick fitzgerald', '10', '10 - 07', '7 / 1 f', 'won by 1 ¼ lengths'], ['2nd', 'encore un peu ( fra )', 'david bridgwater', '9', '10 - 00', '14 / 1', '16 lengths'], ['3rd', 'superior finish', 'richard dunwoody', '10', '10 - 03', '9 / 1', 'short head'], ['4th', 'sir peter lely', 'mr chris bonner', '9', '10 - 00', '33 / 1', '¾ length'], ['5th', 'young hustler', 'chris maude', '9', '11 - 07', '8 / 1', '4 lengths'], ['6th', 'three brownies', 'paul carberry', '9', '10 - 00', '100 / 1', '14 lengths'], ['7th', 'life of a lord', 'charlie swan', '10', '11 - 06', '10 / 1', '13 lengths'], ['8th', 'antonin ( fra )', 'john burke', '8', '10 - 00', '28 / 1', '2 ½ lengths'], ['9th', 'over the deel', 'mr tim mccarthy', '10', '10 - 00', '33 / 1', '15 lengths'], ['10th', 'vicompt de valmont', 'philip hide', '11', '10 - 01', '22 / 1', '4 lengths'], ['11th', 'captain dibble', 'tom jenks', '11', '10 - 00', '40 / 1', '2 lengths'], ['12th', 'riverside boy', 'david walsh', '13', '10 - 00', '66 / 1', '14 lengths'], ['13th', 'over the stream', 'andrew thornton', '10', '10 - 00', '50 / 1', '14 lengths'], ['14th', 'greenhill raffles', 'martin foster', '10', '10 - 00', '100 / 1', '3 lengths'], ['15th', 'into the red', 'richard guest', '12', '10 - 00', '33 / 1', 'a distance'], ['16th', 'lusty light', 'warren marston', '10', '10 - 11', '14 / 1', 'a distance']] |
utah jazz all - time roster | https://en.wikipedia.org/wiki/Utah_Jazz_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11545282-4.html.csv | unique | darryl dawkins is the only player on the utah jazz all - time roster from the maynard evans hs team . | {'scope': 'all', 'row': '3', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'maynard evans hs', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'maynard evans hs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to maynard evans hs .', 'tostr': 'filter_eq { all_rows ; school / club team ; maynard evans hs }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; school / club team ; maynard evans hs } }', 'tointer': 'select the rows whose school / club team record fuzzily matches to maynard evans hs . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'maynard evans hs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to maynard evans hs .', 'tostr': 'filter_eq { all_rows ; school / club team ; maynard evans hs }'}, 'player'], 'result': 'darryl dawkins', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school / club team ; maynard evans hs } ; player }'}, 'darryl dawkins'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; school / club team ; maynard evans hs } ; player } ; darryl dawkins }', 'tointer': 'the player record of this unqiue row is darryl dawkins .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; school / club team ; maynard evans hs } } ; eq { hop { filter_eq { all_rows ; school / club team ; maynard evans hs } ; player } ; darryl dawkins } } = true', 'tointer': 'select the rows whose school / club team record fuzzily matches to maynard evans hs . there is only one such row in the table . the player record of this unqiue row is darryl dawkins .'} | and { only { filter_eq { all_rows ; school / club team ; maynard evans hs } } ; eq { hop { filter_eq { all_rows ; school / club team ; maynard evans hs } ; player } ; darryl dawkins } } = true | select the rows whose school / club team record fuzzily matches to maynard evans hs . there is only one such row in the table . the player record of this unqiue row is darryl dawkins . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / club team_7': 7, 'maynard evans hs_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'darryl dawkins_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / club team_7': 'school / club team', 'maynard evans hs_8': 'maynard evans hs', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'darryl dawkins_10': 'darryl dawkins'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / club team_7': [0], 'maynard evans hs_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'darryl dawkins_10': [3]} | ['player', 'no', 'nationality', 'position', 'years for jazz', 'school / club team'] | [['adrian dantley', '4', 'united states', 'guard - forward', '1979 - 86', 'notre dame'], ['brad davis', '12', 'united states', 'guard', '1979 - 80', 'maryland'], ['darryl dawkins', '45', 'united states', 'center', '1987 - 88', 'maynard evans hs'], ['paul dawkins', '31', 'united states', 'guard', '1979 - 80', 'northern illinois'], ['greg deane', '33', 'united states', 'guard', '1979 - 80', 'utah'], ['james donaldson', '54', 'united states', 'center', '1993 - 95', 'washington state'], ['john drew', '22', 'united states', 'guard - forward', '1982 - 85', 'gardner - webb']] |
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/2-17937080-1.html.csv | majority | all of the records held by barcelona in the spanish football records had them scoring 90 or more points in a year . | {'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '90', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'barcelona'}} | {'func': 'all_greater_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'barcelona'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; club ; barcelona }', 'tointer': 'select the rows whose club record fuzzily matches to barcelona .'}, 'points', '90'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to barcelona . for the points records of these rows , all of them are greater than or equal to 90 .', 'tostr': 'all_greater_eq { filter_eq { all_rows ; club ; barcelona } ; points ; 90 } = true'} | all_greater_eq { filter_eq { all_rows ; club ; barcelona } ; points ; 90 } = true | select the rows whose club record fuzzily matches to barcelona . for the points records of these rows , all of them are greater than or equal to 90 . | 2 | 2 | {'all_greater_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'club_4': 4, 'barcelona_5': 5, 'points_6': 6, '90_7': 7} | {'all_greater_eq_1': 'all_greater_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'club_4': 'club', 'barcelona_5': 'barcelona', 'points_6': 'points', '90_7': '90'} | {'all_greater_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'club_4': [0], 'barcelona_5': [0], 'points_6': [1], '90_7': [1]} | ['rank', 'club', 'season', 'points', 'apps'] | [['1', 'real madrid', '2011 / 12', '100', '38'], ['1', 'barcelona', '2012 / 13', '100', '38'], ['3', 'barcelona', '2009 / 10', '99', '38'], ['4', 'real madrid', '2009 / 10', '96', '38'], ['4', 'barcelona', '2010 / 11', '96', '38'], ['6', 'real madrid', '2010 / 11', '92', '38'], ['7', 'real madrid', '1996 / 97', '92', '42'], ['8', 'barcelona', '2011 / 12', '91', '38'], ['9', 'barcelona', '1996 / 97', '90', '42']] |
corey hill | https://en.wikipedia.org/wiki/Corey_Hill | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11034773-2.html.csv | comparative | corey hill 's fight against ryan thomas lasted a longer amount of time than his fight against stryder fann . | {'row_1': '1', 'row_2': '11', 'col': '7', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'ryan thomas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to ryan thomas .', 'tostr': 'filter_eq { all_rows ; opponent ; ryan thomas }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; ryan thomas } ; time }', 'tointer': 'select the rows whose opponent record fuzzily matches to ryan thomas . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'stryder fann'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to stryder fann .', 'tostr': 'filter_eq { all_rows ; opponent ; stryder fann }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; stryder fann } ; time }', 'tointer': 'select the rows whose opponent record fuzzily matches to stryder fann . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; ryan thomas } ; time } ; hop { filter_eq { all_rows ; opponent ; stryder fann } ; time } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to ryan thomas . take the time record of this row . select the rows whose opponent record fuzzily matches to stryder fann . take the time record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; ryan thomas } ; time } ; hop { filter_eq { all_rows ; opponent ; stryder fann } ; time } } = true | select the rows whose opponent record fuzzily matches to ryan thomas . take the time record of this row . select the rows whose opponent record fuzzily matches to stryder fann . take the time record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'ryan thomas_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'stryder fann_12': 12, 'time_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'ryan thomas_8': 'ryan thomas', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'stryder fann_12': 'stryder fann', 'time_13': 'time'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'ryan thomas_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'stryder fann_12': [1], 'time_13': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '6 - 5', 'ryan thomas', 'submission ( armbar )', 'xfc 21 : night of champions 2', '1', '2:34', 'nashville , tennessee , united states'], ['win', '6 - 4', 'darryl madison', 'submission ( anaconda choke )', 'complete devastation 5', '1', '1:11', 'altoona , pennsylvania , united states'], ['win', '5 - 4', 'charlie rader', 'submission ( brabo choke )', 'xfc 15 : tribute', '1', '3:58', 'tampa , florida , united states'], ['loss', '4 - 4', 'rob mccullough', 'decision ( unanimous )', 'tachi palace fights 6', '3', '5:00', 'lemoore , california , united states'], ['win', '4 - 3', 'kit cope', 'submission ( triangle choke )', 'raging wolf 8 : cage supremacy', '1', '2:30', 'salamanca , new york , united states'], ['loss', '3 - 3', 'mark holst', 'submission ( kimura )', 'xkl : evolution 1', '2', '4:06', 'ypsilanti , michigan , united states'], ['win', '3 - 2', 'jason trzewieczynski', 'decision ( unanimous )', 'raging wolf 6 : mayhem in the mist', '3', '5:00', 'niagara , new york , united states'], ['loss', '2 - 2', 'dale hartt', 'tko ( broken leg )', 'ufc : fight for the troops', '2', '0:20', 'fayetteville , north carolina , united states'], ['loss', '2 - 1', 'justin buchholz', 'submission ( rear naked choke )', 'ufc 86', '2', '3:57', 'las vegas , nevada , united states'], ['win', '2 - 0', 'joe veres', 'tko ( punches )', 'ufc fight night 12', '2', '0:37', 'las vegas , nevada , united states'], ['win', '1 - 0', 'stryder fann', 'tko ( punches )', 'kickdown classic 31', '1', '0:34', 'casper , wyoming , united states']] |
1987 indianapolis colts season | https://en.wikipedia.org/wiki/1987_Indianapolis_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14871429-1.html.csv | ordinal | the indianapolis colts ' match against cincinnati bengals was the earliest game in the 1987 season . | {'row': '1', 'col': '2', 'order': '1', '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', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'opponent'], 'result': 'cincinnati bengals', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; opponent }'}, 'cincinnati bengals'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 1 } ; opponent } ; cincinnati bengals } = true', 'tointer': 'select the row whose date record of all rows is 1st minimum . the opponent record of this row is cincinnati bengals .'} | eq { hop { nth_argmin { all_rows ; date ; 1 } ; opponent } ; cincinnati bengals } = true | select the row whose date record of all rows is 1st minimum . the opponent record of this row is cincinnati bengals . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'opponent_7': 7, 'cincinnati bengals_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', 'date_5': 'date', '1_6': '1', 'opponent_7': 'opponent', 'cincinnati bengals_8': 'cincinnati bengals'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'opponent_7': [1], 'cincinnati bengals_8': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'game site'] | [['1', 'september 13 , 1987', 'cincinnati bengals', 'l 21 - 23', '0 - 1', 'hoosier dome'], ['2', 'september 20 , 1987', 'miami dolphins', 'l 10 - 23', '0 - 2', 'hoosier dome'], ['3', 'september 27 , 1987', 'st louis cardinals', 'canceled', '0 - 2', 'busch memorial stadium'], ['4', 'october 4 , 1987', 'buffalo bills', 'w 47 - 6', '1 - 2', 'rich stadium'], ['5', 'october 11 , 1987', 'new york jets', 'w 6 - 0', '2 - 2', 'hoosier dome'], ['6', 'october 18 , 1987', 'pittsburgh steelers', 'l 7 - 21', '2 - 3', 'three rivers stadium'], ['7', 'october 25 , 1987', 'new england patriots', 'w 30 - 16', '3 - 3', 'hoosier dome'], ['8', 'november 1 , 1987', 'new york jets', 'w 19 - 14', '4 - 3', 'the meadowlands'], ['9', 'november 8 , 1987', 'san diego chargers', 'l 13 - 16', '4 - 4', 'hoosier dome'], ['10', 'november 15 , 1987', 'miami dolphins', 'w 40 - 20', '5 - 4', 'joe robbie stadium'], ['11', 'november 22 , 1987', 'new england patriots', 'l 0 - 24', '5 - 5', 'sullivan stadium'], ['12', 'november 29 , 1987', 'houston oilers', 'w 51 - 27', '6 - 5', 'hoosier dome'], ['13', 'december 6 , 1987', 'cleveland browns', 'w 9 - 7', '7 - 5', 'cleveland stadium'], ['14', 'december 13 , 1987', 'buffalo bills', 'l 3 - 27', '7 - 6', 'hoosier dome'], ['15', 'december 20 , 1987', 'san diego chargers', 'w 20 - 7', '8 - 6', 'jack murphy stadium'], ['16', 'december 27 , 1987', 'tampa bay buccaneers', 'w 24 - 6', '9 - 6', 'hoosier dome']] |
nfl career scoring leaders | https://en.wikipedia.org/wiki/NFL_career_scoring_leaders | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14083821-2.html.csv | count | 5 players are listed as scoring leaders on the nfl career scoring board . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '2', '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': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 5 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 5 .'} | eq { count { filter_all { all_rows ; player } } ; 5 } = true | select the rows whose player record is arbitrary . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '5_6': [2]} | ['rank', 'player', 'position', 'career', 'points'] | [['31', 'jerry rice', 'wide receiver', '1985 - 2004', '1256'], ['47', 'emmitt smith', 'running back', '1990 - 2004', '1052'], ['52', 'ladainian tomlinson', 'running back', '2001 - 2011', '972'], ['59', 'randy moss', 'wide receiver', '1998 - 2012', '950'], ['61t', 'terrell owens', 'wide receiver', '1996 - 2010', '942']] |
advanced television systems committee standards | https://en.wikipedia.org/wiki/Advanced_Television_Systems_Committee_standards | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-272313-1.html.csv | count | of the listed advanced television systems committee standards two use interlaced scanning . | {'scope': 'all', 'criterion': 'equal', 'value': 'interlaced', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'scanning', 'interlaced'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose scanning record fuzzily matches to interlaced .', 'tostr': 'filter_eq { all_rows ; scanning ; interlaced }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; scanning ; interlaced } }', 'tointer': 'select the rows whose scanning record fuzzily matches to interlaced . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; scanning ; interlaced } } ; 2 } = true', 'tointer': 'select the rows whose scanning record fuzzily matches to interlaced . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; scanning ; interlaced } } ; 2 } = true | select the rows whose scanning record fuzzily matches to interlaced . 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, 'scanning_5': 5, 'interlaced_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', 'scanning_5': 'scanning', 'interlaced_6': 'interlaced', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'scanning_5': [0], 'interlaced_6': [0], '2_7': [2]} | ['vertical', 'horizontal', 'aspect ratio', 'pixel aspect ratio', 'scanning', 'frame rate ( hz )'] | [['1080', '1920', '16:9', '1:1', 'progressive', '23.976 24 29.97 30'], ['1080', '1920', '16:9', '1:1', 'interlaced', '29.97 ( 59.94 fields / s ) 30 ( 60 fields / s )'], ['720', '1280', '16:9', '1:1', 'progressive', '23.976 24 29.97 30 59.94 60'], ['480', '704', '4:3 or 16:9', 'smpte 259 m', 'progressive', '23.976 24 29.97 30 59.94 60'], ['480', '704', '4:3 or 16:9', 'smpte 259 m', 'interlaced', '29.97 ( 59.94 fields / s ) 30 ( 60 fields / s )'], ['480', '640', '4:3', '1:1', 'progressive', '23.976 24 29.97 30 59.94 60']] |
1985 pga tour | https://en.wikipedia.org/wiki/1985_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14640372-3.html.csv | superlative | in the 1985 pga tour , jim thorpe played in the most events among the golfers ranked in the top five . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', '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', 'events'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; events }'}, 'player'], 'result': 'jim thorpe', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; events } ; player }'}, 'jim thorpe'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; events } ; player } ; jim thorpe } = true', 'tointer': 'select the row whose events record of all rows is maximum . the player record of this row is jim thorpe .'} | eq { hop { argmax { all_rows ; events } ; player } ; jim thorpe } = true | select the row whose events record of all rows is maximum . the player record of this row is jim thorpe . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'events_5': 5, 'player_6': 6, 'jim thorpe_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'events_5': 'events', 'player_6': 'player', 'jim thorpe_7': 'jim thorpe'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'events_5': [0], 'player_6': [1], 'jim thorpe_7': [2]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'curtis strange', 'united states', '542321', '25', '3'], ['2', 'lanny wadkins', 'united states', '446893', '24', '3'], ['3', 'calvin peete', 'united states', '384489', '22', '2'], ['4', 'jim thorpe', 'united states', '379091', '28', '2'], ['5', 'raymond floyd', 'united states', '378989', '22', '1']] |
1974 vfl season | https://en.wikipedia.org/wiki/1974_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10869646-12.html.csv | aggregation | the average crowd attendance of matches in the 1974 vfl season was 17128 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '17128', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '17128', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '17128'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 17128 } = true', 'tointer': 'the average of the crowd record of all rows is 17128 .'} | round_eq { avg { all_rows ; crowd } ; 17128 } = true | the average of the crowd record of all rows is 17128 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '17128_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '17128_5': '17128'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '17128_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '28.17 ( 185 )', 'south melbourne', '12.7 ( 79 )', 'arden street oval', '9016', '22 june 1974'], ['hawthorn', '19.17 ( 131 )', 'richmond', '15.18 ( 108 )', 'princes park', '15710', '22 june 1974'], ['fitzroy', '13.14 ( 92 )', 'st kilda', '12.15 ( 87 )', 'junction oval', '12519', '22 june 1974'], ['essendon', '13.12 ( 90 )', 'collingwood', '19.9 ( 123 )', 'windy hill', '25867', '22 june 1974'], ['melbourne', '11.13 ( 79 )', 'carlton', '15.18 ( 108 )', 'mcg', '23336', '22 june 1974'], ['geelong', '13.14 ( 92 )', 'footscray', '8.10 ( 58 )', 'vfl park', '16320', '22 june 1974']] |
spain in the eurovision song contest 2009 | https://en.wikipedia.org/wiki/Spain_in_the_Eurovision_Song_Contest_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19763199-4.html.csv | count | four spanish artists progressed to the finals in the 2008 eurovision song contest . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'final', 'result': '4', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'final'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to final .', 'tostr': 'filter_eq { all_rows ; result ; final }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; final } }', 'tointer': 'select the rows whose result record fuzzily matches to final . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; final } } ; 4 } = true', 'tointer': 'select the rows whose result record fuzzily matches to final . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; result ; final } } ; 4 } = true | select the rows whose result record fuzzily matches to final . 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, 'result_5': 5, 'final_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', 'result_5': 'result', 'final_6': 'final', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'final_6': [0], '4_7': [2]} | ['draw', 'artist', 'song', 'jury votes', 'televotes', 'total votes', 'result'] | [['1', 'diqesi', 'subiré', '5', '4', '9', 'out'], ['2', 'roel', 'y ahora dices', '6', '3', '9', 'out'], ['3', 'salva ortega', 'lujuria', '7', '7', '14', 'second chance > final'], ['4', 'soraya', 'la noche es para mí', '12', '12', '24', 'final'], ['5', 'virginia', 'true love', '10', '10', '20', 'final'], ['6', 'calipop', 'burbuja', '2', '2', '4', 'out'], ['7', 'ángeles vela', 'vístete de primavera', '4', '5', '9', 'out'], ['8', 'jorge gonzález', 'si yo vengo a enamorarte', '8', '8', '16', 'final'], ['9', 'electronikboy', 'mon petit oiseau', '1', '1', '2', 'out']] |
matthew riddle | https://en.wikipedia.org/wiki/Matthew_Riddle | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18017829-2.html.csv | majority | the majority of the matches were decided by decision . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'decision', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'method', 'decision'], 'result': True, 'ind': 0, 'tointer': 'for the method records of all rows , most of them fuzzily match to decision .', 'tostr': 'most_eq { all_rows ; method ; decision } = true'} | most_eq { all_rows ; method ; decision } = true | for the method records of all rows , most of them fuzzily match to decision . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'method_3': 3, 'decision_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'method_3': 'method', 'decision_4': 'decision'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'method_3': [0], 'decision_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['nc', '7 - 3 ( 2 )', 'che mills', 'no contest', 'ufc on fuel tv : barao vs mcdonald', '3', '5:00', 'london , england'], ['win', '7 - 3 ( 1 )', 'john maguire', 'decision ( unanimous )', 'ufc 154', '3', '5:00', 'montreal , quebec , canada'], ['nc', '6 - 3 ( 1 )', 'chris clements', 'no contest', 'ufc 149', '3', '2:02', 'calgary , alberta , canada'], ['win', '6 - 3', 'henry martinez', 'decision ( split )', 'ufc 143', '3', '5:00', 'las vegas , nevada , united states'], ['loss', '5 - 3', 'lance benoist', 'decision ( unanimous )', 'ufc fight night : shields vs ellenberger', '3', '5:00', 'new orleans , louisiana , united states'], ['loss', '5 - 2', 'sean pierson', 'decision ( unanimous )', 'ufc 124', '3', '5:00', 'montreal , quebec , canada'], ['win', '5 - 1', 'damarques johnson', 'tko ( punches )', 'ufc live : jones vs matyushenko', '2', '4:29', 'san diego , california , united states'], ['win', '4 - 1', 'greg soto', 'dq ( illegal upkick )', 'ufc 111', '3', '1:30', 'newark , new jersey , united states'], ['loss', '3 - 1', 'nick osipczak', 'tko ( elbows & punches )', 'ufc 105', '3', '3:53', 'manchester , england'], ['win', '3 - 0', 'dan cramer', 'decision ( unanimous )', 'ufc 101', '3', '5:00', 'philadelphia , pennsylvania , united states'], ['win', '2 - 0', 'steve bruno', 'decision ( unanimous )', 'ufc fight night : lauzon vs stephens', '3', '5:00', 'tampa , florida , united states'], ['win', '1 - 0', 'dante rivera', 'decision ( unanimous )', 'the ultimate fighter 7 finale', '3', '5:00', 'las vegas , nevada , united states']] |
kuba giermaziak | https://en.wikipedia.org/wiki/Kuba_Giermaziak | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26473176-1.html.csv | superlative | kuba giermaziak scored the highest points of his career in the 2008 formula renault 2.0 nec series . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '4', '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', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'series'], 'result': 'formula renault 2.0 nec', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; series }'}, 'formula renault 2.0 nec'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; series } ; formula renault 2.0 nec } = true', 'tointer': 'select the row whose points record of all rows is maximum . the series record of this row is formula renault 2.0 nec .'} | eq { hop { argmax { all_rows ; points } ; series } ; formula renault 2.0 nec } = true | select the row whose points record of all rows is maximum . the series record of this row is formula renault 2.0 nec . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'series_6': 6, 'formula renault 2.0 nec_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'series_6': 'series', 'formula renault 2.0 nec_7': 'formula renault 2.0 nec'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'series_6': [1], 'formula renault 2.0 nec_7': [2]} | ['season', 'series', 'team', 'races', 'wins', 'f / laps', 'podiums', 'points', 'position'] | [['2007', 'formula renault 2.0 nec', 'motopark academy', '15', '0', '0', '0', '97', '10th'], ['2007', 'formula renault 2.0 eurocup', 'motopark academy', '2', '0', '0', '0', '0', 'nc'], ['2008', 'formula renault 2.0 eurocup', 'motopark academy', '14', '0', '0', '0', '10', '18th'], ['2008', 'formula renault 2.0 nec', 'motopark academy', '14', '0', '0', '5', '206', '6th'], ['2008', 'portuguese formula renault 2.0 winter series', 'motopark academy', '2', '0', '0', '0', '4', '18th'], ['2009', 'formula renault 2.0 eurocup', 'motopark academy', '8', '0', '0', '1', '32', '9th'], ['2009', 'formula renault 2.0 nec', 'motopark academy', '10', '0', '0', '1', '115', '14th'], ['2009', 'adac gt masters', 'argo racing', '10', '0', '1', '3', '35', '11th'], ['2010', 'porsche supercup', 'verva racing team', '10', '0', '0', '0', '56', '10th'], ['2010', 'adac gt masters', 'abt sportsline', '10', '2', '0', '4', '42', '8th'], ['2011', 'formula 3 euroseries', 'star racing team', '18', '0', '0', '0', '29', '12th']] |
volleyball at the 2006 asian games | https://en.wikipedia.org/wiki/Volleyball_at_the_2006_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17877429-1.html.csv | aggregation | the average number of gold medals won in volleyball at the 2006 asian games was .67 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '.67', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '.67', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '.67'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; .67 } = true', 'tointer': 'the average of the gold record of all rows is .67 .'} | round_eq { avg { all_rows ; gold } ; .67 } = true | the average of the gold record of all rows is .67 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '.67_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '.67_5': '.67'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '.67_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'china ( chn )', '3', '2', '1', '6'], ['2', 'south korea ( kor )', '1', '0', '0', '1'], ['3', 'japan ( jpn )', '0', '2', '0', '2'], ['4', 'chinese taipei ( tpe )', '0', '0', '1', '1'], ['4', 'indonesia ( ina )', '0', '0', '1', '1'], ['4', 'saudi arabia ( ksa )', '0', '0', '1', '1'], ['total', 'total', '4', '4', '4', '12']] |
2008 mls superdraft | https://en.wikipedia.org/wiki/2008_MLS_SuperDraft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15214004-4.html.csv | count | in the 2008 mls superdraft , two players were picked by the colorado rapids . | {'scope': 'all', 'criterion': 'equal', 'value': 'colorado rapids', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mls team', 'colorado rapids'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mls team record fuzzily matches to colorado rapids .', 'tostr': 'filter_eq { all_rows ; mls team ; colorado rapids }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; mls team ; colorado rapids } }', 'tointer': 'select the rows whose mls team record fuzzily matches to colorado rapids . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; mls team ; colorado rapids } } ; 2 } = true', 'tointer': 'select the rows whose mls team record fuzzily matches to colorado rapids . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; mls team ; colorado rapids } } ; 2 } = true | select the rows whose mls team record fuzzily matches to colorado rapids . 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, 'mls team_5': 5, 'COLORADO RAPIDS_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', 'mls team_5': 'mls team', 'COLORADO RAPIDS_6': 'colorado rapids', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'mls team_5': [0], 'COLORADO RAPIDS_6': [0], '2_7': [2]} | ['pick', 'mls team', 'player', 'position', 'affiliation'] | [['43', 'chivas usa', 'keith savage', 'm', 'west florida central florida kraze'], ['44', 'new york red bulls', 'david roth', 'm', 'northwestern chicago fire premier'], ['45', 'fc dallas', 'jamil roberts', 'd', 'santa clara'], ['46', 'los angeles galaxy', 'brandon mcdonald', 'm', 'san francisco san jose frogs'], ['47', 'colorado rapids', 'brian grazier', 'm', 'saint louis'], ['48', 'columbus crew', 'steven lenhart', 'f', 'azusa pacific southern california seahorses'], ['49', 'colorado rapids', 'scott campbell', 'm', 'north carolina'], ['50', 'fc dallas', 'ben nason', 'm', 'virginia tech'], ['51', 'los angeles galaxy', 'matt hatzke', 'd', 'santa clara'], ['52', 'dc united', 'tony schmitz', 'm', 'creighton'], ['53', 'kansas city wizards', 'rauwshan mckenzie', 'd', 'michigan state chicago fire premier'], ['54', 'chicago fire', 'austin washington', 'd', 'gonzaga spokane spiders'], ['55', 'new england revolution', 'spencer wadsworth', 'f', 'duke'], ['56', 'houston dynamo', 'jeremy barlow', 'm', 'virginia']] |
1982 open championship | https://en.wikipedia.org/wiki/1982_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18166348-7.html.csv | aggregation | the total amount of money won by players in the 1982 open championship was 146800 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '146800', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'money'], 'result': '146800', 'ind': 0, 'tostr': 'sum { all_rows ; money }'}, '146800'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; money } ; 146800 } = true', 'tointer': 'the sum of the money record of all rows is 146800 .'} | round_eq { sum { all_rows ; money } ; 146800 } = true | the sum of the money record of all rows is 146800 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'money_4': 4, '146800_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'money_4': 'money', '146800_5': '146800'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'money_4': [0], '146800_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'tom watson', 'united states', '69 + 71 + 74 + 70 = 284', '- 4', '32000'], ['t2', 'peter oosterhuis', 'england', '74 + 67 + 74 + 70 = 285', '- 3', '19300'], ['t2', 'nick price', 'zimbabwe', '69 + 69 + 74 + 73 = 285', '- 3', '19300'], ['t4', 'nick faldo', 'england', '73 + 73 + 71 + 69 = 286', '- 2', '11000'], ['t4', 'masahiro kuramoto', 'japan', '71 + 73 + 71 + 71 = 286', '- 2', '11000'], ['t4', 'tom purtzer', 'united states', '76 + 66 + 75 + 69 = 286', '- 2', '11000'], ['t4', 'des smyth', 'ireland', '70 + 69 + 74 + 73 = 286', '- 2', '11000'], ['t8', 'sandy lyle', 'scotland', '74 + 66 + 73 + 74 = 287', '- 1', '8750'], ['t8', 'fuzzy zoeller', 'united states', '73 + 71 + 73 + 70 = 287', '- 1', '8750'], ['t10', 'bobby clampett', 'united states', '67 + 66 + 78 + 77 = 288', 'e', '7350'], ['t10', 'jack nicklaus', 'united states', '77 + 70 + 72 + 69 = 288', 'e', '7350']] |
1951 world wrestling championships | https://en.wikipedia.org/wiki/1951_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16853558-1.html.csv | count | 6 nations were represented in the 1951 world wrestling championships . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'nation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record is arbitrary .', 'tostr': 'filter_all { all_rows ; nation }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; nation } }', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; nation } } ; 6 } = true', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; nation } } ; 6 } = true | select the rows whose nation record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'nation_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'nation_5': 'nation', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'nation_5': [0], '6_6': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'turkey', '6', '0', '1', '7'], ['2', 'sweden', '2', '1', '3', '6'], ['3', 'finland', '0', '4', '0', '4'], ['4', 'iran', '0', '2', '2', '4'], ['5', 'italy', '0', '1', '1', '2'], ['6', 'west germany', '0', '0', '1', '1'], ['total', 'total', '8', '8', '8', '24']] |
tom lehman | https://en.wikipedia.org/wiki/Tom_Lehman | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1516564-12.html.csv | unique | tom lehman only ever won the open championship one time . | {'scope': 'all', 'row': '3', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'the open championship', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'the open championship'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to the open championship .', 'tostr': 'filter_eq { all_rows ; tournament ; the open championship }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; tournament ; the open championship } }', 'tointer': 'select the rows whose tournament record fuzzily matches to the open championship . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'the open championship'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to the open championship .', 'tostr': 'filter_eq { all_rows ; tournament ; the open championship }'}, 'wins'], 'result': '1', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; the open championship } ; wins }'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; the open championship } ; wins } ; 1 }', 'tointer': 'the wins record of this unqiue row is 1 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; tournament ; the open championship } } ; eq { hop { filter_eq { all_rows ; tournament ; the open championship } ; wins } ; 1 } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to the open championship . there is only one such row in the table . the wins record of this unqiue row is 1 .'} | and { only { filter_eq { all_rows ; tournament ; the open championship } } ; eq { hop { filter_eq { all_rows ; tournament ; the open championship } ; wins } ; 1 } } = true | select the rows whose tournament record fuzzily matches to the open championship . there is only one such row in the table . the wins record of this unqiue row is 1 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'the open championship_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'wins_9': 9, '1_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'the open championship_8': 'the open championship', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'wins_9': 'wins', '1_10': '1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'tournament_7': [0], 'the open championship_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'wins_9': [2], '1_10': [3]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '2', '3', '7', '13', '9'], ['us open', '0', '4', '5', '8', '18', '12'], ['the open championship', '1', '2', '2', '7', '20', '13'], ['pga championship', '0', '0', '1', '2', '17', '10'], ['totals', '1', '8', '11', '24', '68', '44']] |
1999 belarusian premier league | https://en.wikipedia.org/wiki/1999_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14746581-1.html.csv | superlative | the dinamo , minsk stadium has the highest seating capacity of venues in the 1999 belarusian premier league . | {'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', '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 1998'] | [['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '1'], ['bate', 'borisov', 'city stadium , borisov', '5500', '2'], ['belshina', 'bobruisk', 'spartak , bobruisk', '3550', '3'], ['lokomotiv - 96', 'vitebsk', 'central , vitebsk', '8300', '4'], ['gomel', 'gomel', 'central , gomel', '11800', '5'], ['slavia', 'mozyr', 'yunost , mozyr', '5500', '6'], ['torpedo - maz', 'minsk', 'torpedo , minsk', '5200', '7'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '8'], ['dinamo brest', 'brest', 'dinamo , brest', '10080', '9'], ['neman - belcard', 'grodno', 'neman', '6300', '10'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '11'], ['torpedo - kadino', 'mogilev', 'torpedo , mogilev', '3500', '12'], ['naftan - devon', 'novopolotsk', 'atlant', '6500', '13'], ['molodechno', 'molodechno', 'city stadium , molodechno', '5500', '14'], ['lida', 'lida', 'city stadium , lida', '4000', 'first league , 1'], ['svisloch - krovlya', 'osipovichi', 'yunost , osipovichi', '4000', 'first league , 2']] |
enlargement of the eurozone | https://en.wikipedia.org/wiki/Enlargement_of_the_eurozone | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12641034-2.html.csv | aggregation | the average central rate per € 1 among the eu members which have not adopted the euro is around 3.4 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '3.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'central rate'], 'result': '3.4', 'ind': 0, 'tostr': 'avg { all_rows ; central rate }'}, '3.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; central rate } ; 3.4 } = true', 'tointer': 'the average of the central rate record of all rows is 3.4 .'} | round_eq { avg { all_rows ; central rate } ; 3.4 } = true | the average of the central rate record of all rows is 3.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'central rate_4': 4, '3.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'central rate_4': 'central rate', '3.4_5': '3.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'central rate_4': [0], '3.4_5': [1]} | ['currency', 'code', 'entry erm ii', 'central rate', 'official target date'] | [['bulgarian lev', 'bgn', '-', '1.95583', '-'], ['croatian kuna', 'hrk', '-', '-', '-'], ['czech koruna', 'czk', '-', '-', '-'], ['danish krone', 'dkk', '1 january 1999', '7.46038', 'formal opt - out'], ['hungarian forint', 'huf', '-', '-', '-'], ['latvian lats', 'lvl', '2 may 2005', '0.702804', '1 january 2014'], ['lithuanian litas', 'ltl', '28 june 2004', '3.45280', '1 january 2015'], ['polish złoty', 'pln', '-', '-', '-'], ['romanian leu', 'ron', '-', '-', '-'], ['swedish krona', 'sek', 'not considered', '-', 'de facto opt - out'], ['british pound sterling gibraltar pound', 'gbp gip', 'not considered', '-', 'formal opt - out']] |
list of sports teams in nebraska | https://en.wikipedia.org/wiki/List_of_sports_teams_in_Nebraska | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14115168-4.html.csv | superlative | york college located in nebraska , holds the highest number of national titles out of all the other colleges that are part of national association of intercollegiate athletics . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', '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', 'national titles'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; national titles }'}, 'school'], 'result': 'york college', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; national titles } ; school }'}, 'york college'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; national titles } ; school } ; york college } = true', 'tointer': 'select the row whose national titles record of all rows is maximum . the school record of this row is york college .'} | eq { hop { argmax { all_rows ; national titles } ; school } ; york college } = true | select the row whose national titles record of all rows is maximum . the school record of this row is york college . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'national titles_5': 5, 'school_6': 6, 'york college_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'national titles_5': 'national titles', 'school_6': 'school', 'york college_7': 'york college'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'national titles_5': [0], 'school_6': [1], 'york college_7': [2]} | ['school', 'mascot', 'conference', 'national titles', 'founded'] | [['bellevue university', 'bellevue bruins', 'midlands', '14', '1966'], ['college of saint mary', 'saint mary flames', 'midlands', '0', '1923'], ['concordia university', 'concordia bulldogs', 'great plains', '1', '1894'], ['doane college', 'doane tigers', 'great plains', '10', '1872'], ['hastings college', 'hastings broncos', 'great plains', '3', '1882'], ['midland university', 'midland warriors', 'great plains', '2', '1883'], ['nebraska wesleyan university', 'nw prairie wolves', 'great plains', '19', '1887'], ['peru state college', 'peru state bobcats', 'midlands', '2', '1865'], ['york college', 'york panthers', 'midlands', '28', '1890']] |
north american x - 15 | https://en.wikipedia.org/wiki/North_American_X-15 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-221315-3.html.csv | aggregation | the average number of total flights for all pilots of the north american x - 15 is 16.63 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '16.63', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total flights'], 'result': '16.63', 'ind': 0, 'tostr': 'avg { all_rows ; total flights }'}, '16.63'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total flights } ; 16.63 } = true', 'tointer': 'the average of the total flights record of all rows is 16.63 .'} | round_eq { avg { all_rows ; total flights } ; 16.63 } = true | the average of the total flights record of all rows is 16.63 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total flights_4': 4, '16.63_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total flights_4': 'total flights', '16.63_5': '16.63'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total flights_4': [0], '16.63_5': [1]} | ['pilot', 'organization', 'total flights', 'usaf space flights', 'fai space flights', 'max mach', 'max speed ( mph )', 'max altitude ( miles )'] | [['michael j adams', 'us air force', '7', '1', '0', '5.59', '3822', '50.3'], ['neil armstrong', 'nasa', '7', '0', '0', '5.74', '3989', '39.2'], ['scott crossfield', 'north american aviation', '14', '0', '0', '2.97', '1959', '15.3'], ['william h dana', 'nasa', '16', '2', '0', '5.53', '3897', '58.1'], ['joseph h engle', 'us air force', '16', '3', '0', '5.71', '3887', '53.1'], ['william j pete knight', 'us air force', '16', '1', '0', '6.70', '4519', '53.1'], ['john b mckay', 'nasa', '29', '1', '0', '5.65', '3863', '55.9'], ['forrest s petersen', 'us navy', '5', '0', '0', '5.3', '3600', '19.2'], ['robert a rushworth', 'us air force', '34', '1', '0', '6.06', '4017', '53.9'], ['milton o thompson', 'nasa', '14', '0', '0', '5.48', '3723', '40.5'], ['joseph a walker', 'nasa', '25', '3', '2', '5.92', '4104', '67.0']] |
sherdrick bonner | https://en.wikipedia.org/wiki/Sherdrick_Bonner | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1570558-1.html.csv | comparative | sherdrick bonner had 2 more touchdowns in 1997 than he had in 1996 . | {'row_1': '5', 'row_2': '4', 'col': '6', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '2', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1997'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1997 .', 'tostr': 'filter_eq { all_rows ; year ; 1997 }'}, "td 's"], 'result': None, 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; year ; 1997 } ; td 's }", 'tointer': "select the rows whose year record fuzzily matches to 1997 . take the td 's record of this row ."}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1996'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1996 .', 'tostr': 'filter_eq { all_rows ; year ; 1996 }'}, "td 's"], 'result': None, 'ind': 3, 'tostr': "hop { filter_eq { all_rows ; year ; 1996 } ; td 's }", 'tointer': "select the rows whose year record fuzzily matches to 1996 . take the td 's record of this row ."}], 'result': '2', 'ind': 4, 'tostr': "diff { hop { filter_eq { all_rows ; year ; 1997 } ; td 's } ; hop { filter_eq { all_rows ; year ; 1996 } ; td 's } }"}, '2'], 'result': True, 'ind': 5, 'tostr': "eq { diff { hop { filter_eq { all_rows ; year ; 1997 } ; td 's } ; hop { filter_eq { all_rows ; year ; 1996 } ; td 's } } ; 2 } = true", 'tointer': "select the rows whose year record fuzzily matches to 1997 . take the td 's record of this row . select the rows whose year record fuzzily matches to 1996 . take the td 's record of this row . the first record is 2 larger than the second record ."} | eq { diff { hop { filter_eq { all_rows ; year ; 1997 } ; td 's } ; hop { filter_eq { all_rows ; year ; 1996 } ; td 's } } ; 2 } = true | select the rows whose year record fuzzily matches to 1997 . take the td 's record of this row . select the rows whose year record fuzzily matches to 1996 . take the td 's record of this row . the first record is 2 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'year_8': 8, '1997_9': 9, "td 's_10": 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'year_12': 12, '1996_13': 13, "td 's_14": 14, '2_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'year_8': 'year', '1997_9': '1997', "td 's_10": "td 's", 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'year_12': 'year', '1996_13': '1996', "td 's_14": "td 's", '2_15': '2'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'year_8': [0], '1997_9': [0], "td 's_10": [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'year_12': [1], '1996_13': [1], "td 's_14": [3], '2_15': [5]} | ['year', 'comp', 'att', 'comp %', 'yards', "td 's", "int 's", 'rating'] | [['1993', '2', '5', '40', '26', '0', '0', '57'], ['1994', '208', '363', '57.3', '2685', '46', '12', '98.5'], ['1995', '54', '90', '60', '574', '11', '3', '95.3'], ['1996', '286', '462', '61.9', '3690', '65', '13', '110.4'], ['1997', '241', '400', '60.3', '3331', '67', '6', '120.3'], ['1998', '295', '451', '65.4', '3571', '70', '8', '121'], ['2000', '269', '473', '56.9', '3454', '72', '7', '111.7'], ['2001', '193', '297', '65', '2505', '46', '7', '120.2'], ['2002', '270', '439', '61.5', '3219', '69', '8', '115.5'], ['2003', '289', '431', '67.1', '3696', '89', '7', '126.5'], ['2004', '348', '536', '64.9', '3850', '77', '9', '115'], ['2005', '189', '320', '59.1', '2334', '51', '10', '108.2'], ['2006', '295', '507', '58.2', '3991', '83', '16', '109.8'], ['2007', '315', '498', '63.3', '4003', '83', '13', '117.2'], ['2008', '60', '94', '63.8', '783', '16', '3', '116.3'], ['career statistics', '3314', '5366', '61.8', '41742', '845', '122', '115.9']] |
nightwatchman ( cricket ) | https://en.wikipedia.org/wiki/Nightwatchman_%28cricket%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1377586-1.html.csv | ordinal | mark boucher is the second highest scoring nightwatchman in cricket . | {'row': '4', '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', 'score', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; score ; 2 }'}, 'player'], 'result': 'mark boucher', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; score ; 2 } ; player }'}, 'mark boucher'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; score ; 2 } ; player } ; mark boucher } = true', 'tointer': 'select the row whose score record of all rows is 2nd maximum . the player record of this row is mark boucher .'} | eq { hop { nth_argmax { all_rows ; score ; 2 } ; player } ; mark boucher } = true | select the row whose score record of all rows is 2nd maximum . the player record of this row is mark boucher . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, '2_6': 6, 'player_7': 7, 'mark boucher_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', 'score_5': 'score', '2_6': '2', 'player_7': 'player', 'mark boucher_8': 'mark boucher'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], '2_6': [0], 'player_7': [1], 'mark boucher_8': [2]} | ['player', 'team', 'score', 'versus', 'year'] | [['nasim - ul - ghani', 'pakistan', '101', 'england', '1962'], ['tony mann', 'australia', '105', 'india', '1977'], ['syed kirmani', 'india', '101 not out', 'australia', '1979'], ['mark boucher', 'south africa', '125', 'zimbabwe', '1999'], ['mark boucher', 'south africa', '108', 'england', '1999'], ['jason gillespie', 'australia', '201 not out', 'bangladesh', '2006']] |
eurovision song contest 1962 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1962 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-181142-1.html.csv | count | a total of four artists in the 1962 eurovision song contest scored a total of 0 points . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; points ; 0 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; points ; 0 } }', 'tointer': 'select the rows whose points record is equal to 0 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; points ; 0 } } ; 4 } = true', 'tointer': 'select the rows whose points record is equal to 0 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; points ; 0 } } ; 4 } = true | select the rows whose points record is equal to 0 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'points_5': 5, '0_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'points_5': 'points', '0_6': '0', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'points_5': [0], '0_6': [0], '4_7': [2]} | ['draw', 'language', 'artist', 'english translation', 'place', 'points'] | [['01', 'finnish', 'marion rung', 'chirpy chirp', '7', '4'], ['02', 'french', 'fud leclerc', 'your name', '13', '0'], ['03', 'spanish', 'victor balaguer', 'call me', '13', '0'], ['04', 'german', 'eleonore schwarz', 'only in the vienna air', '13', '0'], ['05', 'danish', 'ellen winther', 'lullaby', '10', '2'], ['06', 'swedish', 'inger berggren', 'sun and spring', '7', '4'], ['07', 'german', 'conny froboess', 'two little italians', '6', '9'], ['08', 'dutch', 'de spelbrekers', '-', '13', '0'], ['09', 'french', 'isabelle aubret', 'a first love', '1', '26'], ['10', 'norwegian', 'inger jacobsen', 'come sun , come rain', '10', '2'], ['11', 'french', 'jean philippe', 'the return', '10', '2'], ['12', 'serbian', 'lola novaković', "do n't turn the lights on at twilight", '4', '10'], ['13', 'english', 'ronnie carroll', '-', '4', '10'], ['14', 'french', 'camillo felgen', 'little chap', '3', '11'], ['15', 'italian', 'claudio villa', 'goodbye , goodbye', '9', '3'], ['16', 'french', 'françois deguelt', 'say nothing', '2', '13']] |
