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2007 - 08 colorado avalanche season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Colorado_Avalanche_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11786147-8.html.csv | count | in the 2007 - 08 colorado avalanche season , among the games where colorado was a visitor , 2 of them drew more than 20,000 people . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '20000', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'colorado'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'colorado'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; visitor ; colorado }', 'tointer': 'select the rows whose visitor record fuzzily matches to colorado .'}... | eq { count { filter_greater { filter_eq { all_rows ; visitor ; colorado } ; attendance ; 20000 } } ; 2 } = true | select the rows whose visitor record fuzzily matches to colorado . among these rows , select the rows whose attendance record is greater than 20000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'visitor_6': 6, 'colorado_7': 7, 'attendance_8': 8, '20000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'visitor_6': 'visitor', 'colorado_7': 'colorado', 'attendance_8': 'attendance', '20000_9': '20000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'visitor_6': [0], 'colorado_7': [0], 'attendance_8': [1], '20000_9': [1], '2_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['february 1', 'colorado', '0 - 2', 'detroit', 'budaj', '20066', '27 - 21 - 4'], ['february 2', 'colorado', '6 - 4', 'st louis', 'budaj', '19150', '28 - 21 - 4'], ['february 4', 'phoenix', '4 - 3', 'colorado', 'budaj', '14381', '28 - 21 - 5'], ['february 6', 'colorado', '3 - 1', 'san jose', 'theodore', '17087', '29 - ... |
best international athlete espy award | https://en.wikipedia.org/wiki/Best_International_Athlete_ESPY_Award | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10587252-1.html.csv | unique | the only baseball player to receive the best international athlete espy award was albert pujols . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': 'baseball', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'baseball'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sport record fuzzily matches to baseball .', 'tostr': 'filter_eq { all_rows ; sport ; baseball }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; sport ; baseball } } ; eq { hop { filter_eq { all_rows ; sport ; baseball } ; sportsperson } ; albert pujols } } = true | select the rows whose sport record fuzzily matches to baseball . there is only one such row in the table . the sportsperson record of this unqiue row is albert pujols . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'sport_7': 7, 'baseball_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'sportsperson_9': 9, 'albert pujols_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'sport_7': 'sport', 'baseball_8': 'baseball', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'sportsperson_9': 'sportsperson', 'albert pujols_10': 'albert pujols'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'sport_7': [0], 'baseball_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'sportsperson_9': [2], 'albert pujols_10': [3]} | ['year', 'sportsperson', 'nation of birth', 'team', 'competition , federation , or league', 'sport'] | [['2006', 'albert pujols', 'dominican republic', 'st louis cardinals', 'major league baseball', 'baseball'], ['2007', 'roger federer', 'switzerland', 'not applicable', 'atp tour', 'tennis'], ['2008', 'lorena ochoa', 'mexico', 'not applicable', 'lpga tour', 'golf'], ['2009', 'usain bolt', 'jamaica', 'not applicable', 'n... |
longyan | https://en.wikipedia.org/wiki/Longyan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1204998-2.html.csv | ordinal | liancheng county has the 2nd lowest population among districts and counties in longyan . | {'row': '7', 'col': '7', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'population', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; population ; 2 }'}, 'english name'], 'result': 'liancheng county', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; population ; 2 } ; eng... | eq { hop { nth_argmin { all_rows ; population ; 2 } ; english name } ; liancheng county } = true | select the row whose population record of all rows is 2nd minimum . the english name record of this row is liancheng county . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'population_5': 5, '2_6': 6, 'english name_7': 7, 'liancheng county_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', 'population_5': 'population', '2_6': '2', 'english name_7': 'english name', 'liancheng county_8': 'liancheng county'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'population_5': [0], '2_6': [0], 'english name_7': [1], 'liancheng county_8': [2]} | ['english name', 'simplified', 'traditional', 'pinyin', 'hakka', 'area', 'population', 'density'] | [['xinluo district', '新罗区', '新羅區', 'xīnluó qū', 'sîn - lò - khî', '2685', '662429', '247'], ['zhangping city', '漳平市', '漳平市', 'zhāngpíng shì', 'chông - phìn - sṳ', '2975', '240194', '81'], ['changting county', '长汀县', '長汀縣', 'chángtīng xiàn', 'tshòng - tin - yen', '3099', '393390', '127'], ['yongding county', '永定县', '永定縣... |
2008 - 09 rugby - bundesliga | https://en.wikipedia.org/wiki/2008%E2%80%9309_Rugby-Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20989972-8.html.csv | majority | all of the teams in the 2008 - 09 rugby - bundesliga played a total of 18 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '18', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '18'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 18 .', 'tostr': 'all_eq { all_rows ; played ; 18 } = true'} | all_eq { all_rows ; played ; 18 } = true | for the played records of all rows , all of them are equal to 18 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '18_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '18_4': '18'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '18_4': [0]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'difference', 'points'] | [['1', 'dsv 78 / 08 ricklingen', '18', '18', '0', '0', '1138', '135', '1003', '87'], ['2', 'tsv victoria linden', '18', '15', '0', '3', '720', '246', '474', '72'], ['3', 'usv potsdam', '18', '14', '0', '4', '804', '271', '533', '69'], ['4', 'fc st pauli rugby', '18', '11', '0', '7', '632', '311', '321', '56'], ['5', 's... |
1967 - 68 pittsburgh penguins season | https://en.wikipedia.org/wiki/1967%E2%80%9368_Pittsburgh_Penguins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13931419-3.html.csv | majority | in november of the 1967 - 68 pittsburgh penguins season , most games had an attendance under 10000 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'attendance', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the attendance records of all rows , most of them are less than 10000 .', 'tostr': 'most_less { all_rows ; attendance ; 10000 } = true'} | most_less { all_rows ; attendance ; 10000 } = true | for the attendance records of all rows , most of them are less than 10000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'attendance_3': 3, '10000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'attendance_3': 'attendance', '10000_4': '10000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'attendance_3': [0], '10000_4': [0]} | ['date', 'visitor', 'score', 'home', 'attendance', 'record', 'points'] | [['november 1', 'penguins', '4 - 1', 'north stars', '7535', '4 - 6 - 1', '9'], ['november 4', 'penguins', '1 - 0', 'seals', '4549', '5 - 6 - 1', '11'], ['november 8', 'flyers', '1 - 1', 'penguins', '4719', '5 - 6 - 2', '12'], ['november 9', 'penguins', '1 - 5', 'red wings', '10683', '5 - 7 - 2', '12'], ['november 11', ... |
françoise dürr | https://en.wikipedia.org/wiki/Fran%C3%A7oise_D%C3%BCrr | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2112025-3.html.csv | majority | most of the mixed doubles tournaments that françoise dürr competed in were for the french open championship . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'french open', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'championship', 'french open'], 'result': True, 'ind': 0, 'tointer': 'for the championship records of all rows , most of them fuzzily match to french open .', 'tostr': 'most_eq { all_rows ; championship ; french open } = true'} | most_eq { all_rows ; championship ; french open } = true | for the championship records of all rows , most of them fuzzily match to french open . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'championship_3': 3, 'french open_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'championship_3': 'championship', 'french open_4': 'french open'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'championship_3': [0], 'french open_4': [0]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['winner', '1968', 'french open', 'clay', 'jean - claude barclay', 'billie jean king owen davidson', '6 - 1 , 6 - 4'], ['runner - up', '1969', 'french open', 'clay', 'jean - claude barclay', 'margaret court marty riessen', '6 - 3 , 6 - 2'], ['runner - up', '1969', 'us open', 'grass', 'dennis ralston', 'margaret court ... |
dick stockton ( tennis ) | https://en.wikipedia.org/wiki/Dick_Stockton_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11084877-1.html.csv | count | dick stockton ( tennis ) had jimmy connors as an opponent 3 times in 1977 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'jimmy connors', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'jimmy connors'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to jimmy connors .', 'tostr': 'filter_eq { all_rows ; opponent ; jimmy connors }'}], 'result': '3', ... | eq { count { filter_eq { all_rows ; opponent ; jimmy connors } } ; 3 } = true | select the rows whose opponent record fuzzily matches to jimmy connors . 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, 'opponent_5': 5, 'jimmy connors_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', 'opponent_5': 'opponent', 'jimmy connors_6': 'jimmy connors', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'jimmy connors_6': [0], '3_7': [2]} | ['outcome', 'date', 'championship', 'surface', 'opponent', 'score'] | [['runner - up', '1971', 'merion , us', 'hard', 'clark graebner', '2 - 6 , 4 - 6 , 7 - 6 , 5 - 7'], ['runner - up', '1973', 'miami wct , us', 'hard', 'rod laver', '6 - 7 , 3 - 6 , 5 - 7'], ['winner', '1974', 'atlanta wct , us', 'clay', 'jiří hřebec', '6 - 2 , 6 - 1'], ['runner - up', '1974', 'charlotte , us', 'clay', '... |
2007 - 08 fis ski jumping world cup | https://en.wikipedia.org/wiki/2007%E2%80%9308_FIS_Ski_Jumping_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14407512-16.html.csv | comparative | simon ammann 's first jump on 27 january 2008 was longer than thomas morgenstern 's . | {'row_1': '3', 'row_2': '2', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'simon ammann'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to simon ammann .', 'tostr': 'filter_eq { all_rows ; name ; simon ammann }'}, '1st ( m )'], 'result': ... | greater { hop { filter_eq { all_rows ; name ; simon ammann } ; 1st ( m ) } ; hop { filter_eq { all_rows ; name ; thomas morgenstern } ; 1st ( m ) } } = true | select the rows whose name record fuzzily matches to simon ammann . take the 1st ( m ) record of this row . select the rows whose name record fuzzily matches to thomas morgenstern . take the 1st ( m ) 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, 'name_7': 7, 'simon ammann_8': 8, '1st (m)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'thomas morgenstern_12': 12, '1st (m)_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', 'name_7': 'name', 'simon ammann_8': 'simon ammann', '1st (m)_9': '1st ( m )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'thom... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'simon ammann_8': [0], '1st (m)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'thomas morgenstern_12': [1], '1st (m)_13': [3]} | ['rank', 'name', 'nationality', '1st ( m )', 'points', 'overall wc points ( rank )'] | [['1', 'anders bardal', 'nor', '137.0', '149.1', '461 ( 6 )'], ['2', 'thomas morgenstern', 'aut', '135.0', '145.0', '1255 ( 1 )'], ['3', 'simon ammann', 'sui', '136.5', '144.2', '448 ( 8 )'], ['4', 'adam małysz', 'pol', '133.5', '141.3', '386 ( 11 )'], ['5', 'andreas küttel', 'sui', '134.0', '141.2', '459 ( 7 )']] |
w.d. & h.o. wills tournament | https://en.wikipedia.org/wiki/W.D._%26_H.O._Wills_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15942377-1.html.csv | comparative | bernard gallacher had a lower score than peter butler in the w.d. & h.o. wills tournament . | {'row_1': '6', 'row_2': '7', 'col': '5', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'bernard gallacher'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winner record fuzzily matches to bernard gallacher .', 'tostr': 'filter_eq { all_rows ; winner ; bernard gallacher }'}, 'score... | less { hop { filter_eq { all_rows ; winner ; bernard gallacher } ; score } ; hop { filter_eq { all_rows ; winner ; peter butler } ; score } } = true | select the rows whose winner record fuzzily matches to bernard gallacher . take the score record of this row . select the rows whose winner record fuzzily matches to peter butler . take the score 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, 'winner_7': 7, 'bernard gallacher_8': 8, 'score_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'winner_11': 11, 'peter butler_12': 12, 'score_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', 'winner_7': 'winner', 'bernard gallacher_8': 'bernard gallacher', 'score_9': 'score', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'winner_11': 'winner',... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'winner_7': [0], 'bernard gallacher_8': [0], 'score_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'winner_11': [1], 'peter butler_12': [1], 'score_13': [3]} | ['year', 'venue', 'winner', 'country', 'score'] | [['1974', 'kings norton golf club', 'neil coles', 'england', '283 ( - 5 )'], ['1973', 'kings norton golf club', 'charles coody', 'united states', '281 ( - 7 )'], ['1972', 'dalmahoy golf club', 'peter thomson', 'australia', '270 ( - 14 )'], ['1971', 'dalmahoy golf club', 'bernard hunt', 'england', '276 ( - 8 )'], ['1970... |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-15.html.csv | aggregation | the average score of away teams in the 1972 vfl season was 11.36 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '11.36', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'away team score'], 'result': '11.36', 'ind': 0, 'tostr': 'avg { all_rows ; away team score }'}, '11.36'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; away team score } ; 11.36 } = true', 'tointer': 'the average of the away team scor... | round_eq { avg { all_rows ; away team score } ; 11.36 } = true | the average of the away team score record of all rows is 11.36 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'away team score_4': 4, '11.36_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'away team score_4': 'away team score', '11.36_5': '11.36'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'away team score_4': [0], '11.36_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '14.7 ( 91 )', 'st kilda', '9.11 ( 65 )', 'western oval', '18655', '15 july 1972'], ['fitzroy', '16.14 ( 110 )', 'north melbourne', '9.12 ( 66 )', 'junction oval', '7007', '15 july 1972'], ['essendon', '13.12 ( 90 )', 'richmond', '17.9 ( 111 )', 'windy hill', '22251', '15 july 1972'], ['carlton', '20.8 (... |
list of tvb series ( 2006 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%282006%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10942714-1.html.csv | comparative | the saviour of the soul drew more viewers for its finale than men in pain drew for its finale . | {'row_1': '3', 'row_2': '9', 'col': '8', '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', 'english title', 'the saviour of the soul'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose english title record fuzzily matches to the saviour of the soul .', 'tostr': 'filter_eq { all_rows ; english t... | greater { hop { filter_eq { all_rows ; english title ; the saviour of the soul } ; hk viewers } ; hop { filter_eq { all_rows ; english title ; men in pain } ; hk viewers } } = true | select the rows whose english title record fuzzily matches to the saviour of the soul . take the hk viewers record of this row . select the rows whose english title record fuzzily matches to men in pain . take the hk viewers 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, 'english title_7': 7, 'the saviour of the soul_8': 8, 'hk viewers_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'english title_11': 11, 'men in pain_12': 12, 'hk viewers_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', 'english title_7': 'english title', 'the saviour of the soul_8': 'the saviour of the soul', 'hk viewers_9': 'hk viewers', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_ro... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'english title_7': [0], 'the saviour of the soul_8': [0], 'hk viewers_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'english title_11': [1], 'men in pain_12': [1], 'hk viewers_13': [3]} | ['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers'] | [['1', 'la femme desperado', '女人唔易做', '33', '41', '31', '34', '2.14 million'], ['2', 'forensic heroes', '法證先鋒', '33', '43', '28', '37', '2.11 million'], ['3', 'the saviour of the soul', '神鵰俠侶', '32', '40', '32', '35', '2.07 million'], ['4', 'love guaranteed', '愛情全保', '32', '36', '30', '34', '2.07 million'], ['5', 'bar ... |
communication with extraterrestrial intelligence | https://en.wikipedia.org/wiki/Communication_with_extraterrestrial_intelligence | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1446835-2.html.csv | comparative | of the communications with extraterrestrial intelligence , cosmic call " hd 178428 " will arrive earlier than cosmic call " hd 186408 " . | {'row_1': '3', 'row_2': '1', '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', 'designation hd', 'hd 178428'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose designation hd record fuzzily matches to hd 178428 .', 'tostr': 'filter_eq { all_rows ; designation hd ; hd 178428 }'}, 'arriv... | less { hop { filter_eq { all_rows ; designation hd ; hd 178428 } ; arrival date } ; hop { filter_eq { all_rows ; designation hd ; hd 186408 } ; arrival date } } = true | select the rows whose designation hd record fuzzily matches to hd 178428 . take the arrival date record of this row . select the rows whose designation hd record fuzzily matches to hd 186408 . take the arrival 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, 'designation hd_7': 7, 'hd 178428_8': 8, 'arrival date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'designation hd_11': 11, 'hd 186408_12': 12, 'arrival 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', 'designation hd_7': 'designation hd', 'hd 178428_8': 'hd 178428', 'arrival date_9': 'arrival date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'designa... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'designation hd_7': [0], 'hd 178428_8': [0], 'arrival date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'designation hd_11': [1], 'hd 186408_12': [1], 'arrival date_13': [3]} | ['designation hd', 'constellation', 'date sent', 'arrival date', 'message'] | [['hd 186408', 'cygnus', 'may 24 , 1999', 'november 2069', 'cosmic call 1'], ['hd 190406', 'sagitta', 'june 30 , 1999', 'february 2057', 'cosmic call 1'], ['hd 178428', 'sagitta', 'june 30 , 1999', 'october 2067', 'cosmic call 1'], ['hd 190360', 'cygnus', 'july 1 , 1999', 'april 2051', 'cosmic call 1'], ['hip 4872', 'c... |
