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jack mcgrath | https://en.wikipedia.org/wiki/Jack_McGrath | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236208-1.html.csv | majority | the majority of the time jake started in the # 3 position . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '3', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'start', '3'], 'result': True, 'ind': 0, 'tointer': 'for the start records of all rows , most of them are equal to 3 .', 'tostr': 'most_eq { all_rows ; start ; 3 } = true'} | most_eq { all_rows ; start ; 3 } = true | for the start records of all rows , most of them are equal to 3 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'start_3': 3, '3_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'start_3': 'start', '3_4': '3'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'start_3': [0], '3_4': [0]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1948', '13', '124.580', '16', '21', '70'], ['1949', '3', '128.884', '8', '26', '39'], ['1950', '6', '131.868', '10', '14', '131'], ['1951', '3', '134.303', '8', '3', '200'], ['1952', '3', '136.664', '5', '11', '200'], ['1953', '3', '136.602', '13', '5', '200'], ['1954', '1', '141.033', '1', '3', '200'], ['1955', '3'... |
melissa reid | https://en.wikipedia.org/wiki/Melissa_Reid | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29506171-2.html.csv | unique | the only year that melissa reid had 0 wins and played in more than 15 tournaments is 2008 . | {'scope': 'subset', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'greater_than', 'value': '15', 'subset': {'col': '4', 'criterion': 'equal', 'value': '0'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; wins ; 0 }', 'tointer': 'select the rows whose wins record is equal to 0 .'}, 'tournaments played', '15'], 'result': ... | and { only { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } } ; eq { hop { filter_greater { filter_eq { all_rows ; wins ; 0 } ; tournaments played ; 15 } ; year } ; 2008 } } = true | select the rows whose wins record is equal to 0 . among these rows , select the rows whose tournaments played record is greater than 15 . there is only one such row in the table . the year record of this unqiue row is 2008 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'wins_8': 8, '0_9': 9, 'tournaments played_10': 10, '15_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'year_12': 12, '2008_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'wins_8': 'wins', '0_9': '0', 'tournaments played_10': 'tournaments played', '15_11': '15', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'year_12': 'year', '2008_13': '2008'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'wins_8': [0], '0_9': [0], 'tournaments played_10': [1], '15_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'year_12': [3], '2008_13': [4]} | ['year', 'tournaments played', 'cuts made', 'wins', '2nd', '3rd', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank', 'rolex ranking'] | [['2006', '1', '1', '0', '0', '0', '0', 't12', 'n / a', 'n / a', '72.33', 'n / a', '658'], ['2007', '3', '3', '0', '0', '0', '1', '9', '4050 1', 'n / a', '73.18', 'n / a', '307'], ['2008', '16', '12', '0', '3', '1', '7', '2', '136606', '12', '71.96', '26', '169'], ['2009', '14', '13', '0', '1', '2', '8', '2', '168749',... |
1928 vfl season | https://en.wikipedia.org/wiki/1928_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10766119-9.html.csv | majority | all games of the 1928 vfl season were played on the 9th of june . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '9 june 1928', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '9 june 1928'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 9 june 1928 .', 'tostr': 'all_eq { all_rows ; date ; 9 june 1928 } = true'} | all_eq { all_rows ; date ; 9 june 1928 } = true | for the date records of all rows , all of them fuzzily match to 9 june 1928 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '9 june 1928_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '9 june 1928_4': '9 june 1928'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '9 june 1928_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '21.16 ( 142 )', 'south melbourne', '9.12 ( 66 )', 'punt road oval', '21000', '9 june 1928'], ['collingwood', '13.14 ( 92 )', 'melbourne', '11.14 ( 80 )', 'victoria park', '27000', '9 june 1928'], ['carlton', '9.7 ( 61 )', 'footscray', '8.14 ( 62 )', 'princes park', '25000', '9 june 1928'], ['st kilda', '... |
rowing at the 2008 summer olympics - women 's coxless pair | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_coxless_pair | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662697-3.html.csv | unique | canada is the only country that had a boat under water during the women 's coxless pair at the 2008 summer olympics . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'boat under weight', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', 'boat under weight'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to boat under weight .', 'tostr': 'filter_eq { all_rows ; time ; boat under weight }'}], 'result': True,... | and { only { filter_eq { all_rows ; time ; boat under weight } } ; eq { hop { filter_eq { all_rows ; time ; boat under weight } ; country } ; canada } } = true | select the rows whose time record fuzzily matches to boat under weight . there is only one such row in the table . the country record of this unqiue row is canada . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time_7': 7, 'boat under weight_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'canada_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time_7': 'time', 'boat under weight_8': 'boat under weight', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'canada_10': 'canada'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], 'boat under weight_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'canada_10': [3]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'yuliya bichyk , natallia helakh', 'belarus', '7:24.47', 'fa'], ['2', 'juliette haigh , nicola coles', 'new zealand', '7:31.45', 'r'], ['3', 'wu you , gao yulan', 'china', '7:32.50', 'r'], ['4', 'kim crow , sarah cook', 'australia', '7:44.04', 'r'], ['5', 'zoe hoskins , sabrina kolker', 'canada', 'boat under wei... |
wru division four west | https://en.wikipedia.org/wiki/WRU_Division_Four_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13758945-2.html.csv | superlative | the highest number of points against is for cwmgors rfc . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points against'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points against }'}, 'club'], 'result': 'cwmgors rfc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points against } ; club }'}, 'cwmgors rfc'], 're... | eq { hop { argmax { all_rows ; points against } ; club } ; cwmgors rfc } = true | select the row whose points against record of all rows is maximum . the club record of this row is cwmgors rfc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points against_5': 5, 'club_6': 6, 'cwmgors rfc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points against_5': 'points against', 'club_6': 'club', 'cwmgors rfc_7': 'cwmgors rfc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points against_5': [0], 'club_6': [1], 'cwmgors rfc_7': [2]} | ['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'], ['llandeilo rfc', '22', '1', '0', '917', '119', '136', '14', '19', '0', '105'], ['brynamman rfc', '22', '1', '2', '821', '210', '116', '27', '16', '2', '96'], ['tenby united rfc', '... |
ivana abramovi \ xc4 \ x87 | https://en.wikipedia.org/wiki/Ivana_Abramovi%C4%87 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14851245-3.html.csv | count | four of the tournaments that abramovic entered were in 2002 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2002', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2002'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 2002 .', 'tostr': 'filter_eq { all_rows ; date ; 2002 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq {... | eq { count { filter_eq { all_rows ; date ; 2002 } } ; 4 } = true | select the rows whose date record fuzzily matches to 2002 . 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, 'date_5': 5, '2002_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', 'date_5': 'date', '2002_6': '2002', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '2002_6': [0], '4_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', '15 - oct - 2001', 'makarska', 'clay', 'raffaella bindi', 'petra raclavska blanka kumbarova', '4 - 6 , 5 - 7'], ['winner', '03 - dec - 2001', 'bangkok', 'hard', 'kim jin - hee', 'mi - ra jeon manisha malhotra', '6 - 1 7 - 5'], ['runner - up', '08 - jan - 2002', 'tallahassee', 'hard', 'jacqueline trail'... |
international formula master | https://en.wikipedia.org/wiki/International_Formula_Master | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11292165-3.html.csv | unique | the only time the 3000 pro series took place was in 2005 . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '3000 pro series', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series name', '3000 pro series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series name record fuzzily matches to 3000 pro series .', 'tostr': 'filter_eq { all_rows ; series name ; 3000 pro series }'}], ... | and { only { filter_eq { all_rows ; series name ; 3000 pro series } } ; eq { hop { filter_eq { all_rows ; series name ; 3000 pro series } ; season } ; 2005 } } = true | select the rows whose series name record fuzzily matches to 3000 pro series . there is only one such row in the table . the season record of this unqiue row is 2005 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'series name_7': 7, '3000 pro series_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'season_9': 9, '2005_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'series name_7': 'series name', '3000 pro series_8': '3000 pro series', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'season_9': 'season', '2005_10': '2005'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'series name_7': [0], '3000 pro series_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'season_9': [2], '2005_10': [3]} | ['season', 'series name', 'champion', 'team champion', 'secondary class champion'] | [['2005', '3000 pro series', 'norbert siedler / max busnelli', 'draco junior team', 'iago rego rosende ( master junior formula )'], ['2006', 'f3000 international masters', 'jan charouz', 'charouz racing system', 'daniel campos - hull ( master junior formula )'], ['2007', 'international formula master', "jérôme d'ambros... |
1974 world ice hockey championships | https://en.wikipedia.org/wiki/1974_World_Ice_Hockey_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14271063-1.html.csv | superlative | in the 1974 world ice hockey championships the soviet union had the most points . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'soviet union', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'soviet union'], 'result': True, 'ind': 2,... | eq { hop { argmax { all_rows ; points } ; team } ; soviet union } = true | select the row whose points record of all rows is maximum . the team record of this row is soviet union . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'soviet union_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'soviet union_7': 'soviet union'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'soviet union_7': [2]} | ['team', 'games', 'drawn', 'lost', 'points difference', 'points'] | [['soviet union', '10', '0', '1', '64 - 18', '18'], ['czechoslovakia', '10', '0', '3', '57 - 20', '14'], ['sweden', '10', '1', '4', '38 - 24', '11'], ['finland', '10', '2', '4', '34 - 39', '10'], ['poland', '10', '2', '7', '22 - 64', '4'], ['east germany', '10', '1', '8', '19 - 82', '3']] |
asean club championship | https://en.wikipedia.org/wiki/ASEAN_Club_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12303563-1.html.csv | majority | all of the clubs in the asean club championship had 0 finishes in 4th place . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', '4th place', '0'], 'result': True, 'ind': 0, 'tointer': 'for the 4th place records of all rows , all of them are equal to 0 .', 'tostr': 'all_eq { all_rows ; 4th place ; 0 } = true'} | all_eq { all_rows ; 4th place ; 0 } = true | for the 4th place records of all rows , all of them are equal to 0 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, '4th place_3': 3, '0_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', '4th place_3': '4th place', '0_4': '0'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], '4th place_3': [0], '0_4': [0]} | ['', 'nation', 'winners', 'runners - up', '3rd place', '4th place'] | [['1', 'kingfisher east bengal fc', '1', '0', '0', '0'], ['2', 'tampines rovers fc', '1', '0', '0', '0'], ['3', 'bec tero sasana', '0', '1', '0', '0'], ['4', 'pahang fa', '0', '1', '0', '0'], ['5', 'dpmm fc ( duli pengiran muda mahkota fc )', '0', '0', '1', '0'], ['6', 'hoang anh gia lai', '0', '0', '1', '0'], ['7', 'p... |
list of sports teams in nebraska | https://en.wikipedia.org/wiki/List_of_sports_teams_in_Nebraska | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14115168-4.html.csv | comparative | doane college was founded earlier than college of saint mary . | {'row_1': '4', 'row_2': '2', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'doane college'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to doane college .', 'tostr': 'filter_eq { all_rows ; school ; doane college }'}, 'founded'], 'resul... | less { hop { filter_eq { all_rows ; school ; doane college } ; founded } ; hop { filter_eq { all_rows ; school ; college of saint mary } ; founded } } = true | select the rows whose school record fuzzily matches to doane college . take the founded record of this row . select the rows whose school record fuzzily matches to college of saint mary . take the founded record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school_7': 7, 'doane college_8': 8, 'founded_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'school_11': 11, 'college of saint mary_12': 12, 'founded_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school_7': 'school', 'doane college_8': 'doane college', 'founded_9': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'school_11': 'school', 'co... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'school_7': [0], 'doane college_8': [0], 'founded_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'school_11': [1], 'college of saint mary_12': [1], 'founded_13': [3]} | ['school', 'mascot', 'conference', 'national titles', 'founded'] | [['bellevue university', 'bellevue bruins', 'midlands', '14', '1966'], ['college of saint mary', 'saint mary flames', 'midlands', '0', '1923'], ['concordia university', 'concordia bulldogs', 'great plains', '1', '1894'], ['doane college', 'doane tigers', 'great plains', '10', '1872'], ['hastings college', 'hastings bro... |
hisar ( lok sabha constituency ) | https://en.wikipedia.org/wiki/Hisar_%28Lok_Sabha_constituency%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17922483-1.html.csv | majority | the majority of hisar 's constituencies are located in the hisar district . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hisar', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'district', 'hisar'], 'result': True, 'ind': 0, 'tointer': 'for the district records of all rows , most of them fuzzily match to hisar .', 'tostr': 'most_eq { all_rows ; district ; hisar } = true'} | most_eq { all_rows ; district ; hisar } = true | for the district records of all rows , most of them fuzzily match to hisar . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'district_3': 3, 'hisar_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'district_3': 'district', 'hisar_4': 'hisar'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'district_3': [0], 'hisar_4': [0]} | ['constituency number', 'name', 'reserved for ( sc / st / none )', 'district', 'number of electorates ( 2009 )'] | [['37', 'uchana kalan', 'none', 'jind', '154284'], ['47', 'adampur', 'none', 'hisar', '123558'], ['48', 'uklana', 'sc', 'hisar', '147491'], ['49', 'narnaund', 'none', 'hisar', '152958'], ['50', 'hansi', 'none', 'hisar', '133581'], ['51', 'barwala', 'none', 'hisar', '119790'], ['52', 'hisar', 'none', 'hisar', '101595'],... |
1925 vfl season | https://en.wikipedia.org/wiki/1925_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746200-17.html.csv | ordinal | brunswick street oval venue recorded the highest crowd participation during the 1925 vfl season . | {'row': '6', 'col': '6', 'order': '1', 'col_other': '5', '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', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'brunswick street oval', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'brunswic... | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; brunswick street oval } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is brunswick street oval . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'brunswick street oval_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', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'brunswick street oval_8': 'brunswick street oval'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'brunswick street oval_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '9.9 ( 63 )', 'richmond', '2.12 ( 24 )', 'mcg', '16989', '12 september 1925'], ['hawthorn', '7.13 ( 55 )', 'north melbourne', '4.6 ( 30 )', 'glenferrie oval', '8000', '12 september 1925'], ['essendon', '10.7 ( 67 )', 'st kilda', '8.10 ( 58 )', 'windy hill', '15000', '12 september 1925'], ['geelong', '14.... |