2008 brazilian grand prix | https://en.wikipedia.org/wiki/2008_Brazilian_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14270784-2.html.csv | comparative | in the 2008 brazilian grand prix , timo glock completed more laps than adrian sutil . | {'row_1': '6', 'row_2': '16', 'col': '3', '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', 'driver', 'timo glock'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose driver record fuzzily matches to timo glock .', 'tostr': 'filter_eq { all_rows ; driver ; timo glock }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; driver ; timo glock } ; laps }', 'tointer': 'select the rows whose driver record fuzzily matches to timo glock . take the laps record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'driver', 'adrian sutil'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose driver record fuzzily matches to adrian sutil .', 'tostr': 'filter_eq { all_rows ; driver ; adrian sutil }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; driver ; adrian sutil } ; laps }', 'tointer': 'select the rows whose driver record fuzzily matches to adrian sutil . take the laps record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; driver ; timo glock } ; laps } ; hop { filter_eq { all_rows ; driver ; adrian sutil } ; laps } } = true', 'tointer': 'select the rows whose driver record fuzzily matches to timo glock . take the laps record of this row . select the rows whose driver record fuzzily matches to adrian sutil . take the laps record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; driver ; timo glock } ; laps } ; hop { filter_eq { all_rows ; driver ; adrian sutil } ; laps } } = true | select the rows whose driver record fuzzily matches to timo glock . take the laps record of this row . select the rows whose driver record fuzzily matches to adrian sutil . take the laps 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, 'driver_7': 7, 'timo glock_8': 8, 'laps_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'driver_11': 11, 'adrian sutil_12': 12, 'laps_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', 'driver_7': 'driver', 'timo glock_8': 'timo glock', 'laps_9': 'laps', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'driver_11': 'driver', 'adrian sutil_12': 'adrian sutil', 'laps_13': 'laps'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'driver_7': [0], 'timo glock_8': [0], 'laps_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'driver_11': [1], 'adrian sutil_12': [1], 'laps_13': [3]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['felipe massa', 'ferrari', '71', '1:34:11.435', '1'], ['fernando alonso', 'renault', '71', '+ 13.298', '6'], ['kimi räikkönen', 'ferrari', '71', '+ 16.235', '3'], ['sebastian vettel', 'toro rosso - ferrari', '71', '+ 38.011', '7'], ['lewis hamilton', 'mclaren - mercedes', '71', '+ 38.907', '4'], ['timo glock', 'toyota', '71', '+ 44.368', '10'], ['heikki kovalainen', 'mclaren - mercedes', '71', '+ 55.074', '5'], ['jarno trulli', 'toyota', '71', '+ 1:08.433', '2'], ['mark webber', 'red bull - renault', '71', '+ 1:19.666', '12'], ['nick heidfeld', 'bmw sauber', '70', '+ 1 lap', '8'], ['robert kubica', 'bmw sauber', '70', '+ 1 lap', '13'], ['nico rosberg', 'williams - toyota', '70', '+ 1 lap', '18'], ['jenson button', 'honda', '70', '+ 1 lap', '17'], ['sébastien bourdais', 'toro rosso - ferrari', '70', '+ 1 lap', '9'], ['rubens barrichello', 'honda', '70', '+ 1 lap', '15'], ['adrian sutil', 'force india - ferrari', '69', '+ 2 laps', '20'], ['kazuki nakajima', 'williams - toyota', '69', '+ 2 laps', '16'], ['giancarlo fisichella', 'force india - ferrari', '69', '+ 2 laps', '19'], ['nelson piquet jr', 'renault', '0', 'accident', '11'], ['david coulthard', 'red bull - renault', '0', 'collision', '14']] |
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 | ordinal | regarding the 9th seanad , the second highest number of members in the cultural and educational panel was attributed to the fianna fáil party . | {'row': '1', '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', 'cultural and educational panel', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; cultural and educational panel ; 2 }'}, 'party'], 'result': 'fianna fáil', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; cultural and educational panel ; 2 } ; party }'}, 'fianna fáil'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; cultural and educational panel ; 2 } ; party } ; fianna fáil } = true', 'tointer': 'select the row whose cultural and educational panel record of all rows is 2nd maximum . the party record of this row is fianna fáil .'} | eq { hop { nth_argmax { all_rows ; cultural and educational panel ; 2 } ; party } ; fianna fáil } = true | select the row whose cultural and educational panel record of all rows is 2nd maximum . the party record of this row is fianna fáil . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'cultural and educational panel_5': 5, '2_6': 6, 'party_7': 7, 'fianna fáil_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', 'cultural and educational panel_5': 'cultural and educational panel', '2_6': '2', 'party_7': 'party', 'fianna fáil_8': 'fianna fáil'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'cultural and educational panel_5': [0], '2_6': [0], 'party_7': [1], 'fianna fáil_8': [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']] |
the mole ( tv series ) | https://en.wikipedia.org/wiki/The_Mole_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-178242-2.html.csv | comparative | season 2 of the mole had more potential prize money than season 1 . | {'row_1': '2', 'row_2': '1', 'col': '7', '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', 'season', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2 .', 'tostr': 'filter_eq { all_rows ; season ; 2 }'}, 'potential prize money'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season ; 2 } ; potential prize money }', 'tointer': 'select the rows whose season record fuzzily matches to 2 . take the potential prize money record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose season record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; season ; 1 }'}, 'potential prize money'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; season ; 1 } ; potential prize money }', 'tointer': 'select the rows whose season record fuzzily matches to 1 . take the potential prize money record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; season ; 2 } ; potential prize money } ; hop { filter_eq { all_rows ; season ; 1 } ; potential prize money } } = true', 'tointer': 'select the rows whose season record fuzzily matches to 2 . take the potential prize money record of this row . select the rows whose season record fuzzily matches to 1 . take the potential prize money record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; season ; 2 } ; potential prize money } ; hop { filter_eq { all_rows ; season ; 1 } ; potential prize money } } = true | select the rows whose season record fuzzily matches to 2 . take the potential prize money record of this row . select the rows whose season record fuzzily matches to 1 . take the potential prize money 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, 'season_7': 7, '2_8': 8, 'potential prize money_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '1_12': 12, 'potential prize money_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', 'season_7': 'season', '2_8': '2', 'potential prize money_9': 'potential prize money', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '1_12': '1', 'potential prize money_13': 'potential prize money'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2_8': [0], 'potential prize money_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '1_12': [1], 'potential prize money_13': [3]} | ['season', 'year', 'mole', 'winner', 'runner - up', 'total prize money', 'potential prize money', 'destination'] | [['1', '2000', 'alan mason', 'jan moody', 'abby coleman', '115000', '200000', 'australia ( tasmania )'], ['2', '2001', 'michael laffy', 'brooke marshall', 'hal pritchard', '100000', '255000', 'australia ( victoria )'], ['3', '2002', 'alaina taylor', 'crystal - rose cluff', 'marc jongebloed', '108000', '416000', 'australia ( gold coast )'], ['4', '2003', 'petrina edge', 'shaun faulkner', 'nathan beves', '104000', '531000', 'new caledonia'], ['5', '2005', 'john whitehall', 'liz cantor', 'craig murell', '203000', '539000', 'new zealand'], ['6', '2013', 'erin dooley', 'hillal kara - ali', 'aisha jefcoate', '180000', '250000', 'australia']] |
blue ridge hockey conference | https://en.wikipedia.org/wiki/Blue_Ridge_Hockey_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16404837-3.html.csv | count | two of the schools in the blue ridge hockey conference are private institutions . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'private', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'affiliation', 'private'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose affiliation record fuzzily matches to private .', 'tostr': 'filter_eq { all_rows ; affiliation ; private }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; affiliation ; private } }', 'tointer': 'select the rows whose affiliation record fuzzily matches to private . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; affiliation ; private } } ; 2 } = true', 'tointer': 'select the rows whose affiliation record fuzzily matches to private . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; affiliation ; private } } ; 2 } = true | select the rows whose affiliation record fuzzily matches to private . 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, 'affiliation_5': 5, 'private_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', 'affiliation_5': 'affiliation', 'private_6': 'private', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'affiliation_5': [0], 'private_6': [0], '2_7': [2]} | ['school', 'location', 'founded', 'affiliation', 'nickname'] | [['american university', 'washington dc', '1893', 'private / methodist', 'eagles'], ['catholic university', 'washington dc', '1887', 'private / roman catholic', 'cardinals'], ['george mason university', 'fairfax , va', '1957', 'public', 'patriots'], ['university of maryland', 'college park , md', '1856', 'public flagship ( university system of maryland )', 'terrapins'], ['northern virginia community college', 'annandale , va', '1964', 'community college', 'raiders'], ['college of william & mary', 'williamsburg , va', '1693', 'public', 'tribe']] |
haarlem baseball week | https://en.wikipedia.org/wiki/Haarlem_Baseball_Week | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18532667-2.html.csv | ordinal | netherlands recorded the 2nd highest total in the haarlem baseball week tournament . | {'row': '3', 'col': '6', 'order': '2', 'col_other': '2', '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', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'nation'], 'result': 'netherlands', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; nation }'}, 'netherlands'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; netherlands } = true', 'tointer': 'select the row whose total record of all rows is 2nd maximum . the nation record of this row is netherlands .'} | eq { hop { nth_argmax { all_rows ; total ; 2 } ; nation } ; netherlands } = true | select the row whose total record of all rows is 2nd maximum . the nation record of this row is netherlands . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, 'nation_7': 7, 'netherlands_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', 'total_5': 'total', '2_6': '2', 'nation_7': 'nation', 'netherlands_8': 'netherlands'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'nation_7': [1], 'netherlands_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '13', '7', '10', '30'], ['2', 'cuba', '5', '6', '2', '13'], ['3', 'netherlands', '3', '7', '7', '17'], ['4', 'japan', '3', '1', '2', '6'], ['5', 'canada', '1', '1', '0', '2'], ['6', 'netherlands antilles', '1', '0', '1', '2'], ['7', 'south korea', '0', '2', '0', '2'], ['8', 'germany', '0', '1', '1', '2'], ['9', 'australia', '0', '1', '0', '1'], ['9', 'puerto rico', '0', '1', '0', '1'], ['10', 'chinese taipei', '0', '0', '1', '1'], ['10', 'france', '0', '0', '1', '1'], ['10', 'italy', '0', '0', '1', '1']] |
northern indiana athletic conference | https://en.wikipedia.org/wiki/Northern_Indiana_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12264570-1.html.csv | superlative | the highest enrollment for schools in the northern indiana athletic conference was for penn . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', '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 ihsaa class'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment ihsaa class }'}, 'school'], 'result': 'penn', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment ihsaa class } ; school }'}, 'penn'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment ihsaa class } ; school } ; penn } = true', 'tointer': 'select the row whose enrollment ihsaa class record of all rows is maximum . the school record of this row is penn .'} | eq { hop { argmax { all_rows ; enrollment ihsaa class } ; school } ; penn } = true | select the row whose enrollment ihsaa class record of all rows is maximum . the school record of this row is penn . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment ihsaa class_5': 5, 'school_6': 6, 'penn_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment ihsaa class_5': 'enrollment ihsaa class', 'school_6': 'school', 'penn_7': 'penn'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment ihsaa class_5': [0], 'school_6': [1], 'penn_7': [2]} | ['school', 'location', 'mascot', 'county', 'enrollment ihsaa class', 'joined', 'previous conference'] | [['elkhart central', 'elkhart', 'blue blazers', '20 elkhart', '1747 aaaa', '1927', 'independents'], ['mishawaka', 'mishawaka', 'cavemen', '71 st joseph', '1761 aaaa', '1927', 'independents'], ['mishawaka marian', 'mishawaka', 'knights', '71 st joseph', '768 aaa', '2005', 'independents'], ['penn', 'mishawaka', 'kingsmen', '71 st joseph', '3222 aaaa', '1977', 'independents'], ['south bend adams', 'south bend', 'eagles', '71 st joseph', '1773 aaaa', '1941', 'none ( new school )'], ['south bend clay', 'south bend', 'colonials', '71 st joseph', '1466 aaaa', '1979', 'independents'], ['south bend riley', 'south bend', 'wildcats', '71 st joseph', '1511 aaaa', '1931', 'none ( new school )'], ["south bend st joseph 's", 'south bend', 'indians', '71 st joseph', '793 aaa', '2005', 'independents'], ['south bend washington', 'south bend', 'panthers', '71 st joseph', '1428 aaaa', '1938', 'none ( new school )']] |
new york city mayoral elections | https://en.wikipedia.org/wiki/New_York_City_mayoral_elections | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1108394-32.html.csv | superlative | robert f wagner , jr received the highest number of votes between him and arthur levitt in the 1961 democratic primary election . | {'scope': 'all', 'col_superlative': '7', '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', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, '1961 democratic primary'], 'result': 'robert f wagner , jr', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; 1961 democratic primary }'}, 'robert f wagner , jr'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; 1961 democratic primary } ; robert f wagner , jr } = true', 'tointer': 'select the row whose total record of all rows is maximum . the 1961 democratic primary record of this row is robert f wagner , jr .'} | eq { hop { argmax { all_rows ; total } ; 1961 democratic primary } ; robert f wagner , jr } = true | select the row whose total record of all rows is maximum . the 1961 democratic primary record of this row is robert f wagner , jr . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '1961 democratic primary_6': 6, 'robert f wagner , jr_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '1961 democratic primary_6': '1961 democratic primary', 'robert f wagner , jr_7': 'robert f wagner , jr'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '1961 democratic primary_6': [1], 'robert f wagner , jr_7': [2]} | ['1961 democratic primary', 'manhattan', 'the bronx', 'brooklyn', 'queens', 'richmond', 'total'] | [['robert f wagner , jr', '122607', '78626', '136440', '102845', '15498', '456016'], ['robert f wagner , jr', '65 %', '62 %', '57 %', '62 %', '60 %', '456016'], ['arthur levitt', '66917', '47885', '103296', '64157', '10471', '292726'], ['arthur levitt', '35 %', '38 %', '43 %', '38 %', '40 %', '292726'], ['subtotal ( for wagner and levitt only )', '189524', '126511', '239736', '167002', '25969', '748742']] |