tourism in costa rica | https://en.wikipedia.org/wiki/Tourism_in_Costa_Rica | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17781704-3.html.csv | comparative | mexico had the most international tourists in 2011 , and barbados had the least . | {'row_1': '11', 'row_2': '2', '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', 'selected caribbean and n latin america countries', 'mexico'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose selected caribbean and n latin america countries record fuzzily matches to mexico .', 'tostr... | greater { hop { filter_eq { all_rows ; selected caribbean and n latin america countries ; mexico } ; internl tourist arrivals 2011 ( x1000 ) } ; hop { filter_eq { all_rows ; selected caribbean and n latin america countries ; barbados } ; internl tourist arrivals 2011 ( x1000 ) } } = true | select the rows whose selected caribbean and n latin america countries record fuzzily matches to mexico . take the internl tourist arrivals 2011 ( x1000 ) record of this row . select the rows whose selected caribbean and n latin america countries record fuzzily matches to barbados . take the internl tourist arrivals 20... | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'selected caribbean and n latin america countries_7': 7, 'mexico_8': 8, 'internl tourist arrivals 2011 (x1000)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'selected caribbean and n latin america countries_11': 11,... | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'selected caribbean and n latin america countries_7': 'selected caribbean and n latin america countries', 'mexico_8': 'mexico', 'internl tourist arrivals 2011 (x1000)_9': 'internl tourist a... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'selected caribbean and n latin america countries_7': [0], 'mexico_8': [0], 'internl tourist arrivals 2011 (x1000)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'selected caribbean and n latin americ... | ['selected caribbean and n latin america countries', 'internl tourist arrivals 2011 ( x1000 )', 'internl tourism receipts 2011 ( million usd )', 'receipts per arrival 2010 ( col 2 ) / ( col 1 ) ( usd )', 'receipts per capita 2005 usd', 'revenues as % of exports goods and services 2011'] | [['bahamas ( 1 )', '1368', '2059', '1505', '6288', '74.6'], ['barbados', '568', '974', '1715', '2749', '58.5'], ['brazil', '5433', '6555', '1207', '18', '3.2'], ['chile', '3070', '1831', '596', '73', '5.3'], ['costa rica', '2196', '2156', '982', '343', '17.5'], ['colombia ( 1 )', '2385', '2083', '873', '25', '6.6'], ['... |
2008 - 09 cypriot first division | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cypriot_First_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17054062-1.html.csv | superlative | the stadium that can hold the least amount of people is the peyia municipal stadium . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', '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', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; capacity }'}, 'venue'], 'result': 'peyia municipal stadium', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; capacity } ; venue }'}, 'peyia municipal stadiu... | eq { hop { argmin { all_rows ; capacity } ; venue } ; peyia municipal stadium } = true | select the row whose capacity record of all rows is minimum . the venue record of this row is peyia municipal stadium . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'venue_6': 6, 'peyia municipal stadium_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'venue_6': 'venue', 'peyia municipal stadium_7': 'peyia municipal stadium'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'venue_6': [1], 'peyia municipal stadium_7': [2]} | ['team', 'head coach', 'team captain', 'venue', 'capacity', 'kitmaker', 'shirt sponsor', 'club chairman'] | [['aek larnaca', 'savvas constantinou', 'constantinos mina', 'neo gsz stadium', '13032', 'mass', 'cytavision', 'marios ellinas'], ['ael limassol', 'mihai stoichiţă', 'simos krassas', 'tsirion stadium', '13331', 'mass', 'sinergatiko tamieftirio lemesou', 'andreas sofokleous'], ['aep paphos', 'nir klinger', 'giorgos geor... |
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 | count | there are two buildings in germany that are at least 800 feet tall . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '800', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'height ( ft )', '800'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height ( ft ) record is greater than or equal to 800 .', 'tostr': 'filter_greater_eq { all_rows ; height ( ft ) ; 800 }'}], 'result':... | eq { count { filter_greater_eq { all_rows ; height ( ft ) ; 800 } } ; 2 } = true | select the rows whose height ( ft ) record is greater than or equal to 800 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'height (ft)_5': 5, '800_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'height (ft)_5': 'height ( ft )', '800_6': '800', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'height (ft)_5': [0], '800_6': [0], '2_7': [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'... |
2007 toronto argonauts season | https://en.wikipedia.org/wiki/2007_Toronto_Argonauts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916798-4.html.csv | aggregation | in the 2007 toronto argonauts season , the total attendance for the month of august was 83969 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '83969', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'august'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; august }', 'tointer': 'select the rows whose date record fuzzily matches to august .'}, 'attendance'], 'result': '83969', 'ind': 1, '... | round_eq { sum { filter_eq { all_rows ; date ; august } ; attendance } ; 83969 } = true | select the rows whose date record fuzzily matches to august . the sum of the attendance record of these rows is 83969 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'august_6': 6, 'attendance_7': 7, '83969_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', 'august_6': 'august', 'attendance_7': 'attendance', '83969_8': '83969'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'august_6': [0], 'attendance_7': [1], '83969_8': [2]} | ['week', 'date', 'opponent', 'location', 'final score', 'attendance', 'record'] | [['1', 'june 28', 'lions', 'rogers centre', 'l 24 - 22', '29157', '0 - 1'], ['2', 'july 7', 'tiger - cats', 'ivor wynne stadium', 'w 30 - 5', '28198', '1 - 1'], ['3', 'july 12', 'stampeders', 'rogers centre', 'w 48 - 15', '29304', '2 - 1'], ['4', 'july 21', 'stampeders', 'mcmahon stadium', 'l 33 - 10', '28202', '2 - 2'... |
sports in charlotte , north carolina | https://en.wikipedia.org/wiki/Sports_in_Charlotte%2C_North_Carolina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15720079-6.html.csv | ordinal | jim crockett park was the charlotte venue that closed the 2nd earliest . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'closed', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; closed ; 2 }'}, 'venue'], 'result': 'jim crockett park', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; closed ; 2 } ; venue }'}, 'jim crock... | eq { hop { nth_argmin { all_rows ; closed ; 2 } ; venue } ; jim crockett park } = true | select the row whose closed record of all rows is 2nd minimum . the venue record of this row is jim crockett park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'closed_5': 5, '2_6': 6, 'venue_7': 7, 'jim crockett park_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', 'closed_5': 'closed', '2_6': '2', 'venue_7': 'venue', 'jim crockett park_8': 'jim crockett park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'closed_5': [0], '2_6': [0], 'venue_7': [1], 'jim crockett park_8': [2]} | ['venue', 'location', 'environment', 'closed', 'reason'] | [['charlotte coliseum', 'eagle lake , charlotte', 'indoor arena', '2005', 'replaced'], ['jim crockett park', 'dilworth , charlotte', 'open air , natural grass', '1985', 'arson'], ['metrolina speedway', 'metrolina fairgrounds , charlotte', 'open air , dirt', '1990s', 'abandoned'], ['belk gymnasium', 'university city , c... |
new year live | https://en.wikipedia.org/wiki/New_Year_Live | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24212608-1.html.csv | superlative | for the show new years live , the episode with the highest number of viewers was episode 7 . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewers ( millions ) }'}, 'episode'], 'result': '7', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewers ( millions ) } ; episode }'}, '7'], 're... | eq { hop { argmax { all_rows ; viewers ( millions ) } ; episode } ; 7 } = true | select the row whose viewers ( millions ) record of all rows is maximum . the episode record of this row is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewers (millions)_5': 5, 'episode_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewers (millions)_5': 'viewers ( millions )', 'episode_6': 'episode', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewers (millions)_5': [0], 'episode_6': [1], '7_7': [2]} | ['episode', 'broadcast date', 'bbc one presenter ( s )', 'starring', 'radio 1 presenter', 'viewers ( millions )'] | [['1', '2005', 'clare balding', 'doug segal', 'n / a', '6.43'], ['2', '2006', 'myleene klass', 'gethin jones , natasha kaplinsky & alesha dixon', 'n / a', '6.06'], ['3', '2007', 'myleene klass', 'gethin jones , natasha kaplinsky & nick knowles', 'n / a', '5.35'], ['5', '2009', 'myleene klass', 'n / a', 'nihal', '7.65']... |
list of superfund sites in connecticut | https://en.wikipedia.org/wiki/List_of_Superfund_sites_in_Connecticut | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10840672-1.html.csv | unique | in the list of superfund sites in connecticut , new london is the only county which is proposed in 1989 . | {'scope': 'subset', 'row': '13', 'col': '4', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': '1989', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '1989'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'proposed', '1989'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; proposed ; 1989 }', 'tointer': 'select the rows whose proposed record fuzzily matches to 1989 .'}, 'propose... | and { only { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } } ; eq { hop { filter_eq { filter_eq { all_rows ; proposed ; 1989 } ; proposed ; 1989 } ; county } ; new london } } = true | select the rows whose proposed record fuzzily matches to 1989 . among these rows , select the rows whose proposed record fuzzily matches to 1989 . there is only one such row in the table . the county record of this unqiue row is new london . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'proposed_8': 8, '1989_9': 9, 'proposed_10': 10, '1989_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'county_12': 12, 'new london_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'proposed_8': 'proposed', '1989_9': '1989', 'proposed_10': 'proposed', '1989_11': '1989', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'county_12': 'county', 'new lon... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'proposed_8': [0], '1989_9': [0], 'proposed_10': [1], '1989_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'county_12': [3], 'new london_13': [4]} | ['cerclis id', 'name', 'county', 'proposed', 'listed', 'construction completed', 'partially deleted', 'deleted'] | [['ctd980670814', 'kellogg - deering well field', 'fairfield', '09 / 08 / 1983', '09 / 21 / 1984', '09 / 23 / 1996', 'n / a', 'n / a'], ['ctd001186618', 'raymark industries , inc', 'fairfield', '01 / 18 / 1994', '04 / 25 / 1995', 'n / a', 'n / a', 'n / a'], ['ct0002055887', 'broad brook mill', 'hartford', '12 / 01 / 20... |
1980 african cup of champions clubs | https://en.wikipedia.org/wiki/1980_African_Cup_of_Champions_Clubs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12483185-2.html.csv | comparative | mp algiers had a higher scoring game than fortior mahajanga . | {'row_1': '6', 'row_2': '8', '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', 'team 2', 'mp algiers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team 2 record fuzzily matches to mp algiers .', 'tostr': 'filter_eq { all_rows ; team 2 ; mp algiers }'}, '1st leg'], 'result': No... | greater { hop { filter_eq { all_rows ; team 2 ; mp algiers } ; 1st leg } ; hop { filter_eq { all_rows ; team 2 ; fortior mahajanga } ; 1st leg } } = true | select the rows whose team 2 record fuzzily matches to mp algiers . take the 1st leg record of this row . select the rows whose team 2 record fuzzily matches to fortior mahajanga . take the 1st leg 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, 'team 2_7': 7, 'mp algiers_8': 8, '1st leg_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team 2_11': 11, 'fortior mahajanga_12': 12, '1st leg_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', 'team 2_7': 'team 2', 'mp algiers_8': 'mp algiers', '1st leg_9': '1st leg', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team 2_11': 'team 2', 'fo... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team 2_7': [0], 'mp algiers_8': [0], '1st leg_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team 2_11': [1], 'fortior mahajanga_12': [1], '1st leg_13': [3]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['djoliba ac', '1 - 2', 'hearts of oak', '1 - 1', '0 - 1'], ['etoile du congo', '1 - 1 ( 3 - 1 pen )', 'hafia fc', '0 - 1', '1 - 0'], ['simba sc', '2 - 5', 'union douala', '2 - 4', '0 - 1'], ['silures', '0 - 4', 'canon yaoundé', '0 - 1', '0 - 3'], ['ac semassi', '1 - 2', 'asf police', '1 - 1', '0 - 1'], ["stella club ... |
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/2-17100961-20.html.csv | superlative | jim spavital was the highest drafted player for the washington redskins . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'pick'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; pick }'}, 'pick'], 'result': '5', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; pick } ; pick }'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { a... | eq { hop { argmin { all_rows ; pick } ; pick } ; 5 } = true | select the row whose pick record of all rows is minimum . the pick record of this row is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'pick_5': 5, 'pick_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'pick_5': 'pick', 'pick_6': 'pick', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'pick_5': [0], 'pick_6': [1], '5_7': [2]} | ['round', 'pick', 'name', 'position', 'college', 'aafc team'] | [['1', '5', 'jim spavital', 'fb', 'oklahoma a & m', 'los angeles dons'], ['2', '18', 'chuck drazenovich', 'fb', 'penn state', 'los angeles dons'], ['3', '31', 'roland dale', 'ot', 'mississippi', 'brooklyn dodgers'], ['4', '48', 'lloyd eisenberg', 'ot', 'duke', 'los angeles dons'], ['5', '61', 'hardy brown', 'fb', 'tuls... |
1976 - 77 philadelphia flyers season | https://en.wikipedia.org/wiki/1976%E2%80%9377_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14303579-16.html.csv | ordinal | in the 1976-77 philadelphia flyers season , fourth defensive player drafted was dave hynek . | {'scope': 'subset', 'row': '4', 'col': '1', 'order': '4', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'defense'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defense'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; defense }', 'tointer': 'select the rows whose position record fuzzily matches to defense .'}, 'round'... | and { eq { nth_min { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; 4 } ; eq { hop { nth_argmin { filter_eq { all_rows ; position ; defense } ; round ; 4 } ; player } ; dave hynek } } = true | select the rows whose position record fuzzily matches to defense . the 4th minimum round record of these rows is 4 . the player record of the row with 4th minimum round record is dave hynek . | 8 | 7 | {'and_6': 6, 'result_7': 7, 'eq_2': 2, 'nth_min_1': 1, 'filter_str_eq_0': 0, 'all_rows_8': 8, 'position_9': 9, 'defense_10': 10, 'round_11': 11, '4_12': 12, '4_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'nth_argmin_3': 3, 'round_14': 14, '4_15': 15, 'player_16': 16, 'dave hynek_17': 17} | {'and_6': 'and', 'result_7': 'true', 'eq_2': 'eq', 'nth_min_1': 'nth_min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_8': 'all_rows', 'position_9': 'position', 'defense_10': 'defense', 'round_11': 'round', '4_12': '4', '4_13': '4', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'nth_argmin_3': 'nth_argmin', 'round_14... | {'and_6': [7], 'result_7': [], 'eq_2': [6], 'nth_min_1': [2], 'filter_str_eq_0': [1, 3], 'all_rows_8': [0], 'position_9': [0], 'defense_10': [0], 'round_11': [1], '4_12': [1], '4_13': [2], 'str_eq_5': [6], 'str_hop_4': [5], 'nth_argmin_3': [4], 'round_14': [3], '4_15': [3], 'player_16': [4], 'dave hynek_17': [5]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'mark suzor', 'defense', 'canada', 'kingston canadians ( oha )'], ['2', 'drew callander', 'defense', 'canada', 'regina pats ( wchl )'], ['3', 'craig hanmer', 'defense', 'united states', 'mohawk valley comets ( nahl )'], ['4', 'dave hynek', 'defense', 'canada', 'kingston canadians ( oha )'], ['5', 'robin lang', '... |
piercarlo ghinzani | https://en.wikipedia.org/wiki/Piercarlo_Ghinzani | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226331-1.html.csv | unique | 1989 was the only year that the ford cosworth dfr v8 engine was used . | {'scope': 'all', 'row': '15', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'ford cosworth dfr v8', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'ford cosworth dfr v8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to ford cosworth dfr v8 .', 'tostr': 'filter_eq { all_rows ; engine ; ford cosworth dfr v8 }'}], ... | and { only { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } } ; eq { hop { filter_eq { all_rows ; engine ; ford cosworth dfr v8 } ; year } ; 1989 } } = true | select the rows whose engine record fuzzily matches to ford cosworth dfr v8 . there is only one such row in the table . the year record of this unqiue row is 1989 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'engine_7': 7, 'ford cosworth dfr v8_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1989_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'engine_7': 'engine', 'ford cosworth dfr v8_8': 'ford cosworth dfr v8', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1989_10': '1989'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'engine_7': [0], 'ford cosworth dfr v8_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1989_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1981', 'osella squadra corse', 'osella fa1b', 'ford cosworth dfv v8', '0'], ['1983', 'osella squadra corse', 'osella fa1d', 'ford cosworth dfv v8', '0'], ['1983', 'osella squadra corse', 'osella fa1e', 'alfa romeo v12', '0'], ['1984', 'osella squadra corse', 'osella fa1f', 'alfa romeo v8 ( t / c )', '2'], ['1985', '... |