cbo - fm | https://en.wikipedia.org/wiki/CBO-FM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1585163-1.html.csv | comparative | the station in kingston uses a higher frequency than the one in pembroke . | {'row_1': '4', 'row_2': '6', 'col': '3', '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', 'city of license', 'kingston'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city of license record fuzzily matches to kingston .', 'tostr': 'filter_eq { all_rows ; city of license ; kingston }'}, 'fr... | greater { hop { filter_eq { all_rows ; city of license ; kingston } ; frequency } ; hop { filter_eq { all_rows ; city of license ; pembroke } ; frequency } } = true | select the rows whose city of license record fuzzily matches to kingston . take the frequency record of this row . select the rows whose city of license record fuzzily matches to pembroke . take the frequency 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, 'city of license_7': 7, 'kingston_8': 8, 'frequency_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'city of license_11': 11, 'pembroke_12': 12, 'frequency_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', 'city of license_7': 'city of license', 'kingston_8': 'kingston', 'frequency_9': 'frequency', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'city of... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'city of license_7': [0], 'kingston_8': [0], 'frequency_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'city of license_11': [1], 'pembroke_12': [1], 'frequency_13': [3]} | ['city of license', 'identifier', 'frequency', 'power', 'class', 'recnet'] | [['brockville', 'cbob - fm', '91.9 fm', '1080 s watt', 'a', 'query'], ['cornwall', 'cboc - fm', '95.5 fm', '3000 watts', 'a', 'query'], ['deep river', 'cbli', '1110 am', '40 watts', 'lp', 'query'], ['kingston', 'cbck - fm', '107.5 fm', '100000 watts', 'c1', 'query'], ['maniwaki , quebec', 'cbom', '710 am', '40 watts', ... |
ireland in the eurovision song contest 1989 | https://en.wikipedia.org/wiki/Ireland_in_the_Eurovision_Song_Contest_1989 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16956150-1.html.csv | superlative | for irish singers in the 1989 eurovision song contest , the performer with the highest number of points is kiev connolly & the missing passengers . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'performer'], 'result': 'kiev connolly & the missing passengers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; performer }'}, 'kiev ... | eq { hop { argmax { all_rows ; points } ; performer } ; kiev connolly & the missing passengers } = true | select the row whose points record of all rows is maximum . the performer record of this row is kiev connolly & the missing passengers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'performer_6': 6, 'kiev connolly & the missing passengers_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'performer_6': 'performer', 'kiev connolly & the missing passengers_7': 'kiev connolly & the missing passengers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'performer_6': [1], 'kiev connolly & the missing passengers_7': [2]} | ['draw', 'song', 'performer', 'points', 'rank'] | [['1', 'the real me', 'kiev connolly & the missing passengers', '104', '1st'], ['2', 'easy', 'honor heffernan', '97', '2nd'], ['3', "this is n't war ( it 's revolution )", 'nicola kerr', '79', '3rd'], ['4', 'uaigneach', 'barry ronan', '48', '8th'], ['5', 'here we go', 'linda martin', '71', '6th'], ['6', 'angel eyes', '... |
1986 - 87 segunda división | https://en.wikipedia.org/wiki/1986%E2%80%9387_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12109851-2.html.csv | ordinal | the club castilla cf had the second largest number of losses in the 1986 - 87 segunda división . | {'row': '17', 'col': '7', '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', 'losses', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; losses ; 2 }'}, 'club'], 'result': 'castilla cf', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; losses ; 2 } ; club }'}, 'castilla cf'], 'r... | eq { hop { nth_argmax { all_rows ; losses ; 2 } ; club } ; castilla cf } = true | select the row whose losses record of all rows is 2nd maximum . the club record of this row is castilla cf . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'losses_5': 5, '2_6': 6, 'club_7': 7, 'castilla cf_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', 'losses_5': 'losses', '2_6': '2', 'club_7': 'club', 'castilla cf_8': 'castilla cf'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'losses_5': [0], '2_6': [0], 'club_7': [1], 'castilla cf_8': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'valencia cf', '34', '46 + 12', '19', '8', '7', '53', '26', '+ 27'], ['2', 'deportivo de la coruña', '34', '43 + 9', '16', '11', '7', '46', '33', '+ 13'], ['3', 'cd logroñés', '34', '41 + 7', '16', '9', '9', '46', '33', '+ 13'], ['4', 'celta de vigo', '34', '40 + 6', '17', '6', '11', '56', '35', '+ 21'], ['5', '... |
brazil national football team | https://en.wikipedia.org/wiki/Brazil_national_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-149286-9.html.csv | count | for the brazil national football team , when the caps were under 100 , there were 2 times that there were 3 goals . | {'scope': 'subset', 'criterion': 'equal', 'value': '3', 'result': '2', 'col': '3', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '100'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'caps', '100'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; caps ; 100 }', 'tointer': 'select the rows whose caps record is less than 100 .'}, 'goals', '3'], 'result': None, 'i... | eq { count { filter_eq { filter_less { all_rows ; caps ; 100 } ; goals ; 3 } } ; 2 } = true | select the rows whose caps record is less than 100 . among these rows , select the rows whose goals record is equal to 3 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'caps_6': 6, '100_7': 7, 'goals_8': 8, '3_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'caps_6': 'caps', '100_7': '100', 'goals_8': 'goals', '3_9': '3', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'caps_6': [0], '100_7': [0], 'goals_8': [1], '3_9': [1], '2_10': [3]} | ['name', 'caps', 'goals', 'first cap', 'latest cap'] | [['cafu', '142', '5', 'september 12 , 1990', 'july 1 , 2006'], ['roberto carlos', '125', '11', 'february 26 , 1992', 'july 1 , 2006'], ['lúcio', '105', '4', 'november 15 , 2000', 'september 5 , 2011'], ['cláudio taffarel', '101', '0', 'july 7 , 1988', 'july 12 , 1998'], ['djalma santos', '98', '3', 'april 10 , 1952', '... |
fiba eurobasket 2007 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-8.html.csv | count | there are a total of three players that were born in the year 1978 who held a center position in the 2007 fiba eurobasket squads . | {'scope': 'subset', 'criterion': 'equal', 'value': '1978', 'result': '3', 'col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': '1978'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year born', '1978'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year born ; 1978 }', 'tointer': 'select the rows whose year born record is equal to 1978 .'}, 'year born', '1978']... | eq { count { filter_eq { filter_eq { all_rows ; year born ; 1978 } ; year born ; 1978 } } ; 3 } = true | select the rows whose year born record is equal to 1978 . among these rows , select the rows whose year born record is equal to 1978 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'year born_6': 6, '1978_7': 7, 'year born_8': 8, '1978_9': 9, '3_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', 'year born_6': 'year born', '1978_7': '1978', 'year born_8': 'year born', '1978_9': '1978', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'year born_6': [0], '1978_7': [0], 'year born_8': [1], '1978_9': [1], '3_10': [3]} | ['player', 'height', 'position', 'year born', 'current club'] | [['miguel minhava', '1 , 97', 'guard', '1983', "cb l'hospitalet"], ['mário gil fernandes', '1 , 74', 'guard', '1982', 'cb plasencia'], ['sérgio ramos', '2 , 00', 'forward', '1975', 'drac inca'], ['paulo cunha', '1 , 99', 'forward', '1980', 'fc porto'], ['francisco jordão', '2 , 00', 'center', '1979', '1 de agosto'], ['... |
emergency shipbuilding program | https://en.wikipedia.org/wiki/Emergency_Shipbuilding_program | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11552751-4.html.csv | unique | the great lakes engineering co shipbuilding yard is the only yard in the state of michigan . | {'scope': 'all', 'row': '8', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'michigan', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location ( city , state )', 'michigan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location ( city , state ) record fuzzily matches to michigan .', 'tostr': 'filter_eq { all_rows ; location ( city , stat... | and { only { filter_eq { all_rows ; location ( city , state ) ; michigan } } ; eq { hop { filter_eq { all_rows ; location ( city , state ) ; michigan } ; yard name } ; great lakes engineering co } } = true | select the rows whose location ( city , state ) record fuzzily matches to michigan . there is only one such row in the table . the yard name record of this unqiue row is great lakes engineering co . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location (city , state)_7': 7, 'michigan_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'yard name_9': 9, 'great lakes engineering co_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location (city , state)_7': 'location ( city , state )', 'michigan_8': 'michigan', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'yard name_9': 'yard name', 'great lakes engineering co_10': 'great lakes... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location (city , state)_7': [0], 'michigan_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'yard name_9': [2], 'great lakes engineering co_10': [3]} | ['yard name', 'location ( city , state )', '1st ship delivery date', 'ship types delivered', 'total number of ways'] | [['cargill inc', 'savage , minnesota', 'november 1941', 't1 type', 'number'], ['leatham d smith shipbuilding co', 'sturgeon bay , wisconsin', 'november 1942', 'c1 - m type , n3 type , s2 ( frigate ) type', 'number'], ['walter butler shipbuilders', 'superior , wisconsin', 'december 1942', 'c1 - m type , n3 type , s2 ( f... |
81st united states congress | https://en.wikipedia.org/wiki/81st_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1694492-2.html.csv | count | a total of four vacated seats were not filled for the remainder of the term . | {'scope': 'all', 'criterion': 'equal', 'value': 'vacant', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'vacant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to vacant .', 'tostr': 'filter_eq { all_rows ; successor ; vacant }'}], 'result': '4', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; successor ; vacant } } ; 4 } = true | select the rows whose successor record fuzzily matches to vacant . 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, 'successor_5': 5, 'vacant_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', 'successor_5': 'successor', 'vacant_6': 'vacant', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'successor_5': [0], 'vacant_6': [0], '4_7': [2]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['new york 7th', 'vacant', 'rep john j delaney died during previous congress', 'louis b heller ( d )', 'february 15 , 1949'], ['new york 20th', 'sol bloom ( d )', 'died march 7 , 1949', 'franklin delano roosevelt , jr ( lib )', 'may 17 , 1949'], ['new york 10th', 'andrew l somers ( d )', 'died april 6 , 1949', 'edna f... |
wang shi - ting | https://en.wikipedia.org/wiki/Wang_Shi-ting | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15340120-1.html.csv | count | a total of two tournaments that wang shi - ting played in were located in taipei , taiwan . | {'scope': 'all', 'criterion': 'equal', 'value': 'taipei , taiwan', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'taipei , taiwan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to taipei , taiwan .', 'tostr': 'filter_eq { all_rows ; tournament ; taipei , taiwan }'}], 're... | eq { count { filter_eq { all_rows ; tournament ; taipei , taiwan } } ; 2 } = true | select the rows whose tournament record fuzzily matches to taipei , taiwan . 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, 'tournament_5': 5, 'taipei, taiwan_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', 'tournament_5': 'tournament', 'taipei, taiwan_6': 'taipei , taiwan', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tournament_5': [0], 'taipei, taiwan_6': [0], '2_7': [2]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['september 13 , 1993', 'hong kong', 'hard', 'marianne witmeyer', '6 - 4 , 3 - 6 , 7 - 5'], ['october 4 , 1993', 'taipei , taiwan', 'hard', 'linda wild', '6 - 1 , 7 - 6 ( 4 )'], ['november 14 , 1994', 'taipei , taiwan', 'hard', 'kyoko nagatsuka', '6 - 1 , 6 - 3'], ['october 2 , 1995', 'surabaya , indonesia', 'hard', '... |
eurovision song contest 1966 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1966 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184807-1.html.csv | unique | in the eurovision song contest in 1966 , when the language was french , the only time there were 14 points was when the artist was tonia . | {'scope': 'subset', 'row': '3', 'col': '7', 'col_other': '3', 'criterion': 'equal', 'value': '14', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'french'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'french'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; language ; french }', 'tointer': 'select the rows whose language record fuzzily matches to french .'}, 'point... | and { only { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } } ; eq { hop { filter_eq { filter_eq { all_rows ; language ; french } ; points ; 14 } ; artist } ; tonia } } = true | select the rows whose language record fuzzily matches to french . among these rows , select the rows whose points record is equal to 14 . there is only one such row in the table . the artist record of this unqiue row is tonia . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'language_8': 8, 'french_9': 9, 'points_10': 10, '14_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'artist_12': 12, 'tonia_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'language_8': 'language', 'french_9': 'french', 'points_10': 'points', '14_11': '14', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'artist_12': 'artist', 'tonia_13': 'tonia'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'language_8': [0], 'french_9': [0], 'points_10': [1], '14_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'artist_12': [3], 'tonia_13': [4]} | ['draw', 'language', 'artist', 'song', 'english translation', 'place', 'points'] | [['01', 'german', 'margot eskens', 'die zeiger der uhr', 'the hands of the clock', '10', '7'], ['02', 'danish', 'ulla pia', "stop - mens legen er go '", "stop while the going 's good", '14', '4'], ['03', 'french', 'tonia', 'un peu de poivre , un peu de sel', 'a bit of pepper , a bit of salt', '4', '14'], ['04', 'french... |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-12.html.csv | majority | the majority of incumbents in the united states house of representatives elections of 1954 from illinois were with the republican party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'} | most_eq { all_rows ; party ; republican } = true | for the party records of all rows , most of them fuzzily match to republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 2', "barratt o'hara", 'democratic', '1952', 're - elected', "barratt o'hara ( d ) 61.6 % richard b vail ( r ) 38.4 %"], ['illinois 3', 'fred e busbey', 'republican', '1950', 'lost re - election democratic gain', 'james c murray ( d ) 53.8 % fred e busbey ( r ) 46.2 %'], ['illinois 14', 'chauncey w reed', 'r... |
american dad ! ( season 7 ) | https://en.wikipedia.org/wiki/American_Dad%21_%28season_7%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26409328-1.html.csv | superlative | the episode of american dad ! in season 7 that had the highest number of viewers is the one that aired on november 7 , 2010 . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '6', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( millions ) }'}, 'original air date'], 'result': 'november 7 , 2010', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ... | eq { hop { argmax { all_rows ; us viewers ( millions ) } ; original air date } ; november 7 , 2010 } = true | select the row whose us viewers ( millions ) record of all rows is maximum . the original air date record of this row is november 7 , 2010 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, 'original air date_6': 6, 'november 7 , 2010_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (millions)_5': 'us viewers ( millions )', 'original air date_6': 'original air date', 'november 7 , 2010_7': 'november 7 , 2010'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], 'original air date_6': [1], 'november 7 , 2010_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['97', '1', '100 ad ( part 1 )', 'tim parsons', 'keith heisler', 'october 3 , 2010', '5ajn14', '6.16'], ['98', '2', 'son of stan ( part 2 )', 'chris bennett', 'erik sommers', 'october 10 , 2010', '5ajn17', '5.36'], ['99', '3', 'best little horror house in langley falls', 'john aoshima & jansen yee', 'eric weinberg', '... |
colts - patriots rivalry | https://en.wikipedia.org/wiki/Colts%E2%80%93Patriots_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13342861-6.html.csv | count | during the colts - patriots rivalry , there were five games where the location was the rca dome . | {'scope': 'all', 'criterion': 'equal', 'value': 'rca dome', 'result': '5', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'rca dome'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to rca dome .', 'tostr': 'filter_eq { all_rows ; location ; rca dome }'}], 'result': '5', 'ind': 1, 'tost... | eq { count { filter_eq { all_rows ; location ; rca dome } } ; 5 } = true | select the rows whose location record fuzzily matches to rca dome . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'rca dome_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'rca dome_6': 'rca dome', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'rca dome_6': [0], '5_7': [2]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['2000', 'october 8', 'new england patriots', '24 - 16', 'indianapolis colts', 'foxboro stadium'], ['2000', 'october 22', 'indianapolis colts', '30 - 23', 'new england patriots', 'rca dome'], ['2001', 'september 30', 'new england patriots', '44 - 13', 'indianapolis colts', 'foxboro stadium'], ['2001', 'october 21', 'n... |
2007 bc lions season | https://en.wikipedia.org/wiki/2007_BC_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11994830-20.html.csv | comparative | ian smart had a lower rating than dave dickenson during the 2007 bc lions season . | {'row_1': '5', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'ian smart'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to ian smart .', 'tostr': 'filter_eq { all_rows ; player ; ian smart }'}, 'rating'], 'result': None, 'in... | less { hop { filter_eq { all_rows ; player ; ian smart } ; rating } ; hop { filter_eq { all_rows ; player ; dave dickenson } ; rating } } = true | select the rows whose player record fuzzily matches to ian smart . take the rating record of this row . select the rows whose player record fuzzily matches to dave dickenson . take the rating record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'ian smart_8': 8, 'rating_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'dave dickenson_12': 12, 'rating_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'ian smart_8': 'ian smart', 'rating_9': 'rating', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'dave dickens... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'ian smart_8': [0], 'rating_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'dave dickenson_12': [1], 'rating_13': [3]} | ['player', 'att', 'comp', 'yards', 'rating'] | [['jarious jackson', '304', '167', '2553', '88.9'], ['buck pierce', '127', '81', '1013', '91.7'], ['dave dickenson', '87', '56', '740', '88.3'], ['gino guidugli', '11', '6', '138', '92.2'], ['ian smart', '1', '0', '0', '2.1']] |
list of collaborative software | https://en.wikipedia.org/wiki/List_of_collaborative_software | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1779657-2.html.csv | majority | the majority of the software programs do not allow faxing . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'no', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'faxing', 'no'], 'result': True, 'ind': 0, 'tointer': 'for the faxing records of all rows , most of them fuzzily match to no .', 'tostr': 'most_eq { all_rows ; faxing ; no } = true'} | most_eq { all_rows ; faxing ; no } = true | for the faxing records of all rows , most of them fuzzily match to no . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'faxing_3': 3, 'no_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'faxing_3': 'faxing', 'no_4': 'no'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'faxing_3': [0], 'no_4': [0]} | ['name', 'e - mail server', 'faxing', 'instant messaging', 'telephony', 'videoconferencing', 'web conferencing', 'data conferencing', 'application sharing', 'electronic meeting system', 'synchronous conferencing'] | [['ibm sametime', 'no , integrated with lotus domino', 'no', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes'], ['ibm lotus domino', 'yes', 'yes', 'yes with integrated sametime', 'yes with integrated sametime', 'yes with integrated sametime', 'yes with integrated sametime', 'no', 'yes with integrated sametime', '... |
list of pokémon theme songs | https://en.wikipedia.org/wiki/List_of_Pok%C3%A9mon_theme_songs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2144389-8.html.csv | unique | kanako was a vocalist on only one pokemon theme song . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'kanako', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'vocalist', 'kanako'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose vocalist record fuzzily matches to kanako .', 'tostr': 'filter_eq { all_rows ; vocalist ; kanako }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_ro... | only { filter_eq { all_rows ; vocalist ; kanako } } = true | select the rows whose vocalist record fuzzily matches to kanako . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'vocalist_4': 4, 'kanako_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'vocalist_4': 'vocalist', 'kanako_5': 'kanako'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'vocalist_4': [0], 'kanako_5': [0]} | ['', 'japanese title', 'rōmaji', 'japanese translation', 'vocalist', 'episodes used'] | [['1', '君のそばで ～ ヒカリのテーマ ～', 'kimi no soba de ~ hikari no tēma ~', "by your side ~ hikari 's theme ~", 'grin', 'dp001 - dp024'], ['2', '君のそばで ～ ヒカリのテーマ ～ ( popupversion )', 'kimi no soba de ~ hikari no tēma ~ ( popupversion )', "by your side ~ hikari 's theme ~ ( popupversion )", 'grin', 'dp025 - dp050'], ['3', '君のそばで ～... |
uefa club competition records and statistics | https://en.wikipedia.org/wiki/UEFA_club_competition_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12307135-7.html.csv | unique | eusébio was the only player in the top 9 to score less than 55 goals . | {'scope': 'all', 'row': '9', 'col': '3', 'col_other': '2', 'criterion': 'less_than', 'value': '55', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'goals', '55'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals record is less than 55 .', 'tostr': 'filter_less { all_rows ; goals ; 55 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_ro... | and { only { filter_less { all_rows ; goals ; 55 } } ; eq { hop { filter_less { all_rows ; goals ; 55 } ; player } ; eusébio } } = true | select the rows whose goals record is less than 55 . there is only one such row in the table . the player record of this unqiue row is eusébio . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'goals_7': 7, '55_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'eusébio_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'goals_7': 'goals', '55_8': '55', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'eusébio_10': 'eusébio'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'goals_7': [0], '55_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'eusébio_10': [3]} | ['rank', 'player', 'goals', 'games', 'debut in europe'] | [['1', 'raúl', '75', '155', '1995'], ['2', 'filippo inzaghi', '70', '114', '1995'], ['3', 'andriy shevchenko', '67', '142', '1994'], ['4', 'lionel messi', '67', '82', '2004'], ['5', 'gerd müller', '62', '69', '1967'], ['5', 'ruud van nistelrooy', '62', '92', '1998'], ['7', 'henrik larsson', '59', '108', '1996'], ['7', ... |
national democratic congress ( ghana ) | https://en.wikipedia.org/wiki/National_Democratic_Congress_%28Ghana%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1725076-2.html.csv | comparative | the share of votes in 2004 was 12.8 % lower than the share of votes in 1996 . | {'row_1': '4', 'row_2': '7', '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', 'election', '2004'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose election record fuzzily matches to 2004 .', 'tostr': 'filter_eq { all_rows ; election ; 2004 }'}, 'share of votes'], 'result': None, 'ind... | less { hop { filter_eq { all_rows ; election ; 2004 } ; share of votes } ; hop { filter_eq { all_rows ; election ; 1996 } ; share of votes } } = true | select the rows whose election record fuzzily matches to 2004 . take the share of votes record of this row . select the rows whose election record fuzzily matches to 1996 . take the share of votes 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, 'election_7': 7, '2004_8': 8, 'share of votes_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'election_11': 11, '1996_12': 12, 'share of votes_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', 'election_7': 'election', '2004_8': '2004', 'share of votes_9': 'share of votes', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'election_11': 'election',... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'election_7': [0], '2004_8': [0], 'share of votes_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'election_11': [1], '1996_12': [1], 'share of votes_13': [3]} | ['election', 'candidate', 'number of votes', 'share of votes', 'outcome of election'] | [['2012', 'john dramani mahama', '5574761', '50.7 %', 'mahama ndc government'], ['2008 ( 2 )', 'john atta mills', '4501466', '50.1 %', 'mills ndc government'], ['2008 ( 1 )', 'john atta mills', '4056634', '47.9 %', '2nd round election'], ['2004', 'john atta mills', '3850368', '44.6 %', 'ndc opposition'], ['2000 ( 2nd )... |
1991 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1991_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162268-2.html.csv | aggregation | in the 1991 u.s. open , the average number of strokes to par was 2.78 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '2.78', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'to par'], 'result': '2.78', 'ind': 0, 'tostr': 'avg { all_rows ; to par }'}, '2.78'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; to par } ; 2.78 } = true', 'tointer': 'the average of the to par record of all rows is 2.78 .'} | round_eq { avg { all_rows ; to par } ; 2.78 } = true | the average of the to par record of all rows is 2.78 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'to par_4': 4, '2.78_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '2.78_5': '2.78'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'to par_4': [0], '2.78_5': [1]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['scott simpson', 'united states', '1987', '282', '- 6', '2'], ['larry nelson', 'united states', '1983', '285', '- 3', 't3'], ['fuzzy zoeller', 'united states', '1984', '286', '- 2', '5'], ['raymond floyd', 'united states', '1986', '289', '+ 1', 't8'], ['hale irwin', 'united states', '1974 , 1979 , 1990', '290', '+ 2'... |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-37.html.csv | aggregation | the mean vote percentage of the republican candidates representing pennsylvania in the '54 united states house of representatives elections was 51.0 % . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '51.0', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'candidates'], 'result': '51.0', 'ind': 0, 'tostr': 'avg { all_rows ; candidates }'}, '51.0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; candidates } ; 51.0 } = true', 'tointer': 'the average of the candidates record of all rows is... | round_eq { avg { all_rows ; candidates } ; 51.0 } = true | the average of the candidates record of all rows is 51.0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'candidates_4': 4, '51.0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'candidates_4': 'candidates', '51.0_5': '51.0'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'candidates_4': [0], '51.0_5': [1]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 6', 'hugh scott', 'republican', '1946', 're - elected', 'hugh scott ( r ) 50.6 % alexander hemphill ( d ) 49.4 %'], ['pennsylvania 8', 'karl c king', 'republican', '1951', 're - elected', 'karl c king ( r ) 51.2 % john p fullam ( d ) 48.8 %'], ['pennsylvania 9', 'paul b dague', 'republican', '1946', 're... |
united states house of representatives elections , 1998 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341453-44.html.csv | count | a total of three incumbents from tennessee in the 1998 house of representatives elections were from the democratic party . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': '3', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; party ; democratic } } ; 3 } = true | select the rows whose party record fuzzily matches to democratic . 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, 'party_5': 5, 'democratic_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', 'party_5': 'party', 'democratic_6': 'democratic', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '3_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['tennessee 1', 'william l jenkins', 'republican', '1996', 're - elected', 'william l jenkins ( r ) 69 % kay white ( d ) 31 %'], ['tennessee 2', 'jimmy duncan jr', 'republican', '1988', 're - elected', 'jimmy duncan jr ( r ) unopposed'], ['tennessee 3', 'zach wamp', 'republican', '1994', 're - elected', 'zach wamp ( r... |
list of supernanny episodes | https://en.wikipedia.org/wiki/List_of_Supernanny_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-5.html.csv | count | there are 5 listed episodes in the supernanny televised series . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'no in series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no in series record is arbitrary .', 'tostr': 'filter_all { all_rows ; no in series }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { al... | eq { count { filter_all { all_rows ; no in series } } ; 5 } = true | select the rows whose no in series record is arbitrary . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'no in series_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'no in series_5': 'no in series', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'no in series_5': [0], '5_6': [2]} | ['no overall', 'no in series', 'family / families', 'location ( s )', 'original air date'] | [['uk16', '1', 'the hillhouse - docherty family', 'ayr ( scotland )', '29 august 2006'], ['uk17', '2', 'the howat family', 'shenley', '5 september 2006'], ['uk18', '3', 'the brown - smith family', 'warrington', '12 september 2006'], ['uk19', '4', 'the bates family', 'evesham', '19 september 2006'], ['uk20', '5', 'the w... |
list of awards and nominations received by renée zellweger | https://en.wikipedia.org/wiki/List_of_awards_and_nominations_received_by_Ren%C3%A9e_Zellweger | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18747538-7.html.csv | majority | most of renée zellweger 's nominations and awards came after the year 2000 . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'year', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are greater than 2000 .', 'tostr': 'most_greater { all_rows ; year ; 2000 } = true'} | most_greater { all_rows ; year ; 2000 } = true | for the year records of all rows , most of them are greater than 2000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '2000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '2000_4': '2000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '2000_4': [0]} | ['year', 'category', 'film', 'result', 'lost to'] | [['1996', 'outstanding supporting actress', 'jerry maguire', 'nominated', 'lauren bacall ( the mirror has two faces )'], ['2001', 'outstanding actress', "bridget jones 's diary", 'nominated', 'halle berry ( monsters ball )'], ['2002', 'outstanding cast', 'chicago', 'won', '-'], ['2002', 'outstanding actress', 'chicago'... |
1970 isle of man tt | https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-5.html.csv | majority | most of the riders had less than 10 points at the 1970 isle of man tt . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'points', '10'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are less than 10 .', 'tostr': 'most_less { all_rows ; points ; 10 } = true'} | most_less { all_rows ; points ; 10 } = true | for the points records of all rows , most of them are less than 10 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '10_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '10_4': '10'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '10_4': [0]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'kel carruthers', 'australia', 'yamaha', '96.13 mph', '2:21.19.2', '15'], ['2', 'rod gould', 'united kingdom', 'yamaha', '93.75 mph', '2:24.54.0', '12'], ['3', 'günter bartusch', 'east germany', 'mz', '93.75 mph', '2:26.58.0', '10'], ['4', 'chas mortimer', 'united kingdom', 'yamaha', '91.95 mph', '2:27.44.2', '8... |
2010 cfl draft | https://en.wikipedia.org/wiki/2010_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25017530-6.html.csv | count | three of the 2010 cfl draft picks were for the position ol . | {'scope': 'all', 'criterion': 'equal', 'value': 'ol', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'ol'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to ol .', 'tostr': 'filter_eq { all_rows ; position ; ol }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; position ; ol } } ; 3 } = true | select the rows whose position record fuzzily matches to ol . 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, 'position_5': 5, 'ol_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', 'position_5': 'position', 'ol_6': 'ol', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'ol_6': [0], '3_7': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['32', 'toronto argonauts', 'michael warner', 'ol', 'waterloo'], ['33', 'saskatchewan roughriders ( via winnipeg )', 'patrick neufeld', 'ol', 'saskatchewan'], ['34', 'bc lions', 'cauchy muamba', 'db', 'st francis xavier'], ['35', 'edmonton eskimos', 'scott ferguson', 'ol', 'st cloud state'], ['36', 'hamilton tiger - c... |
1992 - 93 toronto maple leafs season | https://en.wikipedia.org/wiki/1992%E2%80%9393_Toronto_Maple_Leafs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13913477-9.html.csv | majority | all games of the toronto maple leafs in the 1992 - 93 season were scheduled for the month of april . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'april', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'april'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to april .', 'tostr': 'all_eq { all_rows ; date ; april } = true'} | all_eq { all_rows ; date ; april } = true | for the date records of all rows , all of them fuzzily match to april . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'april_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'april_4': 'april'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'april_4': [0]} | ['game', 'date', 'visitor', 'score', 'home', 'record', 'points'] | [['78', 'april 3', 'new jersey', '1 - 0', 'toronto', '42 - 25 - 11', '95'], ['79', 'april 4', 'toronto', '0 - 4', 'philadelphia', '42 - 26 - 11', '95'], ['80', 'april 8', 'toronto', '3 - 5', 'winnipeg', '42 - 27 - 11', '95'], ['81', 'april 10', 'philadelphia', '0 - 4', 'toronto', '42 - 28 - 11', '95'], ['82', 'april 11... |
