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orlando magic all - time roster | https://en.wikipedia.org/wiki/Orlando_Magic_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15621965-7.html.csv | majority | the majority of players on the orlando magic all - time roster have united states nationality . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'nationality', 'position', 'years in orlando', 'school / club team'] | [['reece gaines', 'united states', 'guard', '2003 - 2004', 'louisville'], ['kiwane garris', 'united states', 'guard', '1999 - 2000', 'illinois'], ['pat garrity', 'united states', 'forward', '1999 - 2008', 'notre dame'], ['chris gatling', 'united states', 'forward - center', '1999 - 2000', 'old dominion'], ['gordan giri... |
melodifestivalen 2011 | https://en.wikipedia.org/wiki/Melodifestivalen_2011 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27994983-8.html.csv | superlative | danny saucedo had the highest score given by the juries in the melodifestivalen 2011 . | {'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', 'juries'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; juries }'}, 'artist'], 'result': 'danny saucedo', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; juries } ; artist }'}, 'danny saucedo'], 'result': True, 'in... | eq { hop { argmax { all_rows ; juries } ; artist } ; danny saucedo } = true | select the row whose juries record of all rows is maximum . the artist record of this row is danny saucedo . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'juries_5': 5, 'artist_6': 6, 'danny saucedo_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'juries_5': 'juries', 'artist_6': 'artist', 'danny saucedo_7': 'danny saucedo'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'juries_5': [0], 'artist_6': [1], 'danny saucedo_7': [2]} | ['draw', 'artist', 'song ( english translation )', 'lyrics ( l ) / music ( m )', 'juries', 'viewers', 'total', 'place'] | [['1', 'danny saucedo', 'in the club', 'figge boström , peter boström , danny saucedo', '79', '70', '149', '2'], ['2', 'sara varga', 'spring för livet ( run for your life )', 'sara varga , figge boström', '23', '27', '50', '9'], ['3', 'the moniker', 'oh my god !', 'daniel karlsson', '55', '69', '124', '3'], ['4', 'brol... |
2007 steelback grand prix | https://en.wikipedia.org/wiki/2007_Steelback_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12126919-2.html.csv | superlative | in the 2007 steelback grand prix , will power ranks the highest . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'driver'], 'result': 'will power', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; driver }'}, 'will power'], 'result': True, 'ind': 2,... | eq { hop { argmax { all_rows ; points } ; driver } ; will power } = true | select the row whose points record of all rows is maximum . the driver record of this row is will power . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'driver_6': 6, 'will power_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'driver_6': 'driver', 'will power_7': 'will power'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'driver_6': [1], 'will power_7': [2]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['will power', 'team australia', '73', '1:45:58.568', '7', '31'], ['neel jani', 'pkv racing', '73', '+ 2.972', '9', '28'], ['justin wilson', 'rsports', '73', '+ 3.480', '2', '25'], ['simon pagenaud', 'team australia', '73', '+ 5.643', '4', '23'], ['bruno junqueira', 'dale coyne racing', '73', '+ 20.738', '5', '21'], [... |
pádraig harrington | https://en.wikipedia.org/wiki/P%C3%A1draig_Harrington | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1157761-9.html.csv | superlative | the highest number of wins for pádraig harrington came in the open championship . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'wins'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; wins }'}, 'wins'], 'result': '2', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; wins } ; wins }'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { a... | eq { hop { argmax { all_rows ; wins } ; wins } ; 2 } = true | select the row whose wins record of all rows is maximum . the wins record of this row is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'wins_5': 5, 'wins_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'wins_5': 'wins', 'wins_6': 'wins', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'wins_5': [0], 'wins_6': [1], '2_7': [2]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '2', '4', '6', '14', '9'], ['us open', '0', '3', '5', '7', '16', '12'], ['the open championship', '2', '4', '4', '7', '17', '12'], ['pga championship', '1', '1', '2', '4', '14', '9'], ['totals', '3', '10', '15', '24', '61', '42']] |
finland 's next top model | https://en.wikipedia.org/wiki/Finland%27s_Next_Top_Model | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16805656-1.html.csv | aggregation | in finland 's next top model , for the cycles where the number of contestants has been determined , the average number of contestants was 11.4 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '11.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'number of contestants'], 'result': '11.4', 'ind': 0, 'tostr': 'avg { all_rows ; number of contestants }'}, '11.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; number of contestants } ; 11.4 } = true', 'tointer': 'the average of the... | round_eq { avg { all_rows ; number of contestants } ; 11.4 } = true | the average of the number of contestants record of all rows is 11.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'number of contestants_4': 4, '11.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'number of contestants_4': 'number of contestants', '11.4_5': '11.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'number of contestants_4': [0], '11.4_5': [1]} | ['cycle', 'premiere date', 'winner', 'runner - up', 'number of contestants', 'international destinations'] | [['1', 'april 6 , 2008', 'ani alitalo', 'darina shved', '12', 'stockholm turkey'], ['2', 'april 13 , 2009', 'nanna grundfeldt', 'anna - kaisa tyrväinen', '11', 'paris gran canaria'], ['3', 'april 12 , 2010', 'jenna kuokkanen', 'saara sihvonen', '11', 'milan egypt'], ['4', 'september 12 , 2011', 'anna - sofia ali - sist... |
weightlifting at the 1999 pan american games | https://en.wikipedia.org/wiki/Weightlifting_at_the_1999_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11279593-4.html.csv | superlative | idalberto aranda lifted the most weight of all the athletes . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total ( kg )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total ( kg ) }'}, 'name'], 'result': 'idalberto aranda ( cub )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total ( kg ) } ; name }'}, 'idalberto a... | eq { hop { argmax { all_rows ; total ( kg ) } ; name } ; idalberto aranda ( cub ) } = true | select the row whose total ( kg ) record of all rows is maximum . the name record of this row is idalberto aranda ( cub ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total (kg)_5': 5, 'name_6': 6, 'idalberto aranda ( cub )_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total (kg)_5': 'total ( kg )', 'name_6': 'name', 'idalberto aranda ( cub )_7': 'idalberto aranda ( cub )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total (kg)_5': [0], 'name_6': [1], 'idalberto aranda ( cub )_7': [2]} | ['name', 'bodyweight', 'snatch', 'clean & jerk', 'total ( kg )'] | [['idalberto aranda ( cub )', '76.55', '150.0', '205.5 wr', '355.0'], ['walter llerena ( ecu )', '76.78', '150.0', '182.5', '332.5'], ['oscar chaplin iii ( usa )', '76.95', '150.0', '182.5', '332.5'], ['carlos sauri ( pur )', '76.91', '140.0', '165.0', '305.0'], ['marcelo gandolfo ( arg )', '76.25', '130.0', '170.0', '... |
1963 baltimore colts season | https://en.wikipedia.org/wiki/1963_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14984103-1.html.csv | count | a total of 6 games took place at memorial stadium . | {'scope': 'all', 'criterion': 'equal', 'value': 'memorial stadium', 'result': '6', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'memorial stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to memorial stadium .', 'tostr': 'filter_eq { all_rows ; game site ; memorial stadium }'}], 're... | eq { count { filter_eq { all_rows ; game site ; memorial stadium } } ; 6 } = true | select the rows whose game site record fuzzily matches to memorial stadium . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'memorial stadium_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'memorial stadium_6': 'memorial stadium', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'memorial stadium_6': [0], '6_7': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 15 , 1963', 'new york giants', 'l 28 - 37', '0 - 1', 'memorial stadium', '60029'], ['2', 'september 22 , 1963', 'san francisco 49ers', 'w 20 - 14', '1 - 1', 'kezar stadium', '31006'], ['3', 'september 29 , 1963', 'green bay packers', 'l 20 - 31', '1 - 2', 'lambeau field', '42327'], ['4', 'october 6 , ... |
1998 australian touring car championship | https://en.wikipedia.org/wiki/1998_Australian_Touring_Car_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15284222-2.html.csv | majority | holden racing team was the winning team for the majority of races in the 1998 australian touring car championship . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'holden racing team', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'team', 'holden racing team'], 'result': True, 'ind': 0, 'tointer': 'for the team records of all rows , most of them fuzzily match to holden racing team .', 'tostr': 'most_eq { all_rows ; team ; holden racing team } = true'} | most_eq { all_rows ; team ; holden racing team } = true | for the team records of all rows , most of them fuzzily match to holden racing team . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team_3': 3, 'holden racing team_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team_3': 'team', 'holden racing team_4': 'holden racing team'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team_3': [0], 'holden racing team_4': [0]} | ['race title', 'circuit', 'location / state', 'date', 'winner', 'team'] | [['sandown', 'sandown international motor raceway', 'melbourne , victoria', '30 jan - 1 feb', 'craig lowndes', 'holden racing team'], ['launceston', 'symmons plains international raceway', 'launceston , tasmania', '6 - 8 feb', 'craig lowndes', 'holden racing team'], ['lakeside', 'lakeside international raceway', 'brisb... |
media in kelowna | https://en.wikipedia.org/wiki/Media_in_Kelowna | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409326-1.html.csv | count | 9 of the frequencies in kelowna radio are fm radio frequencies . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'fm', 'result': '9', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'frequency', 'fm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose frequency record fuzzily matches to fm .', 'tostr': 'filter_eq { all_rows ; frequency ; fm }'}], 'result': '9', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; frequency ; fm } } ; 9 } = true | select the rows whose frequency record fuzzily matches to fm . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'frequency_5': 5, 'fm_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'frequency_5': 'frequency', 'fm_6': 'fm', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'frequency_5': [0], 'fm_6': [0], '9_7': [2]} | ['frequency', 'call sign', 'branding', 'format', 'owner'] | [['1150 am', 'ckfr', 'am 1150', 'news / talk', 'astral media'], ['00 88.9 fm', 'cbtk - fm', 'cbc radio one', 'public news / talk', 'canadian broadcasting corporation'], ['00 89.7 fm', 'cbu - fm - 3', 'cbc radio 2', 'public music', 'canadian broadcasting corporation'], ['00 90.5 fm', 'cbuf - fm - 2', 'première chaîne', ... |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-15.html.csv | count | in the 1941 vfl season , among the games where home team scored above15 .00 , 2 of them had attendance below 10,000 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '10000', 'result': '2', 'col': '6', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '15.0'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '15.0'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; home team score ; 15.0 }', 'tointer': 'select the rows whose home team score record is greater t... | eq { count { filter_less { filter_greater { all_rows ; home team score ; 15.0 } ; crowd ; 10000 } } ; 2 } = true | select the rows whose home team score record is greater than 15.0 . among these rows , select the rows whose crowd record is less than 10000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'home team score_6': 6, '15.0_7': 7, 'crowd_8': 8, '10000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'home team score_6': 'home team score', '15.0_7': '15.0', 'crowd_8': 'crowd', '10000_9': '10000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'home team score_6': [0], '15.0_7': [0], 'crowd_8': [1], '10000_9': [1], '2_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '22.12 ( 144 )', 'hawthorn', '19.15 ( 129 )', 'kardinia park', '4500', '9 august 1941'], ['fitzroy', '16.17 ( 113 )', 'south melbourne', '11.14 ( 80 )', 'brunswick street oval', '8000', '9 august 1941'], ['carlton', '25.19 ( 169 )', 'north melbourne', '17.15 ( 117 )', 'princes park', '10000', '9 august 194... |
list of sumo record holders | https://en.wikipedia.org/wiki/List_of_sumo_record_holders | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17634218-19.html.csv | superlative | kotonishiki had the highest total of all of the sumo record holders . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'name'], 'result': 'kotonishiki', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; name }'}, 'kotonishiki'], 'result': True, 'ind': 2, 'tos... | eq { hop { argmax { all_rows ; total } ; name } ; kotonishiki } = true | select the row whose total record of all rows is maximum . the name record of this row is kotonishiki . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'name_6': 6, 'kotonishiki_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'name_6': 'name', 'kotonishiki_7': 'kotonishiki'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'name_6': [1], 'kotonishiki_7': [2]} | ['name', 'total', 'first', 'last', 'highest rank'] | [['kotonishiki', '34', 'september 1990', 'september 1999', 'sekiwake'], ['kaiō', '32', 'may 1994', 'july 2000', 'ōzeki'], ['musōyama', '31', 'march 1994', 'september 2000', 'ōzeki'], ['hasegawa', '30', 'november 1965', 'september 1974', 'sekiwake'], ['kotomitsuki', '30', 'january 2001', 'july 2007', 'ōzeki'], ['akinosh... |
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 | comparative | windows nt 3.1 was released earlier than windows 2000 . | {'row_1': '1', 'row_2': '5', 'col': '2', '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', 'name', 'windows nt 3.1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to windows nt 3.1 .', 'tostr': 'filter_eq { all_rows ; name ; windows nt 3.1 }'}, 'release date'], 'res... | less { hop { filter_eq { all_rows ; name ; windows nt 3.1 } ; release date } ; hop { filter_eq { all_rows ; name ; windows 2000 } ; release date } } = true | select the rows whose name record fuzzily matches to windows nt 3.1 . take the release date record of this row . select the rows whose name record fuzzily matches to windows 2000 . take the release 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, 'name_7': 7, 'windows nt 3.1_8': 8, 'release date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'windows 2000_12': 12, 'release 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', 'name_7': 'name', 'windows nt 3.1_8': 'windows nt 3.1', 'release date_9': 'release date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name',... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'windows nt 3.1_8': [0], 'release date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'windows 2000_12': [1], 'release date_13': [3]} | ['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... |
list of career achievements by dwight howard | https://en.wikipedia.org/wiki/List_of_career_achievements_by_Dwight_Howard | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25774493-3.html.csv | superlative | of the career achievements by dwight howard , the highest number of blocks per game was in december 2007 . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'blocks per game'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; blocks per game }'}, 'month'], 'result': 'december 2007', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; blocks per game } ; month }'}, 'december 20... | eq { hop { argmax { all_rows ; blocks per game } ; month } ; december 2007 } = true | select the row whose blocks per game record of all rows is maximum . the month record of this row is december 2007 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'blocks per game_5': 5, 'month_6': 6, 'december 2007_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'blocks per game_5': 'blocks per game', 'month_6': 'month', 'december 2007_7': 'december 2007'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'blocks per game_5': [0], 'month_6': [1], 'december 2007_7': [2]} | ['selection', 'month', 'season', 'team record', 'points per game', 'field goal percentage', 'rebounds per game', 'blocks per game'] | [['1', 'april 2006', '2005 - 06 ( 1 / 1 )', '7-2', '18.1', '531', '14.0', '0.7'], ['2', 'october / november 2006', '2006 - 07 ( 1 / 1 )', '12-4', '17.1', '576', '13.6', '1.9'], ['3', 'october / november 2007', '2007 - 08 ( 1 / 2 )', '14-4', '23.8', '618', '15.0', '2.7'], ['4', 'december 2007', '2007 - 08 ( 2 / 2 )', '8... |