list of the busiest airports in africa | https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_Africa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18600121-1.html.csv | count | four of the busiest airports in africa were in the country of south africa . | {'scope': 'all', 'criterion': 'equal', 'value': 'south africa', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'south africa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to south africa .', 'tostr': 'filter_eq { all_rows ; country ; south africa }'}], 'result': '4', 'ind':... | eq { count { filter_eq { all_rows ; country ; south africa } } ; 4 } = true | select the rows whose country record fuzzily matches to south africa . 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, 'country_5': 5, 'south africa_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', 'country_5': 'country', 'south africa_6': 'south africa', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'south africa_6': [0], '4_7': [2]} | ['country', 'airport', 'city', '2012', 'change ( 12 / 11 )'] | [['south africa', 'or tambo international airport', 'johannesburg', '18681458', '0 1.2 %'], ['spain', 'gran canaria airport', 'las palmas de gran canaria', '9892067', '0 6.1 %'], ['spain', 'tenerife sur', 'granadilla de abona', '8530729', '0 1.5 %'], ['south africa', 'cape town international airport', 'cape town', '850... |
comparison of microsoft windows versions | https://en.wikipedia.org/wiki/Comparison_of_Microsoft_Windows_versions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10758793-4.html.csv | count | 12 of the versions used a closed source license . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'closed source', 'result': '12', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'license', 'closed source'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose license record fuzzily matches to closed source .', 'tostr': 'filter_eq { all_rows ; license ; closed source }'}], 'result': '12', 'i... | eq { count { filter_eq { all_rows ; license ; closed source } } ; 12 } = true | select the rows whose license record fuzzily matches to closed source . the number of such rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'license_5': 5, 'closed source_6': 6, '12_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'license_5': 'license', 'closed source_6': 'closed source', '12_7': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'license_5': [0], 'closed source_6': [0], '12_7': [2]} | ['name', 'release date', 'rtm build', 'current version', 'status support', 'license', 'based on ( kernel )', 'supported architectures', 'os type'] | [['windows nt 3.1', '1993 - 07 - 27', '528', '3.10.528 sp3 ( 1994 - 11 - 10 )', 'unsupported ( 2001 - 12 - 31 )', 'closed source', 'nt 3.1', 'ia - 32 , dec alpha , mips', 'workstation , server'], ['windows nt 3.5', '1994 - 09 - 21', '807', '3.50.807 sp3 ( 1995 - 06 - 21 )', 'unsupported ( 2001 - 12 - 31 )', 'closed sou... |
1931 vfl season | https://en.wikipedia.org/wiki/1931_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10789881-8.html.csv | comparative | north melbourne had a higher away team score than south melbourne in the 1931 vfl season . | {'row_1': '3', 'row_2': '1', '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', 'away team', 'north melbourne'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away team record fuzzily matches to north melbourne .', 'tostr': 'filter_eq { all_rows ; away team ; north melbourne }'}, ... | greater { hop { filter_eq { all_rows ; away team ; north melbourne } ; away team score } ; hop { filter_eq { all_rows ; away team ; south melbourne } ; away team score } } = true | select the rows whose away team record fuzzily matches to north melbourne . take the away team score record of this row . select the rows whose away team record fuzzily matches to south melbourne . take the away team score 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, 'away team_7': 7, 'north melbourne_8': 8, 'away team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'away team_11': 11, 'south melbourne_12': 12, 'away team score_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', 'away team_7': 'away team', 'north melbourne_8': 'north melbourne', 'away team score_9': 'away team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_r... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'away team_7': [0], 'north melbourne_8': [0], 'away team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'away team_11': [1], 'south melbourne_12': [1], 'away team score_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '12.12 ( 84 )', 'south melbourne', '7.15 ( 57 )', 'punt road oval', '18000', '20 june 1931'], ['essendon', '7.13 ( 55 )', 'geelong', '13.11 ( 89 )', 'windy hill', '10000', '20 june 1931'], ['collingwood', '22.22 ( 154 )', 'north melbourne', '9.10 ( 64 )', 'victoria park', '6000', '20 june 1931'], ['carlto... |
list of game of the year awards | https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-39.html.csv | majority | a majority of winners of the game of the year awards are from the playstation 3 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'playstation 3', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'platform ( s )', 'playstation 3'], 'result': True, 'ind': 0, 'tointer': 'for the platform ( s ) records of all rows , most of them fuzzily match to playstation 3 .', 'tostr': 'most_eq { all_rows ; platform ( s ) ; playstation 3 } = true'} | most_eq { all_rows ; platform ( s ) ; playstation 3 } = true | for the platform ( s ) records of all rows , most of them fuzzily match to playstation 3 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'platform (s)_3': 3, 'playstation 3_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'platform (s)_3': 'platform ( s )', 'playstation 3_4': 'playstation 3'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'platform (s)_3': [0], 'playstation 3_4': [0]} | ['year', 'game', 'genre', 'platform ( s )', 'developer ( s )'] | [['2007', 'super mario galaxy', 'platformer', 'wii', 'nintendo'], ['2008', 'grand theft auto iv', 'open world , action', 'xbox 360 , playstation 3 , pc', 'rockstar north'], ['2009', 'uncharted 2 : among thieves', 'third - person shooter', 'playstation 3', 'naughty dog'], ['2010', 'red dead redemption', 'open world : ( ... |
stephanie vogt | https://en.wikipedia.org/wiki/Stephanie_Vogt | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16306899-6.html.csv | majority | most of the tournament surfaces that stephanie vogt played on were clay . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', '24 june 2007', 'davos , switzerland', 'clay', 'jessica moore', '6 - 4 , 4 - 6 , 6 - 3'], ['runner - up', '19 august 2007', 'pesaro , italy', 'clay', 'polona hercog', '2 - 6 , 6 - 2 , 1 - 6'], ['runner - up', '28 october 2007', 'mexico city , mexico', 'hard', 'olivia sanchez', '6 - 2 , 2 - 6 , 2 - 6'], ['ru... |
hey venus ! | https://en.wikipedia.org/wiki/Hey_Venus%21 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10647532-1.html.csv | count | hey venus ! was released two times on vinyl record . | {'scope': 'all', 'criterion': 'equal', 'value': 'vinyl record', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'vinyl record'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose format record fuzzily matches to vinyl record .', 'tostr': 'filter_eq { all_rows ; format ; vinyl record }'}], 'result': '2', 'ind': 1,... | eq { count { filter_eq { all_rows ; format ; vinyl record } } ; 2 } = true | select the rows whose format record fuzzily matches to vinyl record . 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, 'format_5': 5, 'vinyl record_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', 'format_5': 'format', 'vinyl record_6': 'vinyl record', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'format_5': [0], 'vinyl record_6': [0], '2_7': [2]} | ['region', 'date', 'label', 'format', 'catalogue'] | [['united kingdom', '27 august 2007', 'rough trade records', 'vinyl record', 'rtradlp 346'], ['united kingdom', '27 august 2007', 'rough trade records', 'compact disc', 'rtradcd 346'], ['united kingdom', '27 august 2007', 'rough trade records', 'download', '-'], ['united states', '28 august 2007', 'rough trade america'... |
socialist destourian party | https://en.wikipedia.org/wiki/Socialist_Destourian_Party | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13746866-2.html.csv | majority | habib bourguiba was the party leader of the socialist destourian party in all of the elections . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'habib bourguiba', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party leader', 'habib bourguiba'], 'result': True, 'ind': 0, 'tointer': 'for the party leader records of all rows , all of them fuzzily match to habib bourguiba .', 'tostr': 'all_eq { all_rows ; party leader ; habib bourguiba } = true'} | all_eq { all_rows ; party leader ; habib bourguiba } = true | for the party leader records of all rows , all of them fuzzily match to habib bourguiba . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party leader_3': 3, 'habib bourguiba_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party leader_3': 'party leader', 'habib bourguiba_4': 'habib bourguiba'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party leader_3': [0], 'habib bourguiba_4': [0]} | ['election date', 'party leader', 'number of votes received', 'percentage of votes', 'number of deputies'] | [['1964', 'habib bourguiba', '1255153', '100 %', '101'], ['1969', 'habib bourguiba', '1363939', '100 %', '101'], ['1974', 'habib bourguiba', '1570954', '100 %', '112'], ['1979', 'habib bourguiba', '1560753', '100 %', '121'], ['1981', 'habib bourguiba', '1828363', '94.2 %', '136']] |
usa today all - usa high school basketball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677760-30.html.csv | unique | myles mack is the only usa today all - usa high school basketball team member under 6 feel tall . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'less_than', 'value': '6-0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'height', '6-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record is less than 6-0 .', 'tostr': 'filter_less { all_rows ; height ; 6-0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { ... | and { only { filter_less { all_rows ; height ; 6-0 } } ; eq { hop { filter_less { all_rows ; height ; 6-0 } ; player } ; myles mack } } = true | select the rows whose height record is less than 6-0 . there is only one such row in the table . the player record of this unqiue row is myles mack . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'height_7': 7, '6-0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'myles mack_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'height_7': 'height', '6-0_8': '6-0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'myles mack_10': 'myles mack'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'height_7': [0], '6-0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'myles mack_10': [3]} | ['player', 'height', 'school', 'hometown', 'college'] | [['khem birch', '6 - 9', 'notre dame prep', 'montreal , qc , canada', 'pittsburgh / unlv'], ['perry ellis', '6 - 8', 'wichita heights high school', 'wichita , ks', 'kansas'], ['myles mack', '5 - 9', 'st anthony high school', 'jersey city , nj', 'rutgers'], ['shabazz muhammad', '6 - 6', 'bishop gorman high school', 'las... |
1997 cfl draft | https://en.wikipedia.org/wiki/1997_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28059992-1.html.csv | ordinal | in the 1997 cfl draft , the 2nd to last pick was jason clemett . | {'row': '7', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'pick', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; pick ; 2 }'}, 'player'], 'result': 'jason clemett', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pick ; 2 } ; player }'}, 'jason clemett'], ... | eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; jason clemett } = true | select the row whose pick record of all rows is 2nd maximum . the player record of this row is jason clemett . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'pick_5': 5, '2_6': 6, 'player_7': 7, 'jason clemett_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', 'pick_5': 'pick', '2_6': '2', 'player_7': 'player', 'jason clemett_8': 'jason clemett'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'pick_5': [0], '2_6': [0], 'player_7': [1], 'jason clemett_8': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['1', 'toronto argonauts', 'chad folk', 'ol', 'utah'], ['2', 'saskatchewan roughriders', 'ben fairbrother', 'ol', 'calgary'], ['3', 'edmonton eskimos', 'ian franklin', 'cb', 'weber state'], ['4', 'hamilton tiger - cats', 'tim prinsen', 'og', 'north dakota'], ['5', 'calgary stampeders', 'doug brown', 'dl', 'simon frase... |
swimming at the 2008 summer olympics - women 's 50 metre freestyle | https://en.wikipedia.org/wiki/Swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_50_metre_freestyle | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18625234-4.html.csv | ordinal | lisabeth trickett ranked 3rd among the women 's 50 metre freestyle swimmers . | {'row': '3', 'col': '1', 'order': '3', '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', 'rank', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; rank ; 3 }'}, 'name'], 'result': 'lisbeth trickett', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 3 } ; name }'}, 'lisbeth trickett']... | eq { hop { nth_argmin { all_rows ; rank ; 3 } ; name } ; lisbeth trickett } = true | select the row whose rank record of all rows is 3rd minimum . the name record of this row is lisbeth trickett . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, '3_6': 6, 'name_7': 7, 'lisbeth trickett_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', 'rank_5': 'rank', '3_6': '3', 'name_7': 'name', 'lisbeth trickett_8': 'lisbeth trickett'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], '3_6': [0], 'name_7': [1], 'lisbeth trickett_8': [2]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '3', 'britta steffen', 'germany', '24.43'], ['2', '4', 'marleen veldhuis', 'netherlands', '24.46'], ['3', '5', 'lisbeth trickett', 'australia', '24.47'], ['4', '7', 'hinkelien schreuder', 'netherlands', '24.52'], ['5', '1', 'kara lynn joyce', 'united states', '24.63'], ['6', '8', 'aliaksandra herasimenia', 'bela... |
spain men 's national water polo team | https://en.wikipedia.org/wiki/Spain_men%27s_national_water_polo_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18985137-1.html.csv | count | there are 4 players on the team that play the d position . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'd', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', 'd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record fuzzily matches to d .', 'tostr': 'filter_eq { all_rows ; pos ; d }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; ... | eq { count { filter_eq { all_rows ; pos ; d } } ; 4 } = true | select the rows whose pos record fuzzily matches to d . 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, 'pos_5': 5, 'd_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', 'pos_5': 'pos', 'd_6': 'd', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'pos_5': [0], 'd_6': [0], '4_7': [2]} | ['name', 'pos', 'height', 'weight', '2012 club'] | [['iñaki aguilar', 'gk', 'm', '-', 'cn sabadell'], ['mario josé garcía', 'd', 'm', '-', 'real canoe'], ['david martín', 'd', 'm', '-', 'cn atlètic - barceloneta'], ['balázs szirányi', 'cf', 'm', '-', 'real canoe'], ['guillermo molina', 'cf', 'm', '-', 'pro recco'], ['marc minguell', 'cf', 'm', '-', 'posillipo'], ['blai... |
list of ngc objects ( 2001 - 3000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%282001%E2%80%933000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11097664-8.html.csv | unique | out of this sample of ngc objects from 2700-2799 , ngc 2787 is the only lenticular galaxy . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'lenticular galaxy', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'object type', 'lenticular galaxy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose object type record fuzzily matches to lenticular galaxy .', 'tostr': 'filter_eq { all_rows ; object type ; lenticular galaxy ... | and { only { filter_eq { all_rows ; object type ; lenticular galaxy } } ; eq { hop { filter_eq { all_rows ; object type ; lenticular galaxy } ; ngc number } ; 2787 } } = true | select the rows whose object type record fuzzily matches to lenticular galaxy . there is only one such row in the table . the ngc number record of this unqiue row is 2787 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'object type_7': 7, 'lenticular galaxy_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'ngc number_9': 9, '2787_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'object type_7': 'object type', 'lenticular galaxy_8': 'lenticular galaxy', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'ngc number_9': 'ngc number', '2787_10': '2787'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'object type_7': [0], 'lenticular galaxy_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'ngc number_9': [2], '2787_10': [3]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )'] | [['2715', 'spiral galaxy', 'camelopardalis', '09h08 m06 .1 s', 'degree05 ′ 07 ″'], ['2736', 'diffuse nebula', 'vela', '09h00 m', 'degree57 ′'], ['2770', 'spiral galaxy', 'lynx', '09h09 m33 .7 s', 'degree07 ′ 25 ″'], ['2775', 'spiral galaxy', 'cancer', '09h10 m20 .1 s', 'degree02 ′ 18 ″'], ['2787', 'lenticular galaxy', ... |
