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1927 vfl season | https://en.wikipedia.org/wiki/1927_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10747009-9.html.csv | count | during this round of the 1927 vfl season , two away teams had final scores of less than 10.0 . | {'scope': 'all', 'criterion': 'less_than', 'value': '10.0', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'away team score', '10.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away team score record is less than 10.0 .', 'tostr': 'filter_less { all_rows ; away team score ; 10.0 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; away team score ; 10.0 } }', 'tointer': 'select the rows whose away team score record is less than 10.0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; away team score ; 10.0 } } ; 2 } = true', 'tointer': 'select the rows whose away team score record is less than 10.0 . the number of such rows is 2 .'} | eq { count { filter_less { all_rows ; away team score ; 10.0 } } ; 2 } = true | select the rows whose away team score record is less than 10.0 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'away team score_5': 5, '10.0_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'away team score_5': 'away team score', '10.0_6': '10.0', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'away team score_5': [0], '10.0_6': [0], '2_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '9.6 ( 60 )', 'richmond', '9.20 ( 74 )', 'glenferrie oval', '10000', '25 june 1927'], ['essendon', '12.12 ( 84 )', 'south melbourne', '15.9 ( 99 )', 'windy hill', '17000', '25 june 1927'], ['st kilda', '15.7 ( 97 )', 'north melbourne', '13.10 ( 88 )', 'junction oval', '13000', '25 june 1927'], ['melbourne', '10.13 ( 73 )', 'footscray', '7.9 ( 51 )', 'mcg', '15171', '25 june 1927'], ['geelong', '12.15 ( 87 )', 'fitzroy', '12.8 ( 80 )', 'corio oval', '13500', '25 june 1927'], ['collingwood', '13.5 ( 83 )', 'carlton', '14.11 ( 95 )', 'victoria park', '33000', '25 june 1927']] |
u.s. cities with teams from four major league sports | https://en.wikipedia.org/wiki/U.S._cities_with_teams_from_four_major_league_sports | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1205598-2.html.csv | aggregation | among us cities with teams from four major league sports , the average media market ranking is 6th . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'media market ranking'], 'result': '6', 'ind': 0, 'tostr': 'avg { all_rows ; media market ranking }'}, '6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; media market ranking } ; 6 } = true', 'tointer': 'the average of the media market ranking record of all rows is 6 .'} | round_eq { avg { all_rows ; media market ranking } ; 6 } = true | the average of the media market ranking record of all rows is 6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'media market ranking_4': 4, '6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'media market ranking_4': 'media market ranking', '6_5': '6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'media market ranking_4': [0], '6_5': [1]} | ['metropolitan area', 'media market ranking', 'since', 'mlb team ( s )', 'nba team ( s )'] | [['boston , massachusetts', '7', '1996', 'red sox', 'celtics'], ['chicago , illinois', '3', '1998', 'cubs white sox', 'bulls'], ['dallasfort worth metroplex , texas', '5', '1996', 'rangers ( arlington , tx )', 'mavericks'], ['denver , colorado', '16', '1996', 'rockies', 'nuggets'], ['new york , new york', '1', '1996', 'mets yankees', 'knicks nets'], ['philadelphia , pennsylvania', '4', '2010', 'phillies', '76ers'], ['san francisco bay area , california', '6', '2008', 'giants ( san francisco , ca ) athletics ( oakland )', 'warriors ( oakland )'], ['washington , dc', '9', '2005', 'nationals', 'wizards']] |
2011 veikkausliiga | https://en.wikipedia.org/wiki/2011_Veikkausliiga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29250534-1.html.csv | comparative | the stadium where rops play has a smaller capacity than the sonera stadium . | {'row_1': '10', 'row_2': '5', 'col': '4', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'stadium', 'rovaniemen keskuskenttä'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose stadium record fuzzily matches to rovaniemen keskuskenttä .', 'tostr': 'filter_eq { all_rows ; stadium ; rovaniemen keskuskenttä }'}, 'capacity'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; stadium ; rovaniemen keskuskenttä } ; capacity }', 'tointer': 'select the rows whose stadium record fuzzily matches to rovaniemen keskuskenttä . take the capacity record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'stadium', 'sonera stadium'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose stadium record fuzzily matches to sonera stadium .', 'tostr': 'filter_eq { all_rows ; stadium ; sonera stadium }'}, 'capacity'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; stadium ; sonera stadium } ; capacity }', 'tointer': 'select the rows whose stadium record fuzzily matches to sonera stadium . take the capacity record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; stadium ; rovaniemen keskuskenttä } ; capacity } ; hop { filter_eq { all_rows ; stadium ; sonera stadium } ; capacity } } = true', 'tointer': 'select the rows whose stadium record fuzzily matches to rovaniemen keskuskenttä . take the capacity record of this row . select the rows whose stadium record fuzzily matches to sonera stadium . take the capacity record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; stadium ; rovaniemen keskuskenttä } ; capacity } ; hop { filter_eq { all_rows ; stadium ; sonera stadium } ; capacity } } = true | select the rows whose stadium record fuzzily matches to rovaniemen keskuskenttä . take the capacity record of this row . select the rows whose stadium record fuzzily matches to sonera stadium . take the capacity 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, 'stadium_7': 7, 'rovaniemen keskuskenttä_8': 8, 'capacity_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'stadium_11': 11, 'sonera stadium_12': 12, 'capacity_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', 'stadium_7': 'stadium', 'rovaniemen keskuskenttä_8': 'rovaniemen keskuskenttä', 'capacity_9': 'capacity', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'stadium_11': 'stadium', 'sonera stadium_12': 'sonera stadium', 'capacity_13': 'capacity'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'stadium_7': [0], 'rovaniemen keskuskenttä_8': [0], 'capacity_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'stadium_11': [1], 'sonera stadium_12': [1], 'capacity_13': [3]} | ['club', 'location', 'stadium', 'capacity', 'manager', 'captain'] | [['fc honka', 'espoo', 'tapiolan urheilupuisto', '6000', 'mika lehkosuo', 'tomi maanoja'], ['fc inter', 'turku', 'veritas stadion', '10000', 'job dragtsma', 'henri lehtonen'], ['ff jaro', 'jakobstad', 'jakobstads centralplan', '5000', 'alexei eremenko sr', 'heikki aho'], ['haka', 'valkeakoski', 'tehtaan kenttä', '3516', 'sami ristilä', 'regillio nooitmeer'], ['hjk', 'helsinki', 'sonera stadium', '10770', 'antti muurinen', 'ville wallén'], ['jjk', 'jyväskylä', 'harjun stadion', '3000', 'kari martonen', 'mikko hyyrynen'], ['kups', 'kuopio', 'kuopion keskuskenttä', '5000', 'esa pekonen', 'pietari holopainen'], ['ifk mariehamn', 'mariehamn', 'wiklöf holding arena', '4000', 'pekka lyyski', 'allan olesen'], ['mypa', 'kouvola', 'saviniemi', '4167', 'toni korkeakunnas', 'tuomas aho'], ['rops', 'rovaniemi', 'rovaniemen keskuskenttä', '4000', 'matti hiukka', 'tuomo könönen'], ['tps', 'turku', 'veritas stadion', '10000', 'marko rajamäki', 'jarno heinikangas']] |
list of england national rugby union team results 1960 - 69 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1960%E2%80%9369 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18179114-8.html.csv | superlative | ireland played against the least number of opponents in the list of england rugby national teams of 1960-69 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'against'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; against }'}, 'opposing teams'], 'result': 'ireland', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; against } ; opposing teams }'}, 'ireland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; against } ; opposing teams } ; ireland } = true', 'tointer': 'select the row whose against record of all rows is minimum . the opposing teams record of this row is ireland .'} | eq { hop { argmin { all_rows ; against } ; opposing teams } ; ireland } = true | select the row whose against record of all rows is minimum . the opposing teams record of this row is ireland . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'against_5': 5, 'opposing teams_6': 6, 'ireland_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'against_5': 'against', 'opposing teams_6': 'opposing teams', 'ireland_7': 'ireland'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'against_5': [0], 'opposing teams_6': [1], 'ireland_7': [2]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['australia', '23', '07 / 01 / 1967', 'twickenham , london', 'test match'], ['ireland', '3', '11 / 02 / 1967', 'lansdowne road , dublin', 'five nations'], ['france', '16', '25 / 02 / 1967', 'twickenham , london', 'five nations'], ['scotland', '14', '18 / 03 / 1967', 'twickenham , london', 'five nations'], ['wales', '34', '15 / 04 / 1967', 'cardiff arms park , cardiff', 'five nations'], ['new zealand', '23', '04 / 11 / 1967', 'twickenham , london', 'test match']] |
2011 u.s. f2000 national championship | https://en.wikipedia.org/wiki/2011_U.S._F2000_National_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29285076-2.html.csv | ordinal | in the 2011 u.s. f2000 national championship the most recent race with winning driver petri suvanto was on the road america circuit . | {'scope': 'subset', 'row': '10', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '8', 'criterion': 'equal', 'value': 'petri suvanto'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning driver', 'petri suvanto'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winning driver ; petri suvanto }', 'tointer': 'select the rows whose winning driver record fuzzily matches to petri suvanto .'}, 'date', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; winning driver ; petri suvanto } ; date ; 1 }'}, 'circuit'], 'result': 'road america', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; winning driver ; petri suvanto } ; date ; 1 } ; circuit }'}, 'road america'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; winning driver ; petri suvanto } ; date ; 1 } ; circuit } ; road america } = true', 'tointer': 'select the rows whose winning driver record fuzzily matches to petri suvanto . select the row whose date record of these rows is 1st maximum . the circuit record of this row is road america .'} | eq { hop { nth_argmax { filter_eq { all_rows ; winning driver ; petri suvanto } ; date ; 1 } ; circuit } ; road america } = true | select the rows whose winning driver record fuzzily matches to petri suvanto . select the row whose date record of these rows is 1st maximum . the circuit record of this row is road america . | 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, 'winning driver_6': 6, 'petri suvanto_7': 7, 'date_8': 8, '1_9': 9, 'circuit_10': 10, 'road america_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', 'winning driver_6': 'winning driver', 'petri suvanto_7': 'petri suvanto', 'date_8': 'date', '1_9': '1', 'circuit_10': 'circuit', 'road america_11': 'road america'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'winning driver_6': [0], 'petri suvanto_7': [0], 'date_8': [1], '1_9': [1], 'circuit_10': [2], 'road america_11': [3]} | ['rnd', 'circuit', 'location', 'date', 'pole position', 'fastest lap', 'most laps led', 'winning driver', 'winning team', 'supporting'] | [['1', 'sebring raceway', 'sebring , florida', 'march 17', 'zach veach', 'zach veach', 'zach veach', 'zach veach', 'andretti autosport', 'alms'], ['2', 'sebring raceway', 'sebring , florida', 'march 18', 'zach veach', 'luke ellery', 'petri suvanto luke ellery', 'luke ellery', 'jdc motorsports', 'alms'], ['3', 'streets of st petersburg', 'st petersburg , florida', 'march 26', 'spencer pigot', 'petri suvanto', 'spencer pigot', 'spencer pigot', 'andretti autosport', 'indycar series'], ['4', 'streets of st petersburg', 'st petersburg , florida', 'march 27', 'petri suvanto', 'petri suvanto', 'petri suvanto', 'petri suvanto', 'cape motorsports', 'indycar series'], ['5', 'lucas oil raceway at indianapolis', 'clermont , indiana', 'may 28', 'petri suvanto', 'petri suvanto', 'petri suvanto', 'petri suvanto', 'cape motorsports', 'usac midgets'], ['6', 'milwaukee mile', 'west allis , wisconsin', 'june 19', 'zach veach', 'luke ellery', 'wayne boyd', 'wayne boyd', 'belardi auto racing', 'indycar series'], ['7', 'mid - ohio sports car course', 'lexington , ohio', 'august 6', 'petri suvanto', 'petri suvanto', 'petri suvanto', 'petri suvanto', 'cape motorsports', 'indycar series'], ['8', 'mid - ohio sports car course', 'lexington , ohio', 'august 7', 'petri suvanto', 'petri suvanto', 'petri suvanto', 'petri suvanto', 'cape motorsports', 'indycar series'], ['9', 'road america', 'elkhart lake , wisconsin', 'august 19', 'spencer pigot', 'spencer pigot', 'wayne boyd spencer pigot', 'spencer pigot', 'andretti autosport', 'alms'], ['10', 'road america', 'elkhart lake , wisconsin', 'august 20', 'spencer pigot', 'spencer pigot', 'wayne boyd spencer pigot', 'petri suvanto', 'cape motorsports', 'alms'], ['11', 'streets of baltimore', 'baltimore , maryland', 'september 3', 'petri suvanto', 'spencer pigot', 'wayne boyd', 'wayne boyd', 'belardi auto racing', 'indycar series']] |
shane hall | https://en.wikipedia.org/wiki/Shane_Hall | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2649597-1.html.csv | aggregation | shane hall participated in a total of 190 formula one races in his career . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '190', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'races'], 'result': '190', 'ind': 0, 'tostr': 'sum { all_rows ; races }'}, '190'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; races } ; 190 } = true', 'tointer': 'the sum of the races record of all rows is 190 .'} | round_eq { sum { all_rows ; races } ; 190 } = true | the sum of the races record of all rows is 190 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'races_4': 4, '190_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'races_4': 'races', '190_5': '190'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'races_4': [0], '190_5': [1]} | ['year', 'races', 'wins', 'poles', 'top 5', 'top 10', 'dnf', 'finish', 'start', 'winnings', 'season rank', 'team ( s )'] | [['1995', '2', '0', '0', '0', '0', '0', '24.0', '37.0', '5225', '75th', 'stegell motorsports'], ['1996', '14', '0', '0', '0', '0', '6', '26.4', '25.1', '63865', '42nd', 'stegell motorsports'], ['1997', '28', '0', '1', '0', '1', '10', '27.1', '21.6', '196656', '23rd', 'stegell motorsports'], ['1998', '31', '0', '1', '0', '3', '5', '24.9', '25.5', '335163', '19th', 'stegell motorsports'], ['1999', '25', '0', '0', '1', '1', '9', '25.8', '18.2', '243810', '24th', 'curb - agajanian performance group'], ['2000', '2', '0', '0', '0', '0', '1', '35.0', '28.5', '15900', '90th', 'alumni motorsports'], ['2001', '33', '0', '0', '0', '0', '6', '27.9', '32.7', '491977', '23rd', 'hensley racing'], ['2002', '24', '0', '0', '0', '1', '11', '27.0', '33.0', '288325', '29th', 'hensley racing'], ['2003', '5', '0', '0', '0', '0', '4', '35.8', '25.6', '68360', '85th', 'jay robinson racing'], ['2004', '9', '0', '0', '0', '0', '6', '31.4', '37.2', '139685', '54th', 'moy racing / jay robinson racing'], ['2005', '7', '0', '0', '0', '0', '7', '40.9', '32.6', '108921', '83rd', 'jay robinson racing'], ['2006', '9', '0', '0', '0', '0', '7', '38.9', '39.1', '151184', '70th', 'jay robinson racing'], ['2008', '1', '0', '0', '0', '0', '1', '43.0', '34.0', '15674', '149th', 'jay robinson racing']] |
southlink | https://en.wikipedia.org/wiki/SouthLink | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1425948-1.html.csv | superlative | for southlink , chassis 18.280 hocl - nl and body abm cb64a has the largest quantity out of any other chassis-vehicle combination in its fleet . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,3', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'number in fleet'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; number in fleet }'}, 'chassis model'], 'result': '18.280 hocl - nl', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; number in fleet } ; chassis model }'}, '18.280 hocl - nl'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; number in fleet } ; chassis model } ; 18.280 hocl - nl }', 'tointer': 'select the row whose number in fleet record of all rows is maximum . the chassis model record of this row is 18.280 hocl - nl .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'number in fleet'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; number in fleet }'}, 'body model'], 'result': 'abm cb64a', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; number in fleet } ; body model }'}, 'abm cb64a'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; number in fleet } ; body model } ; abm cb64a }', 'tointer': 'the body model record of this row is abm cb64a .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; number in fleet } ; chassis model } ; 18.280 hocl - nl } ; eq { hop { argmax { all_rows ; number in fleet } ; body model } ; abm cb64a } } = true', 'tointer': 'select the row whose number in fleet record of all rows is maximum . the chassis model record of this row is 18.280 hocl - nl . the body model record of this row is abm cb64a .'} | and { eq { hop { argmax { all_rows ; number in fleet } ; chassis model } ; 18.280 hocl - nl } ; eq { hop { argmax { all_rows ; number in fleet } ; body model } ; abm cb64a } } = true | select the row whose number in fleet record of all rows is maximum . the chassis model record of this row is 18.280 hocl - nl . the body model record of this row is abm cb64a . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'number in fleet_8': 8, 'chassis model_9': 9, '18.280 hocl - nl_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'body model_11': 11, 'abm cb64a_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'number in fleet_8': 'number in fleet', 'chassis model_9': 'chassis model', '18.280 hocl - nl_10': '18.280 hocl - nl', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'body model_11': 'body model', 'abm cb64a_12': 'abm cb64a'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'number in fleet_8': [0], 'chassis model_9': [1], '18.280 hocl - nl_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'body model_11': [3], 'abm cb64a_12': [4]} | ['chassis manufacturer', 'chassis model', 'body model', 'number in fleet', 'fleet numbers'] | [['man', '11.190 hocl - nl', 'pmca 160', '20', '2101 - 2120'], ['man', '18.280 hocl - nl', 'abm cb64a', '50', '2701 - 2750'], ['mercedes - benz', 'o405nh', 'abm cb60', '2', '2520 - 2521'], ['mitsubishi', 'fuso rosa', 'mitsubishi rosa', '6', '34 , 2601 - 2603 , 2605 - 2606'], ['scania', 'scania k280ub', 'custom coaches cb60 evo ii', '3', '2522 - 2523 , 3225'], ['scania', 'scania l94ua', 'custom coaches cb60 combo', '22', '2802 - 2823'], ['scania', 'scania l94ua', 'volgren cr228l', '1', '3331'], ['scania', 'scania l94ub', 'volgren cr224l', '30', '2510 - 2511 , 3200 - 3222 , 3269 - 3273'], ['scania', 'scania l94ub', 'volgren cr228l', '2', '3274 - 3275'], ['scania', 'scania l94ub', 'custom coaches cb60a', '29', '2530 - 2558'], ['scania', 'scania l94ub 14.5 m', 'volgren cr224l', '14', '3310 - 3313 , 3350 - 3359'], ['scania', 'scania l94ub 14.5 m', 'volgren cr228l', '3', '3314 - 3316'], ['scania', 'scania k230ub', 'custom coaches cb60 evo ii', '27', '2559 - 2585'], ['scania', 'scania k270ub', 'volgren cr228l', '3', '3276 - 3278'], ['scania', 'scania k230ub', 'custom coaches cb80', '7', '2586 - 2592'], ['scania', 'scania k280ub', 'volgren cr228l', '1', '3230'], ['scania', 'scania k320ua', 'custom coaches evo ii', '6', '2831 - 2836'], ['scania', 'scania k320ua', 'custom coaches cb80', '14', '2837 - 2850'], ['scania', 'scania k360ua', 'custom coaches cb80', '21', '2851 - 2857 , 3371 - 3376 , r800 - r807']] |
public holidays in serbia | https://en.wikipedia.org/wiki/Public_holidays_in_Serbia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18012080-1.html.csv | count | for public holidays in serbia , of those whose 2013 date was in may , there were 2 times the local name was празник рада , praznik rada . | {'scope': 'subset', 'criterion': 'equal', 'value': 'празник рада , praznik rada', 'result': '2', 'col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'may'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2013 date', 'may'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; 2013 date ; may }', 'tointer': 'select the rows whose 2013 date record fuzzily matches to may .'}, 'local name', 'празник рада , praznik rada'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose 2013 date record fuzzily matches to may . among these rows , select the rows whose local name record fuzzily matches to празник рада , praznik rada .', 'tostr': 'filter_eq { filter_eq { all_rows ; 2013 date ; may } ; local name ; празник рада , praznik rada }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; 2013 date ; may } ; local name ; празник рада , praznik rada } }', 'tointer': 'select the rows whose 2013 date record fuzzily matches to may . among these rows , select the rows whose local name record fuzzily matches to празник рада , praznik rada . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; 2013 date ; may } ; local name ; празник рада , praznik rada } } ; 2 } = true', 'tointer': 'select the rows whose 2013 date record fuzzily matches to may . among these rows , select the rows whose local name record fuzzily matches to празник рада , praznik rada . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; 2013 date ; may } ; local name ; празник рада , praznik rada } } ; 2 } = true | select the rows whose 2013 date record fuzzily matches to may . among these rows , select the rows whose local name record fuzzily matches to празник рада , praznik rada . 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, '2013 date_6': 6, 'may_7': 7, 'local name_8': 8, 'празник рада , praznik rada_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', '2013 date_6': '2013 date', 'may_7': 'may', 'local name_8': 'local name', 'празник рада , praznik rada_9': 'празник рада , praznik rada', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], '2013 date_6': [0], 'may_7': [0], 'local name_8': [1], 'празник рада , praznik rada_9': [1], '2_10': [3]} | ['date', 'name', 'local name', '2012 date', '2013 date'] | [['date', 'name', 'local name', '2012 date', '2013 date'], ['january 1 1', "new year 's day", 'нова година , nova godina', 'january 1', 'january 1'], ['january 2 1', "new year 's day", 'нова година , nova godina', 'january 2', 'january 2'], ['january 7', 'julian orthodox christmas', 'божић , božić', 'january 7', 'january 7'], ['february 15 1', 'serbia national day', 'дан државности србије , dan državnosti srbije', 'february 15', 'february 15'], ['february 16 1', 'serbia national day', 'дан државности србије , dan državnosti srbije', 'february 16', 'february 16'], ['varies', 'orthodox good friday', 'велики петак , veliki petak', 'april 13', 'may 3'], ['varies', 'orthodox easter', 'васкрс , vaskrs', 'april 15', 'may 5'], ['varies', 'orthodox easter monday', 'васкрсни понедељак , vaskrsni ponedeljak', 'april 16', 'may 6'], ['may 1 1', "may day / international workers ' day", 'празник рада , praznik rada', 'may 1', 'may 1'], ['may 2 1', "may day / international workers ' day", 'празник рада , praznik rada', 'may 2', 'may 2'], ['november 11 1', 'armistice day', 'дан примирја , dan primirja', 'november 11', 'november 11']] |
2008 washington redskins season | https://en.wikipedia.org/wiki/2008_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10966926-4.html.csv | superlative | the week 9 game against the pitsburgh steelers had the highest time in the 2008 washington redskins season . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,3', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'time ( et )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; time ( et ) }'}, 'week'], 'result': '9', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; time ( et ) } ; week }'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; time ( et ) } ; week } ; 9 }', 'tointer': 'select the row whose time ( et ) record of all rows is maximum . the week record of this row is 9 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'time ( et )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; time ( et ) }'}, 'opponent'], 'result': 'pittsburgh steelers', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; time ( et ) } ; opponent }'}, 'pittsburgh steelers'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; time ( et ) } ; opponent } ; pittsburgh steelers }', 'tointer': 'the opponent record of this row is pittsburgh steelers .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; time ( et ) } ; week } ; 9 } ; eq { hop { argmax { all_rows ; time ( et ) } ; opponent } ; pittsburgh steelers } } = true', 'tointer': 'select the row whose time ( et ) record of all rows is maximum . the week record of this row is 9 . the opponent record of this row is pittsburgh steelers .'} | and { eq { hop { argmax { all_rows ; time ( et ) } ; week } ; 9 } ; eq { hop { argmax { all_rows ; time ( et ) } ; opponent } ; pittsburgh steelers } } = true | select the row whose time ( et ) record of all rows is maximum . the week record of this row is 9 . the opponent record of this row is pittsburgh steelers . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'eq_2': 2, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'time (et)_8': 8, 'week_9': 9, '9_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'opponent_11': 11, 'pittsburgh steelers_12': 12} | {'and_5': 'and', 'result_6': 'true', 'eq_2': 'eq', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'time (et)_8': 'time ( et )', 'week_9': 'week', '9_10': '9', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'opponent_11': 'opponent', 'pittsburgh steelers_12': 'pittsburgh steelers'} | {'and_5': [6], 'result_6': [], 'eq_2': [5], 'num_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'time (et)_8': [0], 'week_9': [1], '9_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'opponent_11': [3], 'pittsburgh steelers_12': [4]} | ['week', 'date', 'opponent', 'time ( et )', 'result', 'game site', 'record', 'match report'] | [['1', 'september 4 , 2008', 'new york giants', '7:00', 'l 7 - 16', 'giants stadium', '0 - 1', 'recap'], ['2', 'september 14 , 2008', 'new orleans saints', '1:00', 'w 29 - 24', 'fedex field', '1 - 1', 'recap'], ['3', 'september 21 , 2008', 'arizona cardinals', '1:00', 'w 24 - 17', 'fedex field', '2 - 1', 'recap'], ['4', 'september 28 , 2008', 'dallas cowboys', '4:15', 'w 26 - 24', 'texas stadium', '3 - 1', 'recap'], ['5', 'october 5 , 2008', 'philadelphia eagles', '1:00', 'w 23 - 17', 'lincoln financial field', '4 - 1', 'recap'], ['6', 'october 12 , 2008', 'st louis rams', '1:00', 'l 17 - 19', 'fedex field', '4 - 2', 'recap'], ['7', 'october 19 , 2008', 'cleveland browns', '4:15', 'w 14 - 11', 'fedex field', '5 - 2', 'recap'], ['8', 'october 26 , 2008', 'detroit lions', '1:00', 'w 25 - 17', 'ford field', '6 - 2', 'recap'], ['9', 'november 3 , 2008', 'pittsburgh steelers', '8:30', 'l 6 - 23', 'fedex field', '6 - 3', 'recap'], ['10', '-', '-', '-', '-', '-', '-', ''], ['11', 'november 16 , 2008', 'dallas cowboys', '8:15', 'l 10 - 14', 'fedex field', '6 - 4', 'recap'], ['12', 'november 23 , 2008', 'seattle seahawks', '4:15', 'w 20 - 17', 'qwest field', '7 - 4', 'recap'], ['13', 'november 30 , 2008', 'new york giants', '1:00', 'l 7 - 23', 'fedex field', '7 - 5', 'recap'], ['14', 'december 7 , 2008', 'baltimore ravens', '8:15', 'l 10 - 24', 'm & t bank stadium', '7 - 6', 'recap'], ['15', 'december 14 , 2008', 'cincinnati bengals', '1:00', 'l 13 - 20', 'paul brown stadium', '7 - 7', 'recap'], ['16', 'december 21 , 2008', 'philadelphia eagles', '4:15', 'w 10 - 3', 'fedex field', '8 - 7', 'recap'], ['17', 'december 28 , 2008', 'san francisco 49ers', '4:15', 'l 24 - 27', 'candlestick park', '8 - 8', 'recap']] |
1965 american football league draft | https://en.wikipedia.org/wiki/1965_American_Football_League_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-7.html.csv | ordinal | in the 1965 american football league draft , the 2nd to last pick was tom neville . | {'row': '7', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'pick', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; pick ; 2 }'}, 'player'], 'result': 'tom neville', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pick ; 2 } ; player }'}, 'tom neville'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; tom neville } = true', 'tointer': 'select the row whose pick record of all rows is 2nd maximum . the player record of this row is tom neville .'} | eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; tom neville } = true | select the row whose pick record of all rows is 2nd maximum . the player record of this row is tom neville . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'pick_5': 5, '2_6': 6, 'player_7': 7, 'tom neville_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'pick_5': 'pick', '2_6': '2', 'player_7': 'player', 'tom neville_8': 'tom neville'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'pick_5': [0], '2_6': [0], 'player_7': [1], 'tom neville_8': [2]} | ['pick', 'team', 'player', 'position', 'college'] | [['49', 'denver broncos', 'jim garcia', 'defensive end', 'purdue'], ['50', 'kansas city chiefs ( from houston oilers )', 'gloster richardson', 'wide receiver', 'jackson state'], ['51', 'new york jets ( from oakland raiders )', 'archie roberts', 'quarterback', 'columbia'], ['52', 'new york jets', 'jim harris , jr', 'defensive tackle', 'utah state'], ['53', 'kansas city chiefs', 'lou bobich', 'defensive back', 'michigan state'], ['54', 'san diego chargers', 'jack snow', 'wide receiver', 'notre dame'], ['55', 'boston patriots', 'tom neville', 'defensive tackle', 'mississippi state'], ['56', 'buffalo bills', 'marty schottenheimer', 'linebacker', 'pittsburgh']] |
lancashire county council election , 2009 | https://en.wikipedia.org/wiki/Lancashire_County_Council_election%2C_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18992950-1.html.csv | ordinal | in the lancashire county council election in 2009 , the 2nd highest total was for the conservative party . | {'row': '2', 'col': '14', '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', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'party'], 'result': 'conservative', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; party }'}, 'conservative'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 2 } ; party } ; conservative } = true', 'tointer': 'select the row whose total record of all rows is 2nd maximum . the party record of this row is conservative .'} | eq { hop { nth_argmax { all_rows ; total ; 2 } ; party } ; conservative } = true | select the row whose total record of all rows is 2nd maximum . the party record of this row is conservative . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, 'party_7': 7, 'conservative_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '2_6': '2', 'party_7': 'party', 'conservative_8': 'conservative'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'party_7': [1], 'conservative_8': [2]} | ['party', 'burnley', 'chorley', 'fylde', 'hyndburn', 'lancaster', 'pendle', 'preston', 'ribble valley', 'rossendale', 'south ribble', 'west lancashire', 'wyre', 'total'] | [['labour', '6', '4', '0', '6', '6', '1', '6', '0', '3', '5', '4', '3', '44'], ['conservative', '0', '3', '5', '0', '3', '2', '3', '3', '2', '1', '4', '5', '31'], ['liberal democrat', '0', '0', '0', '0', '0', '3', '1', '1', '0', '1', '0', '0', '6'], ['green', '0', '0', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '1'], ['idle toad', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1', '0', '0', '1'], ['independent', '0', '0', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '1']] |
texas longhorns women 's basketball | https://en.wikipedia.org/wiki/Texas_Longhorns_women%27s_basketball | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10779468-2.html.csv | superlative | the longhorns women 's basketball have their highest number of overall record wins against texas a & m. | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '10', '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', 'overall record'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; overall record }'}, 'texas vs'], 'result': 'texas a & m', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; overall record } ; texas vs }'}, 'texas a & m'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; overall record } ; texas vs } ; texas a & m } = true', 'tointer': 'select the row whose overall record record of all rows is maximum . the texas vs record of this row is texas a & m .'} | eq { hop { argmax { all_rows ; overall record } ; texas vs } ; texas a & m } = true | select the row whose overall record record of all rows is maximum . the texas vs record of this row is texas a & m . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'overall record_5': 5, 'texas vs_6': 6, 'texas a&m_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'overall record_5': 'overall record', 'texas vs_6': 'texas vs', 'texas a&m_7': 'texas a & m'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'overall record_5': [0], 'texas vs_6': [1], 'texas a&m_7': [2]} | ['texas vs', 'overall record', 'austin', "opponent 's venue", 'neutral site', 'last 5 meetings', 'last 10 meetings', 'current streak'] | [['baylor', 'ut , 57 - 23', 'ut , 27 - 5', 'ut , 22 - 13', 'ut , 7 - 2', 'bu , 3 - 2', 'tied , 5 - 5', 'l 2'], ['colorado', 'ut , 14 - 4', 'ut , 6 - 1', 'ut , 6 - 2', 'ut , 2 - 1', 'ut , 4 - 1', 'ut , 8 - 2', 'w 1'], ['iowa state', 'isu , 10 - 9', 'ut , 6 - 2', 'isu , 5 - 2', 'isu , 3 - 1', 'isu , 3 - 2', 'tied , 5 - 5', 'l 2'], ['kansas', 'ut , 11 - 7', 'ut , 4 - 3', 'tied , 4 - 4', 'ut , 3 - 0', 'ut , 3 - 2', 'ut , 7 - 3', 'w 1'], ['kansas state', 'ut , 10 - 8', 'ut , 6 - 2', 'ksu , 4 - 3', 'ksu , 2 - 1', 'ut , 3 - 2', 'ksu , 6 - 4', 'l 1'], ['missouri', 'ut , 15 - 1', 'ut , 9 - 0', 'ut , 5 - 1', 'ut , 1 - 0', 'ut , 5 - 0', 'ut , 9 - 1', 'w 8'], ['nebraska', 'ut , 12 - 5', 'ut , 6 - 1', 'ut , 4 - 3', 'ut , 2 - 1', 'ut , 3 - 2', 'ut , 8 - 2', 'l 2'], ['oklahoma', 'ut , 21 - 13', 'ut , 11 - 4', 'tied , 7 - 7', 'ut , 3 - 2', 'ou , 3 - 2', 'tied , 5 - 5', 'w 1'], ['oklahoma state', 'ut , 21 - 7', 'ut , 11 - 2', 'ut , 7 - 4', 'ut , 2 - 1', 'osu , 3 - 2', 'ut , 7 - 3', 'l 2'], ['texas a & m', 'ut , 58 - 15', 'ut , 28 - 4', 'ut , 23 - 8', 'ut , 7 - 3', 'a & m , 4 - 1', 'tied , 5 - 5', 'l 3'], ['texas tech', 'ut , 55 - 24', 'ut , 25 - 6', 'ut , 17 - 13', 'ut , 13 - 4', 'ttu , 3 - 2', 'ttu , 6 - 4', 'w 2']] |
ireland in the eurovision song contest 1998 | https://en.wikipedia.org/wiki/Ireland_in_the_Eurovision_Song_Contest_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15696018-1.html.csv | count | only two of the draws had over 90 points in the song contest . | {'scope': 'all', 'criterion': 'greater_than', 'value': '90', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '90'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is greater than 90 .', 'tostr': 'filter_greater { all_rows ; points ; 90 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; points ; 90 } }', 'tointer': 'select the rows whose points record is greater than 90 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; points ; 90 } } ; 2 } = true', 'tointer': 'select the rows whose points record is greater than 90 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; points ; 90 } } ; 2 } = true | select the rows whose points record is greater than 90 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'points_5': 5, '90_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'points_5': 'points', '90_6': '90', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'points_5': [0], '90_6': [0], '2_7': [2]} | ['draw', 'song', 'performer', 'points', 'rank'] | [['1', 'is always over now', 'dawn martin', '95', '1st'], ['2', 'shine on', 'partners in crime', '63', '5th'], ['3', 'cold shoulder', 'ray doherty', '39', '8th'], ['4', 'seol ( sail )', 'the vard sisters', '92', '2nd'], ['5', 'save this dance for me', 'family', '57', '6th'], ['6', 'ina measc ( among them )', 'sean monagahan', '43', '7th'], ['7', 'make the change', 'the carter twins', '77', '4th'], ['8', 'overload', 'jo collins', '84', '3rd']] |
frederick libby | https://en.wikipedia.org/wiki/Frederick_Libby | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17850104-1.html.csv | count | 7 of the aircraft flown by frederick libby were unit number 11 . | {'scope': 'all', 'criterion': 'equal', 'value': '11', 'result': '7', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'unit', '11'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose unit record is equal to 11 .', 'tostr': 'filter_eq { all_rows ; unit ; 11 }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; unit ; 11 } }', 'tointer': 'select the rows whose unit record is equal to 11 . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; unit ; 11 } } ; 7 } = true', 'tointer': 'select the rows whose unit record is equal to 11 . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; unit ; 11 } } ; 7 } = true | select the rows whose unit record is equal to 11 . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'unit_5': 5, '11_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'unit_5': 'unit', '11_6': '11', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'unit_5': [0], '11_6': [0], '7_7': [2]} | ['date', 'unit', 'aircraft', 'opponent', 'location'] | [['15 july 1916', '23', 'fe2b', 'ago c ( desf )', 'bapaume'], ['22 august 1916', '11', 'fe2b ( 6994 )', 'roland cii ( ooc )', 's of bapaume'], ['25 august 1916', '11', 'fe2b ( 6994 )', 'aviatik c ( ooc )', 'bapaume'], ['14 september 1916', '11', 'fe2b ( 6994 )', 'two - seater ( ooc )', 'se of bapaume'], ['22 september 1916', '11', 'fe2b', 'scout ( ooc )', 'logeast'], ['10 october 1916', '11', 'fe2b ( 7678 )', 'scout ( ooc )', 'bapaume'], ['17 october 1916', '11', 'fe2b ( 7027 )', 'albatros di ( ooc )', 'mory'], ['20 october 1916', '11', 'fe2b ( 7027 )', 'albatros di ( ooc )', 'douxcette - ayette'], ['6 may 1917', '43', 'sopwith 1 ½ strutter ( a1010 )', 'two - seater ( des )', 's of avion'], ['23 july 1917', '43', 'sopwith 1 ½ strutter ( a8785 )', 'albatros diii ( ooc )', 'ne of lens'], ['8 august 1917', '25', 'dh4 ( a7543 )', 'albatros dv ( ooc )', 'henin lietard'], ['14 august 1917', '25', 'dh4 ( a7543 )', 'two - seater ( ooc )', 'lens']] |
sandra cecchini | https://en.wikipedia.org/wiki/Sandra_Cecchini | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14979843-3.html.csv | unique | of the tournaments that sandra cecchini participated in , the only one where sabrina goleš was the opponent , was on april 23 , 1984 . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'sabrina goleš', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'sabrina goleš'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to sabrina goleš .', 'tostr': 'filter_eq { all_rows ; opponent ; sabrina goleš }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent ; sabrina goleš } }', 'tointer': 'select the rows whose opponent record fuzzily matches to sabrina goleš . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'sabrina goleš'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to sabrina goleš .', 'tostr': 'filter_eq { all_rows ; opponent ; sabrina goleš }'}, 'date'], 'result': '23 april 1984', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; sabrina goleš } ; date }'}, '23 april 1984'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; sabrina goleš } ; date } ; 23 april 1984 }', 'tointer': 'the date record of this unqiue row is 23 april 1984 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponent ; sabrina goleš } } ; eq { hop { filter_eq { all_rows ; opponent ; sabrina goleš } ; date } ; 23 april 1984 } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to sabrina goleš . there is only one such row in the table . the date record of this unqiue row is 23 april 1984 .'} | and { only { filter_eq { all_rows ; opponent ; sabrina goleš } } ; eq { hop { filter_eq { all_rows ; opponent ; sabrina goleš } ; date } ; 23 april 1984 } } = true | select the rows whose opponent record fuzzily matches to sabrina goleš . there is only one such row in the table . the date record of this unqiue row is 23 april 1984 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'sabrina goleš_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '23 april 1984_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'sabrina goleš_8': 'sabrina goleš', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '23 april 1984_10': '23 april 1984'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent_7': [0], 'sabrina goleš_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '23 april 1984_10': [3]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', '23 april 1984', 'taranto', 'clay', 'sabrina goleš', '6 - 3 , 7 - 5'], ['winner', '9 july 1984', 'rio de janeiro', 'hard', 'adriana villagran', '6 - 3 , 6 - 3'], ['winner', '6 may 1985', 'barcelona', 'clay', 'raffaella reggi', '6 - 3 , 6 - 4'], ['winner', '14 july 1986', 'bregenz', 'clay', 'mariana pérez - roldán', '6 - 4 , 6 - 0'], ['runner - up', '18 may 1987', 'strasbourg', 'clay', 'carling bassett', '3 - 6 , 4 - 6'], ['winner', '6 july 1987', 'båstad', 'clay', 'catarina lindqvist', '6 - 4 , 6 - 4'], ['winner', '2 november 1987', 'little rock', 'hard', 'natalia zvereva', '6 - 0 , 1 - 6 , 3 - 6'], ['winner', '16 may 1988', 'strasbourg', 'clay', 'judith wiesner', '6 - 3 , 6 - 0'], ['runner - up', '4 july 1988', 'båstad', 'clay', 'isabel cueto', '5 - 7 , 1 - 6'], ['winner', '11 july 1988', 'nice', 'clay', 'nathalie tauziat', '7 - 5 , 6 - 4'], ['runner - up', '17 july 1989', 'estoril', 'clay', 'isabel cueto', '6 - 7 ( 3 - 7 ) , 2 - 6'], ['winner', '18 september 1989', 'paris', 'clay', 'regina rajchrtová', '6 - 4 , 6 - 7 ( 5 - 7 ) , 6 - 1'], ['winner', '9 july 1990', 'båstad', 'clay', 'csilla bartos', '6 - 1 , 6 - 2'], ['winner', '22 april 1991', 'bol', 'clay', 'magdalena maleeva', '6 - 4 , 3 - 6 , 7 - 5'], ['runner - up', '8 july 1991', 'palermo', 'clay', 'mary pierce', '0 - 6 , 3 - 6'], ['winner', '14 september 1992', 'paris', 'clay', 'emanuela zardo', '6 - 2 , 6 - 1'], ['runner - up', '19 september 1994', 'moscow', 'carpet ( i )', 'magdalena maleeva', '5 - 7 , 1 - 6'], ['runner - up', '5 august 1996', 'maria lankowitz', 'clay', 'barbara paulus', 'w / o']] |
2008 copa libertadores knockout stages | https://en.wikipedia.org/wiki/2008_Copa_Libertadores_knockout_stages | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16795394-3.html.csv | superlative | the 1st leg match between flamengo and america was the highest scoring match in the 2008 copa libertadores knockout stages . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,3', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', '1st leg'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 1st leg }'}, 'team 1'], 'result': 'flamengo', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; 1st leg } ; team 1 }'}, 'flamengo'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; 1st leg } ; team 1 } ; flamengo }', 'tointer': 'select the row whose 1st leg record of all rows is maximum . the team 1 record of this row is flamengo .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', '1st leg'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; 1st leg }'}, 'team 2'], 'result': 'américa', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; 1st leg } ; team 2 }'}, 'américa'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; 1st leg } ; team 2 } ; américa }', 'tointer': 'the team 2 record of this row is américa .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; 1st leg } ; team 1 } ; flamengo } ; eq { hop { argmax { all_rows ; 1st leg } ; team 2 } ; américa } } = true', 'tointer': 'select the row whose 1st leg record of all rows is maximum . the team 1 record of this row is flamengo . the team 2 record of this row is américa .'} | and { eq { hop { argmax { all_rows ; 1st leg } ; team 1 } ; flamengo } ; eq { hop { argmax { all_rows ; 1st leg } ; team 2 } ; américa } } = true | select the row whose 1st leg record of all rows is maximum . the team 1 record of this row is flamengo . the team 2 record of this row is américa . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, '1st leg_8': 8, 'team 1_9': 9, 'flamengo_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'team 2_11': 11, 'américa_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', '1st leg_8': '1st leg', 'team 1_9': 'team 1', 'flamengo_10': 'flamengo', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'team 2_11': 'team 2', 'américa_12': 'américa'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], '1st leg_8': [0], 'team 1_9': [1], 'flamengo_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'team 2_11': [3], 'américa_12': [4]} | ['team 1', 'points', 'team 2', '1st leg', '2nd leg'] | [['fluminense', '6 - 0', 'atlético nacional', '2 - 1', '1 - 0'], ['flamengo', '3 - 3 ( gd )', 'américa', '4 - 2', '0 - 3'], ['river plate', '1 - 4', 'san lorenzo', '1 - 2', '2 - 2'], ['atlas', '4 - 1', 'lanús', '1 - 0', '2 - 2'], ['cruzeiro', '0 - 6', 'boca juniors', '1 - 2', '1 - 2'], ['estudiantes', '3 - 3 ( gd )', 'ldu quito', '0 - 2', '2 - 1'], ['cúcuta deportivo', '0 - 6', 'santos', '0 - 2', '0 - 2'], ['são paulo', '4 - 1', 'nacional', '0 - 0', '2 - 0']] |
list of intel pentium iii microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Pentium_III_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16400024-3.html.csv | aggregation | the intel pentium iii microprocessors of all listed model numbers average a voltage of 1.75 v. | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '1.75', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'voltage'], 'result': '1.75', 'ind': 0, 'tostr': 'avg { all_rows ; voltage }'}, '1.75'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; voltage } ; 1.75 } = true', 'tointer': 'the average of the voltage record of all rows is 1.75 .'} | round_eq { avg { all_rows ; voltage } ; 1.75 } = true | the average of the voltage record of all rows is 1.75 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'voltage_4': 4, '1.75_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'voltage_4': 'voltage', '1.75_5': '1.75'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'voltage_4': [0], '1.75_5': [1]} | ['model number', 'sspec number', 'frequency', 'l2 cache', 'mult', 'voltage', 'socket', 'release date', 'part number ( s )'] | [['pentium iii 800', 'sl5qd', '800 mhz', '256 kb', '6', '1.75 v', 'socket 370', 'june 2001', 'rb80533pz800256'], ['pentium iii 866', 'sl5hg , sl5qe', '866 mhz', '256 kb', '6.5', '1.75 v', 'socket 370', 'june 2001', 'rk80533pz866256'], ['pentium iii 933', 'sl5hh , sl5qf', '933 mhz', '256 kb', '7', '1.75 v', 'socket 370', 'june 2001', 'rk80533pz933256'], ['pentium iii 1000', 'sl5qj', '1 ghz', '256 kb', '7.5', '1.75 v', 'socket 370', 'june 2001', 'rk80533pz001256'], ['pentiumiii1133', 'sl5qk', '1.13 ghz', '256 kb', '8.5', '1.75 v', 'socket 370', 'june 2001', 'rk80533pz006256']] |
pas de peyrol | https://en.wikipedia.org/wiki/Pas_de_Peyrol | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18369222-1.html.csv | count | aurillac was the start five times for tour de france . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'aurillac', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'start', 'aurillac'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose start record fuzzily matches to aurillac .', 'tostr': 'filter_eq { all_rows ; start ; aurillac }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; start ; aurillac } }', 'tointer': 'select the rows whose start record fuzzily matches to aurillac . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; start ; aurillac } } ; 5 } = true', 'tointer': 'select the rows whose start record fuzzily matches to aurillac . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; start ; aurillac } } ; 5 } = true | select the rows whose start record fuzzily matches to aurillac . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'start_5': 5, 'aurillac_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'start_5': 'start', 'aurillac_6': 'aurillac', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'start_5': [0], 'aurillac_6': [0], '5_7': [2]} | ['year', 'stage', 'category', 'start', 'finish', 'leader at the summit'] | [['2011', '9', '2', 'issoire', 'st flour', 'thomas voeckler'], ['2008', '7', '2', 'brioude', 'aurillac', 'david de la fuente'], ['2004', '10', '1', 'limoges', 'st flour', 'richard virenque'], ['1985', '15', '2', 'saint - étienne', 'aurillac', 'eduardo chozas'], ['1983', '14', '2', 'aurillac', 'issoire', 'lucien van impe'], ['1975', '14', '3', 'aurillac', 'puy - de - dôme', 'lucien van impe'], ['1968', '17', '3', 'aurillac', 'saint - étienne', 'aurelio gonzalez'], ['1963', '14', '3', 'aurillac', 'saint - étienne', 'federico bahamontes'], ['1959', '14', '2', 'aurillac', 'clermont - ferrand', 'louis bergaud']] |
t.o.p ( entertainer ) | https://en.wikipedia.org/wiki/T.O.P_%28entertainer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18180883-6.html.csv | unique | the only nominated work in 2013 was for commitment . | {'scope': 'all', 'row': '11', 'col': '1', 'col_other': '4', 'criterion': 'equal', 'value': '2013', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2013'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2013 .', 'tostr': 'filter_eq { all_rows ; year ; 2013 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; year ; 2013 } }', 'tointer': 'select the rows whose year record is equal to 2013 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2013'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2013 .', 'tostr': 'filter_eq { all_rows ; year ; 2013 }'}, 'nominated work'], 'result': 'commitment', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 2013 } ; nominated work }'}, 'commitment'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 2013 } ; nominated work } ; commitment }', 'tointer': 'the nominated work record of this unqiue row is commitment .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; year ; 2013 } } ; eq { hop { filter_eq { all_rows ; year ; 2013 } ; nominated work } ; commitment } } = true', 'tointer': 'select the rows whose year record is equal to 2013 . there is only one such row in the table . the nominated work record of this unqiue row is commitment .'} | and { only { filter_eq { all_rows ; year ; 2013 } } ; eq { hop { filter_eq { all_rows ; year ; 2013 } ; nominated work } ; commitment } } = true | select the rows whose year record is equal to 2013 . there is only one such row in the table . the nominated work record of this unqiue row is commitment . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '2013_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nominated work_9': 9, 'commitment_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '2013_8': '2013', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nominated work_9': 'nominated work', 'commitment_10': 'commitment'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'year_7': [0], '2013_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nominated work_9': [2], 'commitment_10': [3]} | ['year', 'event', 'category', 'nominated work', 'result'] | [['2010', '47th grand bell awards', 'hallyu popularity', '71 : into the fire', 'won'], ['2010', '47th grand bell awards', 'best new actor', '71 : into the fire', 'nominated'], ['2010', '8th korea film awards', 'best new actor', '71 : into the fire', 'nominated'], ['2010', 'style icon awards', 'new icon ( movie ) ( korean )', '71 : into the fire', 'won'], ['2010', '31st blue dragon film awards', 'best new actor', '71 : into the fire', 'won'], ['2010', '31st blue dragon film awards', 'popularity', '71 : into the fire', 'won'], ['2010', 'max movie award', 'best new actor', '71 : into the fire', 'won'], ['2010', '5th asian film awards', 'best new actor', '71 : into the fire', 'nominated'], ['2010', '47th paeksang arts award', 'best new actor', '71 : into the fire', 'won'], ['2010', '47th paeksang arts award', 'popularity award ( actor in a motion picture )', '71 : into the fire', 'won'], ['2013', '17th biff asia star awards', 'rookie awards', 'commitment', 'won']] |
2008 - 09 süper lig | https://en.wikipedia.org/wiki/2008%E2%80%9309_S%C3%BCper_Lig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17356873-1.html.csv | aggregation | the venues used for the 2008-09 super lig have an approximated capacity aggregate of 22800 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '22800', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '22800', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '22800'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 22800 } = true', 'tointer': 'the average of the capacity record of all rows is 22800 .'} | round_eq { avg { all_rows ; capacity } ; 22800 } = true | the average of the capacity record of all rows is 22800 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '22800_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '22800_5': '22800'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '22800_5': [1]} | ['team', 'head coach', 'team captain', 'venue', 'capacity', 'kitmaker', 'shirt sponsor', 'club chairman'] | [['ankaragücü', 'hakan kutlu', 'murat erdoğan', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'cemal azmi aydın'], ['ankaraspor', 'aykut kocaman', 'hürriyet güçer', 'yenikent asaş stadium', '19626', 'nike', 'turkcell', 'ruhi kurnaz'], ['antalyaspor', 'mehmet özdilek', 'uğur kavuk', 'antalya atatürk stadium', '11137', 'nike', 'mardan', 'hasan y akıncıoğlu'], ['beşiktaş', 'mustafa denizli', 'matías delgado', 'bjk inönü stadium', '32086', 'umbro', 'cola turka', 'yıldırım demirören'], ['bursaspor', 'ertuğrul sağlam', 'ömer erdoğan', 'bursa atatürk stadium', '18587', 'kappa', 'turkcell', 'ibrahim yazıcı'], ['denizlispor', 'mesut bakkal', 'roman kratochvil', 'denizli atatürk stadium', '15427', 'lescon', 'turkcell', 'ali ipek'], ['eskişehirspor', 'rıza çalımbay', 'emre toraman', 'eskişehir atatürk stadium', '18880', 'nike', 'eti', 'halil ünal'], ['fenerbahçe', 'luis aragonés', 'alex', 'şükrü saracoğlu stadium', '53586', 'adidas', 'avea', 'aziz yıldırım'], ['galatasaray', 'bülent korkmaz', 'ayhan akman', 'ali sami yen stadium', '22800', 'adidas', 'avea', 'adnan polat'], ['gaziantepspor', 'josé couceiro', 'bekir irtegün', 'gaziantep kamil ocak stadium', '16981', 'lescon', 'turkcell', 'ibrahim halil kızıl'], ['gençlerbirliği', 'samet aybaba', 'abdel zaher el saka', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'ilhan cavcav'], ['hacettepe', 'erdoğan arıca', 'orhan şam', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'turgay kalemci'], ['istanbul bb', 'abdullah avcı', 'efe inanç', 'atatürk olympic stadium', '76092', 'lescon', 'kalpen', 'göksel gümüşdağ'], ['kayserispor', 'tolunay kafkas', 'mehmet topuz', 'kadir has stadium 1', '32864', 'adidas', 'turkcell', 'recep mamur'], ['kocaelispor', 'erhan altın', 'serdar topraktepe', 'ismet pasa stadium', '12710', 'umbro', 'erciyas', 'serhan gürkan'], ['konyaspor', 'ünal karaman', 'ömer gündostu', 'konya atatürk stadium', '21968', 'lotto', 'turkcell', 'mehmet ali kuntoğlu'], ['sivasspor', 'bülent uygun', 'mehmet yildiz', 'sivas 4 eylül stadium', '14998', 'adidas', 'turkcell', 'mecnun otyakmaz'], ['trabzonspor', 'ersun yanal', 'hüseyin çimşir', 'hüseyin avni aker stadium', '19649', 'nike', 'avea', 'sadri şener']] |
1989 phoenix cardinals season | https://en.wikipedia.org/wiki/1989_Phoenix_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16642092-1.html.csv | ordinal | in the 1989 phoenix cardinals season , the player picked 2nd to last in the regular draft is jeffrey hunter . | {'row': '13', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'round', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; round ; 2 }'}, 'player'], 'result': 'jeffrey hunter', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; round ; 2 } ; player }'}, 'jeffrey hunter'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; round ; 2 } ; player } ; jeffrey hunter } = true', 'tointer': 'select the row whose round record of all rows is 2nd maximum . the player record of this row is jeffrey hunter .'} | eq { hop { nth_argmax { all_rows ; round ; 2 } ; player } ; jeffrey hunter } = true | select the row whose round record of all rows is 2nd maximum . the player record of this row is jeffrey hunter . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'round_5': 5, '2_6': 6, 'player_7': 7, 'jeffrey hunter_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', 'round_5': 'round', '2_6': '2', 'player_7': 'player', 'jeffrey hunter_8': 'jeffrey hunter'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'round_5': [0], '2_6': [0], 'player_7': [1], 'jeffrey hunter_8': [2]} | ['round', 'pick', 'player', 'position', 'school / club team'] | [['1', '10', 'eric hill', 'linebacker', 'louisiana state'], ['1', '17', 'joe wolf', 'offensive guard', 'boston college'], ['2', '40', 'walter reeves', 'tight end', 'auburn'], ['3', '67', 'mike zandofsky', 'guard', 'washington'], ['4', '94', 'jim wahler', 'defensive tackle', 'ucla'], ['5', '123', 'richard tardits', 'linebacker', 'georgia'], ['5', '128', 'david edeen', 'defensive end', 'wyoming'], ['6', '150', 'jay taylor', 'defensive back', 'san jose state'], ['7', '177', 'rickey royal', 'defensive back', 'sam houston state'], ['8', '207', 'john burch', 'running back', 'tennessee - martin'], ['9', '234', 'kendall trainor', 'kicker', 'arkansas'], ['10', '261', 'chris becker', 'punter', 'texas christian'], ['11', '291', 'jeffrey hunter', 'defensive end', 'albany state'], ['12', '318', 'todd nelson', 'guard', 'wisconsin'], ['1', '2', 'timm rosenbach ( supplemental draft )', 'quarterback', 'washington state']] |
bolt thrust | https://en.wikipedia.org/wiki/Bolt_thrust | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26967904-2.html.csv | ordinal | the .300 lapua magnum has the 2nd highest f bolt ( kgf ) in bolt thrust . | {'row': '9', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'f bolt ( kgf )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; f bolt ( kgf ) ; 2 }'}, 'chambering'], 'result': '.300 lapua magnum', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; f bolt ( kgf ) ; 2 } ; chambering }'}, '.300 lapua magnum'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; f bolt ( kgf ) ; 2 } ; chambering } ; .300 lapua magnum } = true', 'tointer': 'select the row whose f bolt ( kgf ) record of all rows is 2nd maximum . the chambering record of this row is .300 lapua magnum .'} | eq { hop { nth_argmax { all_rows ; f bolt ( kgf ) ; 2 } ; chambering } ; .300 lapua magnum } = true | select the row whose f bolt ( kgf ) record of all rows is 2nd maximum . the chambering record of this row is .300 lapua magnum . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'f bolt ( kgf )_5': 5, '2_6': 6, 'chambering_7': 7, '.300 lapua magnum_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', 'f bolt ( kgf )_5': 'f bolt ( kgf )', '2_6': '2', 'chambering_7': 'chambering', '.300 lapua magnum_8': '.300 lapua magnum'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'f bolt ( kgf )_5': [0], '2_6': [0], 'chambering_7': [1], '.300 lapua magnum_8': [2]} | ['chambering', 'p1 diameter ( mm )', 'a external ( cm 2 )', 'p max ( bar )', 'f bolt ( kgf )', 'f bolt'] | [['5.45 x39 mm', '10.00', '0.7854', '3800', '2985', 'n ( lbf )'], ['.223 remington', '9.58', '0.7208', '4300', '3099', 'n ( lbf )'], ['7.62 x39 mm', '11.35', '1.0118', '3550', '3592', 'n ( lbf )'], ['.308 winchester', '11.96', '1.1234', '4150', '4662', 'n ( lbf )'], ['.300 winchester magnum', '13.03', '1.3335', '4300', '5734', 'n ( lbf )'], ['.300 wsm', '14.12', '1.5659', '4450', '6968', 'n ( lbf )'], ['.300 remington ultra magnum', '13.97', '1.5328', '4480', '6876', 'n ( lbf )'], ['.338 lapua magnum', '14.91', '1.7460', '4200', '7333', 'n ( lbf )'], ['.300 lapua magnum', '14.91', '1.7460', '4700', '8339', 'n ( lbf )'], ['.50 bmg', '20.42', '3.2749', '3700', '12117', 'n ( lbf )']] |
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 | comparative | icho larenas 's match against guido carlo lasted fewer rounds than his match against sebastien gauthier . | {'row_1': '2', 'row_2': '3', 'col': '6', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'guido carlo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to guido carlo .', 'tostr': 'filter_eq { all_rows ; opponent ; guido carlo }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; guido carlo } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to guido carlo . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'sebastien gauthier'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to sebastien gauthier .', 'tostr': 'filter_eq { all_rows ; opponent ; sebastien gauthier }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; sebastien gauthier } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to sebastien gauthier . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; guido carlo } ; round } ; hop { filter_eq { all_rows ; opponent ; sebastien gauthier } ; round } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to guido carlo . take the round record of this row . select the rows whose opponent record fuzzily matches to sebastien gauthier . take the round record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; guido carlo } ; round } ; hop { filter_eq { all_rows ; opponent ; sebastien gauthier } ; round } } = true | select the rows whose opponent record fuzzily matches to guido carlo . take the round record of this row . select the rows whose opponent record fuzzily matches to sebastien gauthier . take the round 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, 'opponent_7': 7, 'guido carlo_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'sebastien gauthier_12': 12, 'round_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', 'opponent_7': 'opponent', 'guido carlo_8': 'guido carlo', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'sebastien gauthier_12': 'sebastien gauthier', 'round_13': 'round'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'guido carlo_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'sebastien gauthier_12': [1], 'round_13': [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 )', 'xmma 4 - xtreme mma', '3', '5:00', 'saguenay , quebec , canada'], ['win', '4 - 3', 'steve bossã', 'tko ( punches )', 'tko 31 - young guns', '3', '3:31', 'montreal , quebec , canada'], ['loss', '3 - 3', 'krzysztof soszynski', 'tko ( doctor stoppage )', 'tko 27 - reincarnation', '3', '0:00', 'montreal , quebec , canada'], ['loss', '3 - 2', 'tom murphy', 'tko ( punches )', 'ufc 58', '3', '1:59', 'las vegas , nevada , united states'], ['win', '3 - 1', 'jacob conliffe', 'tko ( punches )', 'tko 20 - champion vs champion', '2', '1:38', 'montreal , quebec , canada'], ['win', '2 - 1', 'yan pellerin', 'tko ( corner stoppage )', 'tko 18 - impact', '1', '5:00', 'montreal , quebec , canada'], ['win', '1 - 1', 'brian magee', 'tko ( punches )', 'tko 17 - revenge', '1', '0:17', 'victoriaville , quebec , canada'], ['loss', '0 - 1', 'todd gouwenberg', 'tko ( punches )', 'tko 16 - infernal', '2', '2:23', 'quebec city , quebec , canada']] |
2001 new england patriots season | https://en.wikipedia.org/wiki/2001_New_England_Patriots_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10716061-1.html.csv | comparative | hakim akbar was selected in an earlier round than leonard myers . | {'row_1': '6', 'row_2': '8', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'hakim akbar'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to hakim akbar .', 'tostr': 'filter_eq { all_rows ; player ; hakim akbar }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; hakim akbar } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to hakim akbar . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'leonard myers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to leonard myers .', 'tostr': 'filter_eq { all_rows ; player ; leonard myers }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; leonard myers } ; round }', 'tointer': 'select the rows whose player record fuzzily matches to leonard myers . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; hakim akbar } ; round } ; hop { filter_eq { all_rows ; player ; leonard myers } ; round } } = true', 'tointer': 'select the rows whose player record fuzzily matches to hakim akbar . take the round record of this row . select the rows whose player record fuzzily matches to leonard myers . take the round record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; hakim akbar } ; round } ; hop { filter_eq { all_rows ; player ; leonard myers } ; round } } = true | select the rows whose player record fuzzily matches to hakim akbar . take the round record of this row . select the rows whose player record fuzzily matches to leonard myers . take the round record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'hakim akbar_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'leonard myers_12': 12, 'round_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'hakim akbar_8': 'hakim akbar', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'leonard myers_12': 'leonard myers', 'round_13': 'round'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'hakim akbar_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'leonard myers_12': [1], 'round_13': [3]} | ['round', 'overall', 'player', 'position', 'college'] | [['1', '6', 'richard seymour', 'defensive tackle', 'georgia'], ['2', '48', 'matt light', 'offensive tackle', 'purdue'], ['3', '86', 'brock williams', 'cornerback', 'notre dame'], ['4', '96', 'kenyatta jones', 'offensive tackle', 'south florida'], ['4', '119', 'jabari holloway', 'tight end', 'notre dame'], ['5', '163', 'hakim akbar', 'safety', 'washington'], ['6', '180', 'arther love', 'tight end', 'south carolina state'], ['6', '200', 'leonard myers', 'cornerback', 'miami ( fl )'], ['7', '216', 'owen pochman', 'kicker', 'byu'], ['7', '239', 't j turner', 'linebacker', 'michigan state']] |
hans - joachim stuck | https://en.wikipedia.org/wiki/Hans-Joachim_Stuck | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1217995-3.html.csv | comparative | hans - joachim stuck drove more laps in 1996 than he drove in 1997 . | {'row_1': '16', 'row_2': '17', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1996'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1996 .', 'tostr': 'filter_eq { all_rows ; year ; 1996 }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1996 } ; laps }', 'tointer': 'select the rows whose year record fuzzily matches to 1996 . take the laps record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1997'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1997 .', 'tostr': 'filter_eq { all_rows ; year ; 1997 }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1997 } ; laps }', 'tointer': 'select the rows whose year record fuzzily matches to 1997 . take the laps record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1996 } ; laps } ; hop { filter_eq { all_rows ; year ; 1997 } ; laps } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1996 . take the laps record of this row . select the rows whose year record fuzzily matches to 1997 . take the laps record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 1996 } ; laps } ; hop { filter_eq { all_rows ; year ; 1997 } ; laps } } = true | select the rows whose year record fuzzily matches to 1996 . take the laps record of this row . select the rows whose year record fuzzily matches to 1997 . take the laps record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '1996_8': 8, 'laps_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1997_12': 12, 'laps_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '1996_8': '1996', 'laps_9': 'laps', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1997_12': '1997', 'laps_13': 'laps'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1996_8': [0], 'laps_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1997_12': [1], 'laps_13': [3]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1972', 'ford motor company deutschland', 'jochen mass', 's 3.0', '152', 'dnf', 'dnf'], ['1973', 'bmw motorsport', 'chris amon', 't 5.0', '160', 'dnf', 'dnf'], ['1980', 'bmw motorsport gmbh', 'hans - georg bürger dominique lacaud', 'imsa', '283', '15th', '5th'], ['1981', 'basf cassetten team gs sport', 'jean - pierre jarier helmut henzler', 'imsa gtx', '57', 'dnf', 'dnf'], ['1982', 'basf cassetten team gs sport', 'jean - louis schlesser dieter quester', 'c', '76', 'dnf', 'dnf'], ['1985', 'rothmans porsche', 'derek bell', 'c1', '367', '3rd', '3rd'], ['1986', 'rothmans porsche', 'derek bell al holbert', 'c1', '368', '1st', '1st'], ['1987', 'rothmans porsche ag', 'derek bell al holbert', 'c1', '368', '1st', '1st'], ['1988', 'porsche ag', 'klaus ludwig derek bell', 'c1', '394', '2nd', '2nd'], ['1989', 'joest racing', 'bob wollek', 'c1', '382', '3rd', '3rd'], ['1990', 'joest porsche racing', 'derek bell frank jelinski', 'c1', '350', '4th', '4th'], ['1991', 'konrad motorsport', 'derek bell frank jelinski', 'c2', '347', '7th', '7th'], ['1993', 'le mans porsche team', 'walter röhrl hurley haywood', 'gt', '79', 'dnf', 'dnf'], ['1994', 'le mans porsche team joest racing', 'thierry boutsen danny sullivan', 'gt1', '343', '3rd', '2nd'], ['1995', 'porsche kremer racing', 'thierry boutsen christophe bouchut', 'wsc', '289', '6th', '2nd'], ['1996', 'porsche ag', 'thierry boutsen bob wollek', 'gt1', '353', '2nd', '1st'], ['1997', 'porsche ag', 'thierry boutsen bob wollek', 'gt1', '238', 'dnf', 'dnf'], ['1998', 'team bmw motorsport', 'steve soper tom kristensen', 'lmp1', '60', 'dnf', 'dnf']] |
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/2-12410929-9.html.csv | majority | the home captain for all of the test matches was allan border . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'allan border', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'home captain', 'allan border'], 'result': True, 'ind': 0, 'tointer': 'for the home captain records of all rows , all of them fuzzily match to allan border .', 'tostr': 'all_eq { all_rows ; home captain ; allan border } = true'} | all_eq { all_rows ; home captain ; allan border } = true | for the home captain records of all rows , all of them fuzzily match to allan border . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'home captain_3': 3, 'allan border_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'home captain_3': 'home captain', 'allan border_4': 'allan border'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'home captain_3': [0], 'allan border_4': [0]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['29 , 30 november , 1 , 2 december 1991', 'allan border', 'mohammad azharuddin', 'brisbane cricket ground', 'aus by 10 wkts'], ['26 , 27 , 28 , 29 december 1991', 'allan border', 'mohammad azharuddin', 'melbourne cricket ground', 'aus by 8 wkts'], ['2 , 3 , 4 , 5 , 6 january 1992', 'allan border', 'mohammad azharuddin', 'sydney cricket ground', 'draw'], ['25 , 26 , 27 , 28 , 29 january 1992', 'allan border', 'mohammad azharuddin', 'adelaide oval', 'aus by 38 runs'], ['1 , 2 , 3 , 4 , 5 february 1992', 'allan border', 'mohammad azharuddin', 'waca ground', 'aus by 300 runs']] |
2003 cricket world cup statistics | https://en.wikipedia.org/wiki/2003_Cricket_World_Cup_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11611293-7.html.csv | superlative | at the 2003 cricket world cup , the last match held in johannesburg took place on 23 - 03 . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'johannesburg'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'johannesburg'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; johannesburg }', 'tointer': 'select the rows whose venue record fuzzily matches to johannesburg .'}, 'date'], 'result': '23 - 03 - 2003', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; venue ; johannesburg } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to johannesburg . the maximum date record of these rows is 23 - 03 - 2003 .'}, '23 - 03 - 2003'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; venue ; johannesburg } ; date } ; 23 - 03 - 2003 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to johannesburg . the maximum date record of these rows is 23 - 03 - 2003 .'} | eq { max { filter_eq { all_rows ; venue ; johannesburg } ; date } ; 23 - 03 - 2003 } = true | select the rows whose venue record fuzzily matches to johannesburg . the maximum date record of these rows is 23 - 03 - 2003 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'johannesburg_6': 6, 'date_7': 7, '23 - 03 - 2003_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'johannesburg_6': 'johannesburg', 'date_7': 'date', '23 - 03 - 2003_8': '23 - 03 - 2003'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'johannesburg_6': [0], 'date_7': [1], '23 - 03 - 2003_8': [2]} | ['runs', 'balls', 'batsman', 'versus', 'venue', 'date', 'strike rate'] | [['172', '151', 'cb wishart', 'namibia', 'harare', '10 - 02 - 2003', '113.91'], ['152', '151', 'sr tendulkar', 'namibia', 'pietermaritzburg', '23 - 02 - 2003', '100.66'], ['143', '125', 'a symonds', 'pakistan', 'johannesburg', '11 - 02 - 2003', '114.40'], ['143', '141', 'hh gibbs', 'new zealand', 'johannesburg', '16 - 02 - 2003', '101.42'], ['141', '125', 'sb styris', 'sri lanka', 'bloemfontein', '10 - 02 - 2003', '112.80'], ['146', '121', 'rt ponting', 'india', 'johannesburg', '23 - 03 - 2003', '115.70'], ['134', '132', 'sp fleming', 'south africa', 'johannesburg', '16 - 02 - 2003', '101.52'], ['134', '129', 'kjj van noortwijk', 'namibia', 'bloemfontein', '03 - 03 - 2003', '103.88'], ['124', '129', 'ms atapattu', 'south africa', 'durban', '03 - 03 - 2003', '96.12'], ['121', '142', 'jf kloppenburg', 'namibia', 'bloemfontein', '03 - 03 - 2003', '85.21']] |
swatch fivb world tour 2007 | https://en.wikipedia.org/wiki/Swatch_FIVB_World_Tour_2007 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18314203-3.html.csv | majority | in the swatch fivb world tour 2007 the majority of countries did not win more than 1 gold medal . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than_eq', 'value': '1', 'subset': None} | {'func': 'most_less_eq', 'args': ['all_rows', 'gold', '1'], 'result': True, 'ind': 0, 'tointer': 'for the gold records of all rows , most of them are less than or equal to 1 .', 'tostr': 'most_less_eq { all_rows ; gold ; 1 } = true'} | most_less_eq { all_rows ; gold ; 1 } = true | for the gold records of all rows , most of them are less than or equal to 1 . | 1 | 1 | {'most_less_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'gold_3': 3, '1_4': 4} | {'most_less_eq_0': 'most_less_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'gold_3': 'gold', '1_4': '1'} | {'most_less_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'gold_3': [0], '1_4': [0]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'brazil', '21', '9', '12', '42'], ['2', 'united states', '9', '3', '6', '18'], ['3', 'china', '1', '9', '8', '18'], ['4', 'australia', '1', '1', '1', '3'], ['4', 'netherlands', '1', '1', '1', '3'], ['6', 'estonia', '1', '0', '0', '1'], ['7', 'germany', '0', '5', '1', '6'], ['8', 'russia', '0', '2', '3', '5'], ['9', 'argentina', '0', '2', '0', '2'], ['10', 'switzerland', '0', '1', '1', '2'], ['11', 'norway', '0', '1', '0', '1'], ['12', 'austria', '0', '0', '1', '1']] |
1971 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1971_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245565-4.html.csv | ordinal | labron harris had the lowest score among the highest finishers in the 1971 us open golf tournament . | {'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', 'score', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; score ; 1 }'}, 'player'], 'result': 'labron harris', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; score ; 1 } ; player }'}, 'labron harris'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; score ; 1 } ; player } ; labron harris } = true', 'tointer': 'select the row whose score record of all rows is 1st minimum . the player record of this row is labron harris .'} | eq { hop { nth_argmin { all_rows ; score ; 1 } ; player } ; labron harris } = true | select the row whose score record of all rows is 1st minimum . the player record of this row is labron harris . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'score_5': 5, '1_6': 6, 'player_7': 7, 'labron harris_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', 'score_5': 'score', '1_6': '1', 'player_7': 'player', 'labron harris_8': 'labron harris'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'score_5': [0], '1_6': [0], 'player_7': [1], 'labron harris_8': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'labron harris', 'united states', '67', '- 3'], ['t2', 'bob goalby', 'united states', '68', '- 2'], ['t2', 'doug sanders', 'united states', '68', '- 2'], ['t2', 'lanny wadkins ( a )', 'united states', '68', '- 2'], ['t5', 'jim colbert', 'united states', '69', '- 1'], ['t5', 'jack nicklaus', 'united states', '69', '- 1'], ['t5', 'bobby nichols', 'united states', '69', '- 1'], ['t8', 'gay brewer', 'united states', '70', 'e'], ['t8', 'charles coody', 'united states', '70', 'e'], ['t8', 'dale douglass', 'united states', '70', 'e'], ['t8', 'ralph johnston', 'united states', '70', 'e'], ['t8', 'johnny miller', 'united states', '70', 'e'], ['t8', 'chi - chi rodríguez', 'united states', '70', 'e'], ['t8', 'john schlee', 'united states', '70', 'e'], ['t8', 'leonard thompson', 'united states', '70', 'e'], ['t8', 'lee trevino', 'united states', '70', 'e'], ['t8', 'tom weiskopf', 'united states', '70', 'e']] |
1964 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1964_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277176-1.html.csv | majority | all players of the 1964 u.s. open ( golf ) were from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; country ; united states } = true'} | all_eq { all_rows ; country ; united states } = true | for the country records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['billy casper', 'united states', '1959', '285', '+ 5', 't4'], ['arnold palmer', 'united states', '1960', '286', '+ 6', 't5'], ['gene littler', 'united states', '1961', '291', '+ 11', 't11'], ['ed furgol', 'united states', '1954', '292', '+ 12', 't14'], ['jack nicklaus', 'united states', '1962', '295', '+ 15', 't23']] |
1970 vfl season | https://en.wikipedia.org/wiki/1970_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1164217-10.html.csv | count | four of the games had a crowd of over 20,000 people . | {'scope': 'all', 'criterion': 'greater_than', 'value': '20,000', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '20,000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is greater than 20,000 .', 'tostr': 'filter_greater { all_rows ; crowd ; 20,000 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; crowd ; 20,000 } }', 'tointer': 'select the rows whose crowd record is greater than 20,000 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; crowd ; 20,000 } } ; 4 } = true', 'tointer': 'select the rows whose crowd record is greater than 20,000 . the number of such rows is 4 .'} | eq { count { filter_greater { all_rows ; crowd ; 20,000 } } ; 4 } = true | select the rows whose crowd record is greater than 20,000 . 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, 'crowd_5': 5, '20,000_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '20,000_6': '20,000', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '20,000_6': [0], '4_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['fitzroy', '14.9 ( 93 )', 'south melbourne', '12.19 ( 91 )', 'junction oval', '16971', '6 june 1970'], ['essendon', '14.13 ( 97 )', 'richmond', '15.14 ( 104 )', 'windy hill', '20650', '6 june 1970'], ['collingwood', '14.23 ( 107 )', 'st kilda', '15.10 ( 100 )', 'victoria park', '30858', '6 june 1970'], ['melbourne', '10.14 ( 74 )', 'geelong', '13.13 ( 91 )', 'mcg', '27665', '6 june 1970'], ['footscray', '15.14 ( 104 )', 'carlton', '14.10 ( 94 )', 'western oval', '22262', '6 june 1970'], ['north melbourne', '9.8 ( 62 )', 'hawthorn', '11.9 ( 75 )', 'vfl park', '14214', '6 june 1970']] |
andrew pattison | https://en.wikipedia.org/wiki/Andrew_Pattison | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10833727-1.html.csv | ordinal | of the competitions that andrew pattison participated in , the 2nd to last one was when his opponent in the final was victor pecci . | {'row': '10', 'col': '2', 'order': '2', 'col_other': '4', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date ; 2 }'}, 'opponent in the final'], 'result': 'víctor pecci', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date ; 2 } ; opponent in the final }'}, 'víctor pecci'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; date ; 2 } ; opponent in the final } ; víctor pecci } = true', 'tointer': 'select the row whose date record of all rows is 2nd maximum . the opponent in the final record of this row is víctor pecci .'} | eq { hop { nth_argmax { all_rows ; date ; 2 } ; opponent in the final } ; víctor pecci } = true | select the row whose date record of all rows is 2nd maximum . the opponent in the final record of this row is víctor pecci . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'opponent in the final_7': 7, 'víctor pecci_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'opponent in the final_7': 'opponent in the final', 'víctor pecci_8': 'víctor pecci'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'opponent in the final_7': [1], 'víctor pecci_8': [2]} | ['outcome', 'date', 'championship', 'opponent in the final', 'score in the final'] | [['runner - up', '23 july 1972', 'columbus , ohio , us', 'jimmy connors', '5 - 7 , 3 - 6 , 5 - 7'], ['runner - up', '30 july 1972', 'tanglewood , usa', 'bob hewitt', '6 - 3 , 3 - 6 , 1 - 6'], ['runner - up', '14 august 1972', 'montreal , canada', 'ilie năstase', '4 - 6 , 3 - 6'], ['winner', '8 april 1974', 'monte carlo , monaco', 'ilie năstase', '5 - 7 , 6 - 3 , 6 - 4'], ['winner', '15 april 1974', 'johannesburg , south africa', 'john alexander', '6 - 3 , 7 - 5'], ['runner - up', '28 october 1974', 'vienna , austria', 'vitas gerulaitis', '4 - 6 , 6 - 3 , 3 - 6 , 2 - 6'], ['runner - up', '7 january 1976', 'columbus , ohio , us', 'arthur ashe', '6 - 3 , 3 - 6 , 6 - 7 ( 4 )'], ['runner - up', '8 february 1976', 'dayton , ohio , us', 'jaime fillol sr', '4 - 6 , 7 - 6 , 4 - 6'], ['winner', '14 september 1977', 'laguna niguel , us', 'colin dibley', '2 - 6 , 7 - 6 , 6 - 4'], ['winner', '27 november 1979', 'johannesburg , south africa', 'víctor pecci', '2 - 6 , 6 - 3 , 6 - 2 , 6 - 3'], ['runner - up', '7 july 1980', 'newport , rhode island , us', 'vijay amritraj', '1 - 6 , 7 - 5 , 3 - 6']] |
list of united states senators expelled or censured | https://en.wikipedia.org/wiki/List_of_United_States_senators_expelled_or_censured | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1436309-2.html.csv | count | according to the list of united states senators expelled or censured , five republican senators resigned . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'resigned', 'result': '5', 'col': '5', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'republican'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; republican }', 'tointer': 'select the rows whose party record fuzzily matches to republican .'}, 'result', 'resigned'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to resigned .', 'tostr': 'filter_eq { filter_eq { all_rows ; party ; republican } ; result ; resigned }'}], 'result': '5', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; resigned } }', 'tointer': 'select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to resigned . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; resigned } } ; 5 } = true', 'tointer': 'select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to resigned . the number of such rows is 5 .'} | eq { count { filter_eq { filter_eq { all_rows ; party ; republican } ; result ; resigned } } ; 5 } = true | select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose result record fuzzily matches to resigned . the number of such rows is 5 . | 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, 'party_6': 6, 'republican_7': 7, 'result_8': 8, 'resigned_9': 9, '5_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', 'party_6': 'party', 'republican_7': 'republican', 'result_8': 'result', 'resigned_9': 'resigned', '5_10': '5'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'party_6': [0], 'republican_7': [0], 'result_8': [1], 'resigned_9': [1], '5_10': [3]} | ['year', 'senator', 'party', 'state', 'result'] | [['1808', 'john smith', 'democrat - republican', 'ohio', 'not expelled'], ['1856', 'henry mower rice', 'democratic', 'minnesota', 'not expelled'], ['1862', 'lazarus w powell', 'democratic', 'kentucky', 'not expelled'], ['1862', 'james f simmons', 'republican', 'rhode island', 'resigned'], ['1873', 'james w patterson', 'republican', 'new hampshire', 'term expired'], ['1893', 'william n roach', 'democratic', 'north dakota', 'not expelled'], ['1905', 'john h mitchell', 'republican', 'oregon', 'died during proceedings'], ['1906', 'joseph r burton', 'republican', 'kansas', 'resigned'], ['1907', 'reed smoot', 'republican', 'utah', 'not expelled'], ['1919', 'robert m la follette , sr', 'republican', 'wisconsin', 'not expelled'], ['1922', 'truman handy newberry', 'republican', 'michigan', 'resigned'], ['1924', 'burton k wheeler', 'democratic', 'montana', 'not expelled'], ['1934', 'john h overton', 'democratic', 'louisiana', 'not expelled'], ['1934', 'huey long', 'democratic', 'louisiana', 'not expelled'], ['1942', 'william langer', 'republican', 'north dakota', 'not expelled'], ['1982', 'harrison a williams', 'democratic', 'new jersey', 'resigned'], ['1995', 'bob packwood', 'republican', 'oregon', 'resigned'], ['2011', 'john ensign', 'republican', 'nevada', 'resigned']] |
bmw 3 series compact | https://en.wikipedia.org/wiki/BMW_3_Series_Compact | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1180976-2.html.csv | comparative | the 325ti model bmw 3 series compact has more power than the 316ti model bmw 3 series compact . | {'row_1': '3', 'row_2': '1', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', '325ti'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to 325ti .', 'tostr': 'filter_eq { all_rows ; model ; 325ti }'}, 'power'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; model ; 325ti } ; power }', 'tointer': 'select the rows whose model record fuzzily matches to 325ti . take the power record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', '316ti'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose model record fuzzily matches to 316ti .', 'tostr': 'filter_eq { all_rows ; model ; 316ti }'}, 'power'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; model ; 316ti } ; power }', 'tointer': 'select the rows whose model record fuzzily matches to 316ti . take the power record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; model ; 325ti } ; power } ; hop { filter_eq { all_rows ; model ; 316ti } ; power } } = true', 'tointer': 'select the rows whose model record fuzzily matches to 325ti . take the power record of this row . select the rows whose model record fuzzily matches to 316ti . take the power record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; model ; 325ti } ; power } ; hop { filter_eq { all_rows ; model ; 316ti } ; power } } = true | select the rows whose model record fuzzily matches to 325ti . take the power record of this row . select the rows whose model record fuzzily matches to 316ti . take the power 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, 'model_7': 7, '325ti_8': 8, 'power_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'model_11': 11, '316ti_12': 12, 'power_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', 'model_7': 'model', '325ti_8': '325ti', 'power_9': 'power', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'model_11': 'model', '316ti_12': '316ti', 'power_13': 'power'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'model_7': [0], '325ti_8': [0], 'power_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'model_11': [1], '316ti_12': [1], 'power_13': [3]} | ['model', 'years', 'engine code', 'power', 'torque'] | [['316ti', '2001 - 2004', 'n42b18 / n46b18', '5500', '3750'], ['318ti', '2001 - 2004', 'n42b20 / n46b20', '6000', '3750'], ['325ti', '2001 - 2004', 'm54b25', '6000', '3500'], ['318td ( diesel )', '2003 - 2004', 'm47d20', '4000', '1750'], ['320td ( diesel )', '2001 - 2004', 'm47d20', '4000', '2000']] |
list of benedictine colleges and universities | https://en.wikipedia.org/wiki/List_of_Benedictine_colleges_and_universities | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14014822-1.html.csv | superlative | in the list of benedictine colleges and universities the highest enrollment in illinois was founded in 1877 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3,5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'illinois'}} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'state', 'illinois'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; state ; illinois }', 'tointer': 'select the rows whose state record fuzzily matches to illinois .'}, 'enrollment'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; state ; illinois } ; enrollment }'}, 'founded'], 'result': '1887', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; state ; illinois } ; enrollment } ; founded }'}, '1887'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; state ; illinois } ; enrollment } ; founded } ; 1887 } = true', 'tointer': 'select the rows whose state record fuzzily matches to illinois . select the row whose enrollment record of these rows is maximum . the founded record of this row is 1887 .'} | eq { hop { argmax { filter_eq { all_rows ; state ; illinois } ; enrollment } ; founded } ; 1887 } = true | select the rows whose state record fuzzily matches to illinois . select the row whose enrollment record of these rows is maximum . the founded record of this row is 1887 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'num_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'state_6': 6, 'illinois_7': 7, 'enrollment_8': 8, 'founded_9': 9, '1887_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'num_hop_2': 'num_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'state_6': 'state', 'illinois_7': 'illinois', 'enrollment_8': 'enrollment', 'founded_9': 'founded', '1887_10': '1887'} | {'eq_3': [4], 'result_4': [], 'num_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'state_6': [0], 'illinois_7': [0], 'enrollment_8': [1], 'founded_9': [2], '1887_10': [3]} | ['school', 'city', 'state', 'enrollment', 'founded'] | [['belmont abbey college', 'belmont', 'north carolina', '1320', '1876'], ['benedictine college', 'atchison', 'kansas', '1855', '1858'], ['benedictine university', 'lisle', 'illinois', '6857', '1887'], ['benedictine university at springfield', 'springfield', 'illinois', '981', '1929'], ['college of saint benedict', 'st joseph', 'minnesota', '2042', '1913'], ['college of saint scholastica', 'duluth', 'minnesota', '3309', '1912'], ['conception seminary college', 'conception', 'missouri', '108', '1886'], ['mount marty college', 'yankton', 'south dakota', '1100', '1936'], ['saint anselm college', 'goffstown', 'new hampshire', '2000', '1889'], ["saint gregory 's university", 'shawnee', 'oklahoma', '800', '1875'], ["saint john 's university", 'collegeville', 'minnesota', '1886', '1857'], ['saint joseph seminary college', 'covington', 'louisiana', '171', '1889'], ['saint leo university', 'saint leo', 'florida', '1628', '1889'], ["saint martin 's university", 'lacey', 'washington', '1650', '1895'], ['saint vincent college', 'latrobe', 'pennsylvania', '1848', '1846'], ['thomas more college ( kentucky )', 'crestview hills', 'kentucky', '1500', '1921'], ['university of mary', 'bismarck', 'north dakota', '2900', '1959'], ['colegio san carlos', 'bogotã ¡', 'colombia', '1400', '1960']] |
nicolas lapierre | https://en.wikipedia.org/wiki/Nicolas_Lapierre | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1628448-4.html.csv | superlative | from 2007 to 2013 , nicolas lapierre 's highest class position in a 24 hours of le mans competition was 4th . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'class pos'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; class pos }'}, 'year'], 'result': '2013', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; class pos } ; year }'}, '2013'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; class pos } ; year } ; 2013 } = true', 'tointer': 'select the row whose class pos record of all rows is minimum . the year record of this row is 2013 .'} | eq { hop { argmin { all_rows ; class pos } ; year } ; 2013 } = true | select the row whose class pos record of all rows is minimum . the year record of this row is 2013 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'class pos_5': 5, 'year_6': 6, '2013_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'class pos_5': 'class pos', 'year_6': 'year', '2013_7': '2013'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'class pos_5': [0], 'year_6': [1], '2013_7': [2]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2007', 'team oreca', 'stéphane ortelli soheil ayari', 'gt1', '318', '16th', '9th'], ['2009', 'team oreca - matmut aim', 'olivier panis soheil ayari', 'lmp1', '370', '5th', '5th'], ['2010', 'team oreca - matmut', 'olivier panis loïc duval', 'lmp1', '373', 'dnf', 'dnf'], ['2011', 'team oreca - matmut', 'olivier panis loïc duval', 'lmp1', '339', '5th', '5th'], ['2012', 'toyota racing', 'alexander wurz kazuki nakajima', 'lmp1', '134', 'dnf', 'dnf'], ['2013', 'toyota racing', 'alexander wurz kazuki nakajima', 'lmp1', '341', '4th', '4th']] |
