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new democratic party candidates , 2008 canadian federal election | https://en.wikipedia.org/wiki/New_Democratic_Party_candidates%2C_2008_Canadian_federal_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10953705-9.html.csv | ordinal | pat martin received the third highest number of votes among new democratic party candidates . | {'row': '11', 'col': '6', 'order': '3', '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', 'votes', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; votes ; 3 }'}, 'candidate'], 'result': 'pat martin', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; votes ; 3 } ; candidate }'}, 'pat martin'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; votes ; 3 } ; candidate } ; pat martin } = true', 'tointer': 'select the row whose votes record of all rows is 3rd maximum . the candidate record of this row is pat martin .'} | eq { hop { nth_argmax { all_rows ; votes ; 3 } ; candidate } ; pat martin } = true | select the row whose votes record of all rows is 3rd maximum . the candidate record of this row is pat martin . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'votes_5': 5, '3_6': 6, 'candidate_7': 7, 'pat martin_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', 'votes_5': 'votes', '3_6': '3', 'candidate_7': 'candidate', 'pat martin_8': 'pat martin'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'votes_5': [0], '3_6': [0], 'candidate_7': [1], 'pat martin_8': [2]} | ['riding', 'candidate', 'gender', 'residence', 'occupation', 'votes', 'rank'] | [['brandon-souris', 'jean luc bouché', 'm', 'brandon', 'locomotive engineer', '6055', '2nd'], ['charleswood-st james-assiniboia', 'fiona shiells', 'f', 'winnipeg', 'ministerial assistant', '7190', '3rd'], ['churchill', 'niki ashton', 'f', 'thompson', 'researcher', '8734', '1st'], ['dauphin-swan river-marquette', 'ron strynadka', 'm', 'birtle', 'retired', '4914', '2nd'], ['elmwood-transcona', 'jim maloway', 'm', 'winnipeg', 'small businessman', '14355', '1st'], ['kildonan-st paul', 'ross eadie', 'm', 'winnipeg', 'self employed / consultant', '12093', '2nd'], ['portage-lisgar', 'mohamed alli', 'm', 'winnipeg', 'distribution centre associate', '2353', '4th'], ['provencher', 'ross c martin', 'm', 'oakbank', 'design coordinator', '4947', '2nd'], ['saint boniface', 'matt schaubroeck', 'm', 'winnipeg', 'student', '5502', '3rd'], ['selkirk-interlake', 'patricia cordner', 'f', 'selkirk', 'retired', '9506', '2nd'], ['winnipeg centre', 'pat martin', 'm', 'winnipeg', 'parliamentarian', '12285', '1st'], ['winnipeg north', 'judy wasylycia - leis', 'f', 'winnipeg', 'parliamentarian', '14097', '1st'], ['winnipeg south', 'sean robert', 'm', 'winnipeg', 'product consultant - mlcc', '4673', '3rd'], ['winnipeg south centre', 'rachel heinrichs', 'f', 'winnipeg', 'student', '5490', '3rd']] |
city of angels ( musical ) | https://en.wikipedia.org/wiki/City_of_Angels_%28musical%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1773562-3.html.csv | count | city of angels ( musical ) had a 4 times nominated result . | {'scope': 'all', 'criterion': 'equal', 'value': 'nominated', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'nominated'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to nominated .', 'tostr': 'filter_eq { all_rows ; result ; nominated }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; nominated } }', 'tointer': 'select the rows whose result record fuzzily matches to nominated . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; nominated } } ; 4 } = true', 'tointer': 'select the rows whose result record fuzzily matches to nominated . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; result ; nominated } } ; 4 } = true | select the rows whose result record fuzzily matches to nominated . 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, 'nominated_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', 'nominated_6': 'nominated', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'nominated_6': [0], '4_7': [2]} | ['year', 'award', 'category', 'nominee', 'result'] | [['1994', 'laurence olivier award', 'best new musical', 'best new musical', 'won'], ['1994', 'laurence olivier award', 'best actor in a musical', 'roger allam', 'nominated'], ['1994', 'laurence olivier award', 'best actress in a musical', 'haydn gwynne', 'nominated'], ['1994', 'laurence olivier award', 'best performance in a supporting role in a musical', 'henry goodman', 'nominated'], ['1994', 'laurence olivier award', 'best director of a musical', 'michael blakemore', 'nominated']] |
cumann na ngaedheal | https://en.wikipedia.org/wiki/Cumann_na_nGaedheal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-147622-1.html.csv | majority | the majority of cumann na ngaedheal party elections were with the cumann na ngaedheal government . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'cumann na ngaedheal government', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'government', 'cumann na ngaedheal government'], 'result': True, 'ind': 0, 'tointer': 'for the government records of all rows , most of them fuzzily match to cumann na ngaedheal government .', 'tostr': 'most_eq { all_rows ; government ; cumann na ngaedheal government } = true'} | most_eq { all_rows ; government ; cumann na ngaedheal government } = true | for the government records of all rows , most of them fuzzily match to cumann na ngaedheal government . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'government_3': 3, 'cumann na ngaedheal government_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'government_3': 'government', 'cumann na ngaedheal government_4': 'cumann na ngaedheal government'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'government_3': [0], 'cumann na ngaedheal government_4': [0]} | ['election', 'dáil', 'share of votes', 'seats', 'government'] | [['1923', '4th', '28.9 %', '63', 'cumann na ngaedheal government'], ['1927 ( jun )', '5th', '27.0 %', '46', 'cumann na ngaedheal government'], ['1927 ( sep )', '6th', '38.7 %', '61', 'cumann na ngaedheal government'], ['1932', '7th', '35.3 %', '57', 'fianna fáil government'], ['1933', '8th', '30.1 %', '48', 'fianna fáil government']] |
private practice ( season 1 ) | https://en.wikipedia.org/wiki/Private_Practice_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24910733-1.html.csv | aggregation | the average number of us viewers , in millions , for season one of private practice , is 11.34 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '11.34', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'us viewers ( millions )'], 'result': '11.34', 'ind': 0, 'tostr': 'avg { all_rows ; us viewers ( millions ) }'}, '11.34'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; us viewers ( millions ) } ; 11.34 } = true', 'tointer': 'the average of the us viewers ( millions ) record of all rows is 11.34 .'} | round_eq { avg { all_rows ; us viewers ( millions ) } ; 11.34 } = true | the average of the us viewers ( millions ) record of all rows is 11.34 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'us viewers (millions)_4': 4, '11.34_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'us viewers (millions)_4': 'us viewers ( millions )', '11.34_5': '11.34'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'us viewers (millions)_4': [0], '11.34_5': [1]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['2', 'in which sam receives an unexpected visitor', 'tony goldwyn', 'mike ostrowski', 'october 3 , 2007', '12.30'], ['3', 'in which addison finds the magic', 'mark tinker', 'shonda rhimes & marti noxon', 'october 10 , 2007', '12.40'], ['4', 'in which addison has a very casual get together', 'arvin brown', 'andrea newman', 'october 17 , 2007', '11.81'], ['5', 'in which addison finds a showerhead', 'julie anne robinson', 'shonda rhimes & marti noxon', 'october 24 , 2007', '11.77'], ['6', 'in which charlotte goes down the rabbit hole', 'david solomon', 'jenna bans', 'october 31 , 2007', '11.21'], ['7', 'in which sam gets taken for a ride', 'jeff melman', 'emily halpern', 'november 14 , 2007', '11.45'], ['8', 'in which cooper finds a port in his storm', 'mark tinker', 'lauren schmidt', 'november 21 , 2007', '8.44']] |
richard gasquet | https://en.wikipedia.org/wiki/Richard_Gasquet | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1750635-13.html.csv | unique | the only time richard received a 1r from the australian open was in 2006 . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '1r', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2006', '1r'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2006 record fuzzily matches to 1r .', 'tostr': 'filter_eq { all_rows ; 2006 ; 1r }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 2006 ; 1r } }', 'tointer': 'select the rows whose 2006 record fuzzily matches to 1r . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2006', '1r'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2006 record fuzzily matches to 1r .', 'tostr': 'filter_eq { all_rows ; 2006 ; 1r }'}, 'tournament'], 'result': 'australian open', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 2006 ; 1r } ; tournament }'}, 'australian open'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 2006 ; 1r } ; tournament } ; australian open }', 'tointer': 'the tournament record of this unqiue row is australian open .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 2006 ; 1r } } ; eq { hop { filter_eq { all_rows ; 2006 ; 1r } ; tournament } ; australian open } } = true', 'tointer': 'select the rows whose 2006 record fuzzily matches to 1r . there is only one such row in the table . the tournament record of this unqiue row is australian open .'} | and { only { filter_eq { all_rows ; 2006 ; 1r } } ; eq { hop { filter_eq { all_rows ; 2006 ; 1r } ; tournament } ; australian open } } = true | select the rows whose 2006 record fuzzily matches to 1r . there is only one such row in the table . the tournament record of this unqiue row is australian open . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, '2006_7': 7, '1r_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'australian open_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', '2006_7': '2006', '1r_8': '1r', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'australian open_10': 'australian open'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], '2006_7': [0], '1r_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'australian open_10': [3]} | ['tournament', '2002', '2004', '2005', '2006'] | [['grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments'], ['australian open', 'a', 'a', 'a', '1r'], ['french open', '1r', 'a', '1r', 'a'], ['wimbledon', 'a', 'a', 'a', 'a'], ['us open', 'a', 'a', 'a', 'a'], ['win - loss', '0 - 1', '0 - 0', '0 - 1', '0 - 1']] |
jakob hlasek | https://en.wikipedia.org/wiki/Jakob_Hlasek | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1727962-1.html.csv | unique | the tournament in gstaad , switzerland was the only tournament in which jakob hlasek faced darren cahill in the final . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'darren cahill', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'darren cahill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to darren cahill .', 'tostr': 'filter_eq { all_rows ; opponent ; darren cahill }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent ; darren cahill } }', 'tointer': 'select the rows whose opponent record fuzzily matches to darren cahill . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'darren cahill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to darren cahill .', 'tostr': 'filter_eq { all_rows ; opponent ; darren cahill }'}, 'championship'], 'result': 'gstaad , switzerland', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; darren cahill } ; championship }'}, 'gstaad , switzerland'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; darren cahill } ; championship } ; gstaad , switzerland }', 'tointer': 'the championship record of this unqiue row is gstaad , switzerland .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponent ; darren cahill } } ; eq { hop { filter_eq { all_rows ; opponent ; darren cahill } ; championship } ; gstaad , switzerland } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to darren cahill . there is only one such row in the table . the championship record of this unqiue row is gstaad , switzerland .'} | and { only { filter_eq { all_rows ; opponent ; darren cahill } } ; eq { hop { filter_eq { all_rows ; opponent ; darren cahill } ; championship } ; gstaad , switzerland } } = true | select the rows whose opponent record fuzzily matches to darren cahill . there is only one such row in the table . the championship record of this unqiue row is gstaad , switzerland . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'darren cahill_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'championship_9': 9, 'gstaad , switzerland_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'darren cahill_8': 'darren cahill', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'championship_9': 'championship', 'gstaad , switzerland_10': 'gstaad , switzerland'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent_7': [0], 'darren cahill_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'championship_9': [2], 'gstaad , switzerland_10': [3]} | ['outcome', 'date', 'championship', 'surface', 'opponent', 'score'] | [['runner - up', '25 march 1985', 'rotterdam , netherlands', 'carpet', 'miloslav mečíř', '1 - 6 , 2 - 6'], ['runner - up', '4 august 1986', 'hilversum , netherlands', 'clay', 'thomas muster', '1 - 6 , 3 - 6 , 3 - 6'], ['runner - up', '11 july 1988', 'gstaad , switzerland', 'clay', 'darren cahill', '3 - 6 , 4 - 6 , 6 - 7 ( 2 - 7 )'], ['runner - up', '10 october 1988', 'basel , switzerland', 'hard ( i )', 'stefan edberg', '5 - 7 , 3 - 6 , 6 - 3 , 2 - 6'], ['winner', '14 november 1988', 'wembley , england', 'carpet', 'jonas svensson', '6 - 7 ( 4 - 7 ) , 3 - 6 , 6 - 4 , 6 - 0 , 7 - 5'], ['winner', '21 november 1988', 'johannesburg , south africa', 'hard ( i )', 'christo van rensburg', '6 - 7 , 6 - 4 , 6 - 1 , 7 - 6'], ['runner - up', '28 november 1988', 'brussels , belgium', 'carpet', 'henri leconte', '6 - 7 ( 3 - 7 ) , 6 - 7 ( 6 - 8 ) , 4 - 6'], ['winner', '13 february 1989', 'rotterdam , netherlands', 'carpet', 'anders järryd', '6 - 1 , 7 - 5'], ['runner - up', '27 february 1989', 'lyon , france', 'carpet', 'john mcenroe', '3 - 6 , 6 - 7 ( 3 - 7 )'], ['winner', '12 november 1990', 'wembley , england', 'carpet', 'michael chang', '7 - 6 ( 9 - 7 ) , 6 - 3'], ['winner', '30 september 1991', 'basel , switzerland', 'hard ( i )', 'john mcenroe', '7 - 6 ( 7 - 4 ) , 6 - 0 , 6 - 3'], ['runner - up', '11 november 1991', 'moscow , russia', 'carpet', 'andrei cherkasov', '6 - 7 ( 2 - 7 ) , 6 - 3 , 6 - 7 ( 5 - 7 )'], ['runner - up', '17 july 1995', 'gstaad , switzerland', 'clay', 'yevgeny kafelnikov', '3 - 6 , 4 - 6 , 6 - 3 , 3 - 6'], ['runner - up', '18 september 1995', 'bordeaux , france', 'hard', 'yahiya doumbia', '4 - 6 , 4 - 6']] |
christian pescatori | https://en.wikipedia.org/wiki/Christian_Pescatori | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514839-1.html.csv | aggregation | the average number of laps for all teams is 192 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '192', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'laps'], 'result': '192', 'ind': 0, 'tostr': 'avg { all_rows ; laps }'}, '192'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; laps } ; 192 } = true', 'tointer': 'the average of the laps record of all rows is 192 .'} | round_eq { avg { all_rows ; laps } ; 192 } = true | the average of the laps record of all rows is 192 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'laps_4': 4, '192_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '192_5': '192'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'laps_4': [0], '192_5': [1]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1997', 'bms scuderia italia', 'pierluigi martini antônio hermann de azevedo', 'gt1', '317', '8th', '4th'], ['1999', 'jb racing', 'jérôme policand mauro baldi', 'lmp', '71', 'dnf', 'dnf'], ['2001', 'audi sport north america', 'laurent aïello rinaldo capello', 'lmp900', '320', '2nd', '2nd'], ['2002', 'audi sport north america', 'johnny herbert rinaldo capello', 'lmp900', '374', '2nd', '2nd'], ['2005', 'bms scuderia italia', 'fabrizio gollin miguel ramos', 'gt1', '67', 'dnf', 'dnf'], ['2006', 'bms scuderia italia', 'fabrizio gollin fabio babini', 'gt1', '3', 'dnf', 'dnf']] |
1984 - 85 philadelphia flyers season | https://en.wikipedia.org/wiki/1984%E2%80%9385_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208855-18.html.csv | count | in the 1984 - 85 philadelphia flyers season , 2 of the canadian players were from london knights ( ohl ) . | {'scope': 'subset', 'criterion': 'equal', 'value': 'london knights ( ohl )', 'result': '2', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'canada'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nationality ; canada }', 'tointer': 'select the rows whose nationality record fuzzily matches to canada .'}, 'college / junior / club team ( league )', 'london knights ( ohl )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose college / junior / club team ( league ) record fuzzily matches to london knights ( ohl ) .', 'tostr': 'filter_eq { filter_eq { all_rows ; nationality ; canada } ; college / junior / club team ( league ) ; london knights ( ohl ) }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; nationality ; canada } ; college / junior / club team ( league ) ; london knights ( ohl ) } }', 'tointer': 'select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose college / junior / club team ( league ) record fuzzily matches to london knights ( ohl ) . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; nationality ; canada } ; college / junior / club team ( league ) ; london knights ( ohl ) } } ; 2 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose college / junior / club team ( league ) record fuzzily matches to london knights ( ohl ) . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; nationality ; canada } ; college / junior / club team ( league ) ; london knights ( ohl ) } } ; 2 } = true | select the rows whose nationality record fuzzily matches to canada . among these rows , select the rows whose college / junior / club team ( league ) record fuzzily matches to london knights ( ohl ) . the number of such rows is 2 . | 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, 'nationality_6': 6, 'canada_7': 7, 'college / junior / club team (league)_8': 8, 'london knights (ohl)_9': 9, '2_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', 'nationality_6': 'nationality', 'canada_7': 'canada', 'college / junior / club team (league)_8': 'college / junior / club team ( league )', 'london knights (ohl)_9': 'london knights ( ohl )', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'nationality_6': [0], 'canada_7': [0], 'college / junior / club team (league)_8': [1], 'london knights (ohl)_9': [1], '2_10': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['2', 'greg smyth', 'defense', 'canada', 'london knights ( ohl )'], ['2', 'scott mellanby', 'right wing', 'canada', 'henry carr secondary school ( toronto )'], ['2', 'jeff chychrun', 'defense', 'canada', 'kingston canadians ( ohl )'], ['3', 'dave mclay', 'forward', 'canada', 'kelowna wings ( whl )'], ['3', 'john stevens', 'defense', 'canada', 'oshawa generals ( ohl )'], ['4', 'david hanson', 'center', 'united states', 'grand forks high school ( n dakota )'], ['5', 'brian dobbin', 'right wing', 'canada', 'london knights ( ohl )'], ['6', 'john dzikowski', 'center', 'canada', 'brandon wheat kings ( whl )'], ['7', 'tom allen', 'defense', 'canada', 'kitchener rangers ( ohl )'], ['8', 'luke vitale', 'forward', 'canada', 'henry carr secondary school ( toronto )'], ['9', 'billy powers', 'forward', 'united states', 'matignon high school ( mass )'], ['10', 'daryn fersovich', 'forward', 'canada', 'st albert saints ( ajhl )'], ['12', 'juraj bakos', 'defense', 'slovakia', 'hc kosice ( czech )']] |
kasper hämäläinen | https://en.wikipedia.org/wiki/Kasper_H%C3%A4m%C3%A4l%C3%A4inen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16009672-1.html.csv | count | there are 2 friendly competitions held in kasper hamalainen . | {'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '2', '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': '2', '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 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; competition ; friendly } } ; 2 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; competition ; friendly } } ; 2 } = true | select the rows whose competition record fuzzily matches to friendly . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, 'friendly_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', 'friendly_6': 'friendly', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly_6': [0], '2_7': [2]} | ['date', 'location', 'score', 'result', 'competition'] | [['17 november 2010', 'helsinki olympic stadium , helsinki , finland', '2 - 0', '8 - 0', 'uefa euro 2012 qualifying'], ['17 november 2010', 'helsinki olympic stadium , helsinki , finland', '5 - 0', '8 - 0', 'uefa euro 2012 qualifying'], ['10 august 2011', 'skonto stadium , riga , latvia', '10', '20', 'friendly'], ['2 september 2011', 'helsinki olympic stadium , helsinki , finland', '10', '41', 'uefa euro 2012 qualifying'], ['2 september 2011', 'helsinki olympic stadium , helsinki , finland', '2 - 0', '41', 'uefa euro 2012 qualifying'], ['12 october 2012', 'helsinki olympic stadium , helsinki , finland', '11', '1 - 1', '2014 fifa world cup qualification'], ['14 august 2013', 'veritas stadion , turku , finland', '20', '20', 'friendly']] |
2008 continental cup of curling | https://en.wikipedia.org/wiki/2008_Continental_Cup_of_Curling | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18446443-1.html.csv | majority | canada was the country most represented with 4 teams . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'canada'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to canada .', 'tostr': 'most_eq { all_rows ; country ; canada } = true'} | most_eq { all_rows ; country ; canada } = true | for the country records of all rows , most of them fuzzily match to canada . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'canada_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'canada_4': 'canada'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'canada_4': [0]} | ['team', 'country', 'home', 'skip', 'third', 'second', 'lead'] | [['north america', 'united states', 'madison , wisconsin', 'craig brown', 'rich ruohonen', 'john dunlop', 'peter annis'], ['north america', 'canada', 'winnipeg , manitoba', 'jennifer jones', 'cathy overton - clapham', 'jill officer', 'dawn askin'], ['north america', 'canada', 'edmonton , alberta', 'kevin koe', 'blake macdonald', 'carter rycroft', 'nolan thiessen'], ['north america', 'canada', 'saskatoon , saskatchewan', 'stefanie lawton', 'marliese kasner', 'teejay surik', 'lana vey'], ['north america', 'canada', 'edmonton , alberta', 'kevin martin', 'john morris', 'marc kennedy', 'ben hebert'], ['north america', 'united states', 'madison , wisconsin', 'debbie mccormick', 'allison pottinger', 'nicole joraanstad', 'tracy sachtjen'], ['world', 'scotland / sweden', 'lockerbie', 'david murdoch', 'ewan macdonald', 'niklas edin', 'euan byers'], ['world', 'sweden', 'härnösand', 'anette norberg', 'kajsa bergström', 'cathrine lindahl', 'anna svärd'], ['world', 'switzerland', 'davos', 'mirjam ott', 'carmen schäfer', 'valeria spälty', 'janine greiner'], ['world', 'china', 'harbin', 'wang bingyu', 'liu yin', 'yue qingshuang', 'zhou yan'], ['world', 'china', 'harbin', 'wang fengchun', 'liu rui', 'xu xiaoming', 'zang jialiang'], ['world', 'norway', 'oslo', 'thomas ulsrud', 'torger nergård', 'christoffer svae', 'håvard vad petersson']] |
jack ahearn | https://en.wikipedia.org/wiki/Jack_Ahearn | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15212423-2.html.csv | superlative | in the seasons of motorcycle racing listed for jack ahearn the highest number of points he achieved in a single year in 500 cc was 25 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '15', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2', 'subset': {'col': '2', 'criterion': 'equal', 'value': '500cc'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', '500cc'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; class ; 500cc }', 'tointer': 'select the rows whose class record fuzzily matches to 500cc .'}, 'points'], 'result': '25', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; class ; 500cc } ; points }', 'tointer': 'select the rows whose class record fuzzily matches to 500cc . the maximum points record of these rows is 25 .'}, '25'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; class ; 500cc } ; points } ; 25 } = true', 'tointer': 'select the rows whose class record fuzzily matches to 500cc . the maximum points record of these rows is 25 .'} | eq { max { filter_eq { all_rows ; class ; 500cc } ; points } ; 25 } = true | select the rows whose class record fuzzily matches to 500cc . the maximum points record of these rows is 25 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'class_5': 5, '500cc_6': 6, 'points_7': 7, '25_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'class_5': 'class', '500cc_6': '500cc', 'points_7': 'points', '25_8': '25'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'class_5': [0], '500cc_6': [0], 'points_7': [1], '25_8': [2]} | ['year', 'class', 'team', 'points', 'wins'] | [['1954', '350cc', 'norton', '0', '0'], ['1954', '500cc', 'norton', '0', '0'], ['1955', '350cc', 'norton', '0', '0'], ['1955', '500cc', 'norton', '1', '0'], ['1958', '350cc', 'ajs', '0', '0'], ['1958', '500cc', 'matchless', '0', '0'], ['1962', '350cc', 'norton', '0', '0'], ['1962', '500cc', 'norton', '0', '0'], ['1963', '125cc', 'ducati', '0', '0'], ['1963', '350cc', 'norton', '4', '0'], ['1963', '500cc', 'norton', '5', '1'], ['1964', '125cc', 'honda', '0', '0'], ['1964', '250cc', 'suzuki', '0', '0'], ['1964', '350cc', 'norton', '1', '0'], ['1964', '500cc', 'norton', '25', '1'], ['1965', '500cc', 'norton', '9', '0'], ['1966', '350cc', 'norton', '8', '0'], ['1966', '500cc', 'norton', '13', '0'], ['1974', '350cc', 'yamaha', '0', '0']] |
charleston southern buccaneers | https://en.wikipedia.org/wiki/Charleston_Southern_Buccaneers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26240481-1.html.csv | unique | 2008 was the only year that the charleston southern buccaneers played an opponent from the mac conference . | {'scope': 'all', 'row': '9', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'mac', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents conference', 'mac'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponents conference record fuzzily matches to mac .', 'tostr': 'filter_eq { all_rows ; opponents conference ; mac }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponents conference ; mac } }', 'tointer': 'select the rows whose opponents conference record fuzzily matches to mac . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents conference', 'mac'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponents conference record fuzzily matches to mac .', 'tostr': 'filter_eq { all_rows ; opponents conference ; mac }'}, 'year'], 'result': '2008', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponents conference ; mac } ; year }'}, '2008'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponents conference ; mac } ; year } ; 2008 }', 'tointer': 'the year record of this unqiue row is 2008 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponents conference ; mac } } ; eq { hop { filter_eq { all_rows ; opponents conference ; mac } ; year } ; 2008 } } = true', 'tointer': 'select the rows whose opponents conference record fuzzily matches to mac . there is only one such row in the table . the year record of this unqiue row is 2008 .'} | and { only { filter_eq { all_rows ; opponents conference ; mac } } ; eq { hop { filter_eq { all_rows ; opponents conference ; mac } ; year } ; 2008 } } = true | select the rows whose opponents conference record fuzzily matches to mac . there is only one such row in the table . the year record of this unqiue row is 2008 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponents conference_7': 7, 'mac_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2008_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponents conference_7': 'opponents conference', 'mac_8': 'mac', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2008_10': '2008'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponents conference_7': [0], 'mac_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2008_10': [3]} | ['year', 'fbs opponent', 'result', 'opponents conference', 'opponents head coach', 'charleston southerns head coach'] | [['2014', 'georgia bulldogs', 'tbd', 'sec', 'mark richt as of 2011', 'jay mills as of 2011'], ['2012', 'illinois fighting illini', 'tbd', 'big ten', 'tim beckman as of 2012', 'jay mills as of 2011'], ['2011', 'ucf knights', 'l , 62 - 0', 'c - usa', "george o'leary", 'jay mills'], ['2011', 'florida state seminoles', 'l , 62 - 10', 'acc', 'jimbo fisher', 'jay mills'], ['2010', 'kentucky wildcats', 'l , 49 - 21', 'sec', 'joker phillips', 'jay mills'], ['2010', 'hawaii warriors', 'l , 66 - 7', 'wac', 'greg mcmackin', 'jay mills'], ['2009', 'south florida bulls', 'l , 59 - 0', 'big east', 'jim leavitt', 'jay mills'], ['2009', 'florida gators', 'l , 62 - 3', 'sec', 'urban meyer', 'jay mills'], ['2008', 'miami redhawks', 'l , 38 - 27', 'mac', 'don treadwell', 'jay mills'], ['2008', 'miami hurricanes', 'l , 52 - 7', 'acc', 'randy shannon', 'jay mills'], ['2007', 'hawaii warriors', 'l , 66 - 10', 'wac', 'june jones', 'jay mills'], ['2003', 'south florida bulls', 'l , 55 - 7', 'big east', 'jim leavitt', 'jay mills'], ['2002', 'south florida bulls', 'l , 56 - 6', 'big east', 'jim leavitt', 'david dowd']] |
1956 team speedway polish championship | https://en.wikipedia.org/wiki/1956_Team_Speedway_Polish_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15432872-5.html.csv | majority | in the 1956 team speedway polish championship , for the teams that had under 20 points , most of the teams had fewer than 10 losses . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '20'}} | {'func': 'most_less', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '20'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; points ; 20 }', 'tointer': 'select the rows whose points record is less than 20 .'}, 'lost', '10'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose points record is less than 20 . for the lost records of these rows , most of them are less than 10 .', 'tostr': 'most_less { filter_less { all_rows ; points ; 20 } ; lost ; 10 } = true'} | most_less { filter_less { all_rows ; points ; 20 } ; lost ; 10 } = true | select the rows whose points record is less than 20 . for the lost records of these rows , most of them are less than 10 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'points_4': 4, '20_5': 5, 'lost_6': 6, '10_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'points_4': 'points', '20_5': '20', 'lost_6': 'lost', '10_7': '10'} | {'most_less_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'points_4': [0], '20_5': [0], 'lost_6': [1], '10_7': [1]} | ['team', 'match', 'points', 'draw', 'lost'] | [['włókniarz częstochowa', '14', '26', '0', '1'], ['stal gorzów wlkp', '14', '23', '1', '2'], ['amk katowice', '14', '15', '1', '6'], ['resovia rzeszów', '14', '14', '0', '7'], ['sparta śrem', '14', '13', '1', '7'], ['gwardia poznań', '14', '12', '0', '8'], ['start gniezno', '14', '7', '1', '10'], ['kolejarz piła', '14', '2', '0', '13']] |