swimming at the 2007 world aquatics championships - men 's 200 metre freestyle | https://en.wikipedia.org/wiki/Swimming_at_the_2007_World_Aquatics_Championships_%E2%80%93_Men%27s_200_metre_freestyle | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10563642-3.html.csv | superlative | pieter van den hoogenband was the swimmer who had the fastest time overall . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'name'], 'result': 'pieter van den hoogenband', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; name }'}, 'pieter van den hoogenband'], 'resu... | eq { hop { argmin { all_rows ; time } ; name } ; pieter van den hoogenband } = true | select the row whose time record of all rows is minimum . the name record of this row is pieter van den hoogenband . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'name_6': 6, 'pieter van den hoogenband_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'name_6': 'name', 'pieter van den hoogenband_7': 'pieter van den hoogenband'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'name_6': [1], 'pieter van den hoogenband_7': [2]} | ['rank', 'heat', 'lane', 'name', 'nationality', '100 m', '150 m', 'time'] | [['1', '2', '4', 'pieter van den hoogenband', 'netherlands', '51.16', '1:18.66', '1:46.33'], ['2', '1', '4', 'michael phelps', 'united states', '52.48', '1:20.10', '1:46.75'], ['3', '2', '2', 'massimiliano rosolino', 'italy', '52.13', '1:19.48', '1:47.44'], ['4', '1', '5', 'kenrick monk', 'australia', '52.96', '1:20.64... |
northern indiana athletic conference | https://en.wikipedia.org/wiki/Northern_Indiana_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12264570-1.html.csv | unique | south bend adams is the only school to join the northern indiana athletic conference in 1941 . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '1941', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'joined', '1941'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose joined record is equal to 1941 .', 'tostr': 'filter_eq { all_rows ; joined ; 1941 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_... | and { only { filter_eq { all_rows ; joined ; 1941 } } ; eq { hop { filter_eq { all_rows ; joined ; 1941 } ; school } ; south bend adams } } = true | select the rows whose joined record is equal to 1941 . there is only one such row in the table . the school record of this unqiue row is south bend adams . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'joined_7': 7, '1941_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'school_9': 9, 'south bend adams_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'joined_7': 'joined', '1941_8': '1941', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'school_9': 'school', 'south bend adams_10': 'south bend adams'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'joined_7': [0], '1941_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'school_9': [2], 'south bend adams_10': [3]} | ['school', 'location', 'mascot', 'county', 'enrollment ihsaa class', 'joined', 'previous conference'] | [['elkhart central', 'elkhart', 'blue blazers', '20 elkhart', '1747 aaaa', '1927', 'independents'], ['mishawaka', 'mishawaka', 'cavemen', '71 st joseph', '1761 aaaa', '1927', 'independents'], ['mishawaka marian', 'mishawaka', 'knights', '71 st joseph', '768 aaa', '2005', 'independents'], ['penn', 'mishawaka', 'kingsmen... |
rizal | https://en.wikipedia.org/wiki/Rizal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-232458-1.html.csv | aggregation | the average population of cities in rizal in 2010 was 187514 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '187514', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population ( 2010 census )'], 'result': '187514', 'ind': 0, 'tostr': 'avg { all_rows ; population ( 2010 census ) }'}, '187514'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population ( 2010 census ) } ; 187514 } = true', 'tointer'... | round_eq { avg { all_rows ; population ( 2010 census ) } ; 187514 } = true | the average of the population ( 2010 census ) record of all rows is 187514 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population (2010 census)_4': 4, '187514_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population (2010 census)_4': 'population ( 2010 census )', '187514_5': '187514'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population (2010 census)_4': [0], '187514_5': [1]} | ['city / municipality', 'no of barangays', 'area ( km square )', 'population ( 2010 census )', 'pop density ( per km square )'] | [['angono', '10', '26.22', '102407', '3905.68'], ['antipolo', '16', '306.10', '677741', '2214.12'], ['baras', '10', '84.93', '32609', '383.95'], ['binangonan', '40', '66.34', '249872', '3766.54'], ['cainta', '7', '42.99', '311845', '7253.90'], ['cardona', '18', '28.56', '47414', '1660.15'], ['jalajala', '11', '44.12', ... |
liberty league | https://en.wikipedia.org/wiki/Liberty_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974482-1.html.csv | aggregation | the average student enrollment at institutions in the liberty league is 4067 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '4067', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '4067', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '4067'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 4067 } = true', 'tointer': 'the average of the enrollment record of all rows is... | round_eq { avg { all_rows ; enrollment } ; 4067 } = true | the average of the enrollment record of all rows is 4067 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '4067_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '4067_5': '4067'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '4067_5': [1]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'joined'] | [['bard college', 'raptors', 'annandale - on - hudson , new york', '1860', 'private', '1958', '2011'], ['clarkson university', 'golden knights', 'potsdam , new york', '1896', 'private', '2848', '1995'], ['hobart college', 'statesmen', 'geneva , new york', '1822', 'private', '905', '1995'], ['rensselaer polytechnic inst... |
1969 vfl season | https://en.wikipedia.org/wiki/1969_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809157-17.html.csv | majority | the majority of the matches were in front of a crowd of 22,000 or less . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '22,000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'crowd', '22,000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are less than 22,000 .', 'tostr': 'most_less { all_rows ; crowd ; 22,000 } = true'} | most_less { all_rows ; crowd ; 22,000 } = true | for the crowd records of all rows , most of them are less than 22,000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '22,000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '22,000_4': '22,000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '22,000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '9.14 ( 68 )', 'south melbourne', '15.10 ( 100 )', 'moorabbin oval', '13400', '9 august 1969'], ['hawthorn', '22.12 ( 144 )', 'north melbourne', '18.18 ( 126 )', 'glenferrie oval', '13504', '9 august 1969'], ['essendon', '19.18 ( 132 )', 'fitzroy', '14.11 ( 95 )', 'windy hill', '15548', '9 august 1969'], ... |
a gift from a flower to a garden | https://en.wikipedia.org/wiki/A_Gift_from_a_Flower_to_a_Garden | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1793227-2.html.csv | count | epic was the label that released the title on six occasions . | {'scope': 'all', 'criterion': 'equal', 'value': 'epic', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'epic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to epic .', 'tostr': 'filter_eq { all_rows ; label ; epic }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_e... | eq { count { filter_eq { all_rows ; label ; epic } } ; 6 } = true | select the rows whose label record fuzzily matches to epic . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'label_5': 5, 'epic_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'label_5': 'label', 'epic_6': 'epic', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'label_5': [0], 'epic_6': [0], '6_7': [2]} | ['region', 'title', 'label', 'format', 'catalog - nr'] | [['usa', 'a gift from a flower to a garden', 'epic', 'mono lp', 'l2n6071'], ['usa', 'a gift from a flower to a garden', 'epic', 'stereo lp', 'b2n171'], ['uk', 'a gift from a flower to a garden', 'pye', 'mono lp', 'npl20000'], ['uk', 'a gift from a flower to a garden', 'pye', 'stereo lp', 'nspl 20000'], ['usa', 'wear yo... |
croatian bol ladies open | https://en.wikipedia.org/wiki/Croatian_Bol_Ladies_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16157440-1.html.csv | unique | for just one yea , the croatian bol ladies open was in the iva category . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'iva', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'iva'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to iva .', 'tostr': 'filter_eq { all_rows ; category ; iva }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; cate... | only { filter_eq { all_rows ; category ; iva } } = true | select the rows whose category record fuzzily matches to iva . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'category_4': 4, 'iva_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'category_4': 'category', 'iva_5': 'iva'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'category_4': [0], 'iva_5': [0]} | ['year', 'category', 'champion', 'runner - up', 'score'] | [['1991', 'v', 'sandra cecchini', 'magdalena maleeva', '6 - 4 , 3 - 6 , 7 - 5'], ['1995', 'iii', 'sabine appelmans', 'silke meier', '6 - 4 , 6 - 3'], ['1996', 'iv', 'gloria pizzichini', 'silvija talaja', '6 - 0 , 6 - 2'], ['1997', 'iv', 'mirjana lučić', 'corina morariu', '7 - 5 , 6 - 7 , 7 - 6'], ['1998', 'iva', 'mirja... |
kelly dullanty | https://en.wikipedia.org/wiki/Kelly_Dullanty | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445415-2.html.csv | count | kelly dullanty had two matches in the ifc wc 13 - warriors challenge 13 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ifc wc 13 - warriors challenge', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'ifc wc 13 - warriors challenge'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to ifc wc 13 - warriors challenge .', 'tostr': 'filter_eq { all_rows ; event ; ifc wc 13 ... | eq { count { filter_eq { all_rows ; event ; ifc wc 13 - warriors challenge } } ; 2 } = true | select the rows whose event record fuzzily matches to ifc wc 13 - warriors challenge . 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, 'event_5': 5, 'ifc wc 13 - warriors challenge_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', 'event_5': 'event', 'ifc wc 13 - warriors challenge_6': 'ifc wc 13 - warriors challenge', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'event_5': [0], 'ifc wc 13 - warriors challenge_6': [0], '2_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['loss', '4 - 2', 'lance wipf', 'ko ( punch )', 'purecombat - bring the pain', '1', 'california , united states'], ['loss', '4 - 1', 'matt serra', 'submission ( triangle choke )', 'ufc 36', '1', 'nevada , united states'], ['win', '4 - 0', 'nuri shakir', 'decision', 'ifc wc 13 - warriors challenge 13', '4', 'california... |
list of tvb series ( 2007 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%282007%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11173827-1.html.csv | count | three different tvb series had an average rating of 32 in 2007 . | {'scope': 'all', 'criterion': 'equal', 'value': '32', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'average', '32'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose average record is equal to 32 .', 'tostr': 'filter_eq { all_rows ; average ; 32 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_row... | eq { count { filter_eq { all_rows ; average ; 32 } } ; 3 } = true | select the rows whose average record is equal to 32 . 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, 'average_5': 5, '32_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'average_5': 'average', '32_6': '32', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'average_5': [0], '32_6': [0], '3_7': [2]} | ['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers'] | [['1', 'the family link', '師奶兵團', '33', '42', '31', '33', '2.12 million'], ['2', 'fathers and sons', '爸爸閉翳', '32', '40', '31', '37', '2.11 million'], ['3', 'heart of greed', '溏心風暴', '32', '48', '29', '40', '2.08 million'], ['4', 'ten brothers', '十兄弟', '32', '39', '29', '36', '2.05 million'], ['5', 'on the first beat', ... |
ken schrader | https://en.wikipedia.org/wiki/Ken_Schrader | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1671401-2.html.csv | unique | the year 1995 was the only year that ken schrader had four top 10 finishes . | {'scope': 'all', 'row': '9', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '4', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top 10', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top 10 record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; top 10 ; 4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; to... | and { only { filter_eq { all_rows ; top 10 ; 4 } } ; eq { hop { filter_eq { all_rows ; top 10 ; 4 } ; year } ; 1995 } } = true | select the rows whose top 10 record is equal to 4 . there is only one such row in the table . the year record of this unqiue row is 1995 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'top 10_7': 7, '4_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1995_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'top 10_7': 'top 10', '4_8': '4', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1995_10': '1995'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'top 10_7': [0], '4_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1995_10': [3]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1987', '1', '0', '1', '1', '0', '21.0', '5.0', '1825', '83rd', 'ken schrader racing'], ['1988', '10', '0', '2', '3', '0', '16.3', '20.1', '45175', '33rd', 'ken schrader racing'], ['1989', '11', '1', '1', '6', '1', '14.3', '17.6', '27577', '32nd', 'ken schrader racing hendrick motorsports'], ['1990', '11', '0', '1', ... |
indra putra mahayuddin | https://en.wikipedia.org/wiki/Indra_Putra_Mahayuddin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11847478-2.html.csv | aggregation | indra putra mahayuddin score a total of 30 goals in the games listed . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '30', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '30', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '30'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 30 } = true', 'tointer': 'the sum of the score record of all rows is 30 .'} | round_eq { sum { all_rows ; score } ; 30 } = true | the sum of the score record of all rows is 30 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '30_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '30_5': '30'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '30_5': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['december 11 , 2002', 'petaling jaya , malaysia', '5 - 0', 'win', 'friendly'], ['december 18 , 2002', 'singapore , singapore', '0 - 4', 'win', '2002 tiger cup group stage'], ['december 20 , 2002', 'singapore , singapore', '3 - 1', 'win', '2002 tiger cup group stage'], ['december 29 , 2002', 'singapore , singapore', '... |
1967 detroit lions season | https://en.wikipedia.org/wiki/1967_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18908350-1.html.csv | comparative | tim jones had a higher pick number than the defensive end . | {'row_1': '5', 'row_2': '4', 'col': '2', 'col_other': '3,4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'tim jones'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to tim jones .', 'tostr': 'filter_eq { all_rows ; player ; tim jones }'}, 'p... | and { greater { hop { filter_eq { all_rows ; player ; tim jones } ; pick } ; hop { filter_eq { all_rows ; player ; lew kamanu } ; pick } } ; and { eq { hop { filter_eq { all_rows ; player ; tim jones } ; position } ; quarterback } ; eq { hop { filter_eq { all_rows ; player ; lew kamanu } ; position } ; defensive end } ... | select the rows whose player record fuzzily matches to tim jones . take the pick record of this row . select the rows whose player record fuzzily matches to lew kamanu . take the pick record of this row . the first record is greater than the second record . the position record of the first row is quarterback . the posi... | 13 | 11 | {'and_10': 10, 'result_11': 11, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_12': 12, 'player_13': 13, 'tim jones_14': 14, 'pick_15': 15, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_16': 16, 'player_17': 17, 'lew kamanu_18': 18, 'pick_19': 19, 'and_9': 9, 'str_eq_6': 6, 'str_hop_5': 5, 'position_... | {'and_10': 'and', 'result_11': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_12': 'all_rows', 'player_13': 'player', 'tim jones_14': 'tim jones', 'pick_15': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_16': 'all_rows', 'player_17':... | {'and_10': [11], 'result_11': [], 'greater_4': [10], 'num_hop_2': [4], 'filter_str_eq_0': [2, 5], 'all_rows_12': [0], 'player_13': [0], 'tim jones_14': [0], 'pick_15': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3, 7], 'all_rows_16': [1], 'player_17': [1], 'lew kamanu_18': [1], 'pick_19': [3], 'and_9': [10], 'str_eq_6':... | ['round', 'pick', 'player', 'position', 'school'] | [['1', '7', 'mel farr', 'running back', 'ucla'], ['2', '34', 'lem barney', 'defensive back', 'jackson state'], ['3', '60', 'paul naumoff', 'linebacker', 'tennessee'], ['4', '88', 'lew kamanu', 'defensive end', 'weber state'], ['6', '141', 'tim jones', 'quarterback', 'weber state']] |