2008 japanese motorcycle grand prix | https://en.wikipedia.org/wiki/2008_Japanese_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16882800-1.html.csv | unique | kousuke akiyoshi is the only racer that had an accident in the entire race . | {'scope': 'all', 'row': '19', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'accident', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time ; accident }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; time ; accident } } ; eq { hop { filter_eq { all_rows ; time ; accident } ; rider } ; kousuke akiyoshi } } = true | select the rows whose time record fuzzily matches to accident . there is only one such row in the table . the rider record of this unqiue row is kousuke akiyoshi . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time_7': 7, 'accident_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'rider_9': 9, 'kousuke akiyoshi_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', 'accident_8': 'accident', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'rider_9': 'rider', 'kousuke akiyoshi_10': 'kousuke akiyoshi'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time_7': [0], 'accident_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'rider_9': [2], 'kousuke akiyoshi_10': [3]} | ['rider', 'manufacturer', 'laps', 'time', 'grid'] | [['valentino rossi', 'yamaha', '24', '43:09.599', '4'], ['casey stoner', 'ducati', '24', '+ 1.943', '2'], ['dani pedrosa', 'honda', '24', '+ 4.866', '5'], ['jorge lorenzo', 'yamaha', '24', '+ 6.165', '1'], ['nicky hayden', 'honda', '24', '+ 24.593', '3'], ['loris capirossi', 'suzuki', '24', '+ 25.685', '6'], ['colin ed... |
allegheny mountain collegiate conference | https://en.wikipedia.org/wiki/Allegheny_Mountain_Collegiate_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1971074-1.html.csv | unique | only one public institution that belongs to the allegheny mountain collegiate conference have been founded before 1940 . | {'scope': 'subset', 'row': '7', 'col': '4', 'col_other': '5', 'criterion': 'less_than', 'value': '1940', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'public'}} | {'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'public'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; public }', 'tointer': 'select the rows whose type record fuzzily matches to public .'}, 'founded', '1940'], 'result': None, 'ind'... | only { filter_less { filter_eq { all_rows ; type ; public } ; founded ; 1940 } } = true | select the rows whose type record fuzzily matches to public . among these rows , select the rows whose founded record is less than 1940 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'type_5': 5, 'public_6': 6, 'founded_7': 7, '1940_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'type_5': 'type', 'public_6': 'public', 'founded_7': 'founded', '1940_8': '1940'} | {'only_2': [3], 'result_3': [], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'type_5': [0], 'public_6': [0], 'founded_7': [1], '1940_8': [1]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined'] | [["d'youville college", 'buffalo , new york', 'spartans', '1946', 'private / catholic', '2900', '2009'], ['franciscan university of steubenville', 'steubenville , ohio', 'barons', '1946', 'private / catholic', '2238', '2008'], ['hilbert college', 'hamburg , new york', 'hawks', '1957', 'private / catholic', '1100', '200... |
1971 - 72 philadelphia flyers season | https://en.wikipedia.org/wiki/1971%E2%80%9372_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14293527-13.html.csv | majority | all of the players drafted by the flyers were canadian . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'canada', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to canada .', 'tostr': 'all_eq { all_rows ; nationality ; canada } = true'} | all_eq { all_rows ; nationality ; canada } = true | for the nationality records of all rows , all of them fuzzily match to canada . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'canada_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'canada_4': 'canada'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'canada_4': [0]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'larry wright', 'center', 'canada', 'regina pats ( wchl )'], ['1', 'pierre plante', 'right wing', 'canada', 'drummondville rangers ( qmjhl )'], ['3', 'glen irwin', 'defense', 'canada', 'estevan bruins ( wchl )'], ['4', 'ted scharf', 'right wing', 'canada', 'kitchener rangers ( oha )'], ['5', 'don mcculloch', 'de... |
ningde | https://en.wikipedia.org/wiki/Ningde | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2013618-1.html.csv | aggregation | the average population of administrative regions in ningde is 338662 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '338662', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population'], 'result': '338662', 'ind': 0, 'tostr': 'avg { all_rows ; population }'}, '338662'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population } ; 338662 } = true', 'tointer': 'the average of the population record of all r... | round_eq { avg { all_rows ; population } ; 338662 } = true | the average of the population record of all rows is 338662 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population_4': 4, '338662_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population_4': 'population', '338662_5': '338662'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population_4': [0], '338662_5': [1]} | ['english name', 'simplified', 'traditional', 'pinyin', 'foochow', 'area', 'population', 'density'] | [['jiaocheng district', '蕉城区', '蕉城區', 'jiāochéng qū', 'ciĕu - siàng - kṳ̆', '1537', '429260', '279'], ["fu'an city", '福安市', '福安市', "fú ' ān shì", 'hók - ăng - chê', '1795', '563640', '314'], ['fuding city', '福鼎市', '福鼎市', 'fúdǐng shì', 'hók - tīng - chê', '1526', '529534', '347'], ['xiapu county', '霞浦县', '霞蒲縣', 'xiápǔ x... |
list of ultras of oceania | https://en.wikipedia.org/wiki/List_of_Ultras_of_Oceania | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18946749-5.html.csv | superlative | mount popomanaseu is the peak that has the highest elevation in meters of ultras in oceania . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'elevation ( m )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; elevation ( m ) }'}, 'peak'], 'result': 'mount popomanaseu', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; elevation ( m ) } ; peak }'}, 'mount pop... | eq { hop { argmax { all_rows ; elevation ( m ) } ; peak } ; mount popomanaseu } = true | select the row whose elevation ( m ) record of all rows is maximum . the peak record of this row is mount popomanaseu . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'elevation (m)_5': 5, 'peak_6': 6, 'mount popomanaseu_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'elevation (m)_5': 'elevation ( m )', 'peak_6': 'peak', 'mount popomanaseu_7': 'mount popomanaseu'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'elevation (m)_5': [0], 'peak_6': [1], 'mount popomanaseu_7': [2]} | ['rank', 'peak', 'country', 'island', 'elevation ( m )', 'col ( m )'] | [['1', 'mount popomanaseu', 'solomon islands', 'guadalcanal', '2335', '0'], ['2', 'mont orohena', 'french polynesia', 'tahiti', '2241', '0'], ['3', 'mount tabwemasana', 'vanuatu', 'espiritu santo', '1879', '0'], ['4', 'silisili', 'samoa', "savai'i", '1858', '0'], ['5', 'mount veve', 'solomon islands', 'kolombangara', '... |
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/1-12962773-15.html.csv | majority | the majority of players on the fiba eurobasket 2007 squad play in the guard position . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'guard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them fuzzily match to guard .', 'tostr': 'most_eq { all_rows ; position ; guard } = true'} | most_eq { all_rows ; position ; guard } = true | for the position records of all rows , most of them fuzzily match to guard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'guard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'guard_4': 'guard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'guard_4': [0]} | ['no', 'player', 'height', 'position', 'year born', 'current club'] | [['4', 'marco belinelli', '1.96', 'guard', '1986', 'golden state warriors'], ['5', 'gianluca basile', '1.95', 'guard', '1975', 'axa fc barcelona'], ['6', 'stefano mancinelli', '2.03', 'forward', '1983', 'climamio bologna'], ['7', 'matteo soragna', '1.97', 'guard', '1975', 'benetton treviso'], ['8', 'denis marconato', '... |
2005 cologne centurions season | https://en.wikipedia.org/wiki/2005_Cologne_Centurions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27764201-2.html.csv | aggregation | the average attendance for the 2005 cologne centurions season was around 19000-20000 fans . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '16828.89', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '16828.89', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '16828.89'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 16828.89 } = true', 'tointer': 'the average of the attendance record of... | round_eq { avg { all_rows ; attendance } ; 16828.89 } = true | the average of the attendance record of all rows is 16828.89 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '16828.89_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '16828.89_5': '16828.89'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '16828.89_5': [1]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , april 2', '6:00 pm', 'hamburg sea devils', 'w 24 - 23', '1 - 0', 'rheinenergiestadion', '9468'], ['2', 'sunday , april 10', '4:00 pm', 'rhein fire', 'w 23 - 10', '2 - 0', 'ltu arena', '25304'], ['3', 'saturday , april 16', '6:00 pm', 'frankfurt galaxy', 'w 23 - 14', '3 - 0', 'rheinenergiestadion', '1... |
2009 - 10 washington capitals season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Washington_Capitals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23308178-9.html.csv | majority | in most games , the capitals scored over 100 points . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '100', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'points', '100'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are greater than 100 .', 'tostr': 'most_greater { all_rows ; points ; 100 } = true'} | most_greater { all_rows ; points ; 100 } = true | for the points records of all rows , most of them are greater than 100 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '100_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '100_4': '100'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '100_4': [0]} | ['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points'] | [['63', 'march 3', 'buffalo sabres', '3 - 1', 'hsbc arena', '18690', '42 - 13 - 8', '92'], ['64', 'march 4', 'tampa bay lightning', '5 - 4', 'verizon center', '18277', '43 - 13 - 8', '94'], ['65', 'march 6', 'new york rangers', '2 - 0', 'verizon center', '18277', '44 - 13 - 8', '96'], ['66', 'march 8', 'dallas stars', ... |
ednilson | https://en.wikipedia.org/wiki/Ednilson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17226452-1.html.csv | aggregation | ednilson made a total of 137 apps from 1999 to 2010 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '137', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'apps'], 'result': '137', 'ind': 0, 'tostr': 'sum { all_rows ; apps }'}, '137'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; apps } ; 137 } = true', 'tointer': 'the sum of the apps record of all rows is 137 .'} | round_eq { sum { all_rows ; apps } ; 137 } = true | the sum of the apps record of all rows is 137 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'apps_4': 4, '137_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'apps_4': 'apps', '137_5': '137'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'apps_4': [0], '137_5': [1]} | ['season', 'team', 'country', 'division', 'apps', 'goals'] | [['1999 - 00', 'roma', 'italy', '1', '1', '0'], ['2000 - 01', 'benfica', 'portugal', '1', '13', '0'], ['2001 - 02', 'benfica', 'portugal', '1', '22', '0'], ['2002 - 03', 'benfica', 'portugal', '1', '8', '0'], ['2003 - 04', 'vitória guimarães', 'portugal', '1', '8', '0'], ['2004 - 05', 'gil vicente', 'portugal', '1', '2... |
2008 - 09 los angeles clippers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Los_Angeles_Clippers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17323529-6.html.csv | majority | in the 2008 - 09 los angeles clippers season , in all of the games at staples center , baron davis had the high assists . | {'scope': 'subset', 'col': '7', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'baron davis', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'staples center'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'staples center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; staples center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to staples center .'},... | all_eq { filter_eq { all_rows ; location attendance ; staples center } ; high assists ; baron davis } = true | select the rows whose location attendance record fuzzily matches to staples center . for the high assists records of these rows , all of them fuzzily match to baron davis . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, 'staples center_5': 5, 'high assists_6': 6, 'baron davis_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', 'staples center_5': 'staples center', 'high assists_6': 'high assists', 'baron davis_7': 'baron davis'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], 'staples center_5': [0], 'high assists_6': [1], 'baron davis_7': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['17', 'december 2', 'dallas', 'l 98 - 100 ( ot )', 'zach randolph ( 27 )', 'marcus camby ( 15 )', 'baron davis ( 6 )', 'american airlines center 19670', '3 - 14'], ['18', 'december 3', 'houston', 'l 96 - 103 ( ot )', 'al thornton ( 24 )', 'zach randolph , marcus camby ( 11 )', 'baron davis ( 9 )', 'toyota center 1535... |
2007 - 08 colorado avalanche season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Colorado_Avalanche_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11786147-3.html.csv | unique | the game on september 20 was the only game in which the colorado avalanche decision was made for wall . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'wall', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decision', 'wall'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decision record fuzzily matches to wall .', 'tostr': 'filter_eq { all_rows ; decision ; wall }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; decision ; wall } } ; eq { hop { filter_eq { all_rows ; decision ; wall } ; date } ; september 20 } } = true | select the rows whose decision record fuzzily matches to wall . there is only one such row in the table . the date record of this unqiue row is september 20 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'decision_7': 7, 'wall_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'september 20_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'decision_7': 'decision', 'wall_8': 'wall', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'september 20_10': 'september 20'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'decision_7': [0], 'wall_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'september 20_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'record'] | [['september 17', 'colorado', '4 - 3', 'phoenix', 'weiman', '1 - 0'], ['september 19', 'los angeles', '3 - 6', 'colorado', 'budaj', '2 - 0'], ['september 20', 'colorado', '6 - 3', 'dallas', 'wall', '3 - 0'], ['september 22', 'colorado', '2 - 3', 'los angeles', 'weiman', '3 - 1'], ['september 25', 'dallas', '5 - 4', 'co... |
2005 jeux de la francophonie | https://en.wikipedia.org/wiki/2005_Jeux_de_la_Francophonie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12402019-5.html.csv | aggregation | the nations in the 2005 jeux de la francophonie received an average of 0.4375 gold medals . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '0.4375', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '0.4375', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '0.4375'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; 0.4375 } = true', 'tointer': 'the average of the gold record of all rows is 0.4375 .'} | round_eq { avg { all_rows ; gold } ; 0.4375 } = true | the average of the gold record of all rows is 0.4375 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '0.4375_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '0.4375_5': '0.4375'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '0.4375_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'lebanon', '2', '1', '0', '3'], ['2', 'french community of belgium', '1', '0', '1', '2'], ['3', 'benin', '1', '0', '0', '1'], ['3', 'canada', '1', '0', '0', '1'], ['3', 'lithuania', '1', '0', '0', '1'], ['3', 'madagascar', '1', '0', '0', '1'], ['7', 'france', '0', '1', '1', '2'], ['7', 'niger', '0', '1', '1', '2... |
1975 masters tournament | https://en.wikipedia.org/wiki/1975_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16456989-2.html.csv | majority | in the 1975 masters tournament all of the players come from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; country ; united states } = true'} | all_eq { all_rows ; country ; united states } = true | for the country records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'bobby nichols', 'united states', '67', '- 5'], ['t2', 'allen miller', 'united states', '68', '- 4'], ['t2', 'jack nicklaus', 'united states', '68', '- 4'], ['t4', 'arnold palmer', 'united states', '69', '- 3'], ['t4', 'j c snead', 'united states', '69', '- 3'], ['t4', 'tom weiskopf', 'united states', '69', '- 3... |
bc lietuvos rytas | https://en.wikipedia.org/wiki/BC_Lietuvos_rytas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1771141-1.html.csv | majority | bc lietuvos rytas were not champions in the lkf cup for the majority of seasons . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': 'champion', 'subset': None} | {'func': 'most_str_not_eq', 'args': ['all_rows', 'lkf cup', 'champion'], 'result': True, 'ind': 0, 'tointer': 'for the lkf cup records of all rows , most of them do not match to champion .', 'tostr': 'most_not_eq { all_rows ; lkf cup ; champion } = true'} | most_not_eq { all_rows ; lkf cup ; champion } = true | for the lkf cup records of all rows , most of them do not match to champion . | 1 | 1 | {'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'lkf cup_3': 3, 'champion_4': 4} | {'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'lkf cup_3': 'lkf cup', 'champion_4': 'champion'} | {'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'lkf cup_3': [0], 'champion_4': [0]} | ['season', 'lkf cup', 'regional competitions', 'europe', 'head coach'] | [['1997 - 98', 'champion', '-', 'korać cup group stage', 'modestas paulauskas , alfredas vainauskas'], ['1998 - 99', '-', 'nebl 3rd place', 'saporta cup group stage', 'vainauskas , sakalauskas'], ['1999 - 00', '-', 'nebl finalist', 'saporta cup semifinalist', 'vainauskas , sakalauskas'], ['2000 - 01', '-', 'nebl 3rd pl... |
2005 tim hortons brier | https://en.wikipedia.org/wiki/2005_Tim_Hortons_Brier | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1505809-2.html.csv | ordinal | shawn adams had the second highest shot percentage of players in the 2005 tim hortons brier . | {'row': '3', 'col': '11', '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', 'shot pct', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; shot pct ; 2 }'}, 'skip'], 'result': 'shawn adams', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; shot pct ; 2 } ; skip }'}, 'shawn adams... | eq { hop { nth_argmax { all_rows ; shot pct ; 2 } ; skip } ; shawn adams } = true | select the row whose shot pct record of all rows is 2nd maximum . the skip record of this row is shawn adams . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'shot pct_5': 5, '2_6': 6, 'skip_7': 7, 'shawn adams_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', 'shot pct_5': 'shot pct', '2_6': '2', 'skip_7': 'skip', 'shawn adams_8': 'shawn adams'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'shot pct_5': [0], '2_6': [0], 'skip_7': [1], 'shawn adams_8': [2]} | ['locale', 'skip', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends', 'shot pct'] | [['alberta', 'randy ferbey', '9', '2', '90', '58', '48', '43', '7', '9', '86 %'], ['manitoba', 'randy dutiaume', '8', '3', '77', '69', '47', '44', '10', '13', '79 %'], ['nova scotia', 'shawn adams', '8', '3', '80', '60', '47', '41', '16', '13', '83 %'], ['quebec', 'jean - michel mãnard', '7', '4', '77', '69', '54', '40... |
24th united states congress | https://en.wikipedia.org/wiki/24th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-225200-4.html.csv | unique | the virginia 2nd district seat was the only seat that was not filled during the 24th united states congress . | {'scope': 'all', 'row': '16', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'not filled this congress', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date successor seated', 'not filled this congress'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date successor seated record fuzzily matches to not filled this congress .', 'tostr': 'filter_eq { all_rows ... | and { only { filter_eq { all_rows ; date successor seated ; not filled this congress } } ; eq { hop { filter_eq { all_rows ; date successor seated ; not filled this congress } ; district } ; virginia 2nd } } = true | select the rows whose date successor seated record fuzzily matches to not filled this congress . there is only one such row in the table . the district record of this unqiue row is virginia 2nd . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date successor seated_7': 7, 'not filled this congress_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'district_9': 9, 'virginia 2nd_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date successor seated_7': 'date successor seated', 'not filled this congress_8': 'not filled this congress', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_9': 'district', 'virginia 2nd_10': 'v... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'date successor seated_7': [0], 'not filled this congress_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'district_9': [2], 'virginia 2nd_10': [3]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['south carolina 6th', 'vacant', 'rep warren r davis died during previous congress', 'waddy thompson , jr ( aj )', 'seated september 10 , 1835'], ['georgia at - large', 'vacant', 'rep james m wayne resigned in previous congress', 'jabez y jackson ( j )', 'seated october 5 , 1835'], ['georgia at - large', 'james c terr... |
2005 pga championship | https://en.wikipedia.org/wiki/2005_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12512153-2.html.csv | majority | most of the players in the 2005 pga championship were 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'] | [['steve elkington', 'australia', '1995', '277', '- 3', 't2'], ['davis love iii', 'united states', '1997', '278', '- 2', 't4'], ['tiger woods', 'united states', '1999 , 2000', '278', '- 2', 't4'], ['vijay singh', 'fiji', '1998 , 2004', '280', 'e', 't10'], ['david toms', 'united states', '2001', '280', 'e', 't10'], ['jo... |
narratives of empire | https://en.wikipedia.org/wiki/Narratives_of_Empire | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11251694-1.html.csv | ordinal | of the narratives of empire , the 2nd to last one published was hollywood . | {'row': '5', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'published', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; published ; 2 }'}, 'title'], 'result': 'hollywood', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; published ; 2 } ; title }'}, 'hollywoo... | eq { hop { nth_argmax { all_rows ; published ; 2 } ; title } ; hollywood } = true | select the row whose published record of all rows is 2nd maximum . the title record of this row is hollywood . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'published_5': 5, '2_6': 6, 'title_7': 7, 'hollywood_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', 'published_5': 'published', '2_6': '2', 'title_7': 'title', 'hollywood_8': 'hollywood'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'published_5': [0], '2_6': [0], 'title_7': [1], 'hollywood_8': [2]} | ['order', 'title', 'story timeline', 'published', 'in order of publication'] | [['1', 'burr', '1775 - 1808 , 1833 - 1836 , 1840', '1973', 'second'], ['2', 'lincoln', '1861 - 1865', '1984', 'fourth'], ['3', '1876', '1875 - 1877', '1976', 'third'], ['4', 'empire', '1898 - 1907', '1987', 'fifth'], ['5', 'hollywood', '1917 - 1923', '1990', 'sixth'], ['6', 'washington , dc', '1937 - 1952', '1967', 'fi... |
atlanta falcons draft history | https://en.wikipedia.org/wiki/Atlanta_Falcons_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-17.html.csv | unique | david tolomu was the only running back drafted by the atlanta falcons in 1982 who was taken higher than 100th overall . | {'scope': 'subset', 'row': '7', 'col': '3', 'col_other': '4', 'criterion': 'greater_than', 'value': '100th', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'running back'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'running back'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; running back }', 'tointer': 'select the rows whose position record fuzzily matches to r... | and { only { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } } ; eq { hop { filter_greater { filter_eq { all_rows ; position ; running back } ; overall ; 100th } ; name } ; david tolomu } } = true | select the rows whose position record fuzzily matches to running back . among these rows , select the rows whose overall record is greater than 100th . there is only one such row in the table . the name record of this unqiue row is david tolomu . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'position_8': 8, 'running back_9': 9, 'overall_10': 10, '100th_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'name_12': 12, 'david tolomu_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'position_8': 'position', 'running back_9': 'running back', 'overall_10': 'overall', '100th_11': '100th', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'name_12': 'n... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'position_8': [0], 'running back_9': [0], 'overall_10': [1], '100th_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'name_12': [3], 'david tolomu_13': [4]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '9', '9', 'gerald riggs', 'running back', 'arizona state'], ['2', '9', '36', 'doug rogers', 'defensive end', 'stanford'], ['3', '8', '63', 'stacey bailey', 'wide receiver', 'san jose state'], ['4', '12', '95', 'reggie brown', 'running back', 'oregon'], ['5', '11', '122', 'von mansfield', 'defensive back', 'wisco... |
1981 san francisco 49ers season | https://en.wikipedia.org/wiki/1981_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15353865-2.html.csv | superlative | the san francisco 49ers ' game against the detroit lions recorded the most attendance in the 1981 season . | {'scope': 'all', 'col_superlative': '5', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'detroit lions', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'detroit lions'], 're... | eq { hop { argmax { all_rows ; attendance } ; opponent } ; detroit lions } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is detroit lions . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'detroit lions_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'detroit lions_7': 'detroit lions'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'detroit lions_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 6 , 1981', 'detroit lions', 'l 17 - 24', '63710'], ['2', 'september 13 , 1981', 'chicago bears', 'w 28 - 17', '49520'], ['3', 'september 20 , 1981', 'atlanta falcons', 'l 17 - 34', '56653'], ['4', 'september 27 , 1981', 'new orleans saints', 'w 21 - 14', '44433'], ['5', 'october 4 , 1981', 'washington... |
primera división de fútbol profesional apertura 2008 | https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18522916-4.html.csv | aggregation | the average attendance for matches in the primera división de fútbol profesional apertura 2008 was 6999 . | {'scope': 'all', 'col': '1', 'type': 'average', 'result': '6999', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '6999', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '6999'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 6999 } = true', 'tointer': 'the average of the attendance record of all rows is... | round_eq { avg { all_rows ; attendance } ; 6999 } = true | the average of the attendance record of all rows is 6999 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '6999_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '6999_5': '6999'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '6999_5': [1]} | ['attendance', 'round', 'date', 'home', 'score', 'away', 'venue', 'weekday', 'time of day'] | [['14403', 'final', '21 december 2008', 'chalatenango', '3 - 3', 'metapán', 'estadio cuscatlán', 'sunday', 'afternoon'], ['11463', 'semifinal - 2nd leg', '13 december 2008', 'fas', '1 - 3', 'metapán', 'estadio oscar quiteño', 'saturday', 'night'], ['7690', 'round 2', '6 august 2008', 'águila', '3 - 1', 'fas', 'estadio ... |
circuit des ardennes | https://en.wikipedia.org/wiki/Circuit_des_Ardennes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18893428-1.html.csv | ordinal | the second person to have won the circuit des ardennes was pierre de crawhez . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, 'formula'], 'result': 'grand prix', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 2 } ; formula }'}, 'grand prix'], 'res... | eq { hop { nth_argmin { all_rows ; year ; 2 } ; formula } ; grand prix } = true | select the row whose year record of all rows is 2nd minimum . the formula record of this row is grand prix . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'formula_7': 7, 'grand prix_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'year_5': 'year', '2_6': '2', 'formula_7': 'formula', 'grand prix_8': 'grand prix'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'formula_7': [1], 'grand prix_8': [2]} | ['year', 'formula', 'driver', 'constructor', 'location', 'report'] | [['1902', 'grand prix', 'charles jarrott', 'panhard 70', 'bastogne', 'report'], ['1903', 'grand prix', 'pierre de crawhez', 'panhard 70', 'bastogne', 'report'], ['1904', 'grand prix', 'george heath', 'panhard 70', 'bastogne', 'report'], ['1905', 'grand prix', 'victor hãmery', 'darracq', 'bastogne', 'report'], ['1906', ... |
badminton at the pan american games | https://en.wikipedia.org/wiki/Badminton_at_the_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10371133-1.html.csv | ordinal | united states won the 2nd highest number of bronze medals in badminton at the pan american games . | {'row': '2', 'col': '5', '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', 'bronze', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; bronze ; 2 }'}, 'nation'], 'result': 'united states ( usa )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 2 } ; nation }'}, 'uni... | eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; united states ( usa ) } = true | select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is united states ( usa ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '2_6': 6, 'nation_7': 7, 'united states (usa)_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', 'bronze_5': 'bronze', '2_6': '2', 'nation_7': 'nation', 'united states (usa)_8': 'united states ( usa )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '2_6': [0], 'nation_7': [1], 'united states (usa)_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'canada ( can )', '16', '16', '11', '43'], ['2', 'united states ( usa )', '7', '6', '12', '25'], ['3', 'guatemala ( gua )', '1', '2', '3', '6'], ['4', 'jamaica ( jam )', '1', '0', '5', '6'], ['5', 'cuba ( cub )', '0', '1', '0', '1'], ['6', 'peru ( per )', '0', '0', '14', '14'], ['7', 'mexico ( mex )', '0', '0', ... |
south wales derby | https://en.wikipedia.org/wiki/South_Wales_derby | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15473253-4.html.csv | unique | the league competition was the only competition with 16 draws . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '16', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'draw', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose draw record is equal to 16 .', 'tostr': 'filter_eq { all_rows ; draw ; 16 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; draw ... | and { only { filter_eq { all_rows ; draw ; 16 } } ; eq { hop { filter_eq { all_rows ; draw ; 16 } ; competition } ; league } } = true | select the rows whose draw record is equal to 16 . there is only one such row in the table . the competition record of this unqiue row is league . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'draw_7': 7, '16_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'competition_9': 9, 'league_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'draw_7': 'draw', '16_8': '16', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'competition_9': 'competition', 'league_10': 'league'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'draw_7': [0], '16_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'competition_9': [2], 'league_10': [3]} | ['competition', 'total matches', 'cardiff win', 'draw', 'swansea win'] | [['league', '55', '19', '16', '20'], ['fa cup', '2', '0', '0', '2'], ['league cup', '5', '2', '0', '3'], ['associate members cup', '4', '1', '1', '2'], ['welsh cup / faw premier cup', '36', '21', '8', '7'], ['southern league', '4', '1', '2', '1'], ['total', '106', '44', '27', '35']] |
list of rampage killers | https://en.wikipedia.org/wiki/List_of_rampage_killers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17794738-5.html.csv | ordinal | ernst august wagner 's rampage killing spree is the second oldest rampage . | {'row': '5', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, 'perpetrator'], 'result': 'wagner , ernst august , 38', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 2 } ; perpetrator ... | eq { hop { nth_argmin { all_rows ; year ; 2 } ; perpetrator } ; wagner , ernst august , 38 } = true | select the row whose year record of all rows is 2nd minimum . the perpetrator record of this row is wagner , ernst august , 38 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'perpetrator_7': 7, 'wagner , ernst august , 38_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'year_5': 'year', '2_6': '2', 'perpetrator_7': 'perpetrator', 'wagner , ernst august , 38_8': 'wagner , ernst august , 38'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'perpetrator_7': [1], 'wagner , ernst august , 38_8': [2]} | ['perpetrator', 'date', 'year', 'location', 'country', 'killed', 'injured'] | [['grachev , peter', '07.31 july 31', '1925', 'ivankovo', 'soviet union', '17', '03 3'], ['ryan , michael robert , 27', '08.19 aug 19', '1987', 'hungerford', 'united kingdom', '16', '15'], ['borel , eric , 16', '09.23 sep 23 / 24', '1995', 'solliès - pont & cuers', 'france', '15', '04 4'], ['leibacher , friedrich , 57'... |
2005 african judo championships | https://en.wikipedia.org/wiki/2005_African_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10642140-3.html.csv | unique | morocco is the only team to have more than 6 bronze medals in the tournament . | {'scope': 'all', 'row': '9', 'col': '5', 'col_other': '2', 'criterion': 'greater_than', 'value': '6', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'bronze', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bronze record is greater than 6 .', 'tostr': 'filter_greater { all_rows ; bronze ; 6 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_grea... | and { only { filter_greater { all_rows ; bronze ; 6 } } ; eq { hop { filter_greater { all_rows ; bronze ; 6 } ; nation } ; morocco } } = true | select the rows whose bronze record is greater than 6 . there is only one such row in the table . the nation record of this unqiue row is morocco . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'bronze_7': 7, '6_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'morocco_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'bronze_7': 'bronze', '6_8': '6', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'morocco_10': 'morocco'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'bronze_7': [0], '6_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'morocco_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'algeria', '9', '2', '5', '16'], ['2', 'tunisia', '4', '6', '6', '16'], ['3', 'egypt', '3', '3', '1', '7'], ['4', 'senegal', '1', '2', '4', '7'], ['5', 'angola', '1', '0', '0', '1'], ['6', 'south africa', '0', '3', '1', '4'], ['7', 'nigeria', '0', '1', '2', '3'], ['8', 'niger', '0', '1', '0', '1'], ['9', 'morocc... |
miss world | https://en.wikipedia.org/wiki/Miss_World | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-150343-3.html.csv | ordinal | the country with the 2nd highest number of miss world semi finalists is south africa . | {'row': '8', 'col': '10', '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', 'semifinalists', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; semifinalists ; 2 }'}, 'country / territory'], 'result': 'south africa', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; semifinalists... | eq { hop { nth_argmax { all_rows ; semifinalists ; 2 } ; country / territory } ; south africa } = true | select the row whose semifinalists record of all rows is 2nd maximum . the country / territory record of this row is south africa . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'semifinalists_5': 5, '2_6': 6, 'country / territory_7': 7, 'south africa_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', 'semifinalists_5': 'semifinalists', '2_6': '2', 'country / territory_7': 'country / territory', 'south africa_8': 'south africa'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'semifinalists_5': [0], '2_6': [0], 'country / territory_7': [1], 'south africa_8': [2]} | ['rank', 'country / territory', 'miss world', '1st runner - up', '2nd runner - up', '3rd runner - up', '4th runner - up', '5th runner - up', '6th runner - up', 'semifinalists', 'total'] | [['1', 'venezuela', '6', '2', '4', '2', '2', '0', '1', '14', '30'], ['2', 'united kingdom', '5', '6', '4', '3', '3', '1', '1', '14', '37'], ['3', 'india', '5', '1', '0', '1', '1', '0', '0', '12', '20'], ['4', 'united states', '3', '5', '2', '0', '6', '2', '1', '25', '44'], ['5', 'sweden', '3', '1', '0', '2', '2', '2', ... |
