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aguaclara | https://en.wikipedia.org/wiki/AguaClara | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18268930-1.html.csv | aggregation | the average design flow of all plants designed by aguaclara is 823.57 lpm . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '823.57', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'design flow ( lpm )'], 'result': '823.57', 'ind': 0, 'tostr': 'avg { all_rows ; design flow ( lpm ) }'}, '823.57'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; design flow ( lpm ) } ; 823.57 } = true', 'tointer': 'the average of the... | round_eq { avg { all_rows ; design flow ( lpm ) } ; 823.57 } = true | the average of the design flow ( lpm ) record of all rows is 823.57 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'design flow (lpm)_4': 4, '823.57_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'design flow (lpm)_4': 'design flow ( lpm )', '823.57_5': '823.57'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'design flow (lpm)_4': [0], '823.57_5': [1]} | ['location', 'partner', 'construction start', 'inauguration date', 'population served', 'design flow ( lpm )'] | [['ojojona , hon', 'app', '2006 june', '2007 july', '2000', '375'], ['tamara , hon', 'app', '2008 january', '2008 june', '3500', '720'], ['marcala , hon', 'irwa', '2007 october', '2008 july', '9000', '1900'], ['4 comunidades , hon', 'app', '2008 october', '2009 march', '2000', '375'], ['agalteca , hon', 'app', '2009 oc... |
henlopen conference | https://en.wikipedia.org/wiki/Henlopen_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-8.html.csv | aggregation | the average number of wins in the division record is approximately 3.14 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '3.14', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'division record'], 'result': '3.14', 'ind': 0, 'tostr': 'avg { all_rows ; division record }'}, '3.14'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; division record } ; 3.14 } = true', 'tointer': 'the average of the division record r... | round_eq { avg { all_rows ; division record } ; 3.14 } = true | the average of the division record record of all rows is 3.14 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'division record_4': 4, '3.14_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'division record_4': 'division record', '3.14_5': '3.14'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'division record_4': [0], '3.14_5': [1]} | ['school', 'team', 'division record', 'overall record', 'season outcome'] | [['delmar', 'wildcats', '6 - 0', '11 - 1', 'loss in div ii championship game'], ['indian river', 'indians', '5 - 1', '8 - 3', 'loss in first round of div ii playoffs'], ['woodbridge', 'blue raiders', '4 - 2', '6 - 4', 'failed to make playoffs'], ['laurel', 'bulldogs', '3 - 3', '6 - 4', 'failed to make playoffs'], ['smy... |
2006 v8 supercar championship series | https://en.wikipedia.org/wiki/2006_V8_Supercar_Championship_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20884160-1.html.csv | majority | the majority of the winner 's teams in the 2006 v8 supercar championship series is the triple eight race engineering . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'triple eight race engineering', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'team', 'triple eight race engineering'], 'result': True, 'ind': 0, 'tointer': 'for the team records of all rows , most of them fuzzily match to triple eight race engineering .', 'tostr': 'most_eq { all_rows ; team ; triple eight race engineering } = true'} | most_eq { all_rows ; team ; triple eight race engineering } = true | for the team records of all rows , most of them fuzzily match to triple eight race engineering . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team_3': 3, 'triple eight race engineering_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team_3': 'team', 'triple eight race engineering_4': 'triple eight race engineering'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team_3': [0], 'triple eight race engineering_4': [0]} | ['rd', 'race title', 'circuit', 'location', 'date', 'format', 'winner', 'team', 'report'] | [['1', 'clipsal 500 adelaide', 'adelaide street circuit', 'adelaide , south australia', '23 - 26 mar', 'two races', 'jamie whincup', 'triple eight race engineering', 'report'], ['2', 'placemakers v8 supercars', 'pukekohe park raceway', 'pukekohe , new zealand', '21 - 23 apr', 'three races', 'mark skaife', 'holden racin... |
pune suburban railway | https://en.wikipedia.org/wiki/Pune_Suburban_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29301050-1.html.csv | majority | the majority of pune suburban railway trains originate from the pune railway station . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'pune railway station', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'origin', 'pune railway station'], 'result': True, 'ind': 0, 'tointer': 'for the origin records of all rows , most of them fuzzily match to pune railway station .', 'tostr': 'most_eq { all_rows ; origin ; pune railway station } = true'} | most_eq { all_rows ; origin ; pune railway station } = true | for the origin records of all rows , most of them fuzzily match to pune railway station . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'origin_3': 3, 'pune railway station_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'origin_3': 'origin', 'pune railway station_4': 'pune railway station'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'origin_3': [0], 'pune railway station_4': [0]} | ['train number', 'train name', 'departure pune', 'arrival lonavla', 'frequency', 'origin'] | [['99804', 'lonavala local', '04:45', '06:05', 'daily', 'pune railway station'], ['99806', 'lonavala local', '05:45', '07:05', 'daily', 'pune railway station'], ['99808', 'lonavala local', '06:30', '07:50', 'daily', 'pune railway station'], ['99810', 'lonavala local', '08:05', '10:25', 'daily', 'pune railway station'],... |
list of are you afraid of the dark ? episodes | https://en.wikipedia.org/wiki/List_of_Are_You_Afraid_of_the_Dark%3F_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10470082-4.html.csv | majority | tucker told the most stories during this list of are you afraid of the dark episodes . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'tucker', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'storyteller', 'tucker'], 'result': True, 'ind': 0, 'tointer': 'for the storyteller records of all rows , most of them fuzzily match to tucker .', 'tostr': 'most_eq { all_rows ; storyteller ; tucker } = true'} | most_eq { all_rows ; storyteller ; tucker } = true | for the storyteller records of all rows , most of them fuzzily match to tucker . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'storyteller_3': 3, 'tucker_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'storyteller_3': 'storyteller', 'tucker_4': 'tucker'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'storyteller_3': [0], 'tucker_4': [0]} | ['no', '-', 'title', 'director', 'writer', 'us air date', 'storyteller', 'villains'] | [['27', '1', 'the tale of the midnight ride', 'd j machale', 'darren kotania', 'january 8 , 1994', 'tucker', 'brad & the headless horseman'], ['28', '2', 'the tale of apartment 214', 'scott peters', 'scott peters', 'january 15 , 1994', 'kiki', 'none'], ['29', '3', "the tale of watcher 's woods", 'david winning', 'grego... |
2006 pga championship | https://en.wikipedia.org/wiki/2006_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12475284-6.html.csv | unique | mike weir was the only player from canada in the 2006 pga championship . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; country ; canada }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; country ; canada } } ; eq { hop { filter_eq { all_rows ; country ; canada } ; player } ; mike weir } } = true | select the rows whose country record fuzzily matches to canada . there is only one such row in the table . the player record of this unqiue row is mike weir . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'canada_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'mike weir_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'canada_8': 'canada', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'mike weir_10': 'mike weir'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'canada_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'mike weir_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'tiger woods', 'united states', '69 + 68 + 65 = 202', '- 14'], ['t1', 'luke donald', 'england', '68 + 68 + 66 = 202', '- 14'], ['3', 'mike weir', 'canada', '72 + 67 + 65 = 204', '- 12'], ['4', 'geoff ogilvy', 'australia', '69 + 68 + 68 = 205', '- 11'], ['t5', 'shaun micheel', 'united states', '69 + 70 + 67 = 20... |
1978 kansas city chiefs season | https://en.wikipedia.org/wiki/1978_Kansas_City_Chiefs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12536374-2.html.csv | comparative | the game against the cincinnati bengals had a higher attendance than the game against the houston oilers . | {'row_1': '1', 'row_2': '2', 'col': '5', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'cincinnati bengals'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to cincinnati bengals .', 'tostr': 'filter_eq { all_rows ; opponent ; cincinnati bengals... | greater { hop { filter_eq { all_rows ; opponent ; cincinnati bengals } ; attendance } ; hop { filter_eq { all_rows ; opponent ; houston oilers } ; attendance } } = true | select the rows whose opponent record fuzzily matches to cincinnati bengals . take the attendance record of this row . select the rows whose opponent record fuzzily matches to houston oilers . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'cincinnati bengals_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'houston oilers_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'cincinnati bengals_8': 'cincinnati bengals', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', ... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'cincinnati bengals_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'houston oilers_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 3 , 1978', 'cincinnati bengals', 'w 24 - 23', '41810'], ['2', 'september 10 , 1978', 'houston oilers', 'l 20 - 17', '40213'], ['3', 'september 17 , 1978', 'new york giants', 'l 26 - 10', '70546'], ['4', 'september 24 , 1978', 'denver broncos', 'l 23 - 17', '60593'], ['5', 'october 1 , 1978', 'buffalo ... |
list of best - selling music artists | https://en.wikipedia.org/wiki/List_of_best-selling_music_artists | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1291598-3.html.csv | comparative | best - selling music artist dire straits had less claimed sales than barbra streisand . | {'row_1': '16', 'row_2': '8', 'col': '6', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'dire straits'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose artist record fuzzily matches to dire straits .', 'tostr': 'filter_eq { all_rows ; artist ; dire straits }'}, 'claimed sales'], 're... | less { hop { filter_eq { all_rows ; artist ; dire straits } ; claimed sales } ; hop { filter_eq { all_rows ; artist ; barbra streisand } ; claimed sales } } = true | select the rows whose artist record fuzzily matches to dire straits . take the claimed sales record of this row . select the rows whose artist record fuzzily matches to barbra streisand . take the claimed sales 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, 'artist_7': 7, 'dire straits_8': 8, 'claimed sales_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'artist_11': 11, 'barbra streisand_12': 12, 'claimed sales_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', 'artist_7': 'artist', 'dire straits_8': 'dire straits', 'claimed sales_9': 'claimed sales', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'artist_11': 'ar... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'artist_7': [0], 'dire straits_8': [0], 'claimed sales_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'artist_11': [1], 'barbra streisand_12': [1], 'claimed sales_13': [3]} | ['artist', 'country of origin', 'period active', 'release - year of first charted record', 'genre', 'claimed sales'] | [['eagles', 'united states', '1971 - present', '1972', 'soft rock / country rock', '150 million'], ['rihanna', 'barbados united states', '2005 - present', '2005', 'r & b / pop / dance / hip - hop', '150 million'], ['u2', 'ireland', '1976 - present', '1980', 'rock', '150 million'], ['billy joel', 'united states', '1964 ... |
inside business | https://en.wikipedia.org/wiki/Inside_Business | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10888144-1.html.csv | majority | the majority of inside business seasons had a length of at least 40 episodes . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '40', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'episodes', '40'], 'result': True, 'ind': 0, 'tointer': 'for the episodes records of all rows , most of them are greater than or equal to 40 .', 'tostr': 'most_greater_eq { all_rows ; episodes ; 40 } = true'} | most_greater_eq { all_rows ; episodes ; 40 } = true | for the episodes records of all rows , most of them are greater than or equal to 40 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'episodes_3': 3, '40_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'episodes_3': 'episodes', '40_4': '40'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'episodes_3': [0], '40_4': [0]} | ['season no', 'season start', 'season end', 'episodes', 'host'] | [['1', '4 august 2002', '8 december 2002', '19', 'alan kohler'], ['2', '9 february 2003', '30 november 2003', '41', 'alan kohler'], ['3', '15 february 2004', '5 december 2004', '41', 'alan kohler'], ['4', '13 february 2005', '4 december 2005', '42', 'alan kohler'], ['5', '12 february 2006', '10 december 2006', '43', 'a... |
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 | comparative | mike logan was drafted in an earlier round by the jacksonville jaguars than jon hesse . | {'row_1': '2', 'row_2': '7', 'col': '1', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'mike logan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to mike logan .', 'tostr': 'filter_eq { all_rows ; name ; mike logan }'}, 'round'], 'result': None, 'ind': ... | less { hop { filter_eq { all_rows ; name ; mike logan } ; round } ; hop { filter_eq { all_rows ; name ; jon hesse } ; round } } = true | select the rows whose name record fuzzily matches to mike logan . take the round record of this row . select the rows whose name record fuzzily matches to jon hesse . take the round record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'mike logan_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'jon hesse_12': 12, 'round_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'mike logan_8': 'mike logan', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'jon hesse_12': 'jon ... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'mike logan_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'jon hesse_12': [1], 'round_13': [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', 'sout... |
2011 british gt season | https://en.wikipedia.org/wiki/2011_British_GT_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30062172-3.html.csv | unique | round five was the only time that chris goodwin and andrew kirkaldy had the pole position . | {'scope': 'all', 'row': '10', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'chris goodwin andrew kirkaldy', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pole position', 'chris goodwin andrew kirkaldy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pole position record fuzzily matches to chris goodwin andrew kirkaldy .', 'tostr': 'filter_eq { all_rows ; pole... | and { only { filter_eq { all_rows ; pole position ; chris goodwin andrew kirkaldy } } ; eq { hop { filter_eq { all_rows ; pole position ; chris goodwin andrew kirkaldy } ; round } ; 5 } } = true | select the rows whose pole position record fuzzily matches to chris goodwin andrew kirkaldy . there is only one such row in the table . the round record of this unqiue row is 5 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'pole position_7': 7, 'chris goodwin andrew kirkaldy_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'round_9': 9, '5_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'pole position_7': 'pole position', 'chris goodwin andrew kirkaldy_8': 'chris goodwin andrew kirkaldy', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'round_9': 'round', '5_10': '5'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'pole position_7': [0], 'chris goodwin andrew kirkaldy_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'round_9': [2], '5_10': [3]} | ['round', 'circuit', 'date', 'length', 'pole position', 'gt3 winner', 'gt4 winner'] | [['1', 'oulton park', '25 april', '60 mins', 'no 5 scuderia vittoria', 'no 1 trackspeed', 'no 44 abg motorsport'], ['1', 'oulton park', '25 april', '60 mins', 'charles bateman michael lyons', 'david ashburn richard westbrook', 'peter belshaw marcus clutton'], ['2', 'oulton park', '25 april', '60 mins', 'no 1 trackspeed... |
henlopen conference | https://en.wikipedia.org/wiki/Henlopen_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-5.html.csv | aggregation | the teams in the henlopen conference have a combined total overall record of 31-31 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '31-31', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'overall record'], 'result': '31-31', 'ind': 0, 'tostr': 'sum { all_rows ; overall record }'}, '31-31'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; overall record } ; 31-31 } = true', 'tointer': 'the sum of the overall record record... | round_eq { sum { all_rows ; overall record } ; 31-31 } = true | the sum of the overall record record of all rows is 31-31 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'overall record_4': 4, '31-31_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'overall record_4': 'overall record', '31-31_5': '31-31'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'overall record_4': [0], '31-31_5': [1]} | ['school', 'team', 'division record', 'overall record', 'season outcome'] | [['dover', 'senators', '5 - 0', '8 - 3', 'loss in first round of div i playoffs'], ['caesar rodney', 'riders', '3 - 2', '4 - 6', 'failed to make playoffs'], ['sussex central', 'golden knights', '2 - 3', '6 - 5', 'loss in first round of div i playoffs'], ['sussex tech', 'ravens', '2 - 3', '5 - 5', 'failed to make playof... |
the new adventures of old christine ( season 1 ) | https://en.wikipedia.org/wiki/The_New_Adventures_of_Old_Christine_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27910411-1.html.csv | count | adam barr was the writer or co-writer for three episodes . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'adam barr', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'adam barr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to adam barr .', 'tostr': 'filter_eq { all_rows ; written by ; adam barr }'}], 'result': '3', 'ind':... | eq { count { filter_eq { all_rows ; written by ; adam barr } } ; 3 } = true | select the rows whose written by record fuzzily matches to adam barr . 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, 'written by_5': 5, 'adam barr_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', 'written by_5': 'written by', 'adam barr_6': 'adam barr', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'adam barr_6': [0], '3_7': [2]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['1', 'pilot', 'andy ackerman', 'kari lizer', 'march 13 , 2006', '12.36'], ['2', 'supertramp', 'andy ackerman', 'teleplay : jeff astrof story : kari lizer', 'march 13 , 2006', '15.09'], ['3', 'open water', 'andy ackerman', 'adam barr', 'march 20 , 2006', '15.13'], ['4', 'one toe over the line , sweet jesus', 'andy ack... |
mañana es para siempre | https://en.wikipedia.org/wiki/Ma%C3%B1ana_es_para_siempre | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18498743-1.html.csv | ordinal | croatia is the second newest country to begin showing episodes of mañana es para siempre . | {'row': '5', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'june 14 , 2009', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; june 14 , 2009 ; 2 }'}, 'mexico'], 'result': 'croatia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; june 14 , 2009 ; 2 } ; mexico... | eq { hop { nth_argmax { all_rows ; june 14 , 2009 ; 2 } ; mexico } ; croatia } = true | select the row whose june 14 , 2009 record of all rows is 2nd maximum . the mexico record of this row is croatia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'june 14 , 2009_5': 5, '2_6': 6, 'mexico_7': 7, 'croatia_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', 'june 14 , 2009_5': 'june 14 , 2009', '2_6': '2', 'mexico_7': 'mexico', 'croatia_8': 'croatia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'june 14 , 2009_5': [0], '2_6': [0], 'mexico_7': [1], 'croatia_8': [2]} | ['mexico', 'mañana es para siempre', 'el canal de las estrellas', 'october 20 , 2008', 'june 14 , 2009', 'monday to friday'] | [['argentina', 'mañana es para siempre', 'canal 9', 'november 10 , 2011', 'march 16 , 2012', 'monday to friday'], ['bulgaria', 'утре и завинаги', 'diema family', 'january 11 , 2010', 'april 30 , 2010', 'monday to friday'], ['bosnia and herzegovina', 'ljubav je večna', 'pink bh', 'december 3 , 2009', 'may 29 , 2010', 'm... |
arkansas highway 60 | https://en.wikipedia.org/wiki/Arkansas_Highway_60 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18506777-1.html.csv | majority | most of the listed arkansas highway 60 locations are in the perry county . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'perry', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'county', 'perry'], 'result': True, 'ind': 0, 'tointer': 'for the county records of all rows , most of them fuzzily match to perry .', 'tostr': 'most_eq { all_rows ; county ; perry } = true'} | most_eq { all_rows ; county ; perry } = true | for the county records of all rows , most of them fuzzily match to perry . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'county_3': 3, 'perry_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'county_3': 'county', 'perry_4': 'perry'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'county_3': [0], 'perry_4': [0]} | ['county', 'location', 'distance', 'total', 'notes'] | [['faulkner', 'conway', '0.0', '0.0', 'eastern terminus'], ['faulkner', 'conway', '1.5', '1.5', '1.8 mile spur to office of emergency services'], ['line', 'county line', '5.5', '7.0', 'toad suck ferry lock & dam'], ['perry', 'bigelow', '7.7', '14.7', 'converge with ar 113'], ['perry', 'houston', '3.8', '18.5', 'north e... |
list of csi : ny characters | https://en.wikipedia.org/wiki/List_of_CSI%3A_NY_characters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11240028-1.html.csv | comparative | on csi : ny , mac taylor appeared in more episodes than jo danville . | {'row_1': '1', 'row_2': '2', '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', 'character', 'mac taylor csi detective'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose character record fuzzily matches to mac taylor csi detective .', 'tostr': 'filter_eq { all_rows ; character ; mac... | greater { hop { filter_eq { all_rows ; character ; mac taylor csi detective } ; episodes } ; hop { filter_eq { all_rows ; character ; jo danville csi detective } ; episodes } } = true | select the rows whose character record fuzzily matches to mac taylor csi detective . take the episodes record of this row . select the rows whose character record fuzzily matches to jo danville csi detective . take the episodes 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, 'character_7': 7, 'mac taylor csi detective_8': 8, 'episodes_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'character_11': 11, 'jo danville csi detective_12': 12, 'episodes_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', 'character_7': 'character', 'mac taylor csi detective_8': 'mac taylor csi detective', 'episodes_9': 'episodes', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'a... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'character_7': [0], 'mac taylor csi detective_8': [0], 'episodes_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'character_11': [1], 'jo danville csi detective_12': [1], 'episodes_13': [3]} | ['character', 'portrayed by', 'first appearance', 'last appearance', 'duration', 'episodes'] | [['mac taylor csi detective', 'gary sinise', 'blink 1 , 2 , 3', 'today is life', '1.01 - 9.17', '197'], ['jo danville csi detective', 'sela ward', 'the 34th floor', 'today is life', '7.01 - 9.17', '57'], ['danny messer csi detective', 'carmine giovinazzo', 'blink 1', 'today is life', '1.01 - 9.17', '197'], ['lindsay mo... |
texas 's 5th congressional district | https://en.wikipedia.org/wiki/Texas%27s_5th_congressional_district | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140249-1.html.csv | unique | george washington jones was the only greenback to have served the 5th district . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'greenback', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'greenback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to greenback .', 'tostr': 'filter_eq { all_rows ; party ; greenback }'}], 'result': True, 'ind': 1, 'tostr': '... | and { only { filter_eq { all_rows ; party ; greenback } } ; eq { hop { filter_eq { all_rows ; party ; greenback } ; name } ; george washington jones } } = true | select the rows whose party record fuzzily matches to greenback . there is only one such row in the table . the name record of this unqiue row is george washington jones . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'party_7': 7, 'greenback_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'george washington jones_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'party_7': 'party', 'greenback_8': 'greenback', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'george washington jones_10': 'george washington jones'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'party_7': [0], 'greenback_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'george washington jones_10': [3]} | ['name', 'took office', 'left office', 'party', 'district residence'] | [['district created march 4 , 1875', 'district created march 4 , 1875', 'district created march 4 , 1875', 'district created march 4 , 1875', 'district created march 4 , 1875'], ['john hancock', 'march 4 , 1875', 'march 3 , 1877', 'democrat', 'austin'], ['dewitt clinton giddings', 'march 4 , 1877', 'march 3 , 1879', 'd... |
wyfk | https://en.wikipedia.org/wiki/WYFK | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14369924-1.html.csv | comparative | call sign w269ax broadcasts on a higher frequency than call sign w230av for wyfk radio . | {'row_1': '2', 'row_2': '1', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'call sign', 'w269ax'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose call sign record fuzzily matches to w269ax .', 'tostr': 'filter_eq { all_rows ; call sign ; w269ax }'}, 'frequency mhz'], 'result':... | greater { hop { filter_eq { all_rows ; call sign ; w269ax } ; frequency mhz } ; hop { filter_eq { all_rows ; call sign ; w230av } ; frequency mhz } } = true | select the rows whose call sign record fuzzily matches to w269ax . take the frequency mhz record of this row . select the rows whose call sign record fuzzily matches to w230av . take the frequency mhz record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'call sign_7': 7, 'w269ax_8': 8, 'frequency mhz_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'call sign_11': 11, 'w230av_12': 12, 'frequency mhz_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'call sign_7': 'call sign', 'w269ax_8': 'w269ax', 'frequency mhz_9': 'frequency mhz', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'call sign_11': ... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'call sign_7': [0], 'w269ax_8': [0], 'frequency mhz_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'call sign_11': [1], 'w230av_12': [1], 'frequency mhz_13': [3]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['w230av', '93.9 fm', 'gadsden , alabama', '10', 'd', 'fcc'], ['w269ax', '101.7 fm', 'anniston , alabama', '10', 'd', 'fcc'], ['w273ae', '102.5 fm', 'albany , georgia', '55', 'd', 'fcc'], ['w282ae', '104.3 fm', 'macon , georgia', '27', 'd', 'fcc'], ['w290ag', '105.9 fm', 'griffin , georgia', '27', 'd', 'fcc']] |
list of highest mountain peaks in washington | https://en.wikipedia.org/wiki/List_of_highest_mountain_peaks_in_Washington | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19716903-1.html.csv | superlative | mount rainier has the highest isolation of all the highest mountain peaks in washington . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'isolation'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; isolation }'}, 'mountain peak'], 'result': 'mount rainier', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; isolation } ; mountain peak }'}, 'mount rainier... | eq { hop { argmax { all_rows ; isolation } ; mountain peak } ; mount rainier } = true | select the row whose isolation record of all rows is maximum . the mountain peak record of this row is mount rainier . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'isolation_5': 5, 'mountain peak_6': 6, 'mount rainier_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'isolation_5': 'isolation', 'mountain peak_6': 'mountain peak', 'mount rainier_7': 'mount rainier'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'isolation_5': [0], 'mountain peak_6': [1], 'mount rainier_7': [2]} | ['rank', 'mountain peak', 'mountain range', 'elevation', 'prominence', 'isolation'] | [['1', 'mount rainier', 'cascade range', '4393.293 = 14411feet 4392 m', '4027.439 = 13211feet 4027 m', '01175.46 = 730.4 miles 1175.5 km'], ['2', 'mount adams', 'cascade range', '3742.988 = 12277feet 3743 m', '2474.390 = 8116feet 2474 m', '00075.14 = 46.7 miles 75.1 km'], ['3', 'mount baker', 'cascade range', '3285.976... |
shaun murphy ( snooker player ) | https://en.wikipedia.org/wiki/Shaun_Murphy_%28snooker_player%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1795208-5.html.csv | count | there were 2 appearances in the world snooker championship . | {'scope': 'all', 'criterion': 'equal', 'value': 'world snooker championship', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'championship', 'world snooker championship'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose championship record fuzzily matches to world snooker championship .', 'tostr': 'filter_eq { all_rows ; championship... | eq { count { filter_eq { all_rows ; championship ; world snooker championship } } ; 2 } = true | select the rows whose championship record fuzzily matches to world snooker championship . 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, 'championship_5': 5, 'world snooker championship_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', 'championship_5': 'championship', 'world snooker championship_6': 'world snooker championship', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'championship_5': [0], 'world snooker championship_6': [0], '2_7': [2]} | ['outcome', 'year', 'championship', 'opponent in the final', 'score'] | [['winner', '2005', 'world snooker championship', 'matthew stevens', '18 - 16'], ['runner - up', '2006', 'welsh open', 'stephen lee', '4 - 9'], ['winner', '2007', 'malta cup', 'ryan day', '9 - 4'], ['runner - up', '2008', 'china open', 'stephen maguire', '9 - 10'], ['winner', '2008', 'uk championship', 'marco fu', '10 ... |
indianapolis colts draft history | https://en.wikipedia.org/wiki/Indianapolis_Colts_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13312898-55.html.csv | count | the indianapolis colts drafted a total of three players from ohio state college . | {'scope': 'all', 'criterion': 'equal', 'value': 'ohio state', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'ohio state'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to ohio state .', 'tostr': 'filter_eq { all_rows ; college ; ohio state }'}], 'result': '3', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; college ; ohio state } } ; 3 } = true | select the rows whose college record fuzzily matches to ohio state . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'college_5': 5, 'ohio state_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'college_5': 'college', 'ohio state_6': 'ohio state', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college_5': [0], 'ohio state_6': [0], '3_7': [2]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '32', '32', 'anthony gonzalez', 'wide receiver', 'ohio state'], ['2', '10', '42', 'tony ugoh', 'offensive tackle', 'arkansas'], ['3', '31', '95', 'daymeion hughes', 'cornerback', 'california'], ['3', '34', '98', 'quinn pitcock', 'defensive tackle', 'ohio state'], ['4', '32', '131', 'brannon condren', 'safety', '... |
shweta mohan | https://en.wikipedia.org/wiki/Shweta_Mohan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18550192-2.html.csv | comparative | nee maatalo was released before the song hey po was released . | {'row_1': '4', 'row_2': '8', 'col': '1', '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', 'song title', 'nee maatalo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose song title record fuzzily matches to nee maatalo .', 'tostr': 'filter_eq { all_rows ; song title ; nee maatalo }'}, 'year'], 're... | less { hop { filter_eq { all_rows ; song title ; nee maatalo } ; year } ; hop { filter_eq { all_rows ; song title ; hey po } ; year } } = true | select the rows whose song title record fuzzily matches to nee maatalo . take the year record of this row . select the rows whose song title record fuzzily matches to hey po . take the year 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, 'song title_7': 7, 'nee maatalo_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'song title_11': 11, 'hey po_12': 12, 'year_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', 'song title_7': 'song title', 'nee maatalo_8': 'nee maatalo', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'song title_11': 'song title... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'song title_7': [0], 'nee maatalo_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'song title_11': [1], 'hey po_12': [1], 'year_13': [3]} | ['year', 'song title', 'film', 'co - singer', 'music - director'] | [['2010', 'amma thale', 'puli ( soundtrack )', 'naresh iyer', 'a r rahman'], ['2010', 'piliche', 'khaleja', 'hemachandra', 'mani sharma'], ['2010', 'boom boom robo ra', 'enthiran', 'tanvi shah', 'a r rahman'], ['2011', 'nee maatalo', '180 ( 2011 indian film )', 'karthik', 'sharreth'], ['2012', 'dil se', 'gabbar singh (... |
1989 cleveland browns season | https://en.wikipedia.org/wiki/1989_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10650760-1.html.csv | aggregation | during the 1989 cleveland browns season , the average game attendance was about 68,559 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '68,559', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '68,559', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '68,559'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 68,559 } = true', 'tointer': 'the average of the attendance record of all r... | round_eq { avg { all_rows ; attendance } ; 68,559 } = true | the average of the attendance record of all rows is 68,559 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '68,559_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '68,559_5': '68,559'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '68,559_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 10 , 1989', 'pittsburgh steelers', 'w 51 - 0', '57928'], ['2', 'september 17 , 1989', 'new york jets', 'w 38 - 24', '73516'], ['3', 'september 25 , 1989', 'cincinnati bengals', 'l 21 - 14', '55996'], ['4', 'october 1 , 1989', 'denver broncos', 'w 16 - 13', '78637'], ['5', 'october 8 , 1989', 'miami do... |
1972 nhl amateur draft | https://en.wikipedia.org/wiki/1972_NHL_Amateur_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1473672-1.html.csv | majority | all of the players selected in the top 16 picks of the 1972 nhl amateur draft were from canada . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'canada', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to canada .', 'tostr': 'all_eq { all_rows ; nationality ; canada } = true'} | all_eq { all_rows ; nationality ; canada } = true | for the nationality records of all rows , all of them fuzzily match to canada . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'canada_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'canada_4': 'canada'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'canada_4': [0]} | ['pick', 'player', 'position', 'nationality', 'nhl team', 'college / junior / club team'] | [['1', 'billy harris', 'right wing', 'canada', 'new york islanders', 'toronto marlboros ( ohl )'], ['2', 'jacques richard', 'left wing', 'canada', 'atlanta flames', 'quebec remparts ( qmjhl )'], ['3', 'don lever', 'centre', 'canada', 'vancouver canucks', 'niagara falls flyers ( omjhl )'], ['4', 'steve shutt', 'left win... |
gulf coast athletic conference | https://en.wikipedia.org/wiki/Gulf_Coast_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10577579-2.html.csv | aggregation | the average enrollment of all institutions in the gulf coast athletic conference is 1128.5 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '1128.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '1128.5', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '1128.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 1128.5 } = true', 'tointer': 'the average of the enrollment record of all r... | round_eq { avg { all_rows ; enrollment } ; 1128.5 } = true | the average of the enrollment record of all rows is 1128.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '1128.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '1128.5_5': '1128.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '1128.5_5': [1]} | ['institution', 'location', 'mens nickname', 'womens nickname', 'founded', 'type', 'enrollment', 'joined'] | [['dillard university', 'new orleans , louisiana', 'bleu devils', 'lady bleu devils', '1869', 'private / ( methodist & church of christ )', '900', '1981'], ['edward waters college', 'jacksonville , florida', 'tigers', 'lady tigers', '1866', 'private / ( african methodist )', '800', '2010'], ['fisk university', 'nashvil... |
jak oni śpiewają | https://en.wikipedia.org/wiki/Jak_oni_%C5%9Bpiewaj%C4%85 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11680517-4.html.csv | unique | season 4 of jak oni śpiewają is the only season that had fifteen stars . | {'scope': 'all', 'row': '4', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '15', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'of stars', '15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose of stars record is equal to 15 .', 'tostr': 'filter_eq { all_rows ; of stars ; 15 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_... | and { only { filter_eq { all_rows ; of stars ; 15 } } ; eq { hop { filter_eq { all_rows ; of stars ; 15 } ; season } ; 4 - autumn 2008 } } = true | select the rows whose of stars record is equal to 15 . there is only one such row in the table . the season record of this unqiue row is 4 - autumn 2008 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'of stars_7': 7, '15_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '4 - autumn 2008_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'of stars_7': 'of stars', '15_8': '15', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '4 - autumn 2008_10': '4 - autumn 2008'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'of stars_7': [0], '15_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '4 - autumn 2008_10': [3]} | ['season', 'of stars', 'of weeks', 'season premiere date', 'season finale date', 'winner', 'runner - up', 'third place'] | [['1 - spring 2007', '13', '13', 'march 16 , 2007', 'june 2 , 2007', 'agnieszka włodarczyk', 'natasza urbańska', 'robert moskwa'], ['2 - autumn 2007', '13', '13', 'september 8 , 2007', 'december 15 , 2007', 'joanna liszowska', 'piotr polk', 'patricia kazadi'], ['3 - spring 2008', '13', '13', 'march 8 , 2008', 'may 31 ,... |
1979 miami dolphins season | https://en.wikipedia.org/wiki/1979_Miami_Dolphins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18847736-2.html.csv | ordinal | the miami dolphins scored the 2nd highest number of points during the game on sept 23 . | {'row': '4', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'dolphins points', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; dolphins points ; 2 }'}, 'date'], 'result': 'sept 23', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; dolphins points ; 2 } ; date ... | eq { hop { nth_argmax { all_rows ; dolphins points ; 2 } ; date } ; sept 23 } = true | select the row whose dolphins points record of all rows is 2nd maximum . the date record of this row is sept 23 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'dolphins points_5': 5, '2_6': 6, 'date_7': 7, 'sept 23_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', 'dolphins points_5': 'dolphins points', '2_6': '2', 'date_7': 'date', 'sept 23_8': 'sept 23'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'dolphins points_5': [0], '2_6': [0], 'date_7': [1], 'sept 23_8': [2]} | ['game', 'date', 'opponent', 'result', 'dolphins points', 'opponents', 'record', 'attendance'] | [['1', 'sept 2', 'buffalo bills', 'win', '9', '7', '1 - 0', '69441'], ['2', 'sept 9', 'seattle seahawks', 'win', '19', '10', '2 - 0', '56233'], ['3', 'sept 16', 'minnesota vikings', 'win', '27', '12', '3 - 0', '46187'], ['4', 'sept 23', 'chicago bears', 'win', '31', '16', '4 - 0', '66011'], ['5', 'sept 30', 'new york j... |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-18.html.csv | unique | in the 1941 vfl season , when the crowd was under 15000 , the only time the venue was lake oval was when the home team was south melbourne . | {'scope': 'subset', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'lake oval', 'subset': {'col': '6', 'criterion': 'less_than', 'value': '15000'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '15000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; crowd ; 15000 }', 'tointer': 'select the rows whose crowd record is less than 15000 .'}, 'venue', 'lake oval'... | and { only { filter_eq { filter_less { all_rows ; crowd ; 15000 } ; venue ; lake oval } } ; eq { hop { filter_eq { filter_less { all_rows ; crowd ; 15000 } ; venue ; lake oval } ; home team } ; south melbourne } } = true | select the rows whose crowd record is less than 15000 . among these rows , select the rows whose venue record fuzzily matches to lake oval . there is only one such row in the table . the home team record of this unqiue row is south melbourne . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_less_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '15000_9': 9, 'venue_10': 10, 'lake oval_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'home team_12': 12, 'south melbourne_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_0': 'filter_less', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '15000_9': '15000', 'venue_10': 'venue', 'lake oval_11': 'lake oval', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'home team_12': 'home team', 'south... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_less_0': [1], 'all_rows_7': [0], 'crowd_8': [0], '15000_9': [0], 'venue_10': [1], 'lake oval_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'home team_12': [3], 'south melbourne_13': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '16.14 ( 110 )', 'st kilda', '13.17 ( 95 )', 'western oval', '7000', '30 august 1941'], ['carlton', '16.17 ( 113 )', 'melbourne', '11.22 ( 88 )', 'princes park', '29000', '30 august 1941'], ['south melbourne', '7.12 ( 54 )', 'hawthorn', '11.17 ( 83 )', 'lake oval', '3000', '30 august 1941'], ['richmond',... |
comparison of amd chipsets | https://en.wikipedia.org/wiki/Comparison_of_AMD_chipsets | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12341355-5.html.csv | ordinal | the sb700 codename series was the second earliest released amd chipset . | {'row': '2', 'col': '3', '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', 'released', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; released ; 2 }'}, 'codename'], 'result': 'sb700', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; released ; 2 } ; codename }'}, 'sb700'], ... | eq { hop { nth_argmin { all_rows ; released ; 2 } ; codename } ; sb700 } = true | select the row whose released record of all rows is 2nd minimum . the codename record of this row is sb700 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'released_5': 5, '2_6': 6, 'codename_7': 7, 'sb700_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', 'released_5': 'released', '2_6': '2', 'codename_7': 'codename', 'sb700_8': 'sb700'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'released_5': [0], '2_6': [0], 'codename_7': [1], 'sb700_8': [2]} | ['model', 'codename', 'released', 'fab ( nm )', 'sata', 'usb 2.0 + 1.1', 'usb 3.0', 'parallel ata 1', 'raid', 'gb ethernet mac', 'package', 'tdp ( w )'] | [['amd 480 / 570 / 580 / 690 crossfire chipset', 'sb600', '2006', '130', '43 gbit / s ahci 1.1 sata revision 2.0', '10 + 0', 'no', '1 ata / 133', '0 , 1 , 10', 'no', '548 - pin fc - bga', '4.0'], ['amd 700 chipset series', 'sb700', 'q1 2008', '130', '63 gbit / s ahci1 .1 sata revision 2.0', '12 + 2', 'no', '1 ata / 133... |
2005 pga championship | https://en.wikipedia.org/wiki/2005_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12512153-2.html.csv | ordinal | hal sutton had the highest total during the 2005 pga championship . | {'row': '7', 'col': '4', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 1 }'}, 'player'], 'result': 'hal sutton', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 1 } ; player }'}, 'hal sutton'], 're... | eq { hop { nth_argmax { all_rows ; total ; 1 } ; player } ; hal sutton } = true | select the row whose total record of all rows is 1st maximum . the player record of this row is hal sutton . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '1_6': 6, 'player_7': 7, 'hal sutton_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '1_6': '1', 'player_7': 'player', 'hal sutton_8': 'hal sutton'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '1_6': [0], 'player_7': [1], 'hal sutton_8': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['steve elkington', 'australia', '1995', '277', '- 3', 't2'], ['davis love iii', 'united states', '1997', '278', '- 2', 't4'], ['tiger woods', 'united states', '1999 , 2000', '278', '- 2', 't4'], ['vijay singh', 'fiji', '1998 , 2004', '280', 'e', 't10'], ['david toms', 'united states', '2001', '280', 'e', 't10'], ['jo... |
2004 úrvalsdeild | https://en.wikipedia.org/wiki/2004_%C3%9Arvalsdeild | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11179106-1.html.csv | superlative | in the 2004 season of úrvalsdeild , the fh team ranks the highest . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'fh', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'fh'], 'result': True, 'ind': 2, 'tostr': 'eq { hop ... | eq { hop { argmax { all_rows ; points } ; team } ; fh } = true | select the row whose points record of all rows is maximum . the team record of this row is fh . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'fh_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'fh_7': 'fh'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'fh_7': [2]} | ['team', 'played', 'draw', 'lost', 'goals for', 'goals against', 'goal difference', 'points'] | [['fh', '18', '7', '1', '33', '16', '+ 17', '37'], ['íbv', '18', '4', '5', '35', '20', '+ 15', '31'], ['ía', '18', '7', '3', '28', '19', '+ 9', '31'], ['fylkir', '18', '5', '5', '26', '20', '+ 6', '29'], ['keflavík', '18', '3', '8', '31', '33', '- 2', '24'], ['kr', '18', '7', '6', '21', '22', '- 1', '22'], ['grindavík'... |
2007 - 08 belgian first division | https://en.wikipedia.org/wiki/2007%E2%80%9308_Belgian_First_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11713303-2.html.csv | ordinal | peter voets ( caretaker ) had the earliest appointment date in the 2007 - 08 belgian first division . | {'row': '1', 'col': '6', 'order': '1', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date of appointment', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date of appointment ; 1 }'}, 'replaced by'], 'result': 'peter voets ( caretaker )', 'ind': 1, 'tostr': 'hop { nth_argmin { all_row... | eq { hop { nth_argmin { all_rows ; date of appointment ; 1 } ; replaced by } ; peter voets ( caretaker ) } = true | select the row whose date of appointment record of all rows is 1st minimum . the replaced by record of this row is peter voets ( caretaker ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date of appointment_5': 5, '1_6': 6, 'replaced by_7': 7, 'peter voets (caretaker)_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date of appointment_5': 'date of appointment', '1_6': '1', 'replaced by_7': 'replaced by', 'peter voets (caretaker)_8': 'peter voets ( caretaker )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date of appointment_5': [0], '1_6': [0], 'replaced by_7': [1], 'peter voets (caretaker)_8': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment'] | [['sint - truiden', 'valère billen', 'quit', '18 september 2007', 'peter voets ( caretaker )', '18 september 2007'], ['anderlecht', 'franky vercauteren', 'mutual consent', '12 november 2007', 'ariel jacobs', '12 november 2007'], ['dender eh', 'jean - pierre van de velde', 'mutual consent', '19 november 2007', 'johan bo... |
1997 in paraguayan football | https://en.wikipedia.org/wiki/1997_in_Paraguayan_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18703133-6.html.csv | count | paraguayan football played a total of 13 matches in 1997 . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '13', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'position'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record is arbitrary .', 'tostr': 'filter_all { all_rows ; position }'}], 'result': '13', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; po... | eq { count { filter_all { all_rows ; position } } ; 13 } = true | select the rows whose position record is arbitrary . the number of such rows is 13 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'position_5': 5, '13_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'position_5': 'position', '13_6': '13'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'position_5': [0], '13_6': [2]} | ['position', 'team', 'played', 'wins', 'draws pk wins / pk losses', 'losses', 'scored', 'conceded', 'points'] | [['1', 'cerro corá', '12', '8', '1 / 2', '1', '22', '11', '28'], ['2', 'guaraní', '12', '6', '1 / 4', '1', '22', '16', '24'], ['3', 'san lorenzo', '12', '5', '2 / 1', '4', '13', '10', '20'], ['4', 'sportivo luqueño', '12', '4', '3 / 2', '3', '18', '16', '20'], ['5', 'olimpia', '12', '4', '4 / 0', '4', '18', '16', '20']... |
list of manila broadcasting company stations | https://en.wikipedia.org/wiki/List_of_Manila_Broadcasting_Company_stations | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28794440-1.html.csv | count | 12 branding of the manila broadcasting company stations use 5 kw power . | {'scope': 'all', 'criterion': 'equal', 'value': '5 kw', 'result': '12', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'power ( kw )', '5 kw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose power ( kw ) record fuzzily matches to 5 kw .', 'tostr': 'filter_eq { all_rows ; power ( kw ) ; 5 kw }'}], 'result': '12', 'ind': 1, 'tos... | eq { count { filter_eq { all_rows ; power ( kw ) ; 5 kw } } ; 12 } = true | select the rows whose power ( kw ) record fuzzily matches to 5 kw . the number of such rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'power (kw)_5': 5, '5 kw_6': 6, '12_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'power (kw)_5': 'power ( kw )', '5 kw_6': '5 kw', '12_7': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'power (kw)_5': [0], '5 kw_6': [0], '12_7': [2]} | ['branding', 'callsign', 'frequency', 'power ( kw )', 'station type', 'location'] | [['dzrh', 'dzrh', '666khz', '50 kw', 'originating', 'metro manila'], ['dzrh laoag', 'dzmt', '990khz', '5 kw', 'relay', 'laoag'], ['dzrh dagupan', 'dwdh', '1440khz', '10 kw', 'relay', 'dagupan'], ['dzrh tuguegarao', 'dwrh', '576khz', '5 kw', 'relay', 'tuguegarao'], ['dzrh isabela', 'dwrh', '828khz', '5 kw', 'relay', 'sa... |
1967 syracuse orangemen football team | https://en.wikipedia.org/wiki/1967_Syracuse_Orangemen_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20850339-1.html.csv | majority | the 1967 syracuse orangemen football team won most of their games . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; result ; win } = true'} | most_eq { all_rows ; result ; win } = true | for the result records of all rows , most of them fuzzily match to win . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'win_4': [0]} | ['game', 'date', 'opponent', 'result', 'orangemen points', 'opponents', 'record'] | [['1', 'sept 23', 'baylor', 'win', '7', '0', '1 - 0'], ['2', 'sept 30', 'west virginia', 'win', '23', '6', '2 - 0'], ['3', 'oct 7', 'maryland', 'win', '7', '3', '3 - 0'], ['4', 'oct 14', 'navy', 'loss', '14', '27', '3 - 1'], ['5', 'oct 21', 'california', 'win', '20', '14', '4 - 1'], ['6', 'oct 28', 'penn state', 'loss'... |
wfcr | https://en.wikipedia.org/wiki/WFCR | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1540742-1.html.csv | superlative | in the wfcr stations , w291ch has the highest frequency of 106.1 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'frequency mhz'], 'result': '106.1', 'ind': 0, 'tostr': 'max { all_rows ; frequency mhz }', 'tointer': 'the maximum frequency mhz record of all rows is 106.1 .'}, '106.1'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; fre... | and { eq { max { all_rows ; frequency mhz } ; 106.1 } ; eq { hop { argmax { all_rows ; frequency mhz } ; call sign } ; w291ch } } = true | the maximum frequency mhz record of all rows is 106.1 . the call sign record of the row with superlative frequency mhz record is w291ch . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'frequency mhz_8': 8, '106.1_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'frequency mhz_11': 11, 'call sign_12': 12, 'w291ch_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'frequency mhz_8': 'frequency mhz', '106.1_9': '106.1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'frequency mhz_11': 'frequency mhz', 'call sign_12': 'call sign', 'w291ch_13... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'frequency mhz_8': [0], '106.1_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'frequency mhz_11': [2], 'call sign_12': [3], 'w291ch_13': [4]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['w291ch', '106.1', 'pittsfield , massachusetts', '10', 'd', 'fcc'], ['w242at', '96.3', 'williamstown , massachusetts', '250', 'd', 'fcc'], ['w252bg', '98.3', 'lee , massachusetts', '13', 'd', 'fcc'], ['w254au', '98.7', 'great barrington , massachusetts', '250', 'd', 'fcc'], ['w266aw', '101.1', 'north adams , massachu... |
duneland athletic conference | https://en.wikipedia.org/wiki/Duneland_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15090962-1.html.csv | ordinal | of the schools in the duneland athletic conference , portage has the second highest enrollment . | {'row': '7', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'enrollment 08 - 09', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; enrollment 08 - 09 ; 2 }'}, 'location'], 'result': 'portage', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; enrollment 08 - 09 ... | eq { hop { nth_argmax { all_rows ; enrollment 08 - 09 ; 2 } ; location } ; portage } = true | select the row whose enrollment 08 - 09 record of all rows is 2nd maximum . the location record of this row is portage . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'enrollment 08 - 09_5': 5, '2_6': 6, 'location_7': 7, 'portage_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', 'enrollment 08 - 09_5': 'enrollment 08 - 09', '2_6': '2', 'location_7': 'location', 'portage_8': 'portage'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'enrollment 08 - 09_5': [0], '2_6': [0], 'location_7': [1], 'portage_8': [2]} | ['school', 'location', 'mascot', 'county', 'enrollment 08 - 09', 'ihsaa class', 'ihsaa class football', 'year joined', 'previous conference'] | [['chesterton', 'chesterton', 'trojans', '64 porter', '1921', '4a', '6a', '1970', 'calumet'], ['crown point', 'crown point', 'bulldogs', '45 lake', '2426', '4a', '6a', '1993', 'lake suburban'], ['lake central', 'saint john', 'indians', '45 lake', '3141', '4a', '6a', '2003', 'independents'], ['laporte', 'laporte', 'slic... |
1948 ashes series | https://en.wikipedia.org/wiki/1948_Ashes_series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16570286-4.html.csv | superlative | alec bedser had the highest average among all the players from both england and australia in the 1948 ashes series . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', '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', 'average'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; average }'}, 'player'], 'result': 'alec bedser', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; average } ; player }'}, 'alec bedser'], 'result': True, 'ind... | eq { hop { argmax { all_rows ; average } ; player } ; alec bedser } = true | select the row whose average record of all rows is maximum . the player record of this row is alec bedser . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'average_5': 5, 'player_6': 6, 'alec bedser_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'average_5': 'average', 'player_6': 'player', 'alec bedser_7': 'alec bedser'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'average_5': [0], 'player_6': [1], 'alec bedser_7': [2]} | ['player', 'team', 'matches', 'wickets', 'average', 'best bowling'] | [['ray lindwall', 'australia', '5', '27', '19.62', '6 / 20'], ['norman yardley', 'england', '5', '9', '22.66', '2 / 32'], ['keith miller', 'australia', '5', '13', '23.15', '4 / 125'], ['bill johnston', 'australia', '5', '27', '23.33', '5 / 36'], ['ernie toshack', 'australia', '4', '11', '33.09', '5 / 40'], ['alec bedse... |
2008 - 09 süper lig | https://en.wikipedia.org/wiki/2008%E2%80%9309_S%C3%BCper_Lig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17356873-1.html.csv | comparative | the bursa atatürk stadium has a smaller capacity than the şükrü saracoğlu stadium . | {'row_1': '5', 'row_2': '8', 'col': '5', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'bursa atatürk stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to bursa atatürk stadium .', 'tostr': 'filter_eq { all_rows ; venue ; bursa atatürk stadium }'... | less { hop { filter_eq { all_rows ; venue ; bursa atatürk stadium } ; capacity } ; hop { filter_eq { all_rows ; venue ; şükrü saracoğlu stadium } ; capacity } } = true | select the rows whose venue record fuzzily matches to bursa atatürk stadium . take the capacity record of this row . select the rows whose venue record fuzzily matches to şükrü saracoğlu stadium . take the capacity record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'bursa atatürk stadium_8': 8, 'capacity_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'şükrü saracoğlu stadium_12': 12, 'capacity_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'bursa atatürk stadium_8': 'bursa atatürk stadium', 'capacity_9': 'capacity', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11'... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'bursa atatürk stadium_8': [0], 'capacity_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'şükrü saracoğlu stadium_12': [1], 'capacity_13': [3]} | ['team', 'head coach', 'team captain', 'venue', 'capacity', 'kitmaker', 'shirt sponsor', 'club chairman'] | [['ankaragücü', 'hakan kutlu', 'murat erdoğan', 'ankara 19 mayıs stadium', '19209', 'lotto', 'turkcell', 'cemal azmi aydın'], ['ankaraspor', 'aykut kocaman', 'hürriyet güçer', 'yenikent asaş stadium', '19626', 'nike', 'turkcell', 'ruhi kurnaz'], ['antalyaspor', 'mehmet özdilek', 'uğur kavuk', 'antalya atatürk stadium',... |
list of game of the year awards | https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-10.html.csv | unique | super mario galaxy 2 is the only game of the year award winner for the wii platform . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'wii', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'platform ( s )', 'wii'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose platform ( s ) record fuzzily matches to wii .', 'tostr': 'filter_eq { all_rows ; platform ( s ) ; wii }'}], 'result': True, 'ind': 1, '... | and { only { filter_eq { all_rows ; platform ( s ) ; wii } } ; eq { hop { filter_eq { all_rows ; platform ( s ) ; wii } ; game } ; super mario galaxy 2 } } = true | select the rows whose platform ( s ) record fuzzily matches to wii . there is only one such row in the table . the game record of this unqiue row is super mario galaxy 2 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'platform (s)_7': 7, 'wii_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'game_9': 9, 'super mario galaxy 2_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'platform (s)_7': 'platform ( s )', 'wii_8': 'wii', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'game_9': 'game', 'super mario galaxy 2_10': 'super mario galaxy 2'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'platform (s)_7': [0], 'wii_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'game_9': [2], 'super mario galaxy 2_10': [3]} | ['year', 'game', 'genre', 'platform ( s )', 'developer ( s )'] | [['2003', 'the legend of zelda : the wind waker', 'action - adventure : open world', 'nintendo gamecube', 'nintendo ead'], ['2009', "demon 's souls", 'action rpg : hack & slash', 'playstation 3', 'from software'], ['2010', 'super mario galaxy 2', 'platformer', 'wii', 'nintendo ead'], ['2011', 'dead space 2', 'survival ... |
westmorland county , new brunswick | https://en.wikipedia.org/wiki/Westmorland_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-176529-1.html.csv | unique | beaubassin east has the only rural community status in westmorland county . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'rural community', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'rural community'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to rural community .', 'tostr': 'filter_eq { all_rows ; status ; rural community }'}], 'result': True,... | and { only { filter_eq { all_rows ; status ; rural community } } ; eq { hop { filter_eq { all_rows ; status ; rural community } ; official name } ; beaubassin east } } = true | select the rows whose status record fuzzily matches to rural community . there is only one such row in the table . the official name record of this unqiue row is beaubassin east . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'status_7': 7, 'rural community_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'official name_9': 9, 'beaubassin east_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'status_7': 'status', 'rural community_8': 'rural community', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'official name_9': 'official name', 'beaubassin east_10': 'beaubassin east'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'status_7': [0], 'rural community_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'official name_9': [2], 'beaubassin east_10': [3]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['moncton', 'city', '141.17', '69074', '79 of 5008'], ['dieppe', 'city', '51.17', '23310', '174 of 5008'], ['beaubassin east', 'rural community', '291.04', '6200', '600 of 5008'], ['shediac', 'town', '11.97', '6053', '610 of 5008'], ['sackville', 'town', '74.32', '5558', '655 of 5008'], ['memramcook', 'village', '185.... |
speedway world championship competitions | https://en.wikipedia.org/wiki/Speedway_World_Championship_Competitions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12592117-1.html.csv | superlative | first speedway world championship competition among individuals took place in 1931 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'individuals'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competing entities', 'individuals'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competing entities ; individuals }', 'tointer': 'select the rows whose competing entities record fuzzily matches to individuals... | eq { min { filter_eq { all_rows ; competing entities ; individuals } ; first held } ; 1931 } = true | select the rows whose competing entities record fuzzily matches to individuals . the minimum first held record of these rows is 1931 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'competing entities_5': 5, 'individuals_6': 6, 'first held_7': 7, '1931_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'competing entities_5': 'competing entities', 'individuals_6': 'individuals', 'first held_7': 'first held', '1931_8': '1931'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competing entities_5': [0], 'individuals_6': [0], 'first held_7': [1], '1931_8': [2]} | ['competing entities', 'first held', 'current holder', 'next', 'held every'] | [['individuals', '1931', 'chris holder ( 2012 )', '2013', 'one year'], ['individuals', '1977', 'michael jespen jensen ( 2012 )', '2013', 'one year'], ['national pairs', '1970', 'sweden ( 1993 )', 'defunct', 'one year until 1993'], ['national teams :', '1960', '( 2012 )', '2013', 'one year'], ['national teams :', '2005'... |
1970 - 71 cleveland cavaliers season | https://en.wikipedia.org/wiki/1970%E2%80%9371_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16275352-5.html.csv | ordinal | the cleveland cavaliers ' game against the atlanta hawks was the earliest in the 1970 - 71 season . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'opponent'], 'result': 'atlanta hawks', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; opponent }'}, 'atlanta hawks... | eq { hop { nth_argmin { all_rows ; date ; 1 } ; opponent } ; atlanta hawks } = true | select the row whose date record of all rows is 1st minimum . the opponent record of this row is atlanta hawks . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'opponent_7': 7, 'atlanta hawks_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', '1_6': '1', 'opponent_7': 'opponent', 'atlanta hawks_8': 'atlanta hawks'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'opponent_7': [1], 'atlanta hawks_8': [2]} | ['date', 'h / a / n', 'opponent', 'score', 'record'] | [['november 1', 'h', 'atlanta hawks', '107 - 130', '0 - 10'], ['november 2', 'a', 'philadelphia 76ers', '87 - 141', '0 - 11'], ['november 4', 'h', 'milwaukee bucks', '108 - 110', '0 - 12'], ['november 7', 'a', 'buffalo braves', '91 - 103', '0 - 13'], ['november 8', 'h', 'seattle supersonics', '105 - 111', '0 - 14'], ['... |
1963 vfl season | https://en.wikipedia.org/wiki/1963_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10783853-8.html.csv | aggregation | the average crowd size across all the games in the 1963 vfl season was around 35000 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '35000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '35000', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '35000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 35000 } = true', 'tointer': 'the average of the crowd record of all rows is 35000 .'} | round_eq { avg { all_rows ; crowd } ; 35000 } = true | the average of the crowd record of all rows is 35000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '35000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '35000_5': '35000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '35000_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '13.11 ( 89 )', 'richmond', '7.5 ( 47 )', 'windy hill', '21200', '8 june 1963'], ['carlton', '6.8 ( 44 )', 'collingwood', '6.10 ( 46 )', 'princes park', '38698', '8 june 1963'], ['st kilda', '8.13 ( 61 )', 'hawthorn', '9.11 ( 65 )', 'junction oval', '34900', '8 june 1963'], ['footscray', '6.16 ( 52 )', 's... |
2008 tour de suisse | https://en.wikipedia.org/wiki/2008_Tour_de_Suisse | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17672470-19.html.csv | unique | in the 2008 tour de suisse , when igor anton was the general classification , the only time markus fothen was the winner was in stage 5 . | {'scope': 'subset', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'markus fothen', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'igor antón'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'general classification', 'igor antón'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; general classification ; igor antón }', 'tointer': 'select the rows whose general class... | and { only { filter_eq { filter_eq { all_rows ; general classification ; igor antón } ; winner ; markus fothen } } ; eq { hop { filter_eq { filter_eq { all_rows ; general classification ; igor antón } ; winner ; markus fothen } ; stage } ; 5 } } = true | select the rows whose general classification record fuzzily matches to igor antón . among these rows , select the rows whose winner record fuzzily matches to markus fothen . there is only one such row in the table . the stage record of this unqiue row is 5 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'general classification_8': 8, 'igor antón_9': 9, 'winner_10': 10, 'markus fothen_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'stage_12': 12, '5_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'general classification_8': 'general classification', 'igor antón_9': 'igor antón', 'winner_10': 'winner', 'markus fothen_11': 'markus fothen', 'str_eq_4': 'str_eq', '... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'general classification_8': [0], 'igor antón_9': [0], 'winner_10': [1], 'markus fothen_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'stage_12': [3], '5_13': [4]} | ['stage', 'winner', 'general classification', 'mountains classification', 'points classification', 'sprints classification', 'team classification'] | [['1', 'óscar freire', 'óscar freire', 'no award', 'óscar freire', 'no award', "caisse d'epargne"], ['2', 'igor antón', 'igor antón', 'david loosli', 'kim kirchen', 'david loosli', 'team csc'], ['3', 'robbie mcewen', 'igor antón', 'david loosli', 'óscar freire', 'rené weissinger', 'team csc'], ['4', 'robbie mcewen', 'i... |
1984 - 85 boston celtics season | https://en.wikipedia.org/wiki/1984%E2%80%9385_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17344651-6.html.csv | count | the boston celtics played against the new york knicks two times . | {'scope': 'all', 'criterion': 'equal', 'value': 'new york knicks', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'new york knicks'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to new york knicks .', 'tostr': 'filter_eq { all_rows ; opponent ; new york knicks }'}], 'result':... | eq { count { filter_eq { all_rows ; opponent ; new york knicks } } ; 2 } = true | select the rows whose opponent record fuzzily matches to new york knicks . 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, 'opponent_5': 5, 'new york knicks_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', 'opponent_5': 'opponent', 'new york knicks_6': 'new york knicks', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'new york knicks_6': [0], '2_7': [2]} | ['game', 'date', 'opponent', 'score', 'location', 'record'] | [['33', 'wed jan 2', 'new jersey nets', '110 - 95', 'brendan byrne arena', '27 - 6'], ['34', 'fri jan 4', 'new york knicks', '105 - 94', 'boston garden', '28 - 6'], ['35', 'mon jan 7', 'new york knicks', '108 - 97', 'madison square garden', '29 - 6'], ['36', 'wed jan 9', 'chicago bulls', '111 - 108', 'boston garden', '... |
wru division four west | https://en.wikipedia.org/wiki/WRU_Division_Four_West | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13758945-2.html.csv | unique | burry port rfc is the only club that lost fourteen times . | {'scope': 'all', 'row': '10', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '14', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lost', '14'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lost record is equal to 14 .', 'tostr': 'filter_eq { all_rows ; lost ; 14 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; lost ... | and { only { filter_eq { all_rows ; lost ; 14 } } ; eq { hop { filter_eq { all_rows ; lost ; 14 } ; club } ; burry port rfc } } = true | select the rows whose lost record is equal to 14 . there is only one such row in the table . the club record of this unqiue row is burry port rfc . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'lost_7': 7, '14_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'burry port rfc_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'lost_7': 'lost', '14_8': '14', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'burry port rfc_10': 'burry port rfc'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'lost_7': [0], '14_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'burry port rfc_10': [3]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['llandeilo rfc', '22', '1', '0', '917', '119', '136', '14', '19', '0', '105'], ['brynamman rfc', '22', '1', '2', '821', '210', '116', '27', '16', '2', '96'], ['tenby united rfc', '... |
test matches ( 1991 - 2000 ) | https://en.wikipedia.org/wiki/Test_matches_%281991%E2%80%932000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12410929-70.html.csv | superlative | of the test matches of 1991-2000 , the match won with the highest number of runs was played at the adelaide oval . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'result'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; result }'}, 'venue'], 'result': 'adelaide oval', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; result } ; venue }'}, 'adelaide oval'], 'result': True, 'ind'... | eq { hop { argmax { all_rows ; result } ; venue } ; adelaide oval } = true | select the row whose result record of all rows is maximum . the venue record of this row is adelaide oval . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'result_5': 5, 'venue_6': 6, 'adelaide oval_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'result_5': 'result', 'venue_6': 'venue', 'adelaide oval_7': 'adelaide oval'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'result_5': [0], 'venue_6': [1], 'adelaide oval_7': [2]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['22 , 23 , 24 , 25 , 26 november 1996', 'mark taylor', 'courtney walsh', 'brisbane cricket ground', 'aus by 123 runs'], ['29 , 30 november , 1 , 2 , 3 december 1996', 'mark taylor', 'courtney walsh', 'sydney cricket ground', 'aus by 124 runs'], ['26 , 27 , 28 december 1996', 'mark taylor', 'courtney walsh', 'melbourn... |
huntington area rapid transit | https://en.wikipedia.org/wiki/Huntington_Area_Rapid_Transit | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14858130-4.html.csv | ordinal | considering the retired fleet of the huntington area rapid transit , the flxible 35096-6 -1 model had the third highest length . | {'row': '2', 'col': '3', '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', 'length', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; length ; 3 }'}, 'model'], 'result': 'flxible 35096 - 6 - 1', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; length ; 3 } ; model }'}, 'flxib... | eq { hop { nth_argmax { all_rows ; length ; 3 } ; model } ; flxible 35096 - 6 - 1 } = true | select the row whose length record of all rows is 3rd maximum . the model record of this row is flxible 35096 - 6 - 1 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, '3_6': 6, 'model_7': 7, 'flxible 35096 - 6 - 1_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', 'length_5': 'length', '3_6': '3', 'model_7': 'model', 'flxible 35096 - 6 - 1_8': 'flxible 35096 - 6 - 1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], '3_6': [0], 'model_7': [1], 'flxible 35096 - 6 - 1_8': [2]} | ['year', 'model', 'length', 'width', 'fleet number'] | [['1970', 'gmc t6h4521a', "35 '", '96', '101 - 103'], ['1977', 'flxible 35096 - 6 - 1', "31 '", '96', '201 - 211'], ['1984', 'orion 01.507', "36 ' 8", '96', '301 - 303'], ['19xx', 'chance rt52', "25 ' 11", '96', "400 's"], ['1993', 'gillig phantom 3096tb', "30 '", '96', '501 - 506'], ['1998', 'gillig phantom 3096tb', "... |
kentucky intercollegiate athletic conference | https://en.wikipedia.org/wiki/Kentucky_Intercollegiate_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10581768-2.html.csv | superlative | indiana university southeast has the most enrollment among institutions in the kentucky intercollegiate athletic conference . | {'scope': 'all', 'col_superlative': '6', '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', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'institution'], 'result': 'indiana university southeast', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; institution }'}, ... | eq { hop { argmax { all_rows ; enrollment } ; institution } ; indiana university southeast } = true | select the row whose enrollment record of all rows is maximum . the institution record of this row is indiana university southeast . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'institution_6': 6, 'indiana university southeast_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'institution_6': 'institution', 'indiana university southeast_7': 'indiana university southeast'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'institution_6': [1], 'indiana university southeast_7': [2]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment'] | [['alice lloyd college', 'eagles', 'pippa passes , kentucky', '1923', 'private', '600'], ['asbury university', 'eagles', 'wilmore , kentucky', '1890', 'private', '1300'], ['berea college', 'mountaineers', 'berea , kentucky', '1855', 'private', '1514'], ['brescia university', 'bearcats', 'owensboro , kentucky', '1950', ... |
list of actors who played president of the united states | https://en.wikipedia.org/wiki/List_of_actors_who_played_President_of_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1673723-9.html.csv | count | anthony hopkins was nominated for two different categories . | {'scope': 'all', 'criterion': 'equal', 'value': 'anthony hopkins', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nominee', 'anthony hopkins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nominee record fuzzily matches to anthony hopkins .', 'tostr': 'filter_eq { all_rows ; nominee ; anthony hopkins }'}], 'result': '2... | eq { count { filter_eq { all_rows ; nominee ; anthony hopkins } } ; 2 } = true | select the rows whose nominee record fuzzily matches to anthony hopkins . 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, 'nominee_5': 5, 'anthony hopkins_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', 'nominee_5': 'nominee', 'anthony hopkins_6': 'anthony hopkins', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nominee_5': [0], 'anthony hopkins_6': [0], '2_7': [2]} | ['year', 'category', 'president', 'nominee', 'film', 'result'] | [['1941', 'best actor', 'abraham lincoln', 'raymond massey', 'abe lincoln in illinois', 'nominated'], ['1976', 'best actor', 'harry s truman', 'james whitmore', "give 'em hell , harry !", 'nominated'], ['1996', 'best actor', 'richard nixon', 'anthony hopkins', 'nixon', 'nominated'], ['1998', 'best supporting actor', 'j... |
wnba finals | https://en.wikipedia.org/wiki/WNBA_Finals | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1164512-3.html.csv | count | 2 teams which participated in the wnba finals had single wins . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; wins ; 1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; wins ; 1... | eq { count { filter_eq { all_rows ; wins ; 1 } } ; 2 } = true | select the rows whose wins record is equal to 1 . 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, 'wins_5': 5, '1_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'wins_5': 'wins', '1_6': '1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'wins_5': [0], '1_6': [0], '2_7': [2]} | ['finals', 'team', 'wins', 'losses', 'pct'] | [['4', 'houston comets 2', '4', '0', '1.000'], ['4', 'detroit shock 3', '3', '1', '750'], ['4', 'new york liberty', '0', '4', '000'], ['3', 'los angeles sparks', '2', '1', '667'], ['3', 'phoenix mercury', '2', '1', '667'], ['3', 'atlanta dream', '0', '3', '000'], ['3', 'minnesota lynx', '2', '1', '667'], ['2', 'seattle... |
sidecarcross world championship | https://en.wikipedia.org/wiki/Sidecarcross_World_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16729457-16.html.csv | unique | the only people to use husaberg - wht equipment were daniel millard/joe millard . | {'scope': 'all', 'row': '10', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'husaberg - wht', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'equipment', 'husaberg - wht'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose equipment record fuzzily matches to husaberg - wht .', 'tostr': 'filter_eq { all_rows ; equipment ; husaberg - wht }'}], 'result':... | and { only { filter_eq { all_rows ; equipment ; husaberg - wht } } ; eq { hop { filter_eq { all_rows ; equipment ; husaberg - wht } ; driver / passenger } ; daniel millard / joe millard } } = true | select the rows whose equipment record fuzzily matches to husaberg - wht . there is only one such row in the table . the driver / passenger record of this unqiue row is daniel millard / joe millard . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'equipment_7': 7, 'husaberg - wht_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver / passenger_9': 9, 'daniel millard / joe millard_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'equipment_7': 'equipment', 'husaberg - wht_8': 'husaberg - wht', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver / passenger_9': 'driver / passenger', 'daniel millard / joe millard_10': 'daniel mi... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'equipment_7': [0], 'husaberg - wht_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver / passenger_9': [2], 'daniel millard / joe millard_10': [3]} | ['position', 'driver / passenger', 'equipment', 'bike no', 'points'] | [['1', 'daniãl willemsen / sven verbrugge 1', 'zabel - wsp', '1', '487'], ['2', 'janis daiders / lauris daiders', 'zabel - vmc', '8', '478'], ['3', 'jan hendrickx / tim smeuninx', 'zabel - vmc', '3', '405'], ['4', 'maris rupeiks / kaspars stupelis 2', 'zabel - wsp', '5', '349'], ['5', 'etienne bax / ben van den bogaart... |
1997 - 98 philadelphia flyers season | https://en.wikipedia.org/wiki/1997%E2%80%9398_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14344681-14.html.csv | comparative | in the 1997-98 philadelphia flyers season , jordon flodell was drafted one round before todd fedoruk . | {'row_1': '5', 'row_2': '6', 'col': '1', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'yes', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'jordon flodell'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to jordon flodell .', 'tostr': 'filter_eq { all_ro... | and { eq { diff { hop { filter_eq { all_rows ; player ; jordon flodell } ; round } ; hop { filter_eq { all_rows ; player ; todd fedoruk } ; round } } ; -1 } ; and { eq { hop { filter_eq { all_rows ; player ; jordon flodell } ; round } ; 6 } ; eq { hop { filter_eq { all_rows ; player ; todd fedoruk } ; round } ; 7 } } }... | select the rows whose player record fuzzily matches to jordon flodell . take the round record of this row . select the rows whose player record fuzzily matches to todd fedoruk . take the round record of this row . the second record is 1 larger than the first record . the round record of the first row is 6 . the round r... | 14 | 10 | {'and_9': 9, 'result_10': 10, 'eq_5': 5, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_11': 11, 'player_12': 12, 'jordon flodell_13': 13, 'round_14': 14, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_15': 15, 'player_16': 16, 'todd fedoruk_17': 17, 'round_18': 18, '-1_19': 19, 'and_8': 8, 'eq_6': 6, '6... | {'and_9': 'and', 'result_10': 'true', 'eq_5': 'eq', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'jordon flodell_13': 'jordon flodell', 'round_14': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_15': 'all_... | {'and_9': [10], 'result_10': [], 'eq_5': [9], 'diff_4': [5], 'num_hop_2': [4, 6], 'filter_str_eq_0': [2], 'all_rows_11': [0], 'player_12': [0], 'jordon flodell_13': [0], 'round_14': [2], 'num_hop_3': [4, 7], 'filter_str_eq_1': [3], 'all_rows_15': [1], 'player_16': [1], 'todd fedoruk_17': [1], 'round_18': [3], '-1_19': ... | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['2', 'jean - marc pelletier', 'goaltender', 'united states', 'cornell big red ( ecac )'], ['2', 'pat kavanagh', 'right wing', 'canada', 'peterborough petes ( ohl )'], ['3', 'kris mallette', 'defense', 'canada', 'kelowna rockets ( whl )'], ['4', 'mikhail chernov', 'defense', 'russia', 'torpedo yaroslavl ( rus )'], ['6... |
1931 vfl season | https://en.wikipedia.org/wiki/1931_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10789881-9.html.csv | majority | most of the games on july 4 , 1931 had a crowd of over 10,000 . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 10000 .', 'tostr': 'most_greater { all_rows ; crowd ; 10000 } = true'} | most_greater { all_rows ; crowd ; 10000 } = true | for the crowd records of all rows , most of them are greater than 10000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '10000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '10000_4': '10000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '10000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '4.12 ( 36 )', 'st kilda', '9.9 ( 63 )', 'mcg', '15826', '4 july 1931'], ['geelong', '13.9 ( 87 )', 'hawthorn', '9.7 ( 61 )', 'corio oval', '9500', '4 july 1931'], ['fitzroy', '8.13 ( 61 )', 'richmond', '14.17 ( 101 )', 'brunswick street oval', '15000', '4 july 1931'], ['south melbourne', '10.13 ( 73 )',... |
1997 cfl draft | https://en.wikipedia.org/wiki/1997_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28059992-6.html.csv | unique | chris hardy was the only player who played the qb position . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'qb', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'qb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to qb .', 'tostr': 'filter_eq { all_rows ; position ; qb }'}], 'result': True, 'ind': 1, 'tostr': 'only { filte... | and { only { filter_eq { all_rows ; position ; qb } } ; eq { hop { filter_eq { all_rows ; position ; qb } ; player } ; chris hardy } } = true | select the rows whose position record fuzzily matches to qb . there is only one such row in the table . the player record of this unqiue row is chris hardy . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'qb_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'chris hardy_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'qb_8': 'qb', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'chris hardy_10': 'chris hardy'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'qb_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'chris hardy_10': [3]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['42', 'saskatchewan', 'dan comiskey', 'ol', 'windsor'], ['43', 'bc', 'kelly lochbaum', 'lb', 'northern arizona'], ['44', 'winnipeg', 'wayne weathers', 'de', 'manitoba'], ['45', 'montreal', 'francis bellefroid', 'lb', "bishop 's"], ['46', 'calgary', 'paul donkersley', 'rb', 'acadia'], ['47', 'edmonton', 'chris hardy',... |
list of schools in the auckland region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Auckland_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12017602-20.html.csv | unique | st mary 's catholic school is the only school in the auckland region that has a state integrated authority . | {'scope': 'all', 'row': '15', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'state integrated', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'authority', 'state integrated'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose authority record fuzzily matches to state integrated .', 'tostr': 'filter_eq { all_rows ; authority ; state integrated }'}], 're... | and { only { filter_eq { all_rows ; authority ; state integrated } } ; eq { hop { filter_eq { all_rows ; authority ; state integrated } ; name } ; st mary 's catholic school } } = true | select the rows whose authority record fuzzily matches to state integrated . there is only one such row in the table . the name record of this unqiue row is st mary 's catholic school . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'authority_7': 7, 'state integrated_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, "st mary 's catholic school_10": 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'authority_7': 'authority', 'state integrated_8': 'state integrated', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', "st mary 's catholic school_10": "st mary 's catholic school"} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'authority_7': [0], 'state integrated_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], "st mary 's catholic school_10": [3]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['conifer grove school', '1 - 8', 'coed', 'takanini', 'state', '7', '526'], ['cosgrove school', '1 - 6', 'coed', 'papakura', 'state', '2', '606'], ['drury school', '1 - 8', 'coed', 'drury', 'state', '8', '423'], ['edmund hillary school', '1 - 8', 'coed', 'papakura', 'state', '1', '146'], ['hingaia peninsula school', '... |
women 's british open | https://en.wikipedia.org/wiki/Women%27s_British_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1520559-2.html.csv | count | karrie webb was the champion of the women 's british open two different times . | {'scope': 'all', 'criterion': 'equal', 'value': 'karrie webb', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'champion', 'karrie webb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose champion record fuzzily matches to karrie webb .', 'tostr': 'filter_eq { all_rows ; champion ; karrie webb }'}], 'result': '2', 'ind':... | eq { count { filter_eq { all_rows ; champion ; karrie webb } } ; 2 } = true | select the rows whose champion record fuzzily matches to karrie webb . 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, 'champion_5': 5, 'karrie webb_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', 'champion_5': 'champion', 'karrie webb_6': 'karrie webb', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'champion_5': [0], 'karrie webb_6': [0], '2_7': [2]} | ['year', 'date', 'venue', 'champion', 'country', 'score', 'to par', 'margin of victory', 'purse', "winner 's share"] | [['2000', 'aug 17 - 20', 'royal birkdale golf club', 'sophie gustafson', 'sweden', '282', '- 6', '2 strokes', '1250000', '178000'], ['1999', 'aug 12 - 15', 'woburn golf and country club', 'sherri steinhauer', 'united states', '283', '- 5', '1 stroke', '1000000', '160000'], ['1998', 'aug 13 - 16', 'royal lytham & st ann... |
2005 open championship | https://en.wikipedia.org/wiki/2005_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16225902-7.html.csv | unique | vijay singh was the only player to represent fiji at the 2005 open championship . | {'scope': 'all', 'row': '10', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'fiji', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'fiji'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to fiji .', 'tostr': 'filter_eq { all_rows ; country ; fiji }'}], 'result': True, 'ind': 1, 'tostr': 'only { fi... | and { only { filter_eq { all_rows ; country ; fiji } } ; eq { hop { filter_eq { all_rows ; country ; fiji } ; player } ; vijay singh } } = true | select the rows whose country record fuzzily matches to fiji . there is only one such row in the table . the player record of this unqiue row is vijay singh . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'fiji_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'vijay singh_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', 'fiji_8': 'fiji', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'vijay singh_10': 'vijay singh'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'fiji_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'vijay singh_10': [3]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'tiger woods', 'united states', '66 + 67 + 71 + 70 = 274', '14', '720000'], ['2', 'colin montgomerie', 'scotland', '71 + 66 + 70 + 72 = 279', '9', '430000'], ['t3', 'fred couples', 'united states', '68 + 71 + 73 + 68 = 280', '8', '242350'], ['t3', 'josé maría olazábal', 'spain', '68 + 70 + 68 + 74 = 280', '8', '... |
ohio high school athletic association | https://en.wikipedia.org/wiki/Ohio_High_School_Athletic_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2849652-2.html.csv | comparative | the soccer team of the ohio high school athletic association had his first tournament before the bowling team . | {'row_1': '3', 'row_2': '4', 'col': '5', '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', 'sport', 'soccer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sport record fuzzily matches to soccer .', 'tostr': 'filter_eq { all_rows ; sport ; soccer }'}, '1st tournament'], 'result': None, 'ind': ... | less { hop { filter_eq { all_rows ; sport ; soccer } ; 1st tournament } ; hop { filter_eq { all_rows ; sport ; bowling } ; 1st tournament } } = true | select the rows whose sport record fuzzily matches to soccer . take the 1st tournament record of this row . select the rows whose sport record fuzzily matches to bowling . take the 1st tournament 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, 'sport_7': 7, 'soccer_8': 8, '1st tournament_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'sport_11': 11, 'bowling_12': 12, '1st tournament_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', 'sport_7': 'sport', 'soccer_8': 'soccer', '1st tournament_9': '1st tournament', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'sport_11': 'sport', 'bowlin... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'sport_7': [0], 'soccer_8': [0], '1st tournament_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'sport_11': [1], 'bowling_12': [1], '1st tournament_13': [3]} | ['season', 'sport', 'tournament structure', 'of divisions', '1st tournament', '2011 - 2012 state tournament location'] | [['fall', 'cross country', 'district , regional , & state', '3', '1978', 'national trail raceway , hebron'], ['fall', 'field hockey', 'state qualifying & state', '1', '1979', 'upper arlington high school , upper arlington'], ['fall', 'soccer', 'sectional , district , regional & state', '3', '1985', 'crew stadium , colu... |
list of england national rugby union team results 1960 - 69 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1960%E2%80%9369 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18179114-2.html.csv | majority | most of the games of the england national rugby union team in 1961 were held in twickenham , london . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'twickenham , london', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'venue', 'twickenham , london'], 'result': True, 'ind': 0, 'tointer': 'for the venue records of all rows , most of them fuzzily match to twickenham , london .', 'tostr': 'most_eq { all_rows ; venue ; twickenham , london } = true'} | most_eq { all_rows ; venue ; twickenham , london } = true | for the venue records of all rows , most of them fuzzily match to twickenham , london . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'venue_3': 3, 'twickenham , london_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'venue_3': 'venue', 'twickenham , london_4': 'twickenham , london'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'venue_3': [0], 'twickenham , london_4': [0]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['south africa', '5', '07 / 01 / 1961', 'twickenham , london', 'test match'], ['wales', '6', '21 / 01 / 1961', 'cardiff arms park , cardiff', 'five nations'], ['ireland', '11', '11 / 02 / 1961', 'lansdowne road , dublin', 'five nations'], ['france', '5', '25 / 02 / 1961', 'twickenham , london', 'five nations'], ['scot... |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-21.html.csv | majority | all of the matches of the 1972 vfl season took place on 26 august 1972 . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '26 august 1972', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '26 august 1972'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 26 august 1972 .', 'tostr': 'all_eq { all_rows ; date ; 26 august 1972 } = true'} | all_eq { all_rows ; date ; 26 august 1972 } = true | for the date records of all rows , all of them fuzzily match to 26 august 1972 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '26 august 1972_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '26 august 1972_4': '26 august 1972'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '26 august 1972_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '17.22 ( 124 )', 'north melbourne', '14.7 ( 91 )', 'mcg', '11241', '26 august 1972'], ['footscray', '17.21 ( 123 )', 'richmond', '18.17 ( 125 )', 'western oval', '18117', '26 august 1972'], ['collingwood', '22.17 ( 149 )', 'south melbourne', '11.6 ( 72 )', 'victoria park', '19934', '26 august 1972'], ['c... |
list of windmills in belgium | https://en.wikipedia.org/wiki/List_of_windmills_in_Belgium | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18843333-3.html.csv | count | only three of the windmills are believed to have been built during the 18th century . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '19th', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'built', '19th'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose built record fuzzily matches to 19th .', 'tostr': 'filter_eq { all_rows ; built ; 19th }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_e... | eq { count { filter_eq { all_rows ; built ; 19th } } ; 4 } = true | select the rows whose built record fuzzily matches to 19th . 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, 'built_5': 5, '19th_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', 'built_5': 'built', '19th_6': '19th', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'built_5': [0], '19th_6': [0], '4_7': [2]} | ['location', 'name of mill', 'type', 'built', 'notes'] | [['andenne', 'molen de stud', 'grondzeiler', '18th century', 'molenechos ( dutch )'], ['belgrade', 'moulin massinon', 'grondzeiler', '1828', 'molenechos ( dutch )'], ['frasnes - lez - couvin', 'moulin tromcourt moulin de géronsart', 'grondzeiler', 'early 19th century', 'molenechos ( dutch )'], ['gembloux - sur - orneau... |
bobby riggs | https://en.wikipedia.org/wiki/Bobby_Riggs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17188888-2.html.csv | ordinal | the first time bobby riggs lost a pro championship was in 1942 against don budge . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '5', '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', 'year', '1'], 'result': '1942', 'ind': 0, 'tostr': 'nth_min { all_rows ; year ; 1 }', 'tointer': 'the 1st minimum year record of all rows is 1942 .'}, '1942'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; year ; 1... | and { eq { nth_min { all_rows ; year ; 1 } ; 1942 } ; eq { hop { nth_argmin { all_rows ; year ; 1 } ; opponent in the final } ; don budge } } = true | the 1st minimum year record of all rows is 1942 . the opponent in the final record of the row with 1st minimum year record is don budge . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'year_8': 8, '1_9': 9, '1942_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'year_12': 12, '1_13': 13, 'opponent in the final_14': 14, 'don budge_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'year_8': 'year', '1_9': '1', '1942_10': '1942', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'year_12': 'year', '1_13': '1', 'opponent in the final_14': 'oppone... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'year_8': [0], '1_9': [0], '1942_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'year_12': [2], '1_13': [2], 'opponent in the final_14': [3], 'don budge_15': [4]} | ['outcome', 'year', 'pro slam championship', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '1942', 'us pro', 'grass', 'don budge', '2 - 6 , 2 - 6 , 2 - 6'], ['winner', '1946', 'us pro', 'grass', 'don budge', '6 - 3 , 6 - 1 , 6 - 1'], ['winner', '1947', 'us pro', 'grass', 'don budge', '3 - 6 , 6 - 3 , 10 - 8 , 4 - 6 , 6 - 3'], ['runner - up', '1948', 'us pro', 'grass', 'jack kramer', '12 - 14... |
1984 senior pga tour | https://en.wikipedia.org/wiki/1984_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622840-4.html.csv | majority | most of the players in the 1984 pga tour earned over 300,000 dollars . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '300,000', 'subset': None} | {'func': 'all_greater', 'args': ['all_rows', 'earnings', '300,000'], 'result': True, 'ind': 0, 'tointer': 'for the earnings records of all rows , all of them are greater than 300,000 .', 'tostr': 'all_greater { all_rows ; earnings ; 300,000 } = true'} | all_greater { all_rows ; earnings ; 300,000 } = true | for the earnings records of all rows , all of them are greater than 300,000 . | 1 | 1 | {'all_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'earnings_3': 3, '300,000_4': 4} | {'all_greater_0': 'all_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'earnings_3': 'earnings', '300,000_4': '300,000'} | {'all_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'earnings_3': [0], '300,000_4': [0]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'don january', 'united states', '791990', '14'], ['2', 'miller barber', 'united states', '720134', '14'], ['3', 'arnold palmer', 'united states', '442974', '8'], ['4', 'billy casper', 'united states', '395386', '4'], ['5', 'gene littler', 'united states', '358770', '3']] |
iberian peninsula | https://en.wikipedia.org/wiki/Iberian_Peninsula | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14883-2.html.csv | superlative | the highest populated urban area on the iberian peninsula is madrid . | {'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', 'population'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; population }'}, 'urban area'], 'result': 'madrid', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; population } ; urban area }'}, 'madrid'], 'result': Tru... | eq { hop { argmax { all_rows ; population } ; urban area } ; madrid } = true | select the row whose population record of all rows is maximum . the urban area record of this row is madrid . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'population_5': 5, 'urban area_6': 6, 'madrid_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'population_5': 'population', 'urban area_6': 'urban area', 'madrid_7': 'madrid'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'population_5': [0], 'urban area_6': [1], 'madrid_7': [2]} | ['urban area', 'country', 'region', 'population', 'globalization index'] | [['madrid', 'spain', 'community of madrid', '6321398', 'alpha'], ['barcelona', 'spain', 'catalonia', '4604000', 'alpha -'], ['lisbon', 'portugal', 'lisbon region', '3035000', 'alpha -'], ['porto', 'portugal', 'norte region', '1676848', 'gamma -'], ['valencia', 'spain', 'community of valencia', '1564145', 'gamma']] |
2005 world weightlifting championships | https://en.wikipedia.org/wiki/2005_World_Weightlifting_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10929638-3.html.csv | comparative | in the 2005 world weightlifting championships , russia won less total medals than china . | {'row_1': '2', 'row_2': '1', 'col': '6', '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', 'nation', 'russia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to russia .', 'tostr': 'filter_eq { all_rows ; nation ; russia }'}, 'total'], 'result': None, 'ind': 2, 'to... | less { hop { filter_eq { all_rows ; nation ; russia } ; total } ; hop { filter_eq { all_rows ; nation ; china } ; total } } = true | select the rows whose nation record fuzzily matches to russia . take the total record of this row . select the rows whose nation record fuzzily matches to china . take the total 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, 'nation_7': 7, 'russia_8': 8, 'total_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'china_12': 12, 'total_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', 'nation_7': 'nation', 'russia_8': 'russia', 'total_9': 'total', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'china_12': 'china', ... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'russia_8': [0], 'total_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'china_12': [1], 'total_13': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'china', '7', '4', '1', '12'], ['2', 'russia', '2', '4', '4', '10'], ['3', 'thailand', '1', '3', '1', '5'], ['4', 'south korea', '1', '2', '0', '2'], ['5', 'azerbaijan', '1', '0', '0', '1'], ['5', 'chinese taipei', '1', '0', '0', '1'], ['5', 'iran', '1', '0', '0', '1'], ['5', 'kazakhstan', '1', '0', '0', '1'], [... |
list of ngc objects ( 5001 - 6000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%285001%E2%80%936000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11051845-9.html.csv | unique | only object 5877 has the object type " triple star . " . | {'scope': 'all', 'row': '9', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'triple star', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'object type', 'triple star'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose object type record fuzzily matches to triple star .', 'tostr': 'filter_eq { all_rows ; object type ; triple star }'}], 'result': Tr... | and { only { filter_eq { all_rows ; object type ; triple star } } ; eq { hop { filter_eq { all_rows ; object type ; triple star } ; ngc number } ; 5877 } } = true | select the rows whose object type record fuzzily matches to triple star . there is only one such row in the table . the ngc number record of this unqiue row is 5877 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'object type_7': 7, 'triple star_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'ngc number_9': 9, '5877_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'object type_7': 'object type', 'triple star_8': 'triple star', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'ngc number_9': 'ngc number', '5877_10': '5877'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'object type_7': [0], 'triple star_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'ngc number_9': [2], '5877_10': [3]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )'] | [['5822', 'open cluster', 'lupus', '15h04 m', 'degree24 ′'], ['5823', 'open cluster', 'circinus', '15h05 m44 .8 s', 'degree37 ′ 30 ″'], ['5824', 'globular cluster', 'lupus', '15h03 m58 .5 s', 'degree04 ′ 04 ″'], ['5825', 'elliptical galaxy', 'boötes', '14h54 m31 .5 s', 'degree38 ′ 31 ″'], ['5838', 'lenticular galaxy', ... |
2007 - 08 carolina hurricanes season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Carolina_Hurricanes_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11772511-6.html.csv | count | in the 2007 - 08 carolina hurricanes season , among the games where carolina was a visitor , 3 of them had attendance over 19,000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '19000', 'result': '3', 'col': '6', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'carolina'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'carolina'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; visitor ; carolina }', 'tointer': 'select the rows whose visitor record fuzzily matches to carolina .'}... | eq { count { filter_greater { filter_eq { all_rows ; visitor ; carolina } ; attendance ; 19000 } } ; 3 } = true | select the rows whose visitor record fuzzily matches to carolina . among these rows , select the rows whose attendance record is greater than 19000 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'visitor_6': 6, 'carolina_7': 7, 'attendance_8': 8, '19000_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'visitor_6': 'visitor', 'carolina_7': 'carolina', 'attendance_8': 'attendance', '19000_9': '19000', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'visitor_6': [0], 'carolina_7': [0], 'attendance_8': [1], '19000_9': [1], '3_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['january 2', 'atlanta', '5 - 4', 'carolina', 'ward', '13506', '20 - 18 - 4'], ['january 4', 'carolina', '4 - 3', 'atlanta', 'leighton', '16097', '21 - 18 - 4'], ['january 5', 'carolina', '0 - 1', 'st louis', 'leighton', '19150', '21 - 19 - 4'], ['january 8', 'carolina', '1 - 0', 'boston', 'ward', '14549', '22 - 19 - ... |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-8.html.csv | comparative | south melbourne had a higher home team score than north melbourne in the 1972 vfl season . | {'row_1': '3', 'row_2': '4', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'south melbourne'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to south melbourne .', 'tostr': 'filter_eq { all_rows ; home team ; south melbourne }'}, ... | greater { hop { filter_eq { all_rows ; home team ; south melbourne } ; home team score } ; hop { filter_eq { all_rows ; home team ; north melbourne } ; home team score } } = true | select the rows whose home team record fuzzily matches to south melbourne . take the home team score record of this row . select the rows whose home team record fuzzily matches to north melbourne . take the home team score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'home team_7': 7, 'south melbourne_8': 8, 'home team score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'north melbourne_12': 12, 'home team score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'home team_7': 'home team', 'south melbourne_8': 'south melbourne', 'home team score_9': 'home team score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_r... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'south melbourne_8': [0], 'home team score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'north melbourne_12': [1], 'home team score_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['collingwood', '7.14 ( 56 )', 'footscray', '11.14 ( 80 )', 'victoria park', '25986', '20 may 1972'], ['melbourne', '20.14 ( 134 )', 'geelong', '14.17 ( 101 )', 'mcg', '19023', '20 may 1972'], ['south melbourne', '9.7 ( 61 )', 'fitzroy', '18.11 ( 119 )', 'lake oval', '12421', '20 may 1972'], ['north melbourne', '8.13 ... |
2007 - 08 detroit pistons season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Detroit_Pistons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11960944-11.html.csv | majority | all games of the detroit pistons ' in the 2007 - 08 season were played in the month of may . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'may', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'may'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to may .', 'tostr': 'all_eq { all_rows ; date ; may } = true'} | all_eq { all_rows ; date ; may } = true | for the date records of all rows , all of them fuzzily match to may . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'may_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'may_4': 'may'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'may_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 20', 'boston', 'l 88 - 79', 'prince ( 16 )', 'mcdyess ( 11 )', 'wallace ( 4 )', 'td banknorth garden 18624', '0 - 1'], ['2', 'may 22', 'boston', 'w 103 - 97', 'hamilton ( 25 )', 'wallace ( 10 )', 'billups ( 7 )', 'td banknorth garden 18624', '1 - 1'], ['3', 'may 24', 'boston', 'l 94 - 80', 'hamilton ( 26 )'... |
doctor who merchandise | https://en.wikipedia.org/wiki/Doctor_Who_merchandise | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1713215-1.html.csv | unique | mission to venus is the only title in the doctor who merchandise series with an unknown isbn us value . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'unknown', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'isbn us', 'unknown'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose isbn us record fuzzily matches to unknown .', 'tostr': 'filter_eq { all_rows ; isbn us ; unknown }'}], 'result': True, 'ind': 1, 'tostr': '... | and { only { filter_eq { all_rows ; isbn us ; unknown } } ; eq { hop { filter_eq { all_rows ; isbn us ; unknown } ; title } ; mission to venus } