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chak ting fung | https://en.wikipedia.org/wiki/Chak_Ting_Fung | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18699027-2.html.csv | count | two of the competitions took place in hong kong stadium . | {'scope': 'all', 'criterion': 'equal', 'value': 'hong kong stadium , hong kong', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'hong kong stadium , hong kong'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to hong kong stadium , hong kong .', 'tostr': 'filter_eq { all_rows ; venue ; hong kong stadium , hong kong }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; hong kong stadium , hong kong } }', 'tointer': 'select the rows whose venue record fuzzily matches to hong kong stadium , hong kong . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; hong kong stadium , hong kong } } ; 2 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to hong kong stadium , hong kong . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; venue ; hong kong stadium , hong kong } } ; 2 } = true | select the rows whose venue record fuzzily matches to hong kong stadium , hong kong . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'hong kong stadium, hong kong_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'hong kong stadium, hong kong_6': 'hong kong stadium , hong kong', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'hong kong stadium, hong kong_6': [0], '2_7': [2]} | ['date', 'venue', 'result', 'scored', 'competition'] | [['3 march 2010', 'hong kong stadium , hong kong', '0 - 0', '0', '2011 afc asian cup qualification'], ['9 october 2010', 'kaohsiung national stadium , kaohsiung', '4 - 2', '0', '2010 long teng cup'], ['10 october 2010', 'kaohsiung national stadium , kaohsiung', '4 - 0', '0', '2010 long teng cup'], ['12 october 2010', 'kaohsiung national stadium , kaohsiung', '1 - 1', '0', '2010 long teng cup'], ['23 july 2011', 'prince mohamed bin fahd stadium , dammam', '0 - 3', '0', '2014 fifa world cup qualification'], ['30 september 2011', 'kaohsiung national stadium , kaohsiung', '3 - 3', '0', '2011 long teng cup'], ['2 october 2011', 'kaohsiung national stadium , kaohsiung', '5 - 1', '0', '2011 long teng cup'], ['4 october 2011', 'kaohsiung national stadium , kaohsiung', '6 - 0', '0', '2011 long teng cup'], ['29 february 2012', 'mong kok stadium , hong kong', '5 - 1', '0', 'friendly'], ['1 june 2012', 'hong kong stadium , hong kong', '1 - 0', '0', 'friendly'], ['10 june 2012', 'mong kok stadium , hong kong', '1 - 2', '0', 'friendly'], ['15 august 2012', 'jurong west stadium , singapore', '0 - 2', '0', 'friendly']] |
reinhold roth | https://en.wikipedia.org/wiki/Reinhold_Roth | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14860855-3.html.csv | superlative | reinhold roth 's most successful year in racing was 1989 with 190 points . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '11', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'year'], 'result': '1989', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; year }'}, '1989'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; year } ; 1989 } = true', 'tointer': 'select the row whose points record of all rows is maximum . the year record of this row is 1989 .'} | eq { hop { argmax { all_rows ; points } ; year } ; 1989 } = true | select the row whose points record of all rows is maximum . the year record of this row is 1989 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'year_6': 6, '1989_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'year_6': 'year', '1989_7': '1989'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'year_6': [1], '1989_7': [2]} | ['year', 'class', 'team', 'points', 'wins'] | [['1979', '350cc', 'yamaha', '3', '0'], ['1980', '250cc', 'yamaha', '4', '0'], ['1982', '250cc', 'yamaha', '4', '0'], ['1982', '500cc', 'suzuki', '0', '0'], ['1983', '250cc', 'yamaha', '14', '0'], ['1984', '500cc', 'honda', '14', '0'], ['1985', '250cc', 'romer - juchem', '29', '0'], ['1986', '250cc', 'hb - honda', '10', '0'], ['1987', '250cc', 'hb - honda', '108', '1'], ['1988', '250cc', 'hb - honda', '158', '0'], ['1989', '250cc', 'hb - honda', '190', '2'], ['1990', '250cc', 'hb - honda', '52', '0']] |
australia at the rugby world cup | https://en.wikipedia.org/wiki/Australia_at_the_Rugby_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11942082-10.html.csv | count | a total of four of the stadiums used for the australian rugby world cup are in the state of new south wales . | {'scope': 'all', 'criterion': 'equal', 'value': 'new south wales', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'state', 'new south wales'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose state record fuzzily matches to new south wales .', 'tostr': 'filter_eq { all_rows ; state ; new south wales }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; state ; new south wales } }', 'tointer': 'select the rows whose state record fuzzily matches to new south wales . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; state ; new south wales } } ; 4 } = true', 'tointer': 'select the rows whose state record fuzzily matches to new south wales . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; state ; new south wales } } ; 4 } = true | select the rows whose state record fuzzily matches to new south wales . 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, 'state_5': 5, 'new south wales_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', 'state_5': 'state', 'new south wales_6': 'new south wales', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'state_5': [0], 'new south wales_6': [0], '4_7': [2]} | ['stadium', 'games', 'city', 'state', 'capacity', 'best crowd'] | [['telstra stadium', '7', 'sydney', 'new south wales', '83500', '82957 ( final : australia vs england )'], ['aussie stadium', '5', 'sydney', 'new south wales', '41159', '37137 ( scotland vs fiji )'], ['central coast stadium', '3', 'gosford', 'new south wales', '20119', '19653 ( japan vs united states )'], ['win stadium', '2', 'wollongong', 'new south wales', '18484', '17833 ( france vs united states )'], ['suncorp stadium', '9', 'brisbane', 'queensland', '52500', '48778 ( australia vs romania )'], ['dairy farmers stadium', '3', 'townsville', 'queensland', '24843', '21309 ( france vs japan )'], ['telstra dome', '7', 'melbourne', 'victoria', '53371', '54206 ( australia vs ireland )'], ['subiaco oval', '5', 'perth', 'western australia', '42922', '38834 ( south africa vs england )'], ['canberra stadium', '4', 'canberra', 'australian capital territory', '24647', '22641 ( italy vs wales )'], ["adelaide oval '", '2', 'adelaide', 'south australia', '33597', '33000 ( australia vs namibia )'], ['york park', '1', 'launceston', 'tasmania', '19891', '15457 ( namibia vs romania )']] |
larry davidson | https://en.wikipedia.org/wiki/Larry_Davidson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20107762-1.html.csv | aggregation | larry davidson played in an average of just over 26 games per season / . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '26.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'games'], 'result': '26.8', 'ind': 0, 'tostr': 'avg { all_rows ; games }'}, '26.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; games } ; 26.8 } = true', 'tointer': 'the average of the games record of all rows is 26.8 .'} | round_eq { avg { all_rows ; games } ; 26.8 } = true | the average of the games record of all rows is 26.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'games_4': 4, '26.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'games_4': 'games', '26.8_5': '26.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'games_4': [0], '26.8_5': [1]} | ['year', 'team', 'games', 'mins', 'fg %', '3p %', 'ft %', 'rebounds', 'assists', 'steals', 'blocks', 'points'] | [['2004 - 05', 'hunter pirates', '30', '385:33', '43.4', '34.4', '66.7', '3.2', '0.4', '0.4', '0.5', '4.0'], ['2005 - 06', 'hunter pirates', '19', '440:44', '44.9', '26.8', '71.1', '6.8', '1.1', '0.4', '0.8', '8.0'], ['2006 - 07', 'singapore slingers', '33', '650:56', '53.0', '33.3', '77.6', '4.3', '0.8', '0.3', '0.5', '6.9'], ['2007 - 08', 'wollongong hawks', '30', '744:27', '49.4', '30.9', '73.8', '7.2', '1.2', '0.6', '0.5', '10.5'], ['2008 - 09', 'wollongong hawks', '17', '328:06', '45.2', '28.6', '73.1', '4.4', '1.1', '0.6', '1.1', '6.5'], ['2009 - 10', 'wollongong hawks', '32', '849:39', '48.5', '45.1', '65.2', '6.8', '2.0', '0.7', '1.3', '9.7']] |
1987 in film | https://en.wikipedia.org/wiki/1987_in_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-171293-2.html.csv | unique | fatal attraction was the only film to gross more than 300 million dollars in 1987 . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'greater_than', 'value': '300000000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gross', '300000000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gross record is greater than 300000000 .', 'tostr': 'filter_greater { all_rows ; gross ; 300000000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; gross ; 300000000 } }', 'tointer': 'select the rows whose gross record is greater than 300000000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gross', '300000000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gross record is greater than 300000000 .', 'tostr': 'filter_greater { all_rows ; gross ; 300000000 }'}, 'title'], 'result': 'fatal attraction', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; gross ; 300000000 } ; title }'}, 'fatal attraction'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; gross ; 300000000 } ; title } ; fatal attraction }', 'tointer': 'the title record of this unqiue row is fatal attraction .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; gross ; 300000000 } } ; eq { hop { filter_greater { all_rows ; gross ; 300000000 } ; title } ; fatal attraction } } = true', 'tointer': 'select the rows whose gross record is greater than 300000000 . there is only one such row in the table . the title record of this unqiue row is fatal attraction .'} | and { only { filter_greater { all_rows ; gross ; 300000000 } } ; eq { hop { filter_greater { all_rows ; gross ; 300000000 } ; title } ; fatal attraction } } = true | select the rows whose gross record is greater than 300000000 . there is only one such row in the table . the title record of this unqiue row is fatal attraction . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'gross_7': 7, '300000000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'fatal attraction_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'gross_7': 'gross', '300000000_8': '300000000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'fatal attraction_10': 'fatal attraction'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'gross_7': [0], '300000000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'fatal attraction_10': [3]} | ['rank', 'title', 'studio', 'director', 'gross'] | [['1', 'fatal attraction', 'paramount', 'adrian lyne', '320145693'], ['2', 'beverly hills cop ii', 'paramount', 'tony scott', '299965036'], ['3', 'dirty dancing', 'vestron', 'emile ardolino', '213954274'], ['4', 'the living daylights', 'united artists', 'john glen', '191200000'], ['5', 'three men and a baby', 'touchstone', 'leonard nimoy', '167780960'], ['6', 'good morning , vietnam', 'touchstone', 'barry levinson', '123922370'], ['7', 'lethal weapon', 'warner bros', 'richard donner', '120207127'], ['8', 'the secret of my success', 'universal', 'herbert ross', '110996879'], ['9', 'predator', 'fox', 'john mctiernan', '98267558'], ['10', 'moonstruck', 'mgm', 'norman jewison', '80640528'], ['11', 'the untouchables', 'paramount', 'brian de palma', '76270454'], ['12', 'broadcast news', 'fox', 'james l brooks', '67331309'], ['13', 'dragnet', 'universal', 'tom mankiewicz', '66673516'], ['14', 'outrageous fortune', 'touchstone', 'arthur hiller', '65864741'], ['15', 'stakeout', 'touchstone', 'john badham', '65673233'], ['16', 'the witches of eastwick', 'warner bros', 'george miller', '63766510'], ['17', 'throw momma from the train', 'orion', 'danny devito', '57915972'], ['18', 'la bamba', 'columbia', 'luis valdez', '54215416'], ['19', 'robocop', 'orion', 'paul verhoeven', '53424681'], ['20', 'eddie murphy raw', 'paramount', 'robert townsend', '50505655']] |
1998 masters tournament | https://en.wikipedia.org/wiki/1998_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514546-2.html.csv | unique | josé maría olazábal was the only player from spain during the 1998 masters tournament . | {'scope': 'all', 'row': '7', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'spain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; country ; spain }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; spain } }', 'tointer': 'select the rows whose country record fuzzily matches to spain . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; country ; spain }'}, 'player'], 'result': 'josé maría olazábal', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; spain } ; player }'}, 'josé maría olazábal'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; spain } ; player } ; josé maría olazábal }', 'tointer': 'the player record of this unqiue row is josé maría olazábal .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; spain } } ; eq { hop { filter_eq { all_rows ; country ; spain } ; player } ; josé maría olazábal } } = true', 'tointer': 'select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the player record of this unqiue row is josé maría olazábal .'} | and { only { filter_eq { all_rows ; country ; spain } } ; eq { hop { filter_eq { all_rows ; country ; spain } ; player } ; josé maría olazábal } } = true | select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the player record of this unqiue row is josé maría olazábal . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'spain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'josé maría olazábal_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'spain_8': 'spain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'josé maría olazábal_10': 'josé maría olazábal'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'spain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'josé maría olazábal_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'fred couples', 'united states', '69 + 70 = 139', '- 5'], ['t1', 'david duval', 'united states', '71 + 68 = 139', '- 5'], ['3', 'scott hoch', 'united states', '70 + 71 = 141', '- 3'], ['t4', 'paul azinger', 'united states', '71 + 72 = 143', '- 1'], ['t4', 'jay haas', 'united states', '72 + 71 = 143', '- 1'], ['t4', 'phil mickelson', 'united states', '74 + 69 = 143', '- 1'], ['t4', 'josé maría olazábal', 'spain', '70 + 73 = 143', '- 1'], ['t4', 'tiger woods', 'united states', '71 + 72 = 143', '- 1'], ['t9', 'scott mccarron', 'united states', '73 + 71 = 144', 'e'], ['t9', "mark o'meara", 'united states', '74 + 70 = 144', 'e']] |
edoardo piscopo | https://en.wikipedia.org/wiki/Edoardo_Piscopo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15570607-1.html.csv | superlative | edoardo piscopo won the most times in the italian formula 3 series . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', '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', 'wins'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; wins }'}, 'series'], 'result': 'italian formula three', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; wins } ; series }'}, 'italian formula three'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; wins } ; series } ; italian formula three } = true', 'tointer': 'select the row whose wins record of all rows is maximum . the series record of this row is italian formula three .'} | eq { hop { argmax { all_rows ; wins } ; series } ; italian formula three } = true | select the row whose wins record of all rows is maximum . the series record of this row is italian formula three . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'wins_5': 5, 'series_6': 6, 'italian formula three_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'wins_5': 'wins', 'series_6': 'series', 'italian formula three_7': 'italian formula three'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'wins_5': [0], 'series_6': [1], 'italian formula three_7': [2]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'podiums', 'points', 'position'] | [['2005', 'formula bmw usa', 'eurointernational', '12', '3', '1', '5', '108', '5th'], ['2006', 'eurocup formula renault 2.0', 'cram competition', '14', '0', '0', '0', '34', '10th'], ['2006', 'formula renault 2.0 italy', 'cram competition', '12', '0', '1', '10', '216', '3rd'], ['2006 - 07', 'toyota racing series', 'mark petch motorsport', '5', '0', '0', '1', '78', '25th'], ['2007', 'formula 3 euro series', 'asl mücke motorsport', '20', '0', '0', '1', '8', '15th'], ['2007', 'masters of formula 3', 'asl mücke motorsport', '1', '0', '0', '0', 'n / a', '5th'], ['2007 - 08', 'a1 grand prix', 'a1 team italy', '14', '0', '0', '0', '12', '18th'], ['2008', 'italian formula three', 'team ghinzani', '16', '7', '8', '11', '127', '2nd'], ['2008', 'euroseries 3000', 'sighinolfi autoracing', '2', '0', '0', '2', '10', '14th'], ['2008', 'spanish formula three', 'gta motor competición', '2', '0', '0', '0', '0', 'nc'], ['2008 - 09', 'a1 grand prix', 'a1 team italy', '8', '0', '0', '0', '17', '16th'], ['2009', 'fia formula two championship', 'motorsport vision', '14', '0', '0', '0', '19', '12th'], ['2009', 'euroseries 3000', 'emmebi motorsport', '3', '0', '0', '1', '11', '9th'], ['2009 - 10', 'gp2 asia series', 'dams', '8', '0', '0', '0', '3', '16th'], ['2010', 'auto gp', 'dams', '12', '0', '0', '5', '42', '2nd'], ['2010', 'formula le mans', 'dams', '1', '0', '1', '0', '1', '15th'], ['2010', 'gp2 series', 'trident racing', '2', '0', '0', '0', '2', '26th']] |
list of tyler perry 's house of payne episodes | https://en.wikipedia.org/wiki/List_of_Tyler_Perry%27s_House_of_Payne_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11630008-5.html.csv | unique | for tyler perry 's house of payne , the only episode that was written by jd walker was the one titled guess who 's coming to dinner . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'jd walker', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'jd walker'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to jd walker .', 'tostr': 'filter_eq { all_rows ; written by ; jd walker }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; written by ; jd walker } }', 'tointer': 'select the rows whose written by record fuzzily matches to jd walker . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'jd walker'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to jd walker .', 'tostr': 'filter_eq { all_rows ; written by ; jd walker }'}, 'title'], 'result': "guess who 's coming to dinner", 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; written by ; jd walker } ; title }'}, "guess who 's coming to dinner"], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; written by ; jd walker } ; title } ; guess who 's coming to dinner }", 'tointer': "the title record of this unqiue row is guess who 's coming to dinner ."}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; written by ; jd walker } } ; eq { hop { filter_eq { all_rows ; written by ; jd walker } ; title } ; guess who 's coming to dinner } } = true", 'tointer': "select the rows whose written by record fuzzily matches to jd walker . there is only one such row in the table . the title record of this unqiue row is guess who 's coming to dinner ."} | and { only { filter_eq { all_rows ; written by ; jd walker } } ; eq { hop { filter_eq { all_rows ; written by ; jd walker } ; title } ; guess who 's coming to dinner } } = true | select the rows whose written by record fuzzily matches to jd walker . there is only one such row in the table . the title record of this unqiue row is guess who 's coming to dinner . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'written by_7': 7, 'jd walker_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, "guess who 's coming to dinner_10": 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'written by_7': 'written by', 'jd walker_8': 'jd walker', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', "guess who 's coming to dinner_10": "guess who 's coming to dinner"} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'written by_7': [0], 'jd walker_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], "guess who 's coming to dinner_10": [3]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'production code'] | [['60', '1', 'wife swap', 'tyler perry', 'kellie r griffin', 'march 5 , 2008', '301'], ['61', '2', 'stop being all funky', 'tyler perry', 'kellie r griffin , jenee v giles', 'march 5 , 2008', '302'], ['62', '3', "guess who 's coming to dinner", 'tyler perry', 'jd walker', 'march 12 , 2008', '303'], ['63', '4', 'game over', 'tyler perry', 'buddy lewis', 'march 12 , 2008', '304'], ['64', '5', 'can i get a witness', 'tyler perry', 'teri jackson', 'march 19 , 2008', '305'], ['65', '6', 'commencement day', 'tyler perry', 'steve coulter , dee wagner', 'march 19 , 2008', '306'], ['66', '7', 'a shock to the system', 'tyler perry', 'lamont ferrell', 'march 26 , 2008', '307'], ['67', '8', 'compromising position', 'tyler perry', 'christopher j moore', 'march 26 , 2008', '308'], ['68', '9', 'moral dilemma', 'tyler perry', 'joseph hampton', 'april 2 , 2008', '309'], ['69', '10', 'sex , lies and videotapes', 'tyler perry', 'pamela brewster', 'april 2 , 2008', '310'], ['70', '11', 'time to clean house', 'tyler perry', 'kellie r griffin', 'april 9 , 2008', '311'], ['71', '12', 'living with liz', 'tyler perry', 'teri jackson', 'april 9 , 2008', '312'], ['72', '13', 'beat down', 'tyler perry', 'shontell r mcclain , steve coulter & dee wagner', 'april 16 , 2008', '313'], ['73', '14', 'expectations', 'tyler perry', 'jenee v giles', 'april 16 , 2008', '314'], ['74', '15', 'cheers', 'tyler perry', 'lemelle frazier', 'april 23 , 2008', '315']] |
list of australia one day international cricket records | https://en.wikipedia.org/wiki/List_of_Australia_One_Day_International_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21100348-10.html.csv | aggregation | the average number of runs for players present in the australia one day international cricket records is around 5390 runs . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '5390', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'runs'], 'result': '5390', 'ind': 0, 'tostr': 'avg { all_rows ; runs }'}, '5390'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; runs } ; 5390 } = true', 'tointer': 'the average of the runs record of all rows is 5390 .'} | round_eq { avg { all_rows ; runs } ; 5390 } = true | the average of the runs record of all rows is 5390 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'runs_4': 4, '5390_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'runs_4': 'runs', '5390_5': '5390'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'runs_4': [0], '5390_5': [1]} | ['rank', 'average', 'player', 'runs', 'innings', 'not out', 'period'] | [['1', '56.85', 'george bailey', '1535', '33', '4', '2012 -'], ['2', '53.58', 'michael bevan', '6912', '196', '67', '1994 - 2004'], ['3', '52.53', 'adam voges', '683', '20', '7', '2007 -'], ['4', '48.15', 'mike hussey', '5442', '157', '44', '2004 - 2012'], ['5', '45.08', 'michael clarke', '7484', '209', '43', '2003 -'], ['6', '44.61', 'dean jones', '6068', '161', '25', '1984 - 1994'], ['7', '44.10', 'matthew hayden', '6131', '154', '15', '1993 - 2008'], ['8', '41.81', 'ricky ponting', '13589', '364', '39', '1995 - 2012'], ['9', '41.43', 'callum ferguson', '663', '25', '9', '2009 - 2011']] |
2007 bombardier learjet 550 | https://en.wikipedia.org/wiki/2007_Bombardier_Learjet_550 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17319931-1.html.csv | unique | jon herb was the only driver in the 2007 bombardier learjet 550 race that retired due to accident . | {'scope': 'all', 'row': '20', 'col': '6', 'col_other': '3', 'criterion': 'equal', 'value': 'accident', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time / retired ; accident }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; time / retired ; accident } }', 'tointer': 'select the rows whose time / retired record fuzzily matches to accident . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time / retired ; accident }'}, 'driver'], 'result': 'jon herb', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; time / retired ; accident } ; driver }'}, 'jon herb'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; time / retired ; accident } ; driver } ; jon herb }', 'tointer': 'the driver record of this unqiue row is jon herb .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; time / retired ; accident } } ; eq { hop { filter_eq { all_rows ; time / retired ; accident } ; driver } ; jon herb } } = true', 'tointer': 'select the rows whose time / retired record fuzzily matches to accident . there is only one such row in the table . the driver record of this unqiue row is jon herb .'} | and { only { filter_eq { all_rows ; time / retired ; accident } } ; eq { hop { filter_eq { all_rows ; time / retired ; accident } ; driver } ; jon herb } } = true | select the rows whose time / retired record fuzzily matches to accident . there is only one such row in the table . the driver record of this unqiue row is jon herb . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time / retired_7': 7, 'accident_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'jon herb_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time / retired_7': 'time / retired', 'accident_8': 'accident', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'jon herb_10': 'jon herb'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time / retired_7': [0], 'accident_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'jon herb_10': [3]} | ['fin pos', 'car no', 'driver', 'team', 'laps', 'time / retired', 'grid', 'laps led', 'points'] | [['1', '6', 'sam hornish , jr', 'team penske', '228', '1:52:15.2873', '2', '159', '50 + 3'], ['2', '11', 'tony kanaan', 'andretti green', '228', '+ 0.0786', '4', '1', '40'], ['3', '7', 'danica patrick', 'andretti green', '228', '+ 0.3844', '6', '2', '35'], ['4', '27', 'dario franchitti', 'andretti green', '228', '+ 3.9765', '3', '0', '32'], ['5', '4', 'vitor meira', 'panther racing', '228', '+ 4.0019', '13', '3', '30'], ['6', '17', 'jeff simmons', 'rahal letterman', '228', '+ 4.6340', '8', '5', '28'], ['7', '8', 'scott sharp', 'rahal letterman', '227', '+ 1 lap', '1', '0', '26'], ['8', '15', 'buddy rice', 'dreyer & reinbold racing', '225', '+ 3 laps', '16', '0', '24'], ['9', '55', 'kosuke matsuura', 'panther racing', '225', '+ 3 laps', '15', '0', '22'], ['10', '5', 'sarah fisher', 'dreyer & reinbold racing', '221', '+ 7 laps', '18', '0', '20'], ['11', '23', 'milka duno ( r )', 'samax motorsport', '221', '+ 7 laps', '19', '0', '19'], ['12', '9', 'scott dixon', 'target chip ganassi', '206', '+ 22 laps', '7', '6', '18'], ['13', '14', 'darren manning', 'aj foyt racing', '200', 'mechanical', '11', '0', '17'], ['14', '2', 'tomas scheckter', 'vision racing', '199', '+ 29 laps', '9', '0', '16'], ['15', '10', 'dan wheldon', 'target chip ganassi', '196', 'collision', '5', '52', '15'], ['16', '3', 'hãlio castroneves', 'team penske', '196', 'collision', '10', '0', '14'], ['17', '22', 'a j foyt iv', 'vision racing', '195', 'tire', '17', '0', '13'], ['18', '20', 'ed carpenter', 'vision racing', '195', 'collision', '20', '0', '12'], ['19', '26', 'marco andretti', 'andretti green', '140', 'mechanical', '12', '0', '12'], ['20', '19', 'jon herb', 'racing professionals', '44', 'accident', '14', '0', '12']] |