ice hockey at the 2010 winter olympics - women 's tournament | https://en.wikipedia.org/wiki/Ice_hockey_at_the_2010_Winter_Olympics_%E2%80%93_Women%27s_tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18803620-4.html.csv | aggregation | the total number of goals scored by canadian players at the 2010 winter olympics women 's ice hockey tournament is 26 . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '26', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': '( can )'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', '( can )'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; player ; ( can ) }', 'tointer': 'select the rows whose player record fuzzily matches to ( can ) .'}, 'goals'], 'result': '26', 'ind': 1, ... | round_eq { sum { filter_eq { all_rows ; player ; ( can ) } ; goals } ; 26 } = true | select the rows whose player record fuzzily matches to ( can ) . the sum of the goals record of these rows is 26 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'player_5': 5, '( can )_6': 6, 'goals_7': 7, '26_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'player_5': 'player', '( can )_6': '( can )', 'goals_7': 'goals', '26_8': '26'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'player_5': [0], '( can )_6': [0], 'goals_7': [1], '26_8': [2]} | ['rank', 'player', 'games played', 'goals', 'assists'] | [['1', 'meghan agosta ( can )', '5', '9', '6'], ['2', 'jayna hefford ( can )', '5', '5', '7'], ['3', 'stefanie marty ( sui )', '5', '9', '2'], ['4', 'jenny potter ( usa )', '5', '6', '5'], ['5', 'natalie darwitz ( usa )', '5', '4', '7'], ['6', 'caroline ouellette ( can )', '5', '2', '9'], ['6', 'hayley wickenheiser ( c... |
2008 - 09 phoenix suns season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-9.html.csv | count | in the 2008 - 09 phoenix suns season , when steve nash had the high assists , six of the games were at us airways center . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'us airways center', 'result': '6', 'col': '8', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'steve nash'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'steve nash'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high assists ; steve nash }', 'tointer': 'select the rows whose high assists record fuzzily match... | eq { count { filter_eq { filter_eq { all_rows ; high assists ; steve nash } ; location attendance ; us airways center } } ; 6 } = true | select the rows whose high assists record fuzzily matches to steve nash . among these rows , select the rows whose location attendance record fuzzily matches to us airways center . the number of such rows is 6 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'high assists_6': 6, 'steve nash_7': 7, 'location attendance_8': 8, 'us airways center_9': 9, '6_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'high assists_6': 'high assists', 'steve nash_7': 'steve nash', 'location attendance_8': 'location attendance', 'us airways center_9': 'us airways center', '6_10': '6'... | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'high assists_6': [0], 'steve nash_7': [0], 'location attendance_8': [1], 'us airways center_9': [1], '6_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 1', 'la lakers', 'w 118 - 111 ( ot )', "shaquille o'neal ( 33 )", 'matt barnes ( 10 )', 'matt barnes , leandro barbosa ( 7 )', 'us airways center 18422', '34 - 25'], ['60', 'march 3', 'orlando', 'l 99 - 111 ( ot )', 'jason richardson ( 27 )', "shaquille o'neal ( 11 )", 'steve nash ( 8 )', 'amway arena 17... |
1986 san francisco 49ers season | https://en.wikipedia.org/wiki/1986_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16714751-1.html.csv | superlative | the largest crowd occurred when the date was september 28th , 1986 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'september 28 , 1986', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'september 28 , 1986'],... | eq { hop { argmax { all_rows ; attendance } ; date } ; september 28 , 1986 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is september 28 , 1986 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'september 28 , 1986_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', 'september 28 , 1986_7': 'september 28 , 1986'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'september 28 , 1986_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 7 , 1986', 'tampa bay buccaneers', 'w 31 - 7', '50780'], ['2', 'september 14 , 1986', 'los angeles rams', 'l 13 - 16', '65195'], ['3', 'september 21 , 1986', 'new orleans saints', 'w 26 - 17', '58297'], ['4', 'september 28 , 1986', 'miami dolphins', 'w 31 - 16', '70264'], ['5', 'october 5 , 1986', 'in... |
calgary - edmonton corridor | https://en.wikipedia.org/wiki/Calgary%E2%80%93Edmonton_Corridor | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2134521-1.html.csv | ordinal | in the calgary - edmonton corridor , division no 11 has the highest area ( km square ) among those with pop ( 1996 ) less than 1000000 . | {'scope': 'subset', 'row': '3', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '6', 'criterion': 'less_than', 'value': '1000000'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'pop ( 1996 )', '1000000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; pop ( 1996 ) ; 1000000 }', 'tointer': 'select the rows whose pop ( 1996 ) record is less than 100... | eq { hop { nth_argmax { filter_less { all_rows ; pop ( 1996 ) ; 1000000 } ; area ( km square ) ; 1 } ; census division } ; division no 11 } = true | select the rows whose pop ( 1996 ) record is less than 1000000 . select the row whose area ( km square ) record of these rows is 1st maximum . the census division record of this row is division no 11 . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'pop (1996)_6': 6, '1000000_7': 7, 'area (km square)_8': 8, '1_9': 9, 'census division_10': 10, 'division no 11_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'pop (1996)_6': 'pop ( 1996 )', '1000000_7': '1000000', 'area (km square)_8': 'area ( km square )', '1_9': '1', 'census division_10': 'census division', 'division no... | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'pop (1996)_6': [0], '1000000_7': [0], 'area (km square)_8': [1], '1_9': [1], 'census division_10': [2], 'division no 11_11': [3]} | ['census division', 'area ( km square )', 'pop ( 2011 )', 'pop ( 2006 )', 'pop ( 2001 )', 'pop ( 1996 )'] | [['division no 6', '12645.88', '1311022', '1160936', '1021060', '880859'], ['division no 8', '9909.31', '189243', '175337', '153049', '133592'], ['division no 11', '15767.99', '1203115', '1076103', '975477', '898888'], ['calgary - edmonton corridor', '38323.18', '2703380', '2412376', '2149586', '1913339'], ['province o... |
1963 in brazilian football | https://en.wikipedia.org/wiki/1963_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15244400-2.html.csv | majority | most of the teams with less than 10 points had a negative goal difference in 1963 season of brazilian football . | {'scope': 'subset', 'col': '8', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '-', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '10'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; points ; 10 }', 'tointer': 'select the rows whose points record is less than 10 .'}, 'difference', '-'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose... | most_eq { filter_less { all_rows ; points ; 10 } ; difference ; - } = true | select the rows whose points record is less than 10 . for the difference records of these rows , most of them fuzzily match to - . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'points_4': 4, '10_5': 5, 'difference_6': 6, '-_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'points_4': 'points', '10_5': '10', 'difference_6': 'difference', '-_7': '-'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'points_4': [0], '10_5': [0], 'difference_6': [1], '-_7': [1]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'santos', '13', '9', '1', '2', '15', '15'], ['2', 'corinthians', '12', '9', '0', '3', '9', '8'], ['3', 'fluminense', '11', '9', '3', '2', '12', '1'], ['4', 'botafogo', '10', '9', '4', '2', '14', '2'], ['5', 'palmeiras', '10', '9', '2', '3', '12', '0'], ['6', 'portuguesa', '9', '9', '3', '3', '21', '- 3'], ['7', ... |
1988 green bay packers season | https://en.wikipedia.org/wiki/1988_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14650373-1.html.csv | comparative | patrick collins was picked by the packers after sterling sharpe had been picked . | {'row_1': '8', 'row_2': '1', 'col': '1', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'patrick collins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to patrick collins .', 'tostr': 'filter_eq { all_rows ; player ; patrick collins }'}, 'pick'], ... | greater { hop { filter_eq { all_rows ; player ; patrick collins } ; pick } ; hop { filter_eq { all_rows ; player ; sterling sharpe } ; pick } } = true | select the rows whose player record fuzzily matches to patrick collins . take the pick record of this row . select the rows whose player record fuzzily matches to sterling sharpe . take the pick 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, 'player_7': 7, 'patrick collins_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'sterling sharpe_12': 12, 'pick_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', 'player_7': 'player', 'patrick collins_8': 'patrick collins', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player',... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'patrick collins_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'sterling sharpe_12': [1], 'pick_13': [3]} | ['pick', 'nfl team', 'player', 'position', 'college'] | [['7', 'green bay packers', 'sterling sharpe', 'wide receiver', 'south carolina'], ['34', 'green bay packers', 'shawn patterson', 'defensive end', 'arizona state'], ['61', 'green bay packers', 'keith woodside', 'running back', 'texas a & m'], ['88', 'green bay packers', 'rollin putzier', 'nose tackle', 'oregon'], ['89'... |
1976 oakland raiders season | https://en.wikipedia.org/wiki/1976_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12293930-1.html.csv | comparative | the oakland raiders drafted dwight lewis earlier than they drafted doug hogan . | {'row_1': '9', 'row_2': '16', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'dwight lewis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to dwight lewis .', 'tostr': 'filter_eq { all_rows ; player ; dwight lewis }... | and { less { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; hop { filter_eq { all_rows ; player ; doug hogan } ; round } } ; and { eq { hop { filter_eq { all_rows ; player ; dwight lewis } ; round } ; 10 } ; eq { hop { filter_eq { all_rows ; player ; doug hogan } ; round } ; 16 } } } = true | select the rows whose player record fuzzily matches to dwight lewis . take the round record of this row . select the rows whose player record fuzzily matches to doug hogan . take the round record of this row . the first record is less than the second record . the round record of the first row is 10 . the round record o... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'player_11': 11, 'dwight lewis_12': 12, 'round_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'player_15': 15, 'doug hogan_16': 16, 'round_17': 17, 'and_7': 7, 'eq_5': 5, '10_18': 18, 'eq_6': 6, '16_19':... | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'dwight lewis_12': 'dwight lewis', 'round_13': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'player_15':... | {'and_8': [9], 'result_9': [], 'less_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'player_11': [0], 'dwight lewis_12': [0], 'round_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'player_15': [1], 'doug hogan_16': [1], 'round_17': [3], 'and_7': [8], 'eq_5': [7], '... | ['round', 'overall', 'player', 'position', 'college'] | [['2', '34', 'charles philyaw', 'de', 'texas southern'], ['2', '50', 'jeb blount', 'qb', 'tulsa'], ['3', '84', 'rik bonness', 'lb', 'nebraska'], ['4', '110', 'herb mcmath', 'de', 'morningside'], ['5', '146', 'fred steinfort', 'k', 'boston college'], ['7', '204', 'clarence chapman', 'wr', 'eastern michigan'], ['8', '220... |
mike van arsdale | https://en.wikipedia.org/wiki/Mike_van_Arsdale | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14344822-2.html.csv | comparative | mike van arsdale 's fight against chris haseman lasted one more round than his fight against wanderlei silva . | {'row_1': '8', 'row_2': '9', 'col': '5', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'chris haseman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to chris haseman .', 'tostr': 'filter_eq { all_rows ; opponent ; chris h... | eq { diff { hop { filter_eq { all_rows ; opponent ; chris haseman } ; round } ; hop { filter_eq { all_rows ; opponent ; wanderlei silva } ; round } } ; 1 } = true | select the rows whose opponent record fuzzily matches to chris haseman . take the round record of this row . select the rows whose opponent record fuzzily matches to wanderlei silva . take the round record of this row . the first record is 1 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'opponent_8': 8, 'chris haseman_9': 9, 'round_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'opponent_12': 12, 'wanderlei silva_13': 13, 'round_14': 14, '1_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'opponent_8': 'opponent', 'chris haseman_9': 'chris haseman', 'round_10': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'opponent_1... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'opponent_8': [0], 'chris haseman_9': [0], 'round_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'opponent_12': [1], 'wanderlei silva_13': [1], 'round_14': [3], '1_15': [5]} | ['res', 'record', 'opponent', 'method', 'round', 'time', 'location'] | [['loss', '8 - 5', 'matt lindland', 'submission ( guillotine choke )', '1', '3:38', 'california , united states'], ['loss', '8 - 4', 'jorge oliveira', 'submission ( triangle choke )', '1', '4:02', 'idaho , united states'], ['loss', '8 - 3', 'renato sobral', 'submission ( rear naked choke )', '1', '2:21', 'nevada , unit... |
fundraising for the 2008 united states presidential election | https://en.wikipedia.org/wiki/Fundraising_for_the_2008_United_States_presidential_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12030247-4.html.csv | aggregation | candidates in the 2008 united states presidential election averaged 12444351 in total receipts . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '12444351', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total receipts'], 'result': '12444351', 'ind': 0, 'tostr': 'avg { all_rows ; total receipts }'}, '12444351'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total receipts } ; 12444351 } = true', 'tointer': 'the average of the total re... | round_eq { avg { all_rows ; total receipts } ; 12444351 } = true | the average of the total receipts record of all rows is 12444351 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total receipts_4': 4, '12444351_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total receipts_4': 'total receipts', '12444351_5': '12444351'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total receipts_4': [0], '12444351_5': [1]} | ['candidate', 'total receipts', 'loans received', 'receipts w / o loans', 'money spent', 'cash on hand', 'total debt', 'cash on hand minus debt'] | [['hillary clinton', '27339347', '0', '26776409', '39886410', '37947874', '4987425', '32960449'], ['barack obama', '23526004', '0', '22847568', '40896076', '18626248', '792681', '17833567'], ['john edwards', '13900622', '8974714', '4834761', '18537625', '7790458', '9067278', '- 1276820'], ['joe biden', '3190122', '1132... |
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/1-12962773-1.html.csv | aggregation | the average height of the players was 2.01 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '2.01', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height'], 'result': '2.01', 'ind': 0, 'tostr': 'avg { all_rows ; height }'}, '2.01'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height } ; 2.01 } = true', 'tointer': 'the average of the height record of all rows is 2.01 .'} | round_eq { avg { all_rows ; height } ; 2.01 } = true | the average of the height record of all rows is 2.01 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height_4': 4, '2.01_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height_4': 'height', '2.01_5': '2.01'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height_4': [0], '2.01_5': [1]} | ['no', 'player', 'height', 'position', 'year born', 'current club'] | [['4', 'theodoros papaloukas', '2.00', 'guard', '1977', 'cska moscow'], ['5', 'ioannis bourousis', '2.13', 'center', '1983', 'olympiacos'], ['6', 'nikolaos zisis', '1.95', 'guard', '1983', 'cska moscow'], ['7', 'vasileios spanoulis', '1.92', 'guard', '1982', 'panathinaikos'], ['8', 'panagiotis vasilopoulos', '2.01', 'f... |
list of nuclear weapons tests | https://en.wikipedia.org/wiki/List_of_nuclear_weapons_tests | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2189647-1.html.csv | count | between 1952 and 1962 , the soviet union carried out 7 nuclear weapons tests . | {'scope': 'all', 'criterion': 'equal', 'value': 'soviet union', 'result': '7', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'soviet union'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to soviet union .', 'tostr': 'filter_eq { all_rows ; country ; soviet union }'}], 'result': '7', 'ind':... | eq { count { filter_eq { all_rows ; country ; soviet union } } ; 7 } = true | select the rows whose country record fuzzily matches to soviet union . 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, 'country_5': 5, 'soviet union_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', 'country_5': 'country', 'soviet union_6': 'soviet union', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'soviet union_6': [0], '7_7': [2]} | ['date ( gmt )', 'yield ( megatons )', 'deployment', 'country', 'test site', 'name or number'] | [['october 30 , 1961', '50', 'parachute air drop', 'soviet union', 'novaya zemlya', 'tsar bomba , test 130'], ['december 24 , 1962', '24.2', 'air drop', 'soviet union', 'novaya zemlya', 'test 219'], ['august 5 , 1962', '21.1', 'air drop', 'soviet union', 'novaya zemlya', 'test 147'], ['september 27 , 1962', '20.0', 'ai... |