1978 kansas city chiefs season | https://en.wikipedia.org/wiki/1978_Kansas_City_Chiefs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12536374-2.html.csv | unique | the san diego chargers were the only team to score no points against kansas city in 1978 . | {'scope': 'all', 'row': '13', 'col': '4', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': '- 0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '- 0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to - 0 .', 'tostr': 'filter_eq { all_rows ; result ; - 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_e... | and { only { filter_eq { all_rows ; result ; - 0 } } ; eq { hop { filter_eq { all_rows ; result ; - 0 } ; opponent } ; san diego chargers } } = true | select the rows whose result record fuzzily matches to - 0 . there is only one such row in the table . the opponent record of this unqiue row is san diego chargers . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, '- 0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opponent_9': 9, 'san diego chargers_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', '- 0_8': '- 0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opponent_9': 'opponent', 'san diego chargers_10': 'san diego chargers'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], '- 0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opponent_9': [2], 'san diego chargers_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 3 , 1978', 'cincinnati bengals', 'w 24 - 23', '41810'], ['2', 'september 10 , 1978', 'houston oilers', 'l 20 - 17', '40213'], ['3', 'september 17 , 1978', 'new york giants', 'l 26 - 10', '70546'], ['4', 'september 24 , 1978', 'denver broncos', 'l 23 - 17', '60593'], ['5', 'october 1 , 1978', 'buffalo ... |
1935 vfl season | https://en.wikipedia.org/wiki/1935_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790651-6.html.csv | unique | the only game on 3rd jume in the 1935 vfl season with a crowd over 25000 was played at windy hill . | {'scope': 'subset', 'row': '5', 'col': '6', 'col_other': '5,7', 'criterion': 'greater_than', 'value': '25000', 'subset': {'col': '7', 'criterion': 'equal', 'value': '3 june 1935'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '3 june 1935'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 3 june 1935 }', 'tointer': 'select the rows whose date record fuzzily matches to 3 june 1935 .'}... | and { only { filter_greater { filter_eq { all_rows ; date ; 3 june 1935 } ; crowd ; 25000 } } ; eq { hop { filter_greater { filter_eq { all_rows ; date ; 3 june 1935 } ; crowd ; 25000 } ; venue } ; windy hill } } = true | select the rows whose date record fuzzily matches to 3 june 1935 . among these rows , select the rows whose crowd record is greater than 25000 . there is only one such row in the table . the venue record of this unqiue row is windy hill . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'date_8': 8, '3 june 1935_9': 9, 'crowd_10': 10, '25000_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'venue_12': 12, 'windy hill_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', 'date_8': 'date', '3 june 1935_9': '3 june 1935', 'crowd_10': 'crowd', '25000_11': '25000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'venue_12': 'venue', 'windy... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'date_8': [0], '3 june 1935_9': [0], 'crowd_10': [1], '25000_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'venue_12': [3], 'windy hill_13': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['collingwood', '23.11 ( 149 )', 'footscray', '14.14 ( 98 )', 'victoria park', '17500', '1 june 1935'], ['hawthorn', '14.9 ( 93 )', 'geelong', '22.19 ( 151 )', 'glenferrie oval', '9500', '1 june 1935'], ['south melbourne', '23.14 ( 152 )', 'fitzroy', '10.11 ( 71 )', 'lake oval', '33000', '1 june 1935'], ['melbourne', ... |
paul di resta | https://en.wikipedia.org/wiki/Paul_di_Resta | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1746765-1.html.csv | unique | 2010 is the only year that paul di resta served as a test driver for a formula one team . | {'scope': 'all', 'row': '15', 'col': '10', 'col_other': '2', 'criterion': 'equal', 'value': 'test driver', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'test driver'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to test driver .', 'tostr': 'filter_eq { all_rows ; position ; test driver }'}], 'result': True, 'ind'... | and { only { filter_eq { all_rows ; position ; test driver } } ; eq { hop { filter_eq { all_rows ; position ; test driver } ; series } ; formula one } } = true | select the rows whose position record fuzzily matches to test driver . there is only one such row in the table . the series record of this unqiue row is formula one . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'test driver_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'series_9': 9, 'formula one_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'test driver_8': 'test driver', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'series_9': 'series', 'formula one_10': 'formula one'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'test driver_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'series_9': [2], 'formula one_10': [3]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2003', 'formula renault uk', 'eurotek motorsport', '17', '1', '2', '1', '2', '233', '7th'], ['2003', 'formula renault uk', 'team jva', '17', '1', '2', '1', '2', '233', '7th'], ['2004', 'formula renault uk', 'manor motorsport', '20', '4', '4', '2', '9', '415', '3rd'], ['2004', 'formula renault 2000 eurocup', 'manor m... |
1990 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1990_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17129548-4.html.csv | majority | at the 1990 u.s. open , most of the players were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'tim simpson', 'united states', '66 + 69 = 135', '- 9'], ['2', 'jeff sluman', 'united states', '66 + 70 = 136', '- 8'], ['3', 'mike donald', 'united states', '67 + 70 = 137', '- 7'], ['4', 'mark brooks', 'united states', '68 + 70 = 138', '- 6'], ['t5', 'hale irwin', 'united states', '69 + 70 = 139', '- 5'], ['t5... |
kiwirail | https://en.wikipedia.org/wiki/KiwiRail | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18217231-2.html.csv | superlative | of kiwirail 's locomotives , the class with the highest number currently in service is the dc class . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'number in service'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; number in service }'}, 'class'], 'result': 'dc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; number in service } ; class }'}, 'dc'], 'result': ... | eq { hop { argmax { all_rows ; number in service } ; class } ; dc } = true | select the row whose number in service record of all rows is maximum . the class record of this row is dc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'number in service_5': 5, 'class_6': 6, 'dc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'number in service_5': 'number in service', 'class_6': 'class', 'dc_7': 'dc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'number in service_5': [0], 'class_6': [1], 'dc_7': [2]} | ['class', 'introduced', 'number in class', 'number in service', 'power output ( kw )'] | [['dbr', '1980', '10', '7', '709'], ['dc', '1978 - 1981', '85', '69', '1230'], ['dft', '1979 - 1981', '30', '29', '1800'], ['dh', '1979', '6', '6', '672'], ['dl', '2010 -', '48', '40', '2700'], ['dsc', '1959 - 1967', '70', '44', '315'], ['dsg', '1981', '24', '24', '700'], ['dsj', '1982', '5', '5', '350'], ['dx', '1972 ... |
list of tvb dramas in 2011 | https://en.wikipedia.org/wiki/List_of_TVB_dramas_in_2011 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29633639-1.html.csv | comparative | lives of omission had a higher peak than the rippling blossom . | {'row_1': '2', 'row_2': '3', 'col': '5', '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', 'english title', 'lives of omission'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose english title record fuzzily matches to lives of omission .', 'tostr': 'filter_eq { all_rows ; english title ; lives... | greater { hop { filter_eq { all_rows ; english title ; lives of omission } ; peak } ; hop { filter_eq { all_rows ; english title ; the rippling blossom } ; peak } } = true | select the rows whose english title record fuzzily matches to lives of omission . take the peak record of this row . select the rows whose english title record fuzzily matches to the rippling blossom . take the peak 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, 'english title_7': 7, 'lives of omission_8': 8, 'peak_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'english title_11': 11, 'the rippling blossom_12': 12, 'peak_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', 'english title_7': 'english title', 'lives of omission_8': 'lives of omission', 'peak_9': 'peak', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'eng... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'english title_7': [0], 'lives of omission_8': [0], 'peak_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'english title_11': [1], 'the rippling blossom_12': [1], 'peak_13': [3]} | ['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers'] | [['1', 'forensic heroes iii', '法證先鋒iii', '33', '43', '31', '33', '2.11 million'], ['2', 'lives of omission', '潛行狙擊', '31', '40', '29', '33', '1.97 million'], ['3', 'the rippling blossom', '魚躍在花見', '31', '38', '29', '32', '1.95 million'], ['4', 'curse of the royal harem', '萬凰之王', '30', '43', '29', '31', '1.92 million'],... |
1949 giro d'italia | https://en.wikipedia.org/wiki/1949_Giro_d%27Italia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12582434-1.html.csv | unique | mario fazio won only one event in the 1949 giro d'italia . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'mario fazio', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'mario fazio'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winner record fuzzily matches to mario fazio .', 'tostr': 'filter_eq { all_rows ; winner ; mario fazio }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq... | only { filter_eq { all_rows ; winner ; mario fazio } } = true | select the rows whose winner record fuzzily matches to mario fazio . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'winner_4': 4, 'mario fazio_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'winner_4': 'winner', 'mario fazio_5': 'mario fazio'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'winner_4': [0], 'mario fazio_5': [0]} | ['date', 'course', 'distance', 'type', 'winner'] | [['21 may', 'palermo to catania', '100 km', 'stage with mountain ( s )', 'mario fazio ( ita )'], ['22 may', 'catania to messina', '100 km', 'plain stage', 'sergio maggini ( ita )'], ['23 may', 'villa san giovanni to cosenza', '100 km', 'stage with mountain ( s )', 'guido de santi ( ita )'], ['24 may', 'cosenza to saler... |
6th united states congress | https://en.wikipedia.org/wiki/6th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-224840-4.html.csv | count | two of the congressmen vacated their seats due to death . | {'scope': 'all', 'criterion': 'equal', 'value': 'died', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'died'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to died .', 'tostr': 'filter_eq { all_rows ; reason for change ; died }'}], 'result': '2', ... | eq { count { filter_eq { all_rows ; reason for change ; died } } ; 2 } = true | select the rows whose reason for change record fuzzily matches to died . 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, 'reason for change_5': 5, 'died_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', 'reason for change_5': 'reason for change', 'died_6': 'died', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'reason for change_5': [0], 'died_6': [0], '2_7': [2]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['new york 1st', 'jonathan havens ( dr )', 'died october 25 , 1799', 'john smith ( dr )', 'february 27 , 1800'], ['connecticut at - large', 'jonathan brace ( f )', 'resigned sometime in 1800', 'john cotton smith ( f )', 'november 17 , 1800'], ['virginia 13th', 'john marshall ( f )', 'resigned june 7 , 1800 to become s... |
alice anum | https://en.wikipedia.org/wiki/Alice_Anum | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17786147-1.html.csv | unique | 1965 was the only year that alice anum competed in the long jump event . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'long jump', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'extra', 'long jump'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose extra record fuzzily matches to long jump .', 'tostr': 'filter_eq { all_rows ; extra ; long jump }'}], 'result': True, 'ind': 1, 'tostr': '... | and { only { filter_eq { all_rows ; extra ; long jump } } ; eq { hop { filter_eq { all_rows ; extra ; long jump } ; year } ; 1965 } } = true | select the rows whose extra record fuzzily matches to long jump . there is only one such row in the table . the year record of this unqiue row is 1965 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'extra_7': 7, 'long jump_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1965_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'extra_7': 'extra', 'long jump_8': 'long jump', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1965_10': '1965'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'extra_7': [0], 'long jump_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1965_10': [3]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['1965', 'all - africa games', 'brazzaville , congo', '1st', 'long jump'], ['1970', 'british commonwealth games', 'edinburgh , scotland', '2nd', '100 m'], ['1970', 'british commonwealth games', 'edinburgh , scotland', '2nd', '200 m'], ['1972', 'olympic games', 'munich , germany', '6th', '100 m'], ['1972', 'olympic gam... |
tony lema | https://en.wikipedia.org/wiki/Tony_Lema | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1570274-4.html.csv | aggregation | tony lema makes an average of 4 cuts per tournament . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'cuts made'], 'result': '4', 'ind': 0, 'tostr': 'avg { all_rows ; cuts made }'}, '4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; cuts made } ; 4 } = true', 'tointer': 'the average of the cuts made record of all rows is 4 .'} | round_eq { avg { all_rows ; cuts made } ; 4 } = true | the average of the cuts made record of all rows is 4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'cuts made_4': 4, '4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'cuts made_4': 'cuts made', '4_5': '4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'cuts made_4': [0], '4_5': [1]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '2', '4', '4', '4'], ['us open', '0', '2', '3', '4', '6', '5'], ['the open championship', '1', '2', '2', '2', '3', '3'], ['pga championship', '0', '0', '1', '2', '5', '4'], ['totals', '1', '5', '8', '12', '18', '16']] |
brad gumm | https://en.wikipedia.org/wiki/Brad_Gumm | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445678-2.html.csv | count | seven of these events were resolved through the decision method . | {'scope': 'all', 'criterion': 'equal', 'value': 'decision', 'result': '7', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'decision'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to decision .', 'tostr': 'filter_eq { all_rows ; method ; decision }'}], 'result': '7', 'ind': 1, 'tostr': 'c... | eq { count { filter_eq { all_rows ; method ; decision } } ; 7 } = true | select the rows whose method record fuzzily matches to decision . 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, 'method_5': 5, 'decision_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', 'method_5': 'method', 'decision_6': 'decision', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'method_5': [0], 'decision_6': [0], '7_7': [2]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['loss', '10 - 6 - 1', 'hank weis', 'submission ( guillotine choke )', 'kickdown - sturgis', '1', 'south dakota , united states'], ['loss', '10 - 5 - 1', 'don ortega', 'decision', 'pnrf - explosion', '2', 'mexico'], ['loss', '10 - 4 - 1', 'heath sims', 'submission ( strikes )', 'sf 2 - on the move', '2', 'oregon , uni... |
toronto raptors all - time roster | https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-21.html.csv | unique | haywoode workman is the only player on the toronto raptors all - time roster from oral roberts college . | {'scope': 'all', 'row': '15', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'oral roberts', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'oral roberts'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to oral roberts .', 'tostr': 'filter_eq { all_rows ; school / club team ; oral ro... | and { only { filter_eq { all_rows ; school / club team ; oral roberts } } ; eq { hop { filter_eq { all_rows ; school / club team ; oral roberts } ; player } ; haywoode workman } } = true | select the rows whose school / club team record fuzzily matches to oral roberts . there is only one such row in the table . the player record of this unqiue row is haywoode workman . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / club team_7': 7, 'oral roberts_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'haywoode workman_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / club team_7': 'school / club team', 'oral roberts_8': 'oral roberts', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'haywoode workman_10': 'haywoode workman'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / club team_7': [0], 'oral roberts_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'haywoode workman_10': [3]} | ['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team'] | [['john wallace', '44', 'united states', 'forward', '1997 - 99', 'syracuse'], ['sonny weems', '24', 'united states', 'guard', '2009 - 2011', 'arkansas'], ['donald whiteside', '12', 'united states', 'guard', '1996 - 97', 'northern illinois'], ['dwayne whitfield', '23', 'united states', 'forward', '1995 - 96', 'jackson s... |