jordi arrese | https://en.wikipedia.org/wiki/Jordi_Arrese | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1727920-2.html.csv | majority | all of the tennis tournaments that jordi arrese played in were on a clay surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , all of them fuzzily match to clay .', 'tostr': 'all_eq { all_rows ; surface ; clay } = true'} | all_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , all of them fuzzily match to clay . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['runner - up', '1985', 'bologna , italy', 'clay', 'alberto tous', 'paolo canè simone colombo', '5 - 7 , 4 - 6'], ['winner', '1986', 'bordeaux , france', 'clay', 'david de miguel', 'ronald agénor mansour bahrami', '7 - 5 , 6 - 4'], ['winner', '1989', 'prague , czechoslovakia', 'clay', 'horst skoff', 'petr korda tomáš šmíd', '6 - 4 , 6 - 4'], ['winner', '1991', 'san marino', 'clay', 'carlos costa', 'christian miniussi diego pérez', '6 - 3 , 3 - 6 , 6 - 3'], ['runner - up', '1993', 'umag , croatia', 'clay', 'francisco roig', 'filip dewulf tom vanhoudt', '4 - 6 , 5 - 7'], ['runner - up', '1994', 'san marino', 'clay', 'renzo furlan', 'neil broad greg van emburgh', '4 - 6 , 6 - 7'], ['runner - up', '1994', 'bucharest , romania', 'clay', 'jose antonio conde', 'wayne arthurs simon youl', '4 - 6 , 4 - 6'], ['runner - up', '1995', 'oporto , portugal', 'clay', 'àlex corretja', 'tomás carbonell francisco roig', '3 - 6 , 6 - 7'], ['runner - up', '1995', 'kitzbühel , austria', 'clay', 'wayne arthurs', 'francisco montana greg van emburgh', '7 - 6 , 3 - 6 , 6 - 7'], ['winner', '1995', 'san marino', 'clay', 'andrew kratzmann', 'pablo albano federico mordegan', '7 - 6 , 3 - 6 , 6 - 2']] |
2007 volta a catalunya | https://en.wikipedia.org/wiki/2007_Volta_a_Catalunya | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11355733-15.html.csv | aggregation | in the 2007 volta a catalunya , the russian competitors had a total of 90 uci points . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '90', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'russia'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'russia'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; russia }', 'tointer': 'select the rows whose country record fuzzily matches to russia .'}, 'uci points'], 'result': '90', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; country ; russia } ; uci points }'}, '90'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; country ; russia } ; uci points } ; 90 } = true', 'tointer': 'select the rows whose country record fuzzily matches to russia . the sum of the uci points record of these rows is 90 .'} | round_eq { sum { filter_eq { all_rows ; country ; russia } ; uci points } ; 90 } = true | select the rows whose country record fuzzily matches to russia . the sum of the uci points record of these rows is 90 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'russia_6': 6, 'uci points_7': 7, '90_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'russia_6': 'russia', 'uci points_7': 'uci points', '90_8': '90'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'russia_6': [0], 'uci points_7': [1], '90_8': [2]} | ['cyclist', 'country', 'team', 'time', 'uci points'] | [['vladimir karpets', 'russia', "caisse d'epargne", "22h 21 ' 05", '50'], ['denis menchov', 'russia', 'rabobank', '+ 40', '40'], ['michael rogers', 'australia', 't - mobile team', '+ 40', '35'], ['christophe moreau', 'france', 'ag2r prévoyance', "+ 1 ' 34", '30'], ['óscar sevilla', 'spain', 'relax - gam', "+ 1 ' 34", 'n / a'], ['francisco mancebo', 'spain', 'relax - gam', "+ 1 ' 59", 'n / a'], ['john gadret', 'france', 'ag2r prévoyance', "+ 2 ' 19", '15'], ['marcos - antonio serrano', 'spain', 'karpin - galicia', "+ 2 ' 39", 'n / a'], ['laurens ten dam', 'netherlands', 'unibetcom', "+ 2 ' 44", '5'], ['janez brajkovič', 'slovenia', 'discovery channel', "+ 2 ' 47", '2']] |
list of festivals at donington park | https://en.wikipedia.org/wiki/List_of_Festivals_at_Donington_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10311801-2.html.csv | ordinal | the second festival to have taken place at donlington park was the monsters of rock . | {'row': '2', 'col': '1', 'order': '2', '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', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, 'event'], 'result': 'monsters of rock', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 2 } ; event }'}, 'monsters of rock'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 2 } ; event } ; monsters of rock } = true', 'tointer': 'select the row whose year record of all rows is 2nd minimum . the event record of this row is monsters of rock .'} | eq { hop { nth_argmin { all_rows ; year ; 2 } ; event } ; monsters of rock } = true | select the row whose year record of all rows is 2nd minimum . the event record of this row is monsters of rock . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'event_7': 7, 'monsters of rock_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', 'year_5': 'year', '2_6': '2', 'event_7': 'event', 'monsters of rock_8': 'monsters of rock'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'event_7': [1], 'monsters of rock_8': [2]} | ['year', 'date', 'event', 'days', 'stages', 'acts'] | [['1990', '18 august', 'monsters of rock', '1 day', '1 stage', '5 bands'], ['1991', '17 august', 'monsters of rock', '1 day', '1 stage', '5 bands'], ['1992', '2526 july', 'one step beyond', '24 hours', '1 stage', "60 + dj 's"], ['1992', '22 august', 'monsters of rock', '1 day', '1 stage', '6 bands'], ['1994', '4 june', 'monsters of rock', '1 day', '2 stages', '12 bands'], ['1995', '26 august', 'metallica : escape from the studio', '1 day', '1 stage', '9 bands'], ['1996', '17 august', 'monsters of rock', '1 day', '2 stages', '13 bands']] |
wru division five west | https://en.wikipedia.org/wiki/WRU_Division_Five_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17941032-2.html.csv | count | in the wru division five west , when there were 20 games played , there were 5 instances where a club had 1 draw . | {'scope': 'subset', 'criterion': 'equal', 'value': '1', 'result': '5', 'col': '3', 'subset': {'col': '2', 'criterion': 'equal', 'value': '20'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'played', '20'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; played ; 20 }', 'tointer': 'select the rows whose played record is equal to 20 .'}, 'drawn', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose played record is equal to 20 . among these rows , select the rows whose drawn record is equal to 1 .', 'tostr': 'filter_eq { filter_eq { all_rows ; played ; 20 } ; drawn ; 1 }'}], 'result': '5', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; played ; 20 } ; drawn ; 1 } }', 'tointer': 'select the rows whose played record is equal to 20 . among these rows , select the rows whose drawn record is equal to 1 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; played ; 20 } ; drawn ; 1 } } ; 5 } = true', 'tointer': 'select the rows whose played record is equal to 20 . among these rows , select the rows whose drawn record is equal to 1 . the number of such rows is 5 .'} | eq { count { filter_eq { filter_eq { all_rows ; played ; 20 } ; drawn ; 1 } } ; 5 } = true | select the rows whose played record is equal to 20 . among these rows , select the rows whose drawn record is equal to 1 . the number of such rows is 5 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'played_6': 6, '20_7': 7, 'drawn_8': 8, '1_9': 9, '5_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'played_6': 'played', '20_7': '20', 'drawn_8': 'drawn', '1_9': '1', '5_10': '5'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'played_6': [0], '20_7': [0], 'drawn_8': [1], '1_9': [1], '5_10': [3]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['cefneithin rfc', '20', '1', '2', '626', '179', '88', '18', '10', '2', '82'], ['milford haven rfc', '20', '1', '3', '566', '193', '85', '21', '9', '2', '77'], ['furnace united rfc', '20', '0', '5', '608', '234', '94', '32', '13', '3', '76'], ['aberaeron rfc', '20', '1', '7', '396', '208', '59', '25', '8', '4', '62'], ['st clears rfc', '20', '1', '8', '448', '264', '56', '38', '6', '4', '56'], ['neyland rfc', '20', '0', '9', '450', '248', '67', '28', '6', '3', '53'], ['fishguard and goodwick rfc', '20', '0', '9', '368', '315', '48', '41', '4', '3', '51'], ['pontyates rfc', '19', '0', '13', '219', '435', '26', '63', '3', '1', '28'], ['llangwm rfc', '20', '1', '16', '150', '598', '14', '91', '0', '3', '17'], ['st davids rfc', '19', '1', '16', '176', '510', '23', '74', '1', '3', '14'], ['swansea uplands rfc', '20', '0', '18', '97', '920', '12', '141', '0', '0', '8']] |
liga mx | https://en.wikipedia.org/wiki/Liga_MX | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18143210-2.html.csv | majority | most of the teams in liga mix had under 10 top division titles . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'top division titles', '10'], 'result': True, 'ind': 0, 'tointer': 'for the top division titles records of all rows , most of them are less than 10 .', 'tostr': 'most_less { all_rows ; top division titles ; 10 } = true'} | most_less { all_rows ; top division titles ; 10 } = true | for the top division titles records of all rows , most of them are less than 10 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'top division titles_3': 3, '10_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'top division titles_3': 'top division titles', '10_4': '10'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'top division titles_3': [0], '10_4': [0]} | ['club', 'first season in top division', 'number of seasons in top division', 'first season of current spell in top division', 'number of seasons in liga mx', 'top division titles'] | [['américa', '1943 - 44', '89', '1943 - 44', '89', '11'], ['atlante', '1943 - 44', '87', '1991 - 92', '40', '3'], ['atlas', '1943 - 44', '86', '1979 - 80', '51', '1'], ['chiapas', '2002 - 03', '22', '2002 - 03', '22', '0'], ['cruz azul', '1964 - 65', '68', '1964 - 65', '68', '8'], ['guadalajara', '1943 - 44', '89', '1943 - 44', '89', '11'], ['león', '1944 - 45', '65', '2012 - 13', '2', '5'], ['monterrey', '1945 - 46', '74', '1960 - 61', '72', '4'], ['morelia', '1957 - 58', '61', '1981 - 82', '50', '1'], ['pachuca', '1967 - 68', '40', '1998 - 99', '30', '5'], ['puebla', '1944 - 45', '69', '2007 - 08', '12', '2'], ['querétaro', '1990 - 91', '18', '2009 - 10', '8', '0'], ['santos laguna', '1988 - 89', '42', '1988 - 89', '42', '4'], ['tijuana', '2011 - 12', '4', '2011 - 12', '4', '1'], ['toluca', '1953 - 54', '79', '1953 - 54', '79', '10'], ['uanl', '1974 - 75', '55', '1997 - 98', '32', '3'], ['unam', '1962 - 63', '70', '1962 - 63', '70', '7'], ['veracruz', '1943 - 44', '49', '2013 - 14', '0', '2']] |
list of awards and nominations received by the x - files | https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_The_X-Files | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18552926-8.html.csv | count | gillian anderson was nominated for awards for the x-files a total of four times . | {'scope': 'subset', 'criterion': 'equal', 'value': 'nominated', 'result': '4', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'gillian anderson'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'recipients and nominees', 'gillian anderson'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; recipients and nominees ; gillian anderson }', 'tointer': 'select the rows whose recipients and nominees record fuzzily matches to gillian anderson .'}, 'result', 'nominated'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose recipients and nominees record fuzzily matches to gillian anderson . among these rows , select the rows whose result record fuzzily matches to nominated .', 'tostr': 'filter_eq { filter_eq { all_rows ; recipients and nominees ; gillian anderson } ; result ; nominated }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; recipients and nominees ; gillian anderson } ; result ; nominated } }', 'tointer': 'select the rows whose recipients and nominees record fuzzily matches to gillian anderson . among these rows , select the rows whose result record fuzzily matches to nominated . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; recipients and nominees ; gillian anderson } ; result ; nominated } } ; 4 } = true', 'tointer': 'select the rows whose recipients and nominees record fuzzily matches to gillian anderson . among these rows , select the rows whose result record fuzzily matches to nominated . the number of such rows is 4 .'} | eq { count { filter_eq { filter_eq { all_rows ; recipients and nominees ; gillian anderson } ; result ; nominated } } ; 4 } = true | select the rows whose recipients and nominees record fuzzily matches to gillian anderson . among these rows , select the rows whose result record fuzzily matches to nominated . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'recipients and nominees_6': 6, 'gillian anderson_7': 7, 'result_8': 8, 'nominated_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'recipients and nominees_6': 'recipients and nominees', 'gillian anderson_7': 'gillian anderson', 'result_8': 'result', 'nominated_9': 'nominated', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'recipients and nominees_6': [0], 'gillian anderson_7': [0], 'result_8': [1], 'nominated_9': [1], '4_10': [3]} | ['year', 'category', 'recipients and nominees', 'role / episode', 'result'] | [['1996', 'best actor in a leading role - drama series', 'david duchovny', 'fox mulder', 'won'], ['1996', 'best actress in a leading role - drama series', 'gillian anderson', 'dana scully', 'nominated'], ['1996', 'best series - drama', 'best series - drama', 'best series - drama', 'won'], ['1997', 'best actor in a leading role - drama series', 'david duchovny', 'david duchovny', 'nominated'], ['1997', 'best actress in a leading role - drama series', 'gillian anderson', 'gillian anderson', 'nominated'], ['1997', 'best series - drama', 'best series - drama', 'best series - drama', 'nominated'], ['1998', 'best actress in a leading role - drama series', 'gillian anderson', 'gillian anderson', 'nominated'], ['1998', 'best series - drama', 'best series - drama', 'best series - drama', 'nominated'], ['2000', 'best actress in a leading role - drama series', 'gillian anderson', 'gillian anderson', 'nominated']] |
ktlf | https://en.wikipedia.org/wiki/KTLF | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13831309-1.html.csv | aggregation | between the stations operating on 89.3 , the erp w is 950 . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '950', 'subset': {'col': '2', 'criterion': 'equal', 'value': '89.3'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'frequency mhz', '89.3'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; frequency mhz ; 89.3 }', 'tointer': 'select the rows whose frequency mhz record is equal to 89.3 .'}, 'erp w'], 'result': '950', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; frequency mhz ; 89.3 } ; erp w }'}, '950'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; frequency mhz ; 89.3 } ; erp w } ; 950 } = true', 'tointer': 'select the rows whose frequency mhz record is equal to 89.3 . the sum of the erp w record of these rows is 950 .'} | round_eq { sum { filter_eq { all_rows ; frequency mhz ; 89.3 } ; erp w } ; 950 } = true | select the rows whose frequency mhz record is equal to 89.3 . the sum of the erp w record of these rows is 950 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, '89.3_6': 6, 'erp w_7': 7, '950_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'frequency mhz_5': 'frequency mhz', '89.3_6': '89.3', 'erp w_7': 'erp w', '950_8': '950'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], '89.3_6': [0], 'erp w_7': [1], '950_8': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'height m ( ft )', 'class', 'fcc info'] | [['ktlc', '89.1', 'canon city , colorado', '1150', '-', 'c3', 'fcc'], ['ktcf', '89.5', 'dolores , colorado', '500', '-', 'a', 'fcc'], ['ktdu', '88.5', 'durango , colorado', '4000', '-', 'a', 'fcc'], ['ktmh', '89.9', 'montrose , colorado', '4000', '-', 'c1', 'fcc'], ['ktps', '89.7', 'pagosa springs , colorado', '200', '-', 'a', 'fcc'], ['ktsg', '91.7', 'steamboat springs , colorado', '2500', '-', 'c3', 'fcc'], ['ktol', '90.9', 'leadville , colorado', '450', '-', 'a', 'fcc'], ['ktpf', '91.3', 'salida , colorado', '390', '-', 'c2', 'fcc'], ['ktei', '90.7', 'placerville , colorado', '250', '-', 'a', 'fcc'], ['ktdl', '90.7', 'trinidad , colorado', '450', '-', 'a', 'fcc'], ['ktad', '89.9', 'sterling , colorado', '5000', '-', 'c3', 'fcc'], ['ktml', '91.5', 'south fork , colorado', '280', '-', 'c3', 'fcc'], ['ktaw', '89.3', 'walsenburg , colorado', '500', '-', 'a', 'fcc'], ['ktdx', '89.3', 'laramie , wyoming', '450', '-', 'a', 'fcc']] |
volksparkstadion | https://en.wikipedia.org/wiki/Volksparkstadion | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1640212-1.html.csv | count | for volksparkstadion , when there were 50000 spectators , there were two occasions where one of the teams scored 3 points . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '3', 'result': '2', 'col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': '50000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'spectators', '50000'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; spectators ; 50000 }', 'tointer': 'select the rows whose spectators record is equal to 50000 .'}, 'res', '3'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose spectators record is equal to 50000 . among these rows , select the rows whose res record fuzzily matches to 3 .', 'tostr': 'filter_eq { filter_eq { all_rows ; spectators ; 50000 } ; res ; 3 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; spectators ; 50000 } ; res ; 3 } }', 'tointer': 'select the rows whose spectators record is equal to 50000 . among these rows , select the rows whose res record fuzzily matches to 3 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; spectators ; 50000 } ; res ; 3 } } ; 2 } = true', 'tointer': 'select the rows whose spectators record is equal to 50000 . among these rows , select the rows whose res record fuzzily matches to 3 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; spectators ; 50000 } ; res ; 3 } } ; 2 } = true | select the rows whose spectators record is equal to 50000 . among these rows , select the rows whose res record fuzzily matches to 3 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'spectators_6': 6, '50000_7': 7, 'res_8': 8, '3_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'spectators_6': 'spectators', '50000_7': '50000', 'res_8': 'res', '3_9': '3', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'spectators_6': [0], '50000_7': [0], 'res_8': [1], '3_9': [1], '2_10': [3]} | ['date', 'time ( cet )', 'res', 'round', 'spectators'] | [['2006 - 06 - 10', '21.00', '2 - 1', 'group c', '49480'], ['2006 - 06 - 15', '15.00', '3 - 0', 'group a', '50000'], ['2006 - 06 - 19', '18.00', '0 - 4', 'group h', '50000'], ['2006 - 06 - 22', '16.00', '0 - 2', 'group e', '50000'], ['2006 - 06 - 30', '21.00', '3 - 0', 'quarterfinals', '50000']] |
north central conference ( ihsaa ) | https://en.wikipedia.org/wiki/North_Central_Conference_%28IHSAA%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18871102-1.html.csv | aggregation | the average student enrollment of schools in the north central conference is 1432 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1432', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '1432', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '1432'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 1432 } = true', 'tointer': 'the average of the enrollment record of all rows is 1432 .'} | round_eq { avg { all_rows ; enrollment } ; 1432 } = true | the average of the enrollment record of all rows is 1432 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '1432_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '1432_5': '1432'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '1432_5': [1]} | ['school', 'location', 'mascot', 'county', 'enrollment', 'ihsaa class / football / soccer', 'year joined', 'previous conference'] | [['anderson', 'anderson', 'indians', '48 madison', '1884', '4a / 5a / 2a', '1926', 'independents'], ['huntington north', 'huntington', 'vikings', '35 huntington', '1750', '4a / 5a / 2a', '2003', 'olympic'], ['kokomo', 'kokomo', 'wildkats', '34 howard', '1879', '4a / 5a / 2a', '1926', 'independents'], ['logansport community', 'logansport', 'berries', '09 cass', '1245', '4a / 4a / 2a', '1926', 'independents'], ['marion', 'marion', 'giants', '27 grant', '1159', '4a / 4a / 2a', '1933', 'independents'], ['muncie central', 'muncie', 'bearcats', '18 delaware', '915', '3a / 4a / 2a', '1926', 'independents'], ['new castle chrysler', 'new castle', 'trojans', '33 henry', '1108', '4a / 4a / 2a', '1926', 'independents'], ['richmond', 'richmond', 'red devils', '89 wayne', '1516', '4a / 5a / 2a', '1926', 'independents']] |
lexus ls ( xf40 ) | https://en.wikipedia.org/wiki/Lexus_LS_%28XF40%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21530474-1.html.csv | majority | the majority of models produced used a rwd drivetrain . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rwd', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'drivetrain', 'rwd'], 'result': True, 'ind': 0, 'tointer': 'for the drivetrain records of all rows , most of them fuzzily match to rwd .', 'tostr': 'most_eq { all_rows ; drivetrain ; rwd } = true'} | most_eq { all_rows ; drivetrain ; rwd } = true | for the drivetrain records of all rows , most of them fuzzily match to rwd . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'drivetrain_3': 3, 'rwd_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'drivetrain_3': 'drivetrain', 'rwd_4': 'rwd'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'drivetrain_3': [0], 'rwd_4': [0]} | ['chassis code', 'model no', 'production years', 'drivetrain', 'transmission', 'engine type', 'engine code', 'region ( s )'] | [['usf40 ( japanese )', 'ls 460', '2006 -', 'rwd', '8 - speed aa80e at', '4.6 l petrol v8', '1ur - fse', 'n america , asia , europe , oceania'], ['usf40 ( japanese )', 'ls 460', '2006 -', 'rwd', '8 - speed aa80e at', '4.6 l petrol v8', '1ur - fe', 'middle east'], ['usf41', 'ls 460 l', '2006 -', 'rwd', '8 - speed aa80e at', '4.6 l petrol v8', '1ur - fse', 'n america , asia , europe'], ['usf41', 'ls 460 l', '2006 -', 'rwd', '8 - speed aa80e at', '4.6 l petrol v8', '1ur - fe', 'middle east'], ['usf45', 'ls 460 awd', '2007 -', 'awd', '8 - speed aa80e at', '4.6 l petrol v8', '1ur - fse', 'n america'], ['usf46', 'ls 460 l awd', '2007 -', 'awd', '8 - speed aa80e at', '4.6 l petrol v8', '1ur - fse', 'n america'], ['uvf45 ( japanese )', 'ls 600h', '2007 -', 'awd', 'l110f cvt', '5.0 l hybrid v8', '2ur - fse', 'asia , europe']] |
2007 - 08 chicago bulls season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Chicago_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11960610-6.html.csv | aggregation | in the 2007 - 08 chicago bulls season , when wallace had the high rebounds , his average number of rebounds was 11 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '11', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'wallace'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'wallace'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high rebounds ; wallace }', 'tointer': 'select the rows whose high rebounds record fuzzily matches to wallace .'}, 'high rebounds'], 'result': '11', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; high rebounds ; wallace } ; high rebounds }'}, '11'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; high rebounds ; wallace } ; high rebounds } ; 11 } = true', 'tointer': 'select the rows whose high rebounds record fuzzily matches to wallace . the average of the high rebounds record of these rows is 11 .'} | round_eq { avg { filter_eq { all_rows ; high rebounds ; wallace } ; high rebounds } ; 11 } = true | select the rows whose high rebounds record fuzzily matches to wallace . the average of the high rebounds record of these rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high rebounds_5': 5, 'wallace_6': 6, 'high rebounds_7': 7, '11_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high rebounds_5': 'high rebounds', 'wallace_6': 'wallace', 'high rebounds_7': 'high rebounds', '11_8': '11'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'wallace_6': [0], 'high rebounds_7': [1], '11_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['2', 'november 2', 'philadelphia', '85 - 96', 'gordon ( 25 )', 'thomas ( 12 )', 'hinrich ( 8 )', 'united center 22034', '0 - 2'], ['3', 'november 3', 'milwaukee', '72 - 78', 'gordon ( 15 )', 'smith ( 10 )', 'hinrich ( 4 )', 'bradley center 18717', '0 - 3'], ['4', 'november 6', 'la clippers', '91 - 97', 'deng ( 22 )', 'deng ( 8 )', 'thomas ( 5 )', 'united center 21742', '0 - 4'], ['5', 'november 8', 'detroit', '97 - 93', 'thomas ( 19 )', 'thomas ( 14 )', 'hinrich ( 14 )', 'united center 21797', '1 - 4'], ['6', 'november 10', 'toronto', '71 - 101', 'nocioni ( 20 )', 'sefolosha ( 6 )', 'hinrich , duhon , sefolosha ( 4 )', 'united center 22467', '1 - 5'], ['7', 'november 15', 'phoenix', '102 - 112', 'gordon ( 24 )', 'wallace ( 10 )', 'hinrich ( 7 )', 'us airways center 18422', '1 - 6'], ['8', 'november 17', 'la clippers', '92 - 73', 'gordon ( 25 )', 'wallace ( 13 )', 'hinrich , gordon , duhon ( 4 )', 'staples center 17535', '2 - 6'], ['9', 'november 18', 'la lakers', '78 - 106', 'gordon ( 20 )', 'wallace ( 8 )', 'hinrich ( 8 )', 'staples center 18997', '2 - 7'], ['10', 'november 20', 'denver', '91 - 112', 'noah ( 16 )', 'wallace ( 12 )', 'duhon ( 5 )', 'pepsi center 17106', '2 - 8'], ['11', 'november 24', 'new york', '78 - 85', 'nocioni ( 23 )', 'wallace ( 12 )', 'hinrich ( 4 )', 'madison square garden 19763', '2 - 9'], ['12', 'november 25', 'toronto', '78 - 93', 'deng ( 21 )', 'deng ( 9 )', 'hinrich ( 7 )', 'air canada centre 19800', '2 - 10']] |
wybe | https://en.wikipedia.org/wiki/WYBE | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1882668-1.html.csv | comparative | wybe main programming was on channel 35.1 while their russian news programming was on channel 35.4 . | {'row_1': '1', 'row_2': '4', 'col': '1', 'col_other': '5', 'relation': 'diff', 'record_mentioned': 'yes', 'diff_result': {'diff_value': '0.3', 'bigger': 'row2'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'programming', 'main wybe programming'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose programming record fuzzily matches to main wybe programming .', 'tostr': 'filter_eq { all_rows ; programming ; main wybe programming }'}, 'channel'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel }', 'tointer': 'select the rows whose programming record fuzzily matches to main wybe programming . take the channel record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'programming', 'russia today'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose programming record fuzzily matches to russia today .', 'tostr': 'filter_eq { all_rows ; programming ; russia today }'}, 'channel'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; programming ; russia today } ; channel }', 'tointer': 'select the rows whose programming record fuzzily matches to russia today . take the channel record of this row .'}], 'result': '-0.3', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel } ; hop { filter_eq { all_rows ; programming ; russia today } ; channel } }'}, '-0.3'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel } ; hop { filter_eq { all_rows ; programming ; russia today } ; channel } } ; -0.3 }', 'tointer': 'select the rows whose programming record fuzzily matches to main wybe programming . take the channel record of this row . select the rows whose programming record fuzzily matches to russia today . take the channel record of this row . the second record is 0.3 larger than the first record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'programming', 'main wybe programming'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose programming record fuzzily matches to main wybe programming .', 'tostr': 'filter_eq { all_rows ; programming ; main wybe programming }'}, 'channel'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel }', 'tointer': 'select the rows whose programming record fuzzily matches to main wybe programming . take the channel record of this row .'}, '35.1'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel } ; 35.1 }', 'tointer': 'the channel record of the first row is 35.1 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'programming', 'russia today'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose programming record fuzzily matches to russia today .', 'tostr': 'filter_eq { all_rows ; programming ; russia today }'}, 'channel'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; programming ; russia today } ; channel }', 'tointer': 'select the rows whose programming record fuzzily matches to russia today . take the channel record of this row .'}, '35.4'], 'result': True, 'ind': 7, 'tostr': 'eq { hop { filter_eq { all_rows ; programming ; russia today } ; channel } ; 35.4 }', 'tointer': 'the channel record of the second row is 35.4 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel } ; 35.1 } ; eq { hop { filter_eq { all_rows ; programming ; russia today } ; channel } ; 35.4 } }', 'tointer': 'the channel record of the first row is 35.1 . the channel record of the second row is 35.4 .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { diff { hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel } ; hop { filter_eq { all_rows ; programming ; russia today } ; channel } } ; -0.3 } ; and { eq { hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel } ; 35.1 } ; eq { hop { filter_eq { all_rows ; programming ; russia today } ; channel } ; 35.4 } } } = true', 'tointer': 'select the rows whose programming record fuzzily matches to main wybe programming . take the channel record of this row . select the rows whose programming record fuzzily matches to russia today . take the channel record of this row . the second record is 0.3 larger than the first record . the channel record of the first row is 35.1 . the channel record of the second row is 35.4 .'} | and { eq { diff { hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel } ; hop { filter_eq { all_rows ; programming ; russia today } ; channel } } ; -0.3 } ; and { eq { hop { filter_eq { all_rows ; programming ; main wybe programming } ; channel } ; 35.1 } ; eq { hop { filter_eq { all_rows ; programming ; russia today } ; channel } ; 35.4 } } } = true | select the rows whose programming record fuzzily matches to main wybe programming . take the channel record of this row . select the rows whose programming record fuzzily matches to russia today . take the channel record of this row . the second record is 0.3 larger than the first record . the channel record of the first row is 35.1 . the channel record of the second row is 35.4 . | 14 | 10 | {'and_9': 9, 'result_10': 10, 'eq_5': 5, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_11': 11, 'programming_12': 12, 'main wybe programming_13': 13, 'channel_14': 14, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_15': 15, 'programming_16': 16, 'russia today_17': 17, 'channel_18': 18, '-0.3_19': 19, 'and_8': 8, 'eq_6': 6, '35.1_20': 20, 'eq_7': 7, '35.4_21': 21} | {'and_9': 'and', 'result_10': 'true', 'eq_5': 'eq', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_11': 'all_rows', 'programming_12': 'programming', 'main wybe programming_13': 'main wybe programming', 'channel_14': 'channel', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_15': 'all_rows', 'programming_16': 'programming', 'russia today_17': 'russia today', 'channel_18': 'channel', '-0.3_19': '-0.3', 'and_8': 'and', 'eq_6': 'eq', '35.1_20': '35.1', 'eq_7': 'eq', '35.4_21': '35.4'} | {'and_9': [10], 'result_10': [], 'eq_5': [9], 'diff_4': [5], 'num_hop_2': [4, 6], 'filter_str_eq_0': [2], 'all_rows_11': [0], 'programming_12': [0], 'main wybe programming_13': [0], 'channel_14': [2], 'num_hop_3': [4, 7], 'filter_str_eq_1': [3], 'all_rows_15': [1], 'programming_16': [1], 'russia today_17': [1], 'channel_18': [3], '-0.3_19': [5], 'and_8': [9], 'eq_6': [8], '35.1_20': [6], 'eq_7': [8], '35.4_21': [7]} | ['channel', 'video', 'aspect', 'psip short name', 'programming'] | [['35.1', '480i', '4:3', 'mind', 'main wybe programming'], ['35.2', '480i', '4:3', 'nhkwrld', 'nhk world'], ['35.3', '480i', '4:3', 'f24', 'france24'], ['35.4', '480i', '4:3', 'rt', 'russia today'], ['35.66', '480i', '4:3', 'wnyj', 'simulcast of programming from wnyj - tv']] |