vuelta a españa records and statistics | https://en.wikipedia.org/wiki/Vuelta_a_Espa%C3%B1a_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18676973-3.html.csv | superlative | spain has more vuelta wins than any other team in the espana records . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'vuelta wins'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; vuelta wins }'}, 'country'], 'result': 'spain', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; vuelta wins } ; country }'}, 'spain'], 'result': True, 'i... | eq { hop { argmax { all_rows ; vuelta wins } ; country } ; spain } = true | select the row whose vuelta wins record of all rows is maximum . the country record of this row is spain . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'vuelta wins_5': 5, 'country_6': 6, 'spain_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'vuelta wins_5': 'vuelta wins', 'country_6': 'country', 'spain_7': 'spain'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'vuelta wins_5': [0], 'country_6': [1], 'spain_7': [2]} | ['rank', 'country', 'jerseys', 'vuelta wins', 'points', "combo '", 'different holders'] | [['1', 'spain', '631', '31', '15', '12', '85'], ['2', 'france', '155', '9', '5', '2', '24'], ['3', 'belgium', '140', '7', '13', '2', '26'], ['4', 'italy', '100', '5', '4', '1', '18'], ['5', 'switzerland', '89', '5', '2', '1', '5'], ['6', 'germany', '50', '4', '7', '0', '7'], ['7', 'netherlands', '45', '2', '5', '0', '1... |
list of hartford whalers draft picks | https://en.wikipedia.org/wiki/List_of_Hartford_Whalers_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18278177-5.html.csv | count | out of all the players to be picked for nhl team hartford whalers , only 5 of them came from canada . | {'scope': 'all', 'criterion': 'equal', 'value': 'canada', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nationality ; canada }'}], 'result': '5', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; nationality ; canada } } ; 5 } = true | select the rows whose nationality record fuzzily matches to canada . 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, 'nationality_5': 5, 'canada_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', 'nationality_5': 'nationality', 'canada_6': 'canada', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'canada_6': [0], '5_7': [2]} | ['pick', 'player', 'position', 'nationality', 'nhl team', 'college / junior / club team'] | [['11', 'chris govedaris', 'left wing', 'canada', 'hartford whalers', 'toronto marlboros ( ohl )'], ['32', 'barry richter', 'defence', 'united states', 'hartford whalers', 'culver military academy ( ushs - in )'], ['74', 'dean dyer', 'centre', 'canada', 'hartford whalers', 'lake superior state university ( ncaa )'], ['... |
2008 - 09 detroit red wings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17371135-30.html.csv | count | two of the red wings players from the 2008-2009 season were from canada . | {'scope': 'all', 'criterion': 'equal', 'value': 'canada', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nationality ; canada }'}], 'result': '2', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; nationality ; canada } } ; 2 } = true | select the rows whose nationality record fuzzily matches to canada . 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, 'nationality_5': 5, 'canada_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', 'nationality_5': 'nationality', 'canada_6': 'canada', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'canada_6': [0], '2_7': [2]} | ['round', 'overall pick', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', '30', 'thomas mccollum', 'goaltender', 'united states', 'guelph storm ( ohl )'], ['3', '91', 'max nicastro', 'defenseman', 'united states', 'chicago steel ( ushl )'], ['4', '121', 'gustav nyquist', 'center', 'sweden', 'malmã redhawks ( sweden jr )'], ['5', '151', 'julien cayer', 'center', 'canada', 'northwood sc... |
türk telekom arena | https://en.wikipedia.org/wiki/T%C3%BCrk_Telekom_Arena | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12243387-1.html.csv | majority | all the plans for the türk telekom arena called for at least 125 suites . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '125', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'suites', '125'], 'result': True, 'ind': 0, 'tointer': 'for the suites records of all rows , most of them are greater than or equal to 125 .', 'tostr': 'most_greater_eq { all_rows ; suites ; 125 } = true'} | most_greater_eq { all_rows ; suites ; 125 } = true | for the suites records of all rows , most of them are greater than or equal to 125 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'suites_3': 3, '125_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'suites_3': 'suites', '125_4': '125'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'suites_3': [0], '125_4': [0]} | ['project', 'year', 'location', 'capacity', 'suites', 'architect', 'cost'] | [['faruk süren project', '1997 - 2001', 'mecidiyeköy', '40482', '125 + 72 boxes without outside seating', 'bbb architects', '118.5 million ( in 2014 dollars )'], ['mehmet cansun project', '2001', 'mecidiyeköy', '35000', '132', 'gs member architecture group', '35 million ( in 2014 dollars )'], ["özhan canaydın : back to... |
raman vasilyuk | https://en.wikipedia.org/wiki/Raman_Vasilyuk | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17373851-1.html.csv | comparative | raman vasilyuk scored international goals in the games played on 16 august 2000 and 22 august 2007 that were both friendly competitions . | {'row_1': '1', 'row_2': '9', 'col': '5', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '16 august 2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 16 august 2000 .', 'tostr': 'filter_eq { all_rows ; date ; 16 august 2000... | and { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competition } } ; and { eq { hop { filter_eq { all_rows ; date ; 16 august 2000 } ; competition } ; friendly } ; eq { hop { filter_eq { all_rows ; date ; 22 august 2007 } ; competitio... | select the rows whose date record fuzzily matches to 16 august 2000 . take the competition record of this row . select the rows whose date record fuzzily matches to 22 august 2007 . take the competition record of this row . the first record fuzzily matches to the second record . the competition record of the first row ... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'date_11': 11, '16 august 2000_12': 12, 'competition_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'date_15': 15, '22 august 2007_16': 16, 'competition_17': 17, 'and_7': 7, 'str_eq_5': 5, 'friendly_18... | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '16 august 2000_12': '16 august 2000', 'competition_13': 'competition', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_row... | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'date_11': [0], '16 august 2000_12': [0], 'competition_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'date_15': [1], '22 august 2007_16': [1], 'competition_17': [3], 'and_7': [8]... | ['date', 'venue', 'score', 'result', 'competition'] | [['16 august 2000', 'skonto stadium , riga , latvia', '1 - 0', '1 - 0', 'friendly'], ['28 march 2001', 'dynama stadium ( minsk ) , belarus', '2 - 1', '2 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dynama stadium ( minsk ) , belarus', '1 - 0', '4 - 1', '2002 world cup qualifier'], ['5 september 2001', 'dyna... |
list of superfund sites in connecticut | https://en.wikipedia.org/wiki/List_of_Superfund_sites_in_Connecticut | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10840672-1.html.csv | majority | most of sites in new haven county were proposed earlier than 2000 in the list of superfund sites in connecticut . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2000', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'new haven'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'new haven'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; county ; new haven }', 'tointer': 'select the rows whose county record fuzzily matches to new haven .'}, 'proposed', '2000'], 'result': True, 'ind': 1, 'tointe... | most_less { filter_eq { all_rows ; county ; new haven } ; proposed ; 2000 } = true | select the rows whose county record fuzzily matches to new haven . for the proposed records of these rows , most of them are less than 2000 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'county_4': 4, 'new haven_5': 5, 'proposed_6': 6, '2000_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'county_4': 'county', 'new haven_5': 'new haven', 'proposed_6': 'proposed', '2000_7': '2000'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'county_4': [0], 'new haven_5': [0], 'proposed_6': [1], '2000_7': [1]} | ['cerclis id', 'name', 'county', 'proposed', 'listed', 'construction completed', 'partially deleted', 'deleted'] | [['ctd980670814', 'kellogg - deering well field', 'fairfield', '09 / 08 / 1983', '09 / 21 / 1984', '09 / 23 / 1996', 'n / a', 'n / a'], ['ctd001186618', 'raymark industries , inc', 'fairfield', '01 / 18 / 1994', '04 / 25 / 1995', 'n / a', 'n / a', 'n / a'], ['ct0002055887', 'broad brook mill', 'hartford', '12 / 01 / 20... |
usa today all - usa high school baseball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-4.html.csv | count | two of the players on the usa today all-usa team were from ca . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'ca', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'hometown', 'ca'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose hometown record fuzzily matches to ca .', 'tostr': 'filter_eq { all_rows ; hometown ; ca }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; hometown ; ca } } ; 2 } = true | select the rows whose hometown record fuzzily matches to ca . 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, 'hometown_5': 5, 'ca_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', 'hometown_5': 'hometown', 'ca_6': 'ca', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'hometown_5': [0], 'ca_6': [0], '2_7': [2]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['drew henson', 'infielder', 'brighton high school', 'brighton , mi', '3rd round - 97th pick of 1998 draft ( yankees )'], ['josh beckett', 'pitcher', 'spring high school', 'spring , tx', 'beckett was a junior in the 1998 season'], ['j m gold', 'pitcher', 'toms river high school north', 'toms river , nj', '1st round - ... |
ace ( tennis ) | https://en.wikipedia.org/wiki/Ace_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1612222-1.html.csv | ordinal | of the players that served aces in wimbledon , john isner served the most . | {'scope': 'subset', 'row': '1', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'wimbledon'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'wimbledon'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; event ; wimbledon }', 'tointer': 'select the rows whose event record fuzzily matches to wimbledon .'},... | eq { hop { nth_argmax { filter_eq { all_rows ; event ; wimbledon } ; aces ; 1 } ; player } ; john isner } = true | select the rows whose event record fuzzily matches to wimbledon . select the row whose aces record of these rows is 1st maximum . the player record of this row is john isner . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'event_6': 6, 'wimbledon_7': 7, 'aces_8': 8, '1_9': 9, 'player_10': 10, 'john isner_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'event_6': 'event', 'wimbledon_7': 'wimbledon', 'aces_8': 'aces', '1_9': '1', 'player_10': 'player', 'john isner_11': 'john isner'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'event_6': [0], 'wimbledon_7': [0], 'aces_8': [1], '1_9': [1], 'player_10': [2], 'john isner_11': [3]} | ['aces', 'player', 'opponent', 'event', 'sets'] | [['113', 'john isner', 'nicolas mahut', '2010 wimbledon', '5'], ['103', 'nicolas mahut', 'john isner', '2010 wimbledon', '5'], ['78', 'ivo karlović', 'radek štěpánek', '2009 davis cup', '5'], ['55', 'ivo karlović', 'lleyton hewitt', '2009 roland garros', '5'], ['54', 'gary muller', 'peter lundgren', '1993 wimbledon', '... |
2005 philadelphia barrage season | https://en.wikipedia.org/wiki/2005_Philadelphia_Barrage_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12075099-1.html.csv | majority | the majority of games ended in losses for the philadelphia barrage . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'} | most_eq { all_rows ; result ; l } = true | for the result 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, 'result_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]} | ['date', 'opponent', 'home / away', 'field', 'result'] | [['may 29', 'cannons', 'home', 'villanova stadium', 'l 12 - 13'], ['june 4', 'lizards', 'home', 'villanova stadium', 'l 14 - 19'], ['june 12', 'bayhawks', 'away', 'johnny unitas stadium', 'l 9 - 31'], ['june 18', 'pride', 'away', 'alumni stadium ( kean university )', 'w 11 - 10'], ['june 25', 'lizards', 'away', 'mitche... |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-21.html.csv | aggregation | in the 1972 vfl season , the average score for home teams was 17.67 points . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '17.67', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'home team score'], 'result': '17.67', 'ind': 0, 'tostr': 'avg { all_rows ; home team score }'}, '17.67'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; home team score } ; 17.67 } = true', 'tointer': 'the average of the home team scor... | round_eq { avg { all_rows ; home team score } ; 17.67 } = true | the average of the home team score record of all rows is 17.67 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'home team score_4': 4, '17.67_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'home team score_4': 'home team score', '17.67_5': '17.67'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'home team score_4': [0], '17.67_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '17.22 ( 124 )', 'north melbourne', '14.7 ( 91 )', 'mcg', '11241', '26 august 1972'], ['footscray', '17.21 ( 123 )', 'richmond', '18.17 ( 125 )', 'western oval', '18117', '26 august 1972'], ['collingwood', '22.17 ( 149 )', 'south melbourne', '11.6 ( 72 )', 'victoria park', '19934', '26 august 1972'], ['c... |
united states house of representatives elections , 1888 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1888 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431459-6.html.csv | ordinal | the incumbent from the third district of south carolina was the latest seated candidate in office in the 1888 united states house of representatives elections . | {'row': '3', 'col': '4', 'order': '7', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 7 }'}, 'district'], 'result': 'south carolina 3', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 7 } ... | eq { hop { nth_argmin { all_rows ; first elected ; 7 } ; district } ; south carolina 3 } = true | select the row whose first elected record of all rows is 7th minimum . the district record of this row is south carolina 3 . | 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, '7_6': 6, 'district_7': 7, 'south carolina 3_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', '7_6': '7', 'district_7': 'district', 'south carolina 3_8': 'south carolina 3'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '7_6': [0], 'district_7': [1], 'south carolina 3_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['south carolina 1', 'samuel dibble', 'democratic', '1882', 're - elected'], ['south carolina 2', 'george d tillman', 'democratic', '1878', 're - elected'], ['south carolina 3', 'james s cothran', 'democratic', '1886', 're - elected'], ['south carolina 4', 'william h perry', 'democratic', '1884', 're - elected'], ['so... |
list of the colbert report episodes ( 2010 ) | https://en.wikipedia.org/wiki/List_of_The_Colbert_Report_episodes_%282010%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25691838-12.html.csv | unique | episode 806 of the colbert report was the only episode to have garry trudeau as a guest . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'garry trudeau', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'guest', 'garry trudeau'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose guest record fuzzily matches to garry trudeau .', 'tostr': 'filter_eq { all_rows ; guest ; garry trudeau }'}], 'result': True, 'ind': 1... | and { only { filter_eq { all_rows ; guest ; garry trudeau } } ; eq { hop { filter_eq { all_rows ; guest ; garry trudeau } ; episode } ; 806 } } = true | select the rows whose guest record fuzzily matches to garry trudeau . there is only one such row in the table . the episode record of this unqiue row is 806 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'guest_7': 7, 'garry trudeau_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'episode_9': 9, '806_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'guest_7': 'guest', 'garry trudeau_8': 'garry trudeau', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'episode_9': 'episode', '806_10': '806'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'guest_7': [0], 'garry trudeau_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'episode_9': [2], '806_10': [3]} | ['episode', 'the wãrd', 'guest', 'introductory phrase', 'original airdate', 'production code'] | [['804', 'none', 'jake tapper , michelle rhee', 'none', 'december 01', '6152'], ['806', 'unrequited gov', 'garry trudeau', 'none', 'december 06', '6154'], ['807', 'none', 'julie nixon eisenhower and david eisenhower', 'none', 'december 07', '6155'], ['809', 'none', 'daniel ellsberg , william wegman , julie taymor', 'no... |
8th new zealand parliament | https://en.wikipedia.org/wiki/8th_New_Zealand_Parliament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28898974-3.html.csv | count | three incumbents of the 8th new zealand parliament vacated their seats due to death . | {'scope': 'all', 'criterion': 'equal', 'value': 'death', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason', 'death'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason record fuzzily matches to death .', 'tostr': 'filter_eq { all_rows ; reason ; death }'}], 'result': '3', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; reason ; death } } ; 3 } = true | select the rows whose reason record fuzzily matches to death . 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, 'reason_5': 5, 'death_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', 'reason_5': 'reason', 'death_6': 'death', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'reason_5': [0], 'death_6': [0], '3_7': [2]} | ['by - election', 'electorate', 'date', 'incumbent', 'reason', 'winner'] | [['1882', 'franklin north', '9 june', 'benjamin harris', 'election declared void', 'benjamin harris'], ['1882', 'wakanui', '16 june', 'cathcart wason', 'election declared void', 'joseph ivess'], ['1882', 'stanmore', '11 july', 'walter pilliet', 'election declared void', 'walter pilliet'], ['1883', 'peninsula', '22 janu... |