andrew pattison | https://en.wikipedia.org/wiki/Andrew_Pattison | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10833727-1.html.csv | superlative | of the competitions that andrew pattison participated in , the most recent one was in newport , rhode island . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '11', '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', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; date }'}, 'championship'], 'result': 'newport , rhode island , us', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; date } ; championship }'}, 'newport , rhode island , us'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; date } ; championship } ; newport , rhode island , us } = true', 'tointer': 'select the row whose date record of all rows is maximum . the championship record of this row is newport , rhode island , us .'} | eq { hop { argmax { all_rows ; date } ; championship } ; newport , rhode island , us } = true | select the row whose date record of all rows is maximum . the championship record of this row is newport , rhode island , us . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, 'championship_6': 6, 'newport , rhode island , us_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'date_5': 'date', 'championship_6': 'championship', 'newport , rhode island , us_7': 'newport , rhode island , us'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], 'championship_6': [1], 'newport , rhode island , us_7': [2]} | ['outcome', 'date', 'championship', 'opponent in the final', 'score in the final'] | [['runner - up', '23 july 1972', 'columbus , ohio , us', 'jimmy connors', '5 - 7 , 3 - 6 , 5 - 7'], ['runner - up', '30 july 1972', 'tanglewood , usa', 'bob hewitt', '6 - 3 , 3 - 6 , 1 - 6'], ['runner - up', '14 august 1972', 'montreal , canada', 'ilie năstase', '4 - 6 , 3 - 6'], ['winner', '8 april 1974', 'monte carlo , monaco', 'ilie năstase', '5 - 7 , 6 - 3 , 6 - 4'], ['winner', '15 april 1974', 'johannesburg , south africa', 'john alexander', '6 - 3 , 7 - 5'], ['runner - up', '28 october 1974', 'vienna , austria', 'vitas gerulaitis', '4 - 6 , 6 - 3 , 3 - 6 , 2 - 6'], ['runner - up', '7 january 1976', 'columbus , ohio , us', 'arthur ashe', '6 - 3 , 3 - 6 , 6 - 7 ( 4 )'], ['runner - up', '8 february 1976', 'dayton , ohio , us', 'jaime fillol sr', '4 - 6 , 7 - 6 , 4 - 6'], ['winner', '14 september 1977', 'laguna niguel , us', 'colin dibley', '2 - 6 , 7 - 6 , 6 - 4'], ['winner', '27 november 1979', 'johannesburg , south africa', 'víctor pecci', '2 - 6 , 6 - 3 , 6 - 2 , 6 - 3'], ['runner - up', '7 july 1980', 'newport , rhode island , us', 'vijay amritraj', '1 - 6 , 7 - 5 , 3 - 6']] |
list of doctor who audio plays by big finish | https://en.wikipedia.org/wiki/List_of_Doctor_Who_audio_plays_by_Big_Finish | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1620397-2.html.csv | unique | point of entry was the only doctor who audio play by big finish authored by barbara clegg and marc platt . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'barbara clegg and marc platt', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'author', 'barbara clegg and marc platt'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose author record fuzzily matches to barbara clegg and marc platt .', 'tostr': 'filter_eq { all_rows ; author ; barbara clegg and marc platt }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; author ; barbara clegg and marc platt } }', 'tointer': 'select the rows whose author record fuzzily matches to barbara clegg and marc platt . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'author', 'barbara clegg and marc platt'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose author record fuzzily matches to barbara clegg and marc platt .', 'tostr': 'filter_eq { all_rows ; author ; barbara clegg and marc platt }'}, 'title'], 'result': 'point of entry', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; author ; barbara clegg and marc platt } ; title }'}, 'point of entry'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; author ; barbara clegg and marc platt } ; title } ; point of entry }', 'tointer': 'the title record of this unqiue row is point of entry .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; author ; barbara clegg and marc platt } } ; eq { hop { filter_eq { all_rows ; author ; barbara clegg and marc platt } ; title } ; point of entry } } = true', 'tointer': 'select the rows whose author record fuzzily matches to barbara clegg and marc platt . there is only one such row in the table . the title record of this unqiue row is point of entry .'} | and { only { filter_eq { all_rows ; author ; barbara clegg and marc platt } } ; eq { hop { filter_eq { all_rows ; author ; barbara clegg and marc platt } ; title } ; point of entry } } = true | select the rows whose author record fuzzily matches to barbara clegg and marc platt . there is only one such row in the table . the title record of this unqiue row is point of entry . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'author_7': 7, 'barbara clegg and marc platt_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'point of entry_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'author_7': 'author', 'barbara clegg and marc platt_8': 'barbara clegg and marc platt', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'point of entry_10': 'point of entry'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'author_7': [0], 'barbara clegg and marc platt_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'point of entry_10': [3]} | ['', 'series sorted', 'title', 'author', 'doctor', 'featuring', 'released'] | [['1', '6y / aa', 'the nightmare fair', 'graham williams ( adapted by john ainsworth )', '6th', 'peri , celestial toymaker', 'november 2009'], ['2', '6y / ab', 'mission to magnus', 'philip martin', '6th', 'peri , s ice warrior , sil', 'december 2009'], ['3', '6y / ac', 'leviathan', 'brian finch ( adapted by paul finch )', '6th', 'peri', 'january 2010'], ['5', '6y / ae', 'paradise 5', 'pj hammond and andy lane', '6th', 'peri', 'march 2010'], ['6', '6y / af', 'point of entry', 'barbara clegg and marc platt', '6th', 'peri', 'april 2010'], ['7', '6y / ag', 'the song of megaptera', 'pat mills', '6th', 'peri', 'may 2010']] |
2008 armenian cup | https://en.wikipedia.org/wiki/2008_Armenian_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17372848-1.html.csv | superlative | pyunik was the football club that scored the most total goals in the 2008 armenian cup . | {'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', 'agg'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; agg }'}, 'team 1'], 'result': 'pyunik', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; agg } ; team 1 }'}, 'pyunik'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; agg } ; team 1 } ; pyunik } = true', 'tointer': 'select the row whose agg record of all rows is maximum . the team 1 record of this row is pyunik .'} | eq { hop { argmax { all_rows ; agg } ; team 1 } ; pyunik } = true | select the row whose agg record of all rows is maximum . the team 1 record of this row is pyunik . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'agg_5': 5, 'team 1_6': 6, 'pyunik_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'agg_5': 'agg', 'team 1_6': 'team 1', 'pyunik_7': 'pyunik'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'agg_5': [0], 'team 1_6': [1], 'pyunik_7': [2]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['banants - 2', '2 - 6', 'ulisses', '1 - 4', '1 - 2'], ['pyunik', '15 - 2', 'patani', '11 - 2', '4 - 0'], ['gandzasar', '8 - 0', 'pyunik - 2', '3 - 0', '5 - 0'], ['kilikia', '5 - 2', 'mika - 2', '2 - 0', '3 - 2'], ['mika', '11 - 0', 'ararat - 2', '7 - 0', '4 - 0'], ['shengavit', '2 - 3', 'shirak', '1 - 3', '1 - 0']] |
2008 - 09 lega pro prima divisione | https://en.wikipedia.org/wiki/2008%E2%80%9309_Lega_Pro_Prima_Divisione | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17605092-1.html.csv | aggregation | the average capacity of the stadiums in the lega pro prima divisione in the season 2008-09 was around 14950 seats . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '14950', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '14950', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '14950'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 14950 } = true', 'tointer': 'the average of the capacity record of all rows is 14950 .'} | round_eq { avg { all_rows ; capacity } ; 14950 } = true | the average of the capacity record of all rows is 14950 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '14950_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '14950_5': '14950'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '14950_5': [1]} | ['club', 'city', 'stadium', 'capacity', '200708 season'] | [['ac cesena', 'cesena', 'stadio dino manuzzi', '23860', '22nd in serie b'], ['us cremonese', 'cremona', 'stadio giovanni zini', '22000', '2nd in serie c1 / a'], ['calcio lecco 1912', 'lecco', 'stadio rigamonti - ceppi', '4977', '16th in serie c1 / a'], ['ac legnano', 'legnano', 'stadio giovanni mari', '6600', '7th in serie c1 / a'], ['ac lumezzane', 'lumezzane', 'nuovo stadio comunale', '4150', 'serie c2 / a play - off winners'], ['ac monza brianza 1912', 'monza', 'stadio brianteo', '18568', '8th in serie c1 / a'], ['novara calcio', 'novara', 'stadio silvio piola', '8810', '9th in serie c1 / a'], ['calcio padova', 'padua', 'stadio euganeo', '32336', '6th in serie c1 / a'], ['us pergocrema 1932', 'crema', 'stadio giuseppe voltini', '3490', 'serie c2 / a champions'], ['calcio portogruaro summaga', 'portogruaro', 'stadio pier giovanni mecchia', '3335', 'serie c2 / b play - off winners'], ['pro patria', 'busto arsizio', 'stadio carlo speroni', '3990', '14th in serie c1 / a'], ['ac pro sesto', 'sesto san giovanni', 'stadio breda', '4500', '11th in serie c1 / a'], ['ravenna calcio', 'ravenna', 'stadio bruno benelli', '12020', '20th in serie b'], ['ac reggiana 1919', 'reggio emilia', 'stadio giglio', '29546', 'serie c2 / b champions'], ['ss sambenedettese calcio', 'san benedetto del tronto', 'stadio riviera delle palme', '22000', '12th in serie c1 / b'], ['spal 1907', 'ferrara', 'stadio paolo mazza', '19000', '4th in serie c2 / b'], ['ssc venezia', 'venice', 'stadio pierluigi penzo', '10500', '12th in serie c1 / a'], ['hellas verona fc', 'verona', 'stadio marcantonio bentegodi', '39211', '17th in serie c1 / a']] |
fred astaire chronology of performances | https://en.wikipedia.org/wiki/Fred_Astaire_chronology_of_performances | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15186990-4.html.csv | majority | all of fred astaire 's performances took place in the decade of the 1930s . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1930', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'date', '1930'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them are greater than 1930 .', 'tostr': 'most_greater { all_rows ; date ; 1930 } = true'} | most_greater { all_rows ; date ; 1930 } = true | for the date records of all rows , most of them are greater than 1930 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '1930_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '1930_4': '1930'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '1930_4': [0]} | ['date', 'theatre , studio , or network', 'role', 'dance partner', 'director'] | [['june 3 , 1931', 'new amsterdam', 'himself', 'adele astaire tilly losch', 'hassard short'], ['nov 29 1932', 'ethel barrymore', 'guy holden', 'claire luce', 'howard lindsay'], ['nov 2 1933', 'palace', 'guy holden', 'claire luce', 'felix edwardes'], ['dec 2 , 1933', 'mgm', 'himself', 'joan crawford', 'robert z leonard'], ['dec 20 , 1933', 'rko', 'fred ayres', 'dolores del río ginger rogers', 'thornton freeland'], ['oct 3 , 1934', 'rko', 'guy holden', 'ginger rogers', 'mark sandrich'], ['feb 12 , 1935', 'rko', 'huckleberry haines', 'ginger rogers', 'william a seiter'], ['aug 12 1935', 'nbc', 'himself', '-', '-'], ['aug 16 , 1935', 'rko', 'jerry travers', 'ginger rogers', 'mark sandrich'], ['feb 19 , 1936', 'rko', 'bake baker', 'ginger rogers', 'mark sandrich'], ['aug 26 , 1936', 'rko', 'lucky garnett', 'ginger rogers', 'george stevens'], ['sept 15 1936', 'nbc', 'himself ( host )', '-', '-'], ['apr 30 , 1937', 'rko', 'peter p peters', 'ginger rogers', 'mark sandrich'], ['nov 20 , 1937', 'rko', 'jerry halliday', 'george burns & gracie allen joan fontaine', 'george stevens'], ['aug 30 , 1938', 'rko', 'tony flagg', 'ginger rogers', 'mark sandrich'], ['jan 15 1939', 'nbc', '-', '-', '-'], ['mar 31 , 1939', 'rko', 'vernon castle', 'ginger rogers', 'hc potter'], ['feb 14 , 1940', 'mgm', 'johnny brett', 'eleanor powell george murphy', 'norman taurog'], ['dec 3 , 1940', 'paramount', "danny o'neill", 'paulette goddard', 'hc potter']] |
bulgaria in the eurovision song contest 2009 | https://en.wikipedia.org/wiki/Bulgaria_in_the_Eurovision_Song_Contest_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18593648-14.html.csv | comparative | mariana popova received a higher percentage of the televote than stefan dobrev . | {'row_1': '8', 'row_2': '10', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'mariana popova'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose artist record fuzzily matches to mariana popova .', 'tostr': 'filter_eq { all_rows ; artist ; mariana popova }'}, 'televote / sms'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; artist ; mariana popova } ; televote / sms }', 'tointer': 'select the rows whose artist record fuzzily matches to mariana popova . take the televote / sms record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'stefan dobrev'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose artist record fuzzily matches to stefan dobrev .', 'tostr': 'filter_eq { all_rows ; artist ; stefan dobrev }'}, 'televote / sms'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; artist ; stefan dobrev } ; televote / sms }', 'tointer': 'select the rows whose artist record fuzzily matches to stefan dobrev . take the televote / sms record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; artist ; mariana popova } ; televote / sms } ; hop { filter_eq { all_rows ; artist ; stefan dobrev } ; televote / sms } } = true', 'tointer': 'select the rows whose artist record fuzzily matches to mariana popova . take the televote / sms record of this row . select the rows whose artist record fuzzily matches to stefan dobrev . take the televote / sms record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; artist ; mariana popova } ; televote / sms } ; hop { filter_eq { all_rows ; artist ; stefan dobrev } ; televote / sms } } = true | select the rows whose artist record fuzzily matches to mariana popova . take the televote / sms record of this row . select the rows whose artist record fuzzily matches to stefan dobrev . take the televote / sms record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'artist_7': 7, 'mariana popova_8': 8, 'televote / sms_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'artist_11': 11, 'stefan dobrev_12': 12, 'televote / sms_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'artist_7': 'artist', 'mariana popova_8': 'mariana popova', 'televote / sms_9': 'televote / sms', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'artist_11': 'artist', 'stefan dobrev_12': 'stefan dobrev', 'televote / sms_13': 'televote / sms'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'artist_7': [0], 'mariana popova_8': [0], 'televote / sms_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'artist_11': [1], 'stefan dobrev_12': [1], 'televote / sms_13': [3]} | ['draw', 'artist', 'song', 'televote / sms', 'place'] | [['1', 'stefan ilchev', 'get up', '2.95 %', '7'], ['2', 'moto', 'razstoyaniya', '0.37 %', '12'], ['3', 'poli genova', 'one lifetime is not enough', '11.74 %', '2'], ['4', 'danny milev', 'nyama vreme', '2.39 %', '9'], ['5', 'ivelina', 'ready for love', '2.53 %', '8'], ['6', 'grafa', 'vrag', '3.91 %', '5'], ['7', 'sahara', "do n't kiss for the money", '3.20 %', '6'], ['8', 'mariana popova', 'crazy', '8.45 %', '3'], ['9', 'jura tone feat lady b', 'chance to love you', '2.03 %', '10'], ['10', 'stefan dobrev', 'everlasting', '1.16 %', '11'], ['11', 'krassimir avramov', 'illusion', '55.52 %', '1'], ['12', 'nora', "it 's not right", '5.75 %', '4']] |
andrea pirlo | https://en.wikipedia.org/wiki/Andrea_Pirlo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1700594-3.html.csv | count | of the list of international goals scored by andrea pirlo , he scored in three friendly games . | {'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to friendly .', 'tostr': 'filter_eq { all_rows ; competition ; friendly }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; competition ; friendly } }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; competition ; friendly } } ; 3 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; competition ; friendly } } ; 3 } = true | select the rows whose competition record fuzzily matches to friendly . 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, 'competition_5': 5, 'friendly_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', 'competition_5': 'competition', 'friendly_6': 'friendly', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly_6': [0], '3_7': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['30 may 2004', 'stade olympique de radès , radès , tunisia', '3 - 0', '4 - 0', 'friendly'], ['26 march 2005', 'san siro , milan , italy', '1 - 0', '2 - 0', '2006 fifa world cup qualification'], ['26 march 2005', 'san siro , milan , italy', '2 - 0', '2 - 0', '2006 fifa world cup qualification'], ['17 august 2005', 'lansdowne road , dublin , republic of ireland', '1 - 0', '2 - 1', 'friendly'], ['12 june 2006', 'awd - arena , hanover , germany', '1 - 0', '2 - 0', '2006 fifa world cup'], ['13 october 2007', 'stadio luigi ferraris , genoa , italy', '1 - 0', '2 - 0', 'uefa euro 2008 qualification'], ['17 june 2008', 'letzigrund , zurich , switzerland', '1 - 0', '2 - 0', 'uefa euro 2008'], ['28 march 2009', 'podgorica city stadium , podgorica , montenegro', '1 - 0', '2 - 0', '2010 fifa world cup qualification'], ['7 september 2010', 'stadio artemio franchi , florence , italy', '5 - 0', '5 - 0', 'uefa euro 2012 qualification'], ['14 june 2012', 'stadion miejski , poznań , poland', '1 - 0', '1 - 1', 'uefa euro 2012'], ['12 october 2012', 'hrazdan stadium , yerevan , armenia', '1 - 0', '3 - 1', '2014 fifa world cup qualification'], ['31 may 2013', "stadio renato dall ' ara , bologna , italy", '3 - 0', '4 - 0', 'friendly'], ['16 june 2013', 'estádio do maracanã , rio de janeiro , brazil', '1 - 0', '2 - 1', '2013 fifa confederations cup'], ['as of 17 june 2013', 'as of 17 june 2013', 'as of 17 june 2013', 'as of 17 june 2013', 'as of 17 june 2013']] |
1972 - 73 california golden seals season | https://en.wikipedia.org/wiki/1972%E2%80%9373_California_Golden_Seals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18991157-1.html.csv | majority | most of the picks made for the golden seals in the 72-73 season were made after the 3rd round . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '3', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'round', '3'], 'result': True, 'ind': 0, 'tointer': 'for the round records of all rows , most of them are greater than 3 .', 'tostr': 'most_greater { all_rows ; round ; 3 } = true'} | most_greater { all_rows ; round ; 3 } = true | for the round records of all rows , most of them are greater than 3 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'round_3': 3, '3_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'round_3': 'round', '3_4': '3'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'round_3': [0], '3_4': [0]} | ['round', 'pick', 'player', 'nationality', 'college / junior / club team'] | [['2', '22', 'tom cassidy', 'canada', 'kitchener rangers ( oha )'], ['2', '28', 'stan weir', 'canada', 'medicine hat tigers ( wchl )'], ['3', '38', 'paul shakes', 'canada', 'st catharines black hawks ( oha )'], ['4', '54', 'claude st sauveur', 'canada', 'sherbrooke beavers ( qmjhl )'], ['5', '70', 'tim jacobs', 'canada', 'st catharines black hawks ( oha )'], ['6', '86', 'jacques lefebvre', 'canada', 'shawinigan bruins ( qmjhl )'], ['7', '102', 'mike amodeo', 'canada', 'oshawa generals ( oha )'], ['8', '118', 'brent meeke', 'canada', 'niagara falls flyers ( oha )'], ['9', '134', 'denis meloche', 'canada', 'drummondville rangers ( qmjhl )']] |
2005 connecticut sun season | https://en.wikipedia.org/wiki/2005_Connecticut_Sun_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18904831-5.html.csv | count | in the 2005 connecticut sun season , the team lost only once . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'l', 'result': '1', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to l .', 'tostr': 'filter_eq { all_rows ; score ; l }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; l } }', 'tointer': 'select the rows whose score record fuzzily matches to l . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; l } } ; 1 } = true', 'tointer': 'select the rows whose score record fuzzily matches to l . the number of such rows is 1 .'} | eq { count { filter_eq { all_rows ; score ; l } } ; 1 } = true | select the rows whose score record fuzzily matches to l . the number of such rows is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'score_5': 5, 'l_6': 6, '1_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', 'l_6': 'l', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], 'l_6': [0], '1_7': [2]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location', 'record'] | [['4', 'june 4', 'san antonio', 'w 80 - 69', 'douglas , dydek , mcwilliams - franklin ( 15 )', 'jones ( 7 )', 'douglas , whalen ( 6 )', 'mohegan sun arena 6252', '3 - 1'], ['5', 'june 7', 'seattle', 'w 81 - 69', 'douglas ( 20 )', 'dydek ( 14 )', 'whalen ( 8 )', 'mohegan sun arena 7080', '4 - 1'], ['6', 'june 10', 'houston', 'w 77 - 57', 'sales ( 21 )', 'dydek ( 12 )', 'whalen ( 6 )', 'toyota center 5736', '5 - 1'], ['7', 'june 11', 'san antonio', 'w 78 - 69', 'mcwilliams - franklin ( 17 )', 'douglas , mcwilliams - franklin ( 9 )', 'whalen ( 6 )', 'at & t center 9772', '6 - 1'], ['8', 'june 18', 'detroit', 'w 73 - 63', 'sales ( 17 )', 'mcwilliams - franklin ( 10 )', 'whalen ( 6 )', 'mohegan sun arena 7427', '7 - 1'], ['9', 'june 20', 'los angeles', 'w 90 - 70', 'sales ( 26 )', 'dydek ( 10 )', 'douglas , whalen ( 6 )', 'staples center 7246', '8 - 1'], ['10', 'june 22', 'seattle', 'l 86 - 95', 'mcwilliams - franklin ( 21 )', 'dydek , mcwilliams - franklin , whalen ( 5 )', 'whalen ( 6 )', 'keyarena 8120', '8 - 2'], ['11', 'june 24', 'sacramento', 'w 61 - 50', 'mcwilliams - franklin ( 15 )', 'mcwilliams - franklin ( 14 )', 'whalen ( 3 )', 'arco arena 10067', '9 - 2'], ['12', 'june 25', 'phoenix', 'w 77 - 69', 'sales ( 22 )', 'wyckoff ( 9 )', 'sales , wyckoff ( 3 )', 'us airways center 8091', '10 - 2'], ['13', 'june 28', 'sacramento', 'w 70 - 66', 'sales ( 19 )', 'mcwilliams - franklin ( 7 )', 'whalen ( 5 )', 'mohegan sun arena 6789', '11 - 2'], ['14', 'june 30', 'minnesota', 'w 71 - 56', 'sales ( 18 )', 'mcwilliams - franklin ( 9 )', 'whalen ( 6 )', 'mohegan sun arena 6869', '12 - 2']] |
stuart appleby | https://en.wikipedia.org/wiki/Stuart_Appleby | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1662630-1.html.csv | count | stuart appleby participated 3 times in the mercedes championships tournament . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'mercedes', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'mercedes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to mercedes .', 'tostr': 'filter_eq { all_rows ; tournament ; mercedes }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tournament ; mercedes } }', 'tointer': 'select the rows whose tournament record fuzzily matches to mercedes . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tournament ; mercedes } } ; 3 } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to mercedes . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; tournament ; mercedes } } ; 3 } = true | select the rows whose tournament record fuzzily matches to mercedes . 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, 'tournament_5': 5, 'mercedes_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', 'tournament_5': 'tournament', 'mercedes_6': 'mercedes', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tournament_5': [0], 'mercedes_6': [0], '3_7': [2]} | ['date', 'tournament', 'winning score', 'margin of victory', 'runner ( s ) - up'] | [['16 mar 1997', 'honda classic', '14 ( 68 + 68 + 67 + 71 = 274 )', '1 stroke', 'michael bradley , payne stewart'], ['7 jun 1998', 'kemper open', '10 ( 70 + 63 + 69 + 72 = 274 )', '1 stroke', 'scott hoch'], ['2 may 1999', 'shell houston open', '9 ( 70 + 68 + 70 + 71 = 279 )', '1 stroke', 'john cook , hal sutton'], ['12 oct 2003', 'las vegas invitational', '31 ( 62 - 68 + 63 + 66 + 69 = 328 )', 'playoff', 'scott mccarron'], ['11 jan 2004', 'mercedes championships', '22 ( 66 + 67 + 66 + 71 = 270 )', '1 stroke', 'vijay singh'], ['9 jan 2005', 'mercedes championships ( 2 )', '21 ( 74 + 64 + 66 + 67 = 271 )', '1 stroke', 'jonathan kaye'], ['8 jan 2006', 'mercedes championships ( 3 )', '8 ( 71 + 72 + 70 + 71 = 284 )', 'playoff', 'vijay singh'], ['23 apr 2006', 'shell houston open ( 2 )', '19 ( 66 + 67 + 69 + 67 = 269 )', '6 strokes', 'bob estes'], ['1 aug 2010', 'greenbrier classic', '22 ( 66 + 68 + 65 + 59 = 258 )', '1 stroke', 'jeff overton']] |
kevin mirocha | https://en.wikipedia.org/wiki/Kevin_Mirocha | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25369796-1.html.csv | comparative | kevin mirocha participated in more races in the 2010 season than the 2009 season . | {'row_1': '5', 'row_2': '4', 'col': '4', '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', 'season', '2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2010 .', 'tostr': 'filter_eq { all_rows ; season ; 2010 }'}, 'races'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season ; 2010 } ; races }', 'tointer': 'select the rows whose season record fuzzily matches to 2010 . take the races record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2009'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose season record fuzzily matches to 2009 .', 'tostr': 'filter_eq { all_rows ; season ; 2009 }'}, 'races'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; season ; 2009 } ; races }', 'tointer': 'select the rows whose season record fuzzily matches to 2009 . take the races record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; season ; 2010 } ; races } ; hop { filter_eq { all_rows ; season ; 2009 } ; races } } = true', 'tointer': 'select the rows whose season record fuzzily matches to 2010 . take the races record of this row . select the rows whose season record fuzzily matches to 2009 . take the races record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; season ; 2010 } ; races } ; hop { filter_eq { all_rows ; season ; 2009 } ; races } } = true | select the rows whose season record fuzzily matches to 2010 . take the races record of this row . select the rows whose season record fuzzily matches to 2009 . take the races 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, 'season_7': 7, '2010_8': 8, 'races_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2009_12': 12, 'races_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', 'season_7': 'season', '2010_8': '2010', 'races_9': 'races', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2009_12': '2009', 'races_13': 'races'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2010_8': [0], 'races_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2009_12': [1], 'races_13': [3]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2007', 'formula bmw adac', 'adac berlin - brandenburg', '18', '0', '0', '0', '1', '389', '8th'], ['2007', 'formula bmw world final', 'josef kaufmann racing', '1', '0', '0', '0', '0', 'n / a', '22nd'], ['2008', 'ats formel 3 cup', 'josef kaufmann racing', '18', '0', '0', '0', '4', '56', '6th'], ['2009', 'formula 3 euro series', 'hbr motorsport', '6', '0', '0', '0', '0', '0', '29th'], ['2010', 'formula renault 2.0 nec', 'sl formula racing', '8', '1', '0', '2', '3', '137', '9th'], ['2011', 'gp2 series', 'ocean racing technology', '14', '0', '0', '0', '0', '0', '22nd']] |
partnership ( cricket ) | https://en.wikipedia.org/wiki/Partnership_%28cricket%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1670921-1.html.csv | superlative | the most runs scored in partnership cricket were by the players from sri lanka . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'runs'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; runs }'}, 'battling team'], 'result': 'sri lanka', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; runs } ; battling team }'}, 'sri lanka'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; runs } ; battling team } ; sri lanka } = true', 'tointer': 'select the row whose runs record of all rows is maximum . the battling team record of this row is sri lanka .'} | eq { hop { argmax { all_rows ; runs } ; battling team } ; sri lanka } = true | select the row whose runs record of all rows is maximum . the battling team record of this row is sri lanka . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'runs_5': 5, 'battling team_6': 6, 'sri lanka_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'runs_5': 'runs', 'battling team_6': 'battling team', 'sri lanka_7': 'sri lanka'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'runs_5': [0], 'battling team_6': [1], 'sri lanka_7': [2]} | ['wicket', 'runs', 'battling partners', 'battling team', 'fielding team', 'venue', 'season'] | [['1st', '415', 'gc smith and neil mckenzie', 'south africa', 'bangladesh', 'chittagong', '2008'], ['2nd', '576', 'roshan mahanama and sanath jayasuriya', 'sri lanka', 'india', 'colombo', '1997'], ['3rd', '624', 'mahela jayawardene and kumar sangakkara', 'sri lanka', 'south africa', 'colombo', '2006'], ['4th', '437', 'mahela jayawardene and thilan samaraweera', 'sri lanka', 'pakistan', 'karachi', '2008 / 09'], ['5th', '405', 'donald bradman and sid barnes', 'australia', 'england', 'sydney', '1946 / 47'], ['6th', '351', 'mahela jayawardene and prasanna jayawardene', 'sri lanka', 'india', 'ahmedabad', '2009 / 10'], ['7th', '347', 'clairmonte depeiaza and denis atkinson', 'west indies', 'australia', 'bridgetown', '1954 / 55'], ['8th', '332', 'jonathan trott and stuart broad', 'england', 'pakistan', "lord 's", '2010'], ['9th', '195', 'pat symcox and mark boucher', 'south africa', 'pakistan', 'johannesburg', '1997 / 98'], ['10th', '163', 'phillip hughes and ashton agar', 'australia', 'england', 'nottingham', '2013']] |
the magician ( 2006 film ) | https://en.wikipedia.org/wiki/The_Magician_%282006_film%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14674285-1.html.csv | aggregation | the 2006 film , the magician was screened on 461 total screens . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '461', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'screens'], 'result': '461', 'ind': 0, 'tostr': 'sum { all_rows ; screens }'}, '461'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; screens } ; 461 } = true', 'tointer': 'the sum of the screens record of all rows is 461 .'} | round_eq { sum { all_rows ; screens } ; 461 } = true | the sum of the screens record of all rows is 461 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'screens_4': 4, '461_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'screens_4': 'screens', '461_5': '461'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'screens_4': [0], '461_5': [1]} | ['date', 'territory', 'screens', 'rank', 'gross'] | [['october 20 , 2006', 'turkey', '378', '1', '1462608'], ['october 25 , 2006', 'belgium', '6', '19', '38916'], ['october 26 , 2006', 'germany', '52', '12', '198149'], ['october 26 , 2006', 'austria', '4', '13', '41780'], ['october 26 , 2006', 'netherlands', '17', '14', '53749'], ['october 27 , 2006', 'united kingdom', '4', '24', '34704']] |
new year 's revolution ( 2006 ) | https://en.wikipedia.org/wiki/New_Year%27s_Revolution_%282006%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14656943-2.html.csv | majority | most of the wrestlers were eliminated by carlito at the 2006 new year 's revolution . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'carlito', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'eliminated by', 'carlito'], 'result': True, 'ind': 0, 'tointer': 'for the eliminated by records of all rows , most of them fuzzily match to carlito .', 'tostr': 'most_eq { all_rows ; eliminated by ; carlito } = true'} | most_eq { all_rows ; eliminated by ; carlito } = true | for the eliminated by records of all rows , most of them fuzzily match to carlito . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'eliminated by_3': 3, 'carlito_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'eliminated by_3': 'eliminated by', 'carlito_4': 'carlito'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'eliminated by_3': [0], 'carlito_4': [0]} | ['elimination no', 'wrestler', 'entered', 'eliminated by', 'time'] | [['1', 'kurt angle', '4', 'michaels', '13:58'], ['2', 'kane', '6', 'carlito and masters', '19:24'], ['3', 'shawn michaels', '1', 'carlito', '23:35'], ['4', 'chris masters', '5', 'carlito', '28:15'], ['5', 'carlito', '3', 'cena', '28:22'], ['winner', 'john cena', '2', 'n / a', 'n / a']] |
2007 - 08 guildford flames season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Guildford_Flames_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15213262-9.html.csv | majority | in the 2007-08 season the guildford flames won the majority of the games listed . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'won', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to won .', 'tostr': 'most_eq { all_rows ; result ; won } = true'} | most_eq { all_rows ; result ; won } = true | for the result records of all rows , most of them fuzzily match to won . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'won_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'won_4': 'won'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'won_4': [0]} | ['date', 'opponent', 'venue', 'result', 'attendance', 'competition'] | [['1', 'peterborough phantoms', 'home', 'won 6 - 1', '1421', 'league'], ['2', 'peterborough phantoms', 'away', 'won 3 - 2 ( so )', '443', 'league'], ['8', 'swindon wildcats', 'away', 'won 3 - 2', '790', 'knockout cup'], ['9', 'chelmsford chieftains', 'away', 'won 5 - 3', '423', 'league'], ['15', 'sheffield scimitars', 'away', 'won 5 - 3', '351', 'league'], ['16', 'swindon wildcats', 'home', 'won 3 - 1', '1244', 'knockout cup'], ['22', 'romford raiders', 'home', 'won 5 - 2', '1551', 'knockout cup'], ['23', 'romford raiders', 'away', 'lost 2 - 6', 'unknown', 'league'], ['26', 'milton keynes lightning', 'home', 'won 4 - 3', '1228', 'premier cup'], ['29', 'chelmsford chieftains', 'home', 'won 5 - 0', '1117', 'league'], ['30', 'slough jets', 'home', 'won 4 - 3', '1921', 'league']] |