united states house of representatives elections , 1820 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1820 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668329-25.html.csv | unique | thomas newton , jr was the only representative first elected before 1800 . | {'scope': 'all', 'row': '12', 'col': '4', 'col_other': '2', 'criterion': 'less_than', 'value': '1800', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'first elected', '1800'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is less than 1800 .', 'tostr': 'filter_less { all_rows ; first elected ; 1800 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; first elected ; 1800 } }', 'tointer': 'select the rows whose first elected record is less than 1800 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'first elected', '1800'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is less than 1800 .', 'tostr': 'filter_less { all_rows ; first elected ; 1800 }'}, 'incumbent'], 'result': 'thomas newton , jr', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; first elected ; 1800 } ; incumbent }'}, 'thomas newton , jr'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; first elected ; 1800 } ; incumbent } ; thomas newton , jr }', 'tointer': 'the incumbent record of this unqiue row is thomas newton , jr .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; first elected ; 1800 } } ; eq { hop { filter_less { all_rows ; first elected ; 1800 } ; incumbent } ; thomas newton , jr } } = true', 'tointer': 'select the rows whose first elected record is less than 1800 . there is only one such row in the table . the incumbent record of this unqiue row is thomas newton , jr .'} | and { only { filter_less { all_rows ; first elected ; 1800 } } ; eq { hop { filter_less { all_rows ; first elected ; 1800 } ; incumbent } ; thomas newton , jr } } = true | select the rows whose first elected record is less than 1800 . there is only one such row in the table . the incumbent record of this unqiue row is thomas newton , jr . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'first elected_7': 7, '1800_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'thomas newton , jr_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'first elected_7': 'first elected', '1800_8': '1800', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'thomas newton , jr_10': 'thomas newton , jr'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'first elected_7': [0], '1800_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'thomas newton , jr_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['virginia 4', 'william mccoy', 'democratic - republican', '1811', 're - elected', 'william mccoy ( dr )'], ['virginia 5', 'john floyd', 'democratic - republican', '1817', 're - elected', 'john floyd ( dr )'], ['virginia 6', 'alexander smyth', 'democratic - republican', '1817', 're - elected', 'alexander smyth ( dr )'], ['virginia 7', 'ballard smith', 'democratic - republican', '1815', 'retired democratic - republican hold', 'william smith ( dr ) 53.2 % james wilson ( dr ) 46.8 %'], ['virginia 11', 'philip p barbour', 'democratic - republican', '1814 ( special )', 're - elected', 'philip p barbour ( dr )'], ['virginia 12', 'robert s garnett', 'democratic - republican', '1817', 're - elected', 'robert s garnett ( dr ) 100 %'], ['virginia 14', 'william a burwell', 'democratic - republican', '1806 ( special )', 'retired democratic - republican hold', 'jabez leftwich ( dr ) 93.5 % james calloway ( dr ) 6.5 %'], ['virginia 17', 'william s archer', 'democratic - republican', '1820 ( special )', 're - elected', 'william s archer ( dr ) 100 %'], ['virginia 18', 'mark alexander', 'democratic - republican', '1819', 're - elected', 'mark alexander ( dr ) 100 %'], ['virginia 19', 'james jones', 'democratic - republican', '1819', 're - elected', 'james jones ( dr )'], ['virginia 20', 'john c gray', 'democratic - republican', '1820 ( special )', 'lost re - election democratic - republican hold', 'arthur smith ( dr ) 60.3 % john c gray ( dr ) 39.7 %'], ['virginia 21', 'thomas newton , jr', 'democratic - republican', '1797', 're - elected', 'thomas newton , jr ( dr ) 94.7 % others 5.3 %'], ['virginia 22', 'hugh nelson', 'democratic - republican', '1811', 're - elected', 'hugh nelson ( dr ) 100 %']] |
united states house of representatives elections , 1986 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1986 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341586-43.html.csv | count | three of the people that were elected to serve on tennessee 's house of representatives in 1986 were democratic . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; party ; democratic } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; democratic } } ; 3 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; party ; democratic } } ; 3 } = true | select the rows whose party record fuzzily matches to democratic . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'democratic_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'democratic_6': 'democratic', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '3_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['tennessee 1', 'jimmy quillen', 'republican', '1962', 're - elected', 'jimmy quillen ( r ) 68.9 % john b russell ( d ) 31.1 %'], ['tennessee 2', 'john duncan , sr', 'republican', '1964', 're - elected', 'john duncan , sr ( r ) 76.2 % john f bowen ( d ) 23.8 %'], ['tennessee 3', 'marilyn lloyd', 'democratic', '1974', 're - elected', 'marilyn lloyd ( d ) 53.9 % jim golden ( r ) 46.1 %'], ['tennessee 4', 'jim cooper', 'democratic', '1982', 're - elected', 'jim cooper ( d ) unopposed'], ['tennessee 6', 'bart gordon', 'democratic', '1984', 're - elected', 'bart gordon ( d ) 76.8 % fred vail ( r ) 23.2 %'], ['tennessee 7', 'don sundquist', 'republican', '1982', 're - elected', 'don sundquist ( r ) 72.3 % m lloyd hiler ( d ) 27.7 %']] |
el salvador national under - 23 football team | https://en.wikipedia.org/wiki/El_Salvador_national_under-23_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13887424-4.html.csv | aggregation | el salvador national under - 23 football team scored a total of 14 goals . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '14', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '14', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '14'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 14 } = true', 'tointer': 'the sum of the score record of all rows is 14 .'} | round_eq { sum { all_rows ; score } ; 14 } = true | the sum of the score record of all rows is 14 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '14_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '14_5': '14'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '14_5': [1]} | ['date :', 'location :', 'opponent :', 'score', 'competition :'] | [['february 22 , 2012', 'san salvador , el salvador', 'puerto rico', '2 - 1', 'f'], ['march 1 , 2012', 'santa tecla , el salvador', 'santa tecla', '0 - 0', 'uf'], ['march 11 , 2012', 'germantown , united states', 'maryland terrapins', '3 - 1', 'f'], ['march 17 , 2012', 'houston , united states', 'honduras', '0 - 2', 'f'], ['march 22 , 2012', 'nashville , united states', 'canada', '0 - 0', 'oq - gs'], ['march 24 , 2012', 'nashville , united states', 'cuba', '4 - 0', 'oq - gs'], ['march 26 , 2012', 'nashville , united states', 'united states', '3 - 3', 'oq - gs'], ['march 31 , 2012', 'kansas city , united states', 'honduras', '2 - 3 ( aet )', 'oq - sf']] |
gold coast titans | https://en.wikipedia.org/wiki/Gold_Coast_Titans | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1613020-1.html.csv | majority | john cartwright was the head coach of the gold coast titans in all of their seasons . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'john cartwright', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'coach', 'john cartwright'], 'result': True, 'ind': 0, 'tointer': 'for the coach records of all rows , all of them fuzzily match to john cartwright .', 'tostr': 'all_eq { all_rows ; coach ; john cartwright } = true'} | all_eq { all_rows ; coach ; john cartwright } = true | for the coach records of all rows , all of them fuzzily match to john cartwright . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'coach_3': 3, 'john cartwright_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'coach_3': 'coach', 'john cartwright_4': 'john cartwright'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'coach_3': [0], 'john cartwright_4': [0]} | ['competition', 'ladder position', 'coach', 'captain ( s )', 'details'] | [['2007 nrl season', '12 / 16', 'john cartwright', 'luke bailey scott prince', '2007 gold coast titans season'], ['2008 nrl season', '13 / 16', 'john cartwright', 'luke bailey scott prince', '2008 gold coast titans season'], ['2009 nrl season', '3 / 16', 'john cartwright', 'luke bailey scott prince', '2009 gold coast titans season'], ['2010 nrl season', '4 / 16', 'john cartwright', 'scott prince', '2010 gold coast titans season'], ['2011 nrl season', '16 / 16', 'john cartwright', 'scott prince', '2011 gold coast titans season'], ['2012 nrl season', '11 / 16', 'john cartwright', 'scott prince', '2012 gold coast titans season'], ['2013 nrl season', '9 / 16', 'john cartwright', 'greg bird nate myles', '2013 gold coast titans season'], ['2014 nrl season', '16', 'john cartwright', 'greg bird nate myles', '2014 gold coast titans season']] |
2008 - 09 1 . ffc turbine potsdam season | https://en.wikipedia.org/wiki/2008%E2%80%9309_1._FFC_Turbine_Potsdam_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18591990-4.html.csv | aggregation | in the 2008-09 1 . ffc turbine potsdam season , when the venue is away , the average attendance is 565.33 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '565.33', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'away'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'away'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; away }', 'tointer': 'select the rows whose venue record fuzzily matches to away .'}, 'attendance'], 'result': '565.33', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; venue ; away } ; attendance }'}, '565.33'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; venue ; away } ; attendance } ; 565.33 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to away . the average of the attendance record of these rows is 565.33 .'} | round_eq { avg { filter_eq { all_rows ; venue ; away } ; attendance } ; 565.33 } = true | select the rows whose venue record fuzzily matches to away . the average of the attendance record of these rows is 565.33 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'away_6': 6, 'attendance_7': 7, '565.33_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'away_6': 'away', 'attendance_7': 'attendance', '565.33_8': '565.33'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'away_6': [0], 'attendance_7': [1], '565.33_8': [2]} | ['round', 'date', 'opponent', 'venue', 'result', 'attendance', 'report'] | [['1st', 'bye', 'bye', 'bye', 'bye', 'bye', 'bye'], ['2nd', '18 october 2008', 'tennis borussia berlin', 'away', '1:6 ( 0:2 )', '628', 'report'], ['3rd', '9 november 2008', 'mellendorfer tv', 'away', '0:5 ( 0:3 )', '468', 'report'], ['qf', '8 february 2009', 'vfl sindelfingen', 'away', '0:1 ( 0:1 )', '600', 'report'], ['sf', '13 april 2009', 'wattenscheid 09', 'home', '3:0 ( 1:0 )', '1804', 'report'], ['f', '30 may 2009', 'fcr 2001 duisburg', 'berlin', '0:7 ( 0:2 )', '20000', 'report']] |
statistics relating to enlargement of the european union | https://en.wikipedia.org/wiki/Statistics_relating_to_enlargement_of_the_European_Union | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1307842-6.html.csv | unique | austria is the only country with a gdp per capita higher than 18000 us dollars . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'greater_than', 'value': '18000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gdp per capita ( us )', '18000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gdp per capita ( us ) record is greater than 18000 .', 'tostr': 'filter_greater { all_rows ; gdp per capita ( us ) ; 18000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; gdp per capita ( us ) ; 18000 } }', 'tointer': 'select the rows whose gdp per capita ( us ) record is greater than 18000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'gdp per capita ( us )', '18000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gdp per capita ( us ) record is greater than 18000 .', 'tostr': 'filter_greater { all_rows ; gdp per capita ( us ) ; 18000 }'}, 'member countries'], 'result': 'austria', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; gdp per capita ( us ) ; 18000 } ; member countries }'}, 'austria'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; gdp per capita ( us ) ; 18000 } ; member countries } ; austria }', 'tointer': 'the member countries record of this unqiue row is austria .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; gdp per capita ( us ) ; 18000 } } ; eq { hop { filter_greater { all_rows ; gdp per capita ( us ) ; 18000 } ; member countries } ; austria } } = true', 'tointer': 'select the rows whose gdp per capita ( us ) record is greater than 18000 . there is only one such row in the table . the member countries record of this unqiue row is austria .'} | and { only { filter_greater { all_rows ; gdp per capita ( us ) ; 18000 } } ; eq { hop { filter_greater { all_rows ; gdp per capita ( us ) ; 18000 } ; member countries } ; austria } } = true | select the rows whose gdp per capita ( us ) record is greater than 18000 . there is only one such row in the table . the member countries record of this unqiue row is austria . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'gdp per capita (us)_7': 7, '18000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'member countries_9': 9, 'austria_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'gdp per capita (us)_7': 'gdp per capita ( us )', '18000_8': '18000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'member countries_9': 'member countries', 'austria_10': 'austria'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'gdp per capita (us)_7': [0], '18000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'member countries_9': [2], 'austria_10': [3]} | ['member countries', 'population', 'area ( km square )', 'gdp ( billion us )', 'gdp per capita ( us )'] | [['austria', '8206524', '83871', '145.238', '18048'], ['finland', '5261008', '338145', '80.955', '15859'], ['sweden', '9047752', '449964', '156.640', '17644'], ['accession countries', '22029977', '871980', '382.833', '17378'], ['existing members ( 1995 )', '350909402', '2495174', '5894.232', '16797'], ['eu15 ( 1995 )', '372939379 ( + 6.28 % )', '3367154 ( + 34.95 % )', '6277.065 ( + 6.50 % )', '16831 ( + 0.20 % )']] |
nasser al - attiyah | https://en.wikipedia.org/wiki/Nasser_Al-Attiyah | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12927587-5.html.csv | aggregation | stages won from 2004-2013 , during nasser al-attiyah , was a cumiltive 1.6 per year . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1.6', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'stages won'], 'result': '1.6', 'ind': 0, 'tostr': 'avg { all_rows ; stages won }'}, '1.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; stages won } ; 1.6 } = true', 'tointer': 'the average of the stages won record of all rows is 1.6 .'} | round_eq { avg { all_rows ; stages won } ; 1.6 } = true | the average of the stages won record of all rows is 1.6 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'stages won_4': 4, '1.6_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'stages won_4': 'stages won', '1.6_5': '1.6'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'stages won_4': [0], '1.6_5': [1]} | ['year', 'class', 'vehicle', 'position', 'stages won'] | [['2004', 'car', 'mitsubishi', '10', '0'], ['2005', 'car', 'bmw', 'dnf', '0'], ['2006', 'car', 'bmw', 'dnf', '0'], ['2007', 'car', 'bmw', '6', '1'], ['2008', 'event cancelled - replaced by central europe rally', 'event cancelled - replaced by central europe rally', 'event cancelled - replaced by central europe rally', 'event cancelled - replaced by central europe rally'], ['2009', 'car', 'bmw', 'dsq', '2'], ['2010', 'car', 'volkswagen', '2', '4'], ['2011', 'car', 'volkswagen', '1', '4'], ['2012', 'car', 'hummer', 'dnf', '2'], ['2013', 'car', 'demon jefferies', 'dnf', '3']] |
locomotives of the london and north eastern railway | https://en.wikipedia.org/wiki/Locomotives_of_the_London_and_North_Eastern_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1169568-2.html.csv | superlative | the 9c & 9f class had the highest number of locomotives of the london and north eastern railway . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '9', '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', 'quantity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; quantity }'}, 'class'], 'result': '9c & 9f', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; quantity } ; class }'}, '9c & 9f'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; quantity } ; class } ; 9c & 9f } = true', 'tointer': 'select the row whose quantity record of all rows is maximum . the class record of this row is 9c & 9f .'} | eq { hop { argmax { all_rows ; quantity } ; class } ; 9c & 9f } = true | select the row whose quantity record of all rows is maximum . the class record of this row is 9c & 9f . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'quantity_5': 5, 'class_6': 6, '9c & 9f_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'quantity_5': 'quantity', 'class_6': 'class', '9c & 9f_7': '9c & 9f'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'quantity_5': [0], 'class_6': [1], '9c & 9f_7': [2]} | ['class', 'type', 'quantity', 'date', 'lner class'] | [['2', '4 - 4 - 0', '25', '1887 - 1892', 'd7'], ['3', '2 - 4 - 2t', '39', '1889 - 1892', 'f1'], ['6ai', '0 - 6 - 0', '12', '1888', 'j8'], ['6d', '2 - 4 - 0', '3', '1887', 'e2'], ['6db', '4 - 4 - 0', '3', '1888', 'd8'], ['9', '0 - 6 - 0', '6', '1888 - 89', 'j13'], ['9a', '0 - 6 - 2t', '55', '1889 - 92', 'n4'], ['9b & 9e', '0 - 6 - 0', '31', '1891 - 95', 'j9'], ['9c & 9f', '0 - 6 - 2t', '129', '1891 - 1901', 'n5'], ['9d , 9h & 9 m', '0 - 6 - 0', '124', '1892 - 1902', 'j10']] |
yugoslavia national football team results | https://en.wikipedia.org/wiki/Yugoslavia_national_football_team_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14305653-40.html.csv | unique | the yugoslavia national football team only played one game in budapest , hungary . | {'scope': 'all', 'row': '11', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'budapest , hungary', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'budapest , hungary'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city record fuzzily matches to budapest , hungary .', 'tostr': 'filter_eq { all_rows ; city ; budapest , hungary }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; city ; budapest , hungary } } = true', 'tointer': 'select the rows whose city record fuzzily matches to budapest , hungary . there is only one such row in the table .'} | only { filter_eq { all_rows ; city ; budapest , hungary } } = true | select the rows whose city record fuzzily matches to budapest , hungary . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'city_4': 4, 'budapest , hungary_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'city_4': 'city', 'budapest , hungary_5': 'budapest , hungary'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'city_4': [0], 'budapest , hungary_5': [0]} | ['date', 'city', 'opponent', 'results', 'type of game'] | [['may 16', 'belgrade', 'east germany', '3:1', 'friendly'], ['may 31', 'arica , chile', 'ussr', '0:2', 'wc round 1'], ['june 2', 'arica , chile', 'uruguay', '3:1', 'wc round 1'], ['june 7', 'arica , chile', 'colombia', '5:0', 'wc round 1'], ['june 10', 'santiago , chile', 'west germany', '1:0', 'wc round 2'], ['june 13', 'vinja del mar , chile', 'czechoslovakia', '1:3', 'wc round 2'], ['june 16', 'santiago , chile', 'chile', '0:1', 'wc round 2'], ['september 16', 'leipzig , germany', 'east germany', '2:2', 'friendly'], ['september 19', 'belgrade', 'ethiopia', '5:2', 'friendly'], ['september 30', 'zagreb', 'west germany', '2:3', 'friendly'], ['october 14', 'budapest , hungary', 'hungary', '1:0', 'friendly'], ['november 4', 'belgrade', 'belgium', '3:2', "euro '64 qualifying"]] |
2006 east asian judo championships | https://en.wikipedia.org/wiki/2006_East_Asian_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18991964-3.html.csv | superlative | in the 2006 east asian judo championships , china was the nation with the highest amount of silver medals among teams that won 3 gold medals . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,3', 'subset': {'col': '3', 'criterion': 'equal', 'value': '3'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; gold ; 3 }', 'tointer': 'select the rows whose gold record is equal to 3 .'}, 'silver'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; gold ; 3 } ; silver }'}, 'nation'], 'result': 'china', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; gold ; 3 } ; silver } ; nation }'}, 'china'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; gold ; 3 } ; silver } ; nation } ; china } = true', 'tointer': 'select the rows whose gold record is equal to 3 . select the row whose silver record of these rows is maximum . the nation record of this row is china .'} | eq { hop { argmax { filter_eq { all_rows ; gold ; 3 } ; silver } ; nation } ; china } = true | select the rows whose gold record is equal to 3 . select the row whose silver record of these rows is maximum . the nation record of this row is china . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'gold_6': 6, '3_7': 7, 'silver_8': 8, 'nation_9': 9, 'china_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'gold_6': 'gold', '3_7': '3', 'silver_8': 'silver', 'nation_9': 'nation', 'china_10': 'china'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'gold_6': [0], '3_7': [0], 'silver_8': [1], 'nation_9': [2], 'china_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'japan', '6', '1', '6', '13'], ['2', 'china', '3', '4', '4', '11'], ['3', 'south korea', '3', '3', '3', '9'], ['4', 'mongolia', '1', '5', '12', '18'], ['5', 'north korea', '1', '1', '2', '4'], ['6', 'chinese taipei', '0', '0', '1', '1'], ['total', 'total', '14', '14', '28', '56']] |
2007 - 08 san antonio spurs season | https://en.wikipedia.org/wiki/2007%E2%80%9308_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963601-12.html.csv | majority | in the 2007-08 san antonio spurs season , duncan had the high rebounds every time . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'duncan', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'high rebounds', 'duncan'], 'result': True, 'ind': 0, 'tointer': 'for the high rebounds records of all rows , all of them fuzzily match to duncan .', 'tostr': 'all_eq { all_rows ; high rebounds ; duncan } = true'} | all_eq { all_rows ; high rebounds ; duncan } = true | for the high rebounds records of all rows , all of them fuzzily match to duncan . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high rebounds_3': 3, 'duncan_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high rebounds_3': 'high rebounds', 'duncan_4': 'duncan'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high rebounds_3': [0], 'duncan_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 21', 'los angeles', '85 - 89', 'duncan ( 30 )', 'duncan ( 18 )', 'parker ( 6 )', 'staples center 18997', '0 - 1'], ['2', 'may 23', 'los angeles', '71 - 101', 'parker ( 13 )', 'duncan ( 16 )', 'duncan ( 4 )', 'staples center 18997', '0 - 2'], ['3', 'may 25', 'los angeles', '103 - 84', 'ginóbili ( 30 )', 'duncan ( 21 )', 'duncan , parker ( 5 )', 'at & t center 18797', '1 - 2'], ['4', 'may 27', 'los angeles', '91 - 93', 'duncan ( 29 )', 'duncan ( 17 )', 'parker ( 9 )', 'at & t center 18797', '1 - 3'], ['5', 'may 29', 'los angeles', '92 - 100', 'parker ( 23 )', 'duncan ( 15 )', 'duncan ( 10 )', 'staples center 18997', '1 - 4']] |
wzxv | https://en.wikipedia.org/wiki/WZXV | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15493221-1.html.csv | aggregation | the average erp w for all call signs of the wzxv radio station is approximately 23 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '23', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'erp w'], 'result': '23', 'ind': 0, 'tostr': 'avg { all_rows ; erp w }'}, '23'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; erp w } ; 23 } = true', 'tointer': 'the average of the erp w record of all rows is 23 .'} | round_eq { avg { all_rows ; erp w } ; 23 } = true | the average of the erp w record of all rows is 23 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'erp w_4': 4, '23_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'erp w_4': 'erp w', '23_5': '23'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'erp w_4': [0], '23_5': [1]} | ['call sign', 'frequency mhz', 'city of license', 'facility id', 'erp w', 'height m ( ft )', 'class', 'fcc info'] | [['w227bw', '93.3', 'cheektowaga', '151267', '99', '-', 'd', 'fcc'], ['w248at', '97.5', 'corfy', '150935', '10', '-', 'd', 'fcc'], ['w248bc', '97.5', 'dansville', '86505', '10', '-', 'd', 'fcc'], ['w266be', '101.1', 'auburn', '138601', '27', '-', 'd', 'fcc'], ['w273af', '102.5', 'penn yan', '86524', '3', '-', 'd', 'fcc'], ['w275bl', '102.9', 'batavia', '150833', '29', '-', 'd', 'fcc'], ['w278ah', '103.5', 'syracuse / jamesville , new york', '81126', '10', '-', 'd', 'fcc'], ['w281at', '104.1', 'watkins glen', '151635', '10', '-', 'd', 'fcc'], ['w283au', '104.5', 'houghton', '151698', '10', '-', 'd', 'fcc']] |
1980 vfl season | https://en.wikipedia.org/wiki/1980_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809823-19.html.csv | ordinal | the game played at princes park had the 2nd largest crowd size . | {'row': '2', 'col': '6', 'order': '2', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'venue'], 'result': 'princes park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; venue }'}, 'princes park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; princes park } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is princes park .'} | eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; princes park } = true | select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is princes park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'venue_7': 7, 'princes park_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '2_6': '2', 'venue_7': 'venue', 'princes park_8': 'princes park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'venue_7': [1], 'princes park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '18.8 ( 116 )', 'footscray', '11.8 ( 74 )', 'windy hill', '16952', '9 august 1980'], ['carlton', '12.19 ( 91 )', 'richmond', '10.10 ( 70 )', 'princes park', '30051', '9 august 1980'], ['south melbourne', '12.13 ( 85 )', 'north melbourne', '11.7 ( 73 )', 'lake oval', '13681', '9 august 1980'], ['melbourne', '9.10 ( 64 )', 'hawthorn', '19.27 ( 141 )', 'mcg', '15447', '9 august 1980'], ['st kilda', '13.10 ( 88 )', 'geelong', '11.17 ( 83 )', 'moorabbin oval', '13236', '9 august 1980'], ['collingwood', '19.10 ( 124 )', 'fitzroy', '16.19 ( 115 )', 'vfl park', '31013', '9 august 1980']] |
1953 world wrestling championships | https://en.wikipedia.org/wiki/1953_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16869142-1.html.csv | superlative | in the 1953 world wrestling championships , soviet union ranks the highest . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'rank'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; rank }'}, 'nation'], 'result': 'soviet union', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; rank } ; nation }'}, 'soviet union'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; rank } ; nation } ; soviet union } = true', 'tointer': 'select the row whose rank record of all rows is minimum . the nation record of this row is soviet union .'} | eq { hop { argmin { all_rows ; rank } ; nation } ; soviet union } = true | select the row whose rank record of all rows is minimum . the nation record of this row is soviet union . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, 'nation_6': 6, 'soviet union_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'rank_5': 'rank', 'nation_6': 'nation', 'soviet union_7': 'soviet union'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], 'nation_6': [1], 'soviet union_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '5', '1', '1', '7'], ['2', 'sweden', '3', '1', '0', '4'], ['3', 'finland', '0', '2', '1', '3'], ['4', 'hungary', '0', '2', '0', '2'], ['5', 'italy', '0', '1', '3', '4'], ['6', 'turkey', '0', '1', '0', '1'], ['7', 'belgium', '0', '0', '1', '1'], ['7', 'lebanon', '0', '0', '1', '1'], ['7', 'switzerland', '0', '0', '1', '1'], ['total', 'total', '8', '8', '8', '24']] |
volleyball at the 2004 summer olympics - men 's team rosters | https://en.wikipedia.org/wiki/Volleyball_at_the_2004_Summer_Olympics_%E2%80%93_Men%27s_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15859432-3.html.csv | majority | most of the men 's volleyball players at the 2004 summer olympics were born in to 1970s . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '197', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date of birth', '197'], 'result': True, 'ind': 0, 'tointer': 'for the date of birth records of all rows , most of them fuzzily match to 197 .', 'tostr': 'most_eq { all_rows ; date of birth ; 197 } = true'} | most_eq { all_rows ; date of birth ; 197 } = true | for the date of birth records of all rows , most of them fuzzily match to 197 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date of birth_3': 3, '197_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date of birth_3': 'date of birth', '197_4': '197'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date of birth_3': [0], '197_4': [0]} | ['name', 'date of birth', 'height', 'weight', 'spike', 'block'] | [['giovane gávio', '07.09.1970', '196', '89', '340', '322'], ['andré heller', '17.12.1975', '199', '93', '339', '321'], ['mauricio lima', '27.01.1968', '184', '79', '321', '304'], ['gilberto godoy filho', '23.12.1976', '192', '85', '325', '312'], ['andré nascimento', '04.03.1979', '195', '95', '340', '320'], ['sérgio dutra santos', '15.10.1975', '184', '78', '325', '310'], ['anderson rodrigues', '21.05.1974', '190', '95', '330', '321'], ['nalbert bitencourt', '09.03.1974', '195', '82', '329', '309'], ['gustavo endres', '23.08.1975', '203', '98', '337', '325'], ['rodrigo santana', '17.04.1979', '205', '85', '350', '328'], ['ricardo garcia', '19.11.1975', '191', '89', '337', '320'], ['dante amaral', '30.09.1980', '201', '86', '345', '327']] |