media in sherbrooke | https://en.wikipedia.org/wiki/Media_in_Sherbrooke | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409243-1.html.csv | comparative | of the media in sherbrooke , the station cimo - fm is at a higher frequency than the station cfak - fm . | {'row_1': '12', 'row_2': '2', 'col': '1', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'call sign', 'cimo - fm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose call sign record fuzzily matches to cimo - fm .', 'tostr': 'filter_eq { all_rows ; call sign ; cimo - fm }'}, 'frequency'], 'res... | greater { hop { filter_eq { all_rows ; call sign ; cimo - fm } ; frequency } ; hop { filter_eq { all_rows ; call sign ; cfak - fm } ; frequency } } = true | select the rows whose call sign record fuzzily matches to cimo - fm . take the frequency record of this row . select the rows whose call sign record fuzzily matches to cfak - fm . take the frequency 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, 'call sign_7': 7, 'cimo - fm_8': 8, 'frequency_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'call sign_11': 11, 'cfak - fm_12': 12, 'frequency_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', 'call sign_7': 'call sign', 'cimo - fm_8': 'cimo - fm', 'frequency_9': 'frequency', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'call sign_11': 'c... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'call sign_7': [0], 'cimo - fm_8': [0], 'frequency_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'call sign_11': [1], 'cfak - fm_12': [1], 'frequency_13': [3]} | ['frequency', 'call sign', 'format', 'owner', 'notes'] | [['fm 88.1', 'cfpp - fm', 'christian radio', 'fabrique notre - dame du perpétuel - secours', 'french'], ['fm 88.3', 'cfak - fm', 'campus radio', 'université de sherbrooke', 'french'], ['fm 88.9', 'cjmq - fm', 'community radio', "bishop 's university", 'english'], ['fm 89.7', 'cbm - fm - 1', 'public music', 'canadian br... |
canada post stamp releases ( 2005 - 09 ) | https://en.wikipedia.org/wiki/Canada_Post_stamp_releases_%282005%E2%80%9309%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11900773-1.html.csv | count | there were 3 canada post stamp releases designed by hélène lheureux . | {'scope': 'all', 'criterion': 'equal', 'value': 'hélène lheureux', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'design', 'hélène lheureux'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose design record fuzzily matches to hélène lheureux .', 'tostr': 'filter_eq { all_rows ; design ; hélène lheureux }'}], 'result': '3', ... | eq { count { filter_eq { all_rows ; design ; hélène lheureux } } ; 3 } = true | select the rows whose design record fuzzily matches to hélène lheureux . 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, 'design_5': 5, 'hélène lheureux_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', 'design_5': 'design', 'hélène lheureux_6': 'hélène lheureux', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'design_5': [0], 'hélène lheureux_6': [0], '3_7': [2]} | ['date of issue', 'denomination', 'design', 'paper type', 'first day cover cancellation'] | [['7 january 2005', '50 cents', 'hélène lheureux', 'tullis russell coatings', 'vancouver , bc'], ['7 january 2005', '1.45', 'hélène lheureux', 'tullis russell coatings', 'vancouver , bc'], ['29 january 2005', '0.50', 'stéphane huot', 'tullis russell coatings', 'edmonton , alberta'], ['4 february 2005', '0.50', 'circle ... |
2007 amsterdam admirals season | https://en.wikipedia.org/wiki/2007_Amsterdam_Admirals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10392906-2.html.csv | majority | most of the games during the 2007 amsterdam admirals season were losses . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'final score', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the final score records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; final score ; l } = true'} | most_eq { all_rows ; final score ; l } = true | for the final score records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'final score_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'final score_3': 'final score', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'final score_3': [0], 'l_4': [0]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , april 14', '7:00 pm', 'frankfurt galaxy', 'l 14 - 30', '0 - 1', 'commerzbank - arena', '38125'], ['2', 'friday , april 20', '8:00 pm', 'rhein fire', 'l 10 - 16', '0 - 2', 'amsterdam arena', '14611'], ['3', 'saturday , april 28', '6:00 pm', 'berlin thunder', 'w 14 - 10', '1 - 2', 'olympic stadium', '1... |
list of european cup and uefa champions league winning managers | https://en.wikipedia.org/wiki/List_of_European_Cup_and_UEFA_Champions_League_winning_managers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15205941-2.html.csv | comparative | bob paisley won more years of the european cup and uefa champions league than brian clough . | {'row_1': '1', 'row_2': '13', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manager', 'bob paisley'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manager record fuzzily matches to bob paisley .', 'tostr': 'filter_eq { all_rows ; manager ; bob paisley }'}, 'years won'], 'res... | greater { hop { filter_eq { all_rows ; manager ; bob paisley } ; years won } ; hop { filter_eq { all_rows ; manager ; brian clough } ; years won } } = true | select the rows whose manager record fuzzily matches to bob paisley . take the years won record of this row . select the rows whose manager record fuzzily matches to brian clough . take the years won 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, 'manager_7': 7, 'bob paisley_8': 8, 'years won_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'manager_11': 11, 'brian clough_12': 12, 'years won_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', 'manager_7': 'manager', 'bob paisley_8': 'bob paisley', 'years won_9': 'years won', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'manager_11': 'man... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'manager_7': [0], 'bob paisley_8': [0], 'years won_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'manager_11': [1], 'brian clough_12': [1], 'years won_13': [3]} | ['rank', 'manager', 'runner - up', 'years won', 'clubs won'] | [['1', 'bob paisley', '0', '1977 , 1978 , 1981', 'liverpool'], ['2', 'alex ferguson', '2', '1999 , 2008', 'manchester united'], ['2', 'miguel muñoz', '2', '1960 , 1966', 'real madrid'], ['4', 'jupp heynckes', '1', '1998 , 2013', 'real madrid , bayern munich'], ['4', 'carlo ancelotti', '1', '2003 , 2007', 'milan'], ['4'... |
stéphane sarrazin | https://en.wikipedia.org/wiki/St%C3%A9phane_Sarrazin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235636-3.html.csv | aggregation | stephane sarrazin completed a total of 3670 laps between 2001 and 2013 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '3670', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'laps'], 'result': '3670', 'ind': 0, 'tostr': 'sum { all_rows ; laps }'}, '3670'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; laps } ; 3670 } = true', 'tointer': 'the sum of the laps record of all rows is 3670 .'} | round_eq { sum { all_rows ; laps } ; 3670 } = true | the sum of the laps record of all rows is 3670 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'laps_4': 4, '3670_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '3670_5': '3670'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'laps_4': [0], '3670_5': [1]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2001', 'viper team oreca', 'yannick dalmas franck montagny', 'lmp900', '126', 'dnf', 'dnf'], ['2002', 'playstation team oreca', 'franck montagny nicolas minassian', 'lmp900', '359', '6th', '5th'], ['2003', 'pescarolo sport', 'jean - christophe boullion franck lagorce', 'lmp900', '356', '8th', '6th'], ['2005', 'aston... |
i 'm a celebrity ... get me out of here ! ( uk tv series ) | https://en.wikipedia.org/wiki/I%27m_a_Celebrity...Get_Me_Out_of_Here%21_%28UK_TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14345690-3.html.csv | count | on i 'm a celebrity ... get me out of here ! , 3 celebrities exited on day 15 . | {'scope': 'all', 'criterion': 'equal', 'value': 'day 15', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'exited', 'day 15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose exited record fuzzily matches to day 15 .', 'tostr': 'filter_eq { all_rows ; exited ; day 15 }'}], 'result': '3', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; exited ; day 15 } } ; 3 } = true | select the rows whose exited record fuzzily matches to day 15 . 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, 'exited_5': 5, 'day 15_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', 'exited_5': 'exited', 'day 15_6': 'day 15', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'exited_5': [0], 'day 15_6': [0], '3_7': [2]} | ['celebrity', 'famous for', 'entered', 'exited', 'finished'] | [['phil tufnell', 'ex - er cricket', 'day 1', 'day 15', '1st'], ['john fashanu', 'ex - footballer', 'day 1', 'day 15', '2nd'], ['linda barker', 'changing rooms designer', 'day 1', 'day 15', '3rd'], ['wayne sleep', 'r dance', 'day 1', 'day14', '4th'], ['antony worrall thompson', 'tv chef', 'day 1', 'day 13', '5th'], ['t... |
1990 los angeles raiders season | https://en.wikipedia.org/wiki/1990_Los_Angeles_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16376436-4.html.csv | count | four of the raider 's games in the 1990 season was played in november . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'november', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november .', 'tostr': 'filter_eq { all_rows ; date ; november }'}], 'result': '4', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; date ; november } } ; 4 } = true | select the rows whose date record fuzzily matches to november . 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, 'date_5': 5, 'november_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', 'date_5': 'date', 'november_6': 'november', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'november_6': [0], '4_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 9 , 1990', 'denver broncos', 'w 14 - 9', '54206'], ['2', 'september 16 , 1990', 'seattle seahawks', 'w 17 - 13', '61889'], ['3', 'september 23 , 1990', 'pittsburgh steelers', 'w 20 - 3', '50657'], ['4', 'september 30 , 1990', 'chicago bears', 'w 24 - 10', '80156'], ['5', 'october 7 , 1990', 'buffalo b... |
1981 senior pga tour | https://en.wikipedia.org/wiki/1981_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622924-1.html.csv | aggregation | the total payout for all money events during the 1981 senior pga tour was $ 166,000 . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '166,000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', '1st prize'], 'result': '166,000', 'ind': 0, 'tostr': 'sum { all_rows ; 1st prize }'}, '166,000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; 1st prize } ; 166,000 } = true', 'tointer': 'the sum of the 1st prize record of all rows i... | round_eq { sum { all_rows ; 1st prize } ; 166,000 } = true | the sum of the 1st prize record of all rows is 166,000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, '1st prize_4': 4, '166,000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', '1st prize_4': '1st prize', '166,000_5': '166,000'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], '1st prize_4': [0], '166,000_5': [1]} | ['date', 'tournament', 'location', 'purse', 'winner', 'score', '1st prize'] | [['apr 5', 'michelob - egypt temple senior classic', 'florida', '125000', 'don january ( 2 )', '280 ( - 8 )', '20000'], ['jun 7', 'eureka federal savings classic', 'california', '150000', 'don january ( 3 )', '208 ( - 5 )', '25000'], ['jun 14', 'peter jackson champions', 'canada', '200000', 'miller barber ( 1 )', '204 ... |
the good wife ( season 2 ) | https://en.wikipedia.org/wiki/The_Good_Wife_%28season_2%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28561455-1.html.csv | aggregation | season 2 of the good wife episodes written by robert king & michelle king averaged 12.47 million viewers per episode . | {'scope': 'subset', 'col': '7', 'type': 'average', 'result': '12.47', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'robert king & michelle king'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'robert king & michelle king'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; written by ; robert king & michelle king }', 'tointer': 'select the rows whose written by record fuzzily matches ... | round_eq { avg { filter_eq { all_rows ; written by ; robert king & michelle king } ; us viewers ( million ) } ; 12.47 } = true | select the rows whose written by record fuzzily matches to robert king & michelle king . the average of the us viewers ( million ) record of these rows is 12.47 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'written by_5': 5, 'robert king & michelle king_6': 6, 'us viewers (million)_7': 7, '12.47_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'written by_5': 'written by', 'robert king & michelle king_6': 'robert king & michelle king', 'us viewers (million)_7': 'us viewers ( million )', '12.47_8': '12.47'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'robert king & michelle king_6': [0], 'us viewers (million)_7': [1], '12.47_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( million )'] | [['24', '1', 'taking control', 'félix alcalá', 'robert king & michelle king', 'september 28 , 2010', '12.84'], ['25', '2', 'double jeopardy', 'dean parisot', 'ted humphrey', 'october 5 , 2010', '12.76'], ['26', '3', 'breaking fast', 'james whitmore , jr', 'corinne brinkerhoff', 'october 12 , 2010', '11.82'], ['27', '4'... |
1981 open championship | https://en.wikipedia.org/wiki/1981_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18169093-6.html.csv | majority | a majority of those in the top ten of the 1981 open championship were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'bill rogers', 'united states', '72 + 66 + 67 + 71 = 276', '- 4', '25000'], ['2', 'bernhard langer', 'west germany', '73 + 67 + 70 + 70 = 280', 'e', '17500'], ['t3', 'raymond floyd', 'united states', '74 + 70 + 69 + 70 = 283', '+ 3', '11750'], ['t3', 'mark james', 'england', '72 + 70 + 68 + 73 = 283', '+ 3', '11... |
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 | superlative | in the games played at the omni centre the highest number of points scored by any team was 124 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'the omni'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location / attendance', 'the omni'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location / attendance ; the omni }', 'tointer': 'select the rows whose location / attendance record fuzzily matches to the omni... | eq { max { filter_eq { all_rows ; location / attendance ; the omni } ; score } ; w 124 - 91 } = true | select the rows whose location / attendance record fuzzily matches to the omni . the maximum score record of these rows is w 124 - 91 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location / attendance_5': 5, 'the omni_6': 6, 'score_7': 7, 'w 124 - 91_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location / attendance_5': 'location / attendance', 'the omni_6': 'the omni', 'score_7': 'score', 'w 124 - 91_8': 'w 124 - 91'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location / attendance_5': [0], 'the omni_6': [0], 'score_7': [1], 'w 124 - 91_8': [2]} | ['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... |
wru division five south west | https://en.wikipedia.org/wiki/WRU_Division_Five_South_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17675675-1.html.csv | unique | penian rfc was the only team in the division that did n't play any games at all . | {'scope': 'all', 'row': '13', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'played', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose played record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; played ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; pl... | and { only { filter_eq { all_rows ; played ; 0 } } ; eq { hop { filter_eq { all_rows ; played ; 0 } ; club } ; penlan rfc } } = true | select the rows whose played record is equal to 0 . there is only one such row in the table . the club record of this unqiue row is penlan rfc . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'played_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'penlan rfc_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'played_7': 'played', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'penlan rfc_10': 'penlan rfc'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'played_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'penlan rfc_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'], ['birchgrove rfc', '20', '0', '3', '538', '257', '82', '29', '13', '2', '83'], ['neath athletic rfc', '20', '0', '3', '616', '194', '89', '24', '12', '2', '82'], ['trebanos rfc', '2... |
spain men 's national volleyball team | https://en.wikipedia.org/wiki/Spain_men%27s_national_volleyball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13312864-1.html.csv | superlative | josé luis moltó is the tallest player on the spain men 's national volleyball team . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'height'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; height }'}, 'player'], 'result': 'josé luis moltó', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; height } ; player }'}, 'josé luis moltó'], 'result': True,... | eq { hop { argmax { all_rows ; height } ; player } ; josé luis moltó } = true | select the row whose height record of all rows is maximum . the player record of this row is josé luis moltó . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'height_5': 5, 'player_6': 6, 'josé luis moltó_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'height_5': 'height', 'player_6': 'player', 'josé luis moltó_7': 'josé luis moltó'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'height_5': [0], 'player_6': [1], 'josé luis moltó_7': [2]} | ['shirt no', 'player', 'birth date', 'weight', 'height'] | [['1', 'rafael pascual', '16 march 1970', '94', '194'], ['2', 'ibán pérez', '13 november 1983', '89', '198'], ['3', 'josé luis lobato', '19 february 1977', '81', '186'], ['4', 'manuel sevillano', '2 july 1981', '90', '194'], ['7', 'guillermo hernán', '25 july 1982', '68', '181'], ['10', 'miguel ángel falasca', '29 apri... |