2007 - 08 los angeles clippers season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Los_Angeles_Clippers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11965402-4.html.csv | comparative | the los angeles clippers had a game against the suns visitor earlier than the timberwolves . | {'row_1': '13', 'row_2': '15', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'suns'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose visitor record fuzzily matches to suns .', 'tostr': 'filter_eq { all_rows ; visitor ; suns }'}, 'date'], 'result': None, 'ind': 2, 'tostr'... | less { hop { filter_eq { all_rows ; visitor ; suns } ; date } ; hop { filter_eq { all_rows ; visitor ; timberwolves } ; date } } = true | select the rows whose visitor record fuzzily matches to suns . take the date record of this row . select the rows whose visitor record fuzzily matches to timberwolves . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'visitor_7': 7, 'suns_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'visitor_11': 11, 'timberwolves_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'visitor_7': 'visitor', 'suns_8': 'suns', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'visitor_11': 'visitor', 'timberwolves_12': 'tim... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'visitor_7': [0], 'suns_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'visitor_11': [1], 'timberwolves_12': [1], 'date_13': [3]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['december 2 , 2007', 'pacers', '101 - 95', 'clippers', 'chris kaman ( 22 )', '13741', '6 - 9'], ['december 4 , 2007', 'bucks', '87 - 78', 'clippers', 'corey maggette ( 20 )', '16004', '6 - 10'], ['december 5 , 2007', 'clippers', '88 - 95', 'sonics', 'corey maggette ( 23 )', '10961', '6 - 11'], ['december 7 , 2007', '... |
1999 pga tour | https://en.wikipedia.org/wiki/1999_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14611430-4.html.csv | majority | most of the players which participated in the 1999 pga tour were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'greg norman', 'australia', '12507322', '20'], ['2', 'davis love iii', 'united states', '12487463', '13'], ['3', 'payne stewart', 'united states', '11737008', '11'], ['4', 'nick price', 'zimbabwe', '11386236', '17'], ['5', 'tiger woods', 'united states', '11315128', '15']] |
1995 - 96 chicago bulls season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Chicago_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13480122-5.html.csv | superlative | united center was the first location used by chicago bulls during the 1995 - 96 season . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '8', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'location attendance'], 'result': 'united center 23854', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; location attendance }'}, 'united cen... | eq { hop { argmin { all_rows ; date } ; location attendance } ; united center 23854 } = true | select the row whose date record of all rows is minimum . the location attendance record of this row is united center 23854 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'location attendance_6': 6, 'united center 23854_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'location attendance_6': 'location attendance', 'united center 23854_7': 'united center 23854'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'location attendance_6': [1], 'united center 23854_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['29', 'january 3', 'houston', 'w 100 - 86', 'michael jordan ( 38 )', 'dennis rodman ( 15 )', 'scottie pippen ( 9 )', 'united center 23854', '26 - 3'], ['30', 'january 4', 'charlotte', 'w 117 - 93', 'michael jordan ( 27 )', 'dennis rodman ( 11 )', 'ron harper ( 7 )', 'charlotte coliseum 24042', '27 - 3'], ['31', 'janu... |
2007 - 08 chelsea f.c. season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Chelsea_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11927320-3.html.csv | unique | the only competition chelsea fc was not the runner-up was the fa cup . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'not_equal', 'value': 'runner-up', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'final position / round', 'runner-up'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose final position / round record does not match to runner-up .', 'tostr': 'filter_not_eq { all_rows ; final position / ro... | and { only { filter_not_eq { all_rows ; final position / round ; runner-up } } ; eq { hop { filter_not_eq { all_rows ; final position / round ; runner-up } ; competition } ; fa cup } } = true | select the rows whose final position / round record does not match to runner-up . there is only one such row in the table . the competition record of this unqiue row is fa cup . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'final position / round_7': 7, 'runner-up_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'competition_9': 9, 'fa cup_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_6': 'all_rows', 'final position / round_7': 'final position / round', 'runner-up_8': 'runner-up', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'competition_9': 'competition', 'fa cup_10': 'fa cup'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'final position / round_7': [0], 'runner-up_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'competition_9': [2], 'fa cup_10': [3]} | ['competition', 'current position / round', 'final position / round', 'first match', 'last match'] | [['fa community shield', '-', 'runner - up', '5 aug 2007', '5 aug 2007'], ['premier league', '-', 'runner - up', '12 aug 2007', '11 may 2008'], ['uefa champions league', '-', 'runner - up', '18 sep 2007', '21 may 2008'], ['football league cup', '-', 'runner - up', '24 sep 2007', '24 feb 2008'], ['fa cup', '-', 'quarter... |
list of 10 metre air pistol records | https://en.wikipedia.org/wiki/List_of_10_metre_air_pistol_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18986934-1.html.csv | ordinal | in list of 10 metre air pistol records , shooter uwe potteck ( gdr ) scored the highest in austria . | {'scope': 'subset', 'row': '6', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'austria'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'place', 'austria'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; place ; austria }', 'tointer': 'select the rows whose place record fuzzily matches to austria .'}, 'scor... | eq { hop { nth_argmax { filter_eq { all_rows ; place ; austria } ; score ; 1 } ; shooter } ; uwe potteck ( gdr ) } = true | select the rows whose place record fuzzily matches to austria . select the row whose score record of these rows is 1st maximum . the shooter record of this row is uwe potteck ( gdr ) . | 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, 'place_6': 6, 'austria_7': 7, 'score_8': 8, '1_9': 9, 'shooter_10': 10, 'uwe potteck ( gdr )_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', 'place_6': 'place', 'austria_7': 'austria', 'score_8': 'score', '1_9': '1', 'shooter_10': 'shooter', 'uwe potteck ( gdr )_11': 'uwe potteck ( gdr )'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'place_6': [0], 'austria_7': [0], 'score_8': [1], '1_9': [1], 'shooter_10': [2], 'uwe potteck ( gdr )_11': [3]} | ['score', 'shooter', 'date', 'comp', 'place'] | [['385', 'h mertel ( frg )', '1969', 'ech', 'pilsen , czechoslovakia'], ['385', 'rasskazov ( urs )', '1969', 'ech', 'pilsen , czechoslovakia'], ['387', 'v stolypin ( urs )', '1971', 'ech', 'meziboří , czechoslovakia'], ['392', 'grigori kosych ( urs )', '1973', 'ech', 'linz , austria'], ['393', 'harald vollmar ( gdr )',... |
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 | count | there are three high schools in the kingco athletic conference that are located in seattle . | {'scope': 'all', 'criterion': 'equal', 'value': 'seattle', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'seattle'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to seattle .', 'tostr': 'filter_eq { all_rows ; location ; seattle }'}], 'result': '3', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; location ; seattle } } ; 3 } = true | select the rows whose location record fuzzily matches to seattle . 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, 'location_5': 5, 'seattle_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', 'location_5': 'location', 'seattle_6': 'seattle', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'seattle_6': [0], '3_7': [2]} | ['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... |
ross bagdasarian , jr | https://en.wikipedia.org/wiki/Ross_Bagdasarian%2C_Jr. | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1543453-1.html.csv | superlative | " the chipmunk adventure " was the earliest chipmunk movie that ross bagdasarian jr. has worked on . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'year'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; year }'}, 'title'], 'result': 'the chipmunk adventure', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; year } ; title }'}, 'the chipmunk adventure'], 'result':... | eq { hop { argmin { all_rows ; year } ; title } ; the chipmunk adventure } = true | select the row whose year record of all rows is minimum . the title record of this row is the chipmunk adventure . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, 'title_6': 6, 'the chipmunk adventure_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'year_5': 'year', 'title_6': 'title', 'the chipmunk adventure_7': 'the chipmunk adventure'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], 'title_6': [1], 'the chipmunk adventure_7': [2]} | ['year', 'title', 'producer', 'actor', 'role'] | [['1987', 'the chipmunk adventure', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['1999', 'alvin and the chipmunks meet frankenstein', 'yes', 'yes', "alvin seville simon seville david ' dave ' seville"], ['2000', 'alvin and the chipmunks meet the wolfman', 'yes', 'yes', "alvin seville simon sevi... |
1987 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1987_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17231211-5.html.csv | unique | berhand langer was the only player from west germany in the 1987 u.s. open golf tournament . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'west germany', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'west germany'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to west germany .', 'tostr': 'filter_eq { all_rows ; country ; west germany }'}], 'result': True, 'ind'... | and { only { filter_eq { all_rows ; country ; west germany } } ; eq { hop { filter_eq { all_rows ; country ; west germany } ; player } ; bernhard langer } } = true | select the rows whose country record fuzzily matches to west germany . there is only one such row in the table . the player record of this unqiue row is bernhard langer . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'west germany_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'bernhard langer_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'west germany_8': 'west germany', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'bernhard langer_10': 'bernhard langer'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'west germany_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'bernhard langer_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'tom watson', 'united states', '72 + 65 = 137', '- 3'], ['t1', 'mark wiebe', 'united states', '70 + 67 = 137', '- 3'], ['t3', 'john cook', 'united states', '70 + 68 = 138', '- 2'], ['t3', 'bernhard langer', 'west germany', '69 + 69 = 138', '- 2'], ['t3', 'tsuneyuki nakajima', 'japan', '68 + 70 = 138', '- 2'], [... |
hawthorne ( season 2 ) | https://en.wikipedia.org/wiki/Hawthorne_%28season_2%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30030477-1.html.csv | superlative | the episode of hawthorne ( season 2 ) titled " no excuses " had the most viewers of it 's season . | {'scope': 'all', 'col_superlative': '7', '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', 'viewers ( million )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewers ( million ) }'}, 'title'], 'result': 'no excuses', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewers ( million ) } ; title }'}, 'no... | eq { hop { argmax { all_rows ; viewers ( million ) } ; title } ; no excuses } = true | select the row whose viewers ( million ) record of all rows is maximum . the title record of this row is no excuses . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewers (million)_5': 5, 'title_6': 6, 'no excuses_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewers (million)_5': 'viewers ( million )', 'title_6': 'title', 'no excuses_7': 'no excuses'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewers (million)_5': [0], 'title_6': [1], 'no excuses_7': [2]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'viewers ( million )'] | [['11', '1', 'no excuses', 'jeff bleckner', 'glen mazzara', 'june 22 , 2010', '3.42'], ['12', '2', 'the starting line', 'ed bianchi', 'john masius & erica shelton', 'june 29 , 2010', '2.95'], ['13', '3', 'road narrows', 'ed bianchi', 'sang kyu kim', 'july 6 , 2010', '2.73'], ['14', '4', 'afterglow', 'jeff bleckner', 'd... |
2007 - 08 oakland golden grizzlies men 's basketball team | https://en.wikipedia.org/wiki/2007%E2%80%9308_Oakland_Golden_Grizzlies_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15748977-1.html.csv | ordinal | will hudson is the 3rd tallest person on the 2007 - 08 oakland golden grizzlies men 's basketball team . | {'row': '3', 'col': '3', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'height', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; height ; 3 }'}, 'name'], 'result': 'will hudson', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; height ; 3 } ; name }'}, 'will hudson'], 'r... | eq { hop { nth_argmax { all_rows ; height ; 3 } ; name } ; will hudson } = true | select the row whose height record of all rows is 3rd maximum . the name record of this row is will hudson . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'height_5': 5, '3_6': 6, 'name_7': 7, 'will hudson_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'height_5': 'height', '3_6': '3', 'name_7': 'name', 'will hudson_8': 'will hudson'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'height_5': [0], '3_6': [0], 'name_7': [1], 'will hudson_8': [2]} | ['name', 'pos', 'height', 'weight', 'year', 'hometown ( previous school )'] | [['derick nelson', 'f', "6 ' 5", '226', 'jr', 'lansing , mi ( bridgton academy )'], ['peter bunn', 'g', "6 ' 1", '165', 'fr', 'lansing , mi ( lansing christian )'], ['will hudson', 'f', "6 ' 9", '220', 'fr', 'verona , wi ( middleton )'], ['b - jay walker', 'g', "5 ' 8", '149', 'so', 'lathrup village , mi ( shrine catho... |
united states house of representatives elections , 1966 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1966 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341843-44.html.csv | ordinal | wright patman was the first person in the texas house of representatives to have been elected . | {'row': '1', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'incumbent'], 'result': 'wright patman', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; ... | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; incumbent } ; wright patman } = true | select the row whose first elected record of all rows is 1st minimum . the incumbent record of this row is wright patman . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1_6': 6, 'incumbent_7': 7, 'wright patman_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '1_6': '1', 'incumbent_7': 'incumbent', 'wright patman_8': 'wright patman'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'incumbent_7': [1], 'wright patman_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) unopposed'], ['texas 2', 'john dowdy redistricted from 7th', 'democratic', '1952', 're - elected', 'john dowdy ( d ) unopposed'], ['texas 3', 'joe r pool redistricted from at - large', 'democratic', '1962', 're - elected', 'joe r p... |
1974 green bay packers season | https://en.wikipedia.org/wiki/1974_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14655820-2.html.csv | superlative | the game that was played at atlanta stadium drew the lowest attendance . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '14', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; attendance }'}, 'venue'], 'result': 'atlanta stadium', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; attendance } ; venue }'}, 'atlanta stadium'], 'resu... | eq { hop { argmin { all_rows ; attendance } ; venue } ; atlanta stadium } = true | select the row whose attendance record of all rows is minimum . the venue record of this row is atlanta stadium . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'venue_6': 6, 'atlanta stadium_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'venue_6': 'venue', 'atlanta stadium_7': 'atlanta stadium'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'venue_6': [1], 'atlanta stadium_7': [2]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance'] | [['1', 'september 15 , 1974', 'minnesota vikings', 'l 32 - 17', 'lambeau field', '56267'], ['2', 'september 22 , 1974', 'baltimore colts', 'w 20 - 13', 'memorial stadium', '41252'], ['3', 'september 29 , 1974', 'detroit lions', 'w 21 - 19', 'milwaukee county stadium', '47292'], ['4', 'october 6 , 1974', 'buffalo bills'... |
list of better off ted episodes | https://en.wikipedia.org/wiki/List_of_Better_Off_Ted_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21994729-2.html.csv | ordinal | for the show better off ted , the episode with the 2nd earliest original air date was titled " heroes " . | {'row': '2', 'col': '5', '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', 'original air date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; original air date ; 2 }'}, 'title'], 'result': 'heroes', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; original air date ; 2 } ;... | eq { hop { nth_argmin { all_rows ; original air date ; 2 } ; title } ; heroes } = true | select the row whose original air date record of all rows is 2nd minimum . the title record of this row is heroes . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '2_6': 6, 'title_7': 7, 'heroes_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', '2_6': '2', 'title_7': 'title', 'heroes_8': 'heroes'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '2_6': [0], 'title_7': [1], 'heroes_8': [2]} | ['series', 'title', 'directed by', 'written by', 'original air date', 'prod code'] | [['1', 'pilot', 'michael fresco', 'victor fresco', 'march 18 , 2009', '1apx79'], ['2', 'heroes', 'michael fresco', 'victor fresco', 'march 25 , 2009', '1apx01'], ['3', 'through rose - colored hazmat suits', 'michael fresco', 'justin adler', 'april 1 , 2009', '1apx02'], ['4', 'racial sensitivity', 'paul lazarus', 'micha... |
longyan | https://en.wikipedia.org/wiki/Longyan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1204998-2.html.csv | count | four of the locations in longyan have a population greater than 300,000 . | {'scope': 'all', 'criterion': 'greater_than', 'value': '300,000', 'result': '4', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'population', '300,000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose population record is greater than 300,000 .', 'tostr': 'filter_greater { all_rows ; population ; 300,000 }'}], 'result': '4', 'ind': 1,... | eq { count { filter_greater { all_rows ; population ; 300,000 } } ; 4 } = true | select the rows whose population record is greater than 300,000 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'population_5': 5, '300,000_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'population_5': 'population', '300,000_6': '300,000', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'population_5': [0], '300,000_6': [0], '4_7': [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... |
nfl network thursday night football results ( 2006 - present ) | https://en.wikipedia.org/wiki/NFL_Network_Thursday_Night_Football_results_%282006%E2%80%93present%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12771946-3.html.csv | count | four of the games played shown on the nfl network were in december . | {'scope': 'all', 'criterion': 'equal', 'value': 'december', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to december .', 'tostr': 'filter_eq { all_rows ; date ; december }'}], 'result': '4', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; date ; december } } ; 4 } = true | select the rows whose date record fuzzily matches to december . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'december_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'december_6': 'december', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'december_6': [0], '4_7': [2]} | ['date', 'visiting team', 'final score', 'host team', 'stadium'] | [['november 6', 'denver broncos', '34 - 30', 'cleveland browns', 'cleveland browns stadium'], ['november 13', 'new york jets', '34 - 31 ( ot )', 'new england patriots', 'gillette stadium'], ['november 20', 'cincinnati bengals', '10 - 27', 'pittsburgh steelers', 'heinz field'], ['november 27', 'arizona cardinals', '20 -... |
icho larenas | https://en.wikipedia.org/wiki/Icho_Larenas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14712229-2.html.csv | unique | icho larenas 's match against brian magee was the only one that he fought in victoriaville , quebec , canada . | {'scope': 'all', 'row': '9', 'col': '8', 'col_other': '3', 'criterion': 'equal', 'value': 'victoriaville , quebec , canada', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'victoriaville , quebec , canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to victoriaville , quebec , canada .', 'tostr': 'filter_eq { all_rows ; location ;... | and { only { filter_eq { all_rows ; location ; victoriaville , quebec , canada } } ; eq { hop { filter_eq { all_rows ; location ; victoriaville , quebec , canada } ; opponent } ; brian magee } } = true | select the rows whose location record fuzzily matches to victoriaville , quebec , canada . there is only one such row in the table . the opponent record of this unqiue row is brian magee . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'victoriaville , quebec , canada_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opponent_9': 9, 'brian magee_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'victoriaville , quebec , canada_8': 'victoriaville , quebec , canada', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opponent_9': 'opponent', 'brian magee_10': 'brian magee'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'victoriaville , quebec , canada_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opponent_9': [2], 'brian magee_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '6 - 4', 'pablo vargas', 'tko ( punches )', 'conviction mma 2 - consolidation', '1', '2:48', 'buenos aires , argentina'], ['win', '5 - 4', 'guido carlo', 'tko ( punches )', 'tko 34 - sims vs bosse', '1', '4:21', 'montreal , quebec , canada'], ['loss', '4 - 4', 'sebastien gauthier', 'decision ( majority )', 'xm... |
royal canadian mint numismatic coins ( 2000s ) | https://en.wikipedia.org/wiki/Royal_Canadian_Mint_numismatic_coins_%282000s%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916083-40.html.csv | superlative | the design diamonds had the highest mintage of all the royal canadian mint numismatic coins . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', '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', 'mintage'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; mintage }'}, 'design'], 'result': 'diamonds', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; mintage } ; design }'}, 'diamonds'], 'result': True, 'ind': 2, ... | eq { hop { argmax { all_rows ; mintage } ; design } ; diamonds } = true | select the row whose mintage record of all rows is maximum . the design record of this row is diamonds . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'mintage_5': 5, 'design_6': 6, 'diamonds_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'mintage_5': 'mintage', 'design_6': 'design', 'diamonds_7': 'diamonds'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'mintage_5': [0], 'design_6': [1], 'diamonds_7': [2]} | ['year', 'design', 'issue', 'artist', 'mintage', 'issue price'] | [['2003', 'niagara falls', 'hologram', 'gary corcoran', '29967', '79.95'], ['2003', 'rocky mountains', 'colorized', 'josé osio', '28793', '69.95'], ['2004', 'iceberg', 'hologram', 'josé osio', '24879', '69.95'], ['2004', 'northern lights', 'double image hologram', 'gary corcoran', '34135', '79.95'], ['2004', 'hopewell ... |
alabama a & m bulldogs football | https://en.wikipedia.org/wiki/Alabama_A%26M_Bulldogs_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20319085-2.html.csv | aggregation | for the alabama a & m bulldogs football the total combined attendance was 129457 . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '129457', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '129457', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '129457'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 129457 } = true', 'tointer': 'the sum of the attendance record of all rows ... | round_eq { sum { all_rows ; attendance } ; 129457 } = true | the sum of the attendance record of all rows is 129457 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '129457_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '129457_5': '129457'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '129457_5': [1]} | ['season', 'division', 'coach', 'overall record', 'conference record', 'result', 'attendance'] | [['2000', 'swac east', 'ron cooper', '7 - 5', '5 - 2', 'l 14 - 6 grambling state', '34687'], ['2002', 'swac east', 'anthony jones', '8 - 4', '6 - 1', 'l 31 - 19 grambling state', '23727'], ['2005', 'swac east', 'anthony jones', '9 - 3', '7 - 2', 'l 45 - 6 grambling state', '20612'], ['2006', 'swac east', 'anthony jones... |
south london derby | https://en.wikipedia.org/wiki/South_London_derby | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28611996-5.html.csv | count | in the south london derby , when there were less than 10 matches played , there were 3 times when there were 0 palace wins . | {'scope': 'subset', 'criterion': 'equal', 'value': '0', 'result': '3', 'col': '3', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '10'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'played', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; played ; 10 }', 'tointer': 'select the rows whose played record is less than 10 .'}, 'palace wins', '0'], 'result':... | eq { count { filter_eq { filter_less { all_rows ; played ; 10 } ; palace wins ; 0 } } ; 3 } = true | select the rows whose played record is less than 10 . among these rows , select the rows whose palace wins record is equal to 0 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'played_6': 6, '10_7': 7, 'palace wins_8': 8, '0_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'played_6': 'played', '10_7': '10', 'palace wins_8': 'palace wins', '0_9': '0', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'played_6': [0], '10_7': [0], 'palace wins_8': [1], '0_9': [1], '3_10': [3]} | ['', 'played', 'palace wins', 'drawn', 'millwall wins', 'palace goals', 'millwall goals'] | [['the football league', '86', '26', '26', '34', '106', '126'], ['fa cup', '10', '2', '4', '4', '11', '16'], ['football league trophy', '1', '0', '0', '1', '0', '3'], ['anglo - italian cup', '1', '1', '0', '0', '3', '0'], ['sub - total', '98', '29', '30', '39', '120', '145'], ['southern football league', '20', '12', '3... |
eagles - giants rivalry | https://en.wikipedia.org/wiki/Eagles%E2%80%93Giants_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16900662-10.html.csv | aggregation | new york scored over fifty points in 2013 when they were playing against the eagles . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': 'over 50', 'subset': {'col': '1', 'criterion': 'equal', 'value': '2013'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2013'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 2013 }', 'tointer': 'select the rows whose year record is equal to 2013 .'}, 'result'], 'result': 'over 50', 'ind': 1, 'tostr': 'sum { filt... | round_eq { sum { filter_eq { all_rows ; year ; 2013 } ; result } ; over 50 } = true | select the rows whose year record is equal to 2013 . the sum of the result record of these rows is over 50 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '2013_6': 6, 'result_7': 7, 'over 50_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '2013_6': '2013', 'result_7': 'result', 'over 50_8': 'over 50'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '2013_6': [0], 'result_7': [1], 'over 50_8': [2]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['2010', 'november 21', 'philadelphia eagles', '27 - 17', 'new york giants', 'lincoln financial field'], ['2010', 'december 19', 'philadelphia eagles', '38 - 31', 'new york giants', 'new meadowlands stadium'], ['2011', 'september 25', 'new york giants', '29 - 16', 'philadelphia eagles', 'lincoln financial field'], ['2... |
german submarine u - 137 ( 1940 ) | https://en.wikipedia.org/wiki/German_submarine_U-137_%281940%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18914307-1.html.csv | aggregation | the average number of deaths in a german submarine u-137 in 1940 was 13.4 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '13.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'deaths'], 'result': '13.4', 'ind': 0, 'tostr': 'avg { all_rows ; deaths }'}, '13.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; deaths } ; 13.4 } = true', 'tointer': 'the average of the deaths record of all rows is 13.4 .'} | round_eq { avg { all_rows ; deaths } ; 13.4 } = true | the average of the deaths record of all rows is 13.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'deaths_4': 4, '13.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'deaths_4': 'deaths', '13.4_5': '13.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'deaths_4': [0], '13.4_5': [1]} | ['date', 'ship name', 'flag', 'tonnage ( grt )', 'fate', 'deaths'] | [['26 september 1940', 'ashantian', 'great britain', '4917', 'damaged', '4'], ['26 september 1940', 'manchester brigade', 'great britain', '6042', 'sunk', '56'], ['26 september 1940', 'stratford', 'great britain', '4753', 'sunk', '2'], ['14 october 1940', 'hms cheshire', 'great britain', '10552', 'damaged', '0'], ['13 ... |
doug lewis ( skier ) | https://en.wikipedia.org/wiki/Doug_Lewis_%28skier%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10103807-2.html.csv | count | as an american skier , doug lewis had two top ten finishes in the us , both in aspen colorado . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'usa', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to usa .', 'tostr': 'filter_eq { all_rows ; location ; usa }'}], 'result': '2', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; location ; usa } } ; 2 } = true | select the rows whose location record fuzzily matches to usa . 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, 'location_5': 5, 'usa_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', 'location_5': 'location', 'usa_6': 'usa', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'usa_6': [0], '2_7': [2]} | ['season', 'date', 'location', 'discipline', 'place'] | [['1984', '11 mar 1984', 'whistler , bc , canada', 'downhill', '8th'], ['1985', '15 dec 1984', 'val gardena , italy', 'downhill', '9th'], ['1985', '11 jan 1985', 'kitzbühel , austria', 'downhill', '10th'], ['1985', '1985 world championships', '1985 world championships', '1985 world championships', '1985 world champions... |
kontinental hockey league | https://en.wikipedia.org/wiki/Kontinental_Hockey_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16666000-1.html.csv | aggregation | in the kontinental hockey league , when sergei mozyakin was the top scorer , his average number of points was 72.67 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '72.67', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'sergei mozyakin'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'top scorer', 'sergei mozyakin'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; top scorer ; sergei mozyakin }', 'tointer': 'select the rows whose top scorer record fuzzily matches to sergei mozyakin .'}, ... | round_eq { avg { filter_eq { all_rows ; top scorer ; sergei mozyakin } ; top scorer } ; 72.67 } = true | select the rows whose top scorer record fuzzily matches to sergei mozyakin . the average of the top scorer record of these rows is 72.67 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'top scorer_5': 5, 'sergei mozyakin_6': 6, 'top scorer_7': 7, '72.67_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'top scorer_5': 'top scorer', 'sergei mozyakin_6': 'sergei mozyakin', 'top scorer_7': 'top scorer', '72.67_8': '72.67'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'top scorer_5': [0], 'sergei mozyakin_6': [0], 'top scorer_7': [1], '72.67_8': [2]} | ['season', 'duration', 'gagarin cup winner', 'gagarin cup finalist', 'continental cup winner', 'top scorer'] | [['2008 - 09', '2 september 2008 - 12 april 2009', 'ak bars kazan', 'lokomotiv yaroslavl', 'salavat yulaev ufa ( 129 points )', 'sergei mozyakin ( 76 points : 34 g , 42 a )'], ['2009 - 10', '10 september 2009 - 27 april 2010', 'ak bars kazan', 'hc mvd', 'salavat yulaev ufa ( 129 points )', 'sergei mozyakin ( 66 points ... |
list of tyler perry 's house of payne episodes | https://en.wikipedia.org/wiki/List_of_Tyler_Perry%27s_House_of_Payne_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11630008-5.html.csv | majority | all of the episodes of tyler perry 's house of payne were directed by tyler perry . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'tyler perry', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'directed by', 'tyler perry'], 'result': True, 'ind': 0, 'tointer': 'for the directed by records of all rows , all of them fuzzily match to tyler perry .', 'tostr': 'all_eq { all_rows ; directed by ; tyler perry } = true'} | all_eq { all_rows ; directed by ; tyler perry } = true | for the directed by records of all rows , all of them fuzzily match to tyler perry . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'directed by_3': 3, 'tyler perry_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'directed by_3': 'directed by', 'tyler perry_4': 'tyler perry'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'directed by_3': [0], 'tyler perry_4': [0]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'production code'] | [['60', '1', 'wife swap', 'tyler perry', 'kellie r griffin', 'march 5 , 2008', '301'], ['61', '2', 'stop being all funky', 'tyler perry', 'kellie r griffin , jenee v giles', 'march 5 , 2008', '302'], ['62', '3', "guess who 's coming to dinner", 'tyler perry', 'jd walker', 'march 12 , 2008', '303'], ['63', '4', 'game ov... |
1971 vfl season | https://en.wikipedia.org/wiki/1971_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826072-12.html.csv | comparative | more people went to the game at mcg than at vfl park . | {'row_1': '3', 'row_2': '6', 'col': '6', 'col_other': '5', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'mcg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to mcg .', 'tostr': 'filter_eq { all_rows ; venue ; mcg }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'ho... | greater { hop { filter_eq { all_rows ; venue ; mcg } ; crowd } ; hop { filter_eq { all_rows ; venue ; vfl park } ; crowd } } = true | select the rows whose venue record fuzzily matches to mcg . take the crowd record of this row . select the rows whose venue record fuzzily matches to vfl park . take the crowd record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'mcg_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'vfl park_12': 12, 'crowd_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'mcg_8': 'mcg', 'crowd_9': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'vfl park_12': 'vfl park'... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'mcg_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'vfl park_12': [1], 'crowd_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['carlton', '16.18 ( 114 )', 'north melbourne', '3.5 ( 23 )', 'princes park', '13300', '19 june 1971'], ['st kilda', '14.15 ( 99 )', 'geelong', '3.3 ( 21 )', 'moorabbin oval', '14181', '19 june 1971'], ['richmond', '6.11 ( 47 )', 'fitzroy', '8.17 ( 65 )', 'mcg', '24831', '19 june 1971'], ['hawthorn', '14.20 ( 104 )', ... |
2007 fedex cup playoffs | https://en.wikipedia.org/wiki/2007_FedEx_Cup_Playoffs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13282157-1.html.csv | count | six of the athletes at the 2007 fedex cup playoffs were from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '6', 'in... | eq { count { filter_eq { all_rows ; country ; united states } } ; 6 } = true | select the rows whose country record fuzzily matches to united states . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '6_7': [2]} | ['', 'player', 'country', 'points', 'events', 'reset points'] | [['1', 'tiger woods', 'united states', '30574', '13', '100000'], ['2', 'vijay singh', 'fiji', '19129', '23', '99000'], ['3', 'jim furyk', 'united states', '16691', '19', '98500'], ['4', 'phil mickelson', 'united states', '16037', '18', '98000'], ['5', 'kj choi', 'south korea', '15485', '21', '97500'], ['6', 'rory sabba... |