united states house of representatives elections , 1942 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1942 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342256-10.html.csv | comparative | joe hendricks has a first elected year which is earlier than that of robert l f sikes . | {'row_1': '5', 'row_2': '3', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'joe hendricks'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to joe hendricks .', 'tostr': 'filter_eq { all_rows ; incumbent ; joe hendricks }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; joe hendricks } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to joe hendricks . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'robert l f sikes'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to robert l f sikes .', 'tostr': 'filter_eq { all_rows ; incumbent ; robert l f sikes }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; robert l f sikes } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to robert l f sikes . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; joe hendricks } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; robert l f sikes } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to joe hendricks . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to robert l f sikes . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; joe hendricks } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; robert l f sikes } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to joe hendricks . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to robert l f sikes . take the first elected record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'joe hendricks_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'robert l f sikes_12': 12, 'first elected_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'joe hendricks_8': 'joe hendricks', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'robert l f sikes_12': 'robert l f sikes', 'first elected_13': 'first elected'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'joe hendricks_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'robert l f sikes_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['florida 1', 'j hardin peterson', 'democratic', '1932', 're - elected', 'j hardin peterson ( d ) unopposed'], ['florida 2', 'robert a green', 'democratic', '1932', 'ran in at - large district democratic hold', 'emory h price ( d ) unopposed'], ['florida 3', 'robert l f sikes', 'democratic', '1940', 're - elected', 'robert l f sikes ( d ) unopposed'], ['florida 4', 'pat cannon', 'democratic', '1938', 're - elected', 'pat cannon ( d ) 81.4 % bert leigh acker ( r ) 18.6 %'], ['florida 5', 'joe hendricks', 'democratic', '1936', 're - elected', 'joe hendricks ( d ) 70.9 % emory akerman ( r ) 29.1 %']] |
2011 pacific games | https://en.wikipedia.org/wiki/2011_Pacific_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16777236-1.html.csv | superlative | the highest number of bronze medals won at the 2011 pacific games was the holder of rank 1 . | {'scope': 'all', 'col_superlative': '4', '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', 'bronze'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; bronze }'}, 'rank'], 'result': '1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; bronze } ; rank }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; bronze } ; rank } ; 1 } = true', 'tointer': 'select the row whose bronze record of all rows is maximum . the rank record of this row is 1 .'} | eq { hop { argmax { all_rows ; bronze } ; rank } ; 1 } = true | select the row whose bronze record of all rows is maximum . the rank record of this row is 1 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, 'rank_6': 6, '1_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', 'rank_6': 'rank', '1_7': '1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], 'rank_6': [1], '1_7': [2]} | ['rank', 'gold', 'silver', 'bronze', 'total'] | [['1', '120', '107', '61', '288'], ['2', '60', '42', '42', '144'], ['3', '48', '25', '48', '121'], ['4', '33', '44', '53', '130'], ['5', '22', '17', '34', '73'], ['6', '8', '10', '10', '28'], ['7', '4', '6', '10', '20'], ['8', '3', '0', '0', '3'], ['9', '2', '6', '4', '12'], ['10', '2', '3', '7', '12'], ['11', '1', '8', '8', '17'], ['12', '1', '6', '6', '13'], ['13', '1', '0', '0', '1'], ['14', '0', '6', '5', '11'], ['15', '0', '5', '17', '22'], ['16', '0', '3', '3', '6'], ['17', '0', '2', '1', '3'], ['18', '0', '1', '3', '4'], ['19', '0', '0', '0', '0'], ['total', '305', '291', '312', '908']] |
2006 pga championship | https://en.wikipedia.org/wiki/2006_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12475284-5.html.csv | unique | geoff ogilvy was the only player in the 2006 pga championship from australia . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'australia', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; country ; australia }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; australia } }', 'tointer': 'select the rows whose country record fuzzily matches to australia . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; country ; australia }'}, 'player'], 'result': 'geoff ogilvy', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; australia } ; player }'}, 'geoff ogilvy'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; australia } ; player } ; geoff ogilvy }', 'tointer': 'the player record of this unqiue row is geoff ogilvy .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; australia } } ; eq { hop { filter_eq { all_rows ; country ; australia } ; player } ; geoff ogilvy } } = true', 'tointer': 'select the rows whose country record fuzzily matches to australia . there is only one such row in the table . the player record of this unqiue row is geoff ogilvy .'} | and { only { filter_eq { all_rows ; country ; australia } } ; eq { hop { filter_eq { all_rows ; country ; australia } ; player } ; geoff ogilvy } } = true | select the rows whose country record fuzzily matches to australia . there is only one such row in the table . the player record of this unqiue row is geoff ogilvy . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'australia_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'geoff ogilvy_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'australia_8': 'australia', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'geoff ogilvy_10': 'geoff ogilvy'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'australia_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'geoff ogilvy_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'billy andrade', 'united states', '67 + 69 = 136', '- 8'], ['t1', 'luke donald', 'england', '68 + 68 = 136', '- 8'], ['t1', 'henrik stenson', 'sweden', '68 + 68 = 136', '- 8'], ['t1', 'tim herron', 'united states', '69 + 67 = 136', '- 8'], ['t5', 'davis love iii', 'united states', '68 + 69 = 137', '- 7'], ['t5', 'geoff ogilvy', 'australia', '69 + 68 = 137', '- 7'], ['t5', 'tiger woods', 'united states', '69 + 68 = 137', '- 7'], ['t8', 'fred funk', 'united states', '69 + 69 = 138', '- 6'], ['t8', 'billy mayfair', 'united states', '69 + 69 = 138', '- 6'], ['t8', 'chris riley', 'united states', '66 + 72 = 138', '- 6'], ['t8', 'david toms', 'united states', '71 + 67 = 138', '- 6']] |
list of asian and pacific countries by gdp ( ppp ) | https://en.wikipedia.org/wiki/List_of_Asian_and_Pacific_countries_by_GDP_%28PPP%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2248784-4.html.csv | count | of the list of asian and pacific countries by gdp 5 countries have a gdp of less than 100 thousand billion dollars . | {'scope': 'all', 'criterion': 'less_than', 'value': '100', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', '2011 gdp ( ppp ) billions of usd', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2011 gdp ( ppp ) billions of usd record is less than 100 .', 'tostr': 'filter_less { all_rows ; 2011 gdp ( ppp ) billions of usd ; 100 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; 2011 gdp ( ppp ) billions of usd ; 100 } }', 'tointer': 'select the rows whose 2011 gdp ( ppp ) billions of usd record is less than 100 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; 2011 gdp ( ppp ) billions of usd ; 100 } } ; 5 } = true', 'tointer': 'select the rows whose 2011 gdp ( ppp ) billions of usd record is less than 100 . the number of such rows is 5 .'} | eq { count { filter_less { all_rows ; 2011 gdp ( ppp ) billions of usd ; 100 } } ; 5 } = true | select the rows whose 2011 gdp ( ppp ) billions of usd record is less than 100 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, '2011 gdp (ppp) billions of usd_5': 5, '100_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', '2011 gdp (ppp) billions of usd_5': '2011 gdp ( ppp ) billions of usd', '100_6': '100', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], '2011 gdp (ppp) billions of usd_5': [0], '100_6': [0], '5_7': [2]} | ['rank mideast', 'rank asia', 'rank world', 'country', '2011 gdp ( ppp ) billions of usd'] | [['1', '6', '17', 'iran', '930.236'], ['2', '9', '23', 'saudi arabia', '677.663'], ['3', '18', '48', 'united arab emirates', '261.189'], ['4', '19', '50', 'israel', '235.446'], ['5', '21', '55', 'qatar', '181.912'], ['6', '22', '58', 'kuwait', '150.002'], ['7', '23', '60', 'iraq', '127.348'], ['8', '26', '66', 'syria', '107.803'], ['9', '29', '76', 'oman', '81.005'], ['10', '30', '83', 'yemen', '63.344'], ['11', '31', '84', 'lebanon', '61.738'], ['12', '35', '97', 'jordan', '36.897'], ['13', '37', '104', 'bahrain', '30.889']] |
imvic | https://en.wikipedia.org/wiki/IMViC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16083989-1.html.csv | count | three of the bacteria species show negative results on the citrate test . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'negative', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'citrate', 'negative'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose citrate record fuzzily matches to negative .', 'tostr': 'filter_eq { all_rows ; citrate ; negative }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; citrate ; negative } }', 'tointer': 'select the rows whose citrate record fuzzily matches to negative . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; citrate ; negative } } ; 3 } = true', 'tointer': 'select the rows whose citrate record fuzzily matches to negative . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; citrate ; negative } } ; 3 } = true | select the rows whose citrate record fuzzily matches to negative . 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, 'citrate_5': 5, 'negative_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', 'citrate_5': 'citrate', 'negative_6': 'negative', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'citrate_5': [0], 'negative_6': [0], '3_7': [2]} | ['species', 'indole', 'methyl red', 'voges - proskauer', 'citrate'] | [['escherichia coli', 'positive', 'positive', 'negative', 'negative'], ['shigella spp', 'negative', 'positive', 'negative', 'negative'], ['salmonella spp', 'negative', 'positive', 'negative', 'positive'], ['klebsiella spp', 'negative', 'negative', 'positive', 'positive'], ['proteus vulgaris', 'positive', 'positive', 'negative', 'negative'], ['proteus mirabilis', 'negative', 'positive', 'negative', 'positive'], ['enterobacter aerogenes', 'negative', 'negative', 'positive', 'positive']] |
drop dead diva ( season 1 ) | https://en.wikipedia.org/wiki/Drop_Dead_Diva_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27504682-1.html.csv | superlative | episode 8 of drop dead dives drew the highest amount of us viewers . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( millions ) }'}, 'no in series'], 'result': '8', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( millions ) } ; no in series }'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( millions ) } ; no in series } ; 8 } = true', 'tointer': 'select the row whose us viewers ( millions ) record of all rows is maximum . the no in series record of this row is 8 .'} | eq { hop { argmax { all_rows ; us viewers ( millions ) } ; no in series } ; 8 } = true | select the row whose us viewers ( millions ) record of all rows is maximum . the no in series record of this row is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, 'no in series_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (millions)_5': 'us viewers ( millions )', 'no in series_6': 'no in series', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], 'no in series_6': [1], '8_7': [2]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['1', 'pilot', 'james hayman', 'josh berman', 'july 12 , 2009', '2.8'], ['2', 'the f word', 'ron underwood', 'carla kettner & josh berman', 'july 19 , 2009', '2.46'], ['3', 'do over', 'michael lange', 'alex taub', 'july 26 , 2009', '2.80'], ['4', 'the chinese wall', 'lawrence trilling', 'thania st john', 'august 2 , 2009', 'n / a'], ['5', 'lost and found', 'david petrarca', 'jeanette collins & mimi friedman', 'august 9 , 2009', '2.44'], ['6', 'second chances', 'michael schultz', 'jeffrey lippman', 'august 16 , 2009', '3.06'], ['7', 'the magic bullet', 'jamie babbit', 'shawn schepps', 'august 23 , 2009', '2.90'], ['8', 'crazy', 'melanie mayron', 'maurissa tancharoen', 'august 30 , 2009', '3.41'], ['9', 'the dress', 'david petrarca', 'josh berman', 'september 13 , 2009', '3.08'], ['10', 'make me a match', 'matt hastings', 'thania st john', 'september 20 , 2009', '3.06'], ['11', 'what if', 'bethany rooney', 'jeanette collins & mimi friedman', 'september 27 , 2009', 'n / a'], ['12', 'dead model walking', 'ron underwood', 'amy engelberg & wendy engelberg', 'october 4 , 2009', 'n / a']] |
1991 - 92 seattle supersonics season | https://en.wikipedia.org/wiki/1991%E2%80%9392_Seattle_SuperSonics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27902171-8.html.csv | count | the seattle supersonics had 9 wins in march . | {'scope': 'all', 'criterion': 'equal', 'value': 'w', 'result': '9', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; score ; w }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; score ; w } }', 'tointer': 'select the rows whose score record fuzzily matches to w . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; score ; w } } ; 9 } = true', 'tointer': 'select the rows whose score record fuzzily matches to w . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; score ; w } } ; 9 } = true | select the rows whose score record fuzzily matches to w . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'score_5': 5, 'w_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'score_5': 'score', 'w_6': 'w', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], 'w_6': [0], '9_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['58', 'march 1', 'cleveland cavaliers', 'w 113 - 107', 'e johnson , r pierce ( 22 )', 'b benjamin , m cage ( 14 )', 'r pierce ( 6 )', 'seattle center coliseum 13647', '32 - 26'], ['59', 'march 3', 'denver nuggets', 'w 111 - 92', 's kemp ( 21 )', 's kemp ( 13 )', 'g payton ( 9 )', 'seattle center coliseum 9865', '33 - 26'], ['60', 'march 5', 'phoenix suns', 'l 105 - 118', 'r pierce ( 23 )', 's kemp ( 19 )', 'g payton ( 12 )', 'arizona veterans memorial coliseum 14496', '33 - 27'], ['61', 'march 7', 'new jersey nets', 'w 109 - 98', 'r pierce ( 27 )', 'm cage ( 13 )', 'n mcmillan ( 7 )', 'seattle center coliseum 13419', '34 - 27'], ['62', 'march 8', 'portland trail blazers', 'l 97 - 109', 'r pierce ( 28 )', 'r pierce ( 10 )', 'g payton ( 7 )', 'memorial coliseum 12888', '34 - 28'], ['63', 'march 10', 'detroit pistons', 'l 92 - 98', 'g payton ( 19 )', 's kemp ( 9 )', 'n mcmillan ( 5 )', 'seattle center coliseum 13098', '34 - 29'], ['64', 'march 11', 'los angeles clippers', 'w 104 - 96', 'r pierce ( 19 )', 'b benjamin , m cage ( 6 )', 'g payton ( 9 )', 'los angeles memorial sports arena 10912', '35 - 29'], ['65', 'march 15', 'dallas mavericks', 'w 109 - 100', 'r pierce ( 23 )', 's kemp ( 15 )', 'g payton ( 8 )', 'seattle center coliseum 12163', '36 - 29'], ['66', 'march 17', 'golden state warriors', 'l 107 - 119', 'r pierce ( 24 )', 's kemp ( 15 )', 'r pierce ( 5 )', 'seattle center coliseum 13163', '36 - 30'], ['67', 'march 19', 'houston rockets', 'w 112 - 91', 'r pierce ( 22 )', 'm cage , s kemp ( 14 )', 'g payton ( 11 )', 'the summit 15122', '37 - 30'], ['68', 'march 21', 'san antonio spurs', 'l 96 - 101', 'e johnson ( 23 )', 's kemp ( 13 )', 'd barros , m cage , n mcmillan ( 4 )', 'hemisfair arena 16057', '37 - 31'], ['69', 'march 22', 'dallas mavericks', 'w 113 - 105', 'e johnson ( 31 )', 's kemp ( 17 )', 'n mcmillan ( 8 )', 'reunion arena 14345', '38 - 31'], ['70', 'march 24', 'houston rockets', 'w 128 - 106', 'd mckey ( 23 )', 'm cage , s kemp ( 11 )', 'n mcmillan , g payton ( 7 )', 'seattle center coliseum 11377', '39 - 31'], ['71', 'march 27', 'milwaukee bucks', 'w 96 - 95', 'e johnson ( 21 )', 'n mcmillan ( 7 )', 'n mcmillan ( 6 )', 'seattle center coliseum 11450', '40 - 31'], ['72', 'march 28', 'new york knicks', 'l 87 - 92', 's kemp ( 27 )', 's kemp ( 12 )', 'n mcmillan ( 6 )', 'seattle center coliseum 14812', '40 - 32']] |
christian uflacker | https://en.wikipedia.org/wiki/Christian_Uflacker | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13044634-2.html.csv | aggregation | in all matches , christian uflacker spent an average time of 3:09 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '3:09', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '3:09', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '3:09'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 3:09 } = true', 'tointer': 'the average of the time record of all rows is 3:09 .'} | round_eq { avg { all_rows ; time } ; 3:09 } = true | the average of the time record of all rows is 3:09 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '3:09_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '3:09_5': '3:09'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '3:09_5': [1]} | ['res', 'record', 'opponent', 'method', 'round', 'time', 'location'] | [['win', '5 - 0', 'cliff wright', 'technical decision ( unanimous )', '3', '2:26', 'hammond , indiana , united states'], ['win', '4 - 0', 'lc davis', 'decision ( split )', '3', '5:00', 'valparaiso , united states'], ['win', '3 - 0', 'jonatas novaes', 'decision ( unanimous )', '3', '5:00', 'hoffman estates , illinois , united states'], ['win', '2 - 0', 'mark sinclair', 'submission ( rear naked choke )', '1', '1:22', 'hammond , indiana , united states'], ['win', '1 - 0', 'kori trussell', 'submission ( rear naked choke )', '1', '2:20', 'hammond , indiana , united states']] |
2007 - 08 belize premier football league | https://en.wikipedia.org/wiki/2007%E2%80%9308_Belize_Premier_Football_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13713206-1.html.csv | unique | santel 's was the only team to get less than 15 points . | {'scope': 'all', 'row': '9', 'col': '6', 'col_other': '2', 'criterion': 'less_than', 'value': '15', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is less than 15 .', 'tostr': 'filter_less { all_rows ; points ; 15 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; points ; 15 } }', 'tointer': 'select the rows whose points record is less than 15 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is less than 15 .', 'tostr': 'filter_less { all_rows ; points ; 15 }'}, 'club ( city / town )'], 'result': "santel 's ( santa elena )", 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; points ; 15 } ; club ( city / town ) }'}, "santel 's ( santa elena )"], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_less { all_rows ; points ; 15 } ; club ( city / town ) } ; santel 's ( santa elena ) }", 'tointer': "the club ( city / town ) record of this unqiue row is santel 's ( santa elena ) ."}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_less { all_rows ; points ; 15 } } ; eq { hop { filter_less { all_rows ; points ; 15 } ; club ( city / town ) } ; santel 's ( santa elena ) } } = true", 'tointer': "select the rows whose points record is less than 15 . there is only one such row in the table . the club ( city / town ) record of this unqiue row is santel 's ( santa elena ) ."} | and { only { filter_less { all_rows ; points ; 15 } } ; eq { hop { filter_less { all_rows ; points ; 15 } ; club ( city / town ) } ; santel 's ( santa elena ) } } = true | select the rows whose points record is less than 15 . there is only one such row in the table . the club ( city / town ) record of this unqiue row is santel 's ( santa elena ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'points_7': 7, '15_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club (city / town)_9': 9, "santel 's ( santa elena )_10": 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'points_7': 'points', '15_8': '15', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club (city / town)_9': 'club ( city / town )', "santel 's ( santa elena )_10": "santel 's ( santa elena )"} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '15_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club (city / town)_9': [2], "santel 's ( santa elena )_10": [3]} | ['position', 'club ( city / town )', 'games played', 'w - l - d', 'goals for / against', 'points'] | [['1', 'hankook verdes united ( san ignacio )', '16', '7 - 3 - 6', '26 - 17', '27'], ['2', 'fc belize ( belize city )', '16', '8 - 5 - 3', '29 - 22', '27'], ['3', 'wagiya ( dangriga )', '16', '7 - 4 - 5', '29 - 24', '26'], ['4', 'defence force ( belize city )', '16', '6 - 2 - 8', '18 - 14', '26'], ['5', 'san pedro dolphins ( san pedro town )', '16', '6 - 4 - 6', '20 - 18', '24'], ['6', 'georgetown ibayani ( independence )', '16', '5 - 7 - 4', '28 - 32', '19'], ['7', 'juventus ( orange walk , belize )', '16', '5 - 9 - 2', '31 - 32', '17'], ['8', 'revolutionary conquerors ( dangriga )', '16', '3 - 7 - 6', '25 - 32', '15'], ['9', "santel 's ( santa elena )", '16', '4 - 10 - 2', '16 - 31', '14']] |
1963 vfl season | https://en.wikipedia.org/wiki/1963_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10783853-7.html.csv | superlative | of the 1963 vfl matches in which the away team scored 9.12 ( 66 ) , the largest crowd was 29374 . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': '9.12 ( 66 )'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team score', '9.12 ( 66 )'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; away team score ; 9.12 ( 66 ) }', 'tointer': 'select the rows whose away team score record fuzzily matches to 9.12 ( 66 ) .'}, 'crowd'], 'result': '29374', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; away team score ; 9.12 ( 66 ) } ; crowd }', 'tointer': 'select the rows whose away team score record fuzzily matches to 9.12 ( 66 ) . the maximum crowd record of these rows is 29374 .'}, '29374'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; away team score ; 9.12 ( 66 ) } ; crowd } ; 29374 } = true', 'tointer': 'select the rows whose away team score record fuzzily matches to 9.12 ( 66 ) . the maximum crowd record of these rows is 29374 .'} | eq { max { filter_eq { all_rows ; away team score ; 9.12 ( 66 ) } ; crowd } ; 29374 } = true | select the rows whose away team score record fuzzily matches to 9.12 ( 66 ) . the maximum crowd record of these rows is 29374 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'away team score_5': 5, '9.12 (66)_6': 6, 'crowd_7': 7, '29374_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'away team score_5': 'away team score', '9.12 (66)_6': '9.12 ( 66 )', 'crowd_7': 'crowd', '29374_8': '29374'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'away team score_5': [0], '9.12 (66)_6': [0], 'crowd_7': [1], '29374_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '8.10 ( 58 )', 'st kilda', '9.12 ( 66 )', 'arden street oval', '17125', '1 june 1963'], ['geelong', '9.12 ( 66 )', 'hawthorn', '9.12 ( 66 )', 'kardinia park', '29374', '1 june 1963'], ['collingwood', '10.11 ( 71 )', 'essendon', '13.9 ( 87 )', 'victoria park', '44501', '1 june 1963'], ['south melbourne', '11.8 ( 74 )', 'melbourne', '8.22 ( 70 )', 'lake oval', '17160', '1 june 1963'], ['richmond', '17.13 ( 115 )', 'fitzroy', '13.8 ( 86 )', 'punt road oval', '16500', '1 june 1963'], ['footscray', '7.7 ( 49 )', 'carlton', '8.9 ( 57 )', 'western oval', '26107', '1 june 1963']] |
1954 masters tournament | https://en.wikipedia.org/wiki/1954_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13081314-4.html.csv | aggregation | in the 1954 masters tournament , for players that were n't in 1st place , the average number of strokes to par was 4 . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '4', 'subset': {'col': '1', 'criterion': 'not_equal', 'value': 't1'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'place', 't1'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; place ; t1 }', 'tointer': 'select the rows whose place record does not match to t1 .'}, 'to par'], 'result': '4', 'ind': 1, 'tostr': 'avg { filter_not_eq { all_rows ; place ; t1 } ; to par }'}, '4'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_not_eq { all_rows ; place ; t1 } ; to par } ; 4 } = true', 'tointer': 'select the rows whose place record does not match to t1 . the average of the to par record of these rows is 4 .'} | round_eq { avg { filter_not_eq { all_rows ; place ; t1 } ; to par } ; 4 } = true | select the rows whose place record does not match to t1 . the average of the to par record of these rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'place_5': 5, 't1_6': 6, 'to par_7': 7, '4_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'place_5': 'place', 't1_6': 't1', 'to par_7': 'to par', '4_8': '4'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'place_5': [0], 't1_6': [0], 'to par_7': [1], '4_8': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'sam snead', 'united states', '74 + 73 + 70 + 72 = 289', '+ 1', 'playoff'], ['t1', 'ben hogan', 'united states', '72 + 73 + 69 + 75 = 289', '+ 1', 'playoff'], ['3', 'billy joe patton ( a )', 'united states', '70 + 74 + 75 + 71 = 290', '+ 2', '0'], ['t4', 'ej dutch harrison', 'united states', '70 + 79 + 74 + 68 = 291', '+ 3', '1937'], ['t4', 'lloyd mangrum', 'united states', '71 + 75 + 76 + 69 = 291', '+ 3', '1937'], ['t6', 'jerry barber', 'united states', '74 + 76 + 71 + 71 = 292', '+ 4', '1041'], ['t6', 'jack burke , jr', 'united states', '71 + 77 + 73 + 71 = 292', '+ 4', '1041'], ['t6', 'bob rosburg', 'united states', '73 + 73 + 76 + 70 = 292', '+ 4', '1041'], ['t9', 'al besselink', 'united states', '74 + 74 + 74 + 72 = 294', '+ 6', '781'], ['t9', 'cary middlecoff', 'united states', '73 + 76 + 70 + 75 = 294', '+ 6', '781']] |
1992 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1992_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11465246-2.html.csv | unique | week 6 of the 1992 tampa bay buccaneers season was the only week in which a game was not played . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '-', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to - .', 'tostr': 'filter_eq { all_rows ; date ; - }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; - } }', 'tointer': 'select the rows whose date record is equal to - . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to - .', 'tostr': 'filter_eq { all_rows ; date ; - }'}, 'week'], 'result': '6', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; - } ; week }'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 6 }', 'tointer': 'the week record of this unqiue row is 6 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date ; - } } ; eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 6 } } = true', 'tointer': 'select the rows whose date record is equal to - . there is only one such row in the table . the week record of this unqiue row is 6 .'} | and { only { filter_eq { all_rows ; date ; - } } ; eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 6 } } = true | select the rows whose date record is equal to - . there is only one such row in the table . the week record of this unqiue row is 6 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '-_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'week_9': 9, '6_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '-_8': '-', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'week_9': 'week', '6_10': '6'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'date_7': [0], '-_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'week_9': [2], '6_10': [3]} | ['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'] | [['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'], ['1', 'september 6 , 1992', 'phoenix cardinals', 'w 23 - 7', '4:00', 'tampa stadium', '41315', '1 - 0'], ['2', 'september 13 , 1992', 'green bay packers', 'w 31 - 3', '1:00', 'tampa stadium', '50051', '2 - 0'], ['3', 'september 20 , 1992', 'minnesota vikings', 'l 26 - 20', '1:00', 'hubert h humphrey metrodome', '48113', '2 - 1'], ['4', 'september 27 , 1992', 'detroit lions', 'w 27 - 23', '1:00', 'pontiac silverdome', '51374', '3 - 1'], ['5', 'october 4 , 1992', 'indianapolis colts', 'l 24 - 14', '1:00', 'tampa stadium', '56585', '3 - 2'], ['6', '-', '-', '-', '-', '-', '-', ''], ['7', 'october 18 , 1992', 'chicago bears', 'l 31 - 14', '1:00', 'soldier field', '61412', '3 - 3'], ['8', 'october 25 , 1992', 'detroit lions', 'l 38 - 7', '1:00', 'tampa stadium', '53995', '3 - 4'], ['9', 'november 1 , 1992', 'new orleans saints', 'l 23 - 21', '1:00', 'louisiana superdome', '68591', '3 - 5'], ['10', 'november 8 , 1992', 'minnesota vikings', 'l 35 - 7', '1:00', 'tampa stadium', '49095', '3 - 6'], ['11', 'november 15 , 1992', 'chicago bears', 'w 20 - 17', '4:00', 'tampa stadium', '69102', '4 - 6'], ['12', 'november 22 , 1992', 'san diego chargers', 'l 29 - 14', '4:00', 'jack murphy stadium', '43197', '4 - 7'], ['13', 'november 29 , 1992', 'green bay packers', 'l 19 - 14', '1:00', 'milwaukee county stadium', '52347', '4 - 8'], ['14', 'december 6 , 1992', 'los angeles rams', 'l 31 - 27', '1:00', 'tampa stadium', '38387', '4 - 9'], ['15', 'december 13 , 1992', 'atlanta falcons', 'l 35 - 7', '1:00', 'tampa stadium', '39056', '4 - 10'], ['16', 'december 19 , 1992', 'san francisco 49ers', 'l 21 - 14', '4:00', 'candlestick park', '60519', '4 - 11'], ['17', 'december 27 , 1992', 'phoenix cardinals', 'w 7 - 3', '5:00', 'sun devil stadium', '29645', '5 - 11']] |