2003 u.s. bank cleveland grand prix | https://en.wikipedia.org/wiki/2003_U.S._Bank_Cleveland_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18943126-1.html.csv | count | at the 2003 u.s. bank cleveland grand prix , there were 2 competitors from american spirit team johansson . | {'scope': 'all', 'criterion': 'equal', 'value': 'american spirit team johansson', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'american spirit team johansson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to american spirit team johansson .', 'tostr': 'filter_eq { all_rows ; team ; american spirit team johansson }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; american spirit team johansson } }', 'tointer': 'select the rows whose team record fuzzily matches to american spirit team johansson . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; american spirit team johansson } } ; 2 } = true', 'tointer': 'select the rows whose team record fuzzily matches to american spirit team johansson . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; team ; american spirit team johansson } } ; 2 } = true | select the rows whose team record fuzzily matches to american spirit team johansson . 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, 'team_5': 5, 'american spirit team johansson_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', 'team_5': 'team', 'american spirit team johansson_6': 'american spirit team johansson', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'american spirit team johansson_6': [0], '2_7': [2]} | ['name', 'team', 'qual 1', 'qual 2', 'best'] | [['sébastien bourdais', 'newman / haas racing', '59.163', '58.014', '58.014'], ['paul tracy', "team player 's", '58.405', '1:01.294', '58.405'], ['patrick carpentier', "team player 's", '58.868', '58.449', '58.449'], ['oriol servià', 'patrick racing', '59.186', '58.502', '58.502'], ['bruno junqueira', 'newman / haas racing', '59.804', '58.506', '58.506'], ['michel jourdain , jr', 'team rahal', '59.223', '58.700', '58.700'], ['alex tagliani', 'rocketsports racing', '59.247', '58.718', '58.718'], ['mario domínguez', 'herdez competition', '59.535', '58.724', '58.724'], ['roberto moreno', 'herdez competition', '59.954', '58.845', '58.845'], ['jimmy vasser', 'american spirit team johansson', '59.382', '58.861', '58.861'], ['ryan hunter - reay', 'american spirit team johansson', '59.989', '59.073', '59.073'], ['mario haberfeld', 'mi - jack conquest racing', '1:00.333', '59.141', '59.141'], ['darren manning', 'walker racing', '59.776', '59.167', '59.167'], ['adrian fernández', 'fernández racing', '59.340', '59.306', '59.306'], ['rodolfo lavín', 'walker racing', '1:00.670', '59.531', '59.531'], ['tiago monteiro', 'fittipaldi - dingman racing', '1:00.003', '59.822', '59.822'], ['gualter salles', 'dale coyne racing', '1:01.778', '59.968', '59.968'], ['max papis', 'pk racing', '1:00.020', '1:00.080', '1:00.020'], ['geoff boss', 'dale coyne racing', '1:01.103', '1:01.525', '1:01.103']] |
list of via c3 microprocessors | https://en.wikipedia.org/wiki/List_of_VIA_C3_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16341329-2.html.csv | ordinal | the second highest frequency that any of the models had was 933 mhz . | {'row': '8', 'col': '2', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'frequency', '2'], 'result': '933 mhz', 'ind': 0, 'tostr': 'nth_max { all_rows ; frequency ; 2 }', 'tointer': 'the 2nd maximum frequency record of all rows is 933 mhz .'}, '933 mhz'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; frequency ; 2 } ; 933 mhz } = true', 'tointer': 'the 2nd maximum frequency record of all rows is 933 mhz .'} | eq { nth_max { all_rows ; frequency ; 2 } ; 933 mhz } = true | the 2nd maximum frequency record of all rows is 933 mhz . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_max_0': 0, 'all_rows_3': 3, 'frequency_4': 4, '2_5': 5, '933 mhz_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_max_0': 'nth_max', 'all_rows_3': 'all_rows', 'frequency_4': 'frequency', '2_5': '2', '933 mhz_6': '933 mhz'} | {'eq_1': [2], 'result_2': [], 'nth_max_0': [1], 'all_rows_3': [0], 'frequency_4': [0], '2_5': [0], '933 mhz_6': [1]} | ['model number', 'frequency', 'l2 - cache', 'front side bus', 'multiplier', 'voltage', 'socket'] | [['c3 800', '800 mhz', '64 kib', '100 mhz', '8', '1.35 v', 'socket 370'], ['c3 800', '800 mhz', '64 kib', '133 mhz', '6', '1.35 v', 'socket 370'], ['c3 800t', '800 mhz', '64kib', '133 mhz', '6', '1.35 v', 'socket 370'], ['c3 850', '850 mhz', '64kib', '100 mhz', '8.5', '1.35 v', 'socket 370'], ['c3 866', '866 mhz', '64 kib', '133 mhz', '6.5', '1.35 v', 'socket 370'], ['c3 866t', '866 mhz', '64 kib', '133 mhz', '6.5', '1.35 v', 'socket 370'], ['c3 900', '900 mhz', '64kib', '100 mhz', '9', '1.35 v', 'socket 370'], ['c3 933t', '933 mhz', '64kib', '133 mhz', '7', '1.35 v', 'socket 370'], ['c3 1.0 t', '1000 mhz', '64kib', '133 mhz', '7.5', '1.35 v', 'socket 370']] |
being human ( tv series ) | https://en.wikipedia.org/wiki/Being_Human_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15823956-1.html.csv | count | the majority of series numbers of the being human tv show had eight episodes . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '8', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'episodes', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episodes record is greater than or equal to 8 .', 'tostr': 'filter_greater_eq { all_rows ; episodes ; 8 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; episodes ; 8 } }', 'tointer': 'select the rows whose episodes record is greater than or equal to 8 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; episodes ; 8 } } ; 3 } = true', 'tointer': 'select the rows whose episodes record is greater than or equal to 8 . the number of such rows is 3 .'} | eq { count { filter_greater_eq { all_rows ; episodes ; 8 } } ; 3 } = true | select the rows whose episodes record is greater than or equal to 8 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'episodes_5': 5, '8_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'episodes_5': 'episodes', '8_6': '8', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'episodes_5': [0], '8_6': [0], '3_7': [2]} | ['series', 'episodes', 'series premiere', 'series finale', 'region 1', 'region 2', 'region 4'] | [['pilot', '1', '18 february 2008', '18 february 2008', 'n / a', 'n / a', 'n / a'], ['1', '6', '25 january 2009', '1 march 2009', '20 july 2010', '20 april 2009', '6 august 2009'], ['2', '8', '10 january 2010', '28 february 2010', '21 september 2010', '12 april 2010', '5 august 2010'], ['3', '8', '23 january 2011', '13 march 2011', '3 may 2011', '28 march 2011', '5 may 2011'], ['4', '8', '5 february 2012', '25 march 2012', '15 january 2013', '23 april 2012', '7 june 2012']] |
1984 - 85 boston celtics season | https://en.wikipedia.org/wiki/1984%E2%80%9385_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17344651-6.html.csv | unique | game 45 was the only game that the boston celtics played at the hartford civic center . | {'scope': 'all', 'row': '13', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'hartford civic center', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'hartford civic center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to hartford civic center .', 'tostr': 'filter_eq { all_rows ; location ; hartford civic center }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; hartford civic center } }', 'tointer': 'select the rows whose location record fuzzily matches to hartford civic center . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'hartford civic center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to hartford civic center .', 'tostr': 'filter_eq { all_rows ; location ; hartford civic center }'}, 'game'], 'result': '45', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; hartford civic center } ; game }'}, '45'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; hartford civic center } ; game } ; 45 }', 'tointer': 'the game record of this unqiue row is 45 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; hartford civic center } } ; eq { hop { filter_eq { all_rows ; location ; hartford civic center } ; game } ; 45 } } = true', 'tointer': 'select the rows whose location record fuzzily matches to hartford civic center . there is only one such row in the table . the game record of this unqiue row is 45 .'} | and { only { filter_eq { all_rows ; location ; hartford civic center } } ; eq { hop { filter_eq { all_rows ; location ; hartford civic center } ; game } ; 45 } } = true | select the rows whose location record fuzzily matches to hartford civic center . there is only one such row in the table . the game record of this unqiue row is 45 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'hartford civic center_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'game_9': 9, '45_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'hartford civic center_8': 'hartford civic center', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'game_9': 'game', '45_10': '45'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'hartford civic center_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'game_9': [2], '45_10': [3]} | ['game', 'date', 'opponent', 'score', 'location', 'record'] | [['33', 'wed jan 2', 'new jersey nets', '110 - 95', 'brendan byrne arena', '27 - 6'], ['34', 'fri jan 4', 'new york knicks', '105 - 94', 'boston garden', '28 - 6'], ['35', 'mon jan 7', 'new york knicks', '108 - 97', 'madison square garden', '29 - 6'], ['36', 'wed jan 9', 'chicago bulls', '111 - 108', 'boston garden', '30 - 6'], ['37', 'fri jan 11', 'washington bullets', '103 - 101', 'boston garden', '31 - 6'], ['38', 'sat jan 12', 'atlanta hawks', '119 - 111', 'the omni', '32 - 6'], ['39', 'wed jan 16', 'los angeles lakers', '104 - 102', 'boston garden', '33 - 6'], ['40', 'fri jan 18', 'indiana pacers', '86 - 91', 'market square arena', '33 - 7'], ['41', 'sun jan 20', 'philadelphia 76ers', '113 - 97', 'boston garden', '34 - 7'], ['42', 'wed jan 23', 'seattle supersonics', '97 - 107', 'boston garden', '34 - 8'], ['43', 'fri jan 25', 'indiana pacers', '125 - 94', 'boston garden', '35 - 8'], ['44', 'sun jan 27', 'portland trail blazers', '128 - 127', 'boston garden', '36 - 8'], ['45', 'tue jan 29', 'detroit pistons', '131 - 130', 'hartford civic center', '37 - 8'], ['46', 'wed jan 30', 'philadelphia 76ers', '104 - 122', 'the spectrum', '37 - 9']] |
winston parks | https://en.wikipedia.org/wiki/Winston_Parks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1272045-1.html.csv | majority | the majority of winston parks ' goals were in competitions that are in the category of friendly competitions . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friendly', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to friendly .', 'tostr': 'most_eq { all_rows ; competition ; friendly } = true'} | most_eq { all_rows ; competition ; friendly } = true | for the competition records of all rows , most of them fuzzily match to friendly . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', '17 april 2002', '1 - 1', '1 - 1', 'friendly'], ['2', '9 june 2002', '1 - 1', '1 - 1', '2002 fifa world cup'], ['3', '29 march 2003', '2 - 1', '2 - 1', 'friendly'], ['4', '4 june 2004', '2 - 0', '5 - 1', 'friendly'], ['5', '4 june 2004', '4 - 0', '5 - 1', 'friendly'], ['6', '1 june 2010', '0 - 1', '0 - 1', 'friendly']] |
silent witness | https://en.wikipedia.org/wiki/Silent_Witness | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-143678-3.html.csv | superlative | professor leo dalton was the character who appeared in the most episodes of " silent witness . " . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', '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', 'episode count'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; episode count }'}, 'character'], 'result': 'professor leo dalton', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; episode count } ; character }'}, 'professor leo dalton'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; episode count } ; character } ; professor leo dalton } = true', 'tointer': 'select the row whose episode count record of all rows is maximum . the character record of this row is professor leo dalton .'} | eq { hop { argmax { all_rows ; episode count } ; character } ; professor leo dalton } = true | select the row whose episode count record of all rows is maximum . the character record of this row is professor leo dalton . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'episode count_5': 5, 'character_6': 6, 'professor leo dalton_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'episode count_5': 'episode count', 'character_6': 'character', 'professor leo dalton_7': 'professor leo dalton'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'episode count_5': [0], 'character_6': [1], 'professor leo dalton_7': [2]} | ['character', 'actor', 'years', 'series', 'episode count'] | [['dr nikki alexander', 'emilia fox', '2004 -', '8.5 -', '86'], ['dr jack hodgson', 'david caves', '2013 -', '16.1 -', '10'], ['dr clarissa mullery', 'liz carr', '2013 -', '16.1 -', '10'], ['dr thomas chamberlain', 'richard lintern', '2014 -', '17 . -', '0'], ['professor sam ryan', 'amanda burton', '1996 - 2004', '1.1 - 8.2', '54'], ['professor leo dalton', 'william gaminara', '2002 - 2013', '6.1 - 16.10', '106'], ['dr harry cunningham', 'tom ward', '2002 - 2012', '6.1 - 15.10', '96'], ['dr trevor stewart', 'william armstrong', '1996 - 1998', '1.1 - 3.8', '24']] |
franck lagorce | https://en.wikipedia.org/wiki/Franck_Lagorce | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1228355-3.html.csv | superlative | the competition that had the greatest number of laps was the race in 2003 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '10', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'laps'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; laps }'}, 'year'], 'result': '2003', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; laps } ; year }'}, '2003'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; laps } ; year } ; 2003 } = true', 'tointer': 'select the row whose laps record of all rows is maximum . the year record of this row is 2003 .'} | eq { hop { argmax { all_rows ; laps } ; year } ; 2003 } = true | select the row whose laps record of all rows is maximum . the year record of this row is 2003 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'laps_5': 5, 'year_6': 6, '2003_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'laps_5': 'laps', 'year_6': 'year', '2003_7': '2003'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'laps_5': [0], 'year_6': [1], '2003_7': [2]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1994', 'courage compétition', 'henri pescarolo alain ferté', 'lmp1 c90', '142', 'dnf', 'dnf'], ['1995', 'courage compétition', 'henri pescarolo éric bernard', 'wsc', '26', 'dnf', 'dnf'], ['1996', 'la filière elf', 'henri pescarolo emmanuel collard', 'lmp1', '327', '7th', '2nd'], ['1997', 'dams', 'éric bernard jean - christophe boullion', 'gt1', '149', 'dnf', 'dnf'], ['1998', 'nissan motorsports twr', 'john nielsen michael krumm', 'gt1', '342', '5th', '5th'], ['1999', 'amg - mercedes', 'bernd schneider pedro lamy', 'lmgtp', '76', 'dnf', 'dnf'], ['2000', 'team cadillac', 'butch leitzinger andy wallace', 'lmp900', '291', '21st', '11th'], ['2001', 'panoz motorsports', 'david brabham jan magnussen', 'lmp900', '85', 'dnf', 'dnf'], ['2002', 'pescarolo sport', 'sébastien bourdais jean - christophe boullion', 'lmp900', '343', '10th', '9th'], ['2003', 'pescarolo sport', 'stéphane sarrazin jean - christophe boullion', 'lmp900', '356', '8th', '6th']] |
prr locomotive classification | https://en.wikipedia.org/wiki/PRR_locomotive_classification | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140522-5.html.csv | aggregation | a total number of 229 pennsylvania railroad class locomotives were produced . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '229', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total produced'], 'result': '229', 'ind': 0, 'tostr': 'sum { all_rows ; total produced }'}, '229'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total produced } ; 229 } = true', 'tointer': 'the sum of the total produced record of all rows is 229 .'} | round_eq { sum { all_rows ; total produced } ; 229 } = true | the sum of the total produced record of all rows is 229 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total produced_4': 4, '229_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total produced_4': 'total produced', '229_5': '229'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total produced_4': [0], '229_5': [1]} | ['prr class', 'builders model', 'build date', 'total produced', 'wheel arrangement', 'service', 'power output'] | [['fs10', 'h10 - 44', '1948 - 1949', '55', 'b - b', 'switcher', ''], ['fs12', 'h12 - 44', '1952 - 1954', '16', 'b - b', 'switcher', ''], ['ff20', 't erie buil', '1947 - 1948', '36', 'a1a - a1a', 'freight', ''], ['ff20', 'erie built', '1947 - 1948', '12', 'a1a - a1a', 'freight', ''], ['ff16', 'cf - 16 - 4', '1950', '16', 'b - b', 'freight', ''], ['ff16', 'cf - 16 - 4', '1950', '8', 'b - b', 'freight', ''], ['frs - 16', 'h16 - 44', '1952', '10', 'b - b', 'freight', ''], ['frs - 20', 'h20 - 44', '1948 - 1951', '38', 'b - b', 'freight', ''], ['frs - 24', 'h24 - 66', '1948 - 1951', '38', 'c - c', 'freight', '']] |