eurovision song contest 1985 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1985 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-185276-2.html.csv | superlative | in the 1985 eurovision song contest , the highest number of points was for the song la det swinge . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'song'], 'result': 'la det swinge', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; song }'}, 'la det swinge'], 'result': True, 'ind': ... | eq { hop { argmax { all_rows ; points } ; song } ; la det swinge } = true | select the row whose points record of all rows is maximum . the song record of this row is la det swinge . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'song_6': 6, 'la det swinge_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'song_6': 'song', 'la det swinge_7': 'la det swinge'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'song_6': [1], 'la det swinge_7': [2]} | ['draw', 'language', 'song', 'english translation', 'place', 'points'] | [['01', 'english', 'wait until the weekend comes', '-', '6', '91'], ['02', 'finnish', 'eläköön elämä', 'long live life', '9', '58'], ['03', 'greek', 'to katalava arga ( το κατάλαβα αργά )', 'i realised it too late', '16', '15'], ['04', 'danish', "sku ' du spørg ' fra no'en", 'what business is it of yours', '11', '41'],... |
road to ... ( family guy ) | https://en.wikipedia.org/wiki/Road_to..._%28Family_Guy%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28210383-1.html.csv | superlative | the last road to episode of the family guy was the road to the north pole . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'original air date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; original air date }'}, 'title'], 'result': 'road to the north pole', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; original air date } ; title }'... | eq { hop { argmax { all_rows ; original air date } ; title } ; road to the north pole } = true | select the row whose original air date record of all rows is maximum . the title record of this row is road to the north pole . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'title_6': 6, 'road to the north pole_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'title_6': 'title', 'road to the north pole_7': 'road to the north pole'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'title_6': [1], 'road to the north pole_7': [2]} | ['( season )', 'no ( episode )', 'title', 'directed by', 'written by', 'original air date', 'prod code'] | [['1 ( 2 )', '20 ( 13 )', 'road to rhode island', 'dan povenmire', 'gary janetti', 'may 30 , 2000', '2acx12'], ['2 ( 3 )', '48 ( 20 )', 'road to europe', 'dan povenmire', 'daniel palladino', 'february 7 , 2002', '3acx13'], ['3 ( 5 )', '89 ( 9 )', 'road to rupert', 'dan povenmire', 'patrick meighan', 'january 28 , 2007'... |
1979 cincinnati bengals season | https://en.wikipedia.org/wiki/1979_Cincinnati_Bengals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17643197-2.html.csv | aggregation | the games played in the 1979 cincinnati bengals season drew an average crowd attendance of 48344 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '48344', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '48344', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '48344'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 48344 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 48344 } = true | the average of the attendance record of all rows is 48344 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '48344_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '48344_5': '48344'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '48344_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 2 , 1979', 'denver broncos', 'l 10 - 0', '74788'], ['2', 'september 9 , 1979', 'buffalo bills', 'l 51 - 24', '43504'], ['3', 'september 16 , 1979', 'new england patriots', 'l 20 - 14', '41805'], ['4', 'september 23 , 1979', 'houston oilers', 'l 30 - 27', '45615'], ['5', 'september 30 , 1979', 'dallas ... |
2008 - 09 philadelphia flyers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17511295-5.html.csv | count | philadelphia was the visiting team 6 times during the 2008 - 09 philadelphia flyers season . | {'scope': 'all', 'criterion': 'equal', 'value': 'philadelphia', 'result': '6', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'philadelphia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose visitor record fuzzily matches to philadelphia .', 'tostr': 'filter_eq { all_rows ; visitor ; philadelphia }'}], 'result': '6', 'ind':... | eq { count { filter_eq { all_rows ; visitor ; philadelphia } } ; 6 } = true | select the rows whose visitor record fuzzily matches to philadelphia . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'visitor_5': 5, 'philadelphia_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'visitor_5': 'visitor', 'philadelphia_6': 'philadelphia', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'visitor_5': [0], 'philadelphia_6': [0], '6_7': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 2', 'tampa bay', '3 - 4', 'philadelphia', 'biron', '19227', '12 - 7 - 5'], ['december 4', 'new jersey', '3 - 2', 'philadelphia', 'biron', '19577', '12 - 7 - 6'], ['december 6', 'philadelphia', '2 - 1', 'carolina', 'niittymaki', '14061', '13 - 7 - 6'], ['december 9', 'ny islanders', '3 - 4', 'philadelphia', ... |
fiba eurobasket 2007 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-2.html.csv | aggregation | members of the israeli men 's fiba eurobasket 2007 squad averaged 1.97 meters in height . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '1.97 meters', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height'], 'result': '1.97 meters', 'ind': 0, 'tostr': 'avg { all_rows ; height }'}, '1.97 meters'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height } ; 1.97 meters } = true', 'tointer': 'the average of the height record of all ro... | round_eq { avg { all_rows ; height } ; 1.97 meters } = true | the average of the height record of all rows is 1.97 meters . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height_4': 4, '1.97 meters_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height_4': 'height', '1.97 meters_5': '1.97 meters'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height_4': [0], '1.97 meters_5': [1]} | ['player', 'height', 'position', 'year born', 'current club'] | [['dror hagag', '1.78', 'guard', '1978', 'hapoel jerusalem'], ['moran rot', '1.78', 'guard', '1982', 'hapoel holon'], ['yotam halperin', '1.96', 'guard', '1984', 'maccabi tel aviv'], ['lior eliyahu', '2.05', 'forward', '1985', 'maccabi tel aviv'], ['erez markovich', '2.08', 'center', '1978', 'hapoel jerusalem'], ['jero... |
roberta vinci | https://en.wikipedia.org/wiki/Roberta_Vinci | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1818978-1.html.csv | majority | the majority of these events took place on a hard surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'year', 'championship', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', '2012', 'australian open', 'hard', 'sara errani', 'svetlana kuznetsova vera zvonareva', '5 - 7 , 6 - 4 , 6 - 3'], ['winner', '2012', 'french open', 'clay', 'sara errani', 'maria kirilenko nadia petrova', '4 - 6 , 6 - 4 , 6 - 2'], ['winner', '2012', 'us open', 'hard', 'sara errani', 'andrea hlaváčková l... |
fairuz fauzy | https://en.wikipedia.org/wiki/Fairuz_Fauzy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1628093-1.html.csv | majority | for fairuz fauzy , when he had over 20 races , he never had any wins . | {'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '0', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '20'}} | {'func': 'all_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'races', '20'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; races ; 20 }', 'tointer': 'select the rows whose races record is greater than 20 .'}, 'wins', '0'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose race... | all_eq { filter_greater { all_rows ; races ; 20 } ; wins ; 0 } = true | select the rows whose races record is greater than 20 . for the wins records of these rows , all of them are equal to 0 . | 2 | 2 | {'all_eq_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'races_4': 4, '20_5': 5, 'wins_6': 6, '0_7': 7} | {'all_eq_1': 'all_eq', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'races_4': 'races', '20_5': '20', 'wins_6': 'wins', '0_7': '0'} | {'all_eq_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'races_4': [0], '20_5': [0], 'wins_6': [1], '0_7': [1]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'pos'] | [['2003', 'british formula three season', 'promatecme uk / team syr', '24', '0', '0', '0', '0', '30.5', '16th'], ['2004', 'british formula three season', 'menu f3 motorsport / p1 racing', '24', '0', '0', '0', '1', '49', '12th'], ['2005', 'gp2 series', 'dams', '23', '0', '0', '0', '0', '0', '24th'], ['2005 - 06', 'a1 gr... |
list of active indonesian navy ships | https://en.wikipedia.org/wiki/List_of_active_Indonesian_Navy_ships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12232526-2.html.csv | majority | the majority of ships are reportedly still active as of 2009 . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'present', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'service years', 'present'], 'result': True, 'ind': 0, 'tointer': 'for the service years records of all rows , all of them fuzzily match to present .', 'tostr': 'all_eq { all_rows ; service years ; present } = true'} | all_eq { all_rows ; service years ; present } = true | for the service years records of all rows , all of them fuzzily match to present . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'service years_3': 3, 'present_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'service years_3': 'service years', 'present_4': 'present'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'service years_3': [0], 'present_4': [0]} | ['class', 'ship name', 'origin', 'hull numbers', 'service years', 'previously', 'note'] | [['ahmad yani class ( ffghm )', 'kri ahmad yani', 'netherlands', '351', '1986 - present', 'rnn hnlms tjerk hiddes ( f804 )', 'reportedly still active as of 2009'], ['ahmad yani class ( ffghm )', 'kri slamet riyadi', 'netherlands', '352', '1986 - present', 'rnn hnlms van speijk ( f802 )', 'reportedly still active as of ... |
dragon zakura ( tv series ) | https://en.wikipedia.org/wiki/Dragon_Zakura_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25847911-1.html.csv | superlative | english showdown ! fight for stupid 6 was the highest rated episode of dragon zakura . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'ratings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; ratings }'}, 'translation of title'], 'result': 'english showdown ! fight for stupid 6', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; ratings } ; translat... | eq { hop { argmax { all_rows ; ratings } ; translation of title } ; english showdown ! fight for stupid 6 } = true | select the row whose ratings record of all rows is maximum . the translation of title record of this row is english showdown ! fight for stupid 6 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'ratings_5': 5, 'translation of title_6': 6, 'english showdown! fight for stupid 6_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'ratings_5': 'ratings', 'translation of title_6': 'translation of title', 'english showdown! fight for stupid 6_7': 'english showdown ! fight for stupid 6'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'ratings_5': [0], 'translation of title_6': [1], 'english showdown! fight for stupid 6_7': [2]} | ['', 'episode title', 'romanized title', 'translation of title', 'broadcast date', 'ratings'] | [['ep 2', '自分の弱さを知れ !', 'jibun no yowasa wo shire !', 'know your weaknesses !', 'july 15 , 2005', '16.5 %'], ['ep 3', '遊べ!受験はスポーツだ !', 'asobe ! juken wa supootsu da !', 'entrance exams are sports , so play !', 'july 22 , 2005', '13.8 %'], ['ep 4', '壁にぶつかるまで我慢しろ', 'kabe ni butsukaru made gaman shiro', 'hold out until yo... |
1969 - 70 segunda división | https://en.wikipedia.org/wiki/1969%E2%80%9370_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17846691-2.html.csv | majority | all clubs which participated in the 1969 - 70 segunda división season games each played 38 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '38', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '38'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 38 .', 'tostr': 'all_eq { all_rows ; played ; 38 } = true'} | all_eq { all_rows ; played ; 38 } = true | for the played records of all rows , all of them are equal to 38 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '38_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '38_4': '38'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '38_4': [0]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'real gijón', '38', '54', '23', '8', '7', '77', '32', '+ 45'], ['2', 'cd málaga', '38', '49', '17', '15', '6', '56', '33', '+ 23'], ['3', 'rcd español', '38', '49', '19', '11', '8', '64', '35', '+ 29'], ['4', 'real betis', '38', '47', '16', '15', '7', '44', '34', '+ 10'], ['5', 'córdoba cf', '38', '43', '17', '9... |
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/2-12030247-7.html.csv | comparative | the amount of money raised in the third quarter by fred thompson was more than that by john mccain . | {'row_1': '3', 'row_2': '5', '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', 'candidate', 'fred thompson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidate record fuzzily matches to fred thompson .', 'tostr': 'filter_eq { all_rows ; candidate ; fred thompson }'}, 'money... | greater { hop { filter_eq { all_rows ; candidate ; fred thompson } ; money raised , 3q } ; hop { filter_eq { all_rows ; candidate ; john mccain } ; money raised , 3q } } = true | select the rows whose candidate record fuzzily matches to fred thompson . take the money raised , 3q record of this row . select the rows whose candidate record fuzzily matches to john mccain . take the money raised , 3q 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, 'candidate_7': 7, 'fred thompson_8': 8, 'money raised , 3q_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'candidate_11': 11, 'john mccain_12': 12, 'money raised , 3q_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', 'candidate_7': 'candidate', 'fred thompson_8': 'fred thompson', 'money raised , 3q_9': 'money raised , 3q', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_r... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'candidate_7': [0], 'fred thompson_8': [0], 'money raised , 3q_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'candidate_11': [1], 'john mccain_12': [1], 'money raised , 3q_13': [3]} | ['candidate', 'money raised , 3q', 'loans received , 3q', 'money spent , 3q', 'total receipts', 'cash on hand', 'total debt', 'after debt'] | [['rudy giuliani', '11624255', '-', '13300649', '47253520', '16649825', '169256', '16480569'], ['mitt romney', '9896719', '8500000', '21301755', '62829068', '9216517', '17350000', '- 8133483'], ['fred thompson', '9750820', '-', '5706366', '12828110', '7121744', '678432', '6443312'], ['ron paul', '5258455', '-', '216964... |
diezel | https://en.wikipedia.org/wiki/Diezel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1844725-1.html.csv | unique | of diezel 's amplifiers , the schmidt model is the only one with an output of 15 - 30w . | {'scope': 'all', 'row': '6', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '15 - 30w', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'output', '15 - 30w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose output record fuzzily matches to 15 - 30w .', 'tostr': 'filter_eq { all_rows ; output ; 15 - 30w }'}], 'result': True, 'ind': 1, 'tostr': '... | and { only { filter_eq { all_rows ; output ; 15 - 30w } } ; eq { hop { filter_eq { all_rows ; output ; 15 - 30w } ; model } ; schmidt } } = true | select the rows whose output record fuzzily matches to 15 - 30w . there is only one such row in the table . the model record of this unqiue row is schmidt . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'output_7': 7, '15 - 30w_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'model_9': 9, 'schmidt_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'output_7': 'output', '15 - 30w_8': '15 - 30w', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'model_9': 'model', 'schmidt_10': 'schmidt'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'output_7': [0], '15 - 30w_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'model_9': [2], 'schmidt_10': [3]} | ['model', 'poweramp', 'dimensions', 'mass', 'form factor ( s )', 'output'] | [['vh4', 'mono , 4 tubes', '29 11 11 in 74 28 28 cm', '50 lb ( 23 kg )', 'head', '90 - 160w'], ['vh4s', 'stereo , 4 tubes', '29 11 11 in 74 28 28 cm', '50 lb ( 23 kg )', 'head', '2 50w'], ['herbert', 'mono , 6 tubes', '29 11 11 in 74 28 28 cm', '60 lb ( 27 kg )', 'head', '180w'], ['hagen', 'mono , 4 tubes', '29 11 11 i... |
1962 denver broncos season | https://en.wikipedia.org/wiki/1962_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17778417-1.html.csv | count | six of the games took place in the bears stadium . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'bears stadium', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'bears stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to bears stadium .', 'tostr': 'filter_eq { all_rows ; game site ; bears stadium }'}], 'result': '6... | eq { count { filter_eq { all_rows ; game site ; bears stadium } } ; 6 } = true | select the rows whose game site record fuzzily matches to bears stadium . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'bears stadium_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'bears stadium_6': 'bears stadium', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'bears stadium_6': [0], '6_7': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 7 , 1962', 'san diego chargers', 'w 30 - 21', 'university of denver stadium', '1 - 0', '28000'], ['2', 'september 15 , 1962', 'buffalo bills', 'w 23 - 20', 'war memorial stadium', '2 - 0', '30577'], ['3', 'september 21 , 1962', 'boston patriots', 'l 16 - 41', 'boston university field', '2 - 1', '21038... |