libertine ( song ) | https://en.wikipedia.org/wiki/Libertine_%28song%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15204733-2.html.csv | majority | the most versions of libertine were released in 1986 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1986', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'year', '1986'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are equal to 1986 .', 'tostr': 'most_eq { all_rows ; year ; 1986 } = true'} | most_eq { all_rows ; year ; 1986 } = true | for the year records of all rows , most of them are equal to 1986 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '1986_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '1986_4': '1986'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '1986_4': [0]} | ['version', 'length', 'album', 'remixed by', 'year'] | [['album version', '3:49', 'cendres de lune', 'laurent boutonnat', '1986'], ['single version', '3:30', '-', '-', '1986'], ['long version', '4:30', '-', 'laurent boutonnat', '1986'], ['instrumental', '3:31', 'les clips , music videos i', '-', '1986'], ['remix', '4:35', '-', 'laurent boutonnat', '1986'], ['new remix', '3:35', '-', 'thierry rogen', '1986'], ['soundtrack from the video', '3:22', 'les clips , music videos i', '-', '1986'], ['remix special club', '5:53', 'cendres de lune', 'laurent boutonnat', '1986'], ['live version ( recorded in 1989 )', '12:00', 'en concert', '-', '1989'], ['carnal sins remix', '7:00', 'dance remixes', 'laurent boutonnat', '1992'], ['live version ( recorded in 1996 )', '5:40', 'live à bercy', '-', '1996'], ['live version ( recorded in 2000 )', '0:30', 'mylenium tour', '-', '2000'], ['album version', '3:30', 'les mots', 'laurent boutonnat', '2001'], ['y - front remix', '4:02', 'remixes', 'y - front', '2003'], ['live version ( recorded in 2009 )', '5:35', 'n degree5 on tour', '-', '2009']] |
2008 primera división de méxico apertura | https://en.wikipedia.org/wiki/2008_Primera_Divisi%C3%B3n_de_M%C3%A9xico_Apertura | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17329364-2.html.csv | comparative | darío franco was hired earlier than octavio becerril in the 2008 primera división de méxico apertura . | {'row_1': '3', 'row_2': '6', 'col': '6', 'col_other': '5', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incoming manager', 'darío franco'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incoming manager record fuzzily matches to darío franco .', 'tostr': 'filter_eq { all_rows ; incoming manager ; darío franco }'}, 'date hired'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incoming manager ; darío franco } ; date hired }', 'tointer': 'select the rows whose incoming manager record fuzzily matches to darío franco . take the date hired record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incoming manager', 'octavio becerril'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incoming manager record fuzzily matches to octavio becerril .', 'tostr': 'filter_eq { all_rows ; incoming manager ; octavio becerril }'}, 'date hired'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incoming manager ; octavio becerril } ; date hired }', 'tointer': 'select the rows whose incoming manager record fuzzily matches to octavio becerril . take the date hired record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incoming manager ; darío franco } ; date hired } ; hop { filter_eq { all_rows ; incoming manager ; octavio becerril } ; date hired } } = true', 'tointer': 'select the rows whose incoming manager record fuzzily matches to darío franco . take the date hired record of this row . select the rows whose incoming manager record fuzzily matches to octavio becerril . take the date hired record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incoming manager ; darío franco } ; date hired } ; hop { filter_eq { all_rows ; incoming manager ; octavio becerril } ; date hired } } = true | select the rows whose incoming manager record fuzzily matches to darío franco . take the date hired record of this row . select the rows whose incoming manager record fuzzily matches to octavio becerril . take the date hired 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, 'incoming manager_7': 7, 'darío franco_8': 8, 'date hired_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incoming manager_11': 11, 'octavio becerril_12': 12, 'date hired_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', 'incoming manager_7': 'incoming manager', 'darío franco_8': 'darío franco', 'date hired_9': 'date hired', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incoming manager_11': 'incoming manager', 'octavio becerril_12': 'octavio becerril', 'date hired_13': 'date hired'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incoming manager_7': [0], 'darío franco_8': [0], 'date hired_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incoming manager_11': [1], 'octavio becerril_12': [1], 'date hired_13': [3]} | ['team', 'outgoing manager', 'manner of departure', 'date of departure', 'incoming manager', 'date hired', 'position in table'] | [['ciudad juárez', 'sergio orduña', 'sacked', 'aug 18 , 2008', 'héctor eugui', 'aug 19 , 2008', '18th'], ['uag', 'josé trejo', 'sacked', 'sep 1 , 2008', 'miguel herrera', 'sep 2 , 2008', '8th'], ['atlas', 'miguel brindisi', 'resigned', 'sep 4 , 2008', 'darío franco', 'sep 5 , 2008', '17th'], ['puebla', 'josé sánchez', 'sacked', 'sep 17 , 2008', 'mario carrillo', 'sep 17 , 2008', '16th'], ['chiapas', 'sergio almaguer', 'sacked', 'oct 1 , 2008', 'francisco avilán', 'oct 1 , 2008', '18th'], ['necaxa', 'salvador reyes', 'sacked', 'oct 13 , 2008', 'octavio becerril', 'oct 14 , 2008', '18th']] |
junior assunção | https://en.wikipedia.org/wiki/Junior_Assun%C3%A7%C3%A3o | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17441410-2.html.csv | comparative | junior assunção 's fight with andrew chappelle lasted more rounds than his fight with danny payne . | {'row_1': '19', 'row_2': '17', 'col': '6', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'andrew chappelle'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to andrew chappelle .', 'tostr': 'filter_eq { all_rows ; opponent ; andrew chappelle }'}, 'round'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; andrew chappelle } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to andrew chappelle . take the round record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'danny payne'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to danny payne .', 'tostr': 'filter_eq { all_rows ; opponent ; danny payne }'}, 'round'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; danny payne } ; round }', 'tointer': 'select the rows whose opponent record fuzzily matches to danny payne . take the round record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; andrew chappelle } ; round } ; hop { filter_eq { all_rows ; opponent ; danny payne } ; round } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to andrew chappelle . take the round record of this row . select the rows whose opponent record fuzzily matches to danny payne . take the round record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; andrew chappelle } ; round } ; hop { filter_eq { all_rows ; opponent ; danny payne } ; round } } = true | select the rows whose opponent record fuzzily matches to andrew chappelle . take the round record of this row . select the rows whose opponent record fuzzily matches to danny payne . take the round record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'andrew chappelle_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'danny payne_12': 12, 'round_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'andrew chappelle_8': 'andrew chappelle', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'danny payne_12': 'danny payne', 'round_13': 'round'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'andrew chappelle_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'danny payne_12': [1], 'round_13': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '14 - 5', 'guilherme faria de souza', 'submission ( kimura )', 'premium fight championship 2', '4', '2:05', 'campinas , sao paulo , brazil'], ['loss', '13 - 5', 'ross pearson', 'decision ( unanimous )', 'ufc 141', '3', '5:00', 'las vegas , nevada , united states'], ['win', '13 - 4', 'eddie yagin', 'decision ( unanimous )', 'ufc 135', '3', '5:00', 'denver , colorado , united states'], ['win', '12 - 4', 'wesley murch', 'submission ( rear naked choke )', 'recife fc 4', '1', '5:00', 'recife , brazil'], ['win', '11 - 4', 'mark miller', 'ko ( punch )', 'recife fc 3', '1', '4:03', 'recife , brazil'], ['win', '10 - 4', 'john mahlow', 'submission ( guillotine choke )', 'xfc 10 : night of champions', '1', '4:02', 'florida , united states'], ['win', '9 - 4', 'pete grimes', 'decision ( split )', 'shinefights 2', '3', '5:00', 'florida , united states'], ['win', '8 - 4', 'kamrin naville', 'decision ( unanimous )', 'kotc - invincible', '3', '3:00', 'georgia , united states'], ['win', '7 - 4', 'kalvin hackney', 'decision ( unanimous )', "wild bill 's full throttle", '3', '5:00', 'georgia , united states'], ['loss', '6 - 4', 'torrance taylor', 'decision ( unanimous )', 'afl - bulletproof', '3', '5:00', 'georgia , united states'], ['win', '6 - 3', 'steve sharp', 'submission ( guillotine choke )', 'afl : erupption', '3', '4:26', 'kentucky , united states'], ['loss', '5 - 3', 'nate diaz', 'submission ( guillotine choke )', 'ufc fight night 11', '1', '4:10', 'nevada , united states'], ['win', '5 - 2', 'david lee', 'submission ( rear naked choke )', 'ufc 70', '2', '1:55', 'manchester , england'], ['loss', '4 - 2', 'kurt pellegrino', 'submission ( rear naked choke )', 'ufc 64', '1', '2:04', 'nevada , united states'], ['win', '4 - 1', 'scott hope', 'tko ( punches )', 'iscf - knuckle up 4', '1', '1:43', 'georgia , united states'], ['win', '3 - 1', 'dustin hazelett', 'tko ( punches )', 'ft 3 - full throttle 3', '1', '4:27', 'georgia , united states'], ['win', '2 - 1', 'danny payne', 'submission ( rear naked choke )', 'ft 2 - full throttle 2', '1', '0:50', 'georgia , united states'], ['win', '1 - 1', 'will bradford', 'submission ( guillotine choke )', 'iscf - compound fracture 2', '1', '1:55', 'georgia , united states'], ['loss', '0 - 1', 'andrew chappelle', 'decision ( unanimous )', 'iscf - fight party', '3', '3:00', 'georgia , united states']] |
fai world grand prix 2008 | https://en.wikipedia.org/wiki/FAI_World_Grand_Prix_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277703-7.html.csv | majority | all pilots covered a distance of 240.5 km in the 2008 fai world grand prix . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '240.5 km', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'distance', '240.5 km'], 'result': True, 'ind': 0, 'tointer': 'for the distance records of all rows , all of them fuzzily match to 240.5 km .', 'tostr': 'all_eq { all_rows ; distance ; 240.5 km } = true'} | all_eq { all_rows ; distance ; 240.5 km } = true | for the distance records of all rows , all of them fuzzily match to 240.5 km . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'distance_3': 3, '240.5 km_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'distance_3': 'distance', '240.5 km_4': '240.5 km'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'distance_3': [0], '240.5 km_4': [0]} | ['position', 'pilot', 'glider', 'speed', 'distance'] | [['1', 'mario kiessling', 'ventus 2ax', '128.8 km / h', '240.5 km'], ['2', 'uli schwenk', 'ventus 2ax', '128.1 km / h', '240.5 km'], ['3', 'carlos rocca vidal', 'ventus 2b', '127.6 km / h', '240.5 km'], ['4', 'sebastian kawa', 'diana 2', '127.1 km / h', '240.5 km'], ['5', 'thomas gostner', 'diana 2', '126.3 km / h', '240.5 km'], ['6', 'graham parker', 'asg 29', '125.7 km / h', '240.5 km'], ['7', 'tilo holighaus', 'ventus 2ax', '125.3 km / h', '240.5 km'], ['8', 'wolfgang janowitsch', 'ventus 2cax', '124.2 km / h', '240.5 km'], ['9', 'heimo demmerer', 'ventus 2b', '124.1 km / h', '240.5 km'], ['10', 'eduard supersperger', 'ventus 2b', '124.0 km / h', '240.5 km'], ['10', 'stanislaw wujczak', 'asg 29', '123.9 km / h', '240.5 km'], ['10', 'petr krejcirik', 'ventus 2ax', '121.4 km / h', '240.5 km'], ['10', 'rene vidal', 'ventus 2c', '117.1 km / h', '240.5 km'], ['10', 'patrick puskeiler', 'discus 2ax', '111.1 km / h', '240.5 km'], ['10', 'olli teronen', 'asg 29', '95 km / h', '240.5 km']] |
provinces of korea | https://en.wikipedia.org/wiki/Provinces_of_Korea | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-160510-5.html.csv | comparative | the korean province of gangwon has a greater area than the province of jeju . | {'row_1': '3', 'row_2': '13', 'col': '6', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rr romaja', 'gangwon'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rr romaja record fuzzily matches to gangwon .', 'tostr': 'filter_eq { all_rows ; rr romaja ; gangwon }'}, 'area'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; rr romaja ; gangwon } ; area }', 'tointer': 'select the rows whose rr romaja record fuzzily matches to gangwon . take the area record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rr romaja', 'jeju'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rr romaja record fuzzily matches to jeju .', 'tostr': 'filter_eq { all_rows ; rr romaja ; jeju }'}, 'area'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; rr romaja ; jeju } ; area }', 'tointer': 'select the rows whose rr romaja record fuzzily matches to jeju . take the area record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; rr romaja ; gangwon } ; area } ; hop { filter_eq { all_rows ; rr romaja ; jeju } ; area } } = true', 'tointer': 'select the rows whose rr romaja record fuzzily matches to gangwon . take the area record of this row . select the rows whose rr romaja record fuzzily matches to jeju . take the area record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; rr romaja ; gangwon } ; area } ; hop { filter_eq { all_rows ; rr romaja ; jeju } ; area } } = true | select the rows whose rr romaja record fuzzily matches to gangwon . take the area record of this row . select the rows whose rr romaja record fuzzily matches to jeju . take the area 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, 'rr romaja_7': 7, 'gangwon_8': 8, 'area_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'rr romaja_11': 11, 'jeju_12': 12, 'area_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', 'rr romaja_7': 'rr romaja', 'gangwon_8': 'gangwon', 'area_9': 'area', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'rr romaja_11': 'rr romaja', 'jeju_12': 'jeju', 'area_13': 'area'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'rr romaja_7': [0], 'gangwon_8': [0], 'area_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'rr romaja_11': [1], 'jeju_12': [1], 'area_13': [3]} | ['rr romaja', 'm - r romaja', 'hangul / chosongul', 'hanja', 'iso', 'area', 'capital', 'region', 'country'] | [['chungcheongbuk', "ch ' ungch ' ŏngbuk", '충청북도', '忠清北道', 'kr - 43', '7436', 'cheongju', 'hoseo', 'south korea'], ['chungcheongnam', "ch ' ungch ' ŏngnam", '충청남도', '忠清南道', 'kr - 44', '8352', 'hongseong', 'hoseo', 'south korea'], ['gangwon', 'kangwŏn', '강원도', '江原道', 'kr - 44', '16894', 'chuncheon', 'gwandong', 'south korea'], ['gangwon', 'kangwŏn', '강원도', '江原道', 'kp - 07', '11091', 'wonsan', 'gwandong', 'north korea'], ['gyeonggi', 'kyŏnggi', '경기도', '京畿道', 'kr - 41', '10131', 'suwon', 'sudogwon', 'south korea'], ['gyeongsangbuk', 'kyŏngsangbuk', '경상북도', '慶尙北道', 'kr - 47', '19440', 'daegu', 'yeongnam', 'south korea'], ['gyeongsangnam', 'kyŏngsangnam', '경상남도', '慶尙南道', 'kr - 48', '11859', 'changwon', 'yeongnam', 'south korea'], ['hamgyeongbuk', 'hamgyŏngbuk', '함경북도', '咸鏡北道', 'kp - 09', '15980', 'chongjin', 'kwanbuk', 'north korea'], ['hamgyeongnam', 'hamgyŏngnam', '함경남도', '咸鏡南道', 'kp - 08', '18534', 'hamhung', 'kwannam', 'north korea'], ['hwanghaebuk', 'hwanghaebuk', '황해북도', '黃海北道', 'kp - 06', '8154', 'sariwon', 'haeso', 'north korea'], ['hwanghaenam', 'hwanghaenam', '황해남도', '黃海南道', 'kp - 05', '8450', 'sariwon', 'haeso', 'north korea'], ['jagang', 'chagang', '자강도', '慈江道', 'kp - 04', '16765', 'kanggye', 'kwanso', 'north korea'], ['jeju', 'cheju', '제주도', '濟州道', 'kr - 49', '1846', 'jeju city', 'jejudo', 'south korea'], ['jeollabuk', 'chŏllabuk', '전라북도', '全羅北道', 'kr - 45', '8043', 'jeonju', 'honam', 'south korea'], ['jeollanam', 'chŏllanam', '전라남도', '全羅南道', 'kr - 46', '11858', 'muan', 'honam', 'south korea'], ['pyeonganbuk', "p ' yŏnganbuk", '평안북도', '平安北道', 'kp - 03', '12680', 'sinuiju', 'kwanso', 'north korea'], ['pyeongannam', "p ' yŏngannam", '평안남도', '平安南道', 'kp - 02', '11891', 'pyongsong', 'kwanso', 'north korea']] |
sligo rovers f.c | https://en.wikipedia.org/wiki/Sligo_Rovers_F.C. | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1234607-3.html.csv | ordinal | sligo rovers f.c 's player that scored second highest number of goals was from ireland . | {'scope': 'all', 'row': '2', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'goals', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; goals ; 2 }'}, 'nationality'], 'result': 'ireland', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; goals ; 2 } ; nationality }'}, 'ireland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; goals ; 2 } ; nationality } ; ireland } = true', 'tointer': 'select the row whose goals record of all rows is 2nd maximum . the nationality record of this row is ireland .'} | eq { hop { nth_argmax { all_rows ; goals ; 2 } ; nationality } ; ireland } = true | select the row whose goals record of all rows is 2nd maximum . the nationality record of this row is ireland . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'goals_5': 5, '2_6': 6, 'nationality_7': 7, 'ireland_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', 'goals_5': 'goals', '2_6': '2', 'nationality_7': 'nationality', 'ireland_8': 'ireland'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'goals_5': [0], '2_6': [0], 'nationality_7': [1], 'ireland_8': [2]} | ['ranking', 'nationality', 'name', 'years', 'goals'] | [['1', 'scotland', 'johnny armstrong', '1952 - 1964', '83'], ['2', 'ireland', 'padraig moran', '1993 - 2001', '62'], ['3', 'ireland', 'paul mctiernan', '2002 - 2006 & 2008 - 2009', '50'], ['4', 'england', 'gary hulmes', '1977 - 79 & 1980 & 1987', '50'], ['5', 'ireland', 'paul mcgee', '1971 - 72 & 1976 - 1978 & 1984 & 1991 - 93', '50'], ['6', 'ireland', 'raffaele cretaro', '2001 - 2005 & 2007 - 2009 & 2011 -', '50'], ['7', 'ireland', 'gerry mitchell', '1961 - 1975', '46'], ['8', 'ireland', 'brendan bradley', '1980 - 1982', '44'], ['9', 'ireland', 'harry mcloughlin', '1978 - 1988', '36'], ['10', 'england', 'harry litherland', '1937 - 1938', '33']] |
2010 world rally championship season | https://en.wikipedia.org/wiki/2010_World_Rally_Championship_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18812209-20.html.csv | superlative | citroën total world rally team had the highest number of stage wins in the 2010 world rally championship season . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'wins'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; wins }'}, 'constructor'], 'result': 'citroën total world rally team', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; wins } ; constructor }'}, 'citroën total world rally team'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; wins } ; constructor } ; citroën total world rally team } = true', 'tointer': 'select the row whose wins record of all rows is maximum . the constructor record of this row is citroën total world rally team .'} | eq { hop { argmax { all_rows ; wins } ; constructor } ; citroën total world rally team } = true | select the row whose wins record of all rows is maximum . the constructor record of this row is citroën total world rally team . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'wins_5': 5, 'constructor_6': 6, 'citroën total world rally team_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'wins_5': 'wins', 'constructor_6': 'constructor', 'citroën total world rally team_7': 'citroën total world rally team'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'wins_5': [0], 'constructor_6': [1], 'citroën total world rally team_7': [2]} | ['constructor', 'chassis', 'starts', 'finishes', 'wins', 'podiums', 'stage wins', 'points'] | [['citroën total world rally team', 'c4 wrc', '26', '24', '9', '19', '127', '456'], ['bp ford world rally team', 'focus rs wrc 08 and 09', '34', '28', '3', '8', '39', '337'], ['citroën junior team', 'c4 wrc', '23', '20', '1', '4', '26', '217'], ['stobart m - sport ford rally team', 'focus rs wrc 08', '31', '27', '0', '0', '2', '176'], ["munchi 's ford world rally team", 'focus rs wrc 08', '8', '8', '0', '0', '1', '58']] |
swiss locomotive and machine works | https://en.wikipedia.org/wiki/Swiss_Locomotive_and_Machine_Works | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1562368-2.html.csv | count | two of these locamotives were built in 1923 . | {'scope': 'all', 'criterion': 'equal', 'value': '1923', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'built', '1923'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose built record is equal to 1923 .', 'tostr': 'filter_eq { all_rows ; built ; 1923 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; built ; 1923 } }', 'tointer': 'select the rows whose built record is equal to 1923 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; built ; 1923 } } ; 2 } = true', 'tointer': 'select the rows whose built record is equal to 1923 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; built ; 1923 } } ; 2 } = true | select the rows whose built record is equal to 1923 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'built_5': 5, '1923_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'built_5': 'built', '1923_6': '1923', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'built_5': [0], '1923_6': [0], '2_7': [2]} | ['built', 'number', 'type', 'slm number', 'wheel arrangement', 'location', 'notes'] | [['1895', '1', 'mountain railway rack steam locomotive', '923', '0 - 4 - 2 t', 'snowdon mountain railway', 'ladas'], ['1895', '2', 'mountain railway rack steam locomotive', '924', '0 - 4 - 2 t', 'snowdon mountain railway', 'enid'], ['1895', '3', 'mountain railway rack steam locomotive', '925', '0 - 4 - 2 t', 'snowdon mountain railway', 'wyddfa'], ['1896', '4', 'mountain railway rack steam locomotive', '988', '0 - 4 - 2 t', 'snowdon mountain railway', 'snowdon'], ['1896', '5', 'mountain railway rack steam locomotive', '989', '0 - 4 - 2 t', 'snowdon mountain railway', 'moel siabod'], ['1922', '6', 'mountain railway rack steam locomotive', '2838', '0 - 4 - 2 t', 'snowdon mountain railway', 'padarn'], ['1923', '7', 'mountain railway rack steam locomotive', '2869', '0 - 4 - 2 t', 'snowdon mountain railway', 'ralph'], ['1923', '8', 'mountain railway rack steam locomotive', '2870', '0 - 4 - 2 t', 'snowdon mountain railway', 'eryri']] |
list of supernanny episodes | https://en.wikipedia.org/wiki/List_of_Supernanny_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-8.html.csv | count | three of the episodes of supernanny originally aired in february of 2010 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'february 2010', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'february 2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to february 2010 .', 'tostr': 'filter_eq { all_rows ; original air date ; february 2010 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; original air date ; february 2010 } }', 'tointer': 'select the rows whose original air date record fuzzily matches to february 2010 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; original air date ; february 2010 } } ; 3 } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to february 2010 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; original air date ; february 2010 } } ; 3 } = true | select the rows whose original air date record fuzzily matches to february 2010 . 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, 'original air date_5': 5, 'february 2010_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', 'original air date_5': 'original air date', 'february 2010_6': 'february 2010', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'february 2010_6': [0], '3_7': [2]} | ['no overall', 'no in series', 'family / families', 'location ( s )', 'original air date'] | [['uk30', '1', 'the hussain family and the philip family', 'leeds & dorset', '9 february 2010'], ['uk31', '2', 'the ward family and the wren family', 'blackpool & glasgow', '16 february 2010'], ['uk32', '3', 'the coughlan family and the dumbleton family', 'west london & manchester', '23 february 2010'], ['uk33', '4', 'the mccloud family and the griffin family', 'nottingham & birmingham', '2 march 2010'], ['uk34', '5', 'the simmons family', 'north london', '9 march 2010']] |
jacksonville jaguars draft history | https://en.wikipedia.org/wiki/Jacksonville_Jaguars_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15100419-3.html.csv | unique | damon jones was the only player the jacksonville jaguars drafted from southern illinois college . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '4', 'criterion': 'equal', 'value': 'southern illinois', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'southern illinois'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to southern illinois .', 'tostr': 'filter_eq { all_rows ; college ; southern illinois }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; southern illinois } }', 'tointer': 'select the rows whose college record fuzzily matches to southern illinois . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'southern illinois'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to southern illinois .', 'tostr': 'filter_eq { all_rows ; college ; southern illinois }'}, 'name'], 'result': 'damon jones', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; southern illinois } ; name }'}, 'damon jones'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; southern illinois } ; name } ; damon jones }', 'tointer': 'the name record of this unqiue row is damon jones .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; southern illinois } } ; eq { hop { filter_eq { all_rows ; college ; southern illinois } ; name } ; damon jones } } = true', 'tointer': 'select the rows whose college record fuzzily matches to southern illinois . there is only one such row in the table . the name record of this unqiue row is damon jones .'} | and { only { filter_eq { all_rows ; college ; southern illinois } } ; eq { hop { filter_eq { all_rows ; college ; southern illinois } ; name } ; damon jones } } = true | select the rows whose college record fuzzily matches to southern illinois . there is only one such row in the table . the name record of this unqiue row is damon jones . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'southern illinois_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'damon jones_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'southern illinois_8': 'southern illinois', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'damon jones_10': 'damon jones'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'southern illinois_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'damon jones_10': [3]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '21', '21', 'renaldo wynn', 'defensive tackle', 'notre dame'], ['2', '20', '50', 'mike logan', 'cornerback', 'west virginia'], ['3', '19', '79', 'james hamilton', 'linebacker', 'north carolina'], ['4', '18', '114', 'seth payne', 'defensive tackle', 'cornell'], ['5', '17', '147', 'damon jones', 'tight end', 'southern illinois'], ['6', '21', '184', 'daimon shelton', 'fullback', 'sacramento state'], ['7', '20', '221', 'jon hesse', 'linebacker', 'nebraska']] |
2006 toronto argonauts season | https://en.wikipedia.org/wiki/2006_Toronto_Argonauts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20649850-1.html.csv | ordinal | for the 2006 toronto argonauts season , the 2nd to last player picked was obed cetoute . | {'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', 'pick', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; pick ; 2 }'}, 'player'], 'result': 'obed cetoute', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pick ; 2 } ; player }'}, 'obed cetoute'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; obed cetoute } = true', 'tointer': 'select the row whose pick record of all rows is 2nd maximum . the player record of this row is obed cetoute .'} | eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; obed cetoute } = true | select the row whose pick record of all rows is 2nd maximum . the player record of this row is obed cetoute . | 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, 'obed cetoute_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', 'obed cetoute_8': 'obed cetoute'} | {'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], 'obed cetoute_8': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['5', 'toronto argonauts', 'daniel federkeil', 'dl', 'calgary'], ['10', 'toronto argonauts', 'leron mitchell', 'db', 'western ontario'], ['14', 'toronto argonauts', 'aaron wagner', 'lb', 'brigham young'], ['31', 'toronto argonauts', 'obed cetoute', 'wr', 'central florida'], ['39', 'toronto argonauts', 'brian ramsay', 'ol', 'new mexico']] |
global challenge | https://en.wikipedia.org/wiki/Global_Challenge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1227024-4.html.csv | comparative | andy forbes crossed the finish line faster than stuart jackson . | {'row_1': '1', 'row_2': '2', 'col': '5', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'skipper', 'andy forbes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose skipper record fuzzily matches to andy forbes .', 'tostr': 'filter_eq { all_rows ; skipper ; andy forbes }'}, 'combined elapsed time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; skipper ; andy forbes } ; combined elapsed time }', 'tointer': 'select the rows whose skipper record fuzzily matches to andy forbes . take the combined elapsed time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'skipper', 'stuart jackson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose skipper record fuzzily matches to stuart jackson .', 'tostr': 'filter_eq { all_rows ; skipper ; stuart jackson }'}, 'combined elapsed time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; skipper ; stuart jackson } ; combined elapsed time }', 'tointer': 'select the rows whose skipper record fuzzily matches to stuart jackson . take the combined elapsed time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; skipper ; andy forbes } ; combined elapsed time } ; hop { filter_eq { all_rows ; skipper ; stuart jackson } ; combined elapsed time } } = true', 'tointer': 'select the rows whose skipper record fuzzily matches to andy forbes . take the combined elapsed time record of this row . select the rows whose skipper record fuzzily matches to stuart jackson . take the combined elapsed time record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; skipper ; andy forbes } ; combined elapsed time } ; hop { filter_eq { all_rows ; skipper ; stuart jackson } ; combined elapsed time } } = true | select the rows whose skipper record fuzzily matches to andy forbes . take the combined elapsed time record of this row . select the rows whose skipper record fuzzily matches to stuart jackson . take the combined elapsed time 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, 'skipper_7': 7, 'andy forbes_8': 8, 'combined elapsed time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'skipper_11': 11, 'stuart jackson_12': 12, 'combined elapsed time_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', 'skipper_7': 'skipper', 'andy forbes_8': 'andy forbes', 'combined elapsed time_9': 'combined elapsed time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'skipper_11': 'skipper', 'stuart jackson_12': 'stuart jackson', 'combined elapsed time_13': 'combined elapsed time'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'skipper_7': [0], 'andy forbes_8': [0], 'combined elapsed time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'skipper_11': [1], 'stuart jackson_12': [1], 'combined elapsed time_13': [3]} | ['overall place', 'yacht name', 'skipper', 'points', 'combined elapsed time'] | [['1', 'bg spirit', 'andy forbes', '90', '166d 00h 50 m 36s'], ['2', 'barclays adventurer', 'stuart jackson', '76', '168d 09h 39 m 09s'], ['3', 'bp explorer', 'david melville', '74', '167d 13h 16 m 25s'], ['4', 'spirit of sark', 'duggie gillespie', '73', '166d 19h 15 m 25s'], ['5', 'saic la jolla', 'eero lehtinen', '71', '168d 20h 09 m 51s'], ['6', 'team stelmar', 'clive cosby', '66', '184d 15h 04 m 11s'], ['7 =', 'me to you', 'james allen', '63', '170d 16h 07 m 02s'], ['7 =', 'vaio', 'amedeo sorrentino', '63', '170d 11h 31 m 10s'], ['9', 'samsung', 'matt riddell', '58', '170d 06h 13 m 10s'], ['10', 'imagine it done', 'dee caffari', '56', '168d 23h 31 m 26s'], ['11', 'pindar', 'loz marriott', '54', '174d 01h 11 m 59s'], ['12', 'save the children', 'paul kelly', '41', '176d 03h 37 m 23s']] |
german submarine u - 404 | https://en.wikipedia.org/wiki/German_submarine_U-404 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17794265-1.html.csv | comparative | the german u 404 sank the nagara after it sunk the molddanger . | {'row_1': '15', 'row_2': '11', 'col': '1', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ship', 'nagara'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ship record fuzzily matches to nagara .', 'tostr': 'filter_eq { all_rows ; ship ; nagara }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; ship ; nagara } ; date }', 'tointer': 'select the rows whose ship record fuzzily matches to nagara . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ship', 'moldanger'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose ship record fuzzily matches to moldanger .', 'tostr': 'filter_eq { all_rows ; ship ; moldanger }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; ship ; moldanger } ; date }', 'tointer': 'select the rows whose ship record fuzzily matches to moldanger . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; ship ; nagara } ; date } ; hop { filter_eq { all_rows ; ship ; moldanger } ; date } } = true', 'tointer': 'select the rows whose ship record fuzzily matches to nagara . take the date record of this row . select the rows whose ship record fuzzily matches to moldanger . take the date record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; ship ; nagara } ; date } ; hop { filter_eq { all_rows ; ship ; moldanger } ; date } } = true | select the rows whose ship record fuzzily matches to nagara . take the date record of this row . select the rows whose ship record fuzzily matches to moldanger . take the date 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, 'ship_7': 7, 'nagara_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'ship_11': 11, 'moldanger_12': 12, 'date_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', 'ship_7': 'ship', 'nagara_8': 'nagara', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'ship_11': 'ship', 'moldanger_12': 'moldanger', 'date_13': 'date'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'ship_7': [0], 'nagara_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'ship_11': [1], 'moldanger_12': [1], 'date_13': [3]} | ['date', 'ship', 'nationality', 'tonnage', 'fate'] | [['5 march 1942', 'collamer', 'usa', '5112', 'sunk'], ['13 march 1942', 'tolten', 'chile', '1858', 'sunk'], ['14 march 1942', 'lemuel burrows', 'usa', '7610', 'sunk'], ['17 march 1942', 'san demitro', 'great britain', '8073', 'sunk'], ['30 may 1942', 'aloca shipper', 'usa', '5491', 'sunk'], ['1 june 1942', 'west notus', 'usa', '5492', 'sunk'], ['3 june 1942', 'anna', 'sweden', '1345', 'sunk'], ['24 june 1942', 'ljubica matokovic', 'yugoslavia', '3289', 'sunk'], ['25 june 1942', 'manuda', 'usa', '4772', 'sunk'], ['25 june 1942', 'nordal', 'panama', '3845', 'sunk'], ['27 june 1942', 'moldanger', 'norway', '6827', 'sunk'], ['11 september 1942', 'marit ii', 'norway', '7141', 'damaged'], ['12 september 1942', 'daghild', 'norway', '9272', 'damaged'], ['26 september 1942', 'hms veteran', 'great britain', '1120', 'sunk'], ['29 march 1943', 'nagara', 'great britain', '8791', 'sunk'], ['30 march 1943', 'empire bowman', 'great britain', '7031', 'sunk'], ['12 april 1943', 'lancastrian prince', 'great britain', '1914', 'sunk']] |
television in thailand | https://en.wikipedia.org/wiki/Television_in_Thailand | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18987481-2.html.csv | ordinal | launched on january 25 , 1958 , rta tv - 5 was the second tv channel to be launched in thailand . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'launch date', '2'], 'result': '25 january 1958', 'ind': 0, 'tostr': 'nth_min { all_rows ; launch date ; 2 }', 'tointer': 'the 2nd minimum launch date record of all rows is 25 january 1958 .'}, '25 january 1958'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; launch date ; 2 } ; 25 january 1958 }', 'tointer': 'the 2nd minimum launch date record of all rows is 25 january 1958 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'launch date', '2'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; launch date ; 2 }'}, 'name'], 'result': 'rta tv - 5', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; launch date ; 2 } ; name }'}, 'rta tv - 5'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; launch date ; 2 } ; name } ; rta tv - 5 }', 'tointer': 'the name record of the row with 2nd minimum launch date record is rta tv - 5 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; launch date ; 2 } ; 25 january 1958 } ; eq { hop { nth_argmin { all_rows ; launch date ; 2 } ; name } ; rta tv - 5 } } = true', 'tointer': 'the 2nd minimum launch date record of all rows is 25 january 1958 . the name record of the row with 2nd minimum launch date record is rta tv - 5 .'} | and { eq { nth_min { all_rows ; launch date ; 2 } ; 25 january 1958 } ; eq { hop { nth_argmin { all_rows ; launch date ; 2 } ; name } ; rta tv - 5 } } = true | the 2nd minimum launch date record of all rows is 25 january 1958 . the name record of the row with 2nd minimum launch date record is rta tv - 5 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'launch date_8': 8, '2_9': 9, '25 january 1958_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'launch date_12': 12, '2_13': 13, 'name_14': 14, 'rta tv - 5_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'launch date_8': 'launch date', '2_9': '2', '25 january 1958_10': '25 january 1958', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'launch date_12': 'launch date', '2_13': '2', 'name_14': 'name', 'rta tv - 5_15': 'rta tv - 5'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'launch date_8': [0], '2_9': [0], '25 january 1958_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'launch date_12': [2], '2_13': [2], 'name_14': [3], 'rta tv - 5_15': [4]} | ['name', 'network', 'owner', 'launch date', 'channel ( bkk )', 'broadcasting area', 'transmitted area', 'broadcasting hours'] | [['channel 3', 'mcot and bangkok entertainment co , ltd', 'bec - tero', '26 march 1970', '3 / 32 ( vhf / uhf )', 'rama iv road', 'bangkok', '24 - hours'], ['rta tv - 5', 'royal thai army radio and television', 'royal thai army', '25 january 1958', '5 ( vhf )', 'sanam pao', 'bangkok', '24 - hours'], ['bbtv channel 7', 'bangkok broadcasting and tv co , ltd', 'royal thai army', '1 december 1967', '7 ( vhf )', 'mo chit', 'bangkok', '24 - hours'], ['modernine tv', 'mcot', 'mcot', '24 june 1955', '9 ( vhf )', 'mcot', 'bangkok', '24 - hours'], ['nbt', 'nbt', 'government', '11 july 1988', '11 ( vhf )', 'vibhavadi rangsit road din daeng', 'bangkok', '24 - hours'], ['thai pbs', 'thai public broadcasting service', 'government and public', '15 january 2008', '29 ( uhf )', 'vibhavadi rangsit road lak si', 'bangkok', '21 - hours ( 5:00 am - 2:00 am )']] |
somerset county cricket club in 1891 | https://en.wikipedia.org/wiki/Somerset_County_Cricket_Club_in_1891 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28547332-4.html.csv | count | in the 1891 somerset county cricket club season , among the players that had less than 10 matches , 2 of them had more than 14 innings . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '14', 'result': '2', 'col': '3', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '10'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'matches', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; matches ; 10 }', 'tointer': 'select the rows whose matches record is less than 10 .'}, 'innings', '14'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose matches record is less than 10 . among these rows , select the rows whose innings record is greater than 14 .', 'tostr': 'filter_greater { filter_less { all_rows ; matches ; 10 } ; innings ; 14 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_less { all_rows ; matches ; 10 } ; innings ; 14 } }', 'tointer': 'select the rows whose matches record is less than 10 . among these rows , select the rows whose innings record is greater than 14 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_less { all_rows ; matches ; 10 } ; innings ; 14 } } ; 2 } = true', 'tointer': 'select the rows whose matches record is less than 10 . among these rows , select the rows whose innings record is greater than 14 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_less { all_rows ; matches ; 10 } ; innings ; 14 } } ; 2 } = true | select the rows whose matches record is less than 10 . among these rows , select the rows whose innings record is greater than 14 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'matches_6': 6, '10_7': 7, 'innings_8': 8, '14_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'matches_6': 'matches', '10_7': '10', 'innings_8': 'innings', '14_9': '14', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'matches_6': [0], '10_7': [0], 'innings_8': [1], '14_9': [1], '2_10': [3]} | ['player', 'matches', 'innings', 'runs', 'average', 'highest score', '100s', '50s'] | [['lionel palairet', '10', '19', '560', '31.11', '100', '1', '5'], ['john challen', '9', '16', '354', '25.28', '89', '0', '2'], ['richard palairet', '10', '17', '266', '19.00', '74', '0', '1'], ['herbie hewett', '12', '22', '388', '18.47', '65', '0', '2'], ['sammy woods', '11', '19', '330', '18.33', '50', '0', '1'], ['bill roe', '7', '12', '168', '15.27', '36', '0', '0'], ['crescens robinson', '11', '17', '196', '14.00', '55', '0', '1'], ['vernon hill', '9', '15', '184', '12.26', '31', '0', '0'], ['george nichols', '12', '21', '216', '10.28', '37', '0', '0'], ['ted tyler', '12', '20', '168', '9.88', '62', '0', '1']] |
1967 tasman series | https://en.wikipedia.org/wiki/1967_Tasman_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13729095-1.html.csv | majority | team lotus was the winning team in the majority of races in the 1967 tasman series . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'lotus', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'winning car', 'lotus'], 'result': True, 'ind': 0, 'tointer': 'for the winning car records of all rows , most of them fuzzily match to lotus .', 'tostr': 'most_eq { all_rows ; winning car ; lotus } = true'} | most_eq { all_rows ; winning car ; lotus } = true | for the winning car records of all rows , most of them fuzzily match to lotus . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'winning car_3': 3, 'lotus_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'winning car_3': 'winning car', 'lotus_4': 'lotus'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'winning car_3': [0], 'lotus_4': [0]} | ['round', 'name', 'circuit', 'date', 'winning driver', 'winning car', 'winning team', 'report'] | [['new zealand', 'new zealand grand prix', 'pukekohe', '7 january', 'jackie stewart', 'brm p261', 'reg parnell racing', 'report'], ['new zealand', 'levin international', 'levin', '14 january', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['new zealand', 'lady wigram trophy', 'wigram', '21 january', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['new zealand', 'teretonga international', 'teretonga', '28 january', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['australia', 'lakeside international', 'lakeside', '12 february', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['australia', 'australian grand prix', 'warwick farm', '19 february', 'jackie stewart', 'brm p261', 'reg parnell racing', 'report'], ['australia', 'sandown international', 'sandown', '26 february', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['australia', 'south pacific trophy', 'longford', '6 march', 'jack brabham', 'brabham bt23a', 'brabham', 'report']] |
1945 vfl season | https://en.wikipedia.org/wiki/1945_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809271-13.html.csv | aggregation | during round 13 of the 1945 vfl season a total of 77,000 fans attended the games . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '77,000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '77,000', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '77,000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 77,000 } = true', 'tointer': 'the sum of the crowd record of all rows is 77,000 .'} | round_eq { sum { all_rows ; crowd } ; 77,000 } = true | the sum of the crowd record of all rows is 77,000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '77,000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '77,000_5': '77,000'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '77,000_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '7.14 ( 56 )', 'fitzroy', '11.14 ( 80 )', 'windy hill', '10000', '14 july 1945'], ['collingwood', '11.14 ( 80 )', 'south melbourne', '7.12 ( 54 )', 'victoria park', '24000', '14 july 1945'], ['carlton', '13.12 ( 90 )', 'hawthorn', '8.11 ( 59 )', 'princes park', '10000', '14 july 1945'], ['richmond', '18.10 ( 118 )', 'north melbourne', '15.9 ( 99 )', 'punt road oval', '21000', '14 july 1945'], ['st kilda', '9.10 ( 64 )', 'melbourne', '10.23 ( 83 )', 'junction oval', '6000', '14 july 1945'], ['geelong', '11.14 ( 80 )', 'footscray', '13.19 ( 97 )', 'kardinia park', '6000', '14 july 1945']] |
avenger - class mine countermeasures ship | https://en.wikipedia.org/wiki/Avenger-class_mine_countermeasures_ship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16185760-1.html.csv | count | eleven of the avenger-class ships were built by peterson shipbuilders . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'peterson shipbuilders', 'result': '11', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'peterson shipbuilders'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose builder record fuzzily matches to peterson shipbuilders .', 'tostr': 'filter_eq { all_rows ; builder ; peterson shipbuilders }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; builder ; peterson shipbuilders } }', 'tointer': 'select the rows whose builder record fuzzily matches to peterson shipbuilders . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; builder ; peterson shipbuilders } } ; 11 } = true', 'tointer': 'select the rows whose builder record fuzzily matches to peterson shipbuilders . the number of such rows is 11 .'} | eq { count { filter_eq { all_rows ; builder ; peterson shipbuilders } } ; 11 } = true | select the rows whose builder record fuzzily matches to peterson shipbuilders . the number of such rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'builder_5': 5, 'peterson shipbuilders_6': 6, '11_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'builder_5': 'builder', 'peterson shipbuilders_6': 'peterson shipbuilders', '11_7': '11'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'builder_5': [0], 'peterson shipbuilders_6': [0], '11_7': [2]} | ['ship', 'hull no', 'commissioned', 'builder', 'home port', 'nvr page'] | [['avenger', 'mcm - 1', '12 september 1987', 'peterson shipbuilders', 'sasebo , japan', 'mcm01'], ['defender', 'mcm - 2', '30 september 1989', 'marinette marine', 'sasebo , japan', 'mcm02'], ['sentry', 'mcm - 3', '2 september 1989', 'peterson shipbuilders', 'san diego , california', 'mcm03'], ['champion', 'mcm - 4', '8 february 1991', 'marinette marine', 'san diego , california', 'mcm04'], ['guardian', 'mcm - 5', '16 december 1989', 'peterson shipbuilders', 'sasebo , japan', 'mcm05'], ['devastator', 'mcm - 6', '6 october 1990', 'peterson shipbuilders', 'san diego , california', 'mcm06'], ['patriot', 'mcm - 7', '18 october 1991', 'marinette marine', 'sasebo , japan', 'mcm07'], ['scout', 'mcm - 8', '15 december 1990', 'peterson shipbuilders', 'manama , bahrain', 'mcm08'], ['pioneer', 'mcm - 9', '7 december 1992', 'peterson shipbuilders', 'san diego , california', 'mcm09'], ['warrior', 'mcm - 10', '7 april 1993', 'peterson shipbuilders', 'san diego , california', 'mcm10'], ['gladiator', 'mcm - 11', '18 september 1993', 'peterson shipbuilders', 'manama , bahrain', 'mcm11'], ['ardent', 'mcm - 12', '18 february 1994', 'peterson shipbuilders', 'manama , bahrain', 'mcm12'], ['dextrous', 'mcm - 13', '9 july 1994', 'peterson shipbuilders', 'manama , bahrain', 'mcm13'], ['chief', 'mcm - 14', '5 november 1994', 'peterson shipbuilders', 'san diego , california', 'mcm14']] |
levi risamasu | https://en.wikipedia.org/wiki/Levi_Risamasu | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14637463-1.html.csv | majority | levi risamasu did not score a single goal in the majority of his years as an athlete . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'goals', '0'], 'result': True, 'ind': 0, 'tointer': 'for the goals records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; goals ; 0 } = true'} | most_eq { all_rows ; goals ; 0 } = true | for the goals records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'goals_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'goals_3': 'goals', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'goals_3': [0], '0_4': [0]} | ['season', 'club', 'country', 'competition', 'caps', 'goals'] | [['2001 / 02', 'nac breda', 'netherlands', 'eredivisie', '9', '0'], ['2002 / 03', 'nac breda', 'netherlands', 'eredivisie', '2', '0'], ['2003 / 04', 'nac breda', 'netherlands', 'eredivisie', '1', '0'], ['2004 / 05', 'nac breda', 'netherlands', 'eredivisie', '7', '0'], ['2005 / 06', 'agovv apeldoorn', 'netherland', 'eerste divisie', '36', '3'], ['2006 / 07', 'agovv apeldoorn', 'netherland', 'eerste divisie', '26', '0'], ['2007 / 08', 'agovv apeldoorn', 'netherland', 'eerste divisie', '29', '0'], ['2008 / 09', 'sbv excelsior', 'netherland', 'eerste divisie', '6', '0'], ['2009 / 10', 'sbv excelsior', 'netherland', 'eerste divisie', '4', '0']] |
2007 - 08 rugby - bundesliga | https://en.wikipedia.org/wiki/2007%E2%80%9308_Rugby-Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20877272-5.html.csv | majority | all of the clubs played 16 games during the 2007 - 08 rugby - bundesliga competition . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '16', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '16'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 16 .', 'tostr': 'all_eq { all_rows ; played ; 16 } = true'} | all_eq { all_rows ; played ; 16 } = true | for the played records of all rows , all of them are equal to 16 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '16_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '16_4': '16'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '16_4': [0]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'difference', 'points'] | [['1', 'rk 03 berlin', '16', '14', '0', '2', '714', '158', '556', '44'], ['2', 'tsv victoria linden', '16', '12', '0', '4', '527', '232', '295', '40'], ['3', 'fc st pauli rugby', '16', '11', '0', '5', '554', '300', '254', '38'], ['4', 'dsv 78 / 08 ricklingen', '16', '10', '0', '6', '504', '265', '239', '36'], ['5', 'sc germania list', '16', '8', '0', '8', '313', '337', '- 24', '32'], ['6', 'sv odin hannover', '16', '7', '1', '8', '280', '306', '- 26', '29'], ['7', 'usv potsdam', '16', '6', '1', '9', '350', '503', '- 153', '27'], ['8', 'hamburger rc', '16', '2', '0', '14', '137', '556', '- 419', '20']] |
2010 - 11 atlanta thrashers season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Atlanta_Thrashers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27537518-7.html.csv | comparative | in the 2010-11 atlanta thrashers season , the attendance on january 22 , was 3145 more than on january 23rd . | {'row_1': '9', 'row_2': '10', 'col': '8', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'january 22'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to january 22 .', 'tostr': 'filter_eq { all_rows ; date ; january 22 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; january 22 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to january 22 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'january 23'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to january 23 .', 'tostr': 'filter_eq { all_rows ; date ; january 23 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; january 23 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to january 23 . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; january 22 } ; attendance } ; hop { filter_eq { all_rows ; date ; january 23 } ; attendance } }', 'tointer': 'select the rows whose date record fuzzily matches to january 22 . take the attendance record of this row . select the rows whose date record fuzzily matches to january 23 . take the attendance record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'january 22'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to january 22 .', 'tostr': 'filter_eq { all_rows ; date ; january 22 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; january 22 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to january 22 . take the attendance record of this row .'}, '17061'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; january 22 } ; attendance } ; 17061 }', 'tointer': 'the attendance record of the first row is 17061 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'january 23'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to january 23 .', 'tostr': 'filter_eq { all_rows ; date ; january 23 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; january 23 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to january 23 . take the attendance record of this row .'}, '13916'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; january 23 } ; attendance } ; 13916 }', 'tointer': 'the attendance record of the second row is 13916 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; date ; january 22 } ; attendance } ; 17061 } ; eq { hop { filter_eq { all_rows ; date ; january 23 } ; attendance } ; 13916 } }', 'tointer': 'the attendance record of the first row is 17061 . the attendance record of the second row is 13916 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; date ; january 22 } ; attendance } ; hop { filter_eq { all_rows ; date ; january 23 } ; attendance } } ; and { eq { hop { filter_eq { all_rows ; date ; january 22 } ; attendance } ; 17061 } ; eq { hop { filter_eq { all_rows ; date ; january 23 } ; attendance } ; 13916 } } } = true', 'tointer': 'select the rows whose date record fuzzily matches to january 22 . take the attendance record of this row . select the rows whose date record fuzzily matches to january 23 . take the attendance record of this row . the first record is greater than the second record . the attendance record of the first row is 17061 . the attendance record of the second row is 13916 .'} | and { greater { hop { filter_eq { all_rows ; date ; january 22 } ; attendance } ; hop { filter_eq { all_rows ; date ; january 23 } ; attendance } } ; and { eq { hop { filter_eq { all_rows ; date ; january 22 } ; attendance } ; 17061 } ; eq { hop { filter_eq { all_rows ; date ; january 23 } ; attendance } ; 13916 } } } = true | select the rows whose date record fuzzily matches to january 22 . take the attendance record of this row . select the rows whose date record fuzzily matches to january 23 . take the attendance record of this row . the first record is greater than the second record . the attendance record of the first row is 17061 . the attendance record of the second row is 13916 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'date_11': 11, 'january 22_12': 12, 'attendance_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'date_15': 15, 'january 23_16': 16, 'attendance_17': 17, 'and_7': 7, 'eq_5': 5, '17061_18': 18, 'eq_6': 6, '13916_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'january 22_12': 'january 22', 'attendance_13': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'date_15': 'date', 'january 23_16': 'january 23', 'attendance_17': 'attendance', 'and_7': 'and', 'eq_5': 'eq', '17061_18': '17061', 'eq_6': 'eq', '13916_19': '13916'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'date_11': [0], 'january 22_12': [0], 'attendance_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'date_15': [1], 'january 23_16': [1], 'attendance_17': [3], 'and_7': [8], 'eq_5': [7], '17061_18': [5], 'eq_6': [7], '13916_19': [6]} | ['game', 'date', 'opponent', 'score', 'first star', 'decision', 'location', 'attendance', 'record', 'points'] | [['42', 'january 2', 'montreal canadiens', '4 - 3 ot', 'd byfuglien', 'o pavelec', 'bell centre', '21273', '21 - 15 - 6', '48'], ['43', 'january 5', 'florida panthers', '3 - 2', 'r peverley', 'o pavelec', 'bankatlantic center', '12803', '22 - 15 - 6', '50'], ['44', 'january 7', 'toronto maple leafs', '3 - 9', 'm grabovski', 'o pavelec', 'philips arena', '14592', '22 - 16 - 6', '50'], ['45', 'january 9', 'carolina hurricanes', '3 - 4 ot', 't ruutu', 'o pavelec', 'rbc center', '17907', '22 - 16 - 7', '51'], ['46', 'january 14', 'philadelphia flyers', '2 - 5', 'd briere', 'o pavelec', 'philips arena', '15081', '22 - 17 - 7', '51'], ['47', 'january 15', 'dallas stars', '1 - 6', 't daley', 'o pavelec', 'american airlines center', '17702', '22 - 18 - 7', '51'], ['48', 'january 17', 'florida panthers', '3 - 2 so', 'a burmistrov', 'o pavelec', 'bankatlantic center', '11477', '23 - 18 - 7', '53'], ['49', 'january 20', 'tampa bay lightning', '2 - 3 so', 's stamkos', 'o pavelec', 'philips arena', '12314', '23 - 18 - 8', '54'], ['50', 'january 22', 'new york rangers', '2 - 3 so', 'm zuccarello', 'o pavelec', 'philips arena', '17061', '23 - 18 - 9', '55'], ['51', 'january 23', 'tampa bay lightning', '1 - 7', 's gagne', 'o pavelec', 'st pete times forum', '13916', '23 - 19 - 9', '55']] |