northeast delta dental international | https://en.wikipedia.org/wiki/Northeast_Delta_Dental_International | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15315276-1.html.csv | unique | 2011 is the only year that the northeast delta dental international tournament was won by a canadian . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; country ; canada }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; country ; canada } } ; eq { hop { filter_eq { all_rows ; country ; canada } ; year } ; 2011 } } = true | select the rows whose country record fuzzily matches to canada . there is only one such row in the table . the year record of this unqiue row is 2011 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'canada_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2011_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'canada_8': 'canada', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2011_10': '2011'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'canada_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2011_10': [3]} | ['year', 'dates', 'champion', 'country', 'score', 'tournament location', 'purse', "winner 's share"] | [['2013', 'jul 19 - 21', 'pk kongkraphan', 'thailand', '207 ( 9 )', 'beaver meadow golf course', '100000', '15000'], ['2012', 'jul 20 - 22', 'jenny gleason', 'united states', '211 ( 5 )', 'beaver meadow golf course', '100000', '15000'], ['2011', 'jul 22 - 24', 'jessica shepley', 'canada', '203 ( 13 )', 'beaver meadow g... |
list of england national rugby union team results 1990 - 99 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1990%E2%80%9399 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178534-1.html.csv | comparative | france scored more points than wales against the england national rugby union team . | {'row_1': '2', 'row_2': '3', 'col': '2', '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', 'opposing teams', 'france'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opposing teams record fuzzily matches to france .', 'tostr': 'filter_eq { all_rows ; opposing teams ; france }'}, 'against'], ... | greater { hop { filter_eq { all_rows ; opposing teams ; france } ; against } ; hop { filter_eq { all_rows ; opposing teams ; wales } ; against } } = true | select the rows whose opposing teams record fuzzily matches to france . take the against record of this row . select the rows whose opposing teams record fuzzily matches to wales . take the against 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, 'opposing teams_7': 7, 'france_8': 8, 'against_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opposing teams_11': 11, 'wales_12': 12, 'against_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', 'opposing teams_7': 'opposing teams', 'france_8': 'france', 'against_9': 'against', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opposing teams_11... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opposing teams_7': [0], 'france_8': [0], 'against_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opposing teams_11': [1], 'wales_12': [1], 'against_13': [3]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['ireland', '0', '20 / 01 / 1990', 'twickenham , london', 'five nations'], ['france', '7', '03 / 02 / 1990', 'parc des princes , paris', 'five nations'], ['wales', '6', '17 / 02 / 1990', 'twickenham , london', 'five nations'], ['scotland', '13', '17 / 03 / 1990', 'murrayfield , edinburgh', 'five nations'], ['argentina... |
1980 open championship | https://en.wikipedia.org/wiki/1980_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18171018-5.html.csv | superlative | in the 1980 open championship , lee trevino ranks the highest . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'place'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; place }'}, 'player'], 'result': 'lee trevino', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; place } ; player }'}, 'lee trevino'], 'result': True, 'ind': 2, ... | eq { hop { argmin { all_rows ; place } ; player } ; lee trevino } = true | select the row whose place record of all rows is minimum . the player record of this row is lee trevino . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'place_5': 5, 'player_6': 6, 'lee trevino_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'place_5': 'place', 'player_6': 'player', 'lee trevino_7': 'lee trevino'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'place_5': [0], 'player_6': [1], 'lee trevino_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'lee trevino', 'united states', '68 + 67 = 135', '- 7'], ['t2', 'ken brown', 'scotland', '70 + 68 = 138', '- 4'], ['t2', 'jerry pate', 'united states', '71 + 67 = 138', '- 4'], ['t2', 'tom watson', 'united states', '68 + 70 = 138', '- 4'], ['t5', 'seve ballesteros', 'spain', '72 + 68 = 140', '- 2'], ['t5', 'andy... |
pol espargaró | https://en.wikipedia.org/wiki/Pol_Espargar%C3%B3 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16546257-1.html.csv | comparative | pol espargaró had more podium finishes in the 2010 season than the 2011 season . | {'row_1': '5', 'row_2': '6', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2010 .', 'tostr': 'filter_eq { all_rows ; season ; 2010 }'}, 'podium'], 'result': None, 'ind': 2, 'tost... | greater { hop { filter_eq { all_rows ; season ; 2010 } ; podium } ; hop { filter_eq { all_rows ; season ; 2011 } ; podium } } = true | select the rows whose season record fuzzily matches to 2010 . take the podium record of this row . select the rows whose season record fuzzily matches to 2011 . take the podium record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'season_7': 7, '2010_8': 8, 'podium_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2011_12': 12, 'podium_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'season_7': 'season', '2010_8': '2010', 'podium_9': 'podium', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2011_12': '2011'... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2010_8': [0], 'podium_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2011_12': [1], 'podium_13': [3]} | ['season', 'race', 'podium', 'pole', 'flap'] | [['2006', '7', '0', '0', '0'], ['2007', '17', '1', '0', '0'], ['2008', '14', '3', '2', '1'], ['2009', '16', '5', '1', '1'], ['2010', '17', '12', '0', '3'], ['2011', '17', '2', '0', '1'], ['2012', '17', '11', '8', '5'], ['2013', '16', '10', '5', '4'], ['total', '121', '44', '16', '15']] |
thai clubs in the afc cup | https://en.wikipedia.org/wiki/Thai_clubs_in_the_AFC_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16707879-4.html.csv | count | 2 games of the thai clubs in the afc cup occurred in syria . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'syria', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'syria'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to syria .', 'tostr': 'filter_eq { all_rows ; venue ; syria }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; venue ; syria } } ; 2 } = true | select the rows whose venue record fuzzily matches to syria . 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, 'venue_5': 5, 'syria_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', 'venue_5': 'venue', 'syria_6': 'syria', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'syria_6': [0], '2_7': [2]} | ['season', 'team 1', 'score', 'team 2', 'venue'] | [['2010', 'south china', '0:0', 'muangthong united', 'hong kong stadium , hong kong'], ['2010', 'muangthong united', '3:1', 'vb sports club', 'yamaha stadium ( thailand )'], ['2010', 'muangthong united', '4:1', 'persiwa wamena', 'yamaha stadium ( thailand )'], ['2010', 'vb sports club', '2:3', 'muangthong united', 'nat... |
washington redskins draft history | https://en.wikipedia.org/wiki/Washington_Redskins_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-35.html.csv | unique | bob briggs was the only fb selected in the washington redskins draft . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': 'fb', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'fb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to fb .', 'tostr': 'filter_eq { all_rows ; position ; fb }'}], 'result': True, 'ind': 1, 'tostr': 'only { filte... | and { only { filter_eq { all_rows ; position ; fb } } ; eq { hop { filter_eq { all_rows ; position ; fb } ; name } ; bob briggs } } = true | select the rows whose position record fuzzily matches to fb . there is only one such row in the table . the name record of this unqiue row is bob briggs . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'fb_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'bob briggs_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', 'fb_8': 'fb', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'bob briggs_10': 'bob briggs'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'fb_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'bob briggs_10': [3]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['2', '7', '21', 'bob breitenstein', 'ot', 'tulsa'], ['3', '6', '34', 'kent mccloughan', 'cb', 'nebraska'], ['8', '7', '105', 'don croftcheck', 'g', 'indiana'], ['9', '6', '118', 'jerry smith', 'te', 'arizona state'], ['10', '7', '133', 'bob briggs', 'fb', 'central state'], ['11', '6', '146', 'willie adams', 'de', 'ne... |
united states house of representatives elections , 1998 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341453-44.html.csv | comparative | jimmy duncan jr was first elected to the united states house of representatives earlier than zach wamp . | {'row_1': '2', 'row_2': '3', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'jimmy duncan jr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to jimmy duncan jr .', 'tostr': 'filter_eq { all_rows ; incumbent ; jimmy duncan jr }'}, 'fi... | less { hop { filter_eq { all_rows ; incumbent ; jimmy duncan jr } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; zach wamp } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to jimmy duncan jr . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to zach wamp . take the first elected record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'jimmy duncan jr_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'zach wamp_12': 12, 'first elected_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'jimmy duncan jr_8': 'jimmy duncan jr', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'inc... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'jimmy duncan jr_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'zach wamp_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['tennessee 1', 'william l jenkins', 'republican', '1996', 're - elected', 'william l jenkins ( r ) 69 % kay white ( d ) 31 %'], ['tennessee 2', 'jimmy duncan jr', 'republican', '1988', 're - elected', 'jimmy duncan jr ( r ) unopposed'], ['tennessee 3', 'zach wamp', 'republican', '1994', 're - elected', 'zach wamp ( r... |
roy scheider | https://en.wikipedia.org/wiki/Roy_Scheider | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-164370-1.html.csv | aggregation | roy scheider 's matches in 1948 lasted a total of 4 rounds . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '4', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '1948'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '1948'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 1948 }', 'tointer': 'select the rows whose date record fuzzily matches to 1948 .'}, 'round'], 'result': '4', 'ind': 1, 'tostr': 'sum { ... | round_eq { sum { filter_eq { all_rows ; date ; 1948 } ; round } ; 4 } = true | select the rows whose date record fuzzily matches to 1948 . the sum of the round record of these rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '1948_6': 6, 'round_7': 7, '4_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '1948_6': '1948', 'round_7': 'round', '4_8': '4'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '1948_6': [0], 'round_7': [1], '4_8': [2]} | ['result', 'opponent', 'method', 'date', 'round'] | [['win', 'ted lascalza', 'ko', '1958', '1'], ['win', 'nick welling', 'ko', 'july 20 , 1953', '2'], ['win', 'earl garrett', 'ko', '1950', '1'], ['win', 'peter read', 'ko', '1950', '3'], ['win', 'phillip duncan', 'ko', 'february 17 , 1950', '1'], ['win', 'myron greenberg', 'ko', '1950', '1'], ['win', 'peter read', 'ko', ... |
1992 open championship | https://en.wikipedia.org/wiki/1992_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18122130-4.html.csv | majority | the majority of players came from the united states in the 1992 open championship . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'raymond floyd', 'united states', '64', '- 7'], ['t1', 'steve pate', 'united states', '64', '- 7'], ['t3', 'gordon brand , jnr', 'scotland', '65', '- 6'], ['t3', 'ian woosnam', 'wales', '65', '- 6'], ['t5', 'john cook', 'united states', '66', '- 5'], ['t5', 'ernie els', 'south africa', '66', '- 5'], ['t5', 'nic... |
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 | unique | only the soviet union won three silver medals . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '3', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'silver', '3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose silver record is equal to 3 .', 'tostr': 'filter_eq { all_rows ; silver ; 3 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; si... | and { only { filter_eq { all_rows ; silver ; 3 } } ; eq { hop { filter_eq { all_rows ; silver ; 3 } ; nation } ; soviet union } } = true | select the rows whose silver record is equal to 3 . there is only one such row in the table . the nation record of this unqiue row is soviet union . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'silver_7': 7, '3_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'soviet union_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'silver_7': 'silver', '3_8': '3', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'soviet union_10': 'soviet union'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'silver_7': [0], '3_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'soviet union_10': [3]} | ['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', 't... |
wtbs - ld | https://en.wikipedia.org/wiki/WTBS-LD | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1097268-1.html.csv | majority | the majority of the channels have video in 480i . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '480i', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'video', '480i'], 'result': True, 'ind': 0, 'tointer': 'for the video records of all rows , most of them fuzzily match to 480i .', 'tostr': 'most_eq { all_rows ; video ; 480i } = true'} | most_eq { all_rows ; video ; 480i } = true | for the video records of all rows , most of them fuzzily match to 480i . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'video_3': 3, '480i_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'video_3': 'video', '480i_4': '480i'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'video_3': [0], '480i_4': [0]} | ['channel', 'video', 'aspect', 'psip short name', 'programming'] | [['26.1', '1080i', '16:9', 'mfox', 'mundofox'], ['26.2', '480i', '4:3', 'lwn', 'live well network'], ['26.4', '480i', '4:3', 'jtv', 'jewelry tv'], ['26.5', '480i', '4:3', 'f24news', 'france 24 blank screen'], ['26.8', '480i', '4:3', 'tuff tv', 'tuff tv']] |
the general in his labyrinth | https://en.wikipedia.org/wiki/The_General_in_His_Labyrinth | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1162324-1.html.csv | majority | most of the books in the series have less that 300 pages all together . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than_eq', 'value': '300', 'subset': None} | {'func': 'most_less_eq', 'args': ['all_rows', 'pages', '300'], 'result': True, 'ind': 0, 'tointer': 'for the pages records of all rows , most of them are less than or equal to 300 .', 'tostr': 'most_less_eq { all_rows ; pages ; 300 } = true'} | most_less_eq { all_rows ; pages ; 300 } = true | for the pages records of all rows , most of them are less than or equal to 300 . | 1 | 1 | {'most_less_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'pages_3': 3, '300_4': 4} | {'most_less_eq_0': 'most_less_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'pages_3': 'pages', '300_4': '300'} | {'most_less_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'pages_3': [0], '300_4': [0]} | ['year', 'language', 'title', 'translator', 'company', 'pages'] | [['1989', 'arabic', 'al - jiniral fi matahatihi', 'salih ilmani', 'nicosia : ibal', '287'], ['1989', 'german', 'der general in seinem labyrinth : roman', 'dagmar ploetz', 'cologne : kiepenheuer & witsch', '359'], ['1989', 'swedish', 'generalen i sin labyrint', 'jens nordenhök', 'stockholm : wahlström & widstrand', '267... |
2005 masters tournament | https://en.wikipedia.org/wiki/2005_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16147528-2.html.csv | majority | the majority of players in the 2005 masters tournament are from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['tiger woods', 'united states', '1997 , 2001 , 2002', '276', '- 12', '1'], ['vijay singh', 'fiji', '2000', '284', '- 4', 't5'], ['mike weir', 'canada', '2003', '284', '- 4', 't5'], ['phil mickelson', 'united states', '2004', '285', '- 3', '10'], ['bernhard langer', 'germany', '1985 , 1993', '289', '+ 1', 't20'], ["ma... |
driver deaths in motorsport | https://en.wikipedia.org/wiki/Driver_deaths_in_motorsport | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1632486-11.html.csv | count | two of the motorsport driver deaths were in qualifying sessions . | {'scope': 'all', 'criterion': 'equal', 'value': 'qualifying', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'session', 'qualifying'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose session record fuzzily matches to qualifying .', 'tostr': 'filter_eq { all_rows ; session ; qualifying }'}], 'result': '2', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; session ; qualifying } } ; 2 } = true | select the rows whose session record fuzzily matches to qualifying . 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, 'session_5': 5, 'qualifying_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', 'session_5': 'session', 'qualifying_6': 'qualifying', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'session_5': [0], 'qualifying_6': [0], '2_7': [2]} | ['discipline', 'championship', 'circuit', 'event', 'session'] | [['stock car', 'sprint cup series', 'daytona international speedway', 'uno twin 125 qualifiers', 'qualifying'], ['stock car', 'whelen modified tour', 'martinsville speedway', 'winn - dixie 500', 'race'], ['drag racing', 'nhra winston drag racing series', 'indianapolis raceway park', 'mac tools us nationals', 'qualifyin... |