1982 formula one season | https://en.wikipedia.org/wiki/1982_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1140076-2.html.csv | count | renault was the constructor for four of the 1982 formula one race winners . | {'scope': 'all', 'criterion': 'equal', 'value': 'renault', 'result': '4', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constructor', 'renault'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constructor record fuzzily matches to renault .', 'tostr': 'filter_eq { all_rows ; constructor ; renault }'}], 'result': '4', 'ind': 1,... | eq { count { filter_eq { all_rows ; constructor ; renault } } ; 4 } = true | select the rows whose constructor record fuzzily matches to renault . 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, 'constructor_5': 5, 'renault_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', 'constructor_5': 'constructor', 'renault_6': 'renault', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'constructor_5': [0], 'renault_6': [0], '4_7': [2]} | ['rnd', 'race', 'date', 'location', 'pole position', 'fastest lap', 'race winner', 'constructor', 'report'] | [['1', 'south african grand prix', '23 january', 'kyalami', 'rené arnoux', 'alain prost', 'alain prost', 'renault', 'report'], ['2', 'brazilian grand prix', '21 march', 'jacarepaguá', 'alain prost', 'alain prost', 'alain prost', 'renault', 'report'], ['3', 'united states grand prix west', '4 april', 'long beach', 'andr... |
list of west indies test wicket - keepers | https://en.wikipedia.org/wiki/List_of_West_Indies_Test_wicket-keepers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27771406-1.html.csv | superlative | gerry alexander has the most total dismissals among west indies test wicket - keepers . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total dismissals'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total dismissals }'}, 'no'], 'result': '13', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total dismissals } ; no }'}, '13'], 'result': True, 'ind': ... | eq { hop { argmax { all_rows ; total dismissals } ; no } ; 13 } = true | select the row whose total dismissals record of all rows is maximum . the no record of this row is 13 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total dismissals_5': 5, 'no_6': 6, '13_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total dismissals_5': 'total dismissals', 'no_6': 'no', '13_7': '13'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total dismissals_5': [0], 'no_6': [1], '13_7': [2]} | ['no', 'player', 'club', 'test career', 'tests', 'catches', 'stumpings', 'total dismissals'] | [['2', 'errol hunte', 'trinidad and tobago', '1930', '3', '5', '0', '5'], ['3', 'ivan barrow', 'jamaica', '1930 - 1939', '11', '17', '5', '22'], ['4', 'cyril christiani', 'british guiana', '1935', '4', '6', '1', '7'], ['8', 'alfred binns', 'jamaica', '1953 - 1956', '5', '14', '3', '17'], ['9', 'ralph legall', 'trinidad... |
georgia collegiate athletic association | https://en.wikipedia.org/wiki/Georgia_Collegiate_Athletic_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16734640-1.html.csv | comparative | south georgia technical college was founded 13 years before southern crescent technical college . | {'row_1': '18', 'row_2': '19', 'col': '4', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '13', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'south georgia technical college'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to south georgia technical college .', 'tostr': ... | eq { diff { hop { filter_eq { all_rows ; institution ; south georgia technical college } ; founded } ; hop { filter_eq { all_rows ; institution ; southern crescent technical college } ; founded } } ; -13 } = true | select the rows whose institution record fuzzily matches to south georgia technical college . take the founded record of this row . select the rows whose institution record fuzzily matches to southern crescent technical college . take the founded record of this row . the second record is 13 larger than the first 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, 'institution_8': 8, 'south georgia technical college_9': 9, 'founded_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'institution_12': 12, 'southern crescent technical college_13': 13, 'founded_14': 14, '-13... | {'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', 'institution_8': 'institution', 'south georgia technical college_9': 'south georgia technical college', 'founded_10': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_s... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'institution_8': [0], 'south georgia technical college_9': [0], 'founded_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'institution_12': [1], 'southern crescent technical college_13': [1],... | ['institution', 'location', 'nickname', 'founded', 'enrollment', 'joined'] | [['abraham baldwin agricultural college', 'tifton', 'stallions', '1908', '3284', '2010'], ['albany technical college', 'albany', 'titans', '1961', '4000', '2010'], ['andrew college', 'cuthbert', 'fighting tigers', '1854', '350', '2010'], ['atlanta metropolitan state college', 'atlanta', 'trailblazers', '1965', '2001', ... |
tom lehman | https://en.wikipedia.org/wiki/Tom_Lehman | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1516564-12.html.csv | majority | tom lehman participated in more tournaments than he won . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'wins', '0'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; wins ; 0 } = true'} | most_eq { all_rows ; wins ; 0 } = true | for the wins records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '0_4': [0]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '2', '3', '7', '13', '9'], ['us open', '0', '4', '5', '8', '18', '12'], ['the open championship', '1', '2', '2', '7', '20', '13'], ['pga championship', '0', '0', '1', '2', '17', '10'], ['totals', '1', '8', '11', '24', '68', '44']] |
1982 vfl season | https://en.wikipedia.org/wiki/1982_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10824095-16.html.csv | aggregation | the average crowd attendance for the 1982 vfl season is around 24000 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '24000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '24000', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '24000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 24000 } = true', 'tointer': 'the average of the crowd record of all rows is 24000 .'} | round_eq { avg { all_rows ; crowd } ; 24000 } = true | the average of the crowd record of all rows is 24000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '24000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '24000_5': '24000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '24000_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '32.14 ( 206 )', 'north melbourne', '15.22 ( 112 )', 'princes park', '18760', '10 july 1982'], ['footscray', '25.7 ( 157 )', 'geelong', '17.13 ( 115 )', 'western oval', '14004', '10 july 1982'], ['carlton', '21.13 ( 139 )', 'st kilda', '9.9 ( 63 )', 'vfl park', '27829', '10 july 1982'], ['melbourne', '9.1... |
1972 isle of man tt | https://en.wikipedia.org/wiki/1972_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15753390-4.html.csv | majority | all of the riders that participated were from the united kingdom . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united kingdom', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united kingdom'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united kingdom .', 'tostr': 'most_eq { all_rows ; country ; united kingdom } = true'} | most_eq { all_rows ; country ; united kingdom } = true | for the country records of all rows , most of them fuzzily match to united kingdom . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united kingdom_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united kingdom_4': 'united kingdom'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united kingdom_4': [0]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'chas mortimer', 'united kingdom', 'yamaha', '87.49 mph', '1:17.38.2', '15'], ['2', 'charlie williams', 'united kingdom', 'yamaha', '80.49 mph', '1:24.23.0', '12'], ['3', 'billy rae', 'united kingdom', 'maico', '79.29 mph', '1:25.39.8', '10'], ['4', 'lindsay porter', 'united kingdom', 'honda', '78.63 mph', '1:26... |
2007 - 08 leb season | https://en.wikipedia.org/wiki/2007%E2%80%9308_LEB_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16176685-4.html.csv | count | three of the players scored over 30 points each in the 2007 -08 leb season . | {'scope': 'all', 'criterion': 'greater_than', 'value': '30', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'games', '30'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose games record is greater than 30 .', 'tostr': 'filter_greater { all_rows ; games ; 30 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_grea... | eq { count { filter_greater { all_rows ; games ; 30 } } ; 3 } = true | select the rows whose games record is greater than 30 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'games_5': 5, '30_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'games_5': 'games', '30_6': '30', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'games_5': [0], '30_6': [0], '3_7': [2]} | ['rank', 'name', 'team', 'games', 'points'] | [['1', 'jakim donaldson', 'ciudad de la laguna', '36', '357'], ['2', 'oriol junyent', 'ciudad de huelva', '21', '204'], ['3', 'serge ibaka', "l'hospitalet", '28', '234'], ['4', 'ondrej starosta', 'cai zaragoza', '34', '259'], ['5', 'andrew panko', 'bruesa gbc', '38', '287']] |
2007 cfl draft | https://en.wikipedia.org/wiki/2007_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10812403-3.html.csv | count | mcmaster had three players selected between 17th and 24th in the draft . | {'scope': 'all', 'criterion': 'equal', 'value': 'mcmaster', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'mcmaster'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to mcmaster .', 'tostr': 'filter_eq { all_rows ; college ; mcmaster }'}], 'result': '3', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; college ; mcmaster } } ; 3 } = true | select the rows whose college record fuzzily matches to mcmaster . 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, 'college_5': 5, 'mcmaster_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', 'college_5': 'college', 'mcmaster_6': 'mcmaster', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college_5': [0], 'mcmaster_6': [0], '3_7': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['17', 'bc lions ( via hamilton )', 'tad crawford', 's', 'columbia'], ['18', 'montreal alouettes ( via edmonton )', 'chris van zeyl', 'dl', 'mcmaster'], ['19', 'montreal alouettes ( via hamilton via winnipeg )', 'brian jones', 'ol', 'windsor'], ['20', 'saskatchewan roughriders', 'yannick carter', 'lb', 'wilfrid laurie... |
2007 - 08 san antonio spurs season | https://en.wikipedia.org/wiki/2007%E2%80%9308_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963601-6.html.csv | ordinal | in the 2007 - 08 san antonio spurs season the game with the spurs as the visitor with the highest attendance had jazz as the home team . | {'scope': 'subset', 'row': '14', 'col': '6', 'order': '1', 'col_other': '2,4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'spurs'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'spurs'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; visitor ; spurs }', 'tointer': 'select the rows whose visitor record fuzzily matches to spurs .'}, 'atte... | eq { hop { nth_argmax { filter_eq { all_rows ; visitor ; spurs } ; attendance ; 1 } ; home } ; jazz } = true | select the rows whose visitor record fuzzily matches to spurs . select the row whose attendance record of these rows is 1st maximum . the home record of this row is jazz . | 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, 'visitor_6': 6, 'spurs_7': 7, 'attendance_8': 8, '1_9': 9, 'home_10': 10, 'jazz_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', 'visitor_6': 'visitor', 'spurs_7': 'spurs', 'attendance_8': 'attendance', '1_9': '1', 'home_10': 'home', 'jazz_11': 'jazz'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'visitor_6': [0], 'spurs_7': [0], 'attendance_8': [1], '1_9': [1], 'home_10': [2], 'jazz_11': [3]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['january 3 , 2008', 'spurs', '77 - 80', 'nuggets', 'two - way tie ( 20 )', '19155', '21 - 9'], ['january 4 , 2008', 'knicks', '93 - 97', 'spurs', 'bruce bowen ( 15 )', '18797', '22 - 9'], ['january 6 , 2008', 'spurs', '88 - 82', 'clippers', 'tony parker ( 26 )', '16623', '23 - 9'], ['january 7 , 2008', 'spurs', '121 ... |
list of intel core i7 microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Core_i7_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18823880-1.html.csv | count | two of the intel core i7 microprocessors released have a price of 999 us dollars . | {'scope': 'all', 'criterion': 'equal', 'value': '999', 'result': '2', 'col': '15', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'release price ( usd )', '999'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose release price ( usd ) record is equal to 999 .', 'tostr': 'filter_eq { all_rows ; release price ( usd ) ; 999 }'}], 'result': '2', 'i... | eq { count { filter_eq { all_rows ; release price ( usd ) ; 999 } } ; 2 } = true | select the rows whose release price ( usd ) record is equal to 999 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'release price ( usd )_5': 5, '999_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'release price ( usd )_5': 'release price ( usd )', '999_6': '999', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'release price ( usd )_5': [0], '999_6': [0], '2_7': [2]} | ['model number', 'sspec number', 'frequency', 'turbo', 'cores', 'l2 cache', 'l3 cache', 'i / o bus', 'mult', 'memory', 'voltage', 'socket', 'release date', 'part number ( s )', 'release price ( usd )'] | [['core i7 - 920', 'slbch ( c0 ) slbej ( d0 )', '2.67 ghz', '1 / 1 / 1 / 2', '4', '4 256 kb', '8 mb', '1 4.8 gt / s qpi', '20', '3 ddr3 - 1066', '0.8 - 1.375 v', 'lga 1366', 'november 2008', 'bx80601920at80601000741aa', '284'], ['core i7 - 930', 'slbkp ( d0 )', '2.8 ghz', '1 / 1 / 1 / 2', '4', '4 256 kb', '8 mb', '1 4.... |
list of victorious episodes | https://en.wikipedia.org/wiki/List_of_Victorious_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26448179-2.html.csv | majority | most of the episodes of victorious written by dan schneider had less than 5 million viewers . | {'scope': 'subset', 'col': '7', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '5 million', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'dan schneider'}} | {'func': 'most_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'dan schneider'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; written by ; dan schneider }', 'tointer': 'select the rows whose written by record fuzzily matches to dan schneider .'}, 'us viewers ( millions )', '5 ... | most_less { filter_eq { all_rows ; written by ; dan schneider } ; us viewers ( millions ) ; 5 million } = true | select the rows whose written by record fuzzily matches to dan schneider . for the us viewers ( millions ) records of these rows , most of them are less than 5 million . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'written by_4': 4, 'dan schneider_5': 5, 'us viewers (millions)_6': 6, '5 million_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'written by_4': 'written by', 'dan schneider_5': 'dan schneider', 'us viewers (millions)_6': 'us viewers ( millions )', '5 million_7': '5 million'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'written by_4': [0], 'dan schneider_5': [0], 'us viewers (millions)_6': [1], '5 million_7': [1]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['1', 'pilot', 'steve hoefer', 'dan schneider', 'march 27 , 2010', '101', '5.7'], ['2', 'the bird scene', 'steve hoefer', 'dan schneider', 'april 11 , 2010', '102', '3.5'], ['3', 'stage fighting', 'steve hoefer', 'george doty iv', 'april 18 , 2010', '103', '3.3'], ['4', 'the birthweek song', 'adam weissman', 'jake far... |
césar cielo | https://en.wikipedia.org/wiki/C%C3%A9sar_Cielo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12627202-1.html.csv | majority | most of the events that césar cielo competed in were freestyle events . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'freestyle', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'event', 'freestyle'], 'result': True, 'ind': 0, 'tointer': 'for the event records of all rows , most of them fuzzily match to freestyle .', 'tostr': 'most_eq { all_rows ; event ; freestyle } = true'} | most_eq { all_rows ; event ; freestyle } = true | for the event records of all rows , most of them fuzzily match to freestyle . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'event_3': 3, 'freestyle_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'event_3': 'event', 'freestyle_4': 'freestyle'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'event_3': [0], 'freestyle_4': [0]} | ['event', 'time', 'venue', 'date', 'notes'] | [['50 m freestyle', '20.91', 'são paulo', 'december 18 , 2009', 'wr'], ['100 m freestyle', '46.91', 'rome', 'july 30 , 2009', 'wr'], ['50 m freestyle', '21.30', 'beijing', 'august 16 , 2008', 'or'], ['50 m butterfly', '22.76', 'rio de janeiro', 'april 26 , 2012', 'am'], ['450 m freestyle', '1:26.12', 'são paulo', 'dece... |
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 | majority | the majority of entrans were with osella squadra corse . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'osella squadra corse', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'entrant', 'osella squadra corse'], 'result': True, 'ind': 0, 'tointer': 'for the entrant records of all rows , most of them fuzzily match to osella squadra corse .', 'tostr': 'most_eq { all_rows ; entrant ; osella squadra corse } = true'} | most_eq { all_rows ; entrant ; osella squadra corse } = true | for the entrant records of all rows , most of them fuzzily match to osella squadra corse . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'entrant_3': 3, 'osella squadra corse_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'entrant_3': 'entrant', 'osella squadra corse_4': 'osella squadra corse'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'entrant_3': [0], 'osella squadra corse_4': [0]} | ['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 career achievements by jack nicklaus | https://en.wikipedia.org/wiki/List_of_career_achievements_by_Jack_Nicklaus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13026799-1.html.csv | superlative | nicklaus 's greatest margin of victory was 9 strokes in the 1965 masters tournament . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1,2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'margin'], 'result': '9 strokes', 'ind': 0, 'tostr': 'max { all_rows ; margin }', 'tointer': 'the maximum margin record of all rows is 9 strokes .'}, '9 strokes'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; margin } ; 9... | and { eq { max { all_rows ; margin } ; 9 strokes } ; and { eq { hop { argmax { all_rows ; margin } ; year } ; 4 . 1965 } ; eq { hop { argmax { all_rows ; margin } ; championship } ; masters tournament ( 2 ) } } } = true | the maximum margin record of all rows is 9 strokes . the year record of the row with superlative margin record is 4 . 1965 . the championship record of the row with superlative margin record is masters tournament ( 2 ) . | 10 | 9 | {'and_8': 8, 'result_9': 9, 'eq_1': 1, 'max_0': 0, 'all_rows_10': 10, 'margin_11': 11, '9 strokes_12': 12, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_13': 13, 'margin_14': 14, 'year_15': 15, '4. 1965_16': 16, 'str_eq_6': 6, 'str_hop_5': 5, 'championship_17': 17, 'masters tournament (2)_18': 18} | {'and_8': 'and', 'result_9': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_10': 'all_rows', 'margin_11': 'margin', '9 strokes_12': '9 strokes', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_13': 'all_rows', 'margin_14': 'margin', 'year_15': 'year', '4. 1965_16': '4 . 19... | {'and_8': [9], 'result_9': [], 'eq_1': [8], 'max_0': [1], 'all_rows_10': [0], 'margin_11': [0], '9 strokes_12': [1], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'argmax_2': [3, 5], 'all_rows_13': [2], 'margin_14': [2], 'year_15': [3], '4. 1965_16': [4], 'str_eq_6': [7], 'str_hop_5': [6], 'championship_17': [5], 'm... | ['year', 'championship', '54 holes', 'winning score', 'margin'] | [['1 . 1962', 'us open', '2 shot deficit', '1 ( 72 + 70 + 72 + 69 = 283 )', 'playoff 1'], ['2 . 1963', 'masters tournament', '1 shot lead', '2 ( 74 + 66 + 74 + 72 = 286 )', '1 stroke'], ['3 . 1963', 'pga championship', '3 shot deficit', '5 ( 69 + 73 + 69 + 68 = 279 )', '2 strokes'], ['4 . 1965', 'masters tournament ( 2... |
1981 cleveland browns season | https://en.wikipedia.org/wiki/1981_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10650489-1.html.csv | superlative | the lowest number overall for a defensive back is 22 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'defensive back'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defensive back'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; defensive back }', 'tointer': 'select the rows whose position record fuzzily matches to defensive back .'}, 'overall'], 're... | eq { min { filter_eq { all_rows ; position ; defensive back } ; overall } ; 22 } = true | select the rows whose position record fuzzily matches to defensive back . the minimum overall record of these rows is 22 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'defensive back_6': 6, 'overall_7': 7, '22_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'defensive back_6': 'defensive back', 'overall_7': 'overall', '22_8': '22'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'defensive back_6': [0], 'overall_7': [1], '22_8': [2]} | ['round', 'overall', 'player', 'position', 'school / club team'] | [['1', '22', 'hanford dixon', 'defensive back', 'southern miss'], ['4', '92', 'mike robinson', 'defensive end', 'arizona'], ['5', '134', 'steve cox', 'punter', 'arkansas'], ['6', '160', 'ron simmons', 'defensive tackle', 'florida state'], ['7', '187', 'eddie johnson', 'linebacker', 'louisville'], ['9', '244', 'randy sc... |
2001 senior pga tour | https://en.wikipedia.org/wiki/2001_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11603267-3.html.csv | superlative | allen doyle participated in the most events in the 2001 pga tour . | {'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', 'events'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; events }'}, 'player'], 'result': 'allen doyle', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; events } ; player }'}, 'allen doyle'], 'result': True, 'ind': ... | eq { hop { argmax { all_rows ; events } ; player } ; allen doyle } = true | select the row whose events record of all rows is maximum . the player record of this row is allen doyle . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'events_5': 5, 'player_6': 6, 'allen doyle_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'events_5': 'events', 'player_6': 'player', 'allen doyle_7': 'allen doyle'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'events_5': [0], 'player_6': [1], 'allen doyle_7': [2]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'allen doyle', 'united states', '2553582', '34', '2'], ['2', 'bruce fleisher', 'united states', '2411543', '31', '3'], ['3', 'hale irwin', 'united states', '2147422', '26', '3'], ['4', 'larry nelson', 'united states', '2109936', '28', '5'], ['5', 'gil morgan', 'united states', '1885871', '24', '2']] |
six flags magic mountain | https://en.wikipedia.org/wiki/Six_Flags_Magic_Mountain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1017230-2.html.csv | ordinal | revolution has the earliest year first opened among those located in baja ridge in six flags magic mountain . | {'scope': 'subset', 'row': '11', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'baja ridge'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location in park', 'baja ridge'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location in park ; baja ridge }', 'tointer': 'select the rows whose location in park recor... | eq { hop { nth_argmin { filter_eq { all_rows ; location in park ; baja ridge } ; year first opened ; 1 } ; current name } ; revolution } = true | select the rows whose location in park record fuzzily matches to baja ridge . select the row whose year first opened record of these rows is 1st minimum . the current name record of this row is revolution . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location in park_6': 6, 'baja ridge_7': 7, 'year first opened_8': 8, '1_9': 9, 'current name_10': 10, 'revolution_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location in park_6': 'location in park', 'baja ridge_7': 'baja ridge', 'year first opened_8': 'year first opened', '1_9': '1', 'current name_10': 'current name'... | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location in park_6': [0], 'baja ridge_7': [0], 'year first opened_8': [1], '1_9': [1], 'current name_10': [2], 'revolution_11': [3]} | ['current name', 'year first opened', 'manufacturer', 'location in park', 'thrill / intensity rating', 'minimum height requirements'] | [['apocalypse : the ride', '2009', 'great coasters international', 'cyclone bay', 'moderate', '48'], ['batman : the ride', '1994', 'bolliger & mabillard', 'dc universe', 'maximum', '54'], ['canyon blaster', '1999', 'e & f miler industries', 'high sierra territory', 'mild', "33 to ride with an adult '36 to ride alone"],... |
wichita - class replenishment oiler | https://en.wikipedia.org/wiki/Wichita-class_replenishment_oiler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15204876-1.html.csv | count | for the wichita - class replenishment oiler , when the builder is general dynamics , quincy , there were two ships that were commissioned in 1969 . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '1969', 'result': '2', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'general dynamics , quincy'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'general dynamics , quincy'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; builder ; general dynamics , quincy }', 'tointer': 'select the rows whose builder recor... | eq { count { filter_eq { filter_eq { all_rows ; builder ; general dynamics , quincy } ; commissioned - decommissioned ; 1969 } } ; 2 } = true | select the rows whose builder record fuzzily matches to general dynamics , quincy . among these rows , select the rows whose commissioned - decommissioned record fuzzily matches to 1969 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'builder_6': 6, 'general dynamics , quincy_7': 7, 'commissioned - decommissioned_8': 8, '1969_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'builder_6': 'builder', 'general dynamics , quincy_7': 'general dynamics , quincy', 'commissioned - decommissioned_8': 'commissioned - decommissioned', '1969_9': '1969... | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'builder_6': [0], 'general dynamics , quincy_7': [0], 'commissioned - decommissioned_8': [1], '1969_9': [1], '2_10': [3]} | ['ship', 'hull no', 'builder', 'home port', 'commissioned - decommissioned', 'nvr page'] | [['wichita', 'aor - 1', 'general dynamics , quincy', 'oakland', '1969 - 1993', 'aor - 1'], ['milwaukee', 'aor - 2', 'general dynamics , quincy', 'norfolk', '1969 - 1994', 'aor - 2'], ['kansas city', 'aor - 3', 'general dynamics , quincy', 'oakland', '1970 - 1994', 'aor - 3'], ['savannah', 'aor - 4', 'general dynamics ,... |
berlusconi iv cabinet | https://en.wikipedia.org/wiki/Berlusconi_IV_Cabinet | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17310356-2.html.csv | superlative | the latest date that a prime minister took office in the berlusconi iv cabinet was in july of 2011 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'took office'], 'result': '27 july 2011', 'ind': 0, 'tostr': 'max { all_rows ; took office }', 'tointer': 'the maximum took office record of all rows is 27 july 2011 .'}, '27 july 2011'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; took office }... | eq { max { all_rows ; took office } ; 27 july 2011 } = true | the maximum took office record of all rows is 27 july 2011 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'took office_4': 4, '27 july 2011_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'took office_4': 'took office', '27 july 2011_5': '27 july 2011'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'took office_4': [0], '27 july 2011_5': [1]} | ['portfolio', 'minister', 'took office', 'left office', 'party'] | [['minister european affairs', 'andrea ronchi', '8 may 2008', '15 november 2010', 'the people of freedom'], ['minister european affairs', 'anna maria bernini ( it )', '27 july 2011', '16 november 2011', 'the people of freedom'], ['minister of federal reforms', 'umberto bossi', '8 may 2008', '16 november 2011', 'lega no... |
kuba giermaziak | https://en.wikipedia.org/wiki/Kuba_Giermaziak | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26473176-1.html.csv | aggregation | kuba giermaziak scored a combinbed total of 626 points in his racing career . | {'scope': 'all', 'col': '8', 'type': 'sum', 'result': '626', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '626', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '626'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 626 } = true', 'tointer': 'the sum of the points record of all rows is 626 .'} | round_eq { sum { all_rows ; points } ; 626 } = true | the sum of the points record of all rows is 626 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '626_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '626_5': '626'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '626_5': [1]} | ['season', 'series', 'team', 'races', 'wins', 'f / laps', 'podiums', 'points', 'position'] | [['2007', 'formula renault 2.0 nec', 'motopark academy', '15', '0', '0', '0', '97', '10th'], ['2007', 'formula renault 2.0 eurocup', 'motopark academy', '2', '0', '0', '0', '0', 'nc'], ['2008', 'formula renault 2.0 eurocup', 'motopark academy', '14', '0', '0', '0', '10', '18th'], ['2008', 'formula renault 2.0 nec', 'mo... |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-12.html.csv | comparative | chauncey w reed was first elected to the united states house of representatives earlier than sid simpson . | {'row_1': '3', 'row_2': '6', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'chauncey w reed'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to chauncey w reed .', 'tostr': 'filter_eq { all_rows ; incumbent ; chauncey w reed }'}, 'fi... | less { hop { filter_eq { all_rows ; incumbent ; chauncey w reed } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; sid simpson } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to chauncey w reed . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to sid simpson . take the first elected record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'chauncey w reed_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'sid simpson_12': 12, 'first elected_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'chauncey w reed_8': 'chauncey w reed', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'inc... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'chauncey w reed_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'sid simpson_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 2', "barratt o'hara", 'democratic', '1952', 're - elected', "barratt o'hara ( d ) 61.6 % richard b vail ( r ) 38.4 %"], ['illinois 3', 'fred e busbey', 'republican', '1950', 'lost re - election democratic gain', 'james c murray ( d ) 53.8 % fred e busbey ( r ) 46.2 %'], ['illinois 14', 'chauncey w reed', 'r... |
test matches ( 1991 - 2000 ) | https://en.wikipedia.org/wiki/Test_matches_%281991%E2%80%932000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12410929-44.html.csv | unique | the cricket test match that was played at sydney cricket ground was the only one that resulted in a draw . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '4', 'criterion': 'equal', 'value': 'draw', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'draw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to draw .', 'tostr': 'filter_eq { all_rows ; result ; draw }'}], 'result': True, 'ind': 1, 'tostr': 'only { filte... | and { only { filter_eq { all_rows ; result ; draw } } ; eq { hop { filter_eq { all_rows ; result ; draw } ; venue } ; sydney cricket ground } } = true | select the rows whose result record fuzzily matches to draw . there is only one such row in the table . the venue record of this unqiue row is sydney cricket ground . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'draw_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'venue_9': 9, 'sydney cricket ground_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'draw_8': 'draw', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'venue_9': 'venue', 'sydney cricket ground_10': 'sydney cricket ground'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'draw_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'venue_9': [2], 'sydney cricket ground_10': [3]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['25 , 26 , 27 , 28 , 29 november 1994', 'mark taylor', 'mike atherton', 'brisbane cricket ground', 'aus by 184 runs'], ['24 , 26 , 27 , 28 , 29 december 1994', 'mark taylor', 'mike atherton', 'melbourne cricket ground', 'aus by 295 runs'], ['1 , 2 , 3 , 4 , 5 january 1995', 'mark taylor', 'mike atherton', 'sydney cri... |
list of geological features on ganymede | https://en.wikipedia.org/wiki/List_of_geological_features_on_Ganymede | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16768245-5.html.csv | count | there are 2 geological features on ganymede that have a sumerian town as their namesake . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'sumerian town', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'namesake', 'sumerian town'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose namesake record fuzzily matches to sumerian town .', 'tostr': 'filter_eq { all_rows ; namesake ; sumerian town }'}], 'result': '2', ... | eq { count { filter_eq { all_rows ; namesake ; sumerian town } } ; 2 } = true | select the rows whose namesake record fuzzily matches to sumerian town . 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, 'namesake_5': 5, 'sumerian town_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', 'namesake_5': 'namesake', 'sumerian town_6': 'sumerian town', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'namesake_5': [0], 'sumerian town_6': [0], '2_7': [2]} | ['name', 'latitude', 'longitude', 'diameter', 'year named', 'namesake'] | [['akitu sulcus', '38.9 n', '194.3 w', '365.0', '1997', "where marduk 's statue was carried each year"], ['apsu sulci', '39.4 s', '234.7 w', '1950.0', '1979', 'sumero - akkadian , primordial ocean'], ['arbela sulcus', '21.1 s', '349.8 w', '1940.0', '1985', 'assyrian town where ishtar was worshipped'], ['bubastis sulci'... |
jason leffler | https://en.wikipedia.org/wiki/Jason_Leffler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1637041-6.html.csv | count | jason leffler had four years where he obtained at least one top 5 finish . | {'scope': 'all', 'criterion': 'not_equal', 'value': '0', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_not_eq', 'args': ['all_rows', 'top 5', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top 5 record is not equal to 0 .', 'tostr': 'filter_not_eq { all_rows ; top 5 ; 0 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_not_eq { ... | eq { count { filter_not_eq { all_rows ; top 5 ; 0 } } ; 4 } = true | select the rows whose top 5 record is not equal to 0 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_not_eq_0': 0, 'all_rows_4': 4, 'top 5_5': 5, '0_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_not_eq_0': 'filter_not_eq', 'all_rows_4': 'all_rows', 'top 5_5': 'top 5', '0_6': '0', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_not_eq_0': [1], 'all_rows_4': [0], 'top 5_5': [0], '0_6': [0], '4_7': [2]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['2000', '1', '0', '0', '0', '0', '7.0', '29.0', '7220', '103rd', '5 ultra motorsports'], ['2002', '22', '0', '11', '15', '8', '3.9', '9.8', '525519', '4th', '2 ultra motorsports'], ['2003', '16', '1', '5', '10', '2', '8.8', '11.1', '309890', '16th', '2 ultra motorsports'], ['2004', '1', '0', '0', '0', '0', '6.0', '24... |
islands of the clyde | https://en.wikipedia.org/wiki/Islands_of_the_Clyde | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15252-1.html.csv | ordinal | on the islands of clyde , the 2nd highest height was the island of ailsa craig . | {'row': '1', 'col': '7', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'height ( m )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; height ( m ) ; 2 }'}, 'island'], 'result': 'ailsa craig', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; height ( m ) ; 2 } ; island }... | eq { hop { nth_argmax { all_rows ; height ( m ) ; 2 } ; island } ; ailsa craig } = true | select the row whose height ( m ) record of all rows is 2nd maximum . the island record of this row is ailsa craig . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'height (m)_5': 5, '2_6': 6, 'island_7': 7, 'ailsa craig_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'height (m)_5': 'height ( m )', '2_6': '2', 'island_7': 'island', 'ailsa craig_8': 'ailsa craig'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'height (m)_5': [0], '2_6': [0], 'island_7': [1], 'ailsa craig_8': [2]} | ['island', 'gaelic name', 'location', 'area ( ha )', 'population', 'last inhabited', 'height ( m )'] | [['ailsa craig', 'creag ealasaid', 'south ayrshire', '99', '0', '1980s', '338'], ['arran', 'arainn', 'arran', '43201', '4629', '-', '874'], ['bute', 'bòid', 'bute', '12217', '6498', '-', '278'], ['davaar', 'eilean dà bhàrr', 'kintyre', '52', '0', '-', '115'], ['great cumbrae', 'cumaradh mòr', 'bute', '1168', '1376', '-... |
2011 british gt season | https://en.wikipedia.org/wiki/2011_British_GT_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30062172-3.html.csv | superlative | the longest length was when the circuit was dorington park . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '17', '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', 'length'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; length }'}, 'circuit'], 'result': 'donington park', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; length } ; circuit }'}, 'donington park'], 'result': True,... | eq { hop { argmax { all_rows ; length } ; circuit } ; donington park } = true | select the row whose length record of all rows is maximum . the circuit record of this row is donington park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, 'circuit_6': 6, 'donington park_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'length_5': 'length', 'circuit_6': 'circuit', 'donington park_7': 'donington park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], 'circuit_6': [1], 'donington park_7': [2]} | ['round', 'circuit', 'date', 'length', 'pole position', 'gt3 winner', 'gt4 winner'] | [['1', 'oulton park', '25 april', '60 mins', 'no 5 scuderia vittoria', 'no 1 trackspeed', 'no 44 abg motorsport'], ['1', 'oulton park', '25 april', '60 mins', 'charles bateman michael lyons', 'david ashburn richard westbrook', 'peter belshaw marcus clutton'], ['2', 'oulton park', '25 april', '60 mins', 'no 1 trackspeed... |
1957 vfl season | https://en.wikipedia.org/wiki/1957_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10774891-13.html.csv | count | four vfl games had crowds over 20000 on 13 july 1957 . | {'scope': 'all', 'criterion': 'greater_than', 'value': '20000', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '20000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is greater than 20000 .', 'tostr': 'filter_greater { all_rows ; crowd ; 20000 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_greater { all_rows ; crowd ; 20000 } } ; 4 } = true | select the rows whose crowd record is greater than 20000 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '20000_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '20000_6': '20000', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '20000_6': [0], '4_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '12.15 ( 87 )', 'north melbourne', '8.13 ( 61 )', 'kardinia park', '14806', '13 july 1957'], ['collingwood', '7.7 ( 49 )', 'melbourne', '6.13 ( 49 )', 'victoria park', '24216', '13 july 1957'], ['carlton', '11.15 ( 81 )', 'south melbourne', '10.5 ( 65 )', 'princes park', '20572', '13 july 1957'], ['richmon... |
list of superlative academy award winners and nominees | https://en.wikipedia.org/wiki/List_of_superlative_Academy_Award_winners_and_nominees | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10966872-2.html.csv | comparative | clint eastwood was younger when he set his academy award record than john huston was for his record . | {'row_1': '3', 'row_2': '4', 'col': '3', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'clint eastwood'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to clint eastwood .', 'tostr': 'filter_eq { all_rows ; director ; clint eastwood }'}, 'record s... | less { hop { filter_eq { all_rows ; director ; clint eastwood } ; record set } ; hop { filter_eq { all_rows ; director ; john huston } ; record set } } = true | select the rows whose director record fuzzily matches to clint eastwood . take the record set record of this row . select the rows whose director record fuzzily matches to john huston . take the record set 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, 'director_7': 7, 'clint eastwood_8': 8, 'record set_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'director_11': 11, 'john huston_12': 12, 'record set_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', 'director_7': 'director', 'clint eastwood_8': 'clint eastwood', 'record set_9': 'record set', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'director_11':... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'director_7': [0], 'clint eastwood_8': [0], 'record set_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'director_11': [1], 'john huston_12': [1], 'record set_13': [3]} | ['superlative', 'director', 'record set', 'year', 'notes'] | [['most awards', 'john ford', '4 awards', '1952', 'awards resulted from 5 nominations'], ['most nominations', 'william wyler', '12 nominations', '1965', 'nominations resulted in 3 awards'], ['oldest winner', 'clint eastwood', '74 years old', '2004', 'million dollar baby'], ['oldest nominee', 'john huston', '79 years ol... |
list of amd turion microprocessors | https://en.wikipedia.org/wiki/List_of_AMD_Turion_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1604940-9.html.csv | ordinal | the amd turion microprocessor with the second highest frequency is the turion 64 x2 tl - 66 . | {'row': '11', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'frequency', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; frequency ; 2 }'}, 'model number'], 'result': 'turion 64 x2 tl - 66', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; frequency ; 2 } ; mo... | eq { hop { nth_argmax { all_rows ; frequency ; 2 } ; model number } ; turion 64 x2 tl - 66 } = true | select the row whose frequency record of all rows is 2nd maximum . the model number record of this row is turion 64 x2 tl - 66 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'frequency_5': 5, '2_6': 6, 'model number_7': 7, 'turion 64 x2 tl - 66_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', 'frequency_5': 'frequency', '2_6': '2', 'model number_7': 'model number', 'turion 64 x2 tl - 66_8': 'turion 64 x2 tl - 66'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'frequency_5': [0], '2_6': [0], 'model number_7': [1], 'turion 64 x2 tl - 66_8': [2]} | ['model number', 'frequency', 'l2 - cache', 'multiplier 1', 'voltage', 'socket', 'release date', 'order part number'] | [['turion 64 x2 tl - 56', '1800 mhz', '2 x 512 kb', '9x', '1.075 / 1.10 / 1.125 v', 'g socket s1 1', 'may 7 , 2007', 'tmdtl56hax5dc'], ['turion 64 x2 tl - 56', '1800 mhz', '2 x 512 kb', '9x', '1.075 / 1.10 / 1.125 v', 'socket s1 g1', 'may 7 , 2007', 'tmdtl56hax5dm'], ['turion 64 x2 tl - 58', '1900 mhz', '2 x 512 kb', '... |
galatasaray s.k. ( superleague formula team ) | https://en.wikipedia.org/wiki/Galatasaray_S.K._%28Superleague_Formula_team%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23293785-3.html.csv | superlative | for galatasaray s.k. , the highest number of points for race 2 was in france . | {'scope': 'all', 'col_superlative': '7', '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', 'race 2 ( pts )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; race 2 ( pts ) }'}, 'country'], 'result': 'france', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; race 2 ( pts ) } ; country }'}, 'france'], 'result... | eq { hop { argmax { all_rows ; race 2 ( pts ) } ; country } ; france } = true | select the row whose race 2 ( pts ) record of all rows is maximum . the country record of this row is france . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'race 2 (pts)_5': 5, 'country_6': 6, 'france_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'race 2 (pts)_5': 'race 2 ( pts )', 'country_6': 'country', 'france_7': 'france'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'race 2 (pts)_5': [0], 'country_6': [1], 'france_7': [2]} | ['sf round', 'country', 'location', 'date', 'driver', 'race 1 ( pts )', 'race 2 ( pts )', 'race 3', 'race total ( pts )'] | [['1', 'france', 'circuit de nevers magny - cours', '28 june 2009', 'duncan tappy', '32', '16', 'dnq', '48'], ['2', 'belgium', 'zolder', '19 july 2009', 'duncan tappy', '20', '7', 'n / a', '75'], ['3', 'england', 'donington park', '2 august 2009', 'scott mansell', '12', '14', 'dnq', '101'], ['4', 'portugal', 'estoril c... |
mecklenburg - vorpommern state election , 2002 | https://en.wikipedia.org/wiki/Mecklenburg-Vorpommern_state_election%2C_2002 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1265214-1.html.csv | ordinal | in the 2002 mecklenburg - vorpommern state election , the social democratic party ( spd ) recorded the highest number of party list votes . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'party list votes', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; party list votes ; 1 }'}, 'party'], 'result': 'social democratic party ( spd )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pa... | eq { hop { nth_argmax { all_rows ; party list votes ; 1 } ; party } ; social democratic party ( spd ) } = true | select the row whose party list votes record of all rows is 1st maximum . the party record of this row is social democratic party ( spd ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'party list votes_5': 5, '1_6': 6, 'party_7': 7, 'social democratic party (spd)_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', 'party list votes_5': 'party list votes', '1_6': '1', 'party_7': 'party', 'social democratic party (spd)_8': 'social democratic party ( spd )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'party list votes_5': [0], '1_6': [0], 'party_7': [1], 'social democratic party (spd)_8': [2]} | ['party', 'party list votes', 'vote percentage', 'total seats', 'seat percentage'] | [['social democratic party ( spd )', '394118', '40.6 %', '33', '46.5 %'], ['christian democratic union ( cdu )', '304125', '31.4 %', '25', '35.2 %'], ['party of democratic socialism ( pds )', '159065', '16.4 %', '13', '18.3 %'], ["alliance '90 / the greens", '25402', '2.6 %', '0', '0.0 %'], ['free democratic party ( fd... |
1994 - 95 cleveland cavaliers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16188254-8.html.csv | aggregation | during their 1994-1995 season , the cleveland cavaliers ' total attendance for the six games at gund arena was 123,371 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '123371', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'gund arena'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'attendance', 'gund arena'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; attendance ; gund arena }', 'tointer': 'select the rows whose attendance record fuzzily matches to gund arena .'}, 'attendance'], ... | round_eq { sum { filter_eq { all_rows ; attendance ; gund arena } ; attendance } ; 123371 } = true | select the rows whose attendance record fuzzily matches to gund arena . the sum of the attendance record of these rows is 123371 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'gund arena_6': 6, 'attendance_7': 7, '123371_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'gund arena_6': 'gund arena', 'attendance_7': 'attendance', '123371_8': '123371'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'gund arena_6': [0], 'attendance_7': [1], '123371_8': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['april 2', 'denver', '104 - 101', 'cleveland', 'mark price , 21 points', 'gund arena 20562', '39 - 32'], ['april 4', 'boston', '97 - 92', 'cleveland', 'bobby phills , 17 points', 'gund arena 20562', '39 - 33'], ['april 5', 'cleveland', '87 - 96', 'atlanta', 'hot rod williams , 14 points', 'the omni 12539', '39 - 34']... |
latin america | https://en.wikipedia.org/wiki/Latin_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18524-6.html.csv | aggregation | in latin america in 2011 , the average percentage of a country 's gdp raised through tourism was 11.3 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '11.3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'tourism receipts ( 2003 ) ( as % of gdp )'], 'result': '11.3', 'ind': 0, 'tostr': 'avg { all_rows ; tourism receipts ( 2003 ) ( as % of gdp ) }'}, '11.3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; tourism receipts ( 2003 ) ( as %... | round_eq { avg { all_rows ; tourism receipts ( 2003 ) ( as % of gdp ) } ; 11.3 } = true | the average of the tourism receipts ( 2003 ) ( as % of gdp ) record of all rows is 11.3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'tourism receipts (2003) (as % of gdp)_4': 4, '11.3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'tourism receipts (2003) (as % of gdp)_4': 'tourism receipts ( 2003 ) ( as % of gdp )', '11.3_5': '11.3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'tourism receipts (2003) (as % of gdp)_4': [0], '11.3_5': [1]} | ['country', 'tourist arrivals ( 2011 ) ( millions )', 'tourism receipts ( 2011 ) ( millions of us )', 'tourism receipts ( 2011 ) ( us per arrival )', 'tourism receipts ( 2011 ) ( us per capita )', 'tourism receipts ( 2003 ) ( as % of gdp )', 'tourism receipts ( 2003 ) ( as % of exports )', 'tourism competitiveness ( 20... | [['argentina', '5.663', '5353', '945', '133', '7.4', '1.8', '4.20'], ['bolivia', '0.807', '310', '384', '31', '9.4', '2.2', '3.35'], ['brazil', '5.433', '6555', '1207', '34', '3.2', '0.5', '4.36'], ['chile', '3.070', '1831', '596', '107', '5.3', '1.9', '4.27'], ['colombia', '4.356', '4061', '873', '45', '6.6', '1.4', '... |
grasshopper club z \ xc3 \ xbcrich | https://en.wikipedia.org/wiki/Grasshopper_Club_Z%C3%BCrich | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1573615-4.html.csv | count | grasshopper club zürich played a total of four matches in the european cup competition . | {'scope': 'all', 'criterion': 'equal', 'value': 'european cup', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'european cup'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to european cup .', 'tostr': 'filter_eq { all_rows ; competition ; european cup }'}], 'result':... | eq { count { filter_eq { all_rows ; competition ; european cup } } ; 4 } = true | select the rows whose competition record fuzzily matches to european cup . 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, 'competition_5': 5, 'european cup_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', 'competition_5': 'competition', 'european cup_6': 'european cup', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'european cup_6': [0], '4_7': [2]} | ['season', 'competition', 'round', 'opponent', 'home', 'away', 'series'] | [['1980 - 81', 'uefa cup', 'r1', 'kjøbenhavns boldklub', '3 - 1', '5 - 2', '8 - 3'], ['1980 - 81', 'uefa cup', 'r2', 'fc porto', '3 - 0 ( aet )', '0 - 2', '3 - 2'], ['1980 - 81', 'uefa cup', 'r3', 'torino', '2 - 1', '1 - 2', '3 - 3 ( p )'], ['1980 - 81', 'uefa cup', 'qf', 'fc sochaux', '0 - 0', '1 - 2', '1 - 2'], ['198... |
super flight | https://en.wikipedia.org/wiki/Super_Flight | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12694869-2.html.csv | majority | for super flight , the region is always the country of japan . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'japan', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'region', 'japan'], 'result': True, 'ind': 0, 'tointer': 'for the region records of all rows , all of them fuzzily match to japan .', 'tostr': 'all_eq { all_rows ; region ; japan } = true'} | all_eq { all_rows ; region ; japan } = true | for the region records of all rows , all of them fuzzily match to japan . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'region_3': 3, 'japan_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'region_3': 'region', 'japan_4': 'japan'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'region_3': [0], 'japan_4': [0]} | ['region', 'date', 'label', 'format', 'catalog'] | [['japan', 'may 25 , 1979', 'alfa records', 'stereo lp', 'alr - 6017'], ['japan', 'december 21 , 1986', 'alfa records', 'cd', '32xa - 105'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 272'], ['japan', 'june 29 , 1994', 'alfa records', 'cd', 'alca - 9002'], ['japan', 'july 23 , 1998', 'alfa records', 'cd... |
simon shirley | https://en.wikipedia.org/wiki/Simon_Shirley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15170292-1.html.csv | count | three of the tournaments listed were held in austria . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'austria', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'austria'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to austria .', 'tostr': 'filter_eq { all_rows ; venue ; austria }'}], 'result': '3', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; venue ; austria } } ; 3 } = true | select the rows whose venue record fuzzily matches to austria . 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, 'venue_5': 5, 'austria_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', 'venue_5': 'venue', 'austria_6': 'austria', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'austria_6': [0], '3_7': [2]} | ['year', 'tournament', 'venue', 'result', 'event'] | [['1988', 'summer olympics', 'seoul , south korea', '15th', 'decathlon'], ['1994', 'hypo - meeting', 'götzis , austria', '11th', 'decathlon'], ['1994', 'commonwealth games', 'victoria , canada', '2nd', 'decathlon'], ['1995', 'hypo - meeting', 'götzis , austria', '20th', 'decathlon'], ['1996', 'hypo - meeting', 'götzis ... |
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