1975 philadelphia eagles season | https://en.wikipedia.org/wiki/1975_Philadelphia_Eagles_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18908541-2.html.csv | aggregation | for the 1975 philadelphia eagles season the total attendance was 779652 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '779652', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '779652', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '779652'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 779652 } = true', 'tointer': 'the sum of the attendance record of all rows is 779652 .'} | round_eq { sum { all_rows ; attendance } ; 779652 } = true | the sum of the attendance record of all rows is 779652 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '779652_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '779652_5': '779652'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '779652_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 21 , 1975', 'new york giants', 'l 23 - 14', '60798'], ['2', 'september 28 , 1975', 'chicago bears', 'l 15 - 13', '48071'], ['3', 'october 5 , 1975', 'washington redskins', 'w 26 - 10', '64397'], ['4', 'october 12 , 1975', 'miami dolphins', 'l 24 - 16', '60127'], ['5', 'october 19 , 1975', 'st louis cardinals', 'l 31 - 20', '45242'], ['6', 'october 26 , 1975', 'dallas cowboys', 'l 20 - 17', '64889'], ['7', 'november 3 , 1975', 'los angeles rams', 'l 42 - 3', '64601'], ['8', 'november 9 , 1975', 'st louis cardinals', 'l 24 - 23', '60277'], ['9', 'november 16 , 1975', 'new york giants', 'w 13 - 10', '53434'], ['10', 'november 23 , 1975', 'dallas cowboys', 'l 27 - 17', '57893'], ['11', 'november 30 , 1975', 'san francisco 49ers', 'w 27 - 17', '56694'], ['12', 'december 7 , 1975', 'cincinnati bengals', 'l 31 - 0', '56984'], ['13', 'december 14 , 1975', 'denver broncos', 'l 25 - 10', '36860'], ['14', 'december 21 , 1975', 'washington redskins', 'w 26 - 3', '49385']] |
2007 - 08 isthmian league | https://en.wikipedia.org/wiki/2007%E2%80%9308_Isthmian_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17494040-8.html.csv | ordinal | the third highest attendance in the 2007-08 isthmian league occurred when the home team was horsham . | {'row': '4', 'col': '5', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 3 }'}, 'home team'], 'result': 'horsham', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 3 } ; home team }'}, 'horsham'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; home team } ; horsham } = true', 'tointer': 'select the row whose attendance record of all rows is 3rd maximum . the home team record of this row is horsham .'} | eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; home team } ; horsham } = true | select the row whose attendance record of all rows is 3rd maximum . the home team record of this row is horsham . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'home team_7': 7, 'horsham_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '3_6': '3', 'home team_7': 'home team', 'horsham_8': 'horsham'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'home team_7': [1], 'horsham_8': [2]} | ['tie no', 'home team', 'score', 'away team', 'attendance'] | [['51', 'afc hornchurch', '1 - 2', 'ramsgate', '216'], ['52', 'arlesey town', '1 - 4', 'edgware town', '79'], ['53', 'heybridge swifts', '3 - 0', 'dartford', '152'], ['54', 'horsham', '1 - 2', 'walton casuals', '187'], ['55', 'redbridge', '0 - 1', 'afc sudbury', '76'], ['56', 'tonbridge angels', '1 - 3', 'carshalton athletic', '202'], ['57', 'tooting & mitcham united', '1 - 0', 'whyteleafe', '105'], ['58', 'wealdstone', '1 - 0', 'ashford town ( middx )', '88']] |
2010 atlantic coast conference football season | https://en.wikipedia.org/wiki/2010_Atlantic_Coast_Conference_football_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28744929-1.html.csv | majority | during the 2010 atlantic coast conference football season , most of the public schools were founded in the 1800s . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '18', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'founded', '18'], 'result': True, 'ind': 0, 'tointer': 'for the founded records of all rows , most of them fuzzily match to 18 .', 'tostr': 'most_eq { all_rows ; founded ; 18 } = true'} | most_eq { all_rows ; founded ; 18 } = true | for the founded records of all rows , most of them fuzzily match to 18 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'founded_3': 3, '18_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'founded_3': 'founded', '18_4': '18'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'founded_3': [0], '18_4': [0]} | ['institution', 'nickname', 'location', 'founded', 'joined acc', 'school type', 'acc football titles'] | [['boston college', 'eagles', 'chestnut hill , massachusetts', '1863', '2005', 'private / jesuit', '0'], ['clemson', 'tigers', 'clemson , south carolina', '1889', '1953', 'public', '13'], ['duke', 'blue devils', 'durham , north carolina', '1838', '1953', 'private / non - sectarian', '7'], ['florida state', 'seminoles', 'tallahassee , florida', '1851', '1991', 'public', '12'], ['georgia tech', 'yellow jackets', 'atlanta , georgia', '1885', '1979', 'public', '3'], ['maryland', 'terrapins', 'college park , maryland', '1856', '1953', 'public', '9'], ['miami', 'hurricanes', 'coral gables , florida', '1925', '2004', 'private / non - sectarian', '0'], ['north carolina', 'tar heels', 'chapel hill , north carolina', '1789', '1953', 'public', '5'], ['nc state', 'wolfpack', 'raleigh , north carolina', '1887', '1953', 'public', '7'], ['virginia', 'cavaliers', 'charlottesville , virginia', '1819', '1953', 'public', '2'], ['virginia tech', 'hokies', 'blacksburg , virginia', '1872', '2004', 'public', '3']] |
catriona matthew | https://en.wikipedia.org/wiki/Catriona_Matthew | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2167226-3.html.csv | aggregation | all victory participations of catriona matthew on the ladies european tour resulted in a total amount of 444286 euros . | {'scope': 'all', 'col': '8', 'type': 'sum', 'result': '444286', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'winners share'], 'result': '444286', 'ind': 0, 'tostr': 'sum { all_rows ; winners share }'}, '444286'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; winners share } ; 444286 } = true', 'tointer': 'the sum of the winners share record of all rows is 444286 .'} | round_eq { sum { all_rows ; winners share } ; 444286 } = true | the sum of the winners share record of all rows is 444286 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'winners share_4': 4, '444286_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'winners share_4': 'winners share', '444286_5': '444286'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'winners share_4': [0], '444286_5': [1]} | ['no', 'date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up', 'winners share'] | [['1', '9 aug 1998', "mcdonald 's wpga championship", '71 + 69 + 67 + 69 = 276', '- 12', '5 strokes', 'helen alfredsson laura davies', '45000'], ['2', '12 aug 2007', 'scandinavian tpc hosted by annika', '71 + 74 + 66 + 68 = 279', '- 10', '3 strokes', 'sophie gustafson laura diaz', '78750'], ['3', '2 aug 2009', "ricoh women 's british open 1", '74 + 67 + 71 + 73 = 285', '- 3', '3 strokes', 'karrie webb', '235036'], ['4', '20 aug 2011', 'aberdeen ladies scottish open', '70 + 65 + 76 = 201', '- 15', '10 strokes', 'hannah jun', '33000'], ['5', '5 aug 2012', 'ladies irish open', '67 + 71 + 71 = 209', '- 7', '1 stroke', 'suzann pettersen', '52500']] |
1970 isle of man tt | https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-3.html.csv | count | the ducati team had a total of three riders in the 1970 isle of man . | {'scope': 'all', 'criterion': 'equal', 'value': 'ducati', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'ducati'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to ducati .', 'tostr': 'filter_eq { all_rows ; team ; ducati }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; ducati } }', 'tointer': 'select the rows whose team record fuzzily matches to ducati . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; ducati } } ; 3 } = true', 'tointer': 'select the rows whose team record fuzzily matches to ducati . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; team ; ducati } } ; 3 } = true | select the rows whose team record fuzzily matches to ducati . 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, 'team_5': 5, 'ducati_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', 'team_5': 'team', 'ducati_6': 'ducati', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'ducati_6': [0], '3_7': [2]} | ['rank', 'rider', 'team', 'speed', 'time'] | [['1', 'chas mortimer', 'ducati', '84.87 mph', '2:13.23.4'], ['2', 'john williams', 'honda', '84.80 mph', '2:13.29.0'], ['3', 'stan woods', 'suzuki', '84.06 mph', '2:14.40.6'], ['4', 'ghunter', 'ducati', '83.94 mph', '2:14.52.4'], ['5', 'roy boughley', 'honda', '82.26 mph', '2:17.37.6'], ['6', 'raymond ashcroft', 'suzuki', '76.59 mph', '2:27.48.8'], ['7', 'tom loughridge', 'suzuki', '76.32 mph', '2:28.19.0'], ['8', 'cluton', 'ducati', '72.50 mph', '2:36.08.0']] |
list of career achievements by lebron james | https://en.wikipedia.org/wiki/List_of_career_achievements_by_LeBron_James | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11012104-8.html.csv | majority | the majority of basketball games resulted in wins for lebron james . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'box score', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the box score records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; box score ; w } = true'} | most_eq { all_rows ; box score ; w } = true | for the box score records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'box score_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'box score_3': 'box score', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'box score_3': [0], 'w_4': [0]} | ['number', 'opponent', 'box score', 'points', 'fgm - fga', '3 pm - 3pa', 'ftm - fta', 'assists', 'rebounds', 'steals', 'blocks'] | [['1', 'washington wizards', 'w 97 - 96', '41', '16 - 28', '3 - 5', '6 - 9', '3', '5', '2', '0'], ['2', 'washington wizards', 'w 121 - 120', '45', '14 - 23', '0 - 1', '17 - 19', '6', '7', '2', '0'], ['3', 'detroit pistons', 'w 109 - 107', '48', '18 - 33', '2 - 3', '10 - 14', '7', '9', '2', '0'], ['4', 'boston celtics', 'l 92 - 97', '45', '14 - 29', '3 - 11', '14 - 19', '6', '5', '2', '0'], ['5', 'atlanta hawks', 'w 97 - 82', '47', '15 - 25', '5 - 10', '12 - 16', '8', '12', '1', '1'], ['6', 'orlando magic', 'l 106 - 107', '49', '20 - 30', '3 - 6', '6 - 10', '8', '6', '2', '3'], ['7', 'orlando magic', 'l 89 - 99', '41', '11 - 28', '1 - 8', '18 - 24', '9', '7', '2', '1'], ['8', 'orlando magic', 'l 114 - 116', '44', '13 - 29', '4 - 10', '14 - 18', '7', '12', '1', '1'], ['9', 'chicago bulls', 'w 112 - 102', '40', '16 - 23', '2 - 4', '6 - 6', '8', '8', '1', '2'], ['10', 'indiana pacers', 'w 101 - 93', '40', '14 - 27', '0 - 0', '12 - 16', '9', '18', '2', '2'], ['11', 'boston celtics', 'w 98 - 79', '45', '19 - 26', '2 - 4', '5 - 9', '5', '15', '0', '0']] |
gabriela navrátilová | https://en.wikipedia.org/wiki/Gabriela_Navr%C3%A1tilov%C3%A1 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14935689-2.html.csv | ordinal | the second earliest tournament for gabriela navrátilová was when the tournament was in portugal . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'tournament'], 'result': 'estoril , portugal', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; tournament }'}, 'estoril , portugal'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 2 } ; tournament } ; estoril , portugal } = true', 'tointer': 'select the row whose date record of all rows is 2nd minimum . the tournament record of this row is estoril , portugal .'} | eq { hop { nth_argmin { all_rows ; date ; 2 } ; tournament } ; estoril , portugal } = true | select the row whose date record of all rows is 2nd minimum . the tournament record of this row is estoril , portugal . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'tournament_7': 7, 'estoril , portugal_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_5': 'date', '2_6': '2', 'tournament_7': 'tournament', 'estoril , portugal_8': 'estoril , portugal'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'tournament_7': [1], 'estoril , portugal_8': [2]} | ['date', 'tournament', 'surface', 'partnering', 'opponents in the final', 'score'] | [['march 1 , 2004', 'acapulco , mexico', 'clay', 'olga blahotová', 'lisa mcshea milagros sequera', '2 - 6 , 7 - 6 ( 7 - 5 ) , 6 - 4'], ['march 12 , 2004', 'estoril , portugal', 'clay', 'olga blahotová', 'emmanuelle gagliardi janette husárová', '6 - 3 , 6 - 2'], ['january 10 , 2005', 'canberra , australia', 'hard', 'michaela paštiková', 'tathiana garbin tina križan', '7 - 5 , 1 - 6 , 6 - 4'], ['july 11 , 2005', 'modena , italy', 'clay', 'michaela paštiková', 'yulia beygelzimer mervana jugić - salkić', '6 - 2 , 6 - 0'], ['february 5 , 2007', 'paris , france', 'carpet ( i )', 'vladimíra uhlířová', 'cara black liezel huber', '6 - 2 , 6 - 0'], ['april 23 , 2007', 'budapest , hungary', 'clay', 'martina müller', 'ágnes szávay vladimíra uhlířová', '7 - 5 , 6 - 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/1-2668243-22.html.csv | unique | james hamilton jr. was the only incumbent who retired . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'retired', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired .', 'tostr': 'filter_eq { all_rows ; result ; retired }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; retired } }', 'tointer': 'select the rows whose result record fuzzily matches to retired . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired .', 'tostr': 'filter_eq { all_rows ; result ; retired }'}, 'incumbent'], 'result': 'james hamilton , jr', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; retired } ; incumbent }'}, 'james hamilton , jr'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; retired } ; incumbent } ; james hamilton , jr }', 'tointer': 'the incumbent record of this unqiue row is james hamilton , jr .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; retired } } ; eq { hop { filter_eq { all_rows ; result ; retired } ; incumbent } ; james hamilton , jr } } = true', 'tointer': 'select the rows whose result record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is james hamilton , jr .'} | and { only { filter_eq { all_rows ; result ; retired } } ; eq { hop { filter_eq { all_rows ; result ; retired } ; incumbent } ; james hamilton , jr } } = true | select the rows whose result record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is james hamilton , jr . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'retired_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'james hamilton , jr_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'retired_8': 'retired', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'james hamilton , jr_10': 'james hamilton , jr'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'retired_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'james hamilton , jr_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['south carolina 1', 'william drayton', 'jacksonian', '1825 ( special )', 're - elected', 'william drayton ( j )'], ['south carolina 2', 'james hamilton , jr', 'jacksonian', '1822 ( special )', 'retired jacksonian hold', 'robert w barnwell ( j )'], ['south carolina 3', 'thomas r mitchell', 'jacksonian', '1820 1824', 'lost re - election jacksonian hold', 'john campbell ( j ) thomas r mitchell ( j )'], ['south carolina 4', 'william d martin', 'jacksonian', '1826', 're - elected', 'william d martin ( j )'], ['south carolina 5', 'george mcduffie', 'jacksonian', '1820', 're - elected', 'george mcduffie ( j )'], ['south carolina 6', 'warren r davis', 'jacksonian', '1826', 're - elected', 'warren r davis ( j ) 76.1 % cobb 23.9 %'], ['south carolina 7', 'william t nuckolls', 'jacksonian', '1826', 're - elected', 'william t nuckolls ( j )']] |
catanduanes | https://en.wikipedia.org/wiki/Catanduanes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-255829-1.html.csv | comparative | san miguel has a higher number of barangays than gigmoto has . | {'row_1': '9', 'row_2': '5', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'municipality', 'san miguel'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose municipality record fuzzily matches to san miguel .', 'tostr': 'filter_eq { all_rows ; municipality ; san miguel }'}, 'no of barangays'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; municipality ; san miguel } ; no of barangays }', 'tointer': 'select the rows whose municipality record fuzzily matches to san miguel . take the no of barangays record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'municipality', 'gigmoto'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose municipality record fuzzily matches to gigmoto .', 'tostr': 'filter_eq { all_rows ; municipality ; gigmoto }'}, 'no of barangays'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; municipality ; gigmoto } ; no of barangays }', 'tointer': 'select the rows whose municipality record fuzzily matches to gigmoto . take the no of barangays record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; municipality ; san miguel } ; no of barangays } ; hop { filter_eq { all_rows ; municipality ; gigmoto } ; no of barangays } } = true', 'tointer': 'select the rows whose municipality record fuzzily matches to san miguel . take the no of barangays record of this row . select the rows whose municipality record fuzzily matches to gigmoto . take the no of barangays record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; municipality ; san miguel } ; no of barangays } ; hop { filter_eq { all_rows ; municipality ; gigmoto } ; no of barangays } } = true | select the rows whose municipality record fuzzily matches to san miguel . take the no of barangays record of this row . select the rows whose municipality record fuzzily matches to gigmoto . take the no of barangays 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, 'municipality_7': 7, 'san miguel_8': 8, 'no of barangays_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'municipality_11': 11, 'gigmoto_12': 12, 'no of barangays_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', 'municipality_7': 'municipality', 'san miguel_8': 'san miguel', 'no of barangays_9': 'no of barangays', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'municipality_11': 'municipality', 'gigmoto_12': 'gigmoto', 'no of barangays_13': 'no of barangays'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'municipality_7': [0], 'san miguel_8': [0], 'no of barangays_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'municipality_11': [1], 'gigmoto_12': [1], 'no of barangays_13': [3]} | ['municipality', 'no of barangays', 'area ( hectares )', 'population ( 2007 )', 'population ( 2010 )', 'pop density ( per km 2 )'] | [['bagamanoc', '18', '8074', '10183', '11370', '140.8'], ['baras', '29', '10950', '11787', '12243', '111.8'], ['bato', '27', '4862', '18738', '19984', '411.0'], ['caramoran', '27', '26374', '25618', '28063', '106.4'], ['gigmoto', '9', '18182', '7569', '8003', '44.0'], ['pandan', '26', '11990', '19005', '19393', '161.7'], ['panganiban ( payo )', '23', '7996', '9290', '9738', '121.8'], ['san andres ( calolbon )', '38', '16731', '33781', '35779', '213.8'], ['san miguel', '24', '12994', '12966', '14107', '108.6'], ['viga', '31', '15823', '19266', '20669', '130.6']] |
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/2-12307135-6.html.csv | superlative | raãl played the most games among players who debuted in europe in 1995 . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,6', 'subset': {'col': '6', 'criterion': 'equal', 'value': '1995'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'debut in europe', '1995'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; debut in europe ; 1995 }', 'tointer': 'select the rows whose debut in europe record is equal to 1995 .'}, 'games'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; debut in europe ; 1995 } ; games }'}, 'player'], 'result': 'raãl', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; debut in europe ; 1995 } ; games } ; player }'}, 'raãl'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; debut in europe ; 1995 } ; games } ; player } ; raãl } = true', 'tointer': 'select the rows whose debut in europe record is equal to 1995 . select the row whose games record of these rows is maximum . the player record of this row is raãl .'} | eq { hop { argmax { filter_eq { all_rows ; debut in europe ; 1995 } ; games } ; player } ; raãl } = true | select the rows whose debut in europe record is equal to 1995 . select the row whose games record of these rows is maximum . the player record of this row is raãl . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'debut in europe_6': 6, '1995_7': 7, 'games_8': 8, 'player_9': 9, 'raãl_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'debut in europe_6': 'debut in europe', '1995_7': '1995', 'games_8': 'games', 'player_9': 'player', 'raãl_10': 'raãl'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'debut in europe_6': [0], '1995_7': [0], 'games_8': [1], 'player_9': [2], 'raãl_10': [3]} | ['rank', 'player', 'games', 'goals', 'goal ratio', 'debut in europe'] | [['1', 'paolo maldini', '173', '3', '0.02', '1985'], ['2', 'raãl', '161', '76', '0.46', '1995'], ['3', 'clarence seedorf', '161', '15', '0.09', '1992'], ['4', 'javier zanetti', '159', '5', '0.03', '1995'], ['5', 'xavi', '154', '12', '0.08', '1999'], ['6', 'ryan giggs', '151', '29', '0.19', '1991'], ['7', 'jamie carragher', '150', '1', '0.01', '1997'], ['8', 'edwin van der sar', '142', '0', '0.00', '1993'], ['9', 'andriy shevchenko', '142', '67', '0.47', '1994'], ['10', 'roberto carlos', '141', '20', '0.14', '1995']] |
toronto raptors all - time roster | https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-3.html.csv | count | seven different players played in the guard position . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'guard', 'result': '7', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to guard .', 'tostr': 'filter_eq { all_rows ; position ; guard }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; guard } }', 'tointer': 'select the rows whose position record fuzzily matches to guard . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; guard } } ; 7 } = true', 'tointer': 'select the rows whose position record fuzzily matches to guard . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; position ; guard } } ; 7 } = true | select the rows whose position record fuzzily matches to guard . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'guard_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'guard_6': 'guard', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'guard_6': [0], '7_7': [2]} | ['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team'] | [['josé calderón', '8', 'spain', 'guard', '2005 - 2013', 'tau cerámica ( spain )'], ['marcus camby', '21', 'united states', 'center', '1996 - 98', 'massachusetts'], ['anthony carter', '25', 'united states', 'guard', '2011 - 12', 'hawaii'], ['vince carter', '15', 'united states', 'guard - forward', '1998 - 2004', 'north carolina'], ['chris childs', '1', 'united states', 'guard', '2001 - 02', 'boise state'], ['doug christie', '13', 'united states', 'forward', '1996 - 2000', 'pepperdine'], ['keon clark', '7', 'united states', 'forward - center', '2001 - 02', 'unlv'], ['omar cook', '1', 'united states', 'guard', '2005 - 06', "st john 's"], ['tyrone corbin', '23', 'united states', 'guard - forward', '2000 - 01', 'depaul'], ['william cunningham', '54', 'united states', 'center', '1999', 'temple'], ['earl cureton', '35', 'united states', 'forward', '1996 - 97', 'detroit'], ['dell curry', '30', 'united states', 'guard', '1999 - 2002', 'virginia tech']] |
1988 pga tour | https://en.wikipedia.org/wiki/1988_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14639984-4.html.csv | count | all the players which participated in the 1988 pga tour 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]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'jack nicklaus', 'united states', '5005825', '73'], ['2', 'tom watson', 'united states', '4974845', '37'], ['3', 'curtis strange', 'united states', '4263133', '16'], ['4', 'tom kite', 'united states', '4205412', '10'], ['5', 'lanny wadkins', 'united states', '3707586', '18']] |
2003 grand prix of monterey | https://en.wikipedia.org/wiki/2003_Grand_Prix_of_Monterey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18805166-2.html.csv | unique | the driver that had grid position 1 is the only one who received more than 20 points . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '5', 'criterion': 'greater_than', 'value': '20', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is greater than 20 .', 'tostr': 'filter_greater { all_rows ; points ; 20 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; points ; 20 } }', 'tointer': 'select the rows whose points record is greater than 20 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is greater than 20 .', 'tostr': 'filter_greater { all_rows ; points ; 20 }'}, 'grid'], 'result': '1', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; points ; 20 } ; grid }'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; points ; 20 } ; grid } ; 1 }', 'tointer': 'the grid record of this unqiue row is 1 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; points ; 20 } } ; eq { hop { filter_greater { all_rows ; points ; 20 } ; grid } ; 1 } } = true', 'tointer': 'select the rows whose points record is greater than 20 . there is only one such row in the table . the grid record of this unqiue row is 1 .'} | and { only { filter_greater { all_rows ; points ; 20 } } ; eq { hop { filter_greater { all_rows ; points ; 20 } ; grid } ; 1 } } = true | select the rows whose points record is greater than 20 . there is only one such row in the table . the grid record of this unqiue row is 1 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'points_7': 7, '20_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'grid_9': 9, '1_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'points_7': 'points', '20_8': '20', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'grid_9': 'grid', '1_10': '1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '20_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'grid_9': [2], '1_10': [3]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['patrick carpentier', "team player 's", '87', '1:48:11.023', '1', '22'], ['bruno junqueira', 'newman / haas racing', '87', '+ 0.8 secs', '2', '17'], ['paul tracy', "team player 's", '87', '+ 28.6 secs', '3', '14'], ['michel jourdain , jr', 'team rahal', '87', '+ 40.8 secs', '13', '12'], ['mario haberfeld', 'mi - jack conquest racing', '87', '+ 42.1 secs', '6', '10'], ['oriol servià', 'patrick racing', '87', '+ 1:00.2', '10', '8'], ['adrian fernández', 'fernández racing', '87', '+ 1:01.4', '5', '6'], ['jimmy vasser', 'american spirit team johansson', '87', '+ 1:01.8', '8', '5'], ['tiago monteiro', 'fittipaldi - dingman racing', '86', '+ 1 lap', '15', '4'], ['mario domínguez', 'herdez competition', '86', '+ 1 lap', '11', '3'], ['bryan herta', 'pk racing', '86', '+ 1 lap', '12', '2'], ['ryan hunter - reay', 'american spirit team johansson', '86', '+ 1 lap', '17', '1'], ['joël camathias', 'dale coyne racing', '85', '+ 2 laps', '18', '0'], ['alex tagliani', 'rocketsports racing', '85', '+ 2 laps', '14', '0'], ['roberto moreno', 'herdez competition', '85', '+ 2 laps', '9', '0'], ['geoff boss', 'dale coyne racing', '83', 'mechanical', '19', '0'], ['sébastien bourdais', 'newman / haas racing', '77', 'mechanical', '4', '0'], ['darren manning', 'walker racing', '12', 'mechanical', '7', '0'], ['rodolfo lavín', 'walker racing', '10', 'mechanical', '16', '0']] |
central province ( kenya ) | https://en.wikipedia.org/wiki/Central_Province_%28Kenya%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1404414-2.html.csv | comparative | kiambu had a higher population in 2009 than the county of nyeri did . | {'row_1': '5', 'row_2': '2', 'col': '1', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'kiambu'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to kiambu .', 'tostr': 'filter_eq { all_rows ; county ; kiambu }'}, 'code'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; county ; kiambu } ; code }', 'tointer': 'select the rows whose county record fuzzily matches to kiambu . take the code record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'nyeri'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose county record fuzzily matches to nyeri .', 'tostr': 'filter_eq { all_rows ; county ; nyeri }'}, 'code'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; county ; nyeri } ; code }', 'tointer': 'select the rows whose county record fuzzily matches to nyeri . take the code record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; county ; kiambu } ; code } ; hop { filter_eq { all_rows ; county ; nyeri } ; code } } = true', 'tointer': 'select the rows whose county record fuzzily matches to kiambu . take the code record of this row . select the rows whose county record fuzzily matches to nyeri . take the code record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; county ; kiambu } ; code } ; hop { filter_eq { all_rows ; county ; nyeri } ; code } } = true | select the rows whose county record fuzzily matches to kiambu . take the code record of this row . select the rows whose county record fuzzily matches to nyeri . take the code 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, 'county_7': 7, 'kiambu_8': 8, 'code_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'county_11': 11, 'nyeri_12': 12, 'code_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', 'county_7': 'county', 'kiambu_8': 'kiambu', 'code_9': 'code', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'county_11': 'county', 'nyeri_12': 'nyeri', 'code_13': 'code'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'county_7': [0], 'kiambu_8': [0], 'code_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'county_11': [1], 'nyeri_12': [1], 'code_13': [3]} | ['code', 'county', 'former province', 'area ( km 2 )', 'population census 2009', 'capital'] | [['18', 'nyandarua', 'central', '3107.7', '596268', 'ol kalou'], ['19', 'nyeri', 'central', '2361.0', '693558', 'nyeri'], ['20', 'kirinyaga', 'central', '1205.4', '528054', 'kerugoya / kutus'], ['21', "murang ' a", 'central', '2325.8', '942581', "murang ' a"], ['22', 'kiambu', 'central', '2449.2', '1623282', 'kiambu']] |