1959 portuguese grand prix | https://en.wikipedia.org/wiki/1959_Portuguese_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122212-1.html.csv | count | only three four drivers completed at least 60 laps in the 1959 portuguese grand prix . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '60', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'laps', '60'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is greater than or equal to 60 .', 'tostr': 'filter_greater_eq { all_rows ; laps ; 60 }'}], 'result': '4', 'ind': 1, 'tostr': 'coun... | eq { count { filter_greater_eq { all_rows ; laps ; 60 } } ; 4 } = true | select the rows whose laps record is greater than or equal to 60 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'laps_5': 5, '60_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '60_6': '60', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'laps_5': [0], '60_6': [0], '4_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['stirling moss', 'cooper - climax', '62', '2:11:55.41', '1'], ['masten gregory', 'cooper - climax', '61', '+ 1 lap', '3'], ['dan gurney', 'ferrari', '61', '+ 1 lap', '6'], ['maurice trintignant', 'cooper - climax', '60', '+ 2 laps', '4'], ['harry schell', 'brm', '59', '+ 3 laps', '9'], ['roy salvadori', 'aston martin... |
1969 cleveland browns season | https://en.wikipedia.org/wiki/1969_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652161-2.html.csv | superlative | the august 30 , 1969 game vs the packers was the only one with over 80000 people in the stands . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'green bay packers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'green bay packer... | eq { hop { argmax { all_rows ; attendance } ; opponent } ; green bay packers } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is green bay packers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'green bay packers_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'green bay packers_7': 'green bay packers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'green bay packers_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 10 , 1969', 'san francisco 49ers at seattle', 'w 24 - 19', '32219'], ['2', 'august 16 , 1969', 'los angeles rams', 'w 10 - 3', '54937'], ['3', 'august 23 , 1969', 'san diego chargers', 't 19 - 19', '36005'], ['4', 'august 30 , 1969', 'green bay packers', 'l 27 - 17', '85532'], ['5', 'september 6 , 1969',... |
1959 - 60 segunda división | https://en.wikipedia.org/wiki/1959%E2%80%9360_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17710217-2.html.csv | unique | rc celta de vigo was the only club to have 18 wins in the 1959 - 60 segunda división . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '2', '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 } ; club } ; rc celta de vigo } } = true | select the rows whose wins record is equal to 18 . there is only one such row in the table . the club record of this unqiue row is rc celta de vigo . | 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, 'club_9': 9, 'rc celta de vigo_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', 'club_9': 'club', 'rc celta de vigo_10': 'rc celta de vigo'} | {'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], 'club_9': [2], 'rc celta de vigo_10': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'real santander', '30', '42', '17', '8', '5', '63', '28', '+ 35'], ['2', 'rc celta de vigo', '30', '40', '18', '4', '8', '63', '37', '+ 26'], ['3', 'cd orense', '30', '37', '15', '7', '8', '56', '41', '+ 15'], ['4', 'deportivo la coruña', '30', '35', '16', '3', '11', '56', '47', '+ 9'], ['5', 'real gijón', '30',... |
oliver marach | https://en.wikipedia.org/wiki/Oliver_Marach | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15271684-5.html.csv | comparative | oliver marach made it to the quarter final of the australian open in 2011 as compared to 2016 where he exited in the first round . | {'row_1': '2', 'row_2': '2', 'col': '15', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'australian open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to australian open .', 'tostr': 'filter_eq { all_rows ; tournam... | and { eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } } ; and { eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; qf } ; eq { hop { filter_eq { all_rows ; tournament ; australian open } ; 2011 } ; ... | select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row . select the rows whose tournament record fuzzily matches to australian open . take the 2011 record of this row . the first record fuzzily matches to the second record . the 2011 record of the first row is qf .... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'tournament_11': 11, 'australian open_12': 12, '2011_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'tournament_15': 15, 'australian open_16': 16, '2011_17': 17, 'and_7': 7, 'str_eq_5': 5, 'qf_18': 18,... | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'australian open_12': 'australian open', '2011_13': '2011', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_row... | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'tournament_11': [0], 'australian open_12': [0], '2011_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'tournament_15': [1], 'australian open_16': [1], '2011_17': [3], 'and_7': [8]... | ['tournament', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011'] | [['grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams'], ['australian open', 'a', 'a', 'a', 'a', 'a', 'a', 'a', 'a', '1r', '3r', '1r', 'sf', '3r', 'q... |
chet miller | https://en.wikipedia.org/wiki/Chet_Miller | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252058-1.html.csv | superlative | the highest start for chet miller was 3rd in 1936 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'start'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; start }'}, 'year'], 'result': '1936', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; start } ; year }'}, '1936'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { a... | eq { hop { argmin { all_rows ; start } ; year } ; 1936 } = true | select the row whose start record of all rows is minimum . the year record of this row is 1936 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'start_5': 5, 'year_6': 6, '1936_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'start_5': 'start', 'year_6': 'year', '1936_7': '1936'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'start_5': [0], 'year_6': [1], '1936_7': [2]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1930', '15', '97.360', '23', '13', '161'], ['1931', '15', '106.185', '25', '10', '200'], ['1932', '29', '111.053', '23', '21', '125'], ['1933', '32', '112.025', '23', '20', '163'], ['1934', '32', '109.252', '29', '33', '11'], ['1935', '17', '113.552', '24', '10', '200'], ['1936', '3', '117.675', '3', '5', '200'], ['... |
lee gibson | https://en.wikipedia.org/wiki/Lee_Gibson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17624963-2.html.csv | majority | the majority of results for lee gibson 's fights were wins for lee gibson . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'res', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the res records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; res ; win } = true'} | most_eq { all_rows ; res ; win } = true | for the res records of all rows , most of them fuzzily match to win . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'res_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'res_3': 'res', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'res_3': [0], 'win_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['win', '12 - 3', 'joe wilk', 'tko ( strikes )', 'strikeforce challengers : woodley vs bears', '1', 'kansas , united states'], ['loss', '11 - 3', 'muhsin corbbrey', 'decision ( unanimous )', 'shoxcjuly_27 .2 c_2007_card', '3', 'california , united states'], ['win', '11 - 2', 'talon hoffman', 'tko', 'ifo - eastman vs k... |
statistics relating to enlargement of the european union | https://en.wikipedia.org/wiki/Statistics_relating_to_enlargement_of_the_European_Union | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1307842-2.html.csv | ordinal | denmark has the highest population among the countries with area ( km square ) less than 100000 in statistics relating to enlargement of the european union . | {'scope': 'subset', 'row': '1', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '100000'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'area ( km square )', '100000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; area ( km square ) ; 100000 }', 'tointer': 'select the rows whose area ( km square ) record ... | eq { hop { nth_argmax { filter_less { all_rows ; area ( km square ) ; 100000 } ; population ; 1 } ; member countries } ; denmark } = true | select the rows whose area ( km square ) record is less than 100000 . select the row whose population record of these rows is 1st maximum . the member countries record of this row is denmark . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'area (km square)_6': 6, '100000_7': 7, 'population_8': 8, '1_9': 9, 'member countries_10': 10, 'denmark_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'area (km square)_6': 'area ( km square )', '100000_7': '100000', 'population_8': 'population', '1_9': '1', 'member countries_10': 'member countries', 'denmark_11': ... | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'area (km square)_6': [0], '100000_7': [0], 'population_8': [1], '1_9': [1], 'member countries_10': [2], 'denmark_11': [3]} | ['member countries', 'population', 'area ( km square )', 'gdp ( billion us )', 'gdp per capita ( us )'] | [['denmark', '5021861', '43094', '70.032', '59928'], ['ireland', '3073200', '70273', '21.103', '39638'], ['united kingdom', '56210000', '244820', '675.941', '36728'], ['accession countries', '64305061', '358187', '767.076', '11929'], ['existing members ( 1973 )', '192457106', '1299536', '2381396', '12374'], ['ec9 ( 197... |
1962 baltimore colts season | https://en.wikipedia.org/wiki/1962_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14984078-1.html.csv | unique | the game on october 21 , 1962 was the only game played at wrigley field by the baltimore colts . | {'scope': 'all', 'row': '6', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': 'wrigley field', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'wrigley field'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to wrigley field .', 'tostr': 'filter_eq { all_rows ; game site ; wrigley field }'}], 'result': Tr... | and { only { filter_eq { all_rows ; game site ; wrigley field } } ; eq { hop { filter_eq { all_rows ; game site ; wrigley field } ; date } ; october 21 , 1962 } } = true | select the rows whose game site record fuzzily matches to wrigley field . there is only one such row in the table . the date record of this unqiue row is october 21 , 1962 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'game site_7': 7, 'wrigley field_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'october 21 , 1962_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'game site_7': 'game site', 'wrigley field_8': 'wrigley field', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'october 21 , 1962_10': 'october 21 , 1962'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'game site_7': [0], 'wrigley field_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'october 21 , 1962_10': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 16 , 1962', 'los angeles rams', 'w 30 - 27', '1 - 0', 'memorial stadium', '54796'], ['2', 'september 23 , 1962', 'minnesota vikings', 'w 34 - 7', '2 - 0', 'metropolitan stadium', '30787'], ['3', 'september 30 , 1962', 'detroit lions', 'l 20 - 29', '2 - 1', 'memorial stadium', '57966'], ['4', 'october ... |
2008 - 09 boston celtics season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17140608-10.html.csv | count | paul pierce won a total of 5 high points in the 2008-09 boston celtics season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'paul pierce', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', 'paul pierce'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high points record fuzzily matches to paul pierce .', 'tostr': 'filter_eq { all_rows ; high points ; paul pierce }'}], 'result': '5... | eq { count { filter_eq { all_rows ; high points ; paul pierce } } ; 5 } = true | select the rows whose high points record fuzzily matches to paul pierce . 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, 'high points_5': 5, 'paul pierce_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', 'high points_5': 'high points', 'paul pierce_6': 'paul pierce', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'paul pierce_6': [0], '5_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 1', 'charlotte', 'w 111 - 109 ( 2ot )', 'paul pierce ( 32 )', 'kendrick perkins ( 12 )', 'rajon rondo ( 9 )', 'td banknorth garden 18624', '57 - 19'], ['77', 'april 3', 'atlanta', 'w 104 - 92 ( ot )', 'paul pierce ( 21 )', 'kendrick perkins ( 10 )', 'rajon rondo ( 6 )', 'td banknorth garden 18624', '58 -... |
2007 - 08 boston celtics season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11959669-5.html.csv | aggregation | gannet scored 65 high rebounds in the 6 january games he was credited with high rebounds . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '65', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'garnett'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'garnett'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high rebounds ; garnett }', 'tointer': 'select the rows whose high rebounds record fuzzily matches to garnett .'}, 'high rebounds'... | round_eq { sum { filter_eq { all_rows ; high rebounds ; garnett } ; high rebounds } ; 65 } = true | select the rows whose high rebounds record fuzzily matches to garnett . the sum of the high rebounds record of these rows is 65 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high rebounds_5': 5, 'garnett_6': 6, 'high rebounds_7': 7, '65_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high rebounds_5': 'high rebounds', 'garnett_6': 'garnett', 'high rebounds_7': 'high rebounds', '65_8': '65'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'garnett_6': [0], 'high rebounds_7': [1], '65_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['30', 'january 2', 'houston', '97 - 93', 'garnett ( 26 )', 'garnett ( 9 )', 'rondo ( 9 )', 'td banknorth garden 18624', '27 - 3'], ['31', 'january 4', 'memphis', '100 - 96', 'garnett , pierce ( 23 )', 'pierce , posey ( 10 )', 'allen , garnett , pierce ( 5 )', 'td banknorth garden 18624', '28 - 3'], ['32', 'january 5'... |
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/1-25740548-2.html.csv | superlative | out of the episodes that aired in august , the one with the least viewers had 5.17 million . | {'scope': 'subset', 'col_superlative': '7', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'august'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; august }', 'tointer': 'select the rows whose original air date record fuzzily matches to august .'}, 'us viewers ... | eq { min { filter_eq { all_rows ; original air date ; august } ; us viewers ( million ) } ; 5.17 } = true | select the rows whose original air date record fuzzily matches to august . the minimum us viewers ( million ) record of these rows is 5.17 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'august_6': 6, 'us viewers (million)_7': 7, '5.17_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'august_6': 'august', 'us viewers (million)_7': 'us viewers ( million )', '5.17_8': '5.17'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'august_6': [0], 'us viewers (million)_7': [1], '5.17_8': [2]} | ['series', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['1', 'pilot welcome to the cia', 'tim matheson', 'matt corman & chris ord', 'july 13 , 2010', 'ca101', '4.88'], ['2', "walter 's walk", 'félix alcalá', 'matt corman & chris ord', 'july 20 , 2010', 'ca102', '5.21'], ['3', 'south bound suarez', 'john kretchmer', 'james parriott', 'july 27 , 2010', 'ca103', '4.83'], ['4... |
1979 masters tournament | https://en.wikipedia.org/wiki/1979_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16458346-2.html.csv | count | in the 1979 masters tournament two of the people from the united states scored -6 to par . | {'scope': 'subset', 'criterion': 'equal', 'value': '-6', 'result': '2', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united ... | eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; to par ; -6 } } ; 2 } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose to par record is equal to -6 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'to par_8': 8, '-6_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'to par_8': 'to par', '-6_9': '-6', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'to par_8': [1], '-6_9': [1], '2_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'ed sneed', 'united states', '68 + 67 = 135', '- 9'], ['t1', 'craig stadler', 'united states', '69 + 66 = 135', '- 9'], ['t3', 'raymond floyd', 'united states', '70 + 68 = 138', '- 6'], ['t3', 'leonard thompson', 'united states', '68 + 70 = 138', '- 6'], ['t5', 'miller barber', 'united states', '75 + 64 = 139',... |
wake forest demon deacons football , 1980 - 89 | https://en.wikipedia.org/wiki/Wake_Forest_Demon_Deacons_football%2C_1980%E2%80%9389 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15531181-15.html.csv | majority | most of the games resulted in wins for the wake forest demon deacons . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['date', 'opponent', 'location', 'result', 'attendance'] | [['09 / 12 / 1987', 'richmond', 'groves stadium winston - salem , nc', 'w 24 - 0', '14250'], ['09 / 19 / 1987', 'north carolina state', 'groves stadium winston - salem , nc', 'w 21 - 3', '23600'], ['09 / 26 / 1987', 'appalachian state', 'groves stadium winston - salem , nc', 'w 16 - 12', '33400'], ['10 / 01 / 1987', 'a... |
kingco athletic conference | https://en.wikipedia.org/wiki/Kingco_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13759592-1.html.csv | majority | the majority of the high schools in the kingco athletic conference were founded after 1950 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1950', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'founded', '1950'], 'result': True, 'ind': 0, 'tointer': 'for the founded records of all rows , most of them are greater than 1950 .', 'tostr': 'most_greater { all_rows ; founded ; 1950 } = true'} | most_greater { all_rows ; founded ; 1950 } = true | for the founded records of all rows , most of them are greater than 1950 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'founded_3': 3, '1950_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'founded_3': 'founded', '1950_4': '1950'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'founded_3': [0], '1950_4': [0]} | ['high school', 'location', 'founded', 'affiliation', 'enrollment', 'nickname', 'division'] | [['ballard', 'seattle', '1903', 'public ( seattle ps )', '1649', 's beaver', 'crown'], ['bothell', 'bothell', '1959', 'public ( northshore sd )', '1800', 's cougar', 'crown'], ['eastlake', 'sammamish', '1993', 'public ( lake washington sd )', '1329', 'wolves', 'crest'], ['garfield', 'seattle', '1920', 'public ( seattle... |
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