1954 ohio state buckeyes football team | https://en.wikipedia.org/wiki/1954_Ohio_State_Buckeyes_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17963395-2.html.csv | unique | bob myers was the only defensive tackle picked in the 1954 buckeyes football team . | {'scope': 'all', 'row': '7', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'defensive tackle', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defensive tackle'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to defensive tackle .', 'tostr': 'filter_eq { all_rows ; position ; defensive tackle }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; defensive tackle } }', 'tointer': 'select the rows whose position record fuzzily matches to defensive tackle . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defensive tackle'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to defensive tackle .', 'tostr': 'filter_eq { all_rows ; position ; defensive tackle }'}, 'player'], 'result': 'bob myers', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; defensive tackle } ; player }'}, 'bob myers'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; defensive tackle } ; player } ; bob myers }', 'tointer': 'the player record of this unqiue row is bob myers .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; defensive tackle } } ; eq { hop { filter_eq { all_rows ; position ; defensive tackle } ; player } ; bob myers } } = true', 'tointer': 'select the rows whose position record fuzzily matches to defensive tackle . there is only one such row in the table . the player record of this unqiue row is bob myers .'} | and { only { filter_eq { all_rows ; position ; defensive tackle } } ; eq { hop { filter_eq { all_rows ; position ; defensive tackle } ; player } ; bob myers } } = true | select the rows whose position record fuzzily matches to defensive tackle . there is only one such row in the table . the player record of this unqiue row is bob myers . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'defensive tackle_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'bob myers_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'defensive tackle_8': 'defensive tackle', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'bob myers_10': 'bob myers'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'defensive tackle_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'bob myers_10': [3]} | ['player', 'round', 'pick', 'position', 'nfl club'] | [['bobby watkins', '2', '23', 'halfback', 'chicago bears'], ['dean dugger', '4', '46', 'end', 'philadelphia eagles'], ['dave leggett', '7', '74', 'quarterback', 'chicago cardinals'], ['jerry krisher', '13', '153', 'center', 'philadelphia eagles'], ['john borton', '13', '157', 'quarterback', 'cleveland browns'], ['dick brubaker', '15', '170', 'end', 'chicago cardinals'], ['bob myers', '28', '328', 'defensive tackle', 'baltimore colts'], ['dave williams', '28', '330', 'guard', 'pittsburgh steelers']] |
jeep grand cherokee | https://en.wikipedia.org/wiki/Jeep_Grand_Cherokee | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1105695-9.html.csv | ordinal | in jeep grand cherokee , limited , overland were the earliest among those with 5.7 l hemi v8 engine . | {'scope': 'subset', 'row': '4', 'col': '1', 'order': '1', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'equal', 'value': '5.7 l hemi v8'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', '5.7 l hemi v8'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; engine ; 5.7 l hemi v8 }', 'tointer': 'select the rows whose engine record fuzzily matches to 5.7 l hemi v8 .'}, 'years', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; engine ; 5.7 l hemi v8 } ; years ; 1 }'}, 'notes'], 'result': 'limited , overland', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; engine ; 5.7 l hemi v8 } ; years ; 1 } ; notes }'}, 'limited , overland'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; engine ; 5.7 l hemi v8 } ; years ; 1 } ; notes } ; limited , overland } = true', 'tointer': 'select the rows whose engine record fuzzily matches to 5.7 l hemi v8 . select the row whose years record of these rows is 1st minimum . the notes record of this row is limited , overland .'} | eq { hop { nth_argmin { filter_eq { all_rows ; engine ; 5.7 l hemi v8 } ; years ; 1 } ; notes } ; limited , overland } = true | select the rows whose engine record fuzzily matches to 5.7 l hemi v8 . select the row whose years record of these rows is 1st minimum . the notes record of this row is limited , overland . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'engine_6': 6, '5.7l hemi v8_7': 7, 'years_8': 8, '1_9': 9, 'notes_10': 10, 'limited , overland_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'engine_6': 'engine', '5.7l hemi v8_7': '5.7 l hemi v8', 'years_8': 'years', '1_9': '1', 'notes_10': 'notes', 'limited , overland_11': 'limited , overland'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'engine_6': [0], '5.7l hemi v8_7': [0], 'years_8': [1], '1_9': [1], 'notes_10': [2], 'limited , overland_11': [3]} | ['years', 'engine', 'power', 'torque', 'notes'] | [['2005 - 2010', '3.7 l powertech v6', '-', 'n / a', 'laredo , limited'], ['2005 - 2007', '4.7 l powertech v8', '-', 'n / a', 'laredo , limited'], ['2008 - 2009', '4.7 l powertech v8', '-', 'n / a', 'laredo , limited'], ['2005 - 2008', '5.7 l hemi v8', '-', 'n / a', 'limited , overland'], ['2009 - 2010', '5.7 l hemi v8', '-', 'n / a', 'laredo , limited , overland'], ['2006 - 2010', '6.1 l hemi v8', '-', 'n / a', 'srt - 8'], ['2005 ( 2007 - 2008 in na ) -', '3.0 l om642 diesel v6', '-', 'n / a', 'laredo , limited , overland']] |
chris van der drift | https://en.wikipedia.org/wiki/Chris_van_der_Drift | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16864452-1.html.csv | aggregation | the average wins for chris van der drift was 1.43 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1.43', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'wins'], 'result': '1.43', 'ind': 0, 'tostr': 'avg { all_rows ; wins }'}, '1.43'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; wins } ; 1.43 } = true', 'tointer': 'the average of the wins record of all rows is 1.43 .'} | round_eq { avg { all_rows ; wins } ; 1.43 } = true | the average of the wins record of all rows is 1.43 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'wins_4': 4, '1.43_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '1.43_5': '1.43'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'wins_4': [0], '1.43_5': [1]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2004', 'formula bmw adac', 'team rosberg', '20', '0', '0', '0', '8', '168', '4th'], ['2005', 'formula bmw adac', 'team rosberg', '20', '1', '0', '1', '5', '149', '4th'], ['2006', 'formula renault 2.0 eurocup', 'jd motorsport', '14', '2', '2', '1', '6', '91', '2nd'], ['2006', 'formula renault 2.0 nec', 'jd motorsport', '14', '4', '7', '4', '7', '267', '2nd'], ['2007', 'international formula master', 'jd motorsport', '16', '2', '1', '2', '7', '65', '2nd'], ['2008', 'international formula master', 'jd motorsport', '16', '6', '6', '8', '10', '101', '1st'], ['2008 - 09', 'gp2 asia series', 'trident racing', '3', '0', '0', '0', '0', '5', '18th'], ['2008 - 09', 'a1 grand prix', 'new zealand', '4', '0', '0', '0', '0', '36', '7th'], ['2009', 'formula renault 3.5 series', 'epsilon euskadi', '17', '0', '0', '0', '1', '41', '11th'], ['2010', 'superleague formula', 'olympiacos cfp', '18', '4', '2', '3', '10', '653', '4th'], ['2010', 'superleague formula', 'galatasaray', '3', '0', '0', '0', '0', '358', '13th'], ['2011', 'superleague formula', 'new zealand', '3', '0', '0', '0', '0', '116', '7th'], ['2011', 'formula renault 3.5 series', 'mofaz racing', '7', '0', '0', '0', '1', '43', '12th'], ['2012', 'auto gp world series', 'manor mp motorsport', '12', '1', '0', '0', '4', '127', '4th']] |
list of best - selling music artists | https://en.wikipedia.org/wiki/List_of_best-selling_music_artists | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1291598-3.html.csv | aggregation | the average number of claimed sales by the best - selling music artists is 136.875 million . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '136.875 million', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'claimed sales'], 'result': '136.875 million', 'ind': 0, 'tostr': 'avg { all_rows ; claimed sales }'}, '136.875 million'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; claimed sales } ; 136.875 million } = true', 'tointer': 'the average of the claimed sales record of all rows is 136.875 million .'} | round_eq { avg { all_rows ; claimed sales } ; 136.875 million } = true | the average of the claimed sales record of all rows is 136.875 million . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'claimed sales_4': 4, '136.875 million_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'claimed sales_4': 'claimed sales', '136.875 million_5': '136.875 million'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'claimed sales_4': [0], '136.875 million_5': [1]} | ['artist', 'country of origin', 'period active', 'release - year of first charted record', 'genre', 'claimed sales'] | [['eagles', 'united states', '1971 - present', '1972', 'soft rock / country rock', '150 million'], ['rihanna', 'barbados united states', '2005 - present', '2005', 'r & b / pop / dance / hip - hop', '150 million'], ['u2', 'ireland', '1976 - present', '1980', 'rock', '150 million'], ['billy joel', 'united states', '1964 - present', '1971', 'pop / rock', '150 million'], ['phil collins', 'united kingdom', '1980 - 2011', '1981', 'adult contemporary', '150 million'], ['aerosmith', 'united states', '1970 - present', '1973', 'hard rock', '150 million'], ['frank sinatra', 'united states', '1935 - 1995', '1939', 'pop / swing', '150 million'], ['barbra streisand', 'united states', '1960 - present', '1963', 'pop / adult contemporary', '145 million'], ['garth brooks', 'united states', '1989 - present', '1989', 'country', '130 million'], ['genesis', 'united kingdom', '1967 - 1999 2006 - 2011', '1969', 'progressive rock / pop rock', '130 million'], ['donna summer', 'united states', '1968 - 2012', '1974', 'pop / disco / r & b', '130 million'], ['neil diamond', 'united states', '1966 - present', '1966', 'pop / rock', '125 million'], ['bruce springsteen', 'united states', '1972 - present', '1973', 'rock', '120 million'], ['bee gees', 'united kingdom', '1963 - 2003 2009 - 2012', '1963', 'pop / disco', '120 million'], ['julio iglesias', 'spain', '1968 - present', '1968', 'latin', '120 million'], ['dire straits', 'united kingdom', '1977 - 1995', '1978', 'rock / pop', '120 million']] |
1978 san francisco 49ers season | https://en.wikipedia.org/wiki/1978_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18674332-1.html.csv | majority | the san francisco 49ers lost all their games played in the month of november . | {'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'november'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; november }', 'tointer': 'select the rows whose date record fuzzily matches to november .'}, 'result', 'l'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november . for the result records of these rows , all of them fuzzily match to l .', 'tostr': 'all_eq { filter_eq { all_rows ; date ; november } ; result ; l } = true'} | all_eq { filter_eq { all_rows ; date ; november } ; result ; l } = true | select the rows whose date record fuzzily matches to november . for the result records of these rows , all of them fuzzily match to l . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'november_5': 5, 'result_6': 6, 'l_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'november_5': 'november', 'result_6': 'result', 'l_7': 'l'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'november_5': [0], 'result_6': [1], 'l_7': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 3 , 1978', 'cleveland browns', 'l 24 - 7', '68973'], ['2', 'september 10 , 1978', 'chicago bears', 'l 16 - 13', '49502'], ['3', 'september 17 , 1978', 'houston oilers', 'l 20 - 19', '46161'], ['4', 'september 24 , 1978', 'new york giants', 'l 27 - 10', '71536'], ['5', 'october 1 , 1978', 'cincinnati bengals', 'w 28 - 12', '41107'], ['6', 'october 8 , 1978', 'los angeles rams', 'l 27 - 10', '59337'], ['7', 'october 15 , 1978', 'new orleans saints', 'l 14 - 7', '37671'], ['8', 'october 22 , 1978', 'atlanta falcons', 'l 20 - 17', '44235'], ['9', 'october 29 , 1978', 'washington redskins', 'l 38 - 20', '53706'], ['10', 'november 5 , 1978', 'atlanta falcons', 'l 21 - 10', '55468'], ['11', 'november 12 , 1978', 'st louis cardinals', 'l 16 - 10', '33155'], ['12', 'november 19 , 1978', 'los angeles rams', 'l 31 - 28', '45022'], ['13', 'november 27 , 1978', 'pittsburgh steelers', 'l 24 - 7', '51657'], ['14', 'december 3 , 1978', 'new orleans saints', 'l 24 - 13', '50068'], ['15', 'december 10 , 1978', 'tampa bay buccaneers', 'w 6 - 3', '30931'], ['16', 'december 17 , 1978', 'detroit lions', 'l 33 - 14', '56674']] |
1997 cart season | https://en.wikipedia.org/wiki/1997_CART_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14638077-2.html.csv | unique | in the 1997 cart season , when the month is august , the only time maurício gugelmin was the winning driver was when pacwest was the winning team . | {'scope': 'subset', 'row': '15', 'col': '8', 'col_other': '9', 'criterion': 'equal', 'value': 'maurício gugelmin', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'august'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; august }', 'tointer': 'select the rows whose date record fuzzily matches to august .'}, 'winning driver', 'maurício gugelmin'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to august . among these rows , select the rows whose winning driver record fuzzily matches to maurício gugelmin .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin } }', 'tointer': 'select the rows whose date record fuzzily matches to august . among these rows , select the rows whose winning driver record fuzzily matches to maurício gugelmin . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; august }', 'tointer': 'select the rows whose date record fuzzily matches to august .'}, 'winning driver', 'maurício gugelmin'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to august . among these rows , select the rows whose winning driver record fuzzily matches to maurício gugelmin .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin }'}, 'winning team'], 'result': 'pacwest', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin } ; winning team }'}, 'pacwest'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin } ; winning team } ; pacwest }', 'tointer': 'the winning team record of this unqiue row is pacwest .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin } } ; eq { hop { filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin } ; winning team } ; pacwest } } = true', 'tointer': 'select the rows whose date record fuzzily matches to august . among these rows , select the rows whose winning driver record fuzzily matches to maurício gugelmin . there is only one such row in the table . the winning team record of this unqiue row is pacwest .'} | and { only { filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin } } ; eq { hop { filter_eq { filter_eq { all_rows ; date ; august } ; winning driver ; maurício gugelmin } ; winning team } ; pacwest } } = true | select the rows whose date record fuzzily matches to august . among these rows , select the rows whose winning driver record fuzzily matches to maurício gugelmin . there is only one such row in the table . the winning team record of this unqiue row is pacwest . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'date_8': 8, 'august_9': 9, 'winning driver_10': 10, 'maurício gugelmin_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'winning team_12': 12, 'pacwest_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'date_8': 'date', 'august_9': 'august', 'winning driver_10': 'winning driver', 'maurício gugelmin_11': 'maurício gugelmin', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'winning team_12': 'winning team', 'pacwest_13': 'pacwest'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'date_8': [0], 'august_9': [0], 'winning driver_10': [1], 'maurício gugelmin_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'winning team_12': [3], 'pacwest_13': [4]} | ['rnd', 'race name', 'circuit', 'city / location', 'date', 'pole position', 'fastest lap', 'winning driver', 'winning team', 'report'] | [['1', 'marlboro grand prix of miami presented by toyota', 'homestead - miami speedway', 'homestead , florida', 'march 2', 'alex zanardi', 'michael andretti', 'michael andretti', 'newman / haas racing', 'report'], ['2', 'sunbelt indycarnival australia', 'surfers paradise street circuit', 'surfers paradise , australia', 'april 6', 'alex zanardi', 'alex zanardi', 'scott pruett', 'patrick racing', 'report'], ['3', 'toyota grand prix of long beach', 'streets of long beach', 'long beach , california', 'april 13', 'gil de ferran', 'alex zanardi', 'alex zanardi', 'target chip ganassi', 'report'], ['4', 'bosch spark plug grand prix presented by toyota', 'nazareth speedway', 'nazareth , pennsylvania', 'april 27', 'paul tracy', 'paul tracy', 'paul tracy', 'marlboro team penske', 'report'], ['5', 'hollywood rio 400k', 'autódromo de jacarepaguá', 'rio de janeiro , brazil', 'may 11', 'maurício gugelmin', 'gil de ferran', 'paul tracy', 'marlboro team penske', 'report'], ['6', 'motorola 300', 'gateway international raceway', 'madison , illinois', 'may 24', 'raul boesel', 'dario franchitti', 'paul tracy', 'marlboro team penske', 'report'], ['7', 'miller genuine draft 200', 'milwaukee mile', 'west allis , wisconsin', 'june 1', 'paul tracy', 'paul tracy', 'greg moore', 'forsythe racing', 'report'], ['8', 'itt automotive detroit grand prix', 'the raceway on belle isle park', 'detroit , michigan', 'june 8', 'gil de ferran', 'dario franchitti', 'greg moore', 'forsythe racing', 'report'], ['9', "budweiser / gi joe 's 200", 'portland international raceway', 'portland , oregon', 'june 22', 'scott pruett', 'raul boesel', 'mark blundell', 'pacwest', 'report'], ['10', 'medic drug grand prix of cleveland', 'cleveland burke lakefront airport', 'cleveland , ohio', 'july 13', 'alex zanardi', 'alex zanardi', 'alex zanardi', 'target chip ganassi', 'report'], ['11', 'molson indy toronto', 'exhibition place', 'toronto , ontario', 'july 20', 'dario franchitti', 'mark blundell', 'mark blundell', 'pacwest', 'report'], ['12', 'us 500 presented by toyota', 'michigan international speedway', 'brooklyn , michigan', 'july 27', 'scott pruett', 'maurício gugelmin', 'alex zanardi', 'target chip ganassi', 'report'], ['13', 'miller 200', 'mid - ohio sports car course', 'lexington , ohio', 'august 10', 'bryan herta', 'alex zanardi', 'alex zanardi', 'target chip ganassi', 'report'], ['14', 'texaco / havoline 200', 'road america', 'elkhart lake , wisconsin', 'august 17', 'maurício gugelmin', 'alex zanardi', 'alex zanardi', 'target chip ganassi', 'report'], ['15', 'molson indy vancouver', 'streets of vancouver', 'vancouver , british columbia', 'august 31', 'alex zanardi', 'alex zanardi', 'maurício gugelmin', 'pacwest', 'report'], ['16', 'toyota grand prix of monterey', 'mazda raceway laguna seca', 'monterey , california', 'september 7', 'bryan herta', 'mark blundell', 'jimmy vasser', 'target chip ganassi', 'report']] |
world series of poker europe | https://en.wikipedia.org/wiki/World_Series_of_Poker_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12454156-1.html.csv | count | fabrizio baldassar was the runner up 1 time in the world series of poker europe . | {'scope': 'all', 'criterion': 'equal', 'value': 'fabrizio baldassari', 'result': '1', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner - up', 'fabrizio baldassari'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runner - up record fuzzily matches to fabrizio baldassari .', 'tostr': 'filter_eq { all_rows ; runner - up ; fabrizio baldassari }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; runner - up ; fabrizio baldassari } }', 'tointer': 'select the rows whose runner - up record fuzzily matches to fabrizio baldassari . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; runner - up ; fabrizio baldassari } } ; 1 } = true', 'tointer': 'select the rows whose runner - up record fuzzily matches to fabrizio baldassari . the number of such rows is 1 .'} | eq { count { filter_eq { all_rows ; runner - up ; fabrizio baldassari } } ; 1 } = true | select the rows whose runner - up record fuzzily matches to fabrizio baldassari . 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, 'runner - up_5': 5, 'fabrizio baldassari_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', 'runner - up_5': 'runner - up', 'fabrizio baldassari_6': 'fabrizio baldassari', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'runner - up_5': [0], 'fabrizio baldassari_6': [0], '1_7': [2]} | ['year', 'winner', 'winning hand', 'prize money', 'entrants', 'runner - up', 'losing hand'] | [['2007', 'annette obrestad', '7h 7s', '1000000', '362', 'john tabatabai', '5s 6d'], ['2008', 'john juanda', 'ks 6c', '868800', '362', 'stanislav alekhin', 'ac 9s'], ['2009', 'barry shulman', '10s 10c', '801603', '334', 'daniel negreanu', '4s 4d'], ['2010', 'james bord', '10d 10h', '830401', '346', 'fabrizio baldassari', '5s 5h'], ['2011', 'elio fox', 'ad 10s', '1400000', '593', 'chris moorman', 'ah 7s'], ['2012', 'phil hellmuth', 'ah 10d', '1058403', '420', 'sergii baranov', 'as 4c'], ['2013', 'adrián mateos', 'as kc', '1000000', '375', 'fabrice soulier', '9d 8d']] |
list of ngc objects ( 5001 - 6000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%285001%E2%80%936000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11051845-9.html.csv | comparative | object 5823 has a greater right ascension than object 5822 . | {'row_1': '2', 'row_2': '1', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ngc number', '5823'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ngc number record fuzzily matches to 5823 .', 'tostr': 'filter_eq { all_rows ; ngc number ; 5823 }'}, 'right ascension ( j2000 )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; ngc number ; 5823 } ; right ascension ( j2000 ) }', 'tointer': 'select the rows whose ngc number record fuzzily matches to 5823 . take the right ascension ( j2000 ) record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ngc number', '5822'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose ngc number record fuzzily matches to 5822 .', 'tostr': 'filter_eq { all_rows ; ngc number ; 5822 }'}, 'right ascension ( j2000 )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; ngc number ; 5822 } ; right ascension ( j2000 ) }', 'tointer': 'select the rows whose ngc number record fuzzily matches to 5822 . take the right ascension ( j2000 ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; ngc number ; 5823 } ; right ascension ( j2000 ) } ; hop { filter_eq { all_rows ; ngc number ; 5822 } ; right ascension ( j2000 ) } } = true', 'tointer': 'select the rows whose ngc number record fuzzily matches to 5823 . take the right ascension ( j2000 ) record of this row . select the rows whose ngc number record fuzzily matches to 5822 . take the right ascension ( j2000 ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; ngc number ; 5823 } ; right ascension ( j2000 ) } ; hop { filter_eq { all_rows ; ngc number ; 5822 } ; right ascension ( j2000 ) } } = true | select the rows whose ngc number record fuzzily matches to 5823 . take the right ascension ( j2000 ) record of this row . select the rows whose ngc number record fuzzily matches to 5822 . take the right ascension ( j2000 ) 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, 'ngc number_7': 7, '5823_8': 8, 'right ascension ( j2000 )_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'ngc number_11': 11, '5822_12': 12, 'right ascension ( j2000 )_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', 'ngc number_7': 'ngc number', '5823_8': '5823', 'right ascension ( j2000 )_9': 'right ascension ( j2000 )', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'ngc number_11': 'ngc number', '5822_12': '5822', 'right ascension ( j2000 )_13': 'right ascension ( j2000 )'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'ngc number_7': [0], '5823_8': [0], 'right ascension ( j2000 )_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'ngc number_11': [1], '5822_12': [1], 'right ascension ( j2000 )_13': [3]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )'] | [['5822', 'open cluster', 'lupus', '15h04 m', 'degree24 ′'], ['5823', 'open cluster', 'circinus', '15h05 m44 .8 s', 'degree37 ′ 30 ″'], ['5824', 'globular cluster', 'lupus', '15h03 m58 .5 s', 'degree04 ′ 04 ″'], ['5825', 'elliptical galaxy', 'boötes', '14h54 m31 .5 s', 'degree38 ′ 31 ″'], ['5838', 'lenticular galaxy', 'virgo', '15h05 m26 .3 s', 'degree05 ′ 57 ″'], ['5846', 'elliptical galaxy', 'virgo', '15h06 m29 .4 s', 'degree36 ′ 19 ″'], ['5850', 'spiral galaxy', 'virgo', '15h07 m07 .8 s', 'degree32 ′ 39 ″'], ['5866', 'lenticular galaxy', 'draco', '15h06 m29 .5 s', 'degree45 ′ 47 ″'], ['5877', 'triple star', 'lupus', '15h12 m53 .1 s', 'degree55 ′ 38 ″'], ['5879', 'galaxy', 'draco', '15h09 m46 .8 s', 'degree00 ′ 01 ″'], ['5882', 'planetary nebula', 'libra', '15h16 m49 .9 s', 'degree38 ′ 58 ″'], ['5885', 'barred spiral galaxy', 'libra', '15h15 m04 .1 s', 'degree05 ′ 10.0 ″'], ['5886', 'elliptical galaxy', 'boötes', '15h12 m45 .4 s', 'degree12 ′ 02 ″'], ['5888', 'barred spiral galaxy', 'boötes', '15h13 m07 .4 s', 'degree15 ′ 52 ″'], ['5890', 'lenticular galaxy', 'libra', '15h17 m51 .1 s', 'degree35 ′ 19 ″']] |
list of the league episodes | https://en.wikipedia.org/wiki/List_of_The_League_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28348757-3.html.csv | count | there were a total of 5 episodes with ratings under one million total households . | {'scope': 'all', 'criterion': 'less_than', 'value': '1.0', 'result': '5', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'us viewers ( million )', '1.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is less than 1.0 .', 'tostr': 'filter_less { all_rows ; us viewers ( million ) ; 1.0 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; us viewers ( million ) ; 1.0 } }', 'tointer': 'select the rows whose us viewers ( million ) record is less than 1.0 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; us viewers ( million ) ; 1.0 } } ; 5 } = true', 'tointer': 'select the rows whose us viewers ( million ) record is less than 1.0 . the number of such rows is 5 .'} | eq { count { filter_less { all_rows ; us viewers ( million ) ; 1.0 } } ; 5 } = true | select the rows whose us viewers ( million ) record is less than 1.0 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'us viewers (million)_5': 5, '1.0_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'us viewers (million)_5': 'us viewers ( million )', '1.0_6': '1.0', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'us viewers (million)_5': [0], '1.0_6': [0], '5_7': [2]} | ['no', '-', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['7', '1', 'vegas draft', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 16 , 2010', 'xle02001', '1.71'], ['8', '2', 'bro - lo el cuã ± ado', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 23 , 2010', 'xle02002', '1.05'], ['9', '3', 'the white knuckler', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'september 30 , 2010', 'xle02003', '0.89'], ['10', '4', 'the kluneberg', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'october 7 , 2010', 'xle02004', '0.82'], ['11', '5', 'the marathon', 'jackie marcus schaffer', 'craig digregorio', 'october 14 , 2010', 'xle02005', '0.86'], ['12', '6', 'the anniversary party', 'jeff schaffer', 'nick kroll & paul scheer', 'october 21 , 2010', 'xle02006', '0.62'], ['13', '7', 'ghost monkey', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'october 28 , 2010', 'xle02007', '0.67'], ['14', '8', 'the tie', 'jackie marcus schaffer', "dan o'keefe", 'november 4 , 2010', 'xle02008', '1.01'], ['15', '9', 'the expert witness', 'jeff schaffer', 'nick kroll & paul scheer', 'november 11 , 2010', 'xle02009', '1.00'], ['16', '10', 'high school reunion', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'november 18 , 2010', 'xle02010', '1.04'], ['18', '12', 'kegel the elf', 'jeff schaffer', 'jeff schaffer & jackie marcus schaffer', 'december 9 , 2010', 'xle02012', '1.05']] |
isabel cueto | https://en.wikipedia.org/wiki/Isabel_Cueto | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17086086-2.html.csv | unique | of the tournaments that isabel cueto participated in , the only one in sweden was on july 4th , 1988 . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'sweden', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'sweden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to sweden .', 'tostr': 'filter_eq { all_rows ; tournament ; sweden }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; tournament ; sweden } }', 'tointer': 'select the rows whose tournament record fuzzily matches to sweden . 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', 'sweden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to sweden .', 'tostr': 'filter_eq { all_rows ; tournament ; sweden }'}, 'date'], 'result': '4 july 1988', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; sweden } ; date }'}, '4 july 1988'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; sweden } ; date } ; 4 july 1988 }', 'tointer': 'the date record of this unqiue row is 4 july 1988 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; tournament ; sweden } } ; eq { hop { filter_eq { all_rows ; tournament ; sweden } ; date } ; 4 july 1988 } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to sweden . there is only one such row in the table . the date record of this unqiue row is 4 july 1988 .'} | and { only { filter_eq { all_rows ; tournament ; sweden } } ; eq { hop { filter_eq { all_rows ; tournament ; sweden } ; date } ; 4 july 1988 } } = true | select the rows whose tournament record fuzzily matches to sweden . there is only one such row in the table . the date record of this unqiue row is 4 july 1988 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'sweden_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '4 july 1988_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', 'sweden_8': 'sweden', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '4 july 1988_10': '4 july 1988'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'tournament_7': [0], 'sweden_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '4 july 1988_10': [3]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['4 july 1988', 'båstad , sweden', 'clay', 'sandra cecchini', '7 - 5 , 6 - 1'], ['1 august 1988', 'athens , greece', 'clay', 'laura golarsa', '6 - 0 , 6 - 1'], ['17 july 1989', 'estoril , portugal', 'clay', 'sandra cecchini', '7 - 6 ( 3 ) , 6 - 2'], ['31 july 1989', 'sofia , bulgaria', 'clay', 'katerina maleeva', '6 - 2 , 7 - 6 ( 3 )'], ['9 july 1990', 'palermo , italy', 'clay', 'barbara paulus', '6 - 2 , 6 - 3']] |