united states house of representatives elections , 1936 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1936 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342315-4.html.csv | ordinal | william j driver is the incumbent of the 1936 house of representatives elections with the earliest first elected year . | {'row': '1', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'william j driver', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 }... | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; william j driver } = true | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is william j driver . | 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, '1_6': 6, 'incumbent_7': 7, 'william j driver_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', '1_6': '1', 'incumbent_7': 'incumbent', 'william j driver_8': 'william j driver'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'william j driver_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'william j driver', 'democratic', '1920', 're - elected', 'william j driver ( d ) unopposed'], ['arkansas 2', 'john e miller', 'democratic', '1930', 're - elected', 'john e miller ( d ) unopposed'], ['arkansas 3', 'claude fuller', 'democratic', '1928', 're - elected', 'claude fuller ( d ) unopposed'], [... |
united states house of representatives elections , 1812 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1812 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668367-14.html.csv | count | 4 incumbents were re - elected during the 1812 house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're-elected', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re-elected .', 'tostr': 'filter_eq { all_rows ; result ; re-elected }'}], 'result': '4', 'ind': 1, 'tost... | eq { count { filter_eq { all_rows ; result ; re-elected } } ; 4 } = true | select the rows whose result record fuzzily matches to re-elected . 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, 're-elected_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', 're-elected_6': 're-elected', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're-elected_6': [0], '4_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'willis alston', 'democratic - republican', '1798', 're - elected', 'willis alston ( dr ) 56.0 % daniel mason ( f ) 44.0 %'], ['north carolina 5', 'william r king', 'democratic - republican', '1810', 're - elected', 'william r king ( dr ) 100 %'], ['north carolina 6', 'nathaniel macon', 'democrati... |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-46.html.csv | count | 7 incumbents were re - elected during the 2000 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '7', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'results', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose results record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; results ; re - elected }'}], 'result': '7', 'ind':... | eq { count { filter_eq { all_rows ; results ; re - elected } } ; 7 } = true | select the rows whose results record fuzzily matches to re - elected . 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, 'results_5': 5, 're - elected_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', 'results_5': 'results', 're - elected_6': 're - elected', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'results_5': [0], 're - elected_6': [0], '7_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['virginia 2', 'owen b pickett', 'democratic', '1986', 'retired republican gain', 'ed schrock ( r ) 52 % jody wagner ( d ) 48 %'], ['virginia 3', 'bobby scott', 'democratic', '1992', 're - elected', 'bobby scott ( d ) unopposed'], ['virginia 4', 'norman sisisky', 'democratic', '1982', 're - elected', 'norman sisisky (... |
transouth athletic conference | https://en.wikipedia.org/wiki/TranSouth_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1715730-2.html.csv | superlative | the highest enrollment of any of the schools in the transouth athletic conference is at the school based in cleveland , tennessee . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'location'], 'result': 'cleveland , tennessee', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; location }'}, 'cleveland , ... | eq { hop { argmax { all_rows ; enrollment } ; location } ; cleveland , tennessee } = true | select the row whose enrollment record of all rows is maximum . the location record of this row is cleveland , tennessee . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'location_6': 6, 'cleveland , tennessee_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'location_6': 'location', 'cleveland , tennessee_7': 'cleveland , tennessee'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'location_6': [1], 'cleveland , tennessee_7': [2]} | ['location', 'founded', 'type', 'enrollment', 'nickname', 'joined', 'left', 'current conference'] | [['mount berry , georgia', '1902', 'private', '1937', 'vikings', '1996', '2004', 'saa ( ncaa division iii )'], ['birmingham , alabama', '1856', 'private', '1400', 'panthers', '1996', '2001', 'saa ( ncaa division iii )'], ['nashville , tennessee', '1891', 'private', '4278', 'bisons', '1996', '2001', 'atlantic sun ( a - ... |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17596418-4.html.csv | ordinal | of the free transfers cardiff city brought in for the 2008-09 season , the second oldest was 31 years of age . | {'scope': 'subset', 'row': '3', 'col': '6', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'free transfer'}} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'free transfer'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; free transfer }', 'tointer': 'select the rows whose type record fuzzily matches to free transfer .'}, 'age', '2'], 'result': '31... | eq { nth_max { filter_eq { all_rows ; type ; free transfer } ; age ; 2 } ; 31 } = true | select the rows whose type record fuzzily matches to free transfer . the 2nd maximum age record of these rows is 31 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'type_5': 5, 'free transfer_6': 6, 'age_7': 7, '2_8': 8, '31_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_max_1': 'nth_max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'type_5': 'type', 'free transfer_6': 'free transfer', 'age_7': 'age', '2_8': '2', '31_9': '31'} | {'eq_2': [3], 'result_3': [], 'nth_max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'type_5': [0], 'free transfer_6': [0], 'age_7': [1], '2_8': [1], '31_9': [2]} | ['n', 'p', 'name', 'eu', 'country', 'age', 'type', 'moving from', 'transfer window', 'ends', 'transfer fee', 'source'] | [['15', 'df', 'comminges', 'eu', 'gpe', '26', 'free transfer', 'swindon town', 'summer', '2010', 'free', 'bbc sport'], ['21', 'mf', 'kennedy', 'eu', 'irl', '32', 'free transfer', 'crystal palace', 'summer', '2010', 'free', 'bbc sport'], ['1', 'gk', 'enckelman', 'eu', 'fin', '31', 'free transfer', 'blackburn rovers', 's... |
euro convergence criteria | https://en.wikipedia.org/wiki/Euro_convergence_criteria | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1884378-1.html.csv | aggregation | the average central rate for the currencies listed for euro convergence is 3.393 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '3.393', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'central rate'], 'result': '3.393', 'ind': 0, 'tostr': 'avg { all_rows ; central rate }'}, '3.393'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; central rate } ; 3.393 } = true', 'tointer': 'the average of the central rate record of ... | round_eq { avg { all_rows ; central rate } ; 3.393 } = true | the average of the central rate record of all rows is 3.393 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'central rate_4': 4, '3.393_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'central rate_4': 'central rate', '3.393_5': '3.393'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'central rate_4': [0], '3.393_5': [1]} | ['currency', 'code', 'entry erm ii', 'central rate', 'official target date'] | [['bulgarian lev', 'bgn', '-', '1.95583', '-'], ['croatian kuna', 'hrk', '-', '-', '-'], ['czech koruna', 'czk', '-', '-', '-'], ['danish krone', 'dkk', '1 january 1999', '7.46038', 'formal opt - out'], ['hungarian forint', 'huf', '-', '-', '-'], ['latvian lats', 'lvl', '2 may 2005', '0.702804', '1 january 2014'], ['li... |
kumar sanu | https://en.wikipedia.org/wiki/Kumar_Sanu | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1368369-1.html.csv | count | the lyricist for three of kumar sanu 's songs was sameer . | {'scope': 'all', 'criterion': 'equal', 'value': 'sameer', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'lyricist', 'sameer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lyricist record fuzzily matches to sameer .', 'tostr': 'filter_eq { all_rows ; lyricist ; sameer }'}], 'result': '3', 'ind': 1, 'tostr': 'c... | eq { count { filter_eq { all_rows ; lyricist ; sameer } } ; 3 } = true | select the rows whose lyricist record fuzzily matches to sameer . 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, 'lyricist_5': 5, 'sameer_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', 'lyricist_5': 'lyricist', 'sameer_6': 'sameer', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'lyricist_5': [0], 'sameer_6': [0], '3_7': [2]} | ['year', 'song', 'film', 'music director ( s )', 'lyricist'] | [['1991', 'ab tere bin', 'aashiqui', 'nadeem - shravan', 'sameer'], ['1992', 'mera dil bhi kitna pagal hai', 'saajan', 'nadeem - shravan', 'sameer'], ['1993', 'sochenge tumhe pyaar', 'deewana', 'nadeem - shravan', 'sameer'], ['1994', 'yeh kaali kaali aankhen', 'baazigar', 'anu malik', 'rani malik'], ['1995', 'ek ladki ... |
win ( tv station ) | https://en.wikipedia.org/wiki/WIN_%28TV_station%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13596926-1.html.csv | comparative | channel 59 was on air before channel 32 was on the air . | {'row_1': '4', 'row_2': '5', 'col': '3', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ch 1', '59 ( uhf )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ch 1 record fuzzily matches to 59 ( uhf ) .', 'tostr': 'filter_eq { all_rows ; ch 1 ; 59 ( uhf ) }'}, 'on - air date'], 'result': None,... | less { hop { filter_eq { all_rows ; ch 1 ; 59 ( uhf ) } ; on - air date } ; hop { filter_eq { all_rows ; ch 1 ; 32 ( uhf ) } ; on - air date } } = true | select the rows whose ch 1 record fuzzily matches to 59 ( uhf ) . take the on - air date record of this row . select the rows whose ch 1 record fuzzily matches to 32 ( uhf ) . take the on - air date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'ch 1_7': 7, '59 ( uhf )_8': 8, 'on - air date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'ch 1_11': 11, '32 ( uhf )_12': 12, 'on - air date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'ch 1_7': 'ch 1', '59 ( uhf )_8': '59 ( uhf )', 'on - air date_9': 'on - air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'ch 1_11': 'ch 1', '32 (... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'ch 1_7': [0], '59 ( uhf )_8': [0], 'on - air date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'ch 1_11': [1], '32 ( uhf )_12': [1], 'on - air date_13': [3]} | ['region served', 'ch 1', 'on - air date', 'analogue power', 'digital power', 'analogue haat', 'digital haat', 'transmitter location'] | [['canberra', '31 ( uhf )', '31 march 1989', '600 kw', '50 kw', '362 m', '362 m', 'black mountain'], ['central tablelands', '39 ( uhf )', '30 december 1989', '2000 kw', '570 kw', '627 m', '628 m', 'mount canobolas'], ['central western slopes', '32 ( uhf )', '30 december 1989', '1000 kw', '600 kw', '648 m', '653 m', 'mo... |
list of former and unopened london underground stations | https://en.wikipedia.org/wiki/List_of_former_and_unopened_London_Underground_stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-211615-2.html.csv | comparative | turnham green station was cancelled earlier than the crouch end station . | {'row_1': '14', 'row_2': '5', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'station', 'turnham green'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose station record fuzzily matches to turnham green .', 'tostr': 'filter_eq { all_rows ; station ; turnham green }'}, 'cancelled'], '... | less { hop { filter_eq { all_rows ; station ; turnham green } ; cancelled } ; hop { filter_eq { all_rows ; station ; crouch end } ; cancelled } } = true | select the rows whose station record fuzzily matches to turnham green . take the cancelled record of this row . select the rows whose station record fuzzily matches to crouch end . take the cancelled record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'station_7': 7, 'turnham green_8': 8, 'cancelled_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'station_11': 11, 'crouch end_12': 12, 'cancelled_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'station_7': 'station', 'turnham green_8': 'turnham green', 'cancelled_9': 'cancelled', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'station_11': 'stati... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'station_7': [0], 'turnham green_8': [0], 'cancelled_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'station_11': [1], 'crouch end_12': [1], 'cancelled_13': [3]} | ['station', 'line', 'planned', 'cancelled', 'proposal', 'details'] | [['alexandra palace', 'northern', '1935', '1954', 'transfer from lner', 'abandoned part of northern heights project'], ['bushey heath', 'northern', '1936', '1949', 'new station on new route', 'abandoned part of northern heights project'], ['camberwell', 'bakerloo', '1931', '1950', 'new station on new route', 'part of a... |
black swan - class sloop | https://en.wikipedia.org/wiki/Black_Swan-class_sloop | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1220125-2.html.csv | ordinal | in black swan - class sloop , sutlej was the earliest to be laid down among those build by denny , dunbarton . | {'scope': 'subset', 'row': '1', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'denny , dunbarton'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'denny , dunbarton'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; builder ; denny , dunbarton }', 'tointer': 'select the rows whose builder record fuzzily mat... | eq { hop { nth_argmin { filter_eq { all_rows ; builder ; denny , dunbarton } ; laid down ; 1 } ; name } ; sutlej } = true | select the rows whose builder record fuzzily matches to denny , dunbarton . select the row whose laid down record of these rows is 1st minimum . the name record of this row is sutlej . | 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, 'builder_6': 6, 'denny , dunbarton_7': 7, 'laid down_8': 8, '1_9': 9, 'name_10': 10, 'sutlej_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', 'builder_6': 'builder', 'denny , dunbarton_7': 'denny , dunbarton', 'laid down_8': 'laid down', '1_9': '1', 'name_10': 'name', 'sutlej_11': 'sutlej'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'builder_6': [0], 'denny , dunbarton_7': [0], 'laid down_8': [1], '1_9': [1], 'name_10': [2], 'sutlej_11': [3]} | ['name', 'pennant', 'builder', 'laid down', 'launched', 'commissioned'] | [['sutlej', 'u95', 'denny , dunbarton', '4 january 1940', '1 october 1940', '23 april 1941'], ['jumna', 'u21', 'denny , dunbarton', '28 february 1940', '16 november 1940', '13 may 1941'], ['narbada', 'u40', 'thornycroft , woolston', '30 august 1941', '21 november 1942', '29 april 1943'], ['godavari', 'u52', 'thornycrof... |
peter fleming ( tennis ) | https://en.wikipedia.org/wiki/Peter_Fleming_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1834797-2.html.csv | count | four of peter fleming 's tennis championship finals were played on a hard surface . | {'scope': 'all', 'criterion': 'equal', 'value': 'hard', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard .', 'tostr': 'filter_eq { all_rows ; surface ; hard }'}], 'result': '4', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; surface ; hard } } ; 4 } = true | select the rows whose surface record fuzzily matches to hard . 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, 'surface_5': 5, 'hard_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', 'surface_5': 'surface', 'hard_6': 'hard', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'hard_6': [0], '4_7': [2]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '1978', 'maui , us', 'hard', 'bill scanlon', '2 - 6 , 0 - 6'], ['winner', '1978', 'bologna , italy', 'carpet', 'adriano panatta', '6 - 2 , 7 - 6'], ['runner - up', '1978', 'montego bay , jamaica', 'hard', 'ilie năstase', '6 - 2 , 6 - 5 , 2 - 6 , 4 - 6 , 4 - 6'], ['runner - up', '1979', 'san jose , us',... |
kaspars stupelis | https://en.wikipedia.org/wiki/Kaspars_Stupelis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16775140-1.html.csv | unique | kaspars stupelis only had 18 wins once , when the driver was daniel willemsen . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '18', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '18'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 18 .', 'tostr': 'filter_eq { all_rows ; wins ; 18 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; wins ... | and { only { filter_eq { all_rows ; wins ; 18 } } ; eq { hop { filter_eq { all_rows ; wins ; 18 } ; driver } ; daniël willemsen } } = true | select the rows whose wins record is equal to 18 . there is only one such row in the table . the driver record of this unqiue row is daniël willemsen . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'wins_7': 7, '18_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'daniël willemsen_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'wins_7': 'wins', '18_8': '18', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'daniël willemsen_10': 'daniël willemsen'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'wins_7': [0], '18_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'daniël willemsen_10': [3]} | ['driver', 'points', 'races', 'wins', 'second', 'third'] | [['modris stelle', '14', '10', '-', '-', '-'], ['modris stelle', '69', '12', '-', '-', '-'], ['daniël willemsen', '561', '24', '13', '9', '-'], ['daniël willemsen', '572', '26', '18', '4', '1'], ['kristers serģis', '440', '22', '7', '12', '-'], ['kristers serģis', '64', '4', '-', '2', '1'], ['kristers serģis', '242', '... |