1953 green bay packers season | https://en.wikipedia.org/wiki/1953_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14656212-2.html.csv | unique | the green bay packers tied only once in the 1953 season . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 't', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 't'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to t .', 'tostr': 'filter_eq { all_rows ; result ; t }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; t } } = true', 'tointer': 'select the rows whose result record fuzzily matches to t . there is only one such row in the table .'} | only { filter_eq { all_rows ; result ; t } } = true | select the rows whose result record fuzzily matches to t . 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, 'result_4': 4, 't_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'result_4': 'result', 't_5': 't'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'result_4': [0], 't_5': [0]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance'] | [['1', 'september 27 , 1953', 'cleveland browns', 'l 27 - 0', 'milwaukee county stadium', '22604'], ['2', 'october 4 , 1953', 'chicago bears', 'l 17 - 13', 'city stadium', '24835'], ['3', 'october 11 , 1953', 'los angeles rams', 'l 38 - 20', 'milwaukee county stadium', '23353'], ['4', 'october 18 , 1953', 'baltimore colts', 'w 37 - 14', 'city stadium', '18713'], ['5', 'october 24 , 1953', 'pittsburgh steelers', 'l 31 - 14', 'forbes field', '22918'], ['6', 'october 31 , 1953', 'baltimore colts', 'w 35 - 24', 'memorial stadium', '33797'], ['7', 'november 8 , 1953', 'chicago bears', 't 21 - 21', 'wrigley field', '39889'], ['8', 'november 15 , 1953', 'detroit lions', 'l 14 - 7', 'city stadium', '20834'], ['9', 'november 22 , 1953', 'san francisco 49ers', 'l 37 - 7', 'milwaukee county stadium', '16378'], ['10', 'november 26 , 1953', 'detroit lions', 'l 34 - 15', 'briggs stadium', '52607'], ['11', 'december 6 , 1953', 'san francisco 49ers', 'l 48 - 14', 'kezar stadium', '31337'], ['12', 'december 12 , 1953', 'los angeles rams', 'l 33 - 17', 'los angeles memorial coliseum', '23069']] |
2002 miami dolphins season | https://en.wikipedia.org/wiki/2002_Miami_Dolphins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18925638-1.html.csv | superlative | the match on november 10 , 2002 had the highest attendance of all the matches . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '9', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'november 10 , 2002', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'november 10 , 2002'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; november 10 , 2002 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is november 10 , 2002 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; november 10 , 2002 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is november 10 , 2002 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'november 10 , 2002_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', 'date_6': 'date', 'november 10 , 2002_7': 'november 10 , 2002'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'november 10 , 2002_7': [2]} | ['week', 'date', 'opponent', 'result', 'tv time', 'attendance'] | [['1', 'september 8 , 2002', 'detroit lions', 'w 49 - 21', 'fox 1:00 pm', '72216'], ['2', 'september 15 , 2002', 'indianapolis colts', 'w 21 - 13', 'cbs 1:00 pm', '56650'], ['3', 'september 22 , 2002', 'new york jets', 'w 30 - 3', 'cbs 1:00 pm', '73426'], ['4', 'september 29 , 2002', 'kansas city chiefs', 'l 48 - 30', 'cbs 1:00 pm', '78178'], ['5', 'october 6 , 2002', 'new england patriots', 'w 26 - 13', 'cbs 1:00 pm', '73369'], ['6', 'october 13 , 2002', 'denver broncos', 'w 24 - 22', 'espn 8:30 pm', '75941'], ['7', 'october 20 , 2002', 'buffalo bills', 'l 23 - 10', 'cbs 1:00 pm', '73180'], ['9', 'november 4 , 2002', 'green bay packers', 'l 24 - 10', 'abc 9:00 pm', '63284'], ['10', 'november 10 , 2002', 'new york jets', 'l 13 - 10', 'espn 8:30 pm', '78920'], ['11', 'november 17 , 2002', 'baltimore ravens', 'w 26 - 7', 'cbs 4:15 pm', '73013'], ['12', 'november 24 , 2002', 'san diego chargers', 'w 30 - 3', 'cbs 1:00 pm', '73138'], ['13', 'december 1 , 2002', 'buffalo bills', 'l 38 - 21', 'cbs 1:00 pm', '73287'], ['14', 'december 9 , 2002', 'chicago bears', 'w 27 - 9', 'abc 9:00 pm', '73609'], ['15', 'december 15 , 2002', 'oakland raiders', 'w 23 - 17', 'cbs 1:00 pm', '73572'], ['16', 'december 21 , 2002', 'minnesota vikings', 'l 20 - 17', 'cbs 12:30 pm', '64285'], ['17', 'december 29 , 2002', 'new england patriots', 'l 27 - 24', 'cbs 1:00 pm', '68436']] |
1970 isle of man tt | https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-5.html.csv | aggregation | the average speed of the riders during the 1970 isle of man tt was 92.14 mph . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '92.14', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'speed'], 'result': '92.14', 'ind': 0, 'tostr': 'avg { all_rows ; speed }'}, '92.14'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; speed } ; 92.14 } = true', 'tointer': 'the average of the speed record of all rows is 92.14 .'} | round_eq { avg { all_rows ; speed } ; 92.14 } = true | the average of the speed record of all rows is 92.14 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'speed_4': 4, '92.14_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'speed_4': 'speed', '92.14_5': '92.14'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'speed_4': [0], '92.14_5': [1]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'kel carruthers', 'australia', 'yamaha', '96.13 mph', '2:21.19.2', '15'], ['2', 'rod gould', 'united kingdom', 'yamaha', '93.75 mph', '2:24.54.0', '12'], ['3', 'günter bartusch', 'east germany', 'mz', '93.75 mph', '2:26.58.0', '10'], ['4', 'chas mortimer', 'united kingdom', 'yamaha', '91.95 mph', '2:27.44.2', '8'], ['5', 'peter berwick', 'united kingdom', 'suzuki', '91.93 mph', '2:27.46.0', '6'], ['6', 'alex george', 'united kingdom', 'yamaha', '91.42 mph', '2:28.35.8', '5'], ['7', 'ian richardson', 'united kingdom', 'yamaha', '91.22 mph', '2:28.53.6', '4'], ['8', 'börje jansson', 'sweden', 'yamaha', '90.57 mph', '2:29.59.6', '3'], ['9', 'tony smith', 'united kingdom', 'yamaha', '90.44 mph', '2:30.12.2', '2'], ['10', 'bill smith', 'united kingdom', 'yamaha', '90.20 mph', '2:30.36.2', '1']] |
emily hewson | https://en.wikipedia.org/wiki/Emily_Hewson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15272495-4.html.csv | count | in emily hewson 's tennis career , six of the doubles tennis games took place in australia . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'australia', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; tournament ; australia }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tournament ; australia } }', 'tointer': 'select the rows whose tournament record fuzzily matches to australia . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tournament ; australia } } ; 6 } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to australia . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; tournament ; australia } } ; 6 } = true | select the rows whose tournament record fuzzily matches to australia . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'tournament_5': 5, 'australia_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'tournament_5': 'tournament', 'australia_6': 'australia', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tournament_5': [0], 'australia_6': [0], '6_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score'] | [['runner - up', '13 may 2001', 'swansea , wales', 'clay', 'maria bobedova', 'natalia egorova ekaterina sysoeva', '6 - 4 6 - 7 ( 5 - 7 ) 0 - 6'], ['runner - up', '27 may 2001', 'tel aviv , israel', 'hard', 'natasha van der merwe', 'irina kornienko maria pavlidou', 'w / o'], ['runner - up', '5 august 2001', 'dublin , ireland', 'carpet', 'bree calderwood', 'yvonne doyle karen nugent', '4 - 6 2 - 6'], ['runner - up', '21 march 2004', 'wellington , new zealand', 'grass', 'nicole kriz', 'shelley bryce kristen van elden', '1 - 6 6 - 3 3 - 6'], ['runner - up', '21 march 2004', 'yarrawonga , australia', 'grass', 'nicole kriz', 'beti sekulovski cindy watson', '3 - 6 6 - 4 4 - 6'], ['winner', '28 march 2004', 'yarrawonga , australia', 'grass', 'nicole kriz', 'mirielle dittmann kristen van elden', '6 - 3 6 - 2'], ['runner - up', '20 march 2005', 'yarrawonga , australia', 'grass', 'nicole kriz', 'lara picone julia efremova', '4 - 6 3 - 6'], ['winner', '16 march 2007', 'perth , australia', 'hard', 'casey dellacqua', 'trudi musgrave christina wheeler', '6 - 4 4 - 6 6 - 2'], ['winner', '23 march 2007', 'kalgoorlie , australia', 'grass', 'christina wheeler', 'vivien silfany - tony lavinia tananta', '6 - 4 6 - 3'], ['runner - up', '9 november 2007', 'port pirie , australia', 'hard', 'daniella dominikovic', 'sarah borwell courtney nagle', '2 - 6 2 - 6'], ['winner', '23 august 2008', 'trecastagni , italy', 'hard', 'pemra özgen', 'valeria casillo lilly raffa', 'w / o']] |
1977 st. louis cardinals ( nfl ) season | https://en.wikipedia.org/wiki/1977_St._Louis_Cardinals_%28NFL%29_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16678300-2.html.csv | aggregation | for the st. louis cardinals 1977 season the total attendance was 764271 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '764271', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '764271', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '764271'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 764271 } = true', 'tointer': 'the sum of the attendance record of all rows is 764271 .'} | round_eq { sum { all_rows ; attendance } ; 764271 } = true | the sum of the attendance record of all rows is 764271 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '764271_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '764271_5': '764271'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '764271_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 18 , 1977', 'denver broncos', 'l 7 - 0', '75002'], ['2', 'september 25 , 1977', 'chicago bears', 'w 16 - 13', '49878'], ['3', 'october 2 , 1977', 'washington redskins', 'l 24 - 14', '55031'], ['4', 'october 9 , 1977', 'dallas cowboys', 'l 30 - 24', '50129'], ['5', 'october 16 , 1977', 'philadelphia eagles', 'w 21 - 17', '60535'], ['6', 'october 23 , 1977', 'new orleans saints', 'w 49 - 31', '48417'], ['7', 'october 31 , 1977', 'new york giants', 'w 28 - 0', '50323'], ['8', 'november 6 , 1977', 'minnesota vikings', 'w 27 - 7', '47066'], ['9', 'november 14 , 1977', 'dallas cowboys', 'w 24 - 17', '64038'], ['10', 'november 20 , 1977', 'philadelphia eagles', 'w 21 - 16', '48768'], ['11', 'november 24 , 1977', 'miami dolphins', 'l 55 - 14', '50269'], ['12', 'december 4 , 1977', 'new york giants', 'l 27 - 7', '71826'], ['13', 'december 10 , 1977', 'washington redskins', 'l 26 - 20', '36067'], ['14', 'december 18 , 1977', 'tampa bay buccaneers', 'l 17 - 7', '56922']] |
2007 - 08 perth glory season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Perth_Glory_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10866507-1.html.csv | superlative | port macquarie regional stadium was the first stadium to be used during the 2007 - 08 perth glory season . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '7', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'stadium'], 'result': 'port macquarie regional stadium', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; stadium }'}, 'port macquarie regional stadium'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; stadium } ; port macquarie regional stadium } = true', 'tointer': 'select the row whose date record of all rows is minimum . the stadium record of this row is port macquarie regional stadium .'} | eq { hop { argmin { all_rows ; date } ; stadium } ; port macquarie regional stadium } = true | select the row whose date record of all rows is minimum . the stadium record of this row is port macquarie regional stadium . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'stadium_6': 6, 'port macquarie regional stadium_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'stadium_6': 'stadium', 'port macquarie regional stadium_7': 'port macquarie regional stadium'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'stadium_6': [1], 'port macquarie regional stadium_7': [2]} | ['round', 'date', 'home team', 'score', 'away team', 'crowd', 'stadium'] | [['1', '14 july 2007', 'newcastle jets', '0 - 1', 'perth glory', '2700', 'port macquarie regional stadium'], ['2', '20 july 2007', 'adelaide united', '1 - 1', 'perth glory', '3513', 'hindmarsh stadium'], ['3', '28 july 2007', 'perth glory', '2 - 1', 'melbourne victory', '2700', 'darwin football stadium'], ['sf', '4 august 2007', 'central coast mariners', '2 - 3', 'perth glory', '5967', 'bluetongue central coast stadium'], ['gf', '12 august 2007', 'adelaide united', '2 - 1', 'perth glory', '9606', 'hindmarsh stadium']] |
jaime melo | https://en.wikipedia.org/wiki/Jaime_Melo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10251937-1.html.csv | superlative | jaime melo has the lowest number of laps with co - drivers gianmaria bruni and pierre kaffer . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'laps'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; laps }'}, 'co - drivers'], 'result': 'gianmaria bruni pierre kaffer', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; laps } ; co - drivers }'}, 'gianmaria bruni pierre kaffer'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; laps } ; co - drivers } ; gianmaria bruni pierre kaffer } = true', 'tointer': 'select the row whose laps record of all rows is minimum . the co - drivers record of this row is gianmaria bruni pierre kaffer .'} | eq { hop { argmin { all_rows ; laps } ; co - drivers } ; gianmaria bruni pierre kaffer } = true | select the row whose laps record of all rows is minimum . the co - drivers record of this row is gianmaria bruni pierre kaffer . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'laps_5': 5, 'co - drivers_6': 6, 'gianmaria bruni pierre kaffer_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'laps_5': 'laps', 'co - drivers_6': 'co - drivers', 'gianmaria bruni pierre kaffer_7': 'gianmaria bruni pierre kaffer'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'laps_5': [0], 'co - drivers_6': [1], 'gianmaria bruni pierre kaffer_7': [2]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2004', 'jmb racing', 'jean - rené de fornoux stéphane daoudi', 'gt', '133', 'dnf', 'dnf'], ['2007', 'risi competizione', 'mika salo johnny mowlem', 'gt2', '223', 'dnf', 'dnf'], ['2008', 'risi competizione', 'gianmaria bruni mika salo', 'gt2', '326', '19th', '1st'], ['2009', 'risi competizione', 'pierre kaffer mika salo', 'gt2', '329', '18th', '1st'], ['2010', 'risi competizione', 'gianmaria bruni pierre kaffer', 'gt2', '116', 'dnf', 'dnf'], ['2011', 'luxury racing', 'stéphane ortelli frédéric makowiecki', 'gte pro', '183', 'dnf', 'dnf'], ['2012', 'luxury racing', 'frédéric makowiecki dominik farnbacher', 'gte pro', '333', '18th', '2nd']] |
inbee park | https://en.wikipedia.org/wiki/Inbee_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18198579-6.html.csv | aggregation | the average number of yearly tournaments played by inbee park is 16.1 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '16.1', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'tournaments played'], 'result': '16.1', 'ind': 0, 'tostr': 'avg { all_rows ; tournaments played }'}, '16.1'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; tournaments played } ; 16.1 } = true', 'tointer': 'the average of the tournaments played record of all rows is 16.1 .'} | round_eq { avg { all_rows ; tournaments played } ; 16.1 } = true | the average of the tournaments played record of all rows is 16.1 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'tournaments played_4': 4, '16.1_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'tournaments played_4': 'tournaments played', '16.1_5': '16.1'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'tournaments played_4': [0], '16.1_5': [1]} | ['year', 'tournaments played', 'cuts made', 'wins', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank'] | [['2004', '2', '1', '0', '1', 't8', 'n / a', 'n / a', '72.60', 'n / a'], ['2005', '2', '1', '0', '1', '5', 'n / a', 'n / a', '71.00', 'n / a'], ['2006', '2', '2', '0', '0', 't35', '5406', 'n / a', '73.86', 'n / a'], ['2007', '26', '18', '0', '2', 't2', '380263', '37', '73.19', '72'], ['2008', '26', '22', '1', '7', '1', '1138370', '8', '71.78', '26'], ['2009', '23', '16', '0', '2', 't5', '271303', '50', '72.55', '67'], ['2010', '19', '19', '0', '11', '2', '825477', '11', '70.83', '9'], ['2011', '16', '15', '0', '3', 't6', '365231', '31', '72.00', '27'], ['2012', '24', '23', '2', '12', '1', '2287080', '1', '70.21', '1'], ['2013', '21', '20', '6', '9', '1', '2335460', '1', '69.934', '3'], ['totals', '161', '137', '9', '46', 'n / a', '7603184', 'n / a', 'n / a', 'n / a']] |
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