fil world luge natural track championships | https://en.wikipedia.org/wiki/FIL_World_Luge_Natural_Track_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10910853-5.html.csv | superlative | the nation that won the fewest number of bronze medals in the fil world luge natural track championships is the commonwealth of independent states ( '92 only ) . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', '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', 'bronze'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; bronze }'}, 'nation'], 'result': 'commonwealth of independent states ( 1992 only )', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; bronze } ; nation }'}, 'commonwealth of independent states ( 1992 only )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; bronze } ; nation } ; commonwealth of independent states ( 1992 only ) } = true', 'tointer': 'select the row whose bronze record of all rows is minimum . the nation record of this row is commonwealth of independent states ( 1992 only ) .'} | eq { hop { argmin { all_rows ; bronze } ; nation } ; commonwealth of independent states ( 1992 only ) } = true | select the row whose bronze record of all rows is minimum . the nation record of this row is commonwealth of independent states ( 1992 only ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'bronze_5': 5, 'nation_6': 6, 'commonwealth of independent states (1992 only)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', 'nation_6': 'nation', 'commonwealth of independent states (1992 only)_7': 'commonwealth of independent states ( 1992 only )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'bronze_5': [0], 'nation_6': [1], 'commonwealth of independent states (1992 only)_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'italy', '29', '28', '28', '85'], ['2', 'austria', '19', '21', '21', '61'], ['3', 'russia ( since 1994 )', '7', '7', '2', '16'], ['4', 'poland', '0', '0', '4', '4'], ['5', 'commonwealth of independent states ( 1992 only )', '1', '0', '0', '1'], ['6', 'soviet union ( 1979 - 90 )', '0', '0', '1', '1']] |
list of how it 's made episodes | https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15187735-19.html.csv | aggregation | the average episode number of these episodes of how it 's made is 240 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '240', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'episode'], 'result': '240', 'ind': 0, 'tostr': 'avg { all_rows ; episode }'}, '240'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; episode } ; 240 } = true', 'tointer': 'the average of the episode record of all rows is 240 .'} | round_eq { avg { all_rows ; episode } ; 240 } = true | the average of the episode record of all rows is 240 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'episode_4': 4, '240_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'episode_4': 'episode', '240_5': '240'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'episode_4': [0], '240_5': [1]} | ['series ep', 'episode', 'segment a', 'segment b', 'segment c', 'segment d'] | [['19 - 01', '235', 'garden forks', 'english toffee', 'paint chip cards', 'bundt s pan'], ['19 - 02', '236', 'pewter flasks', 'potato salad', 'hydrogen s fuel cell', 'engineered wood siding'], ['19 - 03', '237', 'canvas wall s tent', 's peace pipe', 'shredded wheat cereal', 's cannon'], ['19 - 04', '238', 'ic robot ing hunt s decoy', 'canned tomatoes', 's scoreboard', 's lasso'], ['19 - 05', '239', 'turf grass', 'beef jerky', 'wood chippers', 'bowling pins'], ['19 - 06', '240', 's multi - tool', 'jojoba oil', 's marionette ( part 1 )', 's marionette ( part 2 )'], ['19 - 07', '241', 'fish decoys', 'film digitization', 'cylinder stoves', 'concrete light poles'], ['19 - 08', '242', 'bamboo bicycles', 'chainsaw art', 'breath mints', 'manual motorcycle transmissions'], ['19 - 09', '243', 'dinnerware', 'air brake tanks', 'frosted cereal', 's fossil'], ['19 - 10', '244', 'clay', 'pitted prunes', 's spur', 'polyurethane tires'], ['19 - 11', '245', 's taser', 'canned soup', 'jaw harps & mouth bows', 's diving board'], ['19 - 12', '246', 'navajo rugs', 'crude oil', 's kaleidoscope', 'titanium dental implants']] |
list of australian football league pre - season and night series premiers | https://en.wikipedia.org/wiki/List_of_Australian_Football_League_pre-season_and_night_series_premiers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1139835-9.html.csv | count | there were four occasions where the venue was waverley park . | {'scope': 'all', 'criterion': 'equal', 'value': 'waverley park', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'waverley park'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to waverley park .', 'tostr': 'filter_eq { all_rows ; venue ; waverley park }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; waverley park } }', 'tointer': 'select the rows whose venue record fuzzily matches to waverley park . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; waverley park } } ; 4 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to waverley park . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; venue ; waverley park } } ; 4 } = true | select the rows whose venue record fuzzily matches to waverley park . 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, 'venue_5': 5, 'waverley park_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', 'venue_5': 'venue', 'waverley park_6': 'waverley park', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'waverley park_6': [0], '4_7': [2]} | ['season', 'premier', 'runner up', 'score', 'venue', 'attendance', 'premiership'] | [['1984', 'essendon', 'sydney swans', '13.11 ( 89 ) - 5.8 ( 38 )', 'waverley park', '30824', 'night series'], ['1984', 'essendon', 'hawthorn', '14.21 ( 105 ) - 12.9 ( 81 )', 'mcg', '92685', 'vfl grand final'], ['1986', 'hawthorn', 'carlton', '9.12 ( 66 ) - 5.6 ( 36 )', 'waverley park', '19627', 'night series'], ['1986', 'hawthorn', 'carlton', '16.14 ( 110 ) - 9.14 ( 68 )', 'mcg', '101861', 'vfl grand final'], ['1988', 'hawthorn', 'geelong', '10.10 ( 70 ) - 9.13 ( 67 )', 'waverley park', '35803', 'pre - season cup'], ['1988', 'hawthorn', 'melbourne', '22.20 ( 152 ) - 6.20 ( 56 )', 'mcg', '93754', 'vfl grand final'], ['1993', 'essendon', 'richmond', '14.18 ( 102 ) - 11.13 ( 79 )', 'waverley park', '75533', 'pre - season cup'], ['1993', 'essendon', 'carlton carlton', '20.13 ( 133 ) - 13.11 ( 89 )', 'mcg', '96862', 'afl grand final'], ['2000', 'essendon', 'north melbourne', '16.21 ( 117 ) - 11.10 ( 76 )', 'mcg', '56720', 'pre - season cup'], ['2000', 'essendon', 'melbourne', '19.21 ( 135 ) - 11.9 ( 75 )', 'mcg', '96249', 'afl grand final'], ['2009', 'geelong', 'collingwood', '0.18.19 ( 127 ) - 1.6.6 ( 51 )', 'etihad stadium', '37277', 'pre - season cup']] |
germany | https://en.wikipedia.org/wiki/Germany | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11867-3.html.csv | superlative | volkswagen ag has the most employees among the largest companies in germany . | {'scope': 'all', 'col_superlative': '6', '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', 'employees ( world )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; employees ( world ) }'}, 'name'], 'result': 'volkswagen ag', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; employees ( world ) } ; name }'}, 'volkswagen ag'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; employees ( world ) } ; name } ; volkswagen ag } = true', 'tointer': 'select the row whose employees ( world ) record of all rows is maximum . the name record of this row is volkswagen ag .'} | eq { hop { argmax { all_rows ; employees ( world ) } ; name } ; volkswagen ag } = true | select the row whose employees ( world ) record of all rows is maximum . the name record of this row is volkswagen ag . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'employees (world)_5': 5, 'name_6': 6, 'volkswagen ag_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'employees (world)_5': 'employees ( world )', 'name_6': 'name', 'volkswagen ag_7': 'volkswagen ag'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'employees (world)_5': [0], 'name_6': [1], 'volkswagen ag_7': [2]} | ['rank', 'name', 'headquarters', 'revenue ( mil )', 'profit ( mil )', 'employees ( world )'] | [['0 1', 'volkswagen ag', 'wolfsburg', '159.000', '15.800', '502 ,000'], ['0 2', 'eon se', 'düsseldorf', '113.000', '1.900', '79 ,000'], ['0 3', 'daimler ag', 'stuttgart', '107.000', '6.000', '271 ,000'], ['0 4', 'siemens ag', 'berlin , münchen', '74.000', '6.300', '360 ,000'], ['0 5', 'basf se', 'ludwigshafen am rhein', '73.000', '6.600', '111 ,000'], ['0 6', 'bmw ag', 'münchen', '69.000', '4.900', '100 ,000'], ['0 7', 'metro ag', 'düsseldorf', '67.000', '740', '288 ,000'], ['0 8', 'schwarz - gruppe ( lidl / kaufland )', 'neckarsulm', '63.000', 'n / a', '315 ,000'], ['0 9', 'deutsche telekom ag', 'bonn', '59.000', '670', '235 ,000'], ['0 10', 'deutsche post ag', 'bonn', '53.000', '1.300', '471 ,000'], ['-', 'allianz se', 'münchen', '104.000', '2.800', '141 ,000'], ['-', 'deutsche bank ag', 'frankfurt am main', '2.160.000', '4.300', '101 ,000']] |
1924 in brazilian football | https://en.wikipedia.org/wiki/1924_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15387537-1.html.csv | count | in brazilian football in the year 1924 , there wer six people who played 17 . | {'scope': 'all', 'criterion': 'equal', 'value': '17', 'result': '6', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'played', '17'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose played record is equal to 17 .', 'tostr': 'filter_eq { all_rows ; played ; 17 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; played ; 17 } }', 'tointer': 'select the rows whose played record is equal to 17 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; played ; 17 } } ; 6 } = true', 'tointer': 'select the rows whose played record is equal to 17 . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; played ; 17 } } ; 6 } = true | select the rows whose played record is equal to 17 . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'played_5': 5, '17_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'played_5': 'played', '17_6': '17', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'played_5': [0], '17_6': [0], '6_7': [2]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'corinthians', '25', '17', '1', '4', '23', '23'], ['2', 'paulistano', '23', '17', '3', '4', '15', '16'], ['3', 'aa são bento', '22', '17', '4', '4', '20', '10'], ['4', 'santos', '21', '17', '3', '5', '29', '15'], ['5', 'ypiranga - sp', '20', '17', '2', '6', '24', '5'], ['6', 'sírio', '17', '17', '5', '6', '26', '3'], ['7', 'brás', '10', '16', '4', '9', '41', '- 17'], ['8', 'portuguesa', '8', '16', '2', '11', '39', '- 21']] |
1995 - 96 philadelphia flyers season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14344570-5.html.csv | count | in the 1995-96 philadelphia flyers season , when there were at least 55 points , there were two games against the new york rangers . | {'scope': 'subset', 'criterion': 'equal', 'value': 'new york rangers', 'result': '2', 'col': '3', 'subset': {'col': '6', 'criterion': 'greater_than_eq', 'value': '55'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'points', '55'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; points ; 55 }', 'tointer': 'select the rows whose points record is greater than or equal to 55 .'}, 'opponent', 'new york rangers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose points record is greater than or equal to 55 . among these rows , select the rows whose opponent record fuzzily matches to new york rangers .', 'tostr': 'filter_eq { filter_greater_eq { all_rows ; points ; 55 } ; opponent ; new york rangers }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater_eq { all_rows ; points ; 55 } ; opponent ; new york rangers } }', 'tointer': 'select the rows whose points record is greater than or equal to 55 . among these rows , select the rows whose opponent record fuzzily matches to new york rangers . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater_eq { all_rows ; points ; 55 } ; opponent ; new york rangers } } ; 2 } = true', 'tointer': 'select the rows whose points record is greater than or equal to 55 . among these rows , select the rows whose opponent record fuzzily matches to new york rangers . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater_eq { all_rows ; points ; 55 } ; opponent ; new york rangers } } ; 2 } = true | select the rows whose points record is greater than or equal to 55 . among these rows , select the rows whose opponent record fuzzily matches to new york rangers . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'points_6': 6, '55_7': 7, 'opponent_8': 8, 'new york rangers_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'points_6': 'points', '55_7': '55', 'opponent_8': 'opponent', 'new york rangers_9': 'new york rangers', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'points_6': [0], '55_7': [0], 'opponent_8': [1], 'new york rangers_9': [1], '2_10': [3]} | ['game', 'january', 'opponent', 'score', 'record', 'points'] | [['40', '3', 'san jose sharks', '3 - 1', '23 - 11 - 6', '52'], ['41', '4', 'colorado avalanche', '2 - 2 ot', '23 - 11 - 7', '53'], ['42', '9', 'mighty ducks of anaheim', '2 - 2 ot', '23 - 11 - 8', '54'], ['43', '11', 'st louis blues', '4 - 4 ot', '23 - 12 - 9', '55'], ['44', '13', 'new york rangers', '0 - 4', '23 - 13 - 9', '55'], ['45', '15', 'dallas stars', '6 - 1', '24 - 13 - 9', '57'], ['46', '22', 'florida panthers', '1 - 1 ot', '24 - 12 - 10', '58'], ['47', '24', 'new york rangers', '4 - 4 ot', '24 - 12 - 11', '59'], ['48', '27', 'pittsburgh penguins', '4 - 7', '24 - 13 - 11', '59'], ['49', '28', 'washington capitals', '2 - 3 ot', '24 - 14 - 11', '59']] |
2004 japanese grand prix | https://en.wikipedia.org/wiki/2004_Japanese_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1054525-2.html.csv | count | 2 drivers in the 2004 japanese grand prix had vehicles constructed by toyota . | {'scope': 'all', 'criterion': 'equal', 'value': 'toyota', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constructor', 'toyota'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constructor record fuzzily matches to toyota .', 'tostr': 'filter_eq { all_rows ; constructor ; toyota }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; constructor ; toyota } }', 'tointer': 'select the rows whose constructor record fuzzily matches to toyota . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; constructor ; toyota } } ; 2 } = true', 'tointer': 'select the rows whose constructor record fuzzily matches to toyota . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; constructor ; toyota } } ; 2 } = true | select the rows whose constructor record fuzzily matches to toyota . 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, 'constructor_5': 5, 'toyota_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', 'constructor_5': 'constructor', 'toyota_6': 'toyota', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'constructor_5': [0], 'toyota_6': [0], '2_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['michael schumacher', 'ferrari', '53', '1:24:26.985', '1'], ['ralf schumacher', 'williams - bmw', '53', '+ 14.098', '2'], ['jenson button', 'bar - honda', '53', '+ 19.662', '5'], ['takuma sato', 'bar - honda', '53', '+ 31.781', '4'], ['fernando alonso', 'renault', '53', '+ 37.767', '11'], ['kimi räikkönen', 'mclaren - mercedes', '53', '+ 39.362', '12'], ['juan pablo montoya', 'williams - bmw', '53', '+ 55.347', '13'], ['giancarlo fisichella', 'sauber - petronas', '53', '+ 56.276', '7'], ['felipe massa', 'sauber - petronas', '53', '+ 1:29.656', '19'], ['jacques villeneuve', 'renault', '52', '+ 1 lap', '9'], ['jarno trulli', 'toyota', '52', '+ 1 lap', '6'], ['christian klien', 'jaguar - cosworth', '52', '+ 1 lap', '14'], ['nick heidfeld', 'jordan - ford', '52', '+ 1 lap', '16'], ['olivier panis', 'toyota', '51', '+ 2 lap', '10'], ['timo glock', 'jordan - ford', '51', '+ 2 lap', '17'], ['gianmaria bruni', 'minardi - cosworth', '50', '+ 3 lap', '18'], ['zsolt baumgartner', 'minardi - cosworth', '41', 'spin', '20'], ['david coulthard', 'mclaren - mercedes', '38', 'collision', '8'], ['rubens barrichello', 'ferrari', '38', 'collision', '15'], ['mark webber', 'jaguar - cosworth', '20', 'overheating', '3']] |
blue ridge hockey conference | https://en.wikipedia.org/wiki/Blue_Ridge_Hockey_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16404837-5.html.csv | count | in the blue ridge hockey conference , three of the schools are in north carolina . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'nc', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'nc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to nc .', 'tostr': 'filter_eq { all_rows ; location ; nc }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; nc } }', 'tointer': 'select the rows whose location record fuzzily matches to nc . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; nc } } ; 3 } = true', 'tointer': 'select the rows whose location record fuzzily matches to nc . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; location ; nc } } ; 3 } = true | select the rows whose location record fuzzily matches to nc . 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, 'nc_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', 'nc_6': 'nc', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'nc_6': [0], '3_7': [2]} | ['school', 'location', 'founded', 'affiliation', 'nickname'] | [['appalachian state university', 'boone , nc', '1899', 'public ( university of north carolina system )', 'mountaineers'], ['coastal carolina university', 'conway , sc', '1954', 'public', 'chanticleers'], ['high point university', 'high point , nc', '1924', 'private / methodist', 'panthers'], ['johnson & wales university', 'charlotte , nc', '2004', 'private / non - profit', 'wildcats'], ['virginia military institute', 'lexington , va', '1839', 'public military college', 'keydets']] |
2004 molson indy montreal | https://en.wikipedia.org/wiki/2004_Molson_Indy_Montreal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16838759-2.html.csv | superlative | in the 2004 molson indy montreal , bruno junqueira had the highest number of points . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'driver'], 'result': 'bruno junqueira', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; driver }'}, 'bruno junqueira'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; driver } ; bruno junqueira } = true', 'tointer': 'select the row whose points record of all rows is maximum . the driver record of this row is bruno junqueira .'} | eq { hop { argmax { all_rows ; points } ; driver } ; bruno junqueira } = true | select the row whose points record of all rows is maximum . the driver record of this row is bruno junqueira . | 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, 'bruno junqueira_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', 'bruno junqueira_7': 'bruno junqueira'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'driver_6': [1], 'bruno junqueira_7': [2]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['bruno junqueira', 'newman / haas racing', '69', '1:39:12.432', '4', '32'], ['patrick carpentier', 'forsythe racing', '69', '+ 6.382 secs', '6', '27'], ['mario domínguez', 'herdez competition', '69', '+ 11.142 secs', '3', '26'], ['paul tracy', 'forsythe racing', '69', '+ 16.874 secs', '5', '23'], ['a j allmendinger', 'rusport', '69', '+ 17.561 secs', '2', '22'], ['michel jourdain , jr', 'rusport', '69', '+ 32.256 secs', '12', '20'], ['alex tagliani', 'rocketsports racing', '69', '+ 32.300 secs', '7', '17'], ['jimmy vasser', 'pkv racing', '69', '+ 34.097 secs', '11', '15'], ['oriol servià', 'dale coyne racing', '69', '+ 42.654 secs', '10', '13'], ['roberto gonzález', 'pkv racing', '69', '+ 1:09.190', '15', '11'], ['rodolfo lavín', 'forsythe racing', '69', '+ 1:18.083', '14', '10'], ['gastón mazzacane', 'dale coyne racing', '67', '+ 2 laps', '18', '9'], ['mario haberfeld', 'walker racing', '65', '+ 4 laps', '17', '8'], ['justin wilson', 'mi - jack conquest racing', '55', 'gearbox', '8', '7'], ['sébastien bourdais', 'newman / haas racing', '42', 'contact', '1', '10'], ['guy smith', 'rocketsports racing', '27', 'engine', '16', '5'], ['nelson philippe', 'mi - jack conquest racing', '21', 'lost wheel', '13', '4'], ['ryan hunter - reay', 'herdez competition', '5', 'contact', '9', '3']] |
hatsuhiko tsuji | https://en.wikipedia.org/wiki/Hatsuhiko_Tsuji | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12955031-1.html.csv | aggregation | the bb + hbp total of hatsuhiko tsuji throughout his career is 580 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '580', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'bb + hbp'], 'result': '580', 'ind': 0, 'tostr': 'sum { all_rows ; bb + hbp }'}, '580'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; bb + hbp } ; 580 } = true', 'tointer': 'the sum of the bb + hbp record of all rows is 580 .'} | round_eq { sum { all_rows ; bb + hbp } ; 580 } = true | the sum of the bb + hbp record of all rows is 580 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'bb + hbp_4': 4, '580_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'bb + hbp_4': 'bb + hbp', '580_5': '580'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'bb + hbp_4': [0], '580_5': [1]} | ['year', 'team', 'number', 'bb + hbp', 'ba ( place )'] | [['1984', 'seibu lions', '5', '11', '209'], ['1985', 'seibu lions', '5', '39', '275'], ['1986', 'seibu lions', '5', '44', '296 （ 13 ）'], ['1987', 'seibu lions', '5', '7', '200'], ['1988', 'seibu lions', '5', '31', '263 （ 23 ）'], ['1989', 'seibu lions', '5', '39', '304 （ 7 ）'], ['1990', 'seibu lions', '5', '53', '266 （ 22 ）'], ['1991', 'seibu lions', '5', '51', '271 （ 14 ）'], ['1992', 'seibu lions', '5', '67', '285 （ 14 ）'], ['1993', 'seibu lions', '5', '57', '319 （ 1 ）'], ['1994', 'seibu lions', '5', '39', '294 （ 8 ）'], ['1995', 'seibu lions', '5', '49', '238'], ['1996', 'yakult swallows', '8', '53', '333 （ 2 ）'], ['1997', 'yakult swallows', '8', '22', '262'], ['1998', 'yakult swallows', '8', '12', '304'], ['1999', 'yakult swallows', '8', '6', '196'], ['carer total', 'carer total', 'carer total', '580', '282']] |
1993 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1993_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11452712-1.html.csv | unique | in the 1993 tampa bay buccaneers season , the only player from hawaii was derrick branch . | {'scope': 'all', 'row': '9', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'hawaii', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'hawaii'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to hawaii .', 'tostr': 'filter_eq { all_rows ; school ; hawaii }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; school ; hawaii } }', 'tointer': 'select the rows whose school record fuzzily matches to hawaii . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'hawaii'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to hawaii .', 'tostr': 'filter_eq { all_rows ; school ; hawaii }'}, 'player'], 'result': 'darrick branch', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; hawaii } ; player }'}, 'darrick branch'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; school ; hawaii } ; player } ; darrick branch }', 'tointer': 'the player record of this unqiue row is darrick branch .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; school ; hawaii } } ; eq { hop { filter_eq { all_rows ; school ; hawaii } ; player } ; darrick branch } } = true', 'tointer': 'select the rows whose school record fuzzily matches to hawaii . there is only one such row in the table . the player record of this unqiue row is darrick branch .'} | and { only { filter_eq { all_rows ; school ; hawaii } } ; eq { hop { filter_eq { all_rows ; school ; hawaii } ; player } ; darrick branch } } = true | select the rows whose school record fuzzily matches to hawaii . there is only one such row in the table . the player record of this unqiue row is darrick branch . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school_7': 7, 'hawaii_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'darrick branch_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school_7': 'school', 'hawaii_8': 'hawaii', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'darrick branch_10': 'darrick branch'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school_7': [0], 'hawaii_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'darrick branch_10': [3]} | ['pick', 'round', 'player', 'position', 'school'] | [['6', 'round 1', 'eric curry', 'defensive end', 'alabama'], ['34', 'round 2', 'demetrius dubose', 'linebacker', 'notre dame'], ['60', 'round 3', 'lamar thomas', 'wide receiver', 'miami'], ['82', 'round 3', 'john lynch', 'defensive back', 'stanford'], ['91', 'round 4', 'rudy harris', 'running back', 'clemson'], ['104', 'round 4', 'horace copeland', 'wide receiver', 'miami'], ['145', 'round 6', 'chidi ahanotu', 'defensive tackle', 'california'], ['176', 'round 7', 'tyree davis', 'wide receiver', 'central arkansas'], ['220', 'round 8', 'darrick branch', 'wide receiver', 'hawaii'], ['224', 'round 8', 'daron alcorn', 'kicker', 'akron']] |
1955 formula one season | https://en.wikipedia.org/wiki/1955_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140113-5.html.csv | count | harry schell was the winning driver for two races in the 1955 formula one season . | {'scope': 'all', 'criterion': 'equal', 'value': 'harry schell', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning driver', 'harry schell'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning driver record fuzzily matches to harry schell .', 'tostr': 'filter_eq { all_rows ; winning driver ; harry schell }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; winning driver ; harry schell } }', 'tointer': 'select the rows whose winning driver record fuzzily matches to harry schell . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; winning driver ; harry schell } } ; 2 } = true', 'tointer': 'select the rows whose winning driver record fuzzily matches to harry schell . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; winning driver ; harry schell } } ; 2 } = true | select the rows whose winning driver record fuzzily matches to harry schell . 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, 'winning driver_5': 5, 'harry schell_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', 'winning driver_5': 'winning driver', 'harry schell_6': 'harry schell', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winning driver_5': [0], 'harry schell_6': [0], '2_7': [2]} | ['race name', 'circuit', 'date', 'winning driver', 'constructor', 'report'] | [['gran premio ciudad de buenos aires', 'buenos aires', '30 january', 'juan manuel fangio', 'mercedes', 'report'], ['vii gran premio del valentino', 'valentino park', '27 march', 'alberto ascari', 'lancia', 'report'], ['xvi pau grand prix', 'pau', '11 april', 'jean behra', 'maserati', 'report'], ['iii glover trophy', 'goodwood', '11 april', 'roy salvadori', 'maserati', 'report'], ['iv grand prix de bordeaux', 'bordeaux', '25 april', 'jean behra', 'maserati', 'report'], ['vii brdc international trophy', 'silverstone', '7 may', 'peter collins', 'maserati', 'report'], ['viii gran premio di napoli', 'posillipo', '8 may', 'alberto ascari', 'lancia', 'report'], ["xvii grand prix d'albi", 'albi', '29 may', 'andrã simon', 'maserati', 'report'], ['iii curtis trophy', 'snetteron', '29 may', 'roy salvadori', 'maserati', 'report'], ['iii cornwall mrc formula 1 race', 'davidstow', '30 may', 'leslie marr', 'connaught - alta', 'report'], ['iii london trophy', 'crystal palace', '30 july', 'mike hawthorn', 'maserati', 'report'], ['iii daily record trophy', 'charterhall', '6 august', 'bob gerard', 'maserati', 'report'], ['iii redex trophy', 'snetterton', '13 august', 'harry schell', 'vanwall', 'report'], ['ii daily telegraph trophy', 'aintree', '3 september', 'roy salvadori', 'maserati', 'report'], ['ii international gold cup', 'oulton park', '24 september', 'stirling moss', 'maserati', 'report'], ['i avon trophy', 'castle combe', '1 october', 'harry schell', 'vanwall', 'report'], ['v gran premio di siracusa', 'syracuse', '23 october', 'tony brooks', 'connaught - alta', 'report']] |
shortest tennis match records | https://en.wikipedia.org/wiki/Shortest_tennis_match_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18336099-1.html.csv | superlative | 1968 is the earliest year in which a shortest tennis match record was recorded . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'year'], 'result': '1968', 'ind': 0, 'tostr': 'min { all_rows ; year }', 'tointer': 'the minimum year record of all rows is 1968 .'}, '1968'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; year } ; 1968 } = true', 'tointer': 'the minimum year record of all rows is 1968 .'} | eq { min { all_rows ; year } ; 1968 } = true | the minimum year record of all rows is 1968 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'min_0': 0, 'all_rows_3': 3, 'year_4': 4, '1968_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'min_0': 'min', 'all_rows_3': 'all_rows', 'year_4': 'year', '1968_5': '1968'} | {'eq_1': [2], 'result_2': [], 'min_0': [1], 'all_rows_3': [0], 'year_4': [0], '1968_5': [1]} | ['year', 'grand slam', 'round', 'winner', 'loser'] | [['1968', 'french open', 'first round', 'nikola špear', 'daniel contet'], ['1987', 'french open', 'second round', 'karel nováček', 'eduardo bengoechea'], ['1987', 'wimbledon', 'first round', 'stefan edberg', 'stefan eriksson'], ['1987', 'us open', 'first round', 'ivan lendl', 'barry moir'], ['1993', 'french open', 'second round', 'sergi bruguera', 'thierry champion'], ['2011', 'davis cup', 'second round', 'andy murray', 'laurent bram']] |
uefa club competition records and statistics | https://en.wikipedia.org/wiki/UEFA_club_competition_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12307135-7.html.csv | aggregation | the top 9 uefa club players had an average of about 62-63 goals in total . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '63.78', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'goals'], 'result': '63.78', 'ind': 0, 'tostr': 'avg { all_rows ; goals }'}, '63.78'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; goals } ; 63.78 } = true', 'tointer': 'the average of the goals record of all rows is 63.78 .'} | round_eq { avg { all_rows ; goals } ; 63.78 } = true | the average of the goals record of all rows is 63.78 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'goals_4': 4, '63.78_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'goals_4': 'goals', '63.78_5': '63.78'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'goals_4': [0], '63.78_5': [1]} | ['rank', 'player', 'goals', 'games', 'debut in europe'] | [['1', 'raúl', '75', '155', '1995'], ['2', 'filippo inzaghi', '70', '114', '1995'], ['3', 'andriy shevchenko', '67', '142', '1994'], ['4', 'lionel messi', '67', '82', '2004'], ['5', 'gerd müller', '62', '69', '1967'], ['5', 'ruud van nistelrooy', '62', '92', '1998'], ['7', 'henrik larsson', '59', '108', '1996'], ['7', 'thierry henry', '59', '140', '1996'], ['9', 'eusébio', '53', '71', '1961']] |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-4.html.csv | superlative | melbourne had the highest score of any home team in the 1972 vfl season . | {'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', 'home team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; home team score }'}, 'home team'], 'result': 'melbourne', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; home team score } ; home team }'}, 'melbourne'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; home team score } ; home team } ; melbourne } = true', 'tointer': 'select the row whose home team score record of all rows is maximum . the home team record of this row is melbourne .'} | eq { hop { argmax { all_rows ; home team score } ; home team } ; melbourne } = true | select the row whose home team score record of all rows is maximum . the home team record of this row is melbourne . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'home team score_5': 5, 'home team_6': 6, 'melbourne_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'home team score_5': 'home team score', 'home team_6': 'home team', 'melbourne_7': 'melbourne'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'home team score_5': [0], 'home team_6': [1], 'melbourne_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '18.19 ( 127 )', 'south melbourne', '8.8 ( 56 )', 'mcg', '18594', '22 april 1972'], ['footscray', '15.10 ( 100 )', 'north melbourne', '12.14 ( 86 )', 'western oval', '12827', '22 april 1972'], ['fitzroy', '11.17 ( 83 )', 'hawthorn', '9.10 ( 64 )', 'junction oval', '16937', '22 april 1972'], ['essendon', '17.27 ( 129 )', 'geelong', '12.14 ( 86 )', 'windy hill', '15000', '22 april 1972'], ['carlton', '15.14 ( 104 )', 'richmond', '15.19 ( 109 )', 'princes park', '28536', '22 april 1972'], ['st kilda', '12.15 ( 87 )', 'collingwood', '9.13 ( 67 )', 'vfl park', '40201', '22 april 1972']] |
2010 - 11 miami heat season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Miami_Heat_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27713030-8.html.csv | superlative | the december 11 game during the 2010 - 11 miami heat season had the highest amount of rebounds . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '7', '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', 'high rebounds'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; high rebounds }'}, 'date'], 'result': 'december 11', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; high rebounds } ; date }'}, 'december 11'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; high rebounds } ; date } ; december 11 } = true', 'tointer': 'select the row whose high rebounds record of all rows is maximum . the date record of this row is december 11 .'} | eq { hop { argmax { all_rows ; high rebounds } ; date } ; december 11 } = true | select the row whose high rebounds record of all rows is maximum . the date record of this row is december 11 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'high rebounds_5': 5, 'date_6': 6, 'december 11_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'high rebounds_5': 'high rebounds', 'date_6': 'date', 'december 11_7': 'december 11'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'date_6': [1], 'december 11_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['19', 'december 1', 'detroit', 'w 97 - 72 ( ot )', 'lebron james ( 18 )', 'chris bosh , james jones ( 7 )', 'mario chalmers ( 6 )', 'american airlines arena 19600', '11 - 8'], ['20', 'december 2', 'cleveland', 'w 118 - 90 ( ot )', 'lebron james ( 38 )', 'dwyane wade ( 9 )', 'dwyane wade ( 9 )', 'quicken loans arena 20562', '12 - 8'], ['21', 'december 4', 'atlanta', 'w 89 - 77 ( ot )', 'chris bosh ( 27 )', 'chris bosh , dwyane wade ( 10 )', 'mario chalmers , lebron james ( 4 )', 'american airlines arena 19600', '13 - 8'], ['22', 'december 6', 'milwaukee', 'w 88 - 78 ( ot )', 'dwyane wade ( 25 )', 'dwyane wade ( 14 )', 'lebron james ( 6 )', 'bradley center 17167', '14 - 8'], ['23', 'december 8', 'utah', 'w 111 - 98 ( ot )', 'lebron james ( 33 )', 'žydrūnas ilgauskas ( 10 )', 'lebron james ( 9 )', 'energysolutions arena 19911', '15 - 8'], ['24', 'december 10', 'golden state', 'w 106 - 84 ( ot )', 'dwyane wade ( 34 )', 'dwyane wade ( 9 )', 'lebron james ( 9 )', 'oracle arena 20036', '16 - 8'], ['25', 'december 11', 'sacramento', 'w 104 - 83 ( ot )', 'dwyane wade ( 36 )', 'chris bosh ( 17 )', 'dwyane wade ( 6 )', 'arco arena 16396', '17 - 8'], ['26', 'december 13', 'new orleans', 'w 96 - 84 ( ot )', 'dwyane wade ( 32 )', 'chris bosh ( 11 )', 'lebron james ( 7 )', 'american airlines arena 19600', '18 - 8'], ['27', 'december 15', 'cleveland', 'w 101 - 95 ( ot )', 'dwyane wade ( 28 )', 'lebron james ( 13 )', 'lebron james ( 5 )', 'american airlines arena 19899', '19 - 8'], ['28', 'december 17', 'new york', 'w 113 - 91 ( ot )', 'lebron james ( 32 )', 'lebron james ( 11 )', 'lebron james ( 10 )', 'madison square garden 19763', '20 - 8'], ['29', 'december 18', 'washington', 'w 95 - 94 ( ot )', 'lebron james ( 32 )', 'chris bosh ( 9 )', 'lebron james ( 6 )', 'verizon center 20278', '21 - 8'], ['30', 'december 20', 'dallas', 'l 96 - 98 ( ot )', 'dwyane wade ( 22 )', 'lebron james ( 10 )', 'lebron james , dwyane wade ( 7 )', 'american airlines arena 20178', '21 - 9'], ['31', 'december 23', 'phoenix', 'w 95 - 83 ( ot )', 'lebron james ( 36 )', 'chris bosh ( 11 )', 'lebron james ( 4 )', 'us airways center 18422', '22 - 9'], ['32', 'december 25', 'la lakers', 'w 96 - 80 ( ot )', 'lebron james ( 27 )', 'chris bosh ( 13 )', 'lebron james ( 10 )', 'staples center 18997', '23 - 9']] |
grado labs | https://en.wikipedia.org/wiki/Grado_Labs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1601027-2.html.csv | unique | the headphone hp1000 from grado labs is the only one that did not receive a successor . | {'scope': 'all', 'row': '3', 'col': '9', 'col_other': '1', 'criterion': 'equal', 'value': 'no successor', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'succeeded by', 'no successor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose succeeded by record fuzzily matches to no successor .', 'tostr': 'filter_eq { all_rows ; succeeded by ; no successor }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; succeeded by ; no successor } }', 'tointer': 'select the rows whose succeeded by record fuzzily matches to no successor . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'succeeded by', 'no successor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose succeeded by record fuzzily matches to no successor .', 'tostr': 'filter_eq { all_rows ; succeeded by ; no successor }'}, 'headphone model'], 'result': 'hp1000', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; succeeded by ; no successor } ; headphone model }'}, 'hp1000'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; succeeded by ; no successor } ; headphone model } ; hp1000 }', 'tointer': 'the headphone model record of this unqiue row is hp1000 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; succeeded by ; no successor } } ; eq { hop { filter_eq { all_rows ; succeeded by ; no successor } ; headphone model } ; hp1000 } } = true', 'tointer': 'select the rows whose succeeded by record fuzzily matches to no successor . there is only one such row in the table . the headphone model record of this unqiue row is hp1000 .'} | and { only { filter_eq { all_rows ; succeeded by ; no successor } } ; eq { hop { filter_eq { all_rows ; succeeded by ; no successor } ; headphone model } ; hp1000 } } = true | select the rows whose succeeded by record fuzzily matches to no successor . there is only one such row in the table . the headphone model record of this unqiue row is hp1000 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'succeeded by_7': 7, 'no successor_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'headphone model_9': 9, 'hp1000_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'succeeded by_7': 'succeeded by', 'no successor_8': 'no successor', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'headphone model_9': 'headphone model', 'hp1000_10': 'hp1000'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'succeeded by_7': [0], 'no successor_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'headphone model_9': [2], 'hp1000_10': [3]} | ['headphone model', 'headphone class', 'sensitivity ( db )', 'impedance ( ohms )', 'driver - matched db', 'construction', 'earpads', 'termination', 'succeeded by'] | [['sr40', 'unknown', '100', '32', 'unknown', 'plastic', 'foam', '1 / 8 ( 3.5 mm ) plug with 1 / 4 adaptor', 'igrado'], ['sr325', 'prestige', '98', '32', '0.05', 'aluminum alloy', 'bowls', '1 / 4 ( 6.5 mm ) plug', 'sr325i'], ['hp1000', 'joseph grado signature', 'unknown', '40', 'unknown', 'aluminum alloy', 'flats', '1 / 4 ( 6.5 mm ) plug', 'no successor'], ['sr100', 'prestige', 'unknown', '32', 'unknown', 'plastic', 'flats', '1 / 4 ( 6.5 mm ) plug', 'sr125'], ['sr200', 'prestige', 'unknown', '32', 'unknown', 'plastic', 'flats', '1 / 4 ( 6.5 mm ) plug', 'sr225'], ['sr300', 'prestige', 'unknown', '32', 'unknown', 'plastic', 'flats', '1 / 4 ( 6.5 mm ) plug', 'sr325']] |
doppler spectroscopy | https://en.wikipedia.org/wiki/Doppler_spectroscopy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10932739-2.html.csv | majority | the majority of the planets have a radial velocity that is lower than 10 m/s . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'radial velocity ( m / s )', '10'], 'result': True, 'ind': 0, 'tointer': 'for the radial velocity ( m / s ) records of all rows , most of them are less than 10 .', 'tostr': 'most_less { all_rows ; radial velocity ( m / s ) ; 10 } = true'} | most_less { all_rows ; radial velocity ( m / s ) ; 10 } = true | for the radial velocity ( m / s ) records of all rows , most of them are less than 10 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'radial velocity (m / s)_3': 3, '10_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'radial velocity (m / s)_3': 'radial velocity ( m / s )', '10_4': '10'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'radial velocity (m / s)_3': [0], '10_4': [0]} | ['planet', 'planet type', 'semimajor axis ( au )', 'orbital period', 'radial velocity ( m / s )', 'detectable by :'] | [['51 pegasi b', 'hot jupiter', '0.05', '4.23 days', '55.9', 'first - generation spectrograph'], ['55 cancri d', 'gas giant', '5.77', '14.29 years', '45.2', 'first - generation spectrograph'], ['jupiter', 'gas giant', '5.20', '11.86 years', '12.4', 'first - generation spectrograph'], ['gliese 581c', 'super - earth', '0.07', '12.92 days', '3.18', 'second - generation spectrograph'], ['saturn', 'gas giant', '9.58', '29.46 years', '2.75', 'second - generation spectrograph'], ['alpha centauri bb', 'terrestrial planet', '0.04', '3.23 days', '0.510', 'second - generation spectrograph'], ['neptune', 'ice giant', '30.10', '164.79 years', '0.281', 'third - generation spectrograph'], ['earth', 'habitable planet', '1.00', '365.26 days', '0.089', 'third - generation spectrograph ( likely )']] |
lithuania in the eurovision song contest 2009 | https://en.wikipedia.org/wiki/Lithuania_in_the_Eurovision_Song_Contest_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18932779-1.html.csv | superlative | sasha son scored the highest amount of points among lithuania artists in the eurovision song contest of 2009 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'artist'], 'result': 'sasha son', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; artist }'}, 'sasha son'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; artist } ; sasha son } = true', 'tointer': 'select the row whose points record of all rows is maximum . the artist record of this row is sasha son .'} | eq { hop { argmax { all_rows ; points } ; artist } ; sasha son } = true | select the row whose points record of all rows is maximum . the artist record of this row is sasha son . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'artist_6': 6, 'sasha son_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', 'artist_6': 'artist', 'sasha son_7': 'sasha son'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'artist_6': [1], 'sasha son_7': [2]} | ['draw', 'artist', 'song', 'points', 'place'] | [['1', 'jonas čepulis and skirmantė', 'uosilėli žaliasai', '49', '7'], ['2', 'alanas', 'geras jausmas', '35', '9'], ['3', 'violeta tarasovienė', 'aš būsiu šalia', '74', '3'], ['4', 'milana', 'ar tu mane matei', '30', '12'], ['5', 'vilius tarasovas', 'aš tik tavim tikiu', '64', '4'], ['6', 'augustė', 'not the best time', '41', '8'], ['7', 'darius pranckevičius and violeta valskytė', 'nelytėta viltis', '78', '2'], ['8', 'kamilė', 'no way to run', '33', '10'], ['9', 'sasha son', 'pasiklydęs žmogus', '92', '1'], ['10', 'vita rusaitytė', 'dar pabūkim drauge', '33', '10'], ['11', '69 danguje', 'meilės simfonija', '62', '5'], ['12', 'egidijus sipavičius', 'per mažai', '56', '6']] |
sexuality of adolf hitler | https://en.wikipedia.org/wiki/Sexuality_of_Adolf_Hitler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13941408-1.html.csv | comparative | erna hanfstaengl lived to be older than maria reiter . | {'row_1': '5', 'row_2': '7', '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', 'erna hanfstaengl'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to erna hanfstaengl .', 'tostr': 'filter_eq { all_rows ; name ; erna hanfstaengl }'}, 'life'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; erna hanfstaengl } ; life }', 'tointer': 'select the rows whose name record fuzzily matches to erna hanfstaengl . take the life record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'maria reiter'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to maria reiter .', 'tostr': 'filter_eq { all_rows ; name ; maria reiter }'}, 'life'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; maria reiter } ; life }', 'tointer': 'select the rows whose name record fuzzily matches to maria reiter . take the life record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; erna hanfstaengl } ; life } ; hop { filter_eq { all_rows ; name ; maria reiter } ; life } } = true', 'tointer': 'select the rows whose name record fuzzily matches to erna hanfstaengl . take the life record of this row . select the rows whose name record fuzzily matches to maria reiter . take the life record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; name ; erna hanfstaengl } ; life } ; hop { filter_eq { all_rows ; name ; maria reiter } ; life } } = true | select the rows whose name record fuzzily matches to erna hanfstaengl . take the life record of this row . select the rows whose name record fuzzily matches to maria reiter . take the life 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, 'erna hanfstaengl_8': 8, 'life_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'maria reiter_12': 12, 'life_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', 'erna hanfstaengl_8': 'erna hanfstaengl', 'life_9': 'life', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'maria reiter_12': 'maria reiter', 'life_13': 'life'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'erna hanfstaengl_8': [0], 'life_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'maria reiter_12': [1], 'life_13': [3]} | ['name', 'life', 'age at death', 'first contact with hitler', 'relationship'] | [['stefanie rabatsch', 'unknown', 'unknown', 'c 1905', 'teenage love interest'], ['charlotte lobjoie', '1898 - 1951', '53', 'allegedly met in 1917', 'poorly substantiated claim that she bore his child'], ['eva braun', 'february 6 , 1912 - april 30 , 1945', '33', 'met in autumn 1929', 'wife'], ['geli raubal', 'june 4 , 1908 - september 18 , 1931', '23', 'lived with hitler in 1925', 'niece , speculated lovers'], ['erna hanfstaengl', '1885 - 1981', '96', 'met in 1920s', 'rumoured lovers'], ['renate müller', 'april 26 , 1906 - october 7 , 1937', '31', 'met in 1930s', 'alleged single sexual encounter'], ['maria reiter', 'december 23 , 1911 - 1992', '81', 'met in 1927', 'possibly lovers'], ['unity mitford', 'august 8 , 1914 - may 28 , 1948', '33', 'met in 1934', 'friends , speculated lovers']] |
2002 rio de janeiro motorcycle grand prix | https://en.wikipedia.org/wiki/2002_Rio_de_Janeiro_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17050986-1.html.csv | count | suzuki manufactured two of the motorcycles ridden in the grand prix . | {'scope': 'all', 'criterion': 'equal', 'value': 'suzuki', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'suzuki'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manufacturer record fuzzily matches to suzuki .', 'tostr': 'filter_eq { all_rows ; manufacturer ; suzuki }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; manufacturer ; suzuki } }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to suzuki . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; manufacturer ; suzuki } } ; 2 } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to suzuki . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; manufacturer ; suzuki } } ; 2 } = true | select the rows whose manufacturer record fuzzily matches to suzuki . 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, 'manufacturer_5': 5, 'suzuki_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', 'manufacturer_5': 'manufacturer', 'suzuki_6': 'suzuki', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manufacturer_5': [0], 'suzuki_6': [0], '2_7': [2]} | ['rider', 'manufacturer', 'laps', 'time / retired', 'grid'] | [['valentino rossi', 'honda', '24', '49:09.516', '2'], ['max biaggi', 'yamaha', '24', '+ 1.674', '1'], ['kenny roberts , jr', 'suzuki', '24', '+ 18.764', '16'], ['alex barros', 'honda', '24', '+ 24.759', '15'], ['loris capirossi', 'honda', '24', '+ 32.354', '12'], ['norifumi abe', 'yamaha', '24', '+ 34.360', '11'], ['olivier jacque', 'yamaha', '24', '+ 44.250', '7'], ['sete gibernau', 'suzuki', '24', '+ 57.150', '18'], ['jurgen vd goorbergh', 'honda', '24', '+ 1:09.987', '8'], ['garry mccoy', 'yamaha', '24', '+ 1:17.611', '4'], ['josé luis cardoso', 'yamaha', '24', '+ 1:20.837', '20'], ['nobuatsu aoki', 'proton kr', '24', '+ 1:50.774', '10'], ['tetsuya harada', 'honda', '23', '+ 1 lap', '19'], ['john hopkins', 'yamaha', '23', '+ 1 lap', '14'], ['régis laconi', 'aprilia', '22', 'accident', '17'], ['carlos checa', 'yamaha', '16', 'accident', '5'], ['jeremy mcwilliams', 'proton kr', '4', 'accident', '3'], ['shinya nakano', 'yamaha', '3', 'accident', '13'], ['tohru ukawa', 'honda', '1', 'accident', '9'], ['daijiro kato', 'honda', '0', 'accident', '6']] |
utah jazz all - time roster | https://en.wikipedia.org/wiki/Utah_Jazz_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11545282-6.html.csv | unique | derrick favors is the only player in the utah jazz all-time roster to still be playing in present day . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'present', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'years for jazz', 'present'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose years for jazz record fuzzily matches to present .', 'tostr': 'filter_eq { all_rows ; years for jazz ; present }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; years for jazz ; present } }', 'tointer': 'select the rows whose years for jazz record fuzzily matches to present . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'years for jazz', 'present'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose years for jazz record fuzzily matches to present .', 'tostr': 'filter_eq { all_rows ; years for jazz ; present }'}, 'player'], 'result': 'derrick favors', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; years for jazz ; present } ; player }'}, 'derrick favors'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; years for jazz ; present } ; player } ; derrick favors }', 'tointer': 'the player record of this unqiue row is derrick favors .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; years for jazz ; present } } ; eq { hop { filter_eq { all_rows ; years for jazz ; present } ; player } ; derrick favors } } = true', 'tointer': 'select the rows whose years for jazz record fuzzily matches to present . there is only one such row in the table . the player record of this unqiue row is derrick favors .'} | and { only { filter_eq { all_rows ; years for jazz ; present } } ; eq { hop { filter_eq { all_rows ; years for jazz ; present } ; player } ; derrick favors } } = true | select the rows whose years for jazz record fuzzily matches to present . there is only one such row in the table . the player record of this unqiue row is derrick favors . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'years for jazz_7': 7, 'present_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'derrick favors_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'years for jazz_7': 'years for jazz', 'present_8': 'present', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'derrick favors_10': 'derrick favors'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'years for jazz_7': [0], 'present_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'derrick favors_10': [3]} | ['player', 'no', 'nationality', 'position', 'years for jazz', 'school / club team'] | [['jim farmer', '30', 'united states', 'guard', '1988 - 89', 'alabama'], ['derrick favors', '15', 'united states', 'forward', '2011 - present', 'georgia tech'], ['kyrylo fesenko', '44', 'ukraine', 'center', '2007 - 11', 'cherkasy monkeys ( ukraine )'], ['derek fisher', '2', 'united states', 'guard', '2006 - 2007', 'arkansas - little rock'], ['greg foster', '44', 'united states', 'center / forward', '1995 - 99', 'utep'], ['bernie fryer', '25', 'united states', 'guard', '1975 - 76', 'byu'], ['todd fuller', '52', 'united states', 'center', '1998 - 99', 'north carolina state']] |
1996 - 97 segunda división | https://en.wikipedia.org/wiki/1996%E2%80%9397_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12090729-2.html.csv | comparative | among the 1996-97 segunda division , ud salamanca had a higher goal difference than cp mérida . | {'row_1': '2', 'row_2': '1', 'col': '10', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'ud salamanca'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to ud salamanca .', 'tostr': 'filter_eq { all_rows ; club ; ud salamanca }'}, 'goal difference'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; ud salamanca } ; goal difference }', 'tointer': 'select the rows whose club record fuzzily matches to ud salamanca . take the goal difference record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'cp mérida'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to cp mérida .', 'tostr': 'filter_eq { all_rows ; club ; cp mérida }'}, 'goal difference'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; cp mérida } ; goal difference }', 'tointer': 'select the rows whose club record fuzzily matches to cp mérida . take the goal difference record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; club ; ud salamanca } ; goal difference } ; hop { filter_eq { all_rows ; club ; cp mérida } ; goal difference } } = true', 'tointer': 'select the rows whose club record fuzzily matches to ud salamanca . take the goal difference record of this row . select the rows whose club record fuzzily matches to cp mérida . take the goal difference record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; club ; ud salamanca } ; goal difference } ; hop { filter_eq { all_rows ; club ; cp mérida } ; goal difference } } = true | select the rows whose club record fuzzily matches to ud salamanca . take the goal difference record of this row . select the rows whose club record fuzzily matches to cp mérida . take the goal difference record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'club_7': 7, 'ud salamanca_8': 8, 'goal difference_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'cp mérida_12': 12, 'goal difference_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'club_7': 'club', 'ud salamanca_8': 'ud salamanca', 'goal difference_9': 'goal difference', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'cp mérida_12': 'cp mérida', 'goal difference_13': 'goal difference'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'ud salamanca_8': [0], 'goal difference_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'cp mérida_12': [1], 'goal difference_13': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'cp mérida', '38', '72', '21', '9', '8', '57', '35', '+ 22'], ['2', 'ud salamanca', '38', '71', '20', '11', '7', '72', '33', '+ 39'], ['3', 'rcd mallorca', '38', '70', '20', '10', '8', '59', '38', '+ 21'], ['4', 'albacete', '38', '66', '19', '9', '10', '51', '32', '+ 19'], ['5', 'sd eibar', '38', '66', '17', '15', '6', '44', '26', '+ 18'], ['6', 'cd badajoz', '38', '60', '15', '15', '8', '38', '26', '+ 12'], ['7', 'ud las palmas', '38', '52', '13', '13', '12', '54', '46', '+ 8'], ['8', 'cd leganés', '38', '52', '13', '13', '12', '43', '39', '+ 4'], ['9', 'levante ud', '38', '50', '13', '11', '14', '53', '46', '+ 7'], ['10', 'villarreal cf', '38', '48', '13', '9', '16', '38', '52', '- 14'], ['11', 'ue lleida', '38', '48', '12', '12', '14', '48', '41', '+ 7'], ['12', 'atlético de madrid b', '38', '47', '12', '11', '15', '57', '61', '- 4'], ['13', 'deportivo alavés', '38', '47', '12', '11', '15', '43', '47', '- 4'], ['14', 'cd toledo', '38', '45', '12', '9', '17', '37', '53', '- 16'], ['15', 'cd ourense', '38', '44', '11', '11', '16', '35', '46', '- 11'], ['16', 'ca osasuna', '38', '44', '11', '11', '16', '34', '42', '- 8'], ['17', 'almería cf', '38', '41', '9', '14', '15', '40', '51', '- 11'], ['18', 'real madrid b', '38', '41', '11', '8', '19', '40', '69', '- 29'], ['19', 'barcelona b', '38', '34', '7', '13', '18', '40', '63', '- 23'], ['20', 'écija', '38', '30', '7', '9', '22', '27', '64', '- 37']] |
1971 green bay packers season | https://en.wikipedia.org/wiki/1971_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14655917-1.html.csv | superlative | the largest attendance occurred at the game that was played at los angeles memorial coliseum . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '6', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'game site'], 'result': 'los angeles memorial coliseum', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; game site }'}, 'los angeles memorial coliseum'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; game site } ; los angeles memorial coliseum } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the game site record of this row is los angeles memorial coliseum .'} | eq { hop { argmax { all_rows ; attendance } ; game site } ; los angeles memorial coliseum } = true | select the row whose attendance record of all rows is maximum . the game site record of this row is los angeles memorial coliseum . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'game site_6': 6, 'los angeles memorial coliseum_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'game site_6': 'game site', 'los angeles memorial coliseum_7': 'los angeles memorial coliseum'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'game site_6': [1], 'los angeles memorial coliseum_7': [2]} | ['week', 'date', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'september 19', 'new york giants', 'l 40 - 42', '0 - 1', 'lambeau field', '56263'], ['2', 'september 26', 'denver broncos', 'w 34 - 13', '1 - 1', 'milwaukee county stadium', '47957'], ['3', 'october 3', 'cincinnati bengals', 'w 20 - 17', '2 - 1', 'lambeau field', '56263'], ['4', 'october 10', 'detroit lions', 'l 28 - 31', '2 - 2', 'tiger stadium', '54418'], ['5', 'october 17', 'minnesota vikings', 'l 13 - 24', '2 - 3', 'lambeau field', '56263'], ['6', 'october 24', 'los angeles rams', 'l 13 - 30', '2 - 4', 'los angeles memorial coliseum', '75531'], ['7', 'november 1', 'detroit lions', 't 14 - 14', '2 - 4 - 1', 'milwaukee county stadium', '47961'], ['8', 'november 7', 'chicago bears', 'w 17 - 14', '3 - 4 - 1', 'soldier field', '55049'], ['9', 'november 14', 'minnesota vikings', 'l 0 - 3', '3 - 5 - 1', 'metropolitan stadium', '49784'], ['10', 'november 22', 'atlanta falcons', 'l 21 - 28', '3 - 6 - 1', 'atlanta stadium', '58850'], ['11', 'november 28', 'new orleans saints', 'l 21 - 29', '3 - 7 - 1', 'milwaukee county stadium', '48035'], ['12', 'december 5', 'st louis cardinals', 't 16 - 16', '3 - 7 - 2', 'busch stadium', '50443'], ['13', 'december 12', 'chicago bears', 'w 31 - 10', '4 - 7 - 2', 'lambeau field', '56263']] |
thunder live | https://en.wikipedia.org/wiki/Thunder_Live | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12702752-1.html.csv | ordinal | the december 21 , 1986 release of thunder live was the second earliest release of the album . | {'row': '2', 'col': '2', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '2'], 'result': 'december 21 , 1986', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 2 }', 'tointer': 'the 2nd minimum date record of all rows is december 21 , 1986 .'}, 'december 21 , 1986'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; date ; 2 } ; december 21 , 1986 } = true', 'tointer': 'the 2nd minimum date record of all rows is december 21 , 1986 .'} | eq { nth_min { all_rows ; date ; 2 } ; december 21 , 1986 } = true | the 2nd minimum date record of all rows is december 21 , 1986 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'date_4': 4, '2_5': 5, 'december 21 , 1986_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'date_4': 'date', '2_5': '2', 'december 21 , 1986_6': 'december 21 , 1986'} | {'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'date_4': [0], '2_5': [0], 'december 21 , 1986_6': [1]} | ['region', 'date', 'label', 'format', 'catalog', 'note'] | [['japan', 'april 21 , 1980', 'alfa records', 'stereo lp', 'alr - 6037', '30 cm'], ['japan', 'december 21 , 1986', 'alfa records', 'cd', '32xa - 106', '12 cm'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 273', '12 cm'], ['japan', 'june 29 , 1994', 'alfa records', 'cd', 'alca - 9003', '12 cm'], ['japan', 'july 23 , 1998', 'alfa records', 'cd', 'alca - 9198', '12 cm'], ['japan', 'december 19 , 2001', 'village records', 'ed remaster cd', 'vrcl - 2203', '12 cm , dsd , lp paper jacket'], ['japan', 'january 17 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2223', '12 cm , dsd'], ['japan', 'may 27 , 2009', 'sony music direct', 'ed remaster cd', 'mhcl - 20005', '12 cm , dsd , blu - spec cd , lp paper jacket']] |
tasmania cricket team list a records | https://en.wikipedia.org/wiki/Tasmania_cricket_team_List_A_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16351707-15.html.csv | aggregation | on average , each player in the tasmania cricket team played about 51 games . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '51', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'matches'], 'result': '51', 'ind': 0, 'tostr': 'avg { all_rows ; matches }'}, '51'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; matches } ; 51 } = true', 'tointer': 'the average of the matches record of all rows is 51 .'} | round_eq { avg { all_rows ; matches } ; 51 } = true | the average of the matches record of all rows is 51 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'matches_4': 4, '51_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'matches_4': 'matches', '51_5': '51'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'matches_4': [0], '51_5': [1]} | ['rank', 's wicket', 'player', 'matches', 'average'] | [['1', '63', 'damien wright', '53', '28.80'], ['2', '48', 'adam griffith', '38', '32.58'], ['3', '43', 'shaun young', '64', '33.33'], ['4', '40', 'brett geeves', '30', '28.42'], ['= 4', '40', 'daniel marsh', '71', '40.60']] |
luis ernesto pérez | https://en.wikipedia.org/wiki/Luis_Ernesto_P%C3%A9rez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1257488-1.html.csv | superlative | in the table of international goals scored by luis ernesto pérez , the highest number of goals scored by his team was 8 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'score'], 'result': '8 - 0', 'ind': 0, 'tostr': 'max { all_rows ; score }', 'tointer': 'the maximum score record of all rows is 8 - 0 .'}, '8 - 0'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; score } ; 8 - 0 } = true', 'tointer': 'the maximum score record of all rows is 8 - 0 .'} | eq { max { all_rows ; score } ; 8 - 0 } = true | the maximum score record of all rows is 8 - 0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'score_4': 4, '8 - 0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'score_4': 'score', '8 - 0_5': '8 - 0'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'score_4': [0], '8 - 0_5': [1]} | ['goal', 'date', 'venue', 'score', 'result', 'competition'] | [['1', 'june 7 , 2000', 'cotton bowl , dallas , united states', '2 - 0', '4 - 0', '2000 nike us cup'], ['2', 'november 17 , 2004', 'estadio tecnológico , monterrey , mexico', '2 - 0', '8 - 0', '2006 fifa world cup qualification'], ['3', 'november 17 , 2004', 'estadio tecnológico , monterrey , mexico', '4 - 0', '8 - 0', '2006 fifa world cup qualification'], ['4', 'november 17 , 2004', 'estadio tecnológico , monterrey , mexico', '8 - 0', '8 - 0', '2006 fifa world cup qualification'], ['5', 'june 8 , 2005', 'estadio universitario , san nicolás , mexico', '2 - 0', '2 - 0', '2006 fifa world cup qualification'], ['6', 'september 7 , 2005', 'estadio azteca , mexico city , mexico', '1 - 0', '5 - 0', '2006 fifa world cup qualification'], ['7', 'october 26 , 2005', 'estadio jalisco , guadalajara , mexico', '3 - 1', '3 - 1', 'friendly'], ['8', 'january 26 , 2006', 'monster park , san francisco , united states', '2 - 1', '2 - 1', 'friendly']] |
art competitions at the 1924 summer olympics | https://en.wikipedia.org/wiki/Art_competitions_at_the_1924_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16581439-2.html.csv | count | 9 nations were represented in art competitions at the 1924 summer olympics . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'nation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record is arbitrary .', 'tostr': 'filter_all { all_rows ; nation }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; nation } }', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; nation } } ; 9 } = true', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 9 .'} | eq { count { filter_all { all_rows ; nation } } ; 9 } = true | select the rows whose nation record is arbitrary . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'nation_5': 5, '9_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'nation_5': 'nation', '9_6': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'nation_5': [0], '9_6': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'luxembourg ( lux )', '1', '1', '0', '2'], ['2', 'france ( fra )', '1', '0', '2', '3'], ['3', 'greece ( gre )', '1', '0', '0', '1'], ['4', 'denmark ( den )', '0', '1', '1', '2'], ['4', 'ireland ( irl )', '0', '1', '1', '2'], ['6', 'great britain ( gbr )', '0', '1', '0', '1'], ['6', 'hungary ( hun )', '0', '1', '0', '1'], ['8', 'monaco ( mon )', '0', '0', '1', '1'], ['8', 'netherlands ( ned )', '0', '0', '1', '1']] |
substance dependence | https://en.wikipedia.org/wiki/Substance_dependence | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1778796-1.html.csv | unique | heroin is the only drug that has a 3.0 rating for pleasure , psychological dependence , and physical dependence . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '3.0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'mean', '3.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mean record is equal to 3.0 .', 'tostr': 'filter_eq { all_rows ; mean ; 3.0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; mean ; 3.0 } }', 'tointer': 'select the rows whose mean record is equal to 3.0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'mean', '3.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mean record is equal to 3.0 .', 'tostr': 'filter_eq { all_rows ; mean ; 3.0 }'}, 'drug'], 'result': 'heroin', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; mean ; 3.0 } ; drug }'}, 'heroin'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; mean ; 3.0 } ; drug } ; heroin }', 'tointer': 'the drug record of this unqiue row is heroin .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; mean ; 3.0 } } ; eq { hop { filter_eq { all_rows ; mean ; 3.0 } ; drug } ; heroin } } = true', 'tointer': 'select the rows whose mean record is equal to 3.0 . there is only one such row in the table . the drug record of this unqiue row is heroin .'} | and { only { filter_eq { all_rows ; mean ; 3.0 } } ; eq { hop { filter_eq { all_rows ; mean ; 3.0 } ; drug } ; heroin } } = true | select the rows whose mean record is equal to 3.0 . there is only one such row in the table . the drug record of this unqiue row is heroin . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'mean_7': 7, '3.0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'drug_9': 9, 'heroin_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'mean_7': 'mean', '3.0_8': '3.0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'drug_9': 'drug', 'heroin_10': 'heroin'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'mean_7': [0], '3.0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'drug_9': [2], 'heroin_10': [3]} | ['drug', 'mean', 'pleasure', 'psychological dependence', 'physical dependence'] | [['heroin', '3.00', '3.0', '3.0', '3.0'], ['cocaine', '2.37', '3.0', '2.8', '1.3'], ['alcohol', '1.93', '2.3', '1.9', '1.6'], ['barbiturates', '2.01', '2.0', '2.2', '1.8'], ['benzodiazepines', '1.83', '1.7', '2.1', '1.8'], ['amphetamine', '1.67', '2.0', '1.9', '1.1'], ['cannabis', '1.51', '1.9', '1.7', '0.8'], ['ecstasy', '1.13', '1.5', '1.2', '0.7'], ['lsd', '0.90', '1.3', '1.1', '0.3']] |
1979 vfl season | https://en.wikipedia.org/wiki/1979_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823719-5.html.csv | majority | the majority of venues in the 1979 vfl season drew a crowd attendance of below 30000 . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '30000', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'crowd', '30000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are less than 30000 .', 'tostr': 'most_less { all_rows ; crowd ; 30000 } = true'} | most_less { all_rows ; crowd ; 30000 } = true | for the crowd records of all rows , most of them are less than 30000 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '30000_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '30000_4': '30000'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '30000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '19.24 ( 138 )', 'south melbourne', '12.16 ( 88 )', 'arden street oval', '16015', '5 may 1979'], ['essendon', '10.16 ( 76 )', 'fitzroy', '25.22 ( 172 )', 'windy hill', '19741', '5 may 1979'], ['carlton', '15.20 ( 110 )', 'melbourne', '13.18 ( 96 )', 'princes park', '24248', '5 may 1979'], ['richmond', '11.16 ( 82 )', 'hawthorn', '24.17 ( 161 )', 'mcg', '31448', '5 may 1979'], ['st kilda', '17.10 ( 112 )', 'geelong', '22.10 ( 142 )', 'moorabbin oval', '15481', '5 may 1979'], ['collingwood', '20.17 ( 137 )', 'footscray', '12.17 ( 89 )', 'vfl park', '34163', '5 may 1979']] |
sebastián prieto | https://en.wikipedia.org/wiki/Sebasti%C3%A1n_Prieto | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12746233-2.html.csv | unique | only the tournament held on july 18 , 2005 took place in stuttgart , germany . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'stuttgart , germany', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'stuttgart , germany'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to stuttgart , germany .', 'tostr': 'filter_eq { all_rows ; tournament ; stuttgart , germany }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; tournament ; stuttgart , germany } }', 'tointer': 'select the rows whose tournament record fuzzily matches to stuttgart , germany . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'stuttgart , germany'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to stuttgart , germany .', 'tostr': 'filter_eq { all_rows ; tournament ; stuttgart , germany }'}, 'date'], 'result': 'july 18 , 2005', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; stuttgart , germany } ; date }'}, 'july 18 , 2005'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; stuttgart , germany } ; date } ; july 18 , 2005 }', 'tointer': 'the date record of this unqiue row is july 18 , 2005 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; tournament ; stuttgart , germany } } ; eq { hop { filter_eq { all_rows ; tournament ; stuttgart , germany } ; date } ; july 18 , 2005 } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to stuttgart , germany . there is only one such row in the table . the date record of this unqiue row is july 18 , 2005 .'} | and { only { filter_eq { all_rows ; tournament ; stuttgart , germany } } ; eq { hop { filter_eq { all_rows ; tournament ; stuttgart , germany } ; date } ; july 18 , 2005 } } = true | select the rows whose tournament record fuzzily matches to stuttgart , germany . there is only one such row in the table . the date record of this unqiue row is july 18 , 2005 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'stuttgart , germany_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'july 18 , 2005_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'stuttgart , germany_8': 'stuttgart , germany', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'july 18 , 2005_10': 'july 18 , 2005'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'tournament_7': [0], 'stuttgart , germany_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'july 18 , 2005_10': [3]} | ['outcome', 'date', 'tournament', 'surface', 'partnering', 'opponent in the final', 'score'] | [['winner', 'november 9 , 1998', 'santiago , chile', 'clay', 'mariano hood', 'massimo bertolini devin bowen', '7 - 6 , 6 - 7 , 7 - 6'], ['winner', 'october 4 , 1999', 'palermo , italy', 'clay', 'mariano hood', 'lan bale alberto martín', '6 - 3 , 6 - 1'], ['winner', 'january 28 , 2001', 'bogotá , colombia', 'clay', 'mariano hood', 'martín rodríguez andré sá', '6 - 2 , 6 - 4'], ['winner', 'february 17 , 2003', 'buenos aires , argentina', 'clay', 'mariano hood', 'lucas arnold ker david nalbandian', '6 - 2 , 6 - 2'], ['winner', 'july 18 , 2005', 'stuttgart , germany', 'clay', 'josé acasuso', 'mariano hood tommy robredo', '7 - 6 ( 4 ) , 6 - 3'], ['winner', 'september 12 , 2005', 'bucharest , romania', 'clay', 'josé acasuso', 'victor hănescu andrei pavel', '6 - 3 , 4 - 6 , 6 - 3'], ['winner', 'january 30 , 2006', 'viña del mar , chile', 'clay', 'josé acasuso', 'františek čermák leoš friedl', '7 - 6 ( 2 ) , 6 - 4'], ['winner', 'february 19 , 2007', 'buenos aires , argentina', 'clay', 'martín garcía', 'albert montañés rubén ramírez hidalgo', '6 - 4 , 6 - 2'], ['winner', 'february 2 , 2008', 'viña del mar , chile', 'clay', 'josé acasuso', 'máximo gonzález juan mónaco', '6 - 1 , 3 - 0 , ret'], ['winner', 'february 21 , 2010', 'buenos aires , argentina', 'clay', 'horacio zeballos', 'simon greul peter luczak', '7 - 6 ( 4 ) , 6 - 3']] |
list of widows and widowers | https://en.wikipedia.org/wiki/List_of_widows_and_widowers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24143253-5.html.csv | superlative | martin van buren had the most children with his wife . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '10', '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', 'children together'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; children together }'}, 'name'], 'result': 'martin van buren', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; children together } ; name }'}, 'martin van buren'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; children together } ; name } ; martin van buren } = true', 'tointer': 'select the row whose children together record of all rows is maximum . the name record of this row is martin van buren .'} | eq { hop { argmax { all_rows ; children together } ; name } ; martin van buren } = true | select the row whose children together record of all rows is maximum . the name record of this row is martin van buren . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'children together_5': 5, 'name_6': 6, 'martin van buren_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'children together_5': 'children together', 'name_6': 'name', 'martin van buren_7': 'martin van buren'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'children together_5': [0], 'name_6': [1], 'martin van buren_7': [2]} | ['name', 'deceased spouse', 'cause of death', 'date of spouses death', 'length of marriage', 'children together', 'current marital status'] | [['chester a arthur', 'ellen lewis herndon arthur', 'pneumonia', 'january 12 , 1880 ( aged42 )', '21 years', '1 daughter ( ellen ) 2 sons ( william , chester ii )', 'deceased ( 1886 )'], ['millard fillmore', 'abigail fillmore', 'pneumonia', 'march 30 , 1853 ( aged55 )', '27 years', '1 daughter ( mary ) 1 son ( millard )', 'deceased ( 1874 )'], ['benjamin harrison', 'caroline harrison', 'tuberculosis', 'october 25 , 1892 ( aged60 )', '39 years', '2 daughters ( mary , unnamed ) 1 son ( russell )', 'deceased ( 1901 )'], ['herbert hoover', 'lou henry hoover', 'heart attack', 'january 7 , 1944 ( aged69 )', '45 years', '2 sons ( herbert jr , allan )', 'deceased ( 1964 )'], ['andrew jackson', 'rachel jackson', 'heart attack', 'december 22 , 1828 ( aged61 )', '34 years', '2 sons ( andrew jr adopted , lyncoya adopted )', 'deceased ( 1845 )'], ['james monroe', 'elizabeth monroe', 'several long illnesses', 'september 23 , 1830 ( aged62 )', '44 years', '2 daughters ( eliza , maria ) 1 son ( james )', 'deceased ( 1831 )'], ['richard nixon', 'pat nixon', 'lung cancer', 'june 22 , 1993 ( aged81 )', '53 years', '2 daughters ( patricia , julie )', 'deceased ( 1994 )'], ['franklin pierce', 'jane pierce', 'tuberculosis', 'december 2 , 1863 ( aged57 )', '29 years', '3 sons ( franklin jr , frank , benjamin )', 'deceased ( 1869 )'], ['theodore roosevelt', 'alice roosevelt', "bright 's disease", 'february 14 , 1884 ( aged22 )', '4 years', '1 daughter ( alice )', 'deceased ( 1919 )'], ['martin van buren', 'hannah van buren', 'tuberculosis', 'february 5 , 1819 ( aged35 )', '12 years', '4 sons ( abraham , john , martin , smith )', 'deceased ( 1862 )']] |
port de pailhères | https://en.wikipedia.org/wiki/Port_de_Pailh%C3%A8res | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12095103-1.html.csv | ordinal | 2003 was the year that had the second least amount of stages in the port de pailheres . | {'row': '5', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'stage', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; stage ; 2 }'}, 'year'], 'result': '2003', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; stage ; 2 } ; year }'}, '2003'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; stage ; 2 } ; year } ; 2003 } = true', 'tointer': 'select the row whose stage record of all rows is 2nd minimum . the year record of this row is 2003 .'} | eq { hop { nth_argmin { all_rows ; stage ; 2 } ; year } ; 2003 } = true | select the row whose stage record of all rows is 2nd minimum . the year record of this row is 2003 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'stage_5': 5, '2_6': 6, 'year_7': 7, '2003_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'stage_5': 'stage', '2_6': '2', 'year_7': 'year', '2003_8': '2003'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'stage_5': [0], '2_6': [0], 'year_7': [1], '2003_8': [2]} | ['year', 'stage', 'category', 'start', 'finish', 'leader at the summit'] | [['2013', '8', 'hc', 'castres', 'ax - 3 domaines', 'nairo quintana ( col )'], ['2010', '14', 'hc', 'revel', 'ax - 3 domaines', 'christophe riblon ( fra )'], ['2007', '14', 'hc', 'mazamet', 'plateau - de - beille', 'rubén pérez ( esp )'], ['2005', '14', 'hc', 'agde', 'ax - 3 domaines', 'georg totschnig ( aut )'], ['2003', '13', '1', 'toulouse', 'ax - 3 domaines', 'juan miguel mercado ( esp )']] |
2003 - 04 primeira liga | https://en.wikipedia.org/wiki/2003%E2%80%9304_Primeira_Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17933600-2.html.csv | ordinal | academica de coimbra was the first team to have a manager change during the 2003-2004 primera liga season . | {'row': '1', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date of appointment', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date of appointment ; 1 }'}, 'team'], 'result': 'académica de coimbra', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date of appointment ; 1 } ; team }'}, 'académica de coimbra'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date of appointment ; 1 } ; team } ; académica de coimbra } = true', 'tointer': 'select the row whose date of appointment record of all rows is 1st minimum . the team record of this row is académica de coimbra .'} | eq { hop { nth_argmin { all_rows ; date of appointment ; 1 } ; team } ; académica de coimbra } = true | select the row whose date of appointment record of all rows is 1st minimum . the team record of this row is académica de coimbra . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date of appointment_5': 5, '1_6': 6, 'team_7': 7, 'académica de coimbra_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date of appointment_5': 'date of appointment', '1_6': '1', 'team_7': 'team', 'académica de coimbra_8': 'académica de coimbra'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date of appointment_5': [0], '1_6': [0], 'team_7': [1], 'académica de coimbra_8': [2]} | ['team', 'outgoing manage', 'manner', 'date of vacancy', 'incoming manager', 'date of appointment'] | [['académica de coimbra', 'artur jorge', 'resigned', '28 august 2003', 'vítor oliveira', '28 august 2003'], ['vitória de guimarães', 'augusto inácio', 'sacked', '8 december 2003', 'jorge jesus', '8 december 2003'], ['paços de ferreira', 'josé gomes', 'mutual consent', '21 october 2003', 'josé mota', '22 october 2003'], ['estrela da amadora', 'joão alves', 'sacked', '3 november 2003', 'miguel quaresma', '3 november 2003'], ['gil vicente', 'mário reis', 'sacked', '11 november 2003', 'luís campos', '25 november 2003'], ['belenenses', 'manuel josé', 'resigned', '22 november 2003', 'bogićević', '23 november 2003'], ['belenenses', 'bogićević', 'sacked', '19 january 2004', 'augusto inácio', '20 january 2004'], ['académica de coimbra', 'vítor oliveira', 'sacked', '26 january 2004', 'joão pereira', '27 january 2004'], ['boavista', 'erwin sánchez', 'sacked', '8 march 2004', 'jaime pacheco', '8 march 2004']] |
2005 pga championship | https://en.wikipedia.org/wiki/2005_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12512153-6.html.csv | count | 5 players which participated in the 2005 pga championship were from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '5', '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': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 5 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; country ; united states } } ; 5 } = true | select the rows whose country record fuzzily matches to united states . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '5_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'davis love iii', 'united states', '68 + 68 + 68 = 204', '- 6'], ['t1', 'phil mickelson', 'united states', '67 + 65 + 72 = 204', '- 6'], ['3', 'thomas bjørn', 'denmark', '71 + 71 + 63 = 205', '- 5'], ['t4', 'stuart appleby', 'australia', '67 + 70 + 69 = 206', '- 4'], ['t4', 'steve elkington', 'australia', '68 + 70 + 68 = 206', '- 4'], ['t4', 'pat perez', 'united states', '68 + 71 + 67 = 206', '- 4'], ['t4', 'vijay singh', 'fiji', '70 + 67 + 69 = 206', '- 4'], ['t8', 'jason bohn', 'united states', '71 + 68 + 68 = 207', '- 3'], ['t8', 'ben curtis', 'united states', '67 + 73 + 67 = 207', '- 3'], ['t8', 'retief goosen', 'south africa', '68 + 70 + 69 = 207', '- 3'], ['t8', 'greg owen', 'england', '68 + 69 + 70 = 207', '- 3'], ['t8', 'lee westwood', 'england', '68 + 68 + 71 = 207', '- 3']] |
hampden football netball league | https://en.wikipedia.org/wiki/Hampden_Football_Netball_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18628904-27.html.csv | aggregation | the average number of draws in the hampden football netball league is 9.38 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '9.38', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'draws'], 'result': '9.38', 'ind': 0, 'tostr': 'avg { all_rows ; draws }'}, '9.38'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; draws } ; 9.38 } = true', 'tointer': 'the average of the draws record of all rows is 9.38 .'} | round_eq { avg { all_rows ; draws } ; 9.38 } = true | the average of the draws record of all rows is 9.38 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'draws_4': 4, '9.38_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'draws_4': 'draws', '9.38_5': '9.38'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'draws_4': [0], '9.38_5': [1]} | ['club', 'active', 'wins', 'losses', 'draws', 'percentage wins', 'flags'] | [['camperdown', '1930 - 2011', '723', '665', '15', '51.53 %', '6'], ['cobden', '1930 - 2011', '640', '733', '17', '46.04 %', '6'], ['colac', '1949 - 2000', '597', '373', '10', '60.92 %', '10'], ['coragulac', '1961 - 1979', '118', '225', '2', '33.91 %', '0'], ['koroit', '1961 - 2011', '431', '528', '8', '44.57 %', '5'], ['mortlake', '1930 - 1998', '473', '633', '18', '42.08 %', '3'], ['north warrnambool', '1997 - 2011', '52', '213', '3', '19.40 %', '0'], ['port fairy', '1949 - 2011', '410', '738', '2', '35.65 %', '1'], ['south warrnambool', '1933 - 2011', '745', '611', '17', '54.26 %', '11'], ['terang', '1930 - 2001', '642', '580', '10', '52.11 %', '8'], ['terang mortlake', '2002 - 2011', '141', '61', '1', '69.46 %', '3'], ['warrnambool', '1933 - 2011', '895', '490', '19', '63.75 %', '23'], ['western lions', '1999 - 2000', '2', '17', '0', '10.5 %', '0']] |
list of castle episodes | https://en.wikipedia.org/wiki/List_of_Castle_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23958944-2.html.csv | count | there were two castle shows with a total viewership higher than 10 us million viewers . | {'scope': 'all', 'criterion': 'greater_than', 'value': '10', 'result': '2', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( in millions )', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( in millions ) record is greater than 10 .', 'tostr': 'filter_greater { all_rows ; us viewers ( in millions ) ; 10 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; us viewers ( in millions ) ; 10 } }', 'tointer': 'select the rows whose us viewers ( in millions ) record is greater than 10 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; us viewers ( in millions ) ; 10 } } ; 2 } = true', 'tointer': 'select the rows whose us viewers ( in millions ) record is greater than 10 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; us viewers ( in millions ) ; 10 } } ; 2 } = true | select the rows whose us viewers ( in millions ) record is greater than 10 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'us viewers (in millions)_5': 5, '10_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'us viewers (in millions)_5': 'us viewers ( in millions )', '10_6': '10', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'us viewers (in millions)_5': [0], '10_6': [0], '2_7': [2]} | ['no by series', 'title', 'directed by', 'written by', 'original air date', 'production number', 'us viewers ( in millions )'] | [['1', 'flowers for your grave', 'rob bowman', 'andrew w marlowe', 'march 9 , 2009', '101', '10.76'], ['2', 'nanny mcdead', 'john terlesky', 'barry schindel', 'march 16 , 2009', '103', '10.97'], ['3', 'hedge fund homeboys', 'rob bowman', 'david grae', 'march 23 , 2009', '104', '9.14'], ['4', 'hell hath no fury', 'rob bowman', 'andrew w marlowe', 'march 30 , 2009', '102', '9.09'], ['5', 'a chill goes through her veins', 'bryan spicer', 'charles murray', 'april 6 , 2009', '105', '9.03'], ['6', 'always buy retail', 'jamie babbit', 'gabrielle stanton & harry werksman', 'april 13 , 2009', '107', '7.73'], ['7', 'home is where the heart stops', 'dean white', 'will beall', 'april 20 , 2009', '106', '8.21'], ['8', 'ghosts', 'bryan spicer', 'moira kirland', 'april 27 , 2009', '108', '8.24']] |
llanberis lake railway | https://en.wikipedia.org/wiki/Llanberis_Lake_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1281645-1.html.csv | unique | garrett is the only llanberis lake railway locomotive that was built in 1939 . | {'scope': 'all', 'row': '7', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '1939', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '1939'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to 1939 .', 'tostr': 'filter_eq { all_rows ; date ; 1939 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; 1939 } }', 'tointer': 'select the rows whose date record is equal to 1939 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '1939'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to 1939 .', 'tostr': 'filter_eq { all_rows ; date ; 1939 }'}, 'name'], 'result': 'garrett', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 1939 } ; name }'}, 'garrett'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; 1939 } ; name } ; garrett }', 'tointer': 'the name record of this unqiue row is garrett .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date ; 1939 } } ; eq { hop { filter_eq { all_rows ; date ; 1939 } ; name } ; garrett } } = true', 'tointer': 'select the rows whose date record is equal to 1939 . there is only one such row in the table . the name record of this unqiue row is garrett .'} | and { only { filter_eq { all_rows ; date ; 1939 } } ; eq { hop { filter_eq { all_rows ; date ; 1939 } ; name } ; garrett } } = true | select the rows whose date record is equal to 1939 . there is only one such row in the table . the name record of this unqiue row is garrett . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '1939_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'garrett_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '1939_8': '1939', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'garrett_10': 'garrett'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'date_7': [0], '1939_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'garrett_10': [3]} | ['number', 'name', 'builder', 'type', 'works number', 'date'] | [['1', 'elidir', 'hunslet', '0 - 4 - 0 st', '493', '1889'], ['2', 'thomas bach', 'hunslet', '0 - 4 - 0 st', '894', '1904'], ['3', 'dolbadarn', 'hunslet', '0 - 4 - 0 st', '1430', '1922'], ['3', 'maid marian', 'hunslet', '0 - 4 - 0 st', '822', '1903'], ['7', 'topsy', 'ruston hornsby', '4wdm', '441427', '1961'], ['8', 'twll coed', 'ruston hornsby', '4wdm', '268878', '1952'], ['11', 'garrett', 'ruston hornsby', '4wdm', '198286', '1939'], ['12', 'llanelli', 'ruston hornsby', '4wdm', '451901', '1961']] |
1988 - 89 philadelphia flyers season | https://en.wikipedia.org/wiki/1988%E2%80%9389_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14323142-3.html.csv | count | in the 1988-89 philadelphia flyers season , there were three games where there were 17 points . | {'scope': 'all', 'criterion': 'equal', 'value': '17', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '17'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 17 .', 'tostr': 'filter_eq { all_rows ; points ; 17 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; points ; 17 } }', 'tointer': 'select the rows whose points record is equal to 17 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; points ; 17 } } ; 3 } = true', 'tointer': 'select the rows whose points record is equal to 17 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; points ; 17 } } ; 3 } = true | select the rows whose points record is equal to 17 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'points_5': 5, '17_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'points_5': 'points', '17_6': '17', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'points_5': [0], '17_6': [0], '3_7': [2]} | ['game', 'november', 'opponent', 'score', 'record', 'points'] | [['12', '1', 'new jersey devils', '2 - 3', '6 - 6 - 0', '12'], ['13', '3', 'vancouver canucks', '2 - 5', '6 - 7 - 0', '12'], ['14', '4', 'detroit red wings', '4 - 3', '7 - 7 - 0', '14'], ['15', '6', 'pittsburgh penguins', '5 - 4', '8 - 7 - 0', '16'], ['16', '9', 'new york rangers', '3 - 5', '8 - 8 - 0', '16'], ['17', '10', 'calgary flames', '2 - 3 ot', '8 - 9 - 0', '16'], ['18', '12', 'detroit red wings', '4 - 5', '8 - 10 - 0', '16'], ['19', '15', 'new york rangers', '3 - 3 ot', '8 - 10 - 1', '17'], ['20', '17', 'st louis blues', '1 - 3', '8 - 11 - 1', '17'], ['21', '19', 'quebec nordiques', '5 - 6', '8 - 12 - 1', '17'], ['22', '20', 'new jersey devils', '7 - 1', '9 - 12 - 1', '19'], ['23', '22', 'los angeles kings', '1 - 6', '9 - 13 - 1', '19'], ['24', '24', 'boston bruins', '1 - 2 ot', '9 - 14 - 1', '19'], ['25', '26', 'pittsburgh penguins', '3 - 4', '9 - 15 - 1', '19'], ['26', '27', 'buffalo sabres', '3 - 7', '9 - 16 - 1', '19'], ['27', '29', 'boston bruins', '5 - 1', '10 - 16 - 1', '21']] |
north melbourne football club | https://en.wikipedia.org/wiki/North_Melbourne_Football_Club | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22106-3.html.csv | unique | for the north melbourne football club , when the captain was a simpson , the only time the chairman was j magowan was in 2007 . | {'scope': 'subset', 'row': '8', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'j magowan', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'a simpson'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'captain', 'a simpson'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; captain ; a simpson }', 'tointer': 'select the rows whose captain record fuzzily matches to a simpson .'}, 'chairman', 'j magowan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose captain record fuzzily matches to a simpson . among these rows , select the rows whose chairman record fuzzily matches to j magowan .', 'tostr': 'filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan } }', 'tointer': 'select the rows whose captain record fuzzily matches to a simpson . among these rows , select the rows whose chairman record fuzzily matches to j magowan . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'captain', 'a simpson'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; captain ; a simpson }', 'tointer': 'select the rows whose captain record fuzzily matches to a simpson .'}, 'chairman', 'j magowan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose captain record fuzzily matches to a simpson . among these rows , select the rows whose chairman record fuzzily matches to j magowan .', 'tostr': 'filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan }'}, 'year'], 'result': '2007', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan } ; year }'}, '2007'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan } ; year } ; 2007 }', 'tointer': 'the year record of this unqiue row is 2007 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan } } ; eq { hop { filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan } ; year } ; 2007 } } = true', 'tointer': 'select the rows whose captain record fuzzily matches to a simpson . among these rows , select the rows whose chairman record fuzzily matches to j magowan . there is only one such row in the table . the year record of this unqiue row is 2007 .'} | and { only { filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan } } ; eq { hop { filter_eq { filter_eq { all_rows ; captain ; a simpson } ; chairman ; j magowan } ; year } ; 2007 } } = true | select the rows whose captain record fuzzily matches to a simpson . among these rows , select the rows whose chairman record fuzzily matches to j magowan . there is only one such row in the table . the year record of this unqiue row is 2007 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'captain_8': 8, 'a simpson_9': 9, 'chairman_10': 10, 'j magowan_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'year_12': 12, '2007_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'captain_8': 'captain', 'a simpson_9': 'a simpson', 'chairman_10': 'chairman', 'j magowan_11': 'j magowan', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'year_12': 'year', '2007_13': '2007'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'captain_8': [0], 'a simpson_9': [0], 'chairman_10': [1], 'j magowan_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'year_12': [3], '2007_13': [4]} | ['year', 'w : l : d', 'position', 'chairman', 'ceo', 'coach', 'captain', 'vice - captain', 'best and fairest', 'leading goalkicker'] | [['2000', '15:10:0', '4th', 'r p casey / a carter', 'g miller', 'd pagan', 'w carey', 'a stevens', 'p bell', 'w carey 69'], ['2001', '9:13:0', '13th', 'a carter / a aylett', 'g miller / m easy', 'd pagan', 'w carey', 'a stevens', 's grant', 's rocca 48'], ['2002', '12:11:0', '7th', 'a aylett', 'm easy / g walsh', 'd pagan', 'a stevens', 'g archer', 'a simpson', 's rocca 50'], ['2003', '11:10:1', '10th', 'a aylett', 'g walsh', 'd laidley', 'a stevens', 'g archer', 'b harvey', 'l harding 33'], ['2004', '10:12:0', '10th', 'a aylett', 'g walsh', 'd laidley', 'a simpson', 'b harvey', 'b rawlings', 's rocca 49'], ['2005', '13:10:0', '7th', 'a aylett / g duff', 'g walsh', 'd laidley', 'a simpson', 'b harvey', 'b harvey', 'n thompson 52'], ['2006', '7:15:0', '14th', 'g duff', 'g walsh / r aylett', 'd laidley', 'a simpson', 'b harvey', 'b rawlings', 'n thompson 54'], ['2007', '15:10:0', '3rd', 'g duff / j magowan / j brayshaw', 'r aylett', 'd laidley', 'a simpson', 'b harvey', 'b harvey', 'c jones 43'], ['2008', '12:10:1', '7th', 'j brayshaw', 'e arocca', 'd laidley', 'a simpson', 'b harvey', 'b harvey', 'd hale 37'], ['2009', '7:14:1', '13th', 'j brayshaw', 'e arocca', 'd laidley / d crocker', 'b harvey', 'd petrie', 'a swallow', 'd petrie 27'], ['2010', '11:11:0', '9th', 'j brayshaw', 'e arocca', 'b scott', 'b harvey', 'd petrie', 'b harvey , b rawlings', 'l thomas 29'], ['2011', '10:12:0', '9th', 'j brayshaw', 'e arocca', 'b scott', 'b harvey', 'd petrie', 'a swallow , d wells', 'd petrie 48'], ['2012', '14:8:0', '8th', 'j brayshaw', 'earocca / cvale', 'b scott', 'a swallow', 'd petrie , j ziebell', 'aswallow', 'd petrie 57']] |
2002 belarusian premier league | https://en.wikipedia.org/wiki/2002_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14747981-1.html.csv | count | there were two teams that were relegated to the belarusian first league . | {'scope': 'all', 'criterion': 'equal', 'value': 'first league', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position in 2001', 'first league'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position in 2001 record fuzzily matches to first league .', 'tostr': 'filter_eq { all_rows ; position in 2001 ; first league }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position in 2001 ; first league } }', 'tointer': 'select the rows whose position in 2001 record fuzzily matches to first league . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position in 2001 ; first league } } ; 2 } = true', 'tointer': 'select the rows whose position in 2001 record fuzzily matches to first league . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; position in 2001 ; first league } } ; 2 } = true | select the rows whose position in 2001 record fuzzily matches to first league . 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, 'position in 2001_5': 5, 'first league_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', 'position in 2001_5': 'position in 2001', 'first league_6': 'first league', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position in 2001_5': [0], 'first league_6': [0], '2_7': [2]} | ['team', 'location', 'venue', 'capacity', 'position in 2001'] | [['belshina', 'bobruisk', 'spartak , bobruisk', '3550', '1'], ['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '2'], ['bate', 'borisov', 'city stadium , borisov', '5500', '3'], ['neman', 'grodno', 'neman', '6300', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['gomel', 'gomel', 'central , gomel', '11800', '6'], ['slavia', 'mozyr', 'yunost', '5500', '7'], ['torpedo - maz', 'minsk', 'torpedo , minsk', '5200', '8'], ['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '9'], ['molodechno - 2000', 'molodechno', 'city stadium , molodechno', '5500', '10'], ['dinamo brest', 'brest', 'osk brestskiy', '10080', '11'], ['lokomotiv - 96', 'vitebsk', 'central , vitebsk', '8300', '12'], ['torpedo', 'zhodino', 'torpedo , zhodino', '3020', 'first league , 1'], ['zvezda - va - bgu', 'minsk', 'traktor', '17600', 'first league , 2']] |
united states house of representatives elections , 1828 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1828 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668243-17.html.csv | unique | michael hoffman was the only incumbent from new york , in the 1828 united states house of representative elections that ran without an opponent and received 100 % of the votes . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1,2', 'criterion': 'fuzzily_match', 'value': '100 %', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', '100 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to 100 % .', 'tostr': 'filter_eq { all_rows ; candidates ; 100 % }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; candidates ; 100 % } }', 'tointer': 'select the rows whose candidates record fuzzily matches to 100 % . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', '100 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to 100 % .', 'tostr': 'filter_eq { all_rows ; candidates ; 100 % }'}, 'district'], 'result': 'new york 15', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; candidates ; 100 % } ; district }'}, 'new york 15'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; candidates ; 100 % } ; district } ; new york 15 }', 'tointer': 'the district record of this unqiue row is new york 15 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', '100 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to 100 % .', 'tostr': 'filter_eq { all_rows ; candidates ; 100 % }'}, 'incumbent'], 'result': 'michael hoffman', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; candidates ; 100 % } ; incumbent }'}, 'michael hoffman'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; candidates ; 100 % } ; incumbent } ; michael hoffman }', 'tointer': 'the incumbent record of this unqiue row is michael hoffman .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; candidates ; 100 % } ; district } ; new york 15 } ; eq { hop { filter_eq { all_rows ; candidates ; 100 % } ; incumbent } ; michael hoffman } }', 'tointer': 'the district record of this unqiue row is new york 15 . the incumbent record of this unqiue row is michael hoffman .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; candidates ; 100 % } } ; and { eq { hop { filter_eq { all_rows ; candidates ; 100 % } ; district } ; new york 15 } ; eq { hop { filter_eq { all_rows ; candidates ; 100 % } ; incumbent } ; michael hoffman } } } = true', 'tointer': 'select the rows whose candidates record fuzzily matches to 100 % . there is only one such row in the table . the district record of this unqiue row is new york 15 . the incumbent record of this unqiue row is michael hoffman .'} | and { only { filter_eq { all_rows ; candidates ; 100 % } } ; and { eq { hop { filter_eq { all_rows ; candidates ; 100 % } ; district } ; new york 15 } ; eq { hop { filter_eq { all_rows ; candidates ; 100 % } ; incumbent } ; michael hoffman } } } = true | select the rows whose candidates record fuzzily matches to 100 % . there is only one such row in the table . the district record of this unqiue row is new york 15 . the incumbent record of this unqiue row is michael hoffman . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'candidates_10': 10, '100%_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'district_12': 12, 'new york 15_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'incumbent_14': 14, 'michael hoffman_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'candidates_10': 'candidates', '100%_11': '100 %', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_12': 'district', 'new york 15_13': 'new york 15', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'incumbent_14': 'incumbent', 'michael hoffman_15': 'michael hoffman'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'candidates_10': [0], '100%_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'district_12': [2], 'new york 15_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'incumbent_14': [4], 'michael hoffman_15': [5]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['new york 1', 'silas wood', 'anti - jacksonian', '1818', 'lost re - election jacksonian gain', 'james lent ( j ) 52.3 % silas wood ( aj ) 47.7 %'], ['new york 6', 'john hallock , jr', 'jacksonian', '1824', 'retired jacksonian hold', 'hector craig ( j ) 55.7 % samuel j wilkin ( aj ) 44.3 %'], ['new york 8', 'james strong', 'anti - jacksonian', '1818 1822', 're - elected', 'james strong ( aj ) 50.9 % james vanderpoel ( j ) 49.1 %'], ['new york 11', 'selah r hobbie', 'jacksonian', '1826', 'retired jacksonian hold', 'perkins king ( j ) 61.6 % jacob haight ( aj ) 38.4 %'], ['new york 15', 'michael hoffman', 'jacksonian', '1824', 're - elected', 'michael hoffman ( j ) 100 %'], ['new york 17', 'john w taylor', 'anti - jacksonian', '1812', 're - elected', 'john w taylor ( aj ) 54.9 % john cramer ( j ) 45.1 %'], ['new york 21', 'john c clark', 'jacksonian', '1826', 'retired jacksonian hold', 'robert monell ( j ) 63.6 % tilly lynde 36.4 %'], ['new york 22', 'john g stower', 'jacksonian', '1824', 'lost re - election anti - jacksonian gain', 'thomas beekman ( aj ) 53.4 % john g stower ( j ) 46.6 %'], ['new york 25', 'david woodcock', 'anti - jacksonian', '1821 1826', 'lost re - election jacksonian gain', 'thomas maxwell ( j ) 60.1 % david woodcock ( aj ) 39.9 %']] |
1944 vfl season | https://en.wikipedia.org/wiki/1944_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809142-5.html.csv | aggregation | total vfl match attenance on 3 june 1944 was 78,000 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '78,000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '78,000', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '78,000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 78,000 } = true', 'tointer': 'the sum of the crowd record of all rows is 78,000 .'} | round_eq { sum { all_rows ; crowd } ; 78,000 } = true | the sum of the crowd record of all rows is 78,000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '78,000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '78,000_5': '78,000'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '78,000_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '10.13 ( 73 )', 'st kilda', '13.8 ( 86 )', 'punt road oval', '8000', '3 june 1944'], ['essendon', '17.14 ( 116 )', 'geelong', '11.14 ( 80 )', 'windy hill', '7000', '3 june 1944'], ['carlton', '16.12 ( 108 )', 'richmond', '14.8 ( 92 )', 'princes park', '28000', '3 june 1944'], ['south melbourne', '10.12 ( 72 )', 'north melbourne', '10.13 ( 73 )', 'junction oval', '15000', '3 june 1944'], ['footscray', '8.15 ( 63 )', 'fitzroy', '8.10 ( 58 )', 'western oval', '9000', '3 june 1944'], ['hawthorn', '8.9 ( 57 )', 'collingwood', '10.13 ( 73 )', 'glenferrie oval', '11000', '3 june 1944']] |
international formula master | https://en.wikipedia.org/wiki/International_Formula_Master | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11292165-3.html.csv | majority | the majority of these series were the international formula master . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'international formula master', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'series name', 'international formula master'], 'result': True, 'ind': 0, 'tointer': 'for the series name records of all rows , most of them fuzzily match to international formula master .', 'tostr': 'most_eq { all_rows ; series name ; international formula master } = true'} | most_eq { all_rows ; series name ; international formula master } = true | for the series name records of all rows , most of them fuzzily match to international formula master . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'series name_3': 3, 'international formula master_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'series name_3': 'series name', 'international formula master_4': 'international formula master'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'series name_3': [0], 'international formula master_4': [0]} | ['season', 'series name', 'champion', 'team champion', 'secondary class champion'] | [['2005', '3000 pro series', 'norbert siedler / max busnelli', 'draco junior team', 'iago rego rosende ( master junior formula )'], ['2006', 'f3000 international masters', 'jan charouz', 'charouz racing system', 'daniel campos - hull ( master junior formula )'], ['2007', 'international formula master', "jérôme d'ambrosio", 'cram competition', 'isaac lópez navarro ( master junior formula )'], ['2008', 'international formula master', 'chris van der drift', 'jd motorsport', 'marcello puglisi ( formula master italia )'], ['2009', 'international formula master', 'fabio leimer', 'jd motorsport', 'alexander rossi ( rookie of the year )']] |
list of metropolitan areas in sweden | https://en.wikipedia.org/wiki/List_of_metropolitan_areas_in_Sweden | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1245658-3.html.csv | count | there are 12 municipalities in the metropolitan areas of sweden . | {'scope': 'all', 'criterion': 'not_equal', 'value': 'total', 'result': '12', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'municipality', 'total'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose municipality record does not match to total .', 'tostr': 'filter_not_eq { all_rows ; municipality ; total }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_not_eq { all_rows ; municipality ; total } }', 'tointer': 'select the rows whose municipality record does not match to total . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_not_eq { all_rows ; municipality ; total } } ; 12 } = true', 'tointer': 'select the rows whose municipality record does not match to total . the number of such rows is 12 .'} | eq { count { filter_not_eq { all_rows ; municipality ; total } } ; 12 } = true | select the rows whose municipality record does not match to total . the number of such rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'municipality_5': 5, 'total_6': 6, '12_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'municipality_5': 'municipality', 'total_6': 'total', '12_7': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'municipality_5': [0], 'total_6': [0], '12_7': [2]} | ['municipality', 'number', 'population', 'area', 'density square'] | [['malmö', '1', '309912', '335.14', '925'], ['vellinge', '2', '33725', '143.18', '236'], ['trelleborg', '3', '42744', '342.07', '125'], ['skurup', '4', '15000', '195.17', '77'], ['svedala', '5', '20039', '218.97', '92'], ['lund', '6', '112925', '430.27', '262'], ['staffanstorp', '7', '22572', '107.61', '210'], ['burlöv', '8', '17079', '18.84', '907'], ['lomma', '9', '22415', '55.64', '403'], ['kävlinge', '10', '29513', '153.83', '192'], ['eslöv', '11', '31761', '421.66', '75'], ['höör', '12', '15591', '292.96', '53'], ['total', '12', '673276', '2715.34', '247.95']] |
sagarika ghatge | https://en.wikipedia.org/wiki/Sagarika_Ghatge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12807043-1.html.csv | ordinal | sagarika ghatge 's second to last role was that of ahana sharma . | {'row': '4', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year ; 2 }'}, 'role'], 'result': 'ahana sharma', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year ; 2 } ; role }'}, 'ahana sharma'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; year ; 2 } ; role } ; ahana sharma } = true', 'tointer': 'select the row whose year record of all rows is 2nd maximum . the role record of this row is ahana sharma .'} | eq { hop { nth_argmax { all_rows ; year ; 2 } ; role } ; ahana sharma } = true | select the row whose year record of all rows is 2nd maximum . the role record of this row is ahana sharma . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'role_7': 7, 'ahana sharma_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', 'year_5': 'year', '2_6': '2', 'role_7': 'role', 'ahana sharma_8': 'ahana sharma'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'role_7': [1], 'ahana sharma_8': [2]} | ['year', 'title', 'role', 'language', 'notes'] | [['2007', 'chak de ! india', 'preeti sabarwal', 'hindi', 'supporting role'], ['2009', 'fox', 'urvashi mathur', 'hindi', 'small role'], ['2011', 'miley naa miley hum', 'kamiah', 'hindi', 'supporting role'], ['2012', 'rush', 'ahana sharma', 'hindi', 'released on october 24 , 2012'], ['2013', 'premachi goshta', 'sonal', 'marathi', 'lead role , movie directed by satish rajwade']] |
sigurd rushfeldt | https://en.wikipedia.org/wiki/Sigurd_Rushfeldt | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1207980-1.html.csv | comparative | sigurd rushfeldt 's number of scores on 2005 - 10 - 08 was one lower than it was on 2005 - 02 - 09 . | {'row_1': '6', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2005 - 10 - 08'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 2005 - 10 - 08 .', 'tostr': 'filter_eq { all_rows ; date ; 2005 - 10 - 08 }'}, 'scored'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 2005 - 10 - 08 } ; scored }', 'tointer': 'select the rows whose date record fuzzily matches to 2005 - 10 - 08 . take the scored record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2005 - 02 - 09'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 2005 - 02 - 09 .', 'tostr': 'filter_eq { all_rows ; date ; 2005 - 02 - 09 }'}, 'scored'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 2005 - 02 - 09 } ; scored }', 'tointer': 'select the rows whose date record fuzzily matches to 2005 - 02 - 09 . take the scored record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; date ; 2005 - 10 - 08 } ; scored } ; hop { filter_eq { all_rows ; date ; 2005 - 02 - 09 } ; scored } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 2005 - 10 - 08 . take the scored record of this row . select the rows whose date record fuzzily matches to 2005 - 02 - 09 . take the scored record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; date ; 2005 - 10 - 08 } ; scored } ; hop { filter_eq { all_rows ; date ; 2005 - 02 - 09 } ; scored } } = true | select the rows whose date record fuzzily matches to 2005 - 10 - 08 . take the scored record of this row . select the rows whose date record fuzzily matches to 2005 - 02 - 09 . take the scored 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, 'date_7': 7, '2005 - 10 - 08_8': 8, 'scored_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '2005 - 02 - 09_12': 12, 'scored_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', 'date_7': 'date', '2005 - 10 - 08_8': '2005 - 10 - 08', 'scored_9': 'scored', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '2005 - 02 - 09_12': '2005 - 02 - 09', 'scored_13': 'scored'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '2005 - 10 - 08_8': [0], 'scored_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '2005 - 02 - 09_12': [1], 'scored_13': [3]} | ['date', 'venue', 'result', 'competition', 'scored'] | [['2002 - 05 - 14', 'ullevaal stadion , oslo', '3 - 0', 'friendly match', '1'], ['2003 - 01 - 28', 'bausher , muscat', '2 - 0', 'friendly match', '1'], ['2003 - 02 - 04', 'stade josy barthel , luxembourg city', '2 - 0', 'uefa euro 2004 qualifying', '1'], ['2004 - 04 - 28', 'ullevaal stadion , oslo', '3 - 2', 'friendly match', '1'], ['2005 - 02 - 09', "ta ' qali stadium , attard", '3 - 0', 'friendly match', '2'], ['2005 - 10 - 08', 'ullevaal stadion , oslo', '1 - 0', '2006 fifa world cup qualification', '1']] |
1981 houston oilers season | https://en.wikipedia.org/wiki/1981_Houston_Oilers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18847715-2.html.csv | comparative | the 1981 houston oilers ' game against the cleveland browns had a higher attendance than their game against the pittsburgh steelers . | {'row_1': '2', 'row_2': '8', 'col': '5', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'cleveland browns'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to cleveland browns .', 'tostr': 'filter_eq { all_rows ; opponent ; cleveland browns }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; cleveland browns } ; attendance }', 'tointer': 'select the rows whose opponent record fuzzily matches to cleveland browns . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'pittsburgh steelers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to pittsburgh steelers .', 'tostr': 'filter_eq { all_rows ; opponent ; pittsburgh steelers }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; pittsburgh steelers } ; attendance }', 'tointer': 'select the rows whose opponent record fuzzily matches to pittsburgh steelers . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; cleveland browns } ; attendance } ; hop { filter_eq { all_rows ; opponent ; pittsburgh steelers } ; attendance } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to cleveland browns . take the attendance record of this row . select the rows whose opponent record fuzzily matches to pittsburgh steelers . take the attendance record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; cleveland browns } ; attendance } ; hop { filter_eq { all_rows ; opponent ; pittsburgh steelers } ; attendance } } = true | select the rows whose opponent record fuzzily matches to cleveland browns . take the attendance record of this row . select the rows whose opponent record fuzzily matches to pittsburgh steelers . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'cleveland browns_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'pittsburgh steelers_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'cleveland browns_8': 'cleveland browns', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'pittsburgh steelers_12': 'pittsburgh steelers', 'attendance_13': 'attendance'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'cleveland browns_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'pittsburgh steelers_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 6 , 1981', 'los angeles rams', 'w 27 - 20', '63198'], ['2', 'september 13 , 1981', 'cleveland browns', 'w 9 - 3', '79483'], ['3', 'september 20 , 1981', 'miami dolphins', 'l 16 - 10', '47379'], ['4', 'september 27 , 1981', 'new york jets', 'l 33 - 17', '50309'], ['5', 'october 4 , 1981', 'cincinnati bengals', 'w 17 - 10', '44350'], ['6', 'october 11 , 1981', 'seattle seahawks', 'w 35 - 17', '42671'], ['7', 'october 18 , 1981', 'new england patriots', 'l 38 - 10', '60474'], ['8', 'october 26 , 1981', 'pittsburgh steelers', 'l 26 - 13', '52732'], ['9', 'november 1 , 1981', 'cincinnati bengals', 'l 34 - 21', '54736'], ['10', 'november 8 , 1981', 'oakland raiders', 'w 17 - 16', '45519'], ['11', 'november 15 , 1981', 'kansas city chiefs', 'l 23 - 10', '73984'], ['12', 'november 22 , 1981', 'new orleans saints', 'l 27 - 24', '49581'], ['13', 'november 29 , 1981', 'atlanta falcons', 'l 31 - 27', '40201'], ['14', 'december 3 , 1981', 'cleveland browns', 'w 17 - 13', '44502'], ['15', 'december 13 , 1981', 'san francisco 49ers', 'l 28 - 6', '55707'], ['16', 'december 20 , 1981', 'pittsburgh steelers', 'w 21 - 20', '41056']] |
1931 vfl season | https://en.wikipedia.org/wiki/1931_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10789881-9.html.csv | comparative | there were more people at the game that took place at mcg than at the game at lake oval . | {'row_1': '1', 'row_2': '4', 'col': '6', 'col_other': '5', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', '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': 'hop { filter_eq { all_rows ; venue ; mcg } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to mcg . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'lake oval'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to lake oval .', 'tostr': 'filter_eq { all_rows ; venue ; lake oval }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; lake oval } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to lake oval . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; venue ; mcg } ; crowd } ; hop { filter_eq { all_rows ; venue ; lake oval } ; crowd } } = true', 'tointer': '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 lake oval . take the crowd record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; venue ; mcg } ; crowd } ; hop { filter_eq { all_rows ; venue ; lake oval } ; 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 lake oval . take the crowd record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'mcg_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'lake oval_12': 12, 'crowd_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', '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', 'lake oval_12': 'lake oval', 'crowd_13': 'crowd'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'mcg_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'lake oval_12': [1], 'crowd_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '4.12 ( 36 )', 'st kilda', '9.9 ( 63 )', 'mcg', '15826', '4 july 1931'], ['geelong', '13.9 ( 87 )', 'hawthorn', '9.7 ( 61 )', 'corio oval', '9500', '4 july 1931'], ['fitzroy', '8.13 ( 61 )', 'richmond', '14.17 ( 101 )', 'brunswick street oval', '15000', '4 july 1931'], ['south melbourne', '10.13 ( 73 )', 'essendon', '9.9 ( 63 )', 'lake oval', '11000', '4 july 1931'], ['footscray', '4.16 ( 40 )', 'collingwood', '6.8 ( 44 )', 'western oval', '21500', '4 july 1931'], ['north melbourne', '7.8 ( 50 )', 'carlton', '20.10 ( 130 )', 'arden street oval', '10000', '4 july 1931']] |
no way out ( 2009 ) | https://en.wikipedia.org/wiki/No_Way_Out_%282009%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18438494-3.html.csv | count | a total of two wrestler eliminations were by the method of pinned after a spear . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'pinned after a spear', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method of elimination', 'pinned after a spear'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method of elimination record fuzzily matches to pinned after a spear .', 'tostr': 'filter_eq { all_rows ; method of elimination ; pinned after a spear }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; method of elimination ; pinned after a spear } }', 'tointer': 'select the rows whose method of elimination record fuzzily matches to pinned after a spear . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; method of elimination ; pinned after a spear } } ; 2 } = true', 'tointer': 'select the rows whose method of elimination record fuzzily matches to pinned after a spear . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; method of elimination ; pinned after a spear } } ; 2 } = true | select the rows whose method of elimination record fuzzily matches to pinned after a spear . 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, 'method of elimination_5': 5, 'pinned after a spear_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', 'method of elimination_5': 'method of elimination', 'pinned after a spear_6': 'pinned after a spear', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'method of elimination_5': [0], 'pinned after a spear_6': [0], '2_7': [2]} | ['eliminated', 'wrestler', 'entered', 'eliminated by', 'method of elimination', 'time'] | [['1', 'kane', '3', 'rey mysterio', 'pinned after a seated senton from the top of a pod', '09:37'], ['2', 'mike knox', '4', 'chris jericho', 'pinned after a codebreaker', '14:42'], ['3', 'cena', '6', 'edge', 'pinned after a spear', '22:22'], ['4', 'jericho', '2', 'rey mysterio', 'pinned when mysterio reversed the walls of jericho', '23:54'], ['5', 'rey mysterio', '1', 'edge', 'pinned after a spear', '29:46']] |
2009 belmont stakes | https://en.wikipedia.org/wiki/2009_Belmont_Stakes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22517564-3.html.csv | count | two of the horses that raced in the 2009 belmont stakes were trained by the same person named d wayne lukas . | {'scope': 'all', 'criterion': 'equal', 'value': 'd wayne lukas', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'trainer', 'd wayne lukas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose trainer record fuzzily matches to d wayne lukas .', 'tostr': 'filter_eq { all_rows ; trainer ; d wayne lukas }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; trainer ; d wayne lukas } }', 'tointer': 'select the rows whose trainer record fuzzily matches to d wayne lukas . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; trainer ; d wayne lukas } } ; 2 } = true', 'tointer': 'select the rows whose trainer record fuzzily matches to d wayne lukas . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; trainer ; d wayne lukas } } ; 2 } = true | select the rows whose trainer record fuzzily matches to d wayne lukas . 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, 'trainer_5': 5, 'd wayne lukas_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', 'trainer_5': 'trainer', 'd wayne lukas_6': 'd wayne lukas', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'trainer_5': [0], 'd wayne lukas_6': [0], '2_7': [2]} | ['post', 'horse name', 'trainer', 'jockey', 'opening odds', 'starting odds', 'finishing pos'] | [['1', 'chocolate candy', 'jerry hollendorfer', 'garrett gomez', '10 - 1', '9.50', '9'], ['2', 'dunkirk', 'todd pletcher', 'john velazquez', '4 - 1', '4.60', '2'], ['3', 'mr hot stuff', 'eoin harty', 'edgar prado', '15 - 1', '22.60', '8'], ['4', 'summer bird', 'tim ice', 'kent desormeaux', '12 - 1', '11.90', '1'], ['5', 'luv gov', 'd wayne lukas', 'miguel mena', '20 - 1', '22.40', '5'], ['6', 'charitable man', 'kiaran mclaughlin', 'alan garcia', '3 - 1', '4.60', '4'], ['7', 'mine that bird', 'bennie l woolley , jr', 'calvin borel', '2 - 1', '1.25', '3'], ['8', 'flying private', 'd wayne lukas', 'julien leparoux', '12 - 1', '17.30', '6'], ['9', "miner 's escape", 'nick zito', 'joze lezcano', '15 - 1', '22.00', '10']] |
phil parsons | https://en.wikipedia.org/wiki/Phil_Parsons | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2597876-1.html.csv | majority | phil parsons finished in the top 50 positions in the majority of events he participated in . | {'scope': 'all', 'col': '10', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '50', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'position', '50'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them are less than 50 .', 'tostr': 'most_less { all_rows ; position ; 50 } = true'} | most_less { all_rows ; position ; 50 } = true | for the position records of all rows , most of them are less than 50 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, '50_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', '50_4': '50'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], '50_4': [0]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1983', '5', '0', '0', '0', '0', '15.4', '23.8', '23850', '43rd', '66 johnny hayes racing'], ['1984', '23', '0', '0', '3', '0', '21.0', '19.3', '90700', '24th', '66 johnny hayes racing'], ['1985', '28', '0', '0', '4', '0', '20.5', '21.9', '104840', '21st', '66 jackson bros motorsports 17 hamby racing'], ['1986', '17', '0', '1', '5', '0', '18.6', '20.5', '84680', '27th', '66 jackson bros motorsports 17 hamby racing'], ['1987', '29', '0', '1', '7', '0', '19.4', '16.5', '180261', '14th', '55 jackson bros motorsports'], ['1988', '29', '1', '6', '15', '0', '17.0', '14.3', '532043', '9th', '55 jackson bros motorsports'], ['1989', '29', '0', '2', '3', '0', '22.4', '21.1', '285012', '21st', '55 jackson bros motorsports 60 combs racing'], ['1992', '2', '0', '0', '1', '0', '26.0', '20.0', '58475', '53rd', '9 melling racing'], ['1994', '3', '0', '0', '0', '0', '32.3', '27.3', '21415', '50th', '9 melling racing'], ['1995', '2', '0', '0', '0', '0', '35.0', '41.5', '41450', '60th', '19 tristar motorsports']] |
carlos castro borja | https://en.wikipedia.org/wiki/Carlos_Castro_Borja | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15290075-1.html.csv | superlative | the first goal carlos castro borja scored during 1994 fifa world cup qualification was played at estadio rigoberto lópez . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2,5', 'subset': {'col': '5', 'criterion': 'equal', 'value': '1994 fifa world cup qualification'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '1994 fifa world cup qualification'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competition ; 1994 fifa world cup qualification }', 'tointer': 'select the rows whose competition record fuzzily matches to 1994 fifa world cup qualification .'}, 'date'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; competition ; 1994 fifa world cup qualification } ; date }'}, 'venue'], 'result': 'estadio rigoberto lópez , managua , nicaragua', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; competition ; 1994 fifa world cup qualification } ; date } ; venue }'}, 'estadio rigoberto lópez , managua , nicaragua'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; competition ; 1994 fifa world cup qualification } ; date } ; venue } ; estadio rigoberto lópez , managua , nicaragua } = true', 'tointer': 'select the rows whose competition record fuzzily matches to 1994 fifa world cup qualification . select the row whose date record of these rows is minimum . the venue record of this row is estadio rigoberto lópez , managua , nicaragua .'} | eq { hop { argmin { filter_eq { all_rows ; competition ; 1994 fifa world cup qualification } ; date } ; venue } ; estadio rigoberto lópez , managua , nicaragua } = true | select the rows whose competition record fuzzily matches to 1994 fifa world cup qualification . select the row whose date record of these rows is minimum . the venue record of this row is estadio rigoberto lópez , managua , nicaragua . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'competition_6': 6, '1994 fifa world cup qualification_7': 7, 'date_8': 8, 'venue_9': 9, 'estadio rigoberto lópez , managua , nicaragua_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'competition_6': 'competition', '1994 fifa world cup qualification_7': '1994 fifa world cup qualification', 'date_8': 'date', 'venue_9': 'venue', 'estadio rigoberto lópez , managua , nicaragua_10': 'estadio rigoberto lópez , managua , nicaragua'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'competition_6': [0], '1994 fifa world cup qualification_7': [0], 'date_8': [1], 'venue_9': [2], 'estadio rigoberto lópez , managua , nicaragua_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['18 february 1992', 'estadio cuscatlán , san salvador , el salvador', '1 - 0', '2 - 0', 'friendly match'], ['19 july 1992', 'estadio rigoberto lópez , managua , nicaragua', '3 - 0', '5 - 0', '1994 fifa world cup qualification'], ['23 july 1992', 'estadio cuscatlán , san salvador , el salvador', '1 - 0', '5 - 1', '1994 fifa world cup qualification'], ['23 july 1992', 'estadio cuscatlán , san salvador , el salvador', '3 - 0', '5 - 1', '1994 fifa world cup qualification'], ['4 april 1993', 'estadio cuscatlán , san salvador , el salvador', '1 - 0', '2 - 1', '1994 fifa world cup qualification'], ['23 july 2000', 'estadio cuscatlán , san salvador , el salvador', '2 - 1', '7 - 1', '2002 fifa world cup qualification']] |
2008 - 09 supersport series | https://en.wikipedia.org/wiki/2008%E2%80%9309_Supersport_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19662262-6.html.csv | comparative | in the 2008 - 09 supersport series , juan theron had fewer overs than makhaya ntini . | {'row_1': '3', 'row_2': '1', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'juan theron'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to juan theron .', 'tostr': 'filter_eq { all_rows ; player ; juan theron }'}, 'overs'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; juan theron } ; overs }', 'tointer': 'select the rows whose player record fuzzily matches to juan theron . take the overs record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'makhaya ntini'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to makhaya ntini .', 'tostr': 'filter_eq { all_rows ; player ; makhaya ntini }'}, 'overs'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; makhaya ntini } ; overs }', 'tointer': 'select the rows whose player record fuzzily matches to makhaya ntini . take the overs record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; juan theron } ; overs } ; hop { filter_eq { all_rows ; player ; makhaya ntini } ; overs } } = true', 'tointer': 'select the rows whose player record fuzzily matches to juan theron . take the overs record of this row . select the rows whose player record fuzzily matches to makhaya ntini . take the overs record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; juan theron } ; overs } ; hop { filter_eq { all_rows ; player ; makhaya ntini } ; overs } } = true | select the rows whose player record fuzzily matches to juan theron . take the overs record of this row . select the rows whose player record fuzzily matches to makhaya ntini . take the overs record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'juan theron_8': 8, 'overs_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'makhaya ntini_12': 12, 'overs_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'juan theron_8': 'juan theron', 'overs_9': 'overs', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'makhaya ntini_12': 'makhaya ntini', 'overs_13': 'overs'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'juan theron_8': [0], 'overs_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'makhaya ntini_12': [1], 'overs_13': [3]} | ['player', 'team', 'matches', 'overs', 'wickets', 'economy rate', 'average', 'strike rate', 'bbi', 'bbm'] | [['makhaya ntini', 'warriors', '4', '152.4', '24', '2.18', '13.91', '38.1', '6 / 85', '9 / 109'], ['lonwabo tsotsobe', 'warriors', '4', '127.5', '16', '2.26', '18.12', '47.9', '4 / 3', '5 / 98'], ['juan theron', 'warriors', '4', '133.4', '19', '2.71', '19.10', '42.2', '7 / 46', '7 / 56'], ['mornã morkel', 'titans', '3', '92.2', '17', '3.51', '19.17', '32.7', '6 / 47', '11 / 56'], ['paul harris', 'titans', '3', '126.0', '14', '2.74', '22.28', '54.0', '7 / 94', '12 / 180']] |
ethnic groups in london | https://en.wikipedia.org/wiki/Ethnic_groups_in_London | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19149550-9.html.csv | majority | most of the london boroughs have an indian population of over 10000 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'indian population', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the indian population records of all rows , most of them are greater than 10000 .', 'tostr': 'most_greater { all_rows ; indian population ; 10000 } = true'} | most_greater { all_rows ; indian population ; 10000 } = true | for the indian population records of all rows , most of them are greater than 10000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'indian population_3': 3, '10000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'indian population_3': 'indian population', '10000_4': '10000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'indian population_3': [0], '10000_4': [0]} | ['rank', 'london borough', 'indian population', 'pakistani population', 'bangladeshi population', 'chinese population', 'other asian population', 'total asian population'] | [['1', 'newham', '42484', '30307', '37262', '3930', '19912', '133895'], ['2', 'redbridge', '45660', '31051', '16011', '3000', '20781', '116503'], ['3', 'brent', '58017', '14381', '1749', '3250', '28589', '105986'], ['4', 'tower hamlets', '6787', '2442', '81377', '8109', '5786', '104501'], ['5', 'harrow', '63051', '7797', '1378', '2629', '26953', '101808'], ['6', 'ealing', '48240', '14711', '1786', '4132', '31570', '100439'], ['7', 'hounslow', '48161', '13676', '2189', '2405', '20826', '87257'], ['8', 'hillingdon', '36795', '9200', '2639', '2889', '17730', '69253'], ['9', 'haringey', '36795', '9200', '2639', '2889', '17730', '69253'], ['10', 'barnet', '27920', '5344', '2215', '8259', '22180', '65918'], ['11', 'croydon', '24660', '10865', '2570', '3925', '17607', '59627'], ['12', 'waltham forest', '9134', '26347', '4632', '2579', '11697', '54389'], ['13', 'merton', '8106', '7337', '2216', '2618', '15866', '36143'], ['14', 'camden', '6083', '1489', '12503', '6493', '8878', '35446'], ['15', 'enfield', '11648', '2594', '5599', '2588', '12464', '34893'], ['16', 'wandsworth', '8642', '9718', '1493', '3715', '9770', '33338'], ['17', 'westminster', '7213', '2328', '6299', '5917', '10105', '31862'], ['18', 'greenwich', '7836', '2594', '1645', '5061', '12758', '29894'], ['19', 'barking and dagenham', '7436', '8007', '7701', '1315', '5135', '29594']] |
black diamond conference | https://en.wikipedia.org/wiki/Black_Diamond_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18304058-2.html.csv | majority | the majority of the lack diamond conference schools have at least 400 enrolled students . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '400', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'enrollment ( 2013 / 14 )', '400'], 'result': True, 'ind': 0, 'tointer': 'for the enrollment ( 2013 / 14 ) records of all rows , most of them are greater than 400 .', 'tostr': 'most_greater { all_rows ; enrollment ( 2013 / 14 ) ; 400 } = true'} | most_greater { all_rows ; enrollment ( 2013 / 14 ) ; 400 } = true | for the enrollment ( 2013 / 14 ) records of all rows , most of them are greater than 400 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'enrollment (2013 / 14)_3': 3, '400_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'enrollment (2013 / 14)_3': 'enrollment ( 2013 / 14 )', '400_4': '400'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'enrollment (2013 / 14)_3': [0], '400_4': [0]} | ['team name', 'schools', 'sports', 'host', 'nickname ( s )', 'colors', 'enrollment ( 2013 / 14 )'] | [['christopher - zeigler - royalton', 'christopher zeigler - royalton', 'football , track and field', 'christopher', 'bearcats lady cats', 'blue orange', '412'], ['eldorado - galatia', 'eldorado galatia', 'cross country , golf , track and field', 'eldorado', 'eagles', 'purple gold', '461'], ['elverado - trico', 'elverado trico', 'football', 'elverado', 'falcons', 'blue gold', '436'], ['fairfield - cisne', 'cisne fairfield', 'wrestling', 'fairfield', 'mules lady mules', 'red black', '549'], ['sesser - valier - waltonville', 'sesser - valier waltonville', "girls ' basketball , track and field , volleyball", 'sesser - valier', 'red devils', 'maroon white', '309'], ['sesser - valier - waltonville - woodlawn', 'sesser - valier waltonville woodlawn', 'football', 'sesser - valier', 'red devils', 'maroon white', '494'], ['vienna - goreville', 'goreville vienna', 'football', 'vienna', 'eagles', 'royal blue orange', '503'], ['zeigler - royalton - christopher', 'christopher zeigler - royalton', "baseball , girls ' basketball , golf , softball", 'zeigler - royalton', 'tornadoes', 'navy blue white', '412']] |
1988 - 89 philadelphia flyers season | https://en.wikipedia.org/wiki/1988%E2%80%9389_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14323142-3.html.csv | comparative | in the 1988-89 philadelphia flyers season , the game on november 27th had 2 fewer points than the game on november 29th . | {'row_1': '15', 'row_2': '16', 'col': '6', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '2', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'november', '27'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose november record fuzzily matches to 27 .', 'tostr': 'filter_eq { all_rows ; november ; 27 }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; november ; 27 } ; points }', 'tointer': 'select the rows whose november record fuzzily matches to 27 . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'november', '29'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose november record fuzzily matches to 29 .', 'tostr': 'filter_eq { all_rows ; november ; 29 }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; november ; 29 } ; points }', 'tointer': 'select the rows whose november record fuzzily matches to 29 . take the points record of this row .'}], 'result': '-2', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; november ; 27 } ; points } ; hop { filter_eq { all_rows ; november ; 29 } ; points } }'}, '-2'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; november ; 27 } ; points } ; hop { filter_eq { all_rows ; november ; 29 } ; points } } ; -2 } = true', 'tointer': 'select the rows whose november record fuzzily matches to 27 . take the points record of this row . select the rows whose november record fuzzily matches to 29 . take the points record of this row . the second record is 2 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; november ; 27 } ; points } ; hop { filter_eq { all_rows ; november ; 29 } ; points } } ; -2 } = true | select the rows whose november record fuzzily matches to 27 . take the points record of this row . select the rows whose november record fuzzily matches to 29 . take the points record of this row . the second record is 2 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, 'november_8': 8, '27_9': 9, 'points_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'november_12': 12, '29_13': 13, 'points_14': 14, '-2_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'november_8': 'november', '27_9': '27', 'points_10': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'november_12': 'november', '29_13': '29', 'points_14': 'points', '-2_15': '-2'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'november_8': [0], '27_9': [0], 'points_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'november_12': [1], '29_13': [1], 'points_14': [3], '-2_15': [5]} | ['game', 'november', 'opponent', 'score', 'record', 'points'] | [['12', '1', 'new jersey devils', '2 - 3', '6 - 6 - 0', '12'], ['13', '3', 'vancouver canucks', '2 - 5', '6 - 7 - 0', '12'], ['14', '4', 'detroit red wings', '4 - 3', '7 - 7 - 0', '14'], ['15', '6', 'pittsburgh penguins', '5 - 4', '8 - 7 - 0', '16'], ['16', '9', 'new york rangers', '3 - 5', '8 - 8 - 0', '16'], ['17', '10', 'calgary flames', '2 - 3 ot', '8 - 9 - 0', '16'], ['18', '12', 'detroit red wings', '4 - 5', '8 - 10 - 0', '16'], ['19', '15', 'new york rangers', '3 - 3 ot', '8 - 10 - 1', '17'], ['20', '17', 'st louis blues', '1 - 3', '8 - 11 - 1', '17'], ['21', '19', 'quebec nordiques', '5 - 6', '8 - 12 - 1', '17'], ['22', '20', 'new jersey devils', '7 - 1', '9 - 12 - 1', '19'], ['23', '22', 'los angeles kings', '1 - 6', '9 - 13 - 1', '19'], ['24', '24', 'boston bruins', '1 - 2 ot', '9 - 14 - 1', '19'], ['25', '26', 'pittsburgh penguins', '3 - 4', '9 - 15 - 1', '19'], ['26', '27', 'buffalo sabres', '3 - 7', '9 - 16 - 1', '19'], ['27', '29', 'boston bruins', '5 - 1', '10 - 16 - 1', '21']] |
2003 mls superdraft | https://en.wikipedia.org/wiki/2003_MLS_SuperDraft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1014145-2.html.csv | count | 4 of the drafted players in the 2003 mls superdraft played the m position . | {'scope': 'all', 'criterion': 'equal', 'value': 'm', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to m .', 'tostr': 'filter_eq { all_rows ; position ; m }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; m } }', 'tointer': 'select the rows whose position record fuzzily matches to m . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; m } } ; 4 } = true', 'tointer': 'select the rows whose position record fuzzily matches to m . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; position ; m } } ; 4 } = true | select the rows whose position record fuzzily matches to m . 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, 'position_5': 5, 'm_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', 'position_5': 'position', 'm_6': 'm', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'm_6': [0], '4_7': [2]} | ['pick', 'mls team', 'player', 'position', 'affiliation'] | [['11', 'dc united', 'brian carroll', 'm', 'wake forest university'], ['12', 'metrostars', 'eddie gaven', 'm', 'nike project - 40'], ['13', 'san jose earthquakes', 'arturo alvarez', 'm', 'nike project - 40'], ['14', 'dc united', 'doug warren', 'gk', 'clemson university'], ['15', 'dallas burn', 'jason thompson', 'f', 'eastern illinois university'], ['16', 'los angeles galaxy', 'scot thompson', 'd', 'ucla'], ['17', 'metrostars', 'tim regan', 'd', 'bradley university'], ['18', 'chicago fire', 'damani ralph', 'f', 'university of connecticut'], ['19', 'los angeles galaxy', 'arturo torres', 'm', 'loyola marymount university'], ['20', 'los angeles galaxy', 'ricky lewis', 'd', 'clemson university']] |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17596418-7.html.csv | count | in the 2008 - 09 cardiff city f.c. season , among the players that had bbc sport as a start source , 2 of them had dundee united as a loan club . | {'scope': 'subset', 'criterion': 'equal', 'value': 'dundee united', 'result': '2', 'col': '3', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'bbc sport'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'start source', 'bbc sport'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; start source ; bbc sport }', 'tointer': 'select the rows whose start source record fuzzily matches to bbc sport .'}, 'loan club', 'dundee united'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose start source record fuzzily matches to bbc sport . among these rows , select the rows whose loan club record fuzzily matches to dundee united .', 'tostr': 'filter_eq { filter_eq { all_rows ; start source ; bbc sport } ; loan club ; dundee united }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; start source ; bbc sport } ; loan club ; dundee united } }', 'tointer': 'select the rows whose start source record fuzzily matches to bbc sport . among these rows , select the rows whose loan club record fuzzily matches to dundee united . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; start source ; bbc sport } ; loan club ; dundee united } } ; 2 } = true', 'tointer': 'select the rows whose start source record fuzzily matches to bbc sport . among these rows , select the rows whose loan club record fuzzily matches to dundee united . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; start source ; bbc sport } ; loan club ; dundee united } } ; 2 } = true | select the rows whose start source record fuzzily matches to bbc sport . among these rows , select the rows whose loan club record fuzzily matches to dundee united . 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, 'start source_6': 6, 'bbc sport_7': 7, 'loan club_8': 8, 'dundee united_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', 'start source_6': 'start source', 'bbc sport_7': 'bbc sport', 'loan club_8': 'loan club', 'dundee united_9': 'dundee united', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'start source_6': [0], 'bbc sport_7': [0], 'loan club_8': [1], 'dundee united_9': [1], '2_10': [3]} | ['name', 'country', 'loan club', 'started', 'ended', 'start source'] | [['flood', 'irl', 'dundee united', '2 july', '30 january', 'bbc sport'], ['feeney', 'nir', 'dundee united', '7 july', '19 may', 'bbc sport'], ['sak', 'pol', 'newport county', '2 september', '2 october', 'enews'], ['brown', 'wal', 'wrexham', '25 november', '3 february', 'bbc sport'], ['dennehy', 'irl', 'hereford united', '13 march', '13 april', 'hereford united']] |
opec | https://en.wikipedia.org/wiki/OPEC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-166346-1.html.csv | unique | for opec , for the countries in the africa region , the only one who joined opec in 1969 is algeria . | {'scope': 'subset', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '1969', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'africa'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'africa'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; region ; africa }', 'tointer': 'select the rows whose region record fuzzily matches to africa .'}, 'joined opec', '1969'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose region record fuzzily matches to africa . among these rows , select the rows whose joined opec record is equal to 1969 .', 'tostr': 'filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } }', 'tointer': 'select the rows whose region record fuzzily matches to africa . among these rows , select the rows whose joined opec record is equal to 1969 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'africa'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; region ; africa }', 'tointer': 'select the rows whose region record fuzzily matches to africa .'}, 'joined opec', '1969'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose region record fuzzily matches to africa . among these rows , select the rows whose joined opec record is equal to 1969 .', 'tostr': 'filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 }'}, 'country'], 'result': 'algeria', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } ; country }'}, 'algeria'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } ; country } ; algeria }', 'tointer': 'the country record of this unqiue row is algeria .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } } ; eq { hop { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } ; country } ; algeria } } = true', 'tointer': 'select the rows whose region record fuzzily matches to africa . among these rows , select the rows whose joined opec record is equal to 1969 . there is only one such row in the table . the country record of this unqiue row is algeria .'} | and { only { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } } ; eq { hop { filter_eq { filter_eq { all_rows ; region ; africa } ; joined opec ; 1969 } ; country } ; algeria } } = true | select the rows whose region record fuzzily matches to africa . among these rows , select the rows whose joined opec record is equal to 1969 . there is only one such row in the table . the country record of this unqiue row is algeria . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'region_8': 8, 'africa_9': 9, 'joined opec_10': 10, '1969_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'country_12': 12, 'algeria_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'region_8': 'region', 'africa_9': 'africa', 'joined opec_10': 'joined opec', '1969_11': '1969', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'country_12': 'country', 'algeria_13': 'algeria'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'region_8': [0], 'africa_9': [0], 'joined opec_10': [1], '1969_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'country_12': [3], 'algeria_13': [4]} | ['country', 'region', 'joined opec', 'population ( july 2012 )', 'area ( km square )', 'production ( bbl / day )'] | [['algeria', 'africa', '1969', '37367226', '2381740', '2125000 ( 16th )'], ['angola', 'africa', '2007', '18056072', '1246700', '1948000 ( 17th )'], ['iraq', 'middle east', '1960', '31129225', '437072', '3200000 ( 12th )'], ['kuwait', 'middle east', '1960', '2646314', '17820', '2494000 ( 10th )'], ['libya', 'africa', '1962', '5613380', '1759540', '2210000 ( 15th )'], ['nigeria', 'africa', '1971', '170123740', '923768', '2211000 ( 14th )'], ['qatar', 'middle east', '1961', '1951591', '11437', '1213000 ( 21st )'], ['saudi arabia', 'middle east', '1960', '26534504', '2149690', '8800000 ( 1st )'], ['united arab emirates', 'middle east', '1967', '5314317', '83600', '2798000 ( 8th )'], ['venezuela', 'south america', '1960', '28047938', '912050', '2472000 ( 11th )']] |
1926 world series | https://en.wikipedia.org/wiki/1926_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1332321-8.html.csv | majority | the majority of games played in the 1926 world series were in the location of yankee stadium . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'yankee stadium', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'yankee stadium'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to yankee stadium .', 'tostr': 'most_eq { all_rows ; location ; yankee stadium } = true'} | most_eq { all_rows ; location ; yankee stadium } = true | for the location records of all rows , most of them fuzzily match to yankee stadium . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'yankee stadium_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'yankee stadium_4': 'yankee stadium'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'yankee stadium_4': [0]} | ['game', 'date', 'location', 'time', 'attendance'] | [['1', 'october 2', 'yankee stadium ( i )', '1:48', '61658'], ['2', 'october 3', 'yankee stadium ( i )', '1:57', '63600'], ['3', 'october 5', "sportsman 's park ( iii )", '1:41', '37708'], ['4', 'october 6', "sportsman 's park ( iii )", '2:38', '38825'], ['5', 'october 7', "sportsman 's park ( iii )", '2:28', '39552'], ['6', 'october 9', 'yankee stadium ( i )', '2:05', '48615'], ['7', 'october 10', 'yankee stadium ( i )', '2:15', '38093']] |
united states house of representatives elections , 1972 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1972 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341707-12.html.csv | majority | the majority of georgia incumbents in the 1972 united states house of representatives elections were with the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic .', 'tostr': 'most_eq { all_rows ; party ; democratic } = true'} | most_eq { all_rows ; party ; democratic } = true | for the party records of all rows , most of them fuzzily match to democratic . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['georgia 1', 'george elliott hagan', 'democratic', '1960', 'lost renomination democratic hold', "ronald ' bo ' ginn ( d ) unopposed"], ['georgia 2', 'dawson mathis', 'democratic', '1970', 're - elected', 'dawson mathis ( d ) unopposed'], ['georgia 3', 'jack thomas brinkley', 'democratic', '1966', 're - elected', 'jack thomas brinkley ( d ) unopposed'], ['georgia 5', 'fletcher thompson', 'republican', '1966', 'retired to run for us senate democratic gain', 'andrew young ( d ) 52.8 % rodney m cook ( r ) 47.2 %'], ['georgia 6', 'john james flynt , jr', 'democratic', '1954', 're - elected', 'john james flynt , jr ( d ) unopposed'], ['georgia 7', 'john w davis', 'democratic', '1960', 're - elected', 'john w davis ( d ) 58.3 % charlie sherrill ( r ) 41.7 %'], ['georgia 9', 'phillip m landrum', 'democratic', '1952', 're - elected', 'phillip m landrum ( d ) unopposed']] |
axis & allies | https://en.wikipedia.org/wiki/Axis_%26_Allies | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-173475-1.html.csv | superlative | in axis & allies , the highest number of pieces was in the year 1981 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'pieces'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; pieces }'}, 'release'], 'result': '1981', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; pieces } ; release }'}, '1981'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; pieces } ; release } ; 1981 } = true', 'tointer': 'select the row whose pieces record of all rows is maximum . the release record of this row is 1981 .'} | eq { hop { argmax { all_rows ; pieces } ; release } ; 1981 } = true | select the row whose pieces record of all rows is maximum . the release record of this row is 1981 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'pieces_5': 5, 'release_6': 6, '1981_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'pieces_5': 'pieces', 'release_6': 'release', '1981_7': '1981'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'pieces_5': [0], 'release_6': [1], '1981_7': [2]} | ['release', 'title', 'start', 'pieces', 'board ( inches )', 'board ( cm )', 'type', 'new units new units when compared to the original a & a : classic version of the game', 'playable powers'] | [['1981', 'axis & allies ( nova games edition )', '1942', '415', '37 19 ½', '93 50', 'global', 'same as classic plus nuke pieces were cardboard', '5 : germany , japan , ussr , uk , usa'], ['1999', 'axis & allies : europe', '1941', '373', '30 20', '75 50', 'theater', 'destroyer , artillery', '4 : germany , ussr , uk , usa'], ['2004', 'axis & allies : d - day', '1944', '241', '30 20', '75 50', 'local', 'artillery , blockhouse', '3 : germany , uk , usa'], ['2006', 'axis & allies : battle of the bulge', '1944', '157', '30 20', '75 50', 'local', 'artillery , truck', '3 : germany , uk , usa'], ['2007', 'axis & allies : guadalcanal', '1942', '172', '30 20', '75 50', 'local', 'destroyer , cruiser , artillery', '2 : japan , usa']] |
united states house of representatives elections , 1940 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1940 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342270-43.html.csv | majority | all incumbents of the 1940 united states house of representatives elections were from the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'} | all_eq { all_rows ; party ; democratic } = true | for the party records of all rows , all of them fuzzily match to democratic . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) unopposed'], ['texas 2', 'martin dies , jr', 'democratic', '1930', 're - elected', 'martin dies , jr ( d ) unopposed'], ['texas 3', 'lindley beckworth', 'democratic', '1938', 're - elected', 'lindley beckworth ( d ) unopposed'], ['texas 4', 'sam rayburn', 'democratic', '1912', 're - elected', 'sam rayburn ( d ) unopposed'], ['texas 6', 'luther a johnson', 'democratic', '1922', 're - elected', 'luther a johnson ( d ) unopposed'], ['texas 7', 'nat patton', 'democratic', '1934', 're - elected', 'nat patton ( d ) 98.2 % dudley lawson ( r ) 1.8 %'], ['texas 9', 'joseph j mansfield', 'democratic', '1916', 're - elected', 'joseph j mansfield ( d ) unopposed'], ['texas 10', 'lyndon b johnson', 'democratic', '1937', 're - elected', 'lyndon b johnson ( d ) unopposed'], ['texas 11', 'william r poage', 'democratic', '1936', 're - elected', 'william r poage ( d ) unopposed'], ['texas 12', 'fritz g lanham', 'democratic', '1919', 're - elected', 'fritz g lanham ( d ) unopposed'], ['texas 13', 'ed gossett', 'democratic', '1938', 're - elected', 'ed gossett ( d ) 96.4 % louis n gould ( r ) 3.6 %'], ['texas 14', 'richard m kleberg', 'democratic', '1931', 're - elected', 'richard m kleberg ( d ) unopposed'], ['texas 15', 'milton h west', 'democratic', '1933', 're - elected', 'milton h west ( d ) 92.4 % j a simpson ( r ) 7.6 %'], ['texas 16', 'r ewing thomason', 'democratic', '1930', 're - elected', 'r ewing thomason ( d ) unopposed'], ['texas 17', 'clyde l garrett', 'democratic', '1936', 'lost renomination democratic hold', 'sam m russell ( d ) unopposed'], ['texas 19', 'george h mahon', 'democratic', '1934', 're - elected', 'george h mahon ( d ) unopposed']] |
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