list of manly - warringah sea eagles honours | https://en.wikipedia.org/wiki/List_of_Manly-Warringah_Sea_Eagles_honours | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12573519-8.html.csv | count | 10 games are included in the list of manly - warringah sea eagles honours . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '10', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'competition'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record is arbitrary .', 'tostr': 'filter_all { all_rows ; competition }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; competition } }', 'tointer': 'select the rows whose competition record is arbitrary . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; competition } } ; 10 } = true', 'tointer': 'select the rows whose competition record is arbitrary . the number of such rows is 10 .'} | eq { count { filter_all { all_rows ; competition } } ; 10 } = true | select the rows whose competition record is arbitrary . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'competition_5': 5, '10_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'competition_5': 'competition', '10_6': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'competition_5': [0], '10_6': [2]} | ['year', 'opponent', 'competition', 'score', 'venue', 'attendance'] | [['1951', 'south sydney rabbitohs', 'nswrfl', '14 - 42', 'sydney sports ground', '28505'], ['1957', 'st george dragons', 'nswrfl', '9 - 31', 'sydney cricket ground', '54399'], ['1959', 'st george dragons', 'nswrfl', '0 - 20', 'sydney cricket ground', '49457'], ['1968', 'south sydney rabbitohs', 'nswrfl', '9 - 13', 'sydney cricket ground', '54255'], ['1970', 'south sydney rabbitohs', 'nswrfl', '12 - 23', 'sydney cricket ground', '53241'], ['1982', 'parramatta eels', 'nswrfl', '8 - 21', 'sydney cricket ground', '52186'], ['1983', 'parramatta eels', 'nswrfl', '6 - 18', 'sydney cricket ground', '40285'], ['1995', 'sydney bulldogs', 'arl', '4 - 17', 'sydney football stadium', '41127'], ['1997', 'newcastle knights', 'arl', '16 - 22', 'sydney football stadium', '42482'], ['2007', 'melbourne storm', 'nrl', '8 - 34', 'anz stadium', '81392']] |
telecommunications in moldova | https://en.wikipedia.org/wiki/Telecommunications_in_Moldova | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19246-2.html.csv | count | two of the frequencies used in telecommunications in moldova is 450 mhz . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '450 mhz', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'frequency', '450 mhz'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose frequency record fuzzily matches to 450 mhz .', 'tostr': 'filter_eq { all_rows ; frequency ; 450 mhz }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; frequency ; 450 mhz } }', 'tointer': 'select the rows whose frequency record fuzzily matches to 450 mhz . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; frequency ; 450 mhz } } ; 2 } = true', 'tointer': 'select the rows whose frequency record fuzzily matches to 450 mhz . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; frequency ; 450 mhz } } ; 2 } = true | select the rows whose frequency record fuzzily matches to 450 mhz . 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, 'frequency_5': 5, '450 mhz_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', 'frequency_5': 'frequency', '450 mhz_6': '450 mhz', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'frequency_5': [0], '450 mhz_6': [0], '2_7': [2]} | ['carrier', 'standard', 'frequency', '( down )', '( up )', 'launch date ( ddmmyyyy )'] | [['orange', 'umts hspa', '2100 mhz', '7.2 mbit / s', '2.0 mbit / s', '01.11.2008'], ['orange', 'umts hspa', '2100 mhz', '14.4 mbit / s', '5.76 mbit / s', '02.09.2009'], ['orange', 'umts hspa', '2100 mhz', '21.1 mbit / s', '5.76 mbit / s', '21.12.2009'], ['orange', 'umts hspa', '2100 mhz', '42 mbit / s', '5.76 mbit / s', '27.05.2011'], ['moldcell', 'umts hspa', '2100 mhz', '7.2 mbit / s', '2 mbit / s', '01.10.2008'], ['moldcell', 'umts hspa', '2100 mhz', '21.1 mbit / s', '5.76 mbit / s', '31.05.2011'], ['unité', 'cdma ev - do rev 0', '450 mhz', '2.4 mbit / s', '153 mbit / s', '01.03.2007'], ['unité', 'umts hspa', '2100 mhz', '14.4 mbit / s', '5.76 mbit / s', '01.03.2010'], ['idc', 'cdma ev - do rev 0', '800 mhz', '2.4 мmbit / s', '153 kbit / s', '01.03.2007'], ['idc', 'cdma ev - do rev 0', '450 mhz', '2.4 мmbit / s', '153 kbit / s', '01.03.2007'], ['idc', 'cdma ev - do rev a', '800 мгц', '3.1 mbit / s', '1.8 mbit / s', '21.03.2011']] |
2007 - 08 utah jazz season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Utah_Jazz_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11964263-5.html.csv | ordinal | the utah jazz ' game as visitors against the pistons recorded their highest attendance of the 2007 - 08 season . | {'row': '13', 'col': '6', 'order': '1', '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', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'home'], 'result': 'pistons', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; home }'}, 'pistons'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; home } ; pistons } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the home record of this row is pistons .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; home } ; pistons } = true | select the row whose attendance record of all rows is 1st maximum . the home record of this row is pistons . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'home_7': 7, 'pistons_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'home_7': 'home', 'pistons_8': 'pistons'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'home_7': [1], 'pistons_8': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['november 1', 'rockets', 'l 95 - 106 ( ot )', 'jazz', 'boozer ( 30 )', '19911', '1 - 1'], ['november 3', 'warriors', 'w 133 - 110 ( ot )', 'jazz', 'williams ( 30 )', '19911', '2 - 1'], ['november 4', 'jazz', 'l 109 - 119 ( ot )', 'lakers', 'williams ( 26 )', '18997', '2 - 2'], ['november 7', 'cavaliers', 'w 103 - 101 ( ot )', 'jazz', 'millsap ( 24 )', '19911', '3 - 2'], ['november 9', 'jazz', 'w 103 - 101 ( ot )', 'supersonics', 'boozer ( 27 )', '15980', '4 - 2'], ['november 10', 'grizzlies', 'w 118 - 94 ( ot )', 'jazz', 'boozer ( 31 )', '19771', '5 - 2'], ['november 12', 'kings', 'w 117 - 93 ( ot )', 'jazz', 'boozer ( 32 )', '19911', '6 - 2'], ['november 14', 'jazz', 'w 92 - 88 ( ot )', 'raptors', 'boozer ( 23 )', '17337', '7 - 2'], ['november 16', 'jazz', 'l 94 - 99 ( ot )', 'cavaliers', 'boozer ( 26 )', '19862', '7 - 3'], ['november 17', 'jazz', 'l 97 - 117 ( ot )', 'pacers', 'boozer ( 19 )', '12447', '7 - 4'], ['november 19', 'nets', 'w 102 - 75 ( ot )', 'jazz', 'williams ( 20 )', '19911', '8 - 4'], ['november 23', 'hornets', 'w 99 - 71 ( ot )', 'jazz', 'boozer ( 19 )', '19911', '9 - 4'], ['november 25', 'jazz', 'w 103 - 93 ( ot )', 'pistons', 'boozer ( 36 )', '22076', '10 - 4'], ['november 26', 'jazz', 'l 109 - 113 ( ot )', 'knicks', 'boozer ( 30 )', '18816', '10 - 5'], ['november 28', 'jazz', 'w 106 - 95 ( ot )', '76ers', 'boozer ( 26 )', '11006', '11 - 5'], ['november 30', 'lakers', 'w 120 - 96 ( ot )', 'jazz', 'williams ( 35 )', '19911', '12 - 5']] |
list of big brother ( uk ) shows | https://en.wikipedia.org/wiki/List_of_Big_Brother_%28UK%29_shows | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11748792-2.html.csv | majority | emma willis was the presenter for all the big brother ( uk ) shows on tuesday . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'emma willis', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'tuesday', 'emma willis'], 'result': True, 'ind': 0, 'tointer': 'for the tuesday records of all rows , most of them fuzzily match to emma willis .', 'tostr': 'most_eq { all_rows ; tuesday ; emma willis } = true'} | most_eq { all_rows ; tuesday ; emma willis } = true | for the tuesday records of all rows , most of them fuzzily match to emma willis . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tuesday_3': 3, 'emma willis_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tuesday_3': 'tuesday', 'emma willis_4': 'emma willis'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tuesday_3': [0], 'emma willis_4': [0]} | ['series', 'monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday', 'sunday'] | [['celebrity big brother 8', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['big brother 12', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['celebrity big brother 9', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['big brother 13', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['celebrity big brother 10', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['celebrity big brother 11', 'emma willis jamie east', 'emma willis', 'emma willis', 'emma willis', 'emma willis jamie east', 'alice levine jamie east', 'alice levine jamie east'], ['big brother 14', 'aj odudu rylan clark', 'emma willis', 'emma willis', 'emma willis', 'aj odudu rylan clark', 'aj odudu iain lee', 'rylan clark']] |
wru division one north | https://en.wikipedia.org/wiki/WRU_Division_One_North | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14058433-1.html.csv | aggregation | the average number of games lost between all the teams in the wru division one north rugby union league for the 2011-12 season was 9 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '9', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'lost'], 'result': '9', 'ind': 0, 'tostr': 'avg { all_rows ; lost }'}, '9'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; lost } ; 9 } = true', 'tointer': 'the average of the lost record of all rows is 9 .'} | round_eq { avg { all_rows ; lost } ; 9 } = true | the average of the lost record of all rows is 9 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'lost_4': 4, '9_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'lost_4': 'lost', '9_5': '9'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'lost_4': [0], '9_5': [1]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus'], ['caernarfon rfc', '18', '0', '3', '524', '249', '72', '32', '8', '1'], ['nant conwy rfc', '18', '0', '4', '427', '177', '62', '19', '6', '2'], ['bro ffestiniog rfc', '18', '0', '5', '437', '246', '62', '30', '6', '5'], ['bethesda rfc', '18', '0', '6', '365', '208', '47', '21', '5', '5'], ['pwllheli rfc', '18', '0', '9', '344', '251', '50', '30', '3', '6'], ['bala rfc', '18', '0', '11', '242', '318', '30', '40', '2', '3'], ['llangefni rfc', '18', '0', '10', '271', '450', '28', '63', '0', '0'], ['ruthin rfc', '18', '0', '12', '311', '346', '39', '50', '2', '5'], ['mold rfc', '18', '0', '14', '247', '416', '31', '55', '2', '4'], ['llandudno rfc', '18', '0', '16', '204', '711', '25', '106', '0', '1']] |
law & order : special victims unit | https://en.wikipedia.org/wiki/Law_%26_Order%3A_Special_Victims_Unit | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-197060-1.html.csv | ordinal | the 2nd to last season premiere for law & order : special victims unit was when the ranking was 67th . | {'row': '12', 'col': '4', 'order': '2', 'col_other': '7', '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', 'season premiere', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; season premiere ; 2 }'}, 'ranking'], 'result': '67th', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; season premiere ; 2 } ; ranking }'}, '67th'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; season premiere ; 2 } ; ranking } ; 67th } = true', 'tointer': 'select the row whose season premiere record of all rows is 2nd maximum . the ranking record of this row is 67th .'} | eq { hop { nth_argmax { all_rows ; season premiere ; 2 } ; ranking } ; 67th } = true | select the row whose season premiere record of all rows is 2nd maximum . the ranking record of this row is 67th . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'season premiere_5': 5, '2_6': 6, 'ranking_7': 7, '67th_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', 'season premiere_5': 'season premiere', '2_6': '2', 'ranking_7': 'ranking', '67th_8': '67th'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'season premiere_5': [0], '2_6': [0], 'ranking_7': [1], '67th_8': [2]} | ['season', 'episodes', 'timeslot ( est )', 'season premiere', 'season finale', 'tv season', 'ranking', 'viewers ( in millions )'] | [['1', '22', 'monday 9:00 pm ( 1999 ) friday 10:00 pm ( 2000 )', 'september 20 , 1999', 'may 19 , 2000', '1999 - 2000', '33rd', '12.18'], ['2', '21', 'friday 10:00 pm', 'october 20 , 2000', 'may 11 , 2001', '2000 - 01', '29th', '13.1'], ['3', '23', 'friday 10:00 pm', 'september 28 , 2001', 'may 17 , 2002', '2001 - 02', '14th', '15.2'], ['4', '25', 'friday 10:00 pm', 'september 27 , 2002', 'may 16 , 2003', '2002 - 03', '16th', '14.83'], ['5', '25', 'tuesday 10:00 pm', 'september 23 , 2003', 'may 18 , 2004', '2003 - 04', '21st', '12.72'], ['6', '23', 'tuesday 10:00 pm', 'september 21 , 2004', 'may 24 , 2005', '2004 - 05', '23rd', '13.46'], ['7', '22', 'tuesday 10:00 pm', 'september 20 , 2005', 'may 16 , 2006', '2005 - 06', '24th', '13.78'], ['8', '22', 'tuesday 10:00 pm', 'september 19 , 2006', 'may 22 , 2007', '2006 - 07', '38th', '11.94'], ['9', '19', 'tuesday 10:00 pm', 'september 25 , 2007', 'may 13 , 2008', '2007 - 08', '30th', '11.33'], ['10', '22', 'tuesday 10:00 pm', 'september 23 , 2008', 'june 2 , 2009', '2008 - 09', '39th', '10.11'], ['11', '24', 'wednesday 9:00 pm wednesday 10:00 pm', 'september 23 , 2009', 'may 19 , 2010', '2009 - 10', '44th', '8.81'], ['13', '23', 'wednesday 10:00 pm', 'september 21 , 2011', 'may 23 , 2012', '2011 - 12', '67th', '7.59'], ['14', '24', 'wednesday 9:00 pm', 'september 26 , 2012', 'may 22 , 2013', '2012 - 13', '56th', '7.30']] |
list of festivals at donington park | https://en.wikipedia.org/wiki/List_of_Festivals_at_Donington_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10311801-3.html.csv | unique | of these events , only ozzfest 2002 took place in 2002 . | {'scope': 'all', 'row': '3', 'col': '1', 'col_other': '3', 'criterion': 'equal', 'value': '2002', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2002'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2002 .', 'tostr': 'filter_eq { all_rows ; year ; 2002 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; year ; 2002 } }', 'tointer': 'select the rows whose year record is equal to 2002 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2002'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2002 .', 'tostr': 'filter_eq { all_rows ; year ; 2002 }'}, 'event'], 'result': 'ozzfest 2002', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 2002 } ; event }'}, 'ozzfest 2002'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 2002 } ; event } ; ozzfest 2002 }', 'tointer': 'the event record of this unqiue row is ozzfest 2002 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; year ; 2002 } } ; eq { hop { filter_eq { all_rows ; year ; 2002 } ; event } ; ozzfest 2002 } } = true', 'tointer': 'select the rows whose year record is equal to 2002 . there is only one such row in the table . the event record of this unqiue row is ozzfest 2002 .'} | and { only { filter_eq { all_rows ; year ; 2002 } } ; eq { hop { filter_eq { all_rows ; year ; 2002 } ; event } ; ozzfest 2002 } } = true | select the rows whose year record is equal to 2002 . there is only one such row in the table . the event record of this unqiue row is ozzfest 2002 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '2002_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'event_9': 9, 'ozzfest 2002_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '2002_8': '2002', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'event_9': 'event', 'ozzfest 2002_10': 'ozzfest 2002'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'year_7': [0], '2002_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'event_9': [2], 'ozzfest 2002_10': [3]} | ['year', 'date', 'event', 'days', 'stages', 'acts'] | [['2001', '23 june', 'rock & blues festival', '2 days', '1 stage', '6 bands'], ['2001', '14 july', 'a day at the races', '1 day', '1 stage', '5 bands'], ['2002', '25 may', 'ozzfest 2002', '1 day', '2 stages', '24 bands'], ['2003', '31 may - 1 june', 'download festival ft deconstruction festival', '2 days', '2 stages', '57 bands'], ['2004', '5 - 6 june', 'download festival', '2 days', '3 stages', '73 bands'], ['2005', '10 - 12 june', 'download festival with ozzfest', '3 days', '3 stages', '99 bands'], ['2006', '9 - 11 june', 'download festival', '3 days', '4 stages', '106 bands'], ['2007', '8 - 10 june', 'download festival', '3 days', '3 stages', '101 bands'], ['2008', '13 - 15 june', 'download festival', '3 days', '3 stages', '100 bands'], ['2009', '14 - 16 june', 'download festival', '3 days', '4 stages', '132 bands']] |
2008 indian premier league | https://en.wikipedia.org/wiki/2008_Indian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15734036-10.html.csv | count | a total of three players in the 2008 indian premier league had 14 inns . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '14', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'inns', '14'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose inns record fuzzily matches to 14 .', 'tostr': 'filter_eq { all_rows ; inns ; 14 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; inns ; 14 } }', 'tointer': 'select the rows whose inns record fuzzily matches to 14 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; inns ; 14 } } ; 3 } = true', 'tointer': 'select the rows whose inns record fuzzily matches to 14 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; inns ; 14 } } ; 3 } = true | select the rows whose inns record fuzzily matches to 14 . 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, 'inns_5': 5, '14_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', 'inns_5': 'inns', '14_6': '14', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'inns_5': [0], '14_6': [0], '3_7': [2]} | ['player', 'team', 'inns', 'runs', 'balls'] | [['virender sehwag', 'delhi daredevils', '14', '406', '220'], ['yusuf pathan', 'rajasthan royals', '15', '435', '243'], ['sanath jayasuriya', 'mumbai indians', '14', '514', '309'], ['yuvraj singh', 'kings xi punjab', '14', '299', '184'], ['kumar sangakkara', 'kings xi punjab', '9', '320', '198']] |
choi moon - sik | https://en.wikipedia.org/wiki/Choi_Moon-Sik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11871805-3.html.csv | count | choi moon - sik scored a total of two goals in the 1997 korea cup competition . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '1 goal', 'result': '2', 'col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': '1997 korea cup'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', '1997 korea cup'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competition ; 1997 korea cup }', 'tointer': 'select the rows whose competition record fuzzily matches to 1997 korea cup .'}, 'score', '1 goal'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose competition record fuzzily matches to 1997 korea cup . among these rows , select the rows whose score record fuzzily matches to 1 goal .', 'tostr': 'filter_eq { filter_eq { all_rows ; competition ; 1997 korea cup } ; score ; 1 goal }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; competition ; 1997 korea cup } ; score ; 1 goal } }', 'tointer': 'select the rows whose competition record fuzzily matches to 1997 korea cup . among these rows , select the rows whose score record fuzzily matches to 1 goal . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; competition ; 1997 korea cup } ; score ; 1 goal } } ; 2 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to 1997 korea cup . among these rows , select the rows whose score record fuzzily matches to 1 goal . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; competition ; 1997 korea cup } ; score ; 1 goal } } ; 2 } = true | select the rows whose competition record fuzzily matches to 1997 korea cup . among these rows , select the rows whose score record fuzzily matches to 1 goal . 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, 'competition_6': 6, '1997 korea cup_7': 7, 'score_8': 8, '1 goal_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', 'competition_6': 'competition', '1997 korea cup_7': '1997 korea cup', 'score_8': 'score', '1 goal_9': '1 goal', '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], 'competition_6': [0], '1997 korea cup_7': [0], 'score_8': [1], '1 goal_9': [1], '2_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['may 13 , 1993', 'beirut', '1 goal', '3 - 0', '1994 fifa world cup qualification'], ['may 15 , 1993', 'beirut', '1 goal', '3 - 0', '1994 fifa world cup qualification'], ['june 5 , 1993', 'seoul', '1 goal', '4 - 1', '1994 fifa world cup qualification'], ['september 27 , 1993', 'seoul', '1 goal', '1 - 0', 'friendly match'], ['august 5 , 1996', 'ho chi minh city', '1 goal', '9 - 0', '1996 afc asian cup qualification'], ['february 22 , 1997', 'hong kong', '1 goal', '2 - 0', '1998 fifa world cup qualification'], ['march 2 , 1997', 'bangkok', '1 goal', '3 - 1', '1998 fifa world cup qualification'], ['june 12 , 1997', 'seoul', '1 goal', '3 - 1', '1997 korea cup'], ['june 14 , 1997', 'suwon', '1 goal', '3 - 0', '1997 korea cup']] |
h. f. stephens | https://en.wikipedia.org/wiki/H._F._Stephens | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1152298-2.html.csv | count | three of the locomotive models designed by h. f. stephens were built for the pdswjr railway . | {'scope': 'all', 'criterion': 'equal', 'value': 'pdswjr', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'railway', 'pdswjr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose railway record fuzzily matches to pdswjr .', 'tostr': 'filter_eq { all_rows ; railway ; pdswjr }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; railway ; pdswjr } }', 'tointer': 'select the rows whose railway record fuzzily matches to pdswjr . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; railway ; pdswjr } } ; 3 } = true', 'tointer': 'select the rows whose railway record fuzzily matches to pdswjr . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; railway ; pdswjr } } ; 3 } = true | select the rows whose railway record fuzzily matches to pdswjr . 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, 'railway_5': 5, 'pdswjr_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', 'railway_5': 'railway', 'pdswjr_6': 'pdswjr', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'railway_5': [0], 'pdswjr_6': [0], '3_7': [2]} | ['railway', 'loco name', 'build date', 'wheels', 'disposal'] | [['kesr', 'tenterden', '1900', '2 - 4 - 0 t', 'scrapped 1941'], ['kesr', 'rolvenden', '1900', '2 - 4 - 0 t', 'scrapped 1941'], ['kesr', 'hecate', '1904', '0 - 8 - 0 t', 'to sr and br'], ['pdswjr', 'a s harris', '1907', '0 - 6 - 0 t', 'to sr and br'], ['pdswjr', 'earl of mount edgcumbe', '1907', '0 - 6 - 2 t', 'to sr and br'], ['pdswjr', 'lord st levan', '1907', '0 - 6 - 2t', 'to sr and br'], ['smr', 'pyramus', '1911', '0 - 6 - 2t', 'sold c1916'], ['smr', 'thisbe', '1911', '0 - 6 - 2t', 'sold c1916']] |
1953 argentine grand prix | https://en.wikipedia.org/wiki/1953_Argentine_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122075-2.html.csv | count | ferrari constructed 4 cars in the 1953 argentine grand prix . | {'scope': 'all', 'criterion': 'equal', 'value': 'ferrari', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constructor', 'ferrari'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constructor record fuzzily matches to ferrari .', 'tostr': 'filter_eq { all_rows ; constructor ; ferrari }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; constructor ; ferrari } }', 'tointer': 'select the rows whose constructor record fuzzily matches to ferrari . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; constructor ; ferrari } } ; 4 } = true', 'tointer': 'select the rows whose constructor record fuzzily matches to ferrari . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; constructor ; ferrari } } ; 4 } = true | select the rows whose constructor record fuzzily matches to ferrari . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'constructor_5': 5, 'ferrari_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'constructor_5': 'constructor', 'ferrari_6': 'ferrari', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'constructor_5': [0], 'ferrari_6': [0], '4_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['alberto ascari', 'ferrari', '97', '3:01:04.6', '1'], ['luigi villoresi', 'ferrari', '96', '+ 1 lap', '3'], ['josé froilán gonzález', 'maserati', '96', '+ 1 lap', '5'], ['mike hawthorn', 'ferrari', '96', '+ 1 lap', '6'], ['oscar alfredo gálvez', 'maserati', '96', '+ 1 lap', '9'], ['jean behra', 'gordini', '94', '+ 3 laps', '11'], ['maurice trintignant harry schell', 'gordini', '91', '+ 6 laps', '7'], ['john barber', 'cooper - bristol', '90', '+ 7 laps', '16'], ['alan brown', 'cooper - bristol', '87', '+ 10 laps', '12'], ['robert manzon', 'gordini', '67', 'wheel', '8'], ['juan manuel fangio', 'maserati', '36', 'transmission', '2'], ['felice bonetto', 'maserati', '32', 'transmission', '15'], ['nino farina', 'ferrari', '31', 'accident', '4'], ['carlos menditeguy', 'gordini', '24', 'gearbox', '10'], ['pablo birger', 'simca - gordini - gordini', '21', 'differential', '14'], ['adolfo schwelm cruz', 'cooper - bristol', '20', 'wheel', '13']] |
jet engine | https://en.wikipedia.org/wiki/Jet_engine | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15944-5.html.csv | majority | most jet engines had a specific impulse of over 1000 seconds . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'specific impulse ( s )', '1000'], 'result': True, 'ind': 0, 'tointer': 'for the specific impulse ( s ) records of all rows , most of them are greater than 1000 .', 'tostr': 'most_greater { all_rows ; specific impulse ( s ) ; 1000 } = true'} | most_greater { all_rows ; specific impulse ( s ) ; 1000 } = true | for the specific impulse ( s ) records of all rows , most of them are greater than 1000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'specific impulse (s)_3': 3, '1000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'specific impulse (s)_3': 'specific impulse ( s )', '1000_4': '1000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'specific impulse (s)_3': [0], '1000_4': [0]} | ['engine type', 'scenario', 'sfc in lb / ( lbf h )', 'sfc in g / ( kn s )', 'specific impulse ( s )', 'effective exhaust velocity ( m / s )'] | [['nk - 33 rocket engine', 'vacuum', '10.9', '309', '331', '3240'], ['ssme rocket engine', 'space shuttle vacuum', '7.95', '225', '453', '4423'], ['ramjet', 'mach 1', '4.5', '127', '800', '7877'], ['j - 58 turbojet', 'sr - 71 at mach 3.2 ( wet )', '1.9', '53.8', '1900', '18587'], ['rolls - royce / snecma olympus 593', 'concorde mach 2 cruise ( dry )', '1.195', '33.8', '3012', '29553'], ['cf6 - 80c2b1f turbofan', 'boeing 747 - 400 cruise', '0.605', '17.1', '5950', '58400'], ['general electric cf6 turbofan', 'sea level', '0.307', '8.696', '11700', '115000']] |
imperfect season | https://en.wikipedia.org/wiki/Imperfect_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14417906-6.html.csv | aggregation | imperfect season had a grand total of 212 combined losses . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '212', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'losses'], 'result': '212', 'ind': 0, 'tostr': 'sum { all_rows ; losses }'}, '212'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; losses } ; 212 } = true', 'tointer': 'the sum of the losses record of all rows is 212 .'} | round_eq { sum { all_rows ; losses } ; 212 } = true | the sum of the losses record of all rows is 212 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'losses_4': 4, '212_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'losses_4': 'losses', '212_5': '212'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'losses_4': [0], '212_5': [1]} | ['season', 'team', 'wins', 'losses', 'draws'] | [['1898', 'west adelaide', '0', '14', '0'], ['1906', 'west adelaide', '0', '12', '0'], ['1908', 'sturt', '0', '12', '0'], ['1909', 'south adelaide', '0', '12', '0'], ['1921', 'glenelg', '0', '14', '0'], ['1922', 'glenelg', '0', '14', '0'], ['1923', 'glenelg', '0', '14', '0'], ['1924', 'glenelg', '0', '14', '0'], ['1926', 'south adelaide', '0', '13', '1'], ['1933', 'west adelaide', '0', '17', '0'], ['1948', 'south adelaide', '0', '17', '0'], ['1950', 'south adelaide', '0', '17', '0'], ['1964', 'central district', '0', '20', '0'], ['1995', 'sturt', '0', '22', '0']] |