2010 - 11 uefa champions league | https://en.wikipedia.org/wiki/2010%E2%80%9311_UEFA_Champions_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18255941-28.html.csv | count | a total of two games in the 2010 - 11 uefa champions league 1st leg ended with a 1-1 score . | {'scope': 'all', 'criterion': 'equal', 'value': '1 - 1', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st leg', '1 - 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 1 .', 'tostr': 'filter_eq { all_rows ; 1st leg ; 1 - 1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; 1st leg ; 1 - 1 } } ; 2 } = true | select the rows whose 1st leg 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, '1st leg_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', '1st leg_5': '1st leg', '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], '1st leg_5': [0], '1 - 1_6': [0], '2_7': [2]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['roma', '2 - 6', 'shakhtar donetsk', '2 - 3', '0 - 3'], ['milan', '0 - 1', 'tottenham hotspur', '0 - 1', '0 - 0'], ['valencia', '2 - 4', 'schalke 04', '1 - 1', '1 - 3'], ['internazionale', '( a ) 3 - 3', 'bayern munich', '0 - 1', '3 - 2'], ['lyon', '1 - 4', 'real madrid', '1 - 1', '0 - 3'], ['arsenal', '3 - 4', 'barc... |
2008 afl season | https://en.wikipedia.org/wiki/2008_AFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14312471-4.html.csv | ordinal | st kilda 's away team game recorded the highest crowd participation in the 2008 afl season . | {'row': '4', 'col': '6', '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', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'away team'], 'result': 'st kilda', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; away team }'}, 'st kilda'], '... | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; away team } ; st kilda } = true | select the row whose crowd record of all rows is 1st maximum . the away team record of this row is st kilda . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'away team_7': 7, 'st kilda_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', 'crowd_5': 'crowd', '1_6': '1', 'away team_7': 'away team', 'st kilda_8': 'st kilda'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'away team_7': [1], 'st kilda_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'report'] | [['melbourne', '5.11 ( 41 )', 'geelong', '24.13 ( 157 )', 'mcg', '34610', 'friday , 8 august', 'aflcomau'], ['carlton', '18.24 ( 132 )', 'port adelaide', '9.12 ( 66 )', 'telstra dome', '29696', 'saturday , 9 august', 'aflcomau'], ['hawthorn', '16.14 ( 110 )', 'brisbane lions', '5.11 ( 41 )', 'aurora stadium', '19929', ... |
list of covert affairs episodes | https://en.wikipedia.org/wiki/List_of_Covert_Affairs_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25740548-3.html.csv | count | according to the list of covert affairs episodes , among the episodes directed by stephen kay , two of them were written by norman morrill . | {'scope': 'subset', 'criterion': 'equal', 'value': 'norman morrill', 'result': '2', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'stephen kay'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'stephen kay'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; directed by ; stephen kay }', 'tointer': 'select the rows whose directed by record fuzzily matche... | eq { count { filter_eq { filter_eq { all_rows ; directed by ; stephen kay } ; written by ; norman morrill } } ; 2 } = true | select the rows whose directed by record fuzzily matches to stephen kay . among these rows , select the rows whose written by record fuzzily matches to norman morrill . 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, 'directed by_6': 6, 'stephen kay_7': 7, 'written by_8': 8, 'norman morrill_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', 'directed by_6': 'directed by', 'stephen kay_7': 'stephen kay', 'written by_8': 'written by', 'norman morrill_9': 'norman morrill', '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], 'directed by_6': [0], 'stephen kay_7': [0], 'written by_8': [1], 'norman morrill_9': [1], '2_10': [3]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['12', '1', 'begin the begin', 'kate woods', 'matt corman & chris ord', 'june 7 , 2011', 'ca201', '4.56'], ['13', '2', 'good advices', 'ken girotti', 'stephen hootstein', 'june 14 , 2011', 'ca202', '3.92'], ['14', '3', 'bang and blame', 'allan kroeker', 'erica shelton', 'june 21 , 2011', 'ca203', '4.03'], ['15', '4', ... |
nick price | https://en.wikipedia.org/wiki/Nick_Price | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1132021-7.html.csv | aggregation | nick price had an average of around 5-6 top-10 finishes across the major pga tournaments . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '5-6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'top - 10'], 'result': '5-6', 'ind': 0, 'tostr': 'avg { all_rows ; top - 10 }'}, '5-6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; top - 10 } ; 5-6 } = true', 'tointer': 'the average of the top - 10 record of all rows is 5-6 .'} | round_eq { avg { all_rows ; top - 10 } ; 5-6 } = true | the average of the top - 10 record of all rows is 5-6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'top - 10_4': 4, '5-6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'top - 10_4': 'top - 10', '5-6_5': '5-6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'top - 10_4': [0], '5-6_5': [1]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '4', '11', '20', '13'], ['us open', '0', '3', '5', '12', '20', '15'], ['the open championship', '1', '3', '5', '8', '27', '20'], ['pga championship', '2', '5', '7', '10', '20', '16'], ['totals', '3', '12', '21', '41', '87', '64']] |
list of nurse jackie episodes | https://en.wikipedia.org/wiki/List_of_Nurse_Jackie_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26961951-4.html.csv | ordinal | game on is the title of the nurse jackie drama episode with the earliest original air date . | {'row': '1', 'col': '6', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'original air date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; original air date ; 1 }'}, 'title'], 'result': 'game on', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; original air date ; 1 } ... | eq { hop { nth_argmin { all_rows ; original air date ; 1 } ; title } ; game on } = true | select the row whose original air date record of all rows is 1st minimum . the title record of this row is game on . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '1_6': 6, 'title_7': 7, 'game on_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', 'original air date_5': 'original air date', '1_6': '1', 'title_7': 'title', 'game on_8': 'game on'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '1_6': [0], 'title_7': [1], 'game on_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( million )'] | [['25', '1', 'game on', 'steve buscemi', 'liz brixius & linda wallem', 'march 28 , 2011', '0.61'], ['26', '2', 'enough rope', 'steve buscemi', 'liz brixius', 'april 4 , 2011', '0.49'], ['27', '3', 'play me', 'michael lehmann', 'linda wallem', 'april 11 , 2011', '0.57'], ['28', '4', 'mitten', 'michael lehmann', 'liz fla... |
list of tallest buildings in germany | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Germany | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11328656-3.html.csv | ordinal | the second tallest building in germany is the messeturm in frankfurt . | {'row': '2', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'height ( m )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; height ( m ) ; 2 }'}, 'name'], 'result': 'messeturm', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; height ( m ) ; 2 } ; name }'}, 'm... | eq { hop { nth_argmax { all_rows ; height ( m ) ; 2 } ; name } ; messeturm } = true | select the row whose height ( m ) record of all rows is 2nd maximum . the name record of this row is messeturm . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'height (m)_5': 5, '2_6': 6, 'name_7': 7, 'messeturm_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', 'height (m)_5': 'height ( m )', '2_6': '2', 'name_7': 'name', 'messeturm_8': 'messeturm'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'height (m)_5': [0], '2_6': [0], 'name_7': [1], 'messeturm_8': [2]} | ['name', 'city', 'height ( m )', 'height ( ft )', 'floors', 'years as tallest'] | [['commerzbank tower', 'frankfurt', '259', '850', '56', '1997 - present'], ['messeturm', 'frankfurt', '257', '843', '55', '1990 - 1997'], ['silberturm', 'frankfurt', '166', '545', '32', '1978 - 1990'], ['westend gate', 'frankfurt', '159', '522', '47', '1976 - 1978'], ['colonia - hochhaus', 'cologne', '147', '482', '42'... |
1970 baltimore colts season | https://en.wikipedia.org/wiki/1970_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14966537-1.html.csv | comparative | the 1970 baltimore colts scored more points against the philadelphia eagles than against the chicago bears . | {'row_1': '12', 'row_2': '11', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'philadelphia eagles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to philadelphia eagles .', 'tostr': 'filter_eq { all_rows ; opponent ; philadelphia eag... | greater { hop { filter_eq { all_rows ; opponent ; philadelphia eagles } ; result } ; hop { filter_eq { all_rows ; opponent ; chicago bears } ; result } } = true | select the rows whose opponent record fuzzily matches to philadelphia eagles . take the result record of this row . select the rows whose opponent record fuzzily matches to chicago bears . take the result record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'philadelphia eagles_8': 8, 'result_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'chicago bears_12': 12, 'result_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'philadelphia eagles_8': 'philadelphia eagles', 'result_9': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'oppon... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'philadelphia eagles_8': [0], 'result_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'chicago bears_12': [1], 'result_13': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 20 , 1970', 'san diego chargers', 'w 16 - 14', '1 - 0', 'san diego stadium', '47782'], ['2', 'september 28 , 1970', 'kansas city chiefs', 'l 24 - 44', '1 - 1', 'memorial stadium', '53911'], ['3', 'october 4 , 1970', 'boston patriots', 'w 14 - 6', '2 - 1', 'harvard stadium', '38235'], ['4', 'october 11... |
günter netzer | https://en.wikipedia.org/wiki/G%C3%BCnter_Netzer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1085623-1.html.csv | majority | the majority of günter netzer 's international goals were in friendly competitions . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friendly', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to friendly .', 'tostr': 'most_eq { all_rows ; competition ; friendly } = true'} | most_eq { all_rows ; competition ; friendly } = true | for the competition records of all rows , most of them fuzzily match to friendly . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['22 november 1970', 'athens , greece', '1 - 0', '3 - 1', 'friendly'], ['12 june 1971', 'karlsruhe , germany', '1 - 0', '2 - 0', 'uefa euro 1972 qualifying'], ['22 june 1971', 'oslo , norway', '7 - 0', '7 - 1', 'friendly'], ['8 september 1971', 'hanover , germany', '4 - 0', '5 - 0', 'friendly'], ['29 april 1972', 'lon... |
andrei pavel | https://en.wikipedia.org/wiki/Andrei_Pavel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1723598-5.html.csv | unique | the february 14 , 1999 game was the only one to be played on a carpet surface . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'carpet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; date } ; february 14 , 1999 } } = true | select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the date record of this unqiue row is february 14 , 1999 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'february 14 , 1999_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'carpet_8': 'carpet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'february 14 , 1999_10': 'february 14 , 1999'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'february 14 , 1999_10': [3]} | ['date', 'tournament', 'surface', 'partnering', 'opponents in final', 'score in final'] | [['february 14 , 1999', 'st petersburg , russia', 'carpet', 'menno oosting', 'jeff tarango daniel vacek', '3 - 6 , 6 - 3 , 7 - 5'], ['january 10 , 2005', 'doha , qatar', 'hard', 'mikhail youzhny', 'albert costa rafael nadal', '6 - 3 , 4 - 6 , 6 - 3'], ['september 18 , 2005', 'bucharest , romania', 'clay', 'victor hănes... |
grid energy storage | https://en.wikipedia.org/wiki/Grid_energy_storage | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1646838-1.html.csv | unique | the flow grid energy storage technology is the only type of technology with moving parts . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'moving parts', 'yes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose moving parts record fuzzily matches to yes .', 'tostr': 'filter_eq { all_rows ; moving parts ; yes }'}], 'result': True, 'ind': 1, 'tostr'... | and { only { filter_eq { all_rows ; moving parts ; yes } } ; eq { hop { filter_eq { all_rows ; moving parts ; yes } ; technology } ; flow } } = true | select the rows whose moving parts record fuzzily matches to yes . there is only one such row in the table . the technology record of this unqiue row is flow . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'moving parts_7': 7, 'yes_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'technology_9': 9, 'flow_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'moving parts_7': 'moving parts', 'yes_8': 'yes', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'technology_9': 'technology', 'flow_10': 'flow'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'moving parts_7': [0], 'yes_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'technology_9': [2], 'flow_10': [3]} | ['technology', 'moving parts', 'room temperature', 'flammable', 'toxic materials', 'in production', 'rare metals'] | [['flow', 'yes', 'yes', 'no', 'yes', 'no', 'no'], ['liquid metal', 'no', 'no', 'yes', 'no', 'no', 'no'], ['sodium - ion', 'no', 'no', 'yes', 'no', 'no', 'no'], ['lead - acid', 'no', 'yes', 'no', 'yes', 'yes', 'no'], ['sodium - sulfur batteries', 'no', 'no', 'no', 'yes', 'yes', 'no'], ['ni - cd', 'no', 'yes', 'no', 'yes... |
television in thailand | https://en.wikipedia.org/wiki/Television_in_Thailand | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18987481-2.html.csv | count | two of the channels in thai television are owned by the royal thai army . | {'scope': 'all', 'criterion': 'equal', 'value': 'royal thai army', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'owner', 'royal thai army'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owner record fuzzily matches to royal thai army .', 'tostr': 'filter_eq { all_rows ; owner ; royal thai army }'}], 'result': '2', 'in... | eq { count { filter_eq { all_rows ; owner ; royal thai army } } ; 2 } = true | select the rows whose owner record fuzzily matches to royal thai army . 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, 'owner_5': 5, 'royal thai army_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', 'owner_5': 'owner', 'royal thai army_6': 'royal thai army', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'owner_5': [0], 'royal thai army_6': [0], '2_7': [2]} | ['name', 'network', 'owner', 'launch date', 'channel ( bkk )', 'broadcasting area', 'transmitted area', 'broadcasting hours'] | [['channel 3', 'mcot and bangkok entertainment co , ltd', 'bec - tero', '26 march 1970', '3 / 32 ( vhf / uhf )', 'rama iv road', 'bangkok', '24 - hours'], ['rta tv - 5', 'royal thai army radio and television', 'royal thai army', '25 january 1958', '5 ( vhf )', 'sanam pao', 'bangkok', '24 - hours'], ['bbtv channel 7', '... |
list of sequenced bacterial genomes | https://en.wikipedia.org/wiki/List_of_sequenced_bacterial_genomes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11664498-16.html.csv | comparative | borella garinii has a lower amount of genes than treponema denticola . | {'row_1': '2', 'row_2': '7', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'species', 'borrelia garinii'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose species record fuzzily matches to borrelia garinii .', 'tostr': 'filter_eq { all_rows ; species ; borrelia garinii }'}, 'genes... | less { hop { filter_eq { all_rows ; species ; borrelia garinii } ; genes } ; hop { filter_eq { all_rows ; species ; treponema denticola } ; genes } } = true | select the rows whose species record fuzzily matches to borrelia garinii . take the genes record of this row . select the rows whose species record fuzzily matches to treponema denticola . take the genes record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'species_7': 7, 'borrelia garinii_8': 8, 'genes_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'species_11': 11, 'treponema denticola_12': 12, 'genes_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'species_7': 'species', 'borrelia garinii_8': 'borrelia garinii', 'genes_9': 'genes', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'species_11': 'species... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'species_7': [0], 'borrelia garinii_8': [0], 'genes_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'species_11': [1], 'treponema denticola_12': [1], 'genes_13': [3]} | ['species', 'strain', 'type', 'base pairs', 'genes'] | [['borrelia burgdorferi', 'b31', 'spirochaetes', '910724', '850'], ['borrelia garinii', 'pbi', 'spirochaetes', '904246', '832'], ['leptospira interrogans', '56601', 'spirochaetes', '4332241', '4358'], ['unspecified', 'unspecified', 'spirochaetes', '358943', '367'], ['leptospira interrogans', 'fiocruzl1130', 'spirochaet... |
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