tedd williams | https://en.wikipedia.org/wiki/Tedd_Williams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445700-2.html.csv | unique | the fight against opponent ian freeman was the only loss for tedd williams and the only fight that went to round 3 . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '3', 'criterion': 'equal', 'value': '3', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'round', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; round ; 3 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; round ; 3 } }', 'tointer': 'select the rows whose round record is equal to 3 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'round', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; round ; 3 }'}, 'opponent'], 'result': 'ian freeman', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; round ; 3 } ; opponent }'}, 'ian freeman'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; round ; 3 } ; opponent } ; ian freeman }', 'tointer': 'the opponent record of this unqiue row is ian freeman .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; round ; 3 } } ; eq { hop { filter_eq { all_rows ; round ; 3 } ; opponent } ; ian freeman } } = true', 'tointer': 'select the rows whose round record is equal to 3 . there is only one such row in the table . the opponent record of this unqiue row is ian freeman .'} | and { only { filter_eq { all_rows ; round ; 3 } } ; eq { hop { filter_eq { all_rows ; round ; 3 } ; opponent } ; ian freeman } } = true | select the rows whose round record is equal to 3 . there is only one such row in the table . the opponent record of this unqiue row is ian freeman . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'round_7': 7, '3_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opponent_9': 9, 'ian freeman_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'round_7': 'round', '3_8': '3', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opponent_9': 'opponent', 'ian freeman_10': 'ian freeman'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'round_7': [0], '3_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opponent_9': [2], 'ian freeman_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time'] | [['loss', '7 - 1', 'ian freeman', 'decision', 'ufc 27', '3', '5:00'], ['win', '7 - 0', 'bill parker', 'submission ( armlock )', 'kotc 4 - gladiators', '1', '0:32'], ['win', '6 - 0', 'steve judson', 'ko', 'ufc 24', '1', '3:23'], ['win', '5 - 0', 'bull shaw', 'decision', 'hfp - holiday fight party', '1', '20:00'], ['win', '4 - 0', 'joe campanella', 'submission ( keylock )', 'wef 7 - stomp in the swamp', '1', '1:48'], ['win', '3 - 0', 'travis fulton', 'decision ( unanimous )', 'li - lionheart invitational', '1', '20:00'], ['win', '2 - 0', 'joseph marquez', 'submission ( palm strikes )', 'bri 3 - bas rutten invitational 3', '1', '1:50'], ['win', '1 - 0', 'robert burnell', 'submission', 'esf - empire one', '1', '1:23']] |
i am ... ( ayumi hamasaki album ) | https://en.wikipedia.org/wiki/I_Am..._%28Ayumi_Hamasaki_album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1754908-3.html.csv | ordinal | the evolution track of i am ... ( ayumi hamasaki album ) recorded the 2nd highest number of popularity weeks . | {'row': '2', 'col': '4', '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', 'weeks', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; weeks ; 2 }'}, 'title'], 'result': 'evolution', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; weeks ; 2 } ; title }'}, 'evolution'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; weeks ; 2 } ; title } ; evolution } = true', 'tointer': 'select the row whose weeks record of all rows is 2nd maximum . the title record of this row is evolution .'} | eq { hop { nth_argmax { all_rows ; weeks ; 2 } ; title } ; evolution } = true | select the row whose weeks record of all rows is 2nd maximum . the title record of this row is evolution . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'weeks_5': 5, '2_6': 6, 'title_7': 7, 'evolution_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', 'weeks_5': 'weeks', '2_6': '2', 'title_7': 'title', 'evolution_8': 'evolution'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'weeks_5': [0], '2_6': [0], 'title_7': [1], 'evolution_8': [2]} | ['date', 'title', 'peak position', 'weeks', 'sales'] | [['december 13 , 2000', 'm', '1', '18 weeks', '1319070'], ['january 31 , 2001', 'evolution', '1', '17 weeks', '955250'], ['march 7 , 2001', 'never ever', '1', '12 weeks', '756980'], ['may 16 , 2001', 'endless sorrow', '1', '11 weeks', '768510'], ['july 11 , 2001', 'unite !', '1', '17 weeks', '571110'], ['september 27 , 2001', 'dearest', '1', '16 weeks', '750420'], ['december 12 , 2001', 'a song is born', '1', '10 weeks', '441410'], ['march 6 , 2002', 'daybreak ( re - cut single )', '2', '9 weeks', '197140']] |
hyperon | https://en.wikipedia.org/wiki/Hyperon | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1129026-1.html.csv | comparative | the lambda hyperon particle has a lower rest mass than an omega particle . | {'row_1': '1', 'row_2': '12', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'particle', 'lambda'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose particle record fuzzily matches to lambda .', 'tostr': 'filter_eq { all_rows ; particle ; lambda }'}, 'rest mass mev / c 2'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; particle ; lambda } ; rest mass mev / c 2 }', 'tointer': 'select the rows whose particle record fuzzily matches to lambda . take the rest mass mev / c 2 record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'particle', 'omega'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose particle record fuzzily matches to omega .', 'tostr': 'filter_eq { all_rows ; particle ; omega }'}, 'rest mass mev / c 2'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; particle ; omega } ; rest mass mev / c 2 }', 'tointer': 'select the rows whose particle record fuzzily matches to omega . take the rest mass mev / c 2 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; particle ; lambda } ; rest mass mev / c 2 } ; hop { filter_eq { all_rows ; particle ; omega } ; rest mass mev / c 2 } } = true', 'tointer': 'select the rows whose particle record fuzzily matches to lambda . take the rest mass mev / c 2 record of this row . select the rows whose particle record fuzzily matches to omega . take the rest mass mev / c 2 record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; particle ; lambda } ; rest mass mev / c 2 } ; hop { filter_eq { all_rows ; particle ; omega } ; rest mass mev / c 2 } } = true | select the rows whose particle record fuzzily matches to lambda . take the rest mass mev / c 2 record of this row . select the rows whose particle record fuzzily matches to omega . take the rest mass mev / c 2 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, 'particle_7': 7, 'lambda_8': 8, 'rest mass mev / c 2_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'particle_11': 11, 'omega_12': 12, 'rest mass mev / c 2_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', 'particle_7': 'particle', 'lambda_8': 'lambda', 'rest mass mev / c 2_9': 'rest mass mev / c 2', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'particle_11': 'particle', 'omega_12': 'omega', 'rest mass mev / c 2_13': 'rest mass mev / c 2'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'particle_7': [0], 'lambda_8': [0], 'rest mass mev / c 2_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'particle_11': [1], 'omega_12': [1], 'rest mass mev / c 2_13': [3]} | ['particle', 'symbol', 'makeup', 'rest mass mev / c 2', 'isospin i', 'spin ( parity ) j p', 'commonly decays to'] | [['lambda', 'λ 0', 'u d s', '1 115.683 ( 6 )', '0', '1⁄2 +', 'p + + π or n 0 + π 0'], ['sigma', 'σ +', 'u u s', '1189.37 ( 0.7 )', '1', '1⁄2 +', 'p + + π 0 or n 0 + π +'], ['sigma', 'σ 0', 'u d s', '1192.642 ( 24 )', '1', '1⁄2 +', 'λ 0 + γ'], ['sigma', 'σ', 'd d s', '1197.449 ( 30 )', '1', '1⁄2 +', 'n 0 + π'], ['sigma resonance', 'σ ∗ + ( 1385 )', 'u u s', '1382.8 ( 4 )', '1', '3⁄2 +', 'λ + π or σ + π'], ['sigma resonance', 'σ ∗ 0 ( 1385 )', 'u d s', '1383.7 ± 1.0', '1', '3⁄2 +', 'λ + π or σ + π'], ['sigma resonance', 'σ ∗ ( 1385 )', 'd d s', '1387.2 ( 5 )', '1', '3⁄2 +', 'λ + π or σ + π'], ['xi', 'ξ 0', 'u s s', '1314.83 ( 20 )', '1⁄2', '1⁄2 +', 'λ 0 + π 0'], ['xi', 'ξ', 'd s s', '1321.31 ( 13 )', '1⁄2', '1⁄2 +', 'λ 0 + π'], ['xi resonance', 'ξ ∗ 0 ( 1530 )', 'u s s', '1531.80 ( 32 )', '1⁄2', '3⁄2 +', 'ξ + π'], ['xi resonance', 'ξ ∗ ( 1530 )', 'd s s', '1535.0 ( 6 )', '1⁄2', '3⁄2 +', 'ξ + π'], ['omega', 'ω', 's s s', '1672.45 ( 29 )', '0', '3⁄2 +', 'λ 0 + k or ξ 0 + π or ξ + π 0']] |
2008 - 09 philadelphia flyers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17511295-3.html.csv | majority | biron took the decision for the majority of games in the 2008 - 09 philadelphia flyers season . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'biron', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'decision', 'biron'], 'result': True, 'ind': 0, 'tointer': 'for the decision records of all rows , most of them fuzzily match to biron .', 'tostr': 'most_eq { all_rows ; decision ; biron } = true'} | most_eq { all_rows ; decision ; biron } = true | for the decision records of all rows , most of them fuzzily match to biron . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'decision_3': 3, 'biron_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'decision_3': 'decision', 'biron_4': 'biron'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'decision_3': [0], 'biron_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['october 11', 'ny rangers', '4 - 3', 'philadelphia', 'biron', '19623', '0 - 1 - 0'], ['october 13', 'montreal', '5 - 3', 'philadelphia', 'biron', '19323', '0 - 2 - 0'], ['october 14', 'philadelphia', '2 - 3', 'pittsburgh', 'niittymaki', '16965', '0 - 2 - 1'], ['october 16', 'philadelphia', '2 - 5', 'colorado', 'biron', '18007', '0 - 3 - 1'], ['october 18', 'philadelphia', '4 - 5', 'san jose', 'niittymaki', '17496', '0 - 3 - 2'], ['october 22', 'san jose', '7 - 6', 'philadelphia', 'biron', '19072', '0 - 3 - 3'], ['october 24', 'philadelphia', '6 - 3', 'new jersey', 'biron', '15529', '1 - 3 - 3'], ['october 25', 'new jersey', '2 - 3', 'philadelphia', 'biron', '19611', '2 - 3 - 3'], ['october 28', 'philadelphia', '7 - 0', 'atlanta', 'niittymaki', '13207', '3 - 3 - 3'], ['october 30', 'ny islanders', '2 - 3', 'philadelphia', 'biron', '18227', '4 - 3 - 3']] |
1957 vfl season | https://en.wikipedia.org/wiki/1957_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-12.html.csv | superlative | in the 1957 vfl season , the venue with the largest crowd size was windy hill . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'windy hill', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'windy hill'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; windy hill } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is windy hill .'} | eq { hop { argmax { all_rows ; crowd } ; venue } ; windy hill } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is windy hill . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'windy hill_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'windy hill_7': 'windy hill'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'windy hill_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '17.15 ( 117 )', 'richmond', '10.13 ( 73 )', 'arden street oval', '21000', '6 july 1957'], ['footscray', '9.11 ( 65 )', 'geelong', '9.10 ( 64 )', 'western oval', '23578', '6 july 1957'], ['south melbourne', '11.15 ( 81 )', 'st kilda', '9.17 ( 71 )', 'lake oval', '18000', '6 july 1957'], ['melbourne', '24.14 ( 158 )', 'fitzroy', '10.14 ( 74 )', 'mcg', '21370', '6 july 1957'], ['essendon', '12.16 ( 88 )', 'collingwood', '10.13 ( 73 )', 'windy hill', '26500', '6 july 1957'], ['hawthorn', '7.10 ( 52 )', 'carlton', '8.13 ( 61 )', 'glenferrie oval', '26000', '6 july 1957']] |
1977 vfl season | https://en.wikipedia.org/wiki/1977_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10887379-3.html.csv | aggregation | on april 16 , 1977 , average attendance at a vfl match was 21,268 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '21,268', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '21,268', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '21,268'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 21,268 } = true', 'tointer': 'the average of the crowd record of all rows is 21,268 .'} | round_eq { avg { all_rows ; crowd } ; 21,268 } = true | the average of the crowd record of all rows is 21,268 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '21,268_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '21,268_5': '21,268'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '21,268_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '14.18 ( 102 )', 'north melbourne', '16.9 ( 105 )', 'mcg', '19543', '16 april 1977'], ['geelong', '6.14 ( 50 )', 'hawthorn', '15.15 ( 105 )', 'kardinia park', '19336', '16 april 1977'], ['collingwood', '24.22 ( 166 )', 'essendon', '16.19 ( 115 )', 'victoria park', '26210', '16 april 1977'], ['carlton', '24.26 ( 170 )', 'st kilda', '9.9 ( 63 )', 'princes park', '19336', '16 april 1977'], ['south melbourne', '11.13 ( 79 )', 'richmond', '13.13 ( 91 )', 'lake oval', '25768', '16 april 1977'], ['footscray', '20.16 ( 136 )', 'fitzroy', '16.12 ( 108 )', 'vfl park', '17415', '16 april 1977']] |
peanut oil | https://en.wikipedia.org/wiki/Peanut_oil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1195910-1.html.csv | unique | the peanut oil with 94g total fat is the only one with 3 % of polyunsaturated fat . | {'scope': 'all', 'row': '10', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '3 %', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'polyunsaturated fat', '3 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose polyunsaturated fat record fuzzily matches to 3 % .', 'tostr': 'filter_eq { all_rows ; polyunsaturated fat ; 3 % }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; polyunsaturated fat ; 3 % } }', 'tointer': 'select the rows whose polyunsaturated fat record fuzzily matches to 3 % . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'polyunsaturated fat', '3 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose polyunsaturated fat record fuzzily matches to 3 % .', 'tostr': 'filter_eq { all_rows ; polyunsaturated fat ; 3 % }'}, 'total fat'], 'result': '94 g', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; polyunsaturated fat ; 3 % } ; total fat }'}, '94 g'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; polyunsaturated fat ; 3 % } ; total fat } ; 94 g }', 'tointer': 'the total fat record of this unqiue row is 94 g .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; polyunsaturated fat ; 3 % } } ; eq { hop { filter_eq { all_rows ; polyunsaturated fat ; 3 % } ; total fat } ; 94 g } } = true', 'tointer': 'select the rows whose polyunsaturated fat record fuzzily matches to 3 % . there is only one such row in the table . the total fat record of this unqiue row is 94 g .'} | and { only { filter_eq { all_rows ; polyunsaturated fat ; 3 % } } ; eq { hop { filter_eq { all_rows ; polyunsaturated fat ; 3 % } ; total fat } ; 94 g } } = true | select the rows whose polyunsaturated fat record fuzzily matches to 3 % . there is only one such row in the table . the total fat record of this unqiue row is 94 g . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'polyunsaturated fat_7': 7, '3%_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'total fat_9': 9, '94 g_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'polyunsaturated fat_7': 'polyunsaturated fat', '3%_8': '3 %', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'total fat_9': 'total fat', '94 g_10': '94 g'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'polyunsaturated fat_7': [0], '3%_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'total fat_9': [2], '94 g_10': [3]} | ['total fat', 'saturated fat', 'monounsaturated fat', 'polyunsaturated fat', 'smoke point'] | [['100 g', '11 g', '20 g ( 84 g in high oleic variety )', '69 g ( 4 g in high oleic variety )', 'degree'], ['100 g', '16 g', '23 g', '58 g', 'degree'], ['100 g', '7 g', '63 g', '28 g', 'degree'], ['100 g', '14 g', '73 g', '11 g', 'degree'], ['100 g', '15 g', '30 g', '55 g', 'degree'], ['100 g', '17 g', '46 g', '32 g', 'degree'], ['100 g', '25 g', '38 g', '37 g', 'degree'], ['71 g', '23 g ( 34 % )', '8 g ( 11 % )', '37 g ( 52 % )', 'degree'], ['100 g', '39 g', '45 g', '11 g', 'degree'], ['94 g', '52 g ( 55 % )', '32 g ( 34 % )', '3 g ( 3 % )', '200degree ( 400degree )'], ['81 g', '51 g ( 63 % )', '21 g ( 26 % )', '3 g ( 4 % )', 'degree']] |
list of fish hooks episodes | https://en.wikipedia.org/wiki/List_of_Fish_Hooks_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28146944-2.html.csv | count | william reiss directed seven fish hooks episodes with ch greenblatt . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ch greenblatt & william reiss', 'result': '7', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'ch greenblatt & william reiss'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to ch greenblatt & william reiss .', 'tostr': 'filter_eq { all_rows ; directed by ; ch greenblatt & william reiss }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; ch greenblatt & william reiss } }', 'tointer': 'select the rows whose directed by record fuzzily matches to ch greenblatt & william reiss . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; ch greenblatt & william reiss } } ; 7 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to ch greenblatt & william reiss . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; directed by ; ch greenblatt & william reiss } } ; 7 } = true | select the rows whose directed by record fuzzily matches to ch greenblatt & william reiss . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'directed by_5': 5, 'ch greenblatt & william reiss_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'directed by_5': 'directed by', 'ch greenblatt & william reiss_6': 'ch greenblatt & william reiss', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'ch greenblatt & william reiss_6': [0], '7_7': [2]} | ['no in series', 'title', 'directed by', 'story & storyboards by', 'original air date', 'us viewers ( millions )'] | [['1', 'bea stays in the picture', 'maxwell atoms', 'tim mckeon ( story ) maxwell atoms ( storyboards )', 'september 3 , 2010', '4.8'], ['2', 'fish sleepover party', 'william reiss', 'justin roiland ( story ) william reiss ( storyboards )', 'september 24 , 2010', '3.0'], ['8', 'doggonit', 'maxwell atoms', 'tim mckeon ( story ) carl faruolo ( storyboards )', 'october 22 , 2010', '2.6'], ['9', 'queen bea', 'ch greenblatt', 'tim mckeon ( story ) derek evanick ( storyboards )', 'october 29 , 2010', 'n / a'], ['10', 'fail fish', 'willam reiss', 'tim mckeon ( story ) ian wasseluk ( storyboards )', 'november 5 , 2010', 'n / a'], ['12', 'baldwin the super fish', 'william reiss', 'tim mckeon ( story ) carl faruolo ( storyboards )', 'december 3 , 2010', '2.8'], ['13', 'dances with wolf fish', 'william reiss', 'jackie buscarino ( story ) niki yang ( storyboards )', 'december 10 , 2010', '2.5'], ['14', 'the tale of sir oscar fish', 'william reiss', 'tim mckeon ( story ) ian wasseluk ( storyboards )', 'december 17 , 2010', 'n / a'], ['18', 'fishing for compliments : the albert glass story', 'ch greenblatt', 'justin roiland ( story ) carl faruolo ( storyboards )', 'january 29 , 2011', 'n / a'], ['19', 'big fish', 'ch greenblatt', 'ryan ridley ( story ) derek evanick ( storyboards )', 'february 4 , 2011', 'n / a'], ['23', 'flying fish', 'ch greenblatt & william reiss', 'tim mckeon ( story ) carl faruolo ( storyboards )', 'march 4 , 2011', '2.9'], ['24', 'two clams in love', 'ch greenblatt & william reiss', 'tim mckeon ( story ) alex hirsch ( storyboards )', 'march 11 , 2011', '3.0'], ['25', 'peopleing', 'maxwell atoms', 'justin roiland ( story ) maxwell atoms ( storyboards )', 'april 1 , 2011', '2.4'], ['29', 'riding in cars with fish', 'ch greenblatt & william reiss', 'tim mckeon ( story ) derek evanick ( storyboards )', 'june 18 , 2011', 'n / a'], ['30', "milo 's big idea", 'ch greenblatt & william reiss', 'jackie buscarino ( story ) neil graf ( storyboards )', 'june 18 , 2011', 'n / a'], ['32', 'good morning , freshwater', 'ch greenblatt & william reiss', 'tim mckeon ( story ) diana lafyatis ( storyboards )', 'july 2 , 2011', 'n / a'], ['35', 'run , oscar , run', 'ch greenblatt & william reiss', 'jessica gao ( story ) blake lemons ( storyboards )', 'august 12 , 2011', '3.5'], ['36', 'good times at pupu goodtimes', 'ch greenblatt & william reiss', 'tim mckeon ( story ) derek evanick ( storyboards )', 'august 19 , 2011', '3.3']] |
2008 - 09 cleveland cavaliers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17325580-5.html.csv | ordinal | the cleveland cavaliers ' game against detroit recorded their highest attendance of the 2008 - 09 season . | {'row': '10', 'col': '8', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'location attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 1 }'}, 'team'], 'result': 'detroit', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; 1 } ; team }'}, 'detroit'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; detroit } = true', 'tointer': 'select the row whose location attendance record of all rows is 1st maximum . the team record of this row is detroit .'} | eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; detroit } = true | select the row whose location attendance record of all rows is 1st maximum . the team record of this row is detroit . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '1_6': 6, 'team_7': 7, 'detroit_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', 'location attendance_5': 'location attendance', '1_6': '1', 'team_7': 'team', 'detroit_8': 'detroit'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '1_6': [0], 'team_7': [1], 'detroit_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['3', 'november 1', 'new orleans', 'l 92 - 104 ( ot )', 'žydrūnas ilgauskas ( 18 )', 'ben wallace ( 8 )', 'lebron james ( 13 )', 'new orleans arena 18150', '1 - 2'], ['4', 'november 3', 'dallas', 'w 100 - 81 ( ot )', 'lebron james ( 29 )', 'ben wallace ( 13 )', 'maurice williams ( 6 )', 'american airlines center 19923', '2 - 2'], ['5', 'november 5', 'chicago', 'w 107 - 93 ( ot )', 'lebron james ( 41 )', 'ben wallace ( 14 )', 'lebron james ( 6 )', 'quicken loans arena 20562', '3 - 2'], ['6', 'november 7', 'indiana', 'w 111 - 107 ( ot )', 'lebron james ( 27 )', 'lebron james ( 9 )', 'lebron james ( 8 )', 'quicken loans arena 20562', '4 - 2'], ['7', 'november 8', 'chicago', 'w 106 - 97 ( ot )', 'lebron james ( 41 )', 'lebron james ( 13 )', 'maurice williams ( 7 )', 'united center 21965', '5 - 2'], ['8', 'november 11', 'milwaukee', 'w 99 - 93 ( ot )', 'lebron james ( 41 )', 'anderson varejão , žydrūnas ilgauskas ( 10 )', 'lebron james ( 6 )', 'quicken loans arena 19842', '6 - 2'], ['9', 'november 13', 'denver', 'w 110 - 99 ( ot )', 'maurice williams ( 24 )', 'lebron james , anderson varejão ( 8 )', 'lebron james ( 11 )', 'quicken loans arena 20562', '7 - 2'], ['10', 'november 15', 'utah', 'w 105 - 93 ( ot )', 'lebron james ( 38 )', 'ben wallace ( 10 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '8 - 2'], ['11', 'november 18', 'new jersey', 'w 106 - 82 ( ot )', 'lebron james ( 31 )', 'žydrūnas ilgauskas ( 9 )', 'maurice williams ( 6 )', 'izod center 16911', '9 - 2'], ['12', 'november 19', 'detroit', 'l 89 - 96 ( ot )', 'maurice williams , lebron james ( 25 )', 'anderson varejão ( 11 )', 'lebron james ( 6 )', 'the palace of auburn hills 22076', '9 - 3'], ['13', 'november 22', 'atlanta', 'w 110 - 96 ( ot )', 'lebron james ( 24 )', 'ben wallace ( 8 )', 'lebron james ( 8 )', 'quicken loans arena 20562', '10 - 3'], ['14', 'november 25', 'new york', 'w 119 - 101 ( ot )', 'lebron james ( 26 )', 'žydrūnas ilgauskas ( 10 )', 'daniel gibson ( 7 )', 'madison square garden 19763', '11 - 3'], ['15', 'november 26', 'oklahoma city', 'w 117 - 82 ( ot )', 'žydrūnas ilgauskas ( 17 )', 'žydrūnas ilgauskas , anderson varejão ( 7 )', 'delonte west ( 10 )', 'quicken loans arena 19753', '12 - 3'], ['16', 'november 28', 'golden state', 'w 112 - 97 ( ot )', 'lebron james ( 23 )', 'wally szczerbiak , ben wallace ( 9 )', 'lebron james ( 8 )', 'quicken loans arena 20562', '13 - 3']] |
european poker tour | https://en.wikipedia.org/wiki/European_Poker_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1296513-5.html.csv | count | there were two poker events that were held in london . | {'scope': 'all', 'criterion': 'equal', 'value': 'london', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'london'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city record fuzzily matches to london .', 'tostr': 'filter_eq { all_rows ; city ; london }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; city ; london } }', 'tointer': 'select the rows whose city record fuzzily matches to london . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; city ; london } } ; 2 } = true', 'tointer': 'select the rows whose city record fuzzily matches to london . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; city ; london } } ; 2 } = true | select the rows whose city record fuzzily matches to london . 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, 'city_5': 5, 'london_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', 'city_5': 'city', 'london_6': 'london', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'city_5': [0], 'london_6': [0], '2_7': [2]} | ['date', 'city', 'event', 'winner', 'prize'] | [['10 - 14 september 2008', 'barcelona', 'ept barcelona open', 'sebastian ruthenberg', '1361000'], ['1 - 5 october 2008', 'london', '2008 european poker championships', 'michael martin', '1000000'], ['5 - 6 october 2008', 'london', 'ept london 1 million showdown', 'jason mercier', '516000'], ['28 oct - 1 nov 2008', 'budapest', 'ept hungarian open', 'will fry', '595839'], ['15 - 19 november 2008', 'warsaw', 'ept polish open', 'joão barbosa', 'zł1358420'], ['9 - 13 december 2008', 'prague', 'ept prague', 'salvatore bonavena', '774000'], ['5 - 10 january 2009', 'paradise island', 'ept pokerstars caribbean adventure', 'poorya nazari', '3000000'], ['20 - 24 january 2009', 'deauville', 'ept deauville', 'moritz kranich', '851400'], ['17 - 21 february 2009', 'copenhagen', 'ept scandinavian open', 'jens kyllönen', 'kr6542208'], ['10 - 14 march 2009', 'dortmund', 'ept german open', 'sandra naujoks', '917000'], ['18 - 23 april 2009', 'sanremo', 'ept sanremo', 'constant rijkenberg', '1508000'], ['28 apr - 3 may 2009', 'monte carlo', 'european poker tour grand final', 'pieter de korver', '2300000']] |
2003 - 04 fa cup | https://en.wikipedia.org/wiki/2003%E2%80%9304_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15828727-6.html.csv | count | a total of two games in the 2003 - 04 fa cup ended with a 1-1 draw score . | {'scope': 'all', 'criterion': 'equal', 'value': '1 -1', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '1 -1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 1 -1 .', 'tostr': 'filter_eq { all_rows ; score ; 1 -1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; 1 -1 } }', 'tointer': 'select the rows whose score record fuzzily matches to 1 -1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; 1 -1 } } ; 2 } = true', 'tointer': 'select the rows whose score record fuzzily matches to 1 -1 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; score ; 1 -1 } } ; 2 } = true | select the rows whose score record fuzzily matches to 1 -1 . 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, 'score_5': 5, '1 -1_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', 'score_5': 'score', '1 -1_6': '1 -1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], '1 -1_6': [0], '2_7': [2]} | ['tie no', 'home team', 'score', 'away team', 'attendance'] | [['1', 'liverpool', '1 - 1', 'portsmouth', '34669'], ['replay', 'portsmouth', '1 - 0', 'liverpool', '19529'], ['2', 'sunderland', '1 - 1', 'birmingham city', '24966'], ['replay', 'birmingham city', '0 - 2', 'sunderland', '25645'], ['3', 'sheffield united', '1 - 0', 'colchester united', '17074'], ['4', 'tranmere rovers', '2 - 1', 'swansea city', '12215'], ['5', 'fulham', '0 - 0', 'west ham united', '14705'], ['replay', 'west ham united', '0 - 3', 'fulham', '27934'], ['6', 'manchester united', '4 - 2', 'manchester city', '67228'], ['7', 'millwall', '1 - 0', 'burnley', '10420'], ['8', 'arsenal', '2 - 1', 'chelsea', '38136']] |
1995 - 96 atlanta hawks season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18493036-4.html.csv | unique | in the 1995 - 96 atlanta hawks season , when the hawks won , the only time the opponent was the orlando magic was on november 4th . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2,4', 'criterion': 'equal', 'value': 'orlando magic', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'orlando magic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to orlando magic .', 'tostr': 'filter_eq { all_rows ; opponent ; orlando magic }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent ; orlando magic } }', 'tointer': 'select the rows whose opponent record fuzzily matches to orlando magic . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'orlando magic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to orlando magic .', 'tostr': 'filter_eq { all_rows ; opponent ; orlando magic }'}, 'date'], 'result': 'november 4', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; orlando magic } ; date }'}, 'november 4'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; orlando magic } ; date } ; november 4 }', 'tointer': 'the date record of this unqiue row is november 4 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'orlando magic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to orlando magic .', 'tostr': 'filter_eq { all_rows ; opponent ; orlando magic }'}, 'score'], 'result': 'w 124 - 91', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; opponent ; orlando magic } ; score }'}, 'w 124 - 91'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; orlando magic } ; score } ; w 124 - 91 }', 'tointer': 'the score record of this unqiue row is w 124 - 91 .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; opponent ; orlando magic } ; date } ; november 4 } ; eq { hop { filter_eq { all_rows ; opponent ; orlando magic } ; score } ; w 124 - 91 } }', 'tointer': 'the date record of this unqiue row is november 4 . the score record of this unqiue row is w 124 - 91 .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; opponent ; orlando magic } } ; and { eq { hop { filter_eq { all_rows ; opponent ; orlando magic } ; date } ; november 4 } ; eq { hop { filter_eq { all_rows ; opponent ; orlando magic } ; score } ; w 124 - 91 } } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to orlando magic . there is only one such row in the table . the date record of this unqiue row is november 4 . the score record of this unqiue row is w 124 - 91 .'} | and { only { filter_eq { all_rows ; opponent ; orlando magic } } ; and { eq { hop { filter_eq { all_rows ; opponent ; orlando magic } ; date } ; november 4 } ; eq { hop { filter_eq { all_rows ; opponent ; orlando magic } ; score } ; w 124 - 91 } } } = true | select the rows whose opponent record fuzzily matches to orlando magic . there is only one such row in the table . the date record of this unqiue row is november 4 . the score record of this unqiue row is w 124 - 91 . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'opponent_10': 10, 'orlando magic_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'date_12': 12, 'november 4_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'score_14': 14, 'w 124 - 91_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'opponent_10': 'opponent', 'orlando magic_11': 'orlando magic', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_12': 'date', 'november 4_13': 'november 4', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'score_14': 'score', 'w 124 - 91_15': 'w 124 - 91'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'opponent_10': [0], 'orlando magic_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'date_12': [2], 'november 4_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'score_14': [4], 'w 124 - 91_15': [5]} | ['game', 'date', 'opponent', 'score', 'location / attendance', 'record'] | [['1', 'november 3', 'indiana pacers', 'l 106 - 111', 'the omni', '0 - 1'], ['game', 'date', 'opponent', 'score', 'location / attendance', 'record'], ['2', 'november 4', 'orlando magic', 'w 124 - 91', 'the omni', '1 - 1'], ['3', 'november 6', 'utah jazz', 'l 96 - 105', 'delta center', '1 - 2'], ['4', 'november 8', 'los angeles clippers', 'w 100 - 92', 'los angeles memorial sports arena', '2 - 2'], ['5', 'november 9', 'golden state warriors', 'w 125 - 121', 'oakland coliseum arena', '3 - 2'], ['6', 'november 11', 'dallas mavericks', 'w 113 - 100', 'reunion arena', '4 - 2'], ['7', 'november 14', 'charlotte hornets', 'w 111 - 104', 'the omni', '5 - 2'], ['8', 'november 17', 'miami heat', 'l 88 - 91', 'the omni', '5 - 3'], ['9', 'november 19', 'sacramento kings', 'w 108 - 94', 'arco arena', '6 - 3'], ['10', 'november 21', 'denver nuggets', 'l 99 - 107', 'mcnichols sports arena', '6 - 4'], ['11', 'november 22', 'phoenix suns', 'l 112 - 117', 'america west arena', '6 - 5'], ['12', 'november 25', 'toronto raptors', 'w 114 - 102', 'the omni', '7 - 5'], ['13', 'november 28', 'new york knicks', 'w 102 - 97 ( ot )', 'madison square garden', '8 - 5'], ['14', 'november 29', 'philadelphia 76ers', 'w 106 - 81', 'the omni', '9 - 5']] |
list of dams and reservoirs in asturias | https://en.wikipedia.org/wiki/List_of_dams_and_reservoirs_in_Asturias | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28702208-1.html.csv | majority | most of the embankment dams in asturias are less than 100m in height . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '100', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'embankment'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'embankment'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; embankment }', 'tointer': 'select the rows whose type record fuzzily matches to embankment .'}, 'height ( m )', '100'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose type record fuzzily matches to embankment . for the height ( m ) records of these rows , most of them are less than 100 .', 'tostr': 'most_less { filter_eq { all_rows ; type ; embankment } ; height ( m ) ; 100 } = true'} | most_less { filter_eq { all_rows ; type ; embankment } ; height ( m ) ; 100 } = true | select the rows whose type record fuzzily matches to embankment . for the height ( m ) records of these rows , most of them are less than 100 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'type_4': 4, 'embankment_5': 5, 'height (m)_6': 6, '100_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'type_4': 'type', 'embankment_5': 'embankment', 'height (m)_6': 'height ( m )', '100_7': '100'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'type_4': [0], 'embankment_5': [0], 'height (m)_6': [1], '100_7': [1]} | ['reservoir', 'basin', 'location', 'type', 'height ( m )', 'length along the top ( m )', 'drainage basin ( km square )', 'reservoir surface ( ha )', 'volume ( hm cubic )'] | [['alfilorios', 'barrea', 'ribera de arriba', 'embankment', '67.0', '171.7', '4.09', '52.0', '9.140'], ['arbón', 'navia', 'coaña , villayón', 'embankment', '35.0', '180.0', '2443.0', '270.0', '38.20'], ['barca , la', 'narcea', 'belmonte , tineo', 'arch', '73.5', '178.0', '1216.0', '194.0', '31.10'], ['doiras', 'navia', 'boal', 'arch - gravity', '90.0', '165.0', '2288.0', '347.0', '114.60'], ['florida , la', 'narcea', 'tineo', 'gravity', '19.0', '70.0', '1005.0', '18.40', '0.75'], ['furacón , el', 'nalón', 'trubia ( oviedo )', 'gravity', '14.0', '70.0', '2180.0', '19.0', '0.522'], ['granda , la', 'granda', 'gozón', 'embankment', '23.7', '270.0', '1.25', '32.50', '3.208'], ['jocica , la', 'dobra', 'amieva', 'arch', '87.0', '66.0', '39.0', '6.14', '0.4'], ['mortera , la', 'mortera', 'morcín', 'gravity', '8.0', '91.0', '0.0', '0.0', '0.017'], ['priañes', 'nora', 'oviedo , las regueras', 'gravity', '27.0', '50.0', '340.0', '35.17', '1.9'], ['saliencia', 'saliencia', 'somiedo', 'gravity', '20.0', '33.0', '48.0', '0.30', '0.02'], ['salime', 'navia', 'grandas de salime', 'gravity', '125.67', '250.0', '1806.0', '685.0', '266.30'], ['san andrés tacones', 'aboño', 'sa tacones ( gijón )', 'embankment', '22.0', '434.0', '37.5', '4.0', '71.0'], ['somiedo', 'somiedo', 'somiedo', 'gravity', '24.0', '18.0', '82.0', '0.29', '0.018'], ['tanes', 'nalón', 'caso , sobrescobio', 'gravity', '95.0', '195.0', '271.0', '159.0', '33.27'], ['trasona', 'alvares', 'trasona ( corvera )', 'gravity', '16.0', '332.0', '37.0', '61.0', '4.1'], ['valdemurio', 'trubia', 'quirós', 'gravity', '40.15', '119.0', '196.0', '1.43', '1.43'], ['valduno ii', 'nalón', 'las regueras', 'gravity', '9.9', '105.0', '2500.0', '34.36', '0.3'], ['valle', 'valle', 'somiedo', 'gravity', '12.5', '52.8', '39.0', '23.7', '3.7']] |
conference carolinas | https://en.wikipedia.org/wiki/Conference_Carolinas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11658094-1.html.csv | majority | most of the colleges in the carolinas conference have an enrollment of over 1000 students . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'enrollment', '1000'], 'result': True, 'ind': 0, 'tointer': 'for the enrollment records of all rows , most of them are greater than 1000 .', 'tostr': 'most_greater { all_rows ; enrollment ; 1000 } = true'} | most_greater { all_rows ; enrollment ; 1000 } = true | for the enrollment records of all rows , most of them are greater than 1000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'enrollment_3': 3, '1000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'enrollment_3': 'enrollment', '1000_4': '1000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'enrollment_3': [0], '1000_4': [0]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'joined', 'nickname'] | [['barton college', 'wilson , north carolina', '1902', 'private', '1200', '1930 1', 'bulldogs'], ['belmont abbey college', 'belmont , north carolina', '1876', 'private', '1320', '1989', 'crusaders'], ['converse college 2', 'spartanburg , south carolina', '1889', 'private', '750', '2008', 'valkyries'], ['erskine college', 'due west , south carolina', '1839', 'private', '920', '1995', 'flying fleet'], ['king university', 'bristol , tennessee', '1867', 'private', '1800', '2011', 'tornado'], ['leesmcrae college', 'banner elk , north carolina', '1899', 'private', '800', '1993', 'bobcats'], ['limestone college', 'gaffney , south carolina', '1845', 'private', '3300', '1998', 'saints'], ['mount olive college', 'mount olive , north carolina', '1951', 'private', '2500', '1988', 'trojans'], ['north greenville university', 'tigerville , south carolina', '1891', 'private', '2100', '2011', 'crusaders']] |
list of rampage killers | https://en.wikipedia.org/wiki/List_of_rampage_killers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17794738-6.html.csv | majority | the majority of rampage killers killed over 13 people . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '13', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'killed', '13'], 'result': True, 'ind': 0, 'tointer': 'for the killed records of all rows , most of them are greater than 13 .', 'tostr': 'most_greater { all_rows ; killed ; 13 } = true'} | most_greater { all_rows ; killed ; 13 } = true | for the killed records of all rows , most of them are greater than 13 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'killed_3': 3, '13_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'killed_3': 'killed', '13_4': '13'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'killed_3': [0], '13_4': [0]} | ['perpetrator', 'location', 'country', 'killed', 'injured'] | [['bryant , martin john , 28', 'port arthur , tas', 'australia', '35', '23'], ['unknown', 'siquijor', 'philippines', '32', '0.0'], ['wirjo , 42', 'banjarsari', 'indonesia', '20', '12'], ['formentera , arsenio', 'palompon', 'philippines', '17', '0.0'], ['hodeng', 'kampong tankulu', 'indonesia', '16', '01 1'], ['gz', 'gz', 'iz', '100.9', '100.9'], ['salazar , domingo , 42', 'san nicolas', 'philippines', '16', '01 1'], ['unknown', 'ternate', 'indonesia', '15', '04 4'], ['basobas , florentino', 'quezon , palawan', 'philippines', '15', '04 4'], ['antakin', 'kaningow', 'malaysia', '15', '03 3'], ['pusok anak ngaik , 28', 'kampong bukit merah', 'malaysia', '14', '04 4'], ['sz', 'qz', 'nz', '100.9', '100.9'], ['unknown', 'borneo', 'indonesia', '14', '0.0'], ['unknown', 'gondang', 'indonesia', '13', '03 3'], ['gray , david malcolm , 33', 'aramoana', 'new zealand', '13', '03 3'], ['kalinga boli', 'tagan', 'philippines', '13', '0.0'], ['two unknown men', 'zamboanga', 'philippines', '12', '14']] |
91st united states congress | https://en.wikipedia.org/wiki/91st_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1204065-2.html.csv | majority | all of the vacators of the 91st united states congress left their seats due to death . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'died', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'reason for change', 'died'], 'result': True, 'ind': 0, 'tointer': 'for the reason for change records of all rows , all of them fuzzily match to died .', 'tostr': 'all_eq { all_rows ; reason for change ; died } = true'} | all_eq { all_rows ; reason for change ; died } = true | for the reason for change records of all rows , all of them fuzzily match to died . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'reason for change_3': 3, 'died_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'reason for change_3': 'reason for change', 'died_4': 'died'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'reason for change_3': [0], 'died_4': [0]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['tennessee 8th', 'robert a everett ( d )', 'died january 26 , 1969', 'ed jones ( d )', 'march 25 , 1969'], ['massachusetts 6th', 'william h bates ( r )', 'died june 22 , 1969', 'michael j harrington ( d )', 'september 30 , 1969'], ['illinois 6th', 'daniel j ronan ( d )', 'died august 13 , 1969', 'george w collins ( d )', 'november 3 , 1970'], ['california 24th', 'glenard p lipscomb ( r )', 'died february 1 , 1970', 'john h rousselot ( r )', 'june 30 , 1970'], ['california 35th', 'james b utt ( r )', 'died march 1 , 1970', 'john g schmitz ( r )', 'june 30 , 1970'], ['connecticut 2nd', 'william st onge ( d )', 'died may 1 , 1970', 'robert h steele ( r )', 'november 3 , 1970'], ['ohio 19th', 'michael j kirwan ( d )', 'died july 27 , 1970', 'charles j carney ( d )', 'november 3 , 1970'], ['pennsylvania 9th', 'george watkins ( r )', 'died august 7 , 1970', 'john h ware iii ( r )', 'november 3 , 1970'], ['illinois 1st', 'william l dawson ( d )', 'died november 9 , 1970', 'vacant', 'not filled this term']] |
1st aiba european 2008 olympic qualifying tournament | https://en.wikipedia.org/wiki/1st_AIBA_European_2008_Olympic_Qualifying_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18801466-2.html.csv | count | at the 1st aiba european 2008 olympic qualifying tournament , 2 teams had a total medal count of 3 . | {'scope': 'all', 'criterion': 'equal', 'value': '3', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'total', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; total ; 3 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; total ; 3 } }', 'tointer': 'select the rows whose total record is equal to 3 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; total ; 3 } } ; 2 } = true', 'tointer': 'select the rows whose total record is equal to 3 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; total ; 3 } } ; 2 } = true | select the rows whose total record is equal to 3 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'total_5': 5, '3_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'total_5': 'total', '3_6': '3', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'total_5': [0], '3_6': [0], '2_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'ukraine ( ukr )', '2', '2', '0', '4'], ['2', 'belarus ( blr )', '2', '1', '1', '4'], ['3', 'hungary ( hun )', '2', '0', '0', '2'], ['4', 'ireland ( irl )', '1', '0', '2', '3'], ['5', 'bulgaria ( bul )', '1', '0', '0', '1'], ['5', 'france ( fra )', '1', '0', '0', '1'], ['5', 'sweden ( swe )', '0', '0', '0', '1'], ['5', 'russia ( rus )', '1', '0', '0', '1'], ['9', 'great britain ( gbr ) eng', '0', '2', '2', '4'], ['10', 'azerbaijan ( aze )', '0', '1', '1', '2'], ['10', 'france ( fra )', '0', '1', '1', '2'], ['10', 'moldova ( mda )', '0', '1', '1', '2'], ['10', 'poland ( pol )', '0', '1', '1', '2'], ['14', 'croatia ( cro )', '0', '1', '0', '1'], ['15', 'germany ( ger )', '0', '0', '3', '3'], ['16', 'turkey ( tur )', '0', '0', '2', '2'], ['16', 'lithuania ( ltu )', '0', '0', '2', '2'], ['16', 'armenia ( arm )', '0', '0', '1', '1'], ['16', 'finland ( fin )', '0', '0', '1', '1']] |
1944 vfl season | https://en.wikipedia.org/wiki/1944_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809142-14.html.csv | count | in half of the matches , the home teams scored less than 10.00 . | {'scope': 'all', 'criterion': 'less_than', 'value': '10.0', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'home team score', '10.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team score record is less than 10.0 .', 'tostr': 'filter_less { all_rows ; home team score ; 10.0 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; home team score ; 10.0 } }', 'tointer': 'select the rows whose home team score record is less than 10.0 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; home team score ; 10.0 } } ; 3 } = true', 'tointer': 'select the rows whose home team score record is less than 10.0 . the number of such rows is 3 .'} | eq { count { filter_less { all_rows ; home team score ; 10.0 } } ; 3 } = true | select the rows whose home team score record is less than 10.0 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'home team score_5': 5, '10.0_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'home team score_5': 'home team score', '10.0_6': '10.0', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'home team score_5': [0], '10.0_6': [0], '3_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '7.12 ( 54 )', 'south melbourne', '10.19 ( 79 )', 'junction oval', '8000', '5 august 1944'], ['geelong', '11.20 ( 86 )', 'hawthorn', '9.7 ( 61 )', 'kardinia park', '7000', '5 august 1944'], ['collingwood', '8.12 ( 60 )', 'footscray', '15.9 ( 99 )', 'victoria park', '9000', '5 august 1944'], ['carlton', '4.14 ( 38 )', 'melbourne', '8.6 ( 54 )', 'princes park', '10000', '5 august 1944'], ['north melbourne', '11.12 ( 78 )', 'fitzroy', '15.11 ( 101 )', 'arden street oval', '14000', '5 august 1944'], ['richmond', '11.17 ( 83 )', 'essendon', '12.15 ( 87 )', 'punt road oval', '26000', '5 august 1944']] |
1964 vfl season | https://en.wikipedia.org/wiki/1964_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10784349-18.html.csv | comparative | the crowd size at western oval was 3755 higher than when the location was windy hill . | {'row_1': '1', 'row_2': '2', 'col': '6', 'col_other': '5', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '3755', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'western oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to western oval .', 'tostr': 'filter_eq { all_rows ; venue ; western oval }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; western oval } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to western oval . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'windy hill'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to windy hill .', 'tostr': 'filter_eq { all_rows ; venue ; windy hill }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; windy hill } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to windy hill . take the crowd record of this row .'}], 'result': '3755', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; venue ; western oval } ; crowd } ; hop { filter_eq { all_rows ; venue ; windy hill } ; crowd } }'}, '3755'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; venue ; western oval } ; crowd } ; hop { filter_eq { all_rows ; venue ; windy hill } ; crowd } } ; 3755 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to western oval . take the crowd record of this row . select the rows whose venue record fuzzily matches to windy hill . take the crowd record of this row . the first record is 3755 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; venue ; western oval } ; crowd } ; hop { filter_eq { all_rows ; venue ; windy hill } ; crowd } } ; 3755 } = true | select the rows whose venue record fuzzily matches to western oval . take the crowd record of this row . select the rows whose venue record fuzzily matches to windy hill . take the crowd record of this row . the first record is 3755 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, 'venue_8': 8, 'western oval_9': 9, 'crowd_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'venue_12': 12, 'windy hill_13': 13, 'crowd_14': 14, '3755_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', 'venue_8': 'venue', 'western oval_9': 'western oval', 'crowd_10': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'venue_12': 'venue', 'windy hill_13': 'windy hill', 'crowd_14': 'crowd', '3755_15': '3755'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'venue_8': [0], 'western oval_9': [0], 'crowd_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'venue_12': [1], 'windy hill_13': [1], 'crowd_14': [3], '3755_15': [5]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '12.6 ( 78 )', 'melbourne', '4.14 ( 38 )', 'western oval', '20555', '22 august 1964'], ['essendon', '28.16 ( 184 )', 'south melbourne', '2.7 ( 19 )', 'windy hill', '16800', '22 august 1964'], ['richmond', '9.18 ( 72 )', 'hawthorn', '16.19 ( 115 )', 'punt road oval', '15500', '22 august 1964'], ['st kilda', '12.18 ( 90 )', 'geelong', '11.12 ( 78 )', 'junction oval', '27100', '22 august 1964'], ['north melbourne', '8.13 ( 61 )', 'collingwood', '14.8 ( 92 )', 'arden street oval', '21895', '22 august 1964'], ['fitzroy', '7.12 ( 54 )', 'carlton', '19.20 ( 134 )', 'brunswick street oval', '14151', '22 august 1964']] |
khym | https://en.wikipedia.org/wiki/KHYM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14993391-1.html.csv | superlative | the khym radio channel with the call sign k211ch has the highest erp wattage . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'erp w'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; erp w }'}, 'call sign'], 'result': 'k211ch', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; erp w } ; call sign }'}, 'k211ch'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; erp w } ; call sign } ; k211ch } = true', 'tointer': 'select the row whose erp w record of all rows is maximum . the call sign record of this row is k211ch .'} | eq { hop { argmax { all_rows ; erp w } ; call sign } ; k211ch } = true | select the row whose erp w record of all rows is maximum . the call sign record of this row is k211ch . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'erp w_5': 5, 'call sign_6': 6, 'k211ch_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'erp w_5': 'erp w', 'call sign_6': 'call sign', 'k211ch_7': 'k211ch'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'erp w_5': [0], 'call sign_6': [1], 'k211ch_7': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k297al', '107.3', 'dighton , kansas', '170', 'd', 'fcc'], ['k236 am', '95.1', 'elkhart , kansas', '170', 'd', 'fcc'], ['k207et', '89.3', 'healy , kansas', '75', 'd', 'fcc'], ['k239ax', '95.7', 'larned , kansas', '170', 'd', 'fcc'], ['k211ch', '90.5', 'leoti , kansas', '250', 'd', 'fcc'], ['k232dh', '94.3', 'ulysses , kansas', '170', 'd', 'fcc']] |
andrei tarkovsky filmography | https://en.wikipedia.org/wiki/Andrei_Tarkovsky_filmography | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15044621-3.html.csv | majority | all of andrei tarkovsky 's films were made in the soviet union . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'soviet union', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'country', 'soviet union'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , all of them fuzzily match to soviet union .', 'tostr': 'all_eq { all_rows ; country ; soviet union } = true'} | all_eq { all_rows ; country ; soviet union } = true | for the country records of all rows , all of them fuzzily match to soviet union . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'soviet union_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'soviet union_4': 'soviet union'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'soviet union_4': [0]} | ['year', 'english title', 'original title', 'country', 'length', 'participation as'] | [['1956', 'the killers', 'убийцы', 'soviet union', '19 min', 'actor'], ['1964', 'i am twenty', 'мне двадцать лет', 'soviet union', '189 min', 'actor'], ['1968', 'sergey lazo', 'сергей лазо', 'soviet union', '89 min', 'actor , film editor'], ['1968', 'one chance in one thousand', 'один шанс из тысячи', 'soviet union', '81 min', 'artistic director'], ['1974', 'sour grape', 'терпкий виноград', 'soviet union', '76 min', 'artistic advisor']] |
2002 open championship | https://en.wikipedia.org/wiki/2002_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18009462-7.html.csv | aggregation | an average score at 2002 open championship was 279 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '279', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '279', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '279'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 279 } = true', 'tointer': 'the average of the score record of all rows is 279 .'} | round_eq { avg { all_rows ; score } ; 279 } = true | the average of the score record of all rows is 279 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '279_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '279_5': '279'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '279_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'ernie els', 'south africa', '70 + 66 + 72 + 70 = 278', '- 6', 'playoff'], ['t1', 'thomas levet', 'france', '72 + 66 + 74 + 66 = 278', '- 6', 'playoff'], ['t1', 'stuart appleby', 'australia', '73 + 70 + 70 + 65 = 278', '- 6', 'playoff'], ['t1', 'steve elkington', 'australia', '71 + 73 + 68 + 66 = 278', '- 6', 'playoff'], ['t5', 'gary evans', 'england', '72 + 68 + 74 + 65 = 279', '- 5', '140000'], ['t5', 'pádraig harrington', 'ireland', '69 + 67 + 76 + 67 = 279', '- 5', '140000'], ['t5', 'shigeki maruyama', 'japan', '68 + 68 + 75 + 68 = 279', '- 5', '140000'], ['t8', 'thomas bjørn', 'denmark', '68 + 70 + 73 + 69 = 280', '- 4', '77500'], ['t8', 'sergio garcía', 'spain', '71 + 69 + 71 + 69 = 280', '- 4', '77500'], ['t8', 'retief goosen', 'south africa', '71 + 68 + 74 + 67 = 280', '- 4', '77500'], ['t8', 'søren hansen', 'denmark', '68 + 69 + 73 + 70 = 280', '- 4', '77500'], ['t8', 'scott hoch', 'united states', '74 + 69 + 71 + 66 = 280', '- 4', '77500'], ['t8', "peter o'malley", 'australia', '72 + 68 + 75 + 65 = 280', '- 4', '77500']] |
1961 coppa italia | https://en.wikipedia.org/wiki/1961_Coppa_Italia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17103867-1.html.csv | superlative | nino vaccarella ended the 1961 coppa italia with a first place grid . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'grid'], 'result': '1', 'ind': 0, 'tostr': 'min { all_rows ; grid }', 'tointer': 'the minimum grid record of all rows is 1 .'}, '1'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; grid } ; 1 }', 'tointer': 'the minimum grid record of all rows is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'grid'], 'result': None, 'ind': 2, 'tostr': 'argmin { all_rows ; grid }'}, 'driver'], 'result': 'nino vaccarella', 'ind': 3, 'tostr': 'hop { argmin { all_rows ; grid } ; driver }'}, 'nino vaccarella'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmin { all_rows ; grid } ; driver } ; nino vaccarella }', 'tointer': 'the driver record of the row with superlative grid record is nino vaccarella .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { min { all_rows ; grid } ; 1 } ; eq { hop { argmin { all_rows ; grid } ; driver } ; nino vaccarella } } = true', 'tointer': 'the minimum grid record of all rows is 1 . the driver record of the row with superlative grid record is nino vaccarella .'} | and { eq { min { all_rows ; grid } ; 1 } ; eq { hop { argmin { all_rows ; grid } ; driver } ; nino vaccarella } } = true | the minimum grid record of all rows is 1 . the driver record of the row with superlative grid record is nino vaccarella . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'min_0': 0, 'all_rows_7': 7, 'grid_8': 8, '1_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmin_2': 2, 'all_rows_10': 10, 'grid_11': 11, 'driver_12': 12, 'nino vaccarella_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'min_0': 'min', 'all_rows_7': 'all_rows', 'grid_8': 'grid', '1_9': '1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmin_2': 'argmin', 'all_rows_10': 'all_rows', 'grid_11': 'grid', 'driver_12': 'driver', 'nino vaccarella_13': 'nino vaccarella'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'min_0': [1], 'all_rows_7': [0], 'grid_8': [0], '1_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmin_2': [3], 'all_rows_10': [2], 'grid_11': [2], 'driver_12': [3], 'nino vaccarella_13': [4]} | ['driver', 'entrant', 'constructor', 'time / retired', 'grid', 'heat 1 / 2'] | [['giancarlo baghetti', 'scuderia sant ambroeus', 'porsche', '1.00:53.9', '2', '1st / 1st'], ['ernesto prinoth', 'scuderia dolomiti', 'lotus - climax', '+ 15.3 s', '3', '2nd / 2nd'], ['nino vaccarella', 'scuderia serenissima', 'cooper - maserati', '59 laps', '1', '3rd / 3rd'], ['roberto bussinello', 'isobele de tomaso', 'de tomaso - alfa romeo', '58 laps', '4', '5th / 4th'], ['roberto lippi', 'scuderia settecolli', 'de tomaso - osca', '58 laps', '6', '4th / 5th'], ['albino buticchi', 'scuderi sant ambroeus', 'cooper - climax', '57 laps', '8', '6th / 6th'], ['lucien de sanctis', 'scuderi sant ambroeus', 'cooper - climax', '56 laps', '9', '7th / 7th'], ['gaetano starrabba', 'gaetano starrabba', 'lotus - maserati', '31 laps', '5', '8th / 8th'], ['elio pandolfo', 'scuderia montegrappa', 'elios', '22 laps', '10', '9th / ret'], ['rovero campello', 'rovero campello', 'de sanctis - fiat', 'engine', '7', 'ret / dns'], ['ludovico scarfiotti', 'pescara racing club', 'de tomaso - osca', 'car not ready', '-', '- / -'], ['menato boffa', 'menato boffa', 'cooper - climax', 'car not ready', '-', '- / -']] |
1990 foster 's cup | https://en.wikipedia.org/wiki/1990_Foster%27s_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16387653-1.html.csv | aggregation | the average crowd attendance for the games played in the 1990 foster 's cup was 16470 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '16470', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '16470', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '16470'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 16470 } = true', 'tointer': 'the average of the crowd record of all rows is 16470 .'} | round_eq { avg { all_rows ; crowd } ; 16470 } = true | the average of the crowd record of all rows is 16470 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '16470_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '16470_5': '16470'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '16470_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date'] | [['footscray', '10.15 ( 75 )', 'richmond', '8.6 ( 54 )', 'waverley park', '16968', 'wednesday 7 february'], ['essendon', '5.11 ( 41 )', 'west coast', '4.14 ( 38 )', 'waverley park', '6988', 'saturday 10 february'], ['fitzroy', '12.13 ( 85 )', 'st kilda', '9.13 ( 67 )', 'waverley park', '12656', 'wednesday 14 february'], ['carlton', '17.7 ( 109 )', 'collingwood', '12.10 ( 82 )', 'waverley park', '41185', 'saturday 17 february'], ['north melbourne', '10.8 ( 68 )', 'west coast 1', '8.18 ( 66 )', 'waverley park', '4554', 'wednesday 21 february']] |
scotland national rugby league team match results | https://en.wikipedia.org/wiki/Scotland_national_rugby_league_team_match_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18304748-2.html.csv | count | a total of two scotland national rugby league matches took place in friendly competitions . | {'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '2', 'col': '3', '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': '2', '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 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; competition ; friendly } } ; 2 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; competition ; friendly } } ; 2 } = true | select the rows whose competition record fuzzily matches to friendly . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competition_5': 5, 'friendly_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competition_5': 'competition', 'friendly_6': 'friendly', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly_6': [0], '2_7': [2]} | ['date', 'result', 'competition', 'venue', 'attendance'] | [['29 october 2000', 'scotland 16 - 17 new zealand māori', 'world cup', 'glasgow', '2000'], ['1 november 2000', 'ireland 18 - 6 scotland', 'world cup', 'dublin', '2000'], ['5 november 2000', 'scotland 12 - 20 samoa', 'world cup', 'edinburgh', '2000'], ['3 july 2001', 'france 24 - 40 scotland', 'friendly', 'lezignan', '3000'], ['26 october 2003', 'scotland 22 - 24 ireland', 'european nations cup', 'glasgow', '1000'], ['9 november 2003', 'france 6 - 8 scotland', 'european nations cup', 'narbonne', '2000'], ['24 october 2004', 'scotland 30 - 22 wales', 'european nations cup', 'glasgow', '1000'], ['29 october 2004', 'ireland 43 - 10 scotland', 'european nations cup', 'navan', '600'], ['16 october 2005', 'wales 22 - 14 scotland', 'european nations cup', 'bridgend', '1000'], ['23 october 2005', 'scotland 6 - 12 ireland', 'european nations cup', 'glasgow', '1000'], ['29 october 2006', 'wales 14 - 21 scotland', 'world cup qualification', 'bridgend', '2000'], ['27 october 2007', 'france 46 - 16 scotland', 'friendly', 'perpignan', '7000'], ['4 november 2007', 'scotland 16 - 18 wales', 'world cup qualification', 'glasgow', '1000'], ['26 october 2008', 'scotland 18 - 36 france', 'world cup', 'canberra', '9000'], ['5 november 2008', 'scotland 18 - 16 fiji', 'world cup', 'gosford', '10000'], ['8 november 2008', 'scotland 0 - 48 tonga', 'world cup', 'rockhampton', '6000'], ['17 october 2009', 'italy - 0 - 104 scotland', 'european nations cup', 'padova', '2139'], ['1 november 2009', 'scotland 22 - 10 lebanon', 'european nations cup', 'glasgow', '752'], ['8 november 2009', 'wales 28 - 16 scotland', 'european nations cup', 'bridgend', '1608']] |
1913 world series | https://en.wikipedia.org/wiki/1913_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1332220-1.html.csv | ordinal | game one of the 1913 world series had the third highest attendance of the five games . | {'row': '1', 'col': '5', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 3 }'}, 'game'], 'result': '1', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 3 } ; game }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; game } ; 1 } = true', 'tointer': 'select the row whose attendance record of all rows is 3rd maximum . the game record of this row is 1 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; game } ; 1 } = true | select the row whose attendance record of all rows is 3rd maximum . the game record of this row is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'game_7': 7, '1_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '3_6': '3', 'game_7': 'game', '1_8': '1'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'game_7': [1], '1_8': [2]} | ['game', 'date', 'location', 'time', 'attendance'] | [['1', 'october 7', 'polo grounds ( iv )', '2:06', '36291'], ['2', 'october 8', 'shibe park', '2:22', '20563'], ['3', 'october 9', 'polo grounds ( iv )', '2:11', '36896'], ['4', 'october 10', 'shibe park', '2:09', '20568'], ['5', 'october 11', 'polo grounds ( iv )', '1:39', '36632']] |
good news network | https://en.wikipedia.org/wiki/Good_News_Network | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14986573-1.html.csv | count | for good news network , when the city of license is in georgia , there were 4 times when the class was a. | {'scope': 'subset', 'criterion': 'equal', 'value': 'a', 'result': '4', 'col': '5', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'ga'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city of license', 'ga'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; city of license ; ga }', 'tointer': 'select the rows whose city of license record fuzzily matches to ga .'}, 'class', 'a'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose city of license record fuzzily matches to ga . among these rows , select the rows whose class record fuzzily matches to a .', 'tostr': 'filter_eq { filter_eq { all_rows ; city of license ; ga } ; class ; a }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; city of license ; ga } ; class ; a } }', 'tointer': 'select the rows whose city of license record fuzzily matches to ga . among these rows , select the rows whose class record fuzzily matches to a . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; city of license ; ga } ; class ; a } } ; 4 } = true', 'tointer': 'select the rows whose city of license record fuzzily matches to ga . among these rows , select the rows whose class record fuzzily matches to a . the number of such rows is 4 .'} | eq { count { filter_eq { filter_eq { all_rows ; city of license ; ga } ; class ; a } } ; 4 } = true | select the rows whose city of license record fuzzily matches to ga . among these rows , select the rows whose class record fuzzily matches to a . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'city of license_6': 6, 'ga_7': 7, 'class_8': 8, 'a_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'city of license_6': 'city of license', 'ga_7': 'ga', 'class_8': 'class', 'a_9': 'a', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'city of license_6': [0], 'ga_7': [0], 'class_8': [1], 'a_9': [1], '4_10': [3]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['wlpe', '91.7', 'augusta , ga', '1150', 'a', 'fcc'], ['wgph', '91.5', 'vidalia , ga', '31000', 'c2', 'fcc'], ['wwgf', '107.5', 'donalsonville , ga', '6000', 'a', 'fcc'], ['wpwb', '90.5', 'byron , ga', '16500', 'c2', 'fcc'], ['wlpf', '98.5', 'ocilla , ga', '2300', 'a', 'fcc'], ['wziq', '106.5', 'smithville , ga', '2450', 'a', 'fcc'], ['wlpg', '91.7', 'florence , sc', '20000', 'c2', 'fcc'], ['wpma', '102.7', 'greensboro , ga', '7500', 'c3', 'fcc'], ['wthp', '94.3', 'gibson , ga', '6300', 'c3', 'fcc'], ['wlpt', '88.3', 'jesup , ga', '20000', 'c1', 'fcc'], ['wsja', '91.3', 'york , al', '5000', 'a', 'fcc'], ['wlgp', '100.3', 'jacksonville , nc', '100000', 'c1', 'fcc']] |
remittance | https://en.wikipedia.org/wiki/Remittance | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2941963-1.html.csv | majority | in remittance 2009 , the majority of time was under 23 seconds . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '23', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'remittances 2009', '23'], 'result': True, 'ind': 0, 'tointer': 'for the remittances 2009 records of all rows , most of them are less than 23 .', 'tostr': 'most_less { all_rows ; remittances 2009 ; 23 } = true'} | most_less { all_rows ; remittances 2009 ; 23 } = true | for the remittances 2009 records of all rows , most of them are less than 23 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'remittances 2009_3': 3, '23_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'remittances 2009_3': 'remittances 2009', '23_4': '23'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'remittances 2009_3': [0], '23_4': [0]} | ['country', 'remittances 2008', 'remittances 2009', 'remittances 2010', 'remittances 2011'] | [['india', '49.98', '49.20', '53.48', '63.82'], ['china', '22.69', '22.90', '33.44', '40.48'], ['mexico', '26.04', '22.08', '22.08', '23.59'], ['philippines', '18.63', '19.73', '21.37', '22.97'], ['nigeria', '19.21', '18.37', '19.82', '20.62'], ['france', '16.28', '16.06', '16.71', '19.31'], ['egypt', '8.69', '7.15', '12.45', '14.32'], ['germany', '10.97', '11.30', '11.73', '13.16'], ['pakistan', '7.04', '8.72', '9.69', '12.26'], ['bangladesh', '8.93', '10.52', '10.85', '12.07'], ['belgium', '10.42', '10.44', '10.30', '10.91'], ['spain', '10.15', '8.95', '9.11', '9.91'], ['vietnam', '6.81', '6.02', '8.26', '8.60'], ['south korea', '9.07', '7.28', '7.06', '8.49']] |
1958 green bay packers season | https://en.wikipedia.org/wiki/1958_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14656268-2.html.csv | superlative | the largest attendance occurred during the game on december 14th , 1958 . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '12', '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': 'december 14 , 1958', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'december 14 , 1958'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; december 14 , 1958 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is december 14 , 1958 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; december 14 , 1958 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is december 14 , 1958 . | 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, 'december 14 , 1958_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', 'december 14 , 1958_7': 'december 14 , 1958'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'december 14 , 1958_7': [2]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance'] | [['1', 'september 28 , 1958', 'chicago bears', 'l 34 - 20', 'city stadium', '32150'], ['2', 'october 5 , 1958', 'detroit lions', 't 13 - 13', 'city stadium', '32053'], ['3', 'october 12 , 1958', 'baltimore colts', 'l 24 - 17', 'milwaukee county stadium', '24553'], ['4', 'october 19 , 1958', 'washington redskins', 'l 37 - 21', 'griffith stadium', '25228'], ['5', 'october 26 , 1958', 'philadelphia eagles', 'w 38 - 35', 'city stadium', '31043'], ['6', 'november 2 , 1958', 'baltimore colts', 'l 56 - 0', 'memorial stadium', '51333'], ['7', 'november 9 , 1958', 'chicago bears', 'l 24 - 10', 'wrigley field', '48424'], ['8', 'november 16 , 1958', 'los angeles rams', 'l 20 - 7', 'city stadium', '28051'], ['9', 'november 23 , 1958', 'san francisco 49ers', 'l 33 - 12', 'milwaukee county stadium', '19786'], ['10', 'november 27 , 1958', 'detroit lions', 'l 24 - 14', 'briggs stadium', '50971'], ['11', 'december 7 , 1958', 'san francisco 49ers', 'l 48 - 21', 'kezar stadium', '50793'], ['12', 'december 14 , 1958', 'los angeles rams', 'l 34 - 20', 'los angeles memorial coliseum', '54634']] |
1951 vfl season | https://en.wikipedia.org/wiki/1951_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10701914-10.html.csv | comparative | in the 1951 vfl season , the match that took place at princes park had a larger crowd than the match that took place at brunswick street oval . | {'row_1': '3', 'row_2': '4', 'col': '6', 'col_other': '5', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'princes park'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to princes park .', 'tostr': 'filter_eq { all_rows ; venue ; princes park }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; princes park } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to princes park . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'brunswick street oval'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to brunswick street oval .', 'tostr': 'filter_eq { all_rows ; venue ; brunswick street oval }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; brunswick street oval } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to brunswick street oval . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; venue ; princes park } ; crowd } ; hop { filter_eq { all_rows ; venue ; brunswick street oval } ; crowd } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to princes park . take the crowd record of this row . select the rows whose venue record fuzzily matches to brunswick street oval . take the crowd record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; venue ; princes park } ; crowd } ; hop { filter_eq { all_rows ; venue ; brunswick street oval } ; crowd } } = true | select the rows whose venue record fuzzily matches to princes park . take the crowd record of this row . select the rows whose venue record fuzzily matches to brunswick street oval . take the crowd 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, 'venue_7': 7, 'princes park_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'brunswick street oval_12': 12, 'crowd_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', 'venue_7': 'venue', 'princes park_8': 'princes park', 'crowd_9': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'brunswick street oval_12': 'brunswick street oval', 'crowd_13': 'crowd'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'princes park_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'brunswick street oval_12': [1], 'crowd_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '7.7 ( 49 )', 'south melbourne', '13.15 ( 93 )', 'junction oval', '21000', '30 june 1951'], ['collingwood', '10.12 ( 72 )', 'footscray', '12.5 ( 77 )', 'victoria park', '25000', '30 june 1951'], ['carlton', '14.20 ( 104 )', 'north melbourne', '5.10 ( 40 )', 'princes park', '22000', '30 june 1951'], ['fitzroy', '10.14 ( 74 )', 'hawthorn', '11.9 ( 75 )', 'brunswick street oval', '8500', '7 july 1951'], ['essendon', '10.14 ( 74 )', 'richmond', '10.10 ( 70 )', 'windy hill', '30000', '7 july 1951'], ['melbourne', '7.7 ( 49 )', 'geelong', '12.12 ( 84 )', 'mcg', '22500', '7 july 1951']] |
east kent mavericks | https://en.wikipedia.org/wiki/East_Kent_Mavericks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16994082-1.html.csv | count | the east kent mavericks had 1 tie in 3 different years . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'ties', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ties record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; ties ; 1 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; ties ; 1 } }', 'tointer': 'select the rows whose ties record is equal to 1 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; ties ; 1 } } ; 3 } = true', 'tointer': 'select the rows whose ties record is equal to 1 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; ties ; 1 } } ; 3 } = true | select the rows whose ties record is equal to 1 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'ties_5': 5, '1_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'ties_5': 'ties', '1_6': '1', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'ties_5': [0], '1_6': [0], '3_7': [2]} | ['season', 'division', 'wins', 'ties', 'final position'] | [['2001', 'british senior flag league , southern', '3', '1', '2 / 4'], ['2002', 'british senior flag league , nine - man league', '5', '3', '2 / 7'], ['2003 to 2005', 'did not compete', 'did not compete', 'did not compete', 'did not compete'], ['2006', 'bafl division two south', '0', '0', '4 / 4'], ['2007', 'bafl division two south east', '5', '0', '3 / 6'], ['2008', 'bafl division two south east', '6', '0', '3 / 5'], ['2009', 'bafl division two south east', '8', '1', '1 / 4'], ['2010', 'bafl division one south east', '8', '1', '1 / 4'], ['2011', 'bafl division one south east', '2', '6', ''], ['2012', 'bafl division one south and central', '8', '2', '8 / 2']] |
ranked list of norwegian counties | https://en.wikipedia.org/wiki/Ranked_list_of_Norwegian_counties | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1064198-3.html.csv | majority | the majority of norwegian counties had percentages lower than 6 % in 2000 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '6', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', '% ( 2000 )', '6'], 'result': True, 'ind': 0, 'tointer': 'for the % ( 2000 ) records of all rows , most of them are less than 6 .', 'tostr': 'most_less { all_rows ; % ( 2000 ) ; 6 } = true'} | most_less { all_rows ; % ( 2000 ) ; 6 } = true | for the % ( 2000 ) records of all rows , most of them are less than 6 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, '% (2000)_3': 3, '6_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', '% (2000)_3': '% ( 2000 )', '6_4': '6'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], '% (2000)_3': [0], '6_4': [0]} | ['rank', 'county', '% ( 1960 )', '% ( 2000 )', '% ( 2040 )'] | [['1', 'oslo', '13.2', '11.3', '12.8'], ['2', 'akershus', '6.3', '10.4', '11.9'], ['3', 'hordaland', '9.4', '9.7', '10.2'], ['4', 'rogaland', '6.6', '8.3', '9.9'], ['5', 'sør - trøndelag', '5.8', '5.8', '6.0'], ['6', 'østfold', '5.6', '5.5', '5.5'], ['7', 'buskerud', '4.6', '5.2', '5.4'], ['8', 'møre og romsdal', '5.9', '5.4', '4.8'], ['9', 'nordland', '6.6', '5.3', '3.9'], ['10', 'vestfold', '4.8', '4.7', '4.7'], ['11', 'hedmark', '4.9', '4.1', '3.4'], ['12', 'oppland', '4.6', '4.0', '3.3'], ['13', 'vest - agder', '3.0', '3.4', '3.6'], ['14', 'telemark', '4.1', '3.6', '3.0'], ['15', 'troms', '3.5', '3.3', '2.7'], ['16', 'nord - trøndelag', '3.2', '2.8', '2.4'], ['17', 'aust - agder', '2.1', '2.2', '2.3'], ['18', 'sogn og fjordane', '2.8', '2.4', '1.8'], ['19', 'finnmark', '2.0', '1.6', '1.2'], ['sum', 'norway', '100.0', '100.0', '100.0']] |
aveiro district | https://en.wikipedia.org/wiki/Aveiro_District | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1794599-1.html.csv | aggregation | the municipalities in the aveiro district have an average population of 38009 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '38009', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pop'], 'result': '38009', 'ind': 0, 'tostr': 'avg { all_rows ; pop }'}, '38009'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pop } ; 38009 } = true', 'tointer': 'the average of the pop record of all rows is 38009 .'} | round_eq { avg { all_rows ; pop } ; 38009 } = true | the average of the pop record of all rows is 38009 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pop_4': 4, '38009_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pop_4': 'pop', '38009_5': '38009'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pop_4': [0], '38009_5': [1]} | ['name', 'area ( km square )', 'pop', 'pop / area ( 1 / km square )', 'no p', 'no c / no t', 'subregion'] | [['águeda', '335.3', '47729', '148', '20', '1', 'baixo vouga'], ['albergaria - a - velha', '155.4', '25497', '164', '8', '0', 'baixo vouga'], ['anadia', '216.6', '31671', '146', '15', '1', 'baixo vouga'], ['arouca', '329.1', '24019', '73', '20', '0', 'entre douro e vouga'], ['aveiro', '199.9', '73626', '368', '14', '1', 'baixo vouga'], ['castelo de paiva', '115.0', '17089', '149', '9', '0 / 2', 'tmega'], ['espinho', '21.1', '31703', '1503', '5', '1 / 1', 'grande porto'], ['estarreja', '108.4', '28279', '261', '7', '1 / 3', 'baixo vouga'], ['ílhavo', '73.5', '39247', '534', '4', '2', 'baixo vouga'], ['mealhada', '110.7', '20496', '194', '8', '1', 'baixo vouga'], ['murtosa', '73.3', '9657', '132', '4', '0 / 1', 'baixo vouga'], ['oliveira de azeméis', '163.5', '71243', '436', '19', '1 / 9', 'entre douro e vouga'], ['oliveira do bairro', '87.3', '22365', '256', '6', '1', 'baixo vouga'], ['ovar', '147.4', '56715', '385', '8', '2 / 3', 'baixo vouga'], ['santa maria da feira', '215.1', '142295', '662', '31', '3 / 13', 'entre douro e vouga'], ['são joão da madeira', '7.9', '21538', '2726', '1', '1 / 0', 'entre douro e vouga'], ['sever do vouga', '129.6', '12940', '100', '9', '0', 'baixo vouga'], ['vagos', '169.9', '23205', '137', '11', '0 / 2', 'baixo vouga'], ['vale de cambra', '146.5', '22864', '169', '9', '1', 'entre douro e vouga']] |
gulf coast athletic conference | https://en.wikipedia.org/wiki/Gulf_Coast_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10577579-2.html.csv | ordinal | philander smith college has the 2nd lowest enrollment among institutions in the gulf coast athletic conference . | {'row': '4', 'col': '7', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'enrollment', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; enrollment ; 2 }'}, 'institution'], 'result': 'philander smith college', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; enrollment ; 2 } ; institution }'}, 'philander smith college'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; enrollment ; 2 } ; institution } ; philander smith college } = true', 'tointer': 'select the row whose enrollment record of all rows is 2nd minimum . the institution record of this row is philander smith college .'} | eq { hop { nth_argmin { all_rows ; enrollment ; 2 } ; institution } ; philander smith college } = true | select the row whose enrollment record of all rows is 2nd minimum . the institution record of this row is philander smith college . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '2_6': 6, 'institution_7': 7, 'philander smith college_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', 'enrollment_5': 'enrollment', '2_6': '2', 'institution_7': 'institution', 'philander smith college_8': 'philander smith college'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '2_6': [0], 'institution_7': [1], 'philander smith college_8': [2]} | ['institution', 'location', 'mens nickname', 'womens nickname', 'founded', 'type', 'enrollment', 'joined'] | [['dillard university', 'new orleans , louisiana', 'bleu devils', 'lady bleu devils', '1869', 'private / ( methodist & church of christ )', '900', '1981'], ['edward waters college', 'jacksonville , florida', 'tigers', 'lady tigers', '1866', 'private / ( african methodist )', '800', '2010'], ['fisk university', 'nashville , tennessee', 'bulldogs', 'lady bulldogs', '1866', 'private / ( church of christ )', '800', '2010'], ['philander smith college', 'little rock , arkansas', 'panthers', 'lady panthers', '1864', 'private / ( methodist )', '700', '2011'], ['southern university at new orleans', 'new orleans , louisiana', 'black knights', 'lady knights', '1956', 'public', '3200', '1986'], ['talladega college', 'talladega , alabama', 'tornadoes', 'lady tornadoes', '1867', 'private / ( united church of christ )', '600', '1999 , 2011'], ['tougaloo college', 'tougaloo , mississippi', 'bulldogs', 'lady bulldogs', '1869', 'private / ( church of christ )', '900', '1981']] |
minimum - maximum | https://en.wikipedia.org/wiki/Minimum-Maximum | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1768696-2.html.csv | majority | regardless of the different regions that kraftwerk released their album minimum maximum in , the lyrics sang on the album stayed in english . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'english', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'lyrics', 'english'], 'result': True, 'ind': 0, 'tointer': 'for the lyrics records of all rows , most of them fuzzily match to english .', 'tostr': 'most_eq { all_rows ; lyrics ; english } = true'} | most_eq { all_rows ; lyrics ; english } = true | for the lyrics records of all rows , most of them fuzzily match to english . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'lyrics_3': 3, 'english_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'lyrics_3': 'lyrics', 'english_4': 'english'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'lyrics_3': [0], 'english_4': [0]} | ['region', 'date', 'label', 'format', 'catalog number', 'lyrics'] | [['germany', 'june 6 , 2005', 'emi', 'cd', '3 12046 2', 'german'], ['germany', 'june 6 , 2005', 'emi', '4 x vinyl', '3 11828 1', 'german'], ['eu except germany', 'june 6 , 2005', 'emi', 'cd', '560 6112', 'english'], ['eu except germany', 'june 6 , 2005', 'emi', '4 x vinyl', '560 6111', 'english'], ['eu except germany', 'april 24 , 2006', 'emi', 'sacd', '3 34996 2', 'english'], ['united states', 'june 7 , 2005', 'astralwerks', 'cd', 'asw 60611', 'english'], ['japan', 'august 10 , 2005', 'emi', 'cd', 'tocp - 66427', 'german'], ['japan', 'august 10 , 2005', 'emi', 'cd', 'tocp - 66425', 'english'], ['australasia', 'july 18 , 2005', 'emi', 'cd', '7243 5 60616 2 0 ( australian 2 cd release )', 'english']] |
rowing at the 2008 summer olympics - men 's lightweight double sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_lightweight_double_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662685-5.html.csv | aggregation | the average time for the racers in the men 's lightweight double sculls at the 2008 summer olympics was 6:21.73 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '6:21.73', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '6:21.73', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '6:21.73'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 6:21.73 } = true', 'tointer': 'the average of the time record of all rows is 6:21.73 .'} | round_eq { avg { all_rows ; time } ; 6:21.73 } = true | the average of the time record of all rows is 6:21.73 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '6:21.73_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '6:21.73_5': '6:21.73'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '6:21.73_5': [1]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'mads rasmussen , rasmus quist', 'denmark', '6:14.84', 'sa / b'], ['2', 'douglas vandor , cameron sylvester', 'canada', '6:17.58', 'sa / b'], ['3', 'zsolt hirling , tamã ¡ s varga', 'hungary', '6:19.60', 'r'], ['4', 'rodolfo collazo , angel javier garcia', 'uruguay', '6:25.86', 'r'], ['5', 'thiago gomes , thiago almeida', 'brazil', '6:30.78', 'r']] |
1940 vfl season | https://en.wikipedia.org/wiki/1940_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807253-15.html.csv | unique | essendon is the only home team that played at windy hill during the 1940 vfl season . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'windy hill', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'windy hill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to windy hill .', 'tostr': 'filter_eq { all_rows ; venue ; windy hill }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; windy hill } }', 'tointer': 'select the rows whose venue record fuzzily matches to windy hill . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'windy hill'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to windy hill .', 'tostr': 'filter_eq { all_rows ; venue ; windy hill }'}, 'home team'], 'result': 'essendon', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; windy hill } ; home team }'}, 'essendon'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; windy hill } ; home team } ; essendon }', 'tointer': 'the home team record of this unqiue row is essendon .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; windy hill } } ; eq { hop { filter_eq { all_rows ; venue ; windy hill } ; home team } ; essendon } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to windy hill . there is only one such row in the table . the home team record of this unqiue row is essendon .'} | and { only { filter_eq { all_rows ; venue ; windy hill } } ; eq { hop { filter_eq { all_rows ; venue ; windy hill } ; home team } ; essendon } } = true | select the rows whose venue record fuzzily matches to windy hill . there is only one such row in the table . the home team record of this unqiue row is essendon . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'windy hill_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_9': 9, 'essendon_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'windy hill_8': 'windy hill', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_9': 'home team', 'essendon_10': 'essendon'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'windy hill_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'home team_9': [2], 'essendon_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '10.19 ( 79 )', 'south melbourne', '10.13 ( 73 )', 'glenferrie oval', '8000', '10 august 1940'], ['geelong', '12.15 ( 87 )', 'richmond', '16.11 ( 107 )', 'corio oval', '10000', '10 august 1940'], ['essendon', '10.12 ( 72 )', 'fitzroy', '10.15 ( 75 )', 'windy hill', '18000', '10 august 1940'], ['collingwood', '12.21 ( 93 )', 'north melbourne', '6.17 ( 53 )', 'victoria park', '6500', '10 august 1940'], ['st kilda', '13.9 ( 87 )', 'footscray', '15.22 ( 112 )', 'junction oval', '13000', '10 august 1940'], ['melbourne', '14.12 ( 96 )', 'carlton', '20.13 ( 133 )', 'mcg', '16500', '10 august 1940']] |
jake o'brien | https://en.wikipedia.org/wiki/Jake_O%27Brien | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15985163-2.html.csv | comparative | jake o'brien 's fight against christian wellisch lasted more rounds than his fight against pat harmon . | {'row_1': '7', 'row_2': '13', 'col': '6', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'christian wellisch'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to christian wellisch .', 'tostr': 'filter_eq { all_rows ; opponent ; christian wellisch }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; christian wellisch } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to christian wellisch . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'pat harmon'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to pat harmon .', 'tostr': 'filter_eq { all_rows ; opponent ; pat harmon }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; pat harmon } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to pat harmon . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; christian wellisch } ; round } ; hop { filter_eq { all_rows ; opponent ; pat harmon } ; round } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to christian wellisch . take the round record of this row . select the rows whose opponent record fuzzily matches to pat harmon . take the round record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; christian wellisch } ; round } ; hop { filter_eq { all_rows ; opponent ; pat harmon } ; round } } = true | select the rows whose opponent record fuzzily matches to christian wellisch . take the round record of this row . select the rows whose opponent record fuzzily matches to pat harmon . take the round 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, 'opponent_7': 7, 'christian wellisch_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'pat harmon_12': 12, 'round_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', 'opponent_7': 'opponent', 'christian wellisch_8': 'christian wellisch', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'pat harmon_12': 'pat harmon', 'round_13': 'round'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'christian wellisch_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'pat harmon_12': [1], 'round_13': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round'] | [['win', '15 - 4', 'miodrag petković', 'decision ( unanimous )', 'flawless fighting championship 1 : the beginning', '3'], ['win', '14 - 4', 'james shaw', 'submission ( arm - triangle choke )', 'indy mma', '1'], ['loss', '13 - 4', 'gegard mousasi', 'submission ( guillotine choke )', 'dream 15', '1'], ['win', '13 - 3', 'toni valtonen', 'decision ( unanimous )', 'fight festival 27', '3'], ['win', '12 - 3', 'dave hess', 'submission ( kimura )', 'mma big show - triple threat', '2'], ['loss', '11 - 3', 'jon jones', 'submission ( guillotine choke )', 'ufc 100', '2'], ['win', '11 - 2', 'christian wellisch', 'decision ( split )', 'ufc 94', '3'], ['loss', '10 - 2', 'cain velasquez', 'tko ( punches )', 'ufc : silva vs irvin', '1'], ['loss', '10 - 1', 'andrei arlovski', 'tko ( punches )', 'ufc 82', '2'], ['win', '10 - 0', 'heath herring', 'decision ( unanimous )', 'ufc fight night 8', '3'], ['win', '9 - 0', 'josh schockman', 'decision ( unanimous )', 'ufc 65', '3'], ['win', '8 - 0', 'kristof midoux', 'tko ( referee stoppage )', 'ufc fight night 6', '2'], ['win', '7 - 0', 'pat harmon', 'tko', 'ufl - united fight league', '1'], ['win', '6 - 0', 'antoine hayes', 'tko', 'lof - legends of fighting 6', '1'], ['win', '5 - 0', 'jay white', 'ko ( punch )', 'wec 19', '1'], ['win', '4 - 0', 'johnathan ivey', 'tko', 'lof - legends of fighting 4', '1'], ['win', '3 - 0', 'anthony ferguson', 'tko', 'lof - revolution', '1'], ['win', '2 - 0', 'paul bowers', 'tko', 'ifc - integrated fighting classic 3', '1'], ['win', '1 - 0', 'chris clark', 'tko ( referee stoppage )', 'mt - madtown throwdown 3', '1']] |
uk film council completion fund | https://en.wikipedia.org/wiki/UK_Film_Council_Completion_Fund | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12181447-1.html.csv | comparative | the award for the film furnace four was higher than the award for the hardest part . | {'row_1': '6', 'row_2': '4', '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', 'film', 'furnace four'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose film record fuzzily matches to furnace four .', 'tostr': 'filter_eq { all_rows ; film ; furnace four }'}, 'award'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; film ; furnace four } ; award }', 'tointer': 'select the rows whose film record fuzzily matches to furnace four . take the award record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'film', 'the hardest part'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose film record fuzzily matches to the hardest part .', 'tostr': 'filter_eq { all_rows ; film ; the hardest part }'}, 'award'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; film ; the hardest part } ; award }', 'tointer': 'select the rows whose film record fuzzily matches to the hardest part . take the award record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; film ; furnace four } ; award } ; hop { filter_eq { all_rows ; film ; the hardest part } ; award } } = true', 'tointer': 'select the rows whose film record fuzzily matches to furnace four . take the award record of this row . select the rows whose film record fuzzily matches to the hardest part . take the award record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; film ; furnace four } ; award } ; hop { filter_eq { all_rows ; film ; the hardest part } ; award } } = true | select the rows whose film record fuzzily matches to furnace four . take the award record of this row . select the rows whose film record fuzzily matches to the hardest part . take the award 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, 'film_7': 7, 'furnace four_8': 8, 'award_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'film_11': 11, 'the hardest part_12': 12, 'award_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', 'film_7': 'film', 'furnace four_8': 'furnace four', 'award_9': 'award', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'film_11': 'film', 'the hardest part_12': 'the hardest part', 'award_13': 'award'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'film_7': [0], 'furnace four_8': [0], 'award_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'film_11': [1], 'the hardest part_12': [1], 'award_13': [3]} | ['film', 'director ( s )', 'producer ( s )', 'writer ( s )', 'date', 'award'] | [['bale ( formerly known as hay bales )', 'al mackay', 'andrew ryder', 'al mackay', '25 / 03 / 2009', '7600'], ['the elemental', 'robert sproul - cran', 'katie crook', 'robert sproul - cran', '25 / 03 / 2009', '7120'], ['together', 'eicke bettinga', 'zorana piggott', 'eicke bettinga , zorana piggott', '25 / 03 / 2009', '6730'], ['the hardest part', 'oliver refson', 'adam shakinovsky', 'oliver refson', '25 / 03 / 2009', '2500'], ['the chapel', 'ben winter', 'ben winter', 'ben winter', '25 / 03 / 2009', '3785'], ['furnace four', 'haydn butler', 'vanessa arden - wood', 'ali muriel', '25 / 03 / 2009', '4685']] |
miss mundo dominicana 2004 | https://en.wikipedia.org/wiki/Miss_Mundo_Dominicana_2004 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21346767-3.html.csv | majority | most of contestants in the miss mundo dominicana 2004 peagant were above 18 years of age . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '18', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'age', '18'], 'result': True, 'ind': 0, 'tointer': 'for the age records of all rows , most of them are greater than 18 .', 'tostr': 'most_greater { all_rows ; age ; 18 } = true'} | most_greater { all_rows ; age ; 18 } = true | for the age records of all rows , most of them are greater than 18 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'age_3': 3, '18_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'age_3': 'age', '18_4': '18'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'age_3': [0], '18_4': [0]} | ['province , community', 'contestant', 'age', 'height', 'hometown', 'geographical regions'] | [['azua', 'julissa alcantara de fiallo', '22', 'm ( ft 9in )', 'santo domingo', 'sur occidente'], ['barahona', 'desireé álvarez lama', '19', 'm ( ft 9\xa03⁄4 in )', 'santa cruz de barahona', 'sur occidente'], ['com dom en california', 'mónica angulo pucheaux', '18', 'm ( ft 9\xa01⁄4 in )', 'los angeles', 'exterior'], ['com dom en miami', 'onidys reynosa espinal', '21', 'm ( ft 8in )', 'miami', 'exterior'], ['com dom en nueva york', 'joslyn cabrera ruiz', '18', 'm ( ft 11\xa01⁄4 in )', 'new york', 'exterior'], ['distrito nacional', 'katherine germania almos rey', '24', 'm ( ft 10\xa01⁄2 in )', 'villa juana', 'sur oriente'], ['duarte', 'lissette abreu ynoa', '22', 'm ( ft 7\xa01⁄4 in )', 'constanza', 'cibao oriental'], ['independencia', 'nathalie venecia gutiérrez arias', '20', 'm ( ft 11\xa03⁄4 in )', 'santo domingo', 'sur occidente'], ['la altagracia', 'patrizia karina gagg jiménez', '20', 'm ( ft 11\xa01⁄4 in )', 'villa hermosa', 'sur oriente'], ['la romana', 'anna karina toledo espinoza', '22', 'm ( ft 6\xa01⁄4 in )', 'la romana', 'sur oriente'], ['la vega', 'cindy magdalena torrealba cruz', '17', 'm ( ft 10\xa01⁄2 in )', 'jarabacoa', 'cibao central'], ['maría trinidad sánchez', 'massiel javier cañizarez', '19', 'm ( ft 10\xa03⁄4 in )', 'cabrera', 'cibao oriental'], ['monseñor nouel', 'claudia julissa cruz rodríguez', '18', 'm ( ft 9in )', 'bonao', 'cibao central'], ['monte cristi', 'hareld ellien mossle casado', '17', 'm ( ft 7in )', 'santiago de los caballeros', 'cibao occidental'], ['puerto plata', 'wilma joana abreu nazario', '20', 'm ( ft 6\xa01⁄2 in )', 'santiago de los caballeros', 'cibao occidental'], ['salcedo', 'josefina de arias camacho', '24', 'm ( ft 5\xa01⁄4 in )', 'santo domingo', 'cibao central'], ['samaná', 'genevet nicol gutiérrez kourie', '18', 'm ( ft 7\xa03⁄4 in )', 'santa bárbara de samaná', 'cibao oriental'], ['san pedro de macorís', 'natascha forestieri de los santos', '23', 'm ( ft 0in )', 'san pedro de macorís', 'sur oriente'], ['santiago', 'cindy guerrero reynoso', '26', 'm ( ft 10in )', 'santiago de los caballeros', 'cibao occidental']] |
1895 ahac season | https://en.wikipedia.org/wiki/1895_AHAC_Season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11756240-1.html.csv | superlative | in the 1895 ahac season , the team that had the highest number of goals against was the montreal crystals . | {'scope': 'all', 'col_superlative': '7', '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', 'goals against'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; goals against }'}, 'team'], 'result': 'montreal crystals', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; goals against } ; team }'}, 'montreal crystals'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; goals against } ; team } ; montreal crystals } = true', 'tointer': 'select the row whose goals against record of all rows is maximum . the team record of this row is montreal crystals .'} | eq { hop { argmax { all_rows ; goals against } ; team } ; montreal crystals } = true | select the row whose goals against record of all rows is maximum . the team record of this row is montreal crystals . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'goals against_5': 5, 'team_6': 6, 'montreal crystals_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'goals against_5': 'goals against', 'team_6': 'team', 'montreal crystals_7': 'montreal crystals'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'goals against_5': [0], 'team_6': [1], 'montreal crystals_7': [2]} | ['team', 'games played', 'wins', 'losses', 'ties', 'goals for', 'goals against'] | [['montreal victorias', '8', '6', '2', '0', '35', '20'], ['montreal hockey club', '8', '4', '4', '0', '33', '22'], ['ottawa', '8', '4', '4', '0', '25', '24'], ['montreal crystals', '7', '3', '4', '0', '21', '39'], ['quebec', '7', '2', '5', '0', '18', '27']] |
steam locomotives of ireland | https://en.wikipedia.org/wiki/Steam_locomotives_of_Ireland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1290024-4.html.csv | aggregation | for the steam locomotives of ireland , the average number made was 3.83 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '3.83', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'quantity made'], 'result': '3.83', 'ind': 0, 'tostr': 'avg { all_rows ; quantity made }'}, '3.83'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; quantity made } ; 3.83 } = true', 'tointer': 'the average of the quantity made record of all rows is 3.83 .'} | round_eq { avg { all_rows ; quantity made } ; 3.83 } = true | the average of the quantity made record of all rows is 3.83 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'quantity made_4': 4, '3.83_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'quantity made_4': 'quantity made', '3.83_5': '3.83'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'quantity made_4': [0], '3.83_5': [1]} | ['class', 'type', 'fleet numbers', 'quantity made', 'manufacturer', 'date made', 'date withdrawn'] | [['1', '2 - 4 - 0t', '1 - 3', '3', 'sharp , stewart & co', '1881', '1909 - 1926'], ['2', '4 - 6 - 0t', '4 - 9', '6', 'neilson & co', '1893', '1931 - 1937'], ['3', '4 - 4 - 4t', '10 - 11', '2', 'neilson , reid & co', '1902', '1933'], ['4', '4 - 6 - 4t', '12 - 15', '4', 'nasmyth , wilson & co', '1904', '1953 - 1959'], ['5', '2 - 6 - 4t', '16 - 20', '5', 'nasmyth , wilson & co', '1907', '1940 - 1950'], ['5a', '2 - 6 - 4t', '21 , 2a , 3a', '3', 'nasmyth , wilson & co', '1912', '1959']] |
list of new jersey transit stations | https://en.wikipedia.org/wiki/List_of_New_Jersey_Transit_stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1051326-3.html.csv | superlative | the fairmont avenue station was the earliest station to be closed . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'closed'], 'result': '1983', 'ind': 0, 'tostr': 'min { all_rows ; closed }', 'tointer': 'the minimum closed record of all rows is 1983 .'}, '1983'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; closed } ; 1983 }', 'tointer': 'the minimum closed record of all rows is 1983 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'closed'], 'result': None, 'ind': 2, 'tostr': 'argmin { all_rows ; closed }'}, 'station'], 'result': 'fairmount avenue', 'ind': 3, 'tostr': 'hop { argmin { all_rows ; closed } ; station }'}, 'fairmount avenue'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmin { all_rows ; closed } ; station } ; fairmount avenue }', 'tointer': 'the station record of the row with superlative closed record is fairmount avenue .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { min { all_rows ; closed } ; 1983 } ; eq { hop { argmin { all_rows ; closed } ; station } ; fairmount avenue } } = true', 'tointer': 'the minimum closed record of all rows is 1983 . the station record of the row with superlative closed record is fairmount avenue .'} | and { eq { min { all_rows ; closed } ; 1983 } ; eq { hop { argmin { all_rows ; closed } ; station } ; fairmount avenue } } = true | the minimum closed record of all rows is 1983 . the station record of the row with superlative closed record is fairmount avenue . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'min_0': 0, 'all_rows_7': 7, 'closed_8': 8, '1983_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmin_2': 2, 'all_rows_10': 10, 'closed_11': 11, 'station_12': 12, 'fairmount avenue_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'min_0': 'min', 'all_rows_7': 'all_rows', 'closed_8': 'closed', '1983_9': '1983', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmin_2': 'argmin', 'all_rows_10': 'all_rows', 'closed_11': 'closed', 'station_12': 'station', 'fairmount avenue_13': 'fairmount avenue'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'min_0': [1], 'all_rows_7': [0], 'closed_8': [0], '1983_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmin_2': [3], 'all_rows_10': [2], 'closed_11': [2], 'station_12': [3], 'fairmount avenue_13': [4]} | ['station', 'municipality', 'county', 'former railroad', 'closed'] | [['ampere', 'east orange', 'essex , nj', 'lackawanna', '1991'], ['arlington', 'kearney', 'hudson , nj', 'erie', '2002'], ['benson street', 'glen ridge', 'essex , nj', 'erie', '2002'], ['fairmount avenue', 'hackensack', 'bergen , nj', 'erie', '1983'], ['finderne', 'finderne', 'somerset , nj', 'jersey central', '2006'], ['great notch', 'great notch', 'passaic , nj', 'erie', '2010'], ['grove street', 'east orange', 'essex , nj', 'lackawanna', '1991'], ['harmon cove', 'secaucus', 'hudson , nj', 'erie', '2003'], ['harrison', 'harrison', 'hudson , nj', 'lackawanna', '1984'], ['north newark', 'newark', 'essex , nj', 'lackawanna', '1984'], ['north rahway', 'rahway', 'fairfield , nj', 'pennsylvania', '1993'], ['roseville avenue', 'newark', 'essex , nj', 'lackawanna', '1984'], ['rowe street', 'bloomfield township', 'essex , nj', 'erie', '2002']] |
ireland in the eurovision song contest 1998 | https://en.wikipedia.org/wiki/Ireland_in_the_Eurovision_Song_Contest_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15696018-1.html.csv | majority | the majority of the songs drawn had more than 50 points . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '50', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'points', '50'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than 50 .', 'tostr': 'most_greater { all_rows ; points ; 50 } = true'} | most_greater { all_rows ; points ; 50 } = true | for the points records of all rows , most of them are greater than 50 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '50_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '50_4': '50'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '50_4': [0]} | ['draw', 'song', 'performer', 'points', 'rank'] | [['1', 'is always over now', 'dawn martin', '95', '1st'], ['2', 'shine on', 'partners in crime', '63', '5th'], ['3', 'cold shoulder', 'ray doherty', '39', '8th'], ['4', 'seol ( sail )', 'the vard sisters', '92', '2nd'], ['5', 'save this dance for me', 'family', '57', '6th'], ['6', 'ina measc ( among them )', 'sean monagahan', '43', '7th'], ['7', 'make the change', 'the carter twins', '77', '4th'], ['8', 'overload', 'jo collins', '84', '3rd']] |
mahmoud shelbaieh | https://en.wikipedia.org/wiki/Mahmoud_Shelbaieh | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10935209-1.html.csv | count | for competitions that mahmoud shelbaieh participated in , when the venue was amman , there were six times that he won . | {'scope': 'subset', 'criterion': 'equal', 'value': 'win', 'result': '6', 'col': '4', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'amman'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'amman'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; amman }', 'tointer': 'select the rows whose venue record fuzzily matches to amman .'}, 'result', 'win'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to amman . among these rows , select the rows whose result record fuzzily matches to win .', 'tostr': 'filter_eq { filter_eq { all_rows ; venue ; amman } ; result ; win }'}], 'result': '6', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; venue ; amman } ; result ; win } }', 'tointer': 'select the rows whose venue record fuzzily matches to amman . among these rows , select the rows whose result record fuzzily matches to win . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; venue ; amman } ; result ; win } } ; 6 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to amman . among these rows , select the rows whose result record fuzzily matches to win . the number of such rows is 6 .'} | eq { count { filter_eq { filter_eq { all_rows ; venue ; amman } ; result ; win } } ; 6 } = true | select the rows whose venue record fuzzily matches to amman . among these rows , select the rows whose result record fuzzily matches to win . the number of such rows is 6 . | 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, 'venue_6': 6, 'amman_7': 7, 'result_8': 8, 'win_9': 9, '6_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', 'venue_6': 'venue', 'amman_7': 'amman', 'result_8': 'result', 'win_9': 'win', '6_10': '6'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'venue_6': [0], 'amman_7': [0], 'result_8': [1], 'win_9': [1], '6_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['april 25 , 2001', 'tashkent', '2 - 0', 'win', '2002 fifa world cup qualification'], ['february 9 , 2002', "ta ' qali", '2 - 1', 'loss', 'friendly'], ['september 1 , 2002', 'damascus', '1 - 0', 'win', '2002 west asian football federation championship'], ['december 7 , 2002', 'manama', '3 - 0', 'win', 'friendly ( 2 goals )'], ['december 23 , 2002', 'kuwait city', '2 - 1', 'win', 'friendly'], ['september 26 , 2003', 'amman', '3 - 2', 'win', '2004 afc asian cup qualification'], ['november 18 , 2003', 'amman', '3 - 0', 'win', '2004 afc asian cup qualification'], ['february 18 , 2004', 'amman', '5 - 0', 'win', '2006 fifa world cup qualification'], ['may 30 , 2004', 'annaba', '1 - 1', 'draw', 'friendly'], ['june 21 , 2004', 'tehran', '2 - 0', 'win', '2004 west asian football federation championship'], ['july 31 , 2004', 'chongqing', '1 - 1 aet ( 1:1 , 1:1 ) 4:3 pso', 'loss', '2004 afc asian cup'], ['august 21 , 2004', 'amman', '2 - 2', 'draw', 'friendly ( 2 goals )'], ['october 8 , 2004', 'bangkok', '3 - 2', 'win', 'friendly'], ['october 20 , 2004', 'tripoli', '3 - 0', 'win', 'friendly'], ['february 22 , 2006', 'amman', '3 - 0', 'win', '2007 afc asian cup qualification'], ['october 28 , 2007', 'amman', '2 - 0', 'win', '2010 fifa world cup qualification'], ['january 24 , 2008', 'dubai', '1 - 1', 'draw', 'friendly'], ['january 28 , 2008', 'amman', '4 - 1', 'win', 'friendly'], ['december 30 , 2009', 'jinan', '2 - 2', 'draw', 'friendly ( 2 goals )']] |
1978 kansas city chiefs season | https://en.wikipedia.org/wiki/1978_Kansas_City_Chiefs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12536374-2.html.csv | aggregation | the average attendance at kansas city chiefs games in the 1978 season was 48469 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '48469', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '48469', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '48469'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 48469 } = true', 'tointer': 'the average of the attendance record of all rows is 48469 .'} | round_eq { avg { all_rows ; attendance } ; 48469 } = true | the average of the attendance record of all rows is 48469 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '48469_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '48469_5': '48469'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '48469_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 3 , 1978', 'cincinnati bengals', 'w 24 - 23', '41810'], ['2', 'september 10 , 1978', 'houston oilers', 'l 20 - 17', '40213'], ['3', 'september 17 , 1978', 'new york giants', 'l 26 - 10', '70546'], ['4', 'september 24 , 1978', 'denver broncos', 'l 23 - 17', '60593'], ['5', 'october 1 , 1978', 'buffalo bills', 'l 28 - 13', '47310'], ['6', 'october 8 , 1978', 'tampa bay buccaneers', 'l 30 - 13', '38201'], ['7', 'october 15 , 1978', 'oakland raiders', 'l 28 - 6', '50759'], ['8', 'october 22 , 1978', 'cleveland browns', 'w 17 - 3', '41157'], ['9', 'october 29 , 1978', 'pittsburgh steelers', 'l 27 - 24', '48185'], ['10', 'november 5 , 1978', 'oakland raiders', 'l 20 - 10', '75418'], ['11', 'november 12 , 1978', 'san diego chargers', 'l 29 - 23', '41395'], ['12', 'november 19 , 1978', 'seattle seahawks', 'l 13 - 10', '35252'], ['13', 'november 26 , 1978', 'san diego chargers', 'w 23 - 0', '26248'], ['14', 'december 3 , 1978', 'buffalo bills', 'w 14 - 10', '25781'], ['15', 'december 10 , 1978', 'denver broncos', 'l 24 - 3', '74149'], ['16', 'december 17 , 1978', 'seattle seahawks', 'l 23 - 19', '58490']] |
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/1-1341930-10.html.csv | ordinal | during the united states house of representatives elections , 1958 , the incumbent that was first elected second earliest was unopposed . | {'scope': 'all', 'row': '1', 'col': '4', 'order': '2', 'col_other': '6', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 2 }'}, 'candidates'], 'result': 'charles edward bennett ( d ) unopposed', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 2 } ; candidates }'}, 'charles edward bennett ( d ) unopposed'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; candidates } ; charles edward bennett ( d ) unopposed } = true', 'tointer': 'select the row whose first elected record of all rows is 2nd minimum . the candidates record of this row is charles edward bennett ( d ) unopposed .'} | eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; candidates } ; charles edward bennett ( d ) unopposed } = true | select the row whose first elected record of all rows is 2nd minimum . the candidates record of this row is charles edward bennett ( d ) unopposed . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '2_6': 6, 'candidates_7': 7, 'charles edward bennett (d) unopposed_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', 'first elected_5': 'first elected', '2_6': '2', 'candidates_7': 'candidates', 'charles edward bennett (d) unopposed_8': 'charles edward bennett ( d ) unopposed'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '2_6': [0], 'candidates_7': [1], 'charles edward bennett (d) unopposed_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['florida 2', 'charles edward bennett', 'democratic', '1948', 're - elected', 'charles edward bennett ( d ) unopposed'], ['florida 3', 'robert l f sikes', 'democratic', '1940', 're - elected', 'robert l f sikes ( d ) unopposed'], ['florida 4', 'dante fascell', 'democratic', '1954', 're - elected', 'dante fascell ( d ) unopposed'], ['florida 6', 'paul rogers', 'democratic', '1954', 're - elected', 'paul rogers ( d ) 71.5 % charles p ware ( r ) 28.5 %'], ['florida 7', 'james a haley', 'democratic', '1952', 're - elected', 'james a haley ( d ) unopposed']] |
marta domachowska | https://en.wikipedia.org/wiki/Marta_Domachowska | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15746889-4.html.csv | ordinal | marta domachowska 's 2nd to last tournament took place in the city of cincinnati . | {'row': '4', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date ; 2 }'}, 'tournament'], 'result': 'cincinnati , united states', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date ; 2 } ; tournament }'}, 'cincinnati , united states'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; date ; 2 } ; tournament } ; cincinnati , united states } = true', 'tointer': 'select the row whose date record of all rows is 2nd maximum . the tournament record of this row is cincinnati , united states .'} | eq { hop { nth_argmax { all_rows ; date ; 2 } ; tournament } ; cincinnati , united states } = true | select the row whose date record of all rows is 2nd maximum . the tournament record of this row is cincinnati , united states . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'tournament_7': 7, 'cincinnati , united states_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', 'date_5': 'date', '2_6': '2', 'tournament_7': 'tournament', 'cincinnati , united states_8': 'cincinnati , united states'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'tournament_7': [1], 'cincinnati , united states_8': [2]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponent in final', 'score in final'] | [['runner - up', 'january 31 , 2005', 'pattaya city , thailand', 'hard', 'silvija talaja', 'rosa maría andrés rodríguez andreea vanc', '6 - 3 , 6 - 1'], ['runner - up', 'may 21 , 2005', 'strasbourg , france', 'clay', 'marlene weingärtner', 'marion bartoli anna - lena grönefeld', '6 - 3 , 6 - 2'], ['winner', 'january 13 , 2006', 'canberra , australia', 'hard', 'roberta vinci', 'claire curran liga dekmeijere', '7 - 6 ( 5 ) , 6 - 3'], ['runner - up', 'july 23 , 2006', 'cincinnati , united states', 'hard', 'sania mirza', 'gisela dulko maria elena camerin', '6 - 4 , 3 - 6 , 6 - 2'], ['runner - up', 'september 14 , 2008', 'bali , indonesia', 'hard', 'nadia petrova', 'hsieh su - wei peng shuai', '6 - 7 ( 4 ) , 7 - 6 ( 3 ) ,']] |
2008 copa libertadores knockout stages | https://en.wikipedia.org/wiki/2008_Copa_Libertadores_knockout_stages | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16795394-3.html.csv | superlative | flamengo scored the most points in the 1st leg of the 2008 copa libertadores knockout stages . | {'scope': 'all', 'col_superlative': '4', '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', '1st leg'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 1st leg }'}, 'team 1'], 'result': 'flamengo', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; 1st leg } ; team 1 }'}, 'flamengo'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; 1st leg } ; team 1 } ; flamengo } = true', 'tointer': 'select the row whose 1st leg record of all rows is maximum . the team 1 record of this row is flamengo .'} | eq { hop { argmax { all_rows ; 1st leg } ; team 1 } ; flamengo } = true | select the row whose 1st leg record of all rows is maximum . the team 1 record of this row is flamengo . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, '1st leg_5': 5, 'team 1_6': 6, 'flamengo_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', '1st leg_5': '1st leg', 'team 1_6': 'team 1', 'flamengo_7': 'flamengo'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], '1st leg_5': [0], 'team 1_6': [1], 'flamengo_7': [2]} | ['team 1', 'points', 'team 2', '1st leg', '2nd leg'] | [['fluminense', '6 - 0', 'atlético nacional', '2 - 1', '1 - 0'], ['flamengo', '3 - 3 ( gd )', 'américa', '4 - 2', '0 - 3'], ['river plate', '1 - 4', 'san lorenzo', '1 - 2', '2 - 2'], ['atlas', '4 - 1', 'lanús', '1 - 0', '2 - 2'], ['cruzeiro', '0 - 6', 'boca juniors', '1 - 2', '1 - 2'], ['estudiantes', '3 - 3 ( gd )', 'ldu quito', '0 - 2', '2 - 1'], ['cúcuta deportivo', '0 - 6', 'santos', '0 - 2', '0 - 2']] |
list of pound puppies ( 2010 tv series ) episodes | https://en.wikipedia.org/wiki/List_of_Pound_Puppies_%282010_TV_series%29_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29087004-3.html.csv | count | according to the list of pound puppies ( 2010 tv series ) episodes , among the episodes aired in united states in july , 3 of them were directed by greg sullivan . | {'scope': 'subset', 'criterion': 'equal', 'value': 'greg sullivan', 'result': '3', 'col': '4', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'july'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'united states original airdate', 'july'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; united states original airdate ; july }', 'tointer': 'select the rows whose united states original airdate record fuzzily matches to july .'}, 'directed by', 'greg sullivan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose united states original airdate record fuzzily matches to july . among these rows , select the rows whose directed by record fuzzily matches to greg sullivan .', 'tostr': 'filter_eq { filter_eq { all_rows ; united states original airdate ; july } ; directed by ; greg sullivan }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; united states original airdate ; july } ; directed by ; greg sullivan } }', 'tointer': 'select the rows whose united states original airdate record fuzzily matches to july . among these rows , select the rows whose directed by record fuzzily matches to greg sullivan . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; united states original airdate ; july } ; directed by ; greg sullivan } } ; 3 } = true', 'tointer': 'select the rows whose united states original airdate record fuzzily matches to july . among these rows , select the rows whose directed by record fuzzily matches to greg sullivan . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; united states original airdate ; july } ; directed by ; greg sullivan } } ; 3 } = true | select the rows whose united states original airdate record fuzzily matches to july . among these rows , select the rows whose directed by record fuzzily matches to greg sullivan . 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, 'united states original airdate_6': 6, 'july_7': 7, 'directed by_8': 8, 'greg sullivan_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', 'united states original airdate_6': 'united states original airdate', 'july_7': 'july', 'directed by_8': 'directed by', 'greg sullivan_9': 'greg sullivan', '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], 'united states original airdate_6': [0], 'july_7': [0], 'directed by_8': [1], 'greg sullivan_9': [1], '3_10': [3]} | ['series', 'production code', 'title', 'directed by', 'written by', 'united states original airdate', 'canada original airdate'] | [['27', '201', 'zipper the zoomit dog', 'jos humphrey', 'mark drop', 'june 2 , 2012', 'september 7 , 2012'], ['28', '202', 'the fraud princess', 'greg sullivan', 'rachel lipman', 'june 9 , 2012', 'september 14 , 2012'], ['29', '203', 'the super secret pup club', 'jos humphrey', 'bart jennett', 'june 16 , 2012', 'september 21 , 2012'], ['30', '204', 'barlow', 'greg sullivan', 'alan hanson', 'june 23 , 2012', 'september 28 , 2012'], ['31', '205', "there 's something about camelia", 'jos humphrey', 'tony infante', 'june 30 , 2012', 'october 5 , 2012'], ['32', '206', 'good dog , mcleish !', 'greg sullivan', 'evan gore', 'july 7 , 2012', 'october 12 , 2012'], ['33', '208', 'the ruff ruff bunch', 'jos humphrey', 'rich fogel', 'july 14 , 2012', 'october 19 , 2012'], ['34', '209', 'salty', 'greg sullivan', 'merriwether williams', 'july 21 , 2012', 'october 26 , 2012'], ['35', '207', 'squawk', 'greg sullivan', 'chelsea meyer', 'july 28 , 2012', 'november 2 , 2012'], ['36', '212', 'the accidental pup star', 'jos humphrey', 'tony infante', 'august 25 , 2012', 'november 9 , 2012'], ['37', '210', 'no dogs allowed', 'jos humphrey', 'rich whitley', 'september 1 , 2012', 'november 16 , 2012'], ['38', '211', 'pound preemies', 'jos humphrey', 'eric trueheart', 'december 1 , 2012', 'september 18 , 2012']] |
1948 vfl season | https://en.wikipedia.org/wiki/1948_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809529-8.html.csv | ordinal | collingwood had the 2nd highest score of any away team in the 1948 vfl season . | {'row': '2', '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', 'away team score', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; away team score ; 2 }'}, 'home team'], 'result': 'collingwood', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; away team score ; 2 } ; home team }'}, 'collingwood'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; away team score ; 2 } ; home team } ; collingwood } = true', 'tointer': 'select the row whose away team score record of all rows is 2nd maximum . the home team record of this row is collingwood .'} | eq { hop { nth_argmax { all_rows ; away team score ; 2 } ; home team } ; collingwood } = true | select the row whose away team score record of all rows is 2nd maximum . the home team record of this row is collingwood . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'away team score_5': 5, '2_6': 6, 'home team_7': 7, 'collingwood_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', 'away team score_5': 'away team score', '2_6': '2', 'home team_7': 'home team', 'collingwood_8': 'collingwood'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'away team score_5': [0], '2_6': [0], 'home team_7': [1], 'collingwood_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '15.16 ( 106 )', 'south melbourne', '19.12 ( 126 )', 'kardinia park', '19500', '5 june 1948'], ['collingwood', '11.17 ( 83 )', 'melbourne', '11.10 ( 76 )', 'victoria park', '20000', '5 june 1948'], ['st kilda', '7.12 ( 54 )', 'hawthorn', '10.12 ( 72 )', 'junction oval', '7000', '5 june 1948'], ['north melbourne', '11.6 ( 72 )', 'footscray', '8.9 ( 57 )', 'arden street oval', '12000', '5 june 1948'], ['fitzroy', '12.8 ( 80 )', 'essendon', '9.10 ( 64 )', 'brunswick street oval', '25000', '5 june 1948'], ['richmond', '13.10 ( 88 )', 'carlton', '9.21 ( 75 )', 'punt road oval', '33000', '5 june 1948']] |
2008 - 09 guildford flames season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Guildford_Flames_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17120964-9.html.csv | ordinal | in the 2008-09 guildford flames season , the 2nd highest attendance was on the 15th . | {'row': '4', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': '15th', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}, '15th'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; 15th } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the date record of this row is 15th .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; 15th } = true | select the row whose attendance record of all rows is 2nd maximum . the date record of this row is 15th . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, '15th_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', '15th_8': '15th'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], '15th_8': [2]} | ['date', 'opponent', 'venue', 'result', 'attendance', 'competition', 'man of the match'] | [['1st', 'milton keynes lightning', 'home', 'won 5 - 4', '1336', 'league', 'terry miles'], ['8th', 'bracknell bees', 'away', 'won 4 - 3 ( ot )', 'n / a', 'league', 'ollie bronnimann'], ['14th', 'peterborough phantoms', 'away', 'won 4 - 2', '493', 'league', 'n / a'], ['15th', 'slough jets', 'home', 'lost 3 - 2', '1634', 'league', 'joe watkins'], ['19th', 'slough jets', 'home', 'drawn 1 - 1', '2057', 'cup semi - final ( 1st leg )', 'david savage'], ['21st', 'peterborough phantoms', 'home', 'won 5 - 3', '1551', 'league', 'ben austin'], ['22nd', 'sheffield scimitars', 'away', 'lost 5 - 4', '627', 'league', 'n / a'], ['25th', 'slough jets', 'away', 'won 4 - 2', '702', 'cup semi - final ( 2nd leg )', 'n / a'], ['28th', 'wightlink raiders', 'away', 'lost 3 - 2 ( so )', '582', 'league', 'stuart potts']] |
regionalliga süd | https://en.wikipedia.org/wiki/Regionalliga_S%C3%BCd | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12272590-2.html.csv | superlative | in the regionalliga sud , the season in the 90s with the most goals was 1994-1995 with 37 . | {'scope': 'subset', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': '199'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '199'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; season ; 199 }', 'tointer': 'select the rows whose season record fuzzily matches to 199 .'}, 'goals'], 'result': '37', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; season ; 199 } ; goals }', 'tointer': 'select the rows whose season record fuzzily matches to 199 . the maximum goals record of these rows is 37 .'}, '37'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; season ; 199 } ; goals } ; 37 } = true', 'tointer': 'select the rows whose season record fuzzily matches to 199 . the maximum goals record of these rows is 37 .'} | eq { max { filter_eq { all_rows ; season ; 199 } ; goals } ; 37 } = true | select the rows whose season record fuzzily matches to 199 . the maximum goals record of these rows is 37 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'season_5': 5, '199_6': 6, 'goals_7': 7, '37_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'season_5': 'season', '199_6': '199', 'goals_7': 'goals', '37_8': '37'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'season_5': [0], '199_6': [0], 'goals_7': [1], '37_8': [2]} | ['season', 'overall spectators', 'per game', 'best supported club', 'spectators / game', 'top goal scorer', 'goals'] | [['1994 - 95', '427576', '1397', 'stuttgarter kickers', '2759', 'jonathan akpoborie ( sk )', '37'], ['1995 - 96', '353617', '1156', 'stuttgarter kickers', '3181', 'dragan trkulja ( ulm )', '25'], ['1996 - 97', '779612', '2548', '1 . fc nuremberg', '15328', 'frank türr ( gf )', '25'], ['1997 - 98', '693500', '2375', 'kickers offenbach', '12906', 'dieter eckstein ( fca )', '21'], ['1998 - 99', '568494', '1858', 'kickers offenbach', '11500', 'marijo maric ( ssv )', '23'], ['1999 - 2000', '365281', '1194', 'sv darmstadt 98', '3667', 'oliver djappa ( ssv )', '36'], ['2000 - 01', '932249', '3047', 'karlsruher sc', '10050', 'marko barlecaj ( scp )', '18'], ['2001 - 02', '717193', '2344', 'kickers offenbach', '6911', 'saber ben neticha ( svw )', '18'], ['2002 - 03', '803856', '2350', 'jahn regensburg', '5105', 'francisco copado ( spvggu )', '24'], ['2003 - 04', '670371', '2191', '1 . fc saarbrücken', '6141', 'zvjezdan misimovic ( fcb ) josé guerrero ( fcb )', '21'], ['2004 - 05', '711904', '2326', 'kickers offenbach', '6669', 'patrick helmes ( sfs )', '21'], ['2005 - 06', '561058', '1834', 'tus koblenz', '4657', 'maximilian nicu ( svw ) christian okpala ( fca )', '16'], ['2006 - 07', '685182', '2239', 'hessen kassel', '4383', 'mirnes mesic ( tsg ) jonathan jäger ( 1 . fcs )', '17'], ['2007 - 08', '775651', '2535', 'sportfreunde siegen', '6095', 'thorsten bauer ( ksv )', '20'], ['2008 - 09', '424619', '1388', 'hessen kassel', '4282', 'thorsten bauer ( ksv )', '32'], ['2009 - 10', '367834', '1202', 'vfr aalen', '3258', 'mijo tunjic ( sk ) abedin krasniqi ( sg )', '19'], ['2010 - 11', '304647', '1269', 'hessen kassel', '5520', 'kai herdling ( tsg )', '19'], ['2011 - 12', '308062', '1007', 'stuttgarter kickers', '3561', 'karl lappe ( fci ii )', '18']] |
orlando magic all - time roster | https://en.wikipedia.org/wiki/Orlando_Magic_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15621965-2.html.csv | comparative | brandon bass played for the orlando magic after andre barrett did . | {'row_1': '3', 'row_2': '2', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'brandon bass'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to brandon bass .', 'tostr': 'filter_eq { all_rows ; player ; brandon bass }'}, 'years in orlando'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; brandon bass } ; years in orlando }', 'tointer': 'select the rows whose player record fuzzily matches to brandon bass . take the years in orlando record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'andre barrett'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to andre barrett .', 'tostr': 'filter_eq { all_rows ; player ; andre barrett }'}, 'years in orlando'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; andre barrett } ; years in orlando }', 'tointer': 'select the rows whose player record fuzzily matches to andre barrett . take the years in orlando record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; brandon bass } ; years in orlando } ; hop { filter_eq { all_rows ; player ; andre barrett } ; years in orlando } } = true', 'tointer': 'select the rows whose player record fuzzily matches to brandon bass . take the years in orlando record of this row . select the rows whose player record fuzzily matches to andre barrett . take the years in orlando record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; brandon bass } ; years in orlando } ; hop { filter_eq { all_rows ; player ; andre barrett } ; years in orlando } } = true | select the rows whose player record fuzzily matches to brandon bass . take the years in orlando record of this row . select the rows whose player record fuzzily matches to andre barrett . take the years in orlando 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, 'player_7': 7, 'brandon bass_8': 8, 'years in orlando_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'andre barrett_12': 12, 'years in orlando_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', 'player_7': 'player', 'brandon bass_8': 'brandon bass', 'years in orlando_9': 'years in orlando', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'andre barrett_12': 'andre barrett', 'years in orlando_13': 'years in orlando'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'brandon bass_8': [0], 'years in orlando_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'andre barrett_12': [1], 'years in orlando_13': [3]} | ['player', 'nationality', 'position', 'years in orlando', 'school / club team'] | [['matt barnes', 'united states', 'guard - forward', '2009 - 2010', 'ucla'], ['andre barrett', 'united states', 'guard', '2005', 'seton hall'], ['brandon bass', 'united states', 'forward', '2009 - 2011', 'louisiana state'], ['tony battie', 'united states', 'forward - center', '2004 - 2009', 'texas tech'], ['david benoit', 'united states', 'forward', '1998', 'alabama'], ['keith bogans', 'united states', 'guard', '2003 - 2004', 'kentucky'], ['keith bogans', 'united states', 'guard', '2006 - 2009', 'kentucky'], ['anthony bonner', 'united states', 'forward', '1995 - 1996', 'st louis'], ['anthony bowie', 'united states', 'guard', '1991 - 1996', 'oklahoma'], ['earl boykins', 'united states', 'guard', '1999', 'eastern michigan'], ['michael bradley', 'united states', 'forward', '2004 - 2005', 'villanova'], ['dee brown', 'united states', 'guard', '2000 - 2002', 'jacksonville'], ['jud buechler', 'united states', 'guard - forward', '2001 - 2002', 'arizona'], ['pat burke', 'ireland', 'center', '2002 - 2003', 'auburn']] |
1957 world wrestling championships | https://en.wikipedia.org/wiki/1957_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16852841-1.html.csv | count | two of the countries won exactly one gold medal . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; gold ; 1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; gold ; 1 } }', 'tointer': 'select the rows whose gold record is equal to 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; gold ; 1 } } ; 2 } = true', 'tointer': 'select the rows whose gold record is equal to 1 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; gold ; 1 } } ; 2 } = true | select the rows whose gold record is equal to 1 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'gold_5': 5, '1_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'gold_5': 'gold', '1_6': '1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'gold_5': [0], '1_6': [0], '2_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'turkey', '4', '2', '2', '8'], ['2', 'soviet union', '2', '3', '1', '6'], ['3', 'iran', '1', '1', '0', '2'], ['4', 'bulgaria', '1', '0', '2', '3'], ['5', 'finland', '0', '1', '0', '1'], ['5', 'west germany', '0', '1', '0', '1'], ['7', 'japan', '0', '0', '2', '2'], ['8', 'italy', '0', '0', '1', '1'], ['total', 'total', '8', '8', '8', '24']] |
mike skinner ( racing driver ) | https://en.wikipedia.org/wiki/Mike_Skinner_%28racing_driver%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1640715-2.html.csv | superlative | mike skinner had the most starts in his career in 2001 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'starts'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; starts }'}, 'year'], 'result': '2001', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; starts } ; year }'}, '2001'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; starts } ; year } ; 2001 } = true', 'tointer': 'select the row whose starts record of all rows is maximum . the year record of this row is 2001 .'} | eq { hop { argmax { all_rows ; starts } ; year } ; 2001 } = true | select the row whose starts record of all rows is maximum . the year record of this row is 2001 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'starts_5': 5, 'year_6': 6, '2001_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'starts_5': 'starts', 'year_6': 'year', '2001_7': '2001'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'starts_5': [0], 'year_6': [1], '2001_7': [2]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1987', '1', '0', '0', '0', '0', '35.0', '27.0', '470', '66th', '0'], ['1992', '1', '0', '0', '0', '0', '12.0', '28.0', '5800', '119th', '91 barry owen racing'], ['1994', '5', '0', '0', '0', '1', '11.4', '28.0', '18750', '57th', '88 gene petty motorsports'], ['1999', '13', '1', '1', '3', '0', '23.7', '24.5', '138405', '44th', '19 team yellow racing'], ['2000', '8', '0', '1', '2', '1', '18.0', '20.5', '117240', '52nd', '19 team yellow racing 15 andy petree racing'], ['2001', '14', '0', '6', '9', '1', '7.3', '9.4', '359798', '27th', '21 richard childress racing'], ['2003', '1', '0', '0', '1', '0', '9.0', '7.0', '15892', '106th', '7 evans motorsports'], ['2006', '9', '0', '0', '1', '0', '18.0', '22.0', '170795', '46th', '12 fitzbradshaw racing']] |
2008 skycity triple crown | https://en.wikipedia.org/wiki/2008_Skycity_Triple_Crown | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18282916-2.html.csv | majority | in the 2008 skycity triple crown , for the positions above 2 , all of them had over 1000 points . | {'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '1000', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '2'}} | {'func': 'all_greater', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'position', '2'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; position ; 2 }', 'tointer': 'select the rows whose position record is less than 2 .'}, 'points', '1000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose position record is less than 2 . for the points records of these rows , all of them are greater than 1000 .', 'tostr': 'all_greater { filter_less { all_rows ; position ; 2 } ; points ; 1000 } = true'} | all_greater { filter_less { all_rows ; position ; 2 } ; points ; 1000 } = true | select the rows whose position record is less than 2 . for the points records of these rows , all of them are greater than 1000 . | 2 | 2 | {'all_greater_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'position_4': 4, '2_5': 5, 'points_6': 6, '1000_7': 7} | {'all_greater_1': 'all_greater', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'position_4': 'position', '2_5': '2', 'points_6': 'points', '1000_7': '1000'} | {'all_greater_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'position_4': [0], '2_5': [0], 'points_6': [1], '1000_7': [1]} | ['position', 'number', 'name', 'team', 'points'] | [['1', '5', 'mark winterbottom', 'ford performance racing', '1402'], ['2', '1', 'garth tander', 'holden racing team', '1344'], ['3', '88', 'jamie whincup', 'team vodafone', '1276'], ['4', '15', 'rick kelly', 'hsv dealer team', '1208'], ['5', '6', 'steven richards', 'ford performance racing', '1123']] |
merom ( microprocessor ) | https://en.wikipedia.org/wiki/Merom_%28microprocessor%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24099916-1.html.csv | unique | the merom microprocessor used on the t5xxx and t7xxx models , was the only one that used all 3 sockets ( m , p and bga479 ) . | {'scope': 'all', 'row': '4', 'col': '6', 'col_other': '3', 'criterion': 'equal', 'value': 'socket m socket p bga479', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'socket', 'socket m socket p bga479'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose socket record fuzzily matches to socket m socket p bga479 .', 'tostr': 'filter_eq { all_rows ; socket ; socket m socket p bga479 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; socket ; socket m socket p bga479 } }', 'tointer': 'select the rows whose socket record fuzzily matches to socket m socket p bga479 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'socket', 'socket m socket p bga479'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose socket record fuzzily matches to socket m socket p bga479 .', 'tostr': 'filter_eq { all_rows ; socket ; socket m socket p bga479 }'}, 'model ( list )'], 'result': 't5xxx t7xxx', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; socket ; socket m socket p bga479 } ; model ( list ) }'}, 't5xxx t7xxx'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; socket ; socket m socket p bga479 } ; model ( list ) } ; t5xxx t7xxx }', 'tointer': 'the model ( list ) record of this unqiue row is t5xxx t7xxx .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; socket ; socket m socket p bga479 } } ; eq { hop { filter_eq { all_rows ; socket ; socket m socket p bga479 } ; model ( list ) } ; t5xxx t7xxx } } = true', 'tointer': 'select the rows whose socket record fuzzily matches to socket m socket p bga479 . there is only one such row in the table . the model ( list ) record of this unqiue row is t5xxx t7xxx .'} | and { only { filter_eq { all_rows ; socket ; socket m socket p bga479 } } ; eq { hop { filter_eq { all_rows ; socket ; socket m socket p bga479 } ; model ( list ) } ; t5xxx t7xxx } } = true | select the rows whose socket record fuzzily matches to socket m socket p bga479 . there is only one such row in the table . the model ( list ) record of this unqiue row is t5xxx t7xxx . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'socket_7': 7, 'socket m socket p bga479_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'model (list)_9': 9, 't5xxx t7xxx_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'socket_7': 'socket', 'socket m socket p bga479_8': 'socket m socket p bga479', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'model (list)_9': 'model ( list )', 't5xxx t7xxx_10': 't5xxx t7xxx'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'socket_7': [0], 'socket m socket p bga479_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'model (list)_9': [2], 't5xxx t7xxx_10': [3]} | ['processor', 'brand name', 'model ( list )', 'cores', 'l2 cache', 'socket', 'tdp'] | [['merom - l', 'mobile core 2 solo', 'u2xxx', '1', '2 mib', 'bga479', '5.5 w'], ['merom - 2 m', 'mobile core 2 duo', 'u7xxx', '2', '2 mib', 'bga479', '10 w'], ['merom', 'mobile core 2 duo', 'l7xxx', '2', '4 mib', 'bga479', '17 w'], ['merom merom - 2 m', 'mobile core 2 duo', 't5xxx t7xxx', '2', '2 - 4 mib', 'socket m socket p bga479', '35 w'], ['merom', 'mobile core 2 extreme', 'x7xxx', '2', '4 mib', 'socket p', '44 w'], ['merom', 'celeron m', '5x0', '1', '512 kib', 'socket m socket p', '30 w'], ['merom - l', 'celeron m', '5x0', '1', '512 kib', 'socket m socket p', '27 w'], ['merom - 2 m', 'celeron m', '5x5', '1', '1024 kib', 'socket p', '31 w'], ['merom - l', 'celeron m', '5x3', '1', '512 - 1024 kib', 'bga479', '5.5 - 10 w'], ['merom - 2 m', 'celeron dual - core', 't1xxx', '2', '512 - 1024 kib', 'socket p', '35 w']] |
nfl starting quarterback playoff records | https://en.wikipedia.org/wiki/NFL_starting_quarterback_playoff_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17788889-4.html.csv | unique | kerry collins was the only nfl starting quarterback with the giants . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'giants', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'teams', 'giants'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose teams record fuzzily matches to giants .', 'tostr': 'filter_eq { all_rows ; teams ; giants }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; teams ; giants } }', 'tointer': 'select the rows whose teams record fuzzily matches to giants . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'teams', 'giants'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose teams record fuzzily matches to giants .', 'tostr': 'filter_eq { all_rows ; teams ; giants }'}, 'quarterback'], 'result': 'kerry collins', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; teams ; giants } ; quarterback }'}, 'kerry collins'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; teams ; giants } ; quarterback } ; kerry collins }', 'tointer': 'the quarterback record of this unqiue row is kerry collins .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; teams ; giants } } ; eq { hop { filter_eq { all_rows ; teams ; giants } ; quarterback } ; kerry collins } } = true', 'tointer': 'select the rows whose teams record fuzzily matches to giants . there is only one such row in the table . the quarterback record of this unqiue row is kerry collins .'} | and { only { filter_eq { all_rows ; teams ; giants } } ; eq { hop { filter_eq { all_rows ; teams ; giants } ; quarterback } ; kerry collins } } = true | select the rows whose teams record fuzzily matches to giants . there is only one such row in the table . the quarterback record of this unqiue row is kerry collins . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'teams_7': 7, 'giants_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'quarterback_9': 9, 'kerry collins_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'teams_7': 'teams', 'giants_8': 'giants', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'quarterback_9': 'quarterback', 'kerry collins_10': 'kerry collins'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'teams_7': [0], 'giants_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'quarterback_9': [2], 'kerry collins_10': [3]} | ['quarterback', 'games', 'teams', 'wins', 'losses', 'percent'] | [['brad johnson', '7', 'vikings', '0', '1', '571'], ['brad johnson', '7', 'redskins', '1', '1', '571'], ['brad johnson', '7', 'buccaneers', '3', '1', '571'], ['kerry collins', '7', 'panthers', '1', '1', '429'], ['kerry collins', '7', 'giants', '2', '2', '429'], ['kerry collins', '7', 'titans', '0', '1', '429'], ['dave krieg', '9', 'seahawks', '3', '4', '333'], ['dave krieg', '9', 'chiefs', '0', '1', '333'], ['dave krieg', '9', 'lions', '0', '1', '333'], ['jeff garcia', '6', '49ers', '1', '2', '333'], ['jeff garcia', '6', 'eagles', '1', '1', '333'], ['jeff garcia', '6', 'buccaneers', '0', '1', '333']] |
pedro rodríguez ( racing driver ) | https://en.wikipedia.org/wiki/Pedro_Rodr%C3%ADguez_%28racing_driver%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1156744-1.html.csv | count | pedro rodriguez drove for north american racing team a total of three times . | {'scope': 'all', 'criterion': 'equal', 'value': 'north american racing team', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'entrant', 'north american racing team'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose entrant record fuzzily matches to north american racing team .', 'tostr': 'filter_eq { all_rows ; entrant ; north american racing team }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; entrant ; north american racing team } }', 'tointer': 'select the rows whose entrant record fuzzily matches to north american racing team . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; entrant ; north american racing team } } ; 3 } = true', 'tointer': 'select the rows whose entrant record fuzzily matches to north american racing team . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; entrant ; north american racing team } } ; 3 } = true | select the rows whose entrant record fuzzily matches to north american racing team . 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, 'entrant_5': 5, 'north american racing team_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', 'entrant_5': 'entrant', 'north american racing team_6': 'north american racing team', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'entrant_5': [0], 'north american racing team_6': [0], '3_7': [2]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1963', 'team lotus', 'lotus 25', 'climax v8', '0'], ['1964', 'north american racing team', 'ferrari 156 aero', 'ferrari v6', '1'], ['1965', 'north american racing team', 'ferrari 1512', 'ferrari v12', '2'], ['1966', 'team lotus', 'lotus 33', 'climax v8', '0'], ['1966', 'team lotus', 'lotus f2 44', 'cosworth straight - 4', '0'], ['1966', 'team lotus', 'lotus 33', 'brm v8', '0'], ['1967', 'cooper car company', 'cooper t81', 'maserati v12', '15'], ['1968', 'owen racing organisation', 'brm p126', 'brm v12', '18'], ['1968', 'owen racing organisation', 'brm p133', 'brm v12', '18'], ['1968', 'owen racing organisation', 'brm p138', 'brm v12', '18'], ['1969', 'reg parnell racing', 'brm p126', 'brm v12', '3'], ['1969', 'scuderia ferrari', 'ferrari 312', 'ferrari v12', '3'], ['1969', 'north american racing team', 'ferrari 312', 'ferrari v12', '3'], ['1970', 'yardley team brm', 'brm p153', 'brm v12', '23'], ['1971', 'yardley team brm', 'brm p160', 'brm v12', '9']] |
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 | aggregation | carlos pace scored a total of 97 championship points in his formula one racing career . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '97', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '97', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '97'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 97 } = true', 'tointer': 'the sum of the points record of all rows is 97 .'} | round_eq { sum { all_rows ; points } ; 97 } = true | the sum of the points record of all rows is 97 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '97_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '97_5': '97'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '97_5': [1]} | ['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']] |
1936 vfl season | https://en.wikipedia.org/wiki/1936_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790804-4.html.csv | majority | all games of the 1936 vfl season were played on the 23rd of may . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '23 may 1936', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '23 may 1936'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 23 may 1936 .', 'tostr': 'all_eq { all_rows ; date ; 23 may 1936 } = true'} | all_eq { all_rows ; date ; 23 may 1936 } = true | for the date records of all rows , all of them fuzzily match to 23 may 1936 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '23 may 1936_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '23 may 1936_4': '23 may 1936'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '23 may 1936_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '7.18 ( 60 )', 'south melbourne', '18.21 ( 129 )', 'arden street oval', '14000', '23 may 1936'], ['collingwood', '20.17 ( 137 )', 'essendon', '13.10 ( 88 )', 'victoria park', '11000', '23 may 1936'], ['carlton', '16.19 ( 115 )', 'richmond', '18.17 ( 125 )', 'princes park', '43000', '23 may 1936'], ['melbourne', '16.20 ( 116 )', 'hawthorn', '11.11 ( 77 )', 'mcg', '10152', '23 may 1936'], ['st kilda', '19.11 ( 125 )', 'geelong', '12.10 ( 82 )', 'junction oval', '22500', '23 may 1936'], ['footscray', '13.11 ( 89 )', 'fitzroy', '10.14 ( 74 )', 'western oval', '18000', '23 may 1936']] |
1974 minnesota vikings season | https://en.wikipedia.org/wiki/1974_Minnesota_Vikings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10361453-2.html.csv | majority | the minnesota vikings had a positive record by winning the majority of its games in the 1974 season . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; result ; win } = true'} | most_eq { all_rows ; result ; win } = true | for the result records of all rows , most of them fuzzily match to win . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'win_4': [0]} | ['game', 'date', 'opponent', 'result', 'vikings points', 'opponents', 'record', 'attendance'] | [['1', 'sept 15', 'green bay packers', 'win', '32', '17', '1 - 0', '56267'], ['2', 'sept 22', 'detroit lions', 'win', '7', '6', '2 - 0', '49703'], ['3', 'sept 29', 'chicago bears', 'win', '11', '7', '3 - 0', '46217'], ['4', 'oct 6', 'dallas cowboys', 'win', '23', '21', '4 - 0', '57847'], ['5', 'oct 13', 'houston oilers', 'win', '51', '10', '5 - 0', '48006'], ['6', 'oct 20', 'detroit lions', 'loss', '16', '20', '5 - 1', '47807'], ['7', 'oct 27', 'new england patriots', 'loss', '14', '17', '5 - 2', '48177'], ['8', 'nov 3', 'chicago bears', 'win', '17', '0', '6 - 2', '33343'], ['9', 'nov 11', 'st louis cardinals', 'win', '28', '24', '7 - 2', '50183'], ['10', 'nov 17', 'green bay packers', 'loss', '7', '19', '7 - 3', '47924'], ['11', 'nov 24', 'los angeles rams', 'loss', '17', '20', '7 - 4', '90266'], ['12', 'dec 1', 'new orleans saints', 'win', '29', '9', '8 - 4', '44202'], ['13', 'dec 7', 'atlanta falcons', 'win', '23', '10', '9 - 4', '47105']] |
1983 senior pga tour | https://en.wikipedia.org/wiki/1983_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622862-1.html.csv | aggregation | the average purse of the tournaments in the 1983 senior pga tour is 163250 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '163250', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'purse'], 'result': '163250', 'ind': 0, 'tostr': 'avg { all_rows ; purse }'}, '163250'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; purse } ; 163250 } = true', 'tointer': 'the average of the purse record of all rows is 163250 .'} | round_eq { avg { all_rows ; purse } ; 163250 } = true | the average of the purse record of all rows is 163250 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'purse_4': 4, '163250_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'purse_4': 'purse', '163250_5': '163250'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'purse_4': [0], '163250_5': [1]} | ['date', 'tournament', 'location', 'purse', 'winner', 'score', '1st prize'] | [['mar 20', 'greater daytona senior classic', 'florida', '150000', 'gene littler ( 1 )', '203 ( - 13 )', '25000'], ['may 22', 'hall of fame tournament', 'north carolina', '150000', 'rod funseth ( 1 )', '198 ( - 18 )', '25000'], ['jun 5', 'gatlin brothers seniors golf classic', 'nevada', '200000', 'don january ( 6 )', '208 ( - 8 )', '33500'], ['jun 12', 'senior tournament players championship', 'ohio', '250000', 'miller barber ( 7 )', '278 ( - 10 )', '40000'], ['jun 26', 'peter jackson champions', 'canada', '200000', 'don january ( 7 )', '274 ( - 10 )', '33250'], ['jul 3', 'marlboro classic', 'massachusetts', '150000', 'don january ( 8 )', '273 ( - 11 )', '25000'], ['jul 10', "greater syracuse senior 's pro classic", 'new york', '150000', 'gene littler ( 2 )', '275 ( - 9 )', '25000'], ['jul 17', 'merrill lynch / golf digest commemorative pro - am', 'rhode island', '150000', 'miller barber ( 8 )', '200 ( - 16 )', '25000'], ['jul 25', 'us senior open', 'minnesota', '175000', 'billy casper ( 3 )', '288 ( 4 )', '30566'], ['aug 21', 'denver post champions of golf', 'colorado', '150000', 'don january ( 9 )', '271 ( - 17 )', '25000'], ['sep 4', 'citizens union senior golf classic', 'kentucky', '150000', 'don january ( 10 )', '269 ( - 19 )', '25000'], ['sep 25', 'world seniors invitational', 'north carolina', '152000', 'doug sanders ( 1 )', '283 ( - 5 )', '25000'], ['oct 2', 'united virginia bank seniors', 'virginia', '150000', 'miller barber ( 9 )', '211 ( - 5 )', '25000'], ['oct 16', 'suntree classic', 'florida', '135000', 'don january ( 11 )', '274 ( - 14 )', '22500'], ['oct 23', 'hilton head seniors international', 'south carolina', '150000', 'miller barber ( 10 )', '281 ( - 7 )', '25000'], ['dec 4', 'boca grove seniors classic', 'florida', '150000', 'arnold palmer ( 5 )', '271 ( - 17 )', '25000']] |
.38 special | https://en.wikipedia.org/wiki/.38_Special | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-173103-1.html.csv | aggregation | the average max pressure of .38 special guns measured in psi is 26611 psi . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '26611', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'max pressure'], 'result': '26611', 'ind': 0, 'tostr': 'avg { all_rows ; max pressure }'}, '26611'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; max pressure } ; 26611 } = true', 'tointer': 'the average of the max pressure record of all rows is 26611 .'} | round_eq { avg { all_rows ; max pressure } ; 26611 } = true | the average of the max pressure record of all rows is 26611 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'max pressure_4': 4, '26611_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'max pressure_4': 'max pressure', '26611_5': '26611'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'max pressure_4': [0], '26611_5': [1]} | ['cartridge', 'bullet weight', 'muzzle velocity', 'muzzle energy', 'max pressure'] | [['.38 short colt', 'gr ( g )', 'ft / s ( m / s )', '181ft lbf ( 245 j )', '7500 cup'], ['.38 long colt', 'gr ( g )', 'ft / s ( m / s )', '201ft lbf ( 273 j )', '12000 cup'], ['.38 s & w', 'gr ( g )', 'ft / s ( m / s )', '206ft lbf ( 279 j )', '14500 psi'], ['.38 s & w special', 'gr ( g )', 'ft / s ( m / s )', '310ft lbf ( 420 j )', '17000 psi'], ['.38 special + p', 'gr ( g )', 'ft / s ( m / s )', '351ft lbf ( 476 j )', '20000 psi'], ['.38 special + p +', 'gr ( g )', 'ft / s ( m / s )', '295ft lbf ( 400 j )', '> 20000 psi'], ['.380 acp', 'gr ( g )', 'ft / s ( m / s )', '178ft lbf ( 241 j )', '21500 psi'], ['9x19 mm parabellum', 'gr ( g )', 'ft / s ( m / s )', '420ft lbf ( 570 j )', '39200 psi'], ['9x19 mm parabellum', 'gr ( g )', 'ft / s ( m / s )', '383ft lbf ( 520 j )', '39200 psi'], ['9x18 mm makarov', 'gr ( g )', 'ft / s ( m / s )', '231ft lbf ( 313 j )', '23206 psi'], ['.38 super', 'grains ( g )', 'ft / s ( m / s )', '468ft lbf ( 634 j )', '36500 psi'], ['.357 magnum', 'grains ( g )', 'ft / s ( m / s )', '639ft lbf ( 866 j )', '35000 psi']] |
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