2008 - 09 nbl season | https://en.wikipedia.org/wiki/2008%E2%80%9309_NBL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16653153-20.html.csv | majority | the majority of the games held in december 13 had a crowd of at least 3000 . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '3000', 'subset': {'col': '1', 'criterion': 'equal', 'value': '13 december'}} | {'func': 'most_greater_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '13 december'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 13 december }', 'tointer': 'select the rows whose date record fuzzily matches to 13 december .'}, 'crowd', '3000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 13 december . for the crowd records of these rows , most of them are greater than or equal to 3000 .', 'tostr': 'most_greater_eq { filter_eq { all_rows ; date ; 13 december } ; crowd ; 3000 } = true'} | most_greater_eq { filter_eq { all_rows ; date ; 13 december } ; crowd ; 3000 } = true | select the rows whose date record fuzzily matches to 13 december . for the crowd records of these rows , most of them are greater than or equal to 3000 . | 2 | 2 | {'most_greater_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, '13 december_5': 5, 'crowd_6': 6, '3000_7': 7} | {'most_greater_eq_1': 'most_greater_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', '13 december_5': '13 december', 'crowd_6': 'crowd', '3000_7': '3000'} | {'most_greater_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], '13 december_5': [0], 'crowd_6': [1], '3000_7': [1]} | ['date', 'home team', 'score', 'away team', 'venue', 'crowd', 'box score', 'report'] | [['10 december', 'adelaide 36ers', '100 - 79', 'townsville crocodiles', 'distinctive homes dome', '4208', 'box score', '-'], ['13 december', 'gold coast blaze', '88 - 97', 'cairns taipans', 'gold coast convention centre', '2489', 'box score', '-'], ['13 december', 'melbourne tigers', '98 - 107', 'south dragons', 'state netball and hockey centre', '3500', 'box score', '-'], ['13 december', 'perth wildcats', '129 - 120', 'adelaide 36ers', 'challenge stadium', '4200', 'box score', '-'], ['13 december', 'townsville crocodiles', '104 - 99', 'wollongong hawks', 'townsville entertainment centre', '3913', 'box score', '-']] |
mighty ships | https://en.wikipedia.org/wiki/Mighty_Ships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26168687-3.html.csv | ordinal | " my peace in africa " was the second season of mighty ships to air . | {'row': '2', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'no in season', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; no in season ; 2 }'}, 'title'], 'result': 'mv peace in africa', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; no in season ; 2 } ; title }'}, 'mv peace in africa'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; no in season ; 2 } ; title } ; mv peace in africa } = true', 'tointer': 'select the row whose no in season record of all rows is 2nd minimum . the title record of this row is mv peace in africa .'} | eq { hop { nth_argmin { all_rows ; no in season ; 2 } ; title } ; mv peace in africa } = true | select the row whose no in season record of all rows is 2nd minimum . the title record of this row is mv peace in africa . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'no in season_5': 5, '2_6': 6, 'title_7': 7, 'mv peace in africa_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', 'no in season_5': 'no in season', '2_6': '2', 'title_7': 'title', 'mv peace in africa_8': 'mv peace in africa'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'no in season_5': [0], '2_6': [0], 'title_7': [1], 'mv peace in africa_8': [2]} | ['no in series', 'no in season', 'title', 'vessel type', 'vessel operator', 'narrated by', 'original air date'] | [['5', '1', 'mv resolution', 'turbine installation vessel', 'mpi offshore ltd', 'barbara budd', '2009'], ['6', '2', 'mv peace in africa', 'dredger', 'de beers', 'barbara budd', '2009'], ['7', '3', 'akamalik', 'fishing trawler', 'royal greenland', 'barbara budd', '2009'], ['8', '4', 'ccgs henry larsen', 'icebreaker', 'canadian coast guard', 'barbara budd', '2009'], ['9', '5', 'uss nimitz', 'supercarrier', 'us navy', 'barbara budd', '2009'], ['10', '6', 'hdms absalon', 'flexible support ship', 'royal danish navy', 'barbara budd', '2009'], ['11', '7', 'mv fairplayer', 'heavy lift vessel', 'jumbo shipping', 'barbara budd', '2009'], ['12', '8', 'tyco resolute', 'cable layer', 'tyco telecommunications', 'barbara budd', '2009']] |
fil world luge championships 1978 | https://en.wikipedia.org/wiki/FIL_World_Luge_Championships_1978 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11154705-4.html.csv | superlative | the soviet union had the most gold in the fil world luge championships of 1978 . | {'scope': 'all', 'col_superlative': '3', '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', 'gold'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gold }'}, 'nation'], 'result': 'soviet union', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gold } ; nation }'}, 'soviet union'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gold } ; nation } ; soviet union } = true', 'tointer': 'select the row whose gold record of all rows is maximum . the nation record of this row is soviet union .'} | eq { hop { argmax { all_rows ; gold } ; nation } ; soviet union } = true | select the row whose gold record of all rows is maximum . the nation record of this row is soviet union . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'nation_6': 6, 'soviet union_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'nation_6': 'nation', 'soviet union_7': 'soviet union'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'nation_6': [1], 'soviet union_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '2', '1', '0', '3'], ['2', 'west germany', '0', '2', '0', '2'], ['3', 'austria', '0', '0', '2', '2'], ['4', 'italy', '1', '0', '0', '1'], ['5', 'east germany', '0', '0', '1', '1']] |
agriculture in morocco | https://en.wikipedia.org/wiki/Agriculture_in_Morocco | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21109892-1.html.csv | superlative | wheat is the most produced commodity of the agricultural commodities of morocco . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'production ( mt )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; production ( mt ) }'}, 'commodity'], 'result': 'wheat', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; production ( mt ) } ; commodity }'}, 'wheat'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; production ( mt ) } ; commodity } ; wheat } = true', 'tointer': 'select the row whose production ( mt ) record of all rows is maximum . the commodity record of this row is wheat .'} | eq { hop { argmax { all_rows ; production ( mt ) } ; commodity } ; wheat } = true | select the row whose production ( mt ) record of all rows is maximum . the commodity record of this row is wheat . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'production (mt)_5': 5, 'commodity_6': 6, 'wheat_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'production (mt)_5': 'production ( mt )', 'commodity_6': 'commodity', 'wheat_7': 'wheat'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'production (mt)_5': [0], 'commodity_6': [1], 'wheat_7': [2]} | ['rank', 'commodity', 'value ( int 1000 )', 'production ( mt )', 'quantity world rank', 'value world rank'] | [['1', 'wheat', '939150', '6400000', '19', '17'], ['2', 'indigenous chicken meat', '635889', '446424', 'na', 'na'], ['3', 'olives', '616541', '770000', '6', '6'], ['4', 'tomatoes', '480433', '1300000', '17', '17'], ['5', 'indigenous cattle meat', '433257', '160384', 'na', 'na'], ['6', 'cow milk , whole , fresh', '409566', '1750000', 'na', 'na'], ['7', 'barley', '389709', '3800000', '12', '7'], ['8', 'indigenous sheep meat', '325935', '119706', 'na', 'na'], ['9', 'almonds , with shell', '307240', '104115', '5', '5'], ['10', 'oranges', '231910', '1200000', '14', '14'], ['11', 'potatoes', '230032', '1500000', 'na', 'na'], ['12', 'hen eggs , in shell', '221668', '267267', 'na', 'na'], ['13', 'string beans', '173716', '182180', '3', '3'], ['14', 'grapes', '171485', '300000', 'na', 'na'], ['15', 'apples', '169166', '400000', 'na', 'na'], ['16', 'strawberries', '168627', '124239', '11', '11'], ['17', 'onions , dry', '136521', '650000', '23', '23'], ['18', 'other melons ( inccantaloupes )', '134386', '730000', '8', '8'], ['19', 'tangerines , mandarins , clem', '128945', '522000', '12', '12']] |
1969 oakland raiders season | https://en.wikipedia.org/wiki/1969_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12828987-1.html.csv | aggregation | the average attendance for 1969 oakland raiders game was 48121 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '48121', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '48121', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '48121'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 48121 } = true', 'tointer': 'the average of the attendance record of all rows is 48121 .'} | round_eq { avg { all_rows ; attendance } ; 48121 } = true | the average of the attendance record of all rows is 48121 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '48121_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '48121_5': '48121'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '48121_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 14 , 1969', 'houston oilers', 'w 21 - 17', '49361'], ['2', 'september 20 , 1969', 'miami dolphins', 'w 20 - 17', '50277'], ['3', 'september 28 , 1969', 'boston patriots', 'w 38 - 23', '19069'], ['4', 'october 4 , 1969', 'miami dolphins', 't 20 - 20', '35614'], ['5', 'october 12 , 1969', 'denver broncos', 'w 24 - 14', '49511'], ['6', 'october 19 , 1969', 'buffalo bills', 'w 50 - 21', '54418'], ['7', 'october 26 , 1969', 'san diego chargers', 'w 24 - 12', '54008'], ['8', 'november 2 , 1969', 'cincinnati bengals', 'l 31 - 17', '27927'], ['9', 'november 9 , 1969', 'denver broncos', 'w 41 - 10', '54416'], ['10', 'november 16 , 1969', 'san diego chargers', 'w 21 - 16', '54372'], ['11', 'november 23 , 1969', 'kansas city chiefs', 'w 27 - 24', '51982'], ['12', 'november 30 , 1969', 'new york jets', 'w 27 - 14', '63865'], ['13', 'december 7 , 1969', 'cincinnati bengals', 'w 37 - 17', '54427'], ['14', 'december 13 , 1969', 'kansas city chiefs', 'w 10 - 6', '54443']] |
alice anum | https://en.wikipedia.org/wiki/Alice_Anum | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17786147-1.html.csv | aggregation | alice anum has an average result of about 3rd place from 1965 to 1974 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '3rd place', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'result'], 'result': '3rd place', 'ind': 0, 'tostr': 'avg { all_rows ; result }'}, '3rd place'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; result } ; 3rd place } = true', 'tointer': 'the average of the result record of all rows is 3rd place .'} | round_eq { avg { all_rows ; result } ; 3rd place } = true | the average of the result record of all rows is 3rd place . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'result_4': 4, '3rd place_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'result_4': 'result', '3rd place_5': '3rd place'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'result_4': [0], '3rd place_5': [1]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['1965', 'all - africa games', 'brazzaville , congo', '1st', 'long jump'], ['1970', 'british commonwealth games', 'edinburgh , scotland', '2nd', '100 m'], ['1970', 'british commonwealth games', 'edinburgh , scotland', '2nd', '200 m'], ['1972', 'olympic games', 'munich , germany', '6th', '100 m'], ['1972', 'olympic games', 'munich , germany', '7th', '200 m'], ['1973', 'all - africa games', 'lagos , nigeria', '1st', '100 m'], ['1973', 'all - africa games', 'lagos , nigeria', '1st', '200 m'], ['1974', 'british commonwealth games', 'christchurch , new zealand', '3rd', '200 m']] |
2002 jacksonville jaguars season | https://en.wikipedia.org/wiki/2002_Jacksonville_Jaguars_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17977772-1.html.csv | majority | in the 2002 jacksonville jaguars season , for players in a tackle position , all of them were picked before round 7 . | {'scope': 'subset', 'col': '1', 'most_or_all': 'all', 'criterion': 'less_than', 'value': '7', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'tackle'}} | {'func': 'all_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'tackle'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; tackle }', 'tointer': 'select the rows whose position record fuzzily matches to tackle .'}, 'round', '7'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to tackle . for the round records of these rows , all of them are less than 7 .', 'tostr': 'all_less { filter_eq { all_rows ; position ; tackle } ; round ; 7 } = true'} | all_less { filter_eq { all_rows ; position ; tackle } ; round ; 7 } = true | select the rows whose position record fuzzily matches to tackle . for the round records of these rows , all of them are less than 7 . | 2 | 2 | {'all_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'position_4': 4, 'tackle_5': 5, 'round_6': 6, '7_7': 7} | {'all_less_1': 'all_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'position_4': 'position', 'tackle_5': 'tackle', 'round_6': 'round', '7_7': '7'} | {'all_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'position_4': [0], 'tackle_5': [0], 'round_6': [1], '7_7': [1]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '9', '9', 'john henderson', 'defensive tackle', 'tennessee'], ['2', '8', '40', 'mike pearson', 'offensive tackle', 'florida'], ['3', '24', '89', 'akin ayodele', 'linebacker', 'purdue'], ['4', '10', '108', 'david garrard', 'quarterback', 'east carolina'], ['4', '20', '118', 'chris luzar', 'tight end', 'virginia'], ['6', '8', '180', 'clenton ballard', 'defensive tackle', 'southwest texas state'], ['7', '11', '222', 'kendall newson', 'wide receiver', 'middle tennessee state'], ['7', '36', '247', 'steve smith', 'defensive back', 'oregon'], ['7', '37', '248', 'hayden epstein', 'kicker', 'michigan']] |
list of european ultra prominent peaks | https://en.wikipedia.org/wiki/List_of_European_ultra_prominent_peaks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18918776-6.html.csv | aggregation | the average elevation for the mountains with ultra prominent peaks in europe is 2494.63 m. | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '2494.63', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'elevation ( m )'], 'result': '2494.63', 'ind': 0, 'tostr': 'avg { all_rows ; elevation ( m ) }'}, '2494.63'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; elevation ( m ) } ; 2494.63 } = true', 'tointer': 'the average of the elevation ( m ) record of all rows is 2494.63 .'} | round_eq { avg { all_rows ; elevation ( m ) } ; 2494.63 } = true | the average of the elevation ( m ) record of all rows is 2494.63 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'elevation (m)_4': 4, '2494.63_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'elevation (m)_4': 'elevation ( m )', '2494.63_5': '2494.63'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'elevation (m)_4': [0], '2494.63_5': [1]} | ['peak', 'country', 'elevation ( m )', 'prominence ( m )', 'col ( m )'] | [['mount etna', 'italy ( sicily )', '3323', '3323', '0'], ['monte cinto', 'france ( corsica )', '2706', '2706', '0'], ['corno grande', 'italy', '2912', '2476', '436'], ['punta la marmora', 'italy ( sardinia )', '1834', '1834', '0'], ['monte amaro', 'italy', '2795', '1812', '983'], ['monte dolcedorme', 'italy', '2267', '1715', '552'], ['montalto', 'italy', '1955', '1709', '246'], ['monte cimone', 'italy', '2165', '1577', '588']] |
united states house of representatives elections , 1926 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1926 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342379-10.html.csv | count | 9 of the georgia incumbents in the 1926 united states house of representatives elections were re-elected . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '9', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; result ; re - elected }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re - elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re - elected } } ; 9 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 9 } = true | select the rows whose result record fuzzily matches to re - elected . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're - elected_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're - elected_6': 're - elected', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '9_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['georgia 1', 'charles gordon edwards', 'democratic', '1924', 're - elected', 'charles gordon edwards ( d ) unopposed'], ['georgia 2', 'edward e cox', 'democratic', '1924', 're - elected', 'edward e cox ( d ) unopposed'], ['georgia 3', 'charles r crisp', 'democratic', '1912', 're - elected', 'charles r crisp ( d ) unopposed'], ['georgia 4', 'william c wright', 'democratic', '1918', 're - elected', 'william c wright ( d ) unopposed'], ['georgia 5', 'william d upshaw', 'democratic', '1918', 'lost renomination democratic hold', 'leslie jasper steele ( d ) unopposed'], ['georgia 6', 'samuel rutherford', 'democratic', '1924', 're - elected', 'samuel rutherford ( d ) unopposed'], ['georgia 7', 'gordon lee', 'democratic', '1904', 'retired democratic hold', 'malcolm c tarver ( d ) unopposed'], ['georgia 8', 'charles h brand', 'democratic', '1916', 're - elected', 'charles h brand ( d ) unopposed'], ['georgia 9', 'thomas montgomery bell', 'democratic', '1904', 're - elected', 'thomas montgomery bell ( d ) unopposed'], ['georgia 10', 'carl vinson', 'democratic', '1914', 're - elected', 'carl vinson ( d ) unopposed'], ['georgia 11', 'william c lankford', 'democratic', '1918', 're - elected', 'william c lankford ( d ) unopposed']] |
2001 senior pga tour | https://en.wikipedia.org/wiki/2001_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11603267-3.html.csv | count | five different players participated in the 2001 senior pga tour . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 5 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 5 .'} | eq { count { filter_all { all_rows ; player } } ; 5 } = true | select the rows whose player record is arbitrary . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '5_6': [2]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'allen doyle', 'united states', '2553582', '34', '2'], ['2', 'bruce fleisher', 'united states', '2411543', '31', '3'], ['3', 'hale irwin', 'united states', '2147422', '26', '3'], ['4', 'larry nelson', 'united states', '2109936', '28', '5'], ['5', 'gil morgan', 'united states', '1885871', '24', '2']] |
list of artists who reached number one on the french singles chart | https://en.wikipedia.org/wiki/List_of_artists_who_reached_number_one_on_the_French_Singles_Chart | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27441210-11.html.csv | aggregation | for the list of artists who reached number one on the french singles chart the average weeks at 1 was 4.8 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '4.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weeks at 1'], 'result': '4.8', 'ind': 0, 'tostr': 'avg { all_rows ; weeks at 1 }'}, '4.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weeks at 1 } ; 4.8 } = true', 'tointer': 'the average of the weeks at 1 record of all rows is 4.8 .'} | round_eq { avg { all_rows ; weeks at 1 } ; 4.8 } = true | the average of the weeks at 1 record of all rows is 4.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weeks at 1_4': 4, '4.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weeks at 1_4': 'weeks at 1', '4.8_5': '4.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weeks at 1_4': [0], '4.8_5': [1]} | ['artist', 'country', 'number - one single ( s )', 'year', 'weeks at 1', 'straight to 1'] | [['j - five', 'united states', 'modern times', '2004', '1', 'no'], ['jackson , jermaine', 'united states', 'when the rain begins to fall', '1984', '3', 'no'], ['jackson , michael', 'united states', 'black or white', '1991', '2', 'no'], ['jackson , michael', 'united states', 'you are not alone', '1995', '2', 'no'], ['jackson , michael', 'united states', 'you rock my world', '2001', '3', 'yes'], ['jean , wyclef', 'haiti', "hips do n't lie 1", '2006', '1', 'yes'], ['jessie j', 'united kingdom', 'price tag', '2011', '1', 'no'], ['jigulina , vika', 'romania', 'stereo love', '2009', '4', 'no'], ['jive bunny and the mastermixers', 'united kingdom', 'swing the mood', '1989', '5', 'no'], ['john , elton', 'united kingdom', 'sacrifice', '1990', '3', 'no'], ['john , elton', 'united kingdom', "do n't let the sun go down on me", '1991', '7', 'no'], ['john , elton', 'united kingdom', 'can you feel the love tonight', '1993', '10', 'no'], ['jones , michael', 'united kingdom', 'je te donne', '1985', '8', 'no'], ['jones , tom', 'united kingdom', 'sex bomb', '2000', '7', 'no'], ['jordy', 'france', "dur dur d'être bébé !", '1992', '15', 'no'], ['jordy', 'france', 'alison', '1993', '5', 'no']] |
powerade tigers all - time roster | https://en.wikipedia.org/wiki/Powerade_Tigers_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15463188-17.html.csv | aggregation | of the powerade tigers all-time roster players whose surname begins with the letter s , the median year value of the participation start years , incl . any possible restarts , is 2007 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '2007', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'season'], 'result': '2007', 'ind': 0, 'tostr': 'avg { all_rows ; season }'}, '2007'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; season } ; 2007 } = true', 'tointer': 'the average of the season record of all rows is 2007 .'} | round_eq { avg { all_rows ; season } ; 2007 } = true | the average of the season record of all rows is 2007 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'season_4': 4, '2007_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'season_4': 'season', '2007_5': '2007'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'season_4': [0], '2007_5': [1]} | ['name', 'position', 'number', 'school / club team', 'season', 'acquisition via'] | [['allan salangsang', 'forward', '24', 'letran', '2006 - 2007', 'free agency'], ['jondan salvador', 'forward / center', '5', 'saint benilde', '2012', 'trade'], ['mark sanford', 'forward / center', '3', 'washington', '2004 - 2005', 'import'], ['rodney santos', 'guard / forward', '45', 'san sebastian', '2009', 'free agency'], ['jovy sese', 'forward', '20', 'manuel luis quezon', '2002', 'free agency'], ['dale singson', 'guard', '50', 'santo tomas', '2005 - 2006 , 2009 - 2010', 'trade'], ['omar sneed', 'forward', '11', 'memphis', '2012', 'import'], ['ervin sotto', 'forward / center', '13', 'saint francis', '2007', 'trade']] |
2008 - 09 phoenix suns season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-7.html.csv | count | during the 2008 - 09 phoenix suns season 7 games at the us airways center had an attendance of 18422 . | {'scope': 'all', 'criterion': 'equal', 'value': 'us airways center 18422', 'result': '7', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'us airways center 18422'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to us airways center 18422 .', 'tostr': 'filter_eq { all_rows ; location attendance ; us airways center 18422 }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location attendance ; us airways center 18422 } }', 'tointer': 'select the rows whose location attendance record fuzzily matches to us airways center 18422 . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location attendance ; us airways center 18422 } } ; 7 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to us airways center 18422 . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; location attendance ; us airways center 18422 } } ; 7 } = true | select the rows whose location attendance record fuzzily matches to us airways center 18422 . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'us airways center 18422_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'us airways center 18422_6': 'us airways center 18422', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'us airways center 18422_6': [0], '7_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['31', 'january 2', 'la clippers', 'w 106 - 98 ( ot )', "amar ' e stoudemire ( 23 )", "shaquille o'neal ( 9 )", 'steve nash ( 11 )', 'us airways center 18422', '19 - 12'], ['32', 'january 7', 'indiana', 'l 110 - 113 ( ot )', "amar ' e stoudemire ( 23 )", 'louis amundson ( 14 )', 'steve nash ( 12 )', 'us airways center 18422', '19 - 13'], ['33', 'january 9', 'dallas', 'w 128 - 100 ( ot )', "shaquille o'neal ( 25 )", "shaquille o'neal ( 10 )", 'steve nash ( 12 )', 'us airways center 18422', '20 - 13'], ['34', 'january 11', 'la clippers', 'w 109 - 103 ( ot )', "amar ' e stoudemire ( 26 )", "shaquille o'neal ( 10 )", 'steve nash ( 12 )', 'staples center 17307', '21 - 13'], ['35', 'january 13', 'atlanta', 'w 107 - 102 ( ot )', "shaquille o'neal ( 26 )", "matt barnes , shaquille o'neal ( 10 )", 'steve nash ( 6 )', 'us airways center 18422', '22 - 13'], ['36', 'january 15', 'denver', 'l 113 - 119 ( ot )', 'grant hill ( 25 )', "grant hill , amar ' e stoudemire ( 8 )", 'steve nash ( 14 )', 'pepsi center 18073', '22 - 14'], ['37', 'january 16', 'minnesota', 'l 103 - 105 ( ot )', "shaquille o'neal , leandro barbosa ( 22 )", "shaquille o'neal ( 11 )", 'steve nash ( 6 )', 'us airways center 18422', '22 - 15'], ['38', 'january 18', 'toronto', 'w 117 - 113 ( ot )', "amar ' e stoudemire ( 31 )", 'grant hill ( 9 )', 'steve nash ( 18 )', 'air canada centre 19800', '23 - 15'], ['39', 'january 19', 'boston', 'l 87 - 104 ( ot )', "shaquille o'neal ( 16 )", "shaquille o'neal ( 11 )", 'steve nash ( 8 )', 'td banknorth garden 18624', '23 - 16'], ['40', 'january 21', 'new york', 'l 109 - 114 ( ot )', 'jason richardson ( 27 )', "shaquille o'neal ( 12 )", 'steve nash ( 19 )', 'madison square garden 19256', '23 - 17'], ['41', 'january 23', 'charlotte', 'l 76 - 98 ( ot )', "shaquille o'neal ( 20 )", "amar ' e stoudemire ( 9 )", 'steve nash ( 5 )', 'time warner cable arena 19104', '23 - 18'], ['42', 'january 25', 'atlanta', 'w 104 - 99 ( ot )', "amar ' e stoudemire ( 23 )", "shaquille o'neal ( 11 )", 'steve nash ( 13 )', 'philips arena 19153', '24 - 18'], ['43', 'january 26', 'washington', 'w 103 - 87 ( ot )', "shaquille o'neal ( 29 )", "amar ' e stoudemire ( 15 )", 'steve nash ( 15 )', 'verizon center 17344', '25 - 18'], ['44', 'january 29', 'san antonio', 'l 104 - 114 ( ot )', "amar ' e stoudemire ( 28 )", "amar ' e stoudemire , grant hill ( 10 )", 'steve nash ( 18 )', 'us airways center 18422', '25 - 19'], ['45', 'january 31', 'chicago', 'l 111 - 122 ( ot )', 'leandro barbosa ( 32 )', "shaquille o'neal ( 8 )", 'steve nash ( 10 )', 'us airways center 18422', '25 - 20']] |
2008 primera división de méxico apertura | https://en.wikipedia.org/wiki/2008_Primera_Divisi%C3%B3n_de_M%C3%A9xico_Apertura | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17329364-2.html.csv | ordinal | josé trejo was the second manager to be sacked in the 2008 primera división de méxico apertura . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date of departure', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date of departure ; 2 }'}, 'outgoing manager'], 'result': 'josé trejo', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date of departure ; 2 } ; outgoing manager }'}, 'josé trejo'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date of departure ; 2 } ; outgoing manager } ; josé trejo } = true', 'tointer': 'select the row whose date of departure record of all rows is 2nd minimum . the outgoing manager record of this row is josé trejo .'} | eq { hop { nth_argmin { all_rows ; date of departure ; 2 } ; outgoing manager } ; josé trejo } = true | select the row whose date of departure record of all rows is 2nd minimum . the outgoing manager record of this row is josé trejo . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date of departure_5': 5, '2_6': 6, 'outgoing manager_7': 7, 'josé trejo_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 departure_5': 'date of departure', '2_6': '2', 'outgoing manager_7': 'outgoing manager', 'josé trejo_8': 'josé trejo'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date of departure_5': [0], '2_6': [0], 'outgoing manager_7': [1], 'josé trejo_8': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of departure', 'incoming manager', 'date hired', 'position in table'] | [['ciudad juárez', 'sergio orduña', 'sacked', 'aug 18 , 2008', 'héctor eugui', 'aug 19 , 2008', '18th'], ['uag', 'josé trejo', 'sacked', 'sep 1 , 2008', 'miguel herrera', 'sep 2 , 2008', '8th'], ['atlas', 'miguel brindisi', 'resigned', 'sep 4 , 2008', 'darío franco', 'sep 5 , 2008', '17th'], ['puebla', 'josé sánchez', 'sacked', 'sep 17 , 2008', 'mario carrillo', 'sep 17 , 2008', '16th'], ['chiapas', 'sergio almaguer', 'sacked', 'oct 1 , 2008', 'francisco avilán', 'oct 1 , 2008', '18th'], ['necaxa', 'salvador reyes', 'sacked', 'oct 13 , 2008', 'octavio becerril', 'oct 14 , 2008', '18th']] |
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 | count | four headphones produced by the grado labs were constructed in plastic material . | {'scope': 'all', 'criterion': 'equal', 'value': 'plastic', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'construction', 'plastic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose construction record fuzzily matches to plastic .', 'tostr': 'filter_eq { all_rows ; construction ; plastic }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; construction ; plastic } }', 'tointer': 'select the rows whose construction record fuzzily matches to plastic . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; construction ; plastic } } ; 4 } = true', 'tointer': 'select the rows whose construction record fuzzily matches to plastic . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; construction ; plastic } } ; 4 } = true | select the rows whose construction record fuzzily matches to plastic . 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, 'construction_5': 5, 'plastic_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', 'construction_5': 'construction', 'plastic_6': 'plastic', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'construction_5': [0], 'plastic_6': [0], '4_7': [2]} | ['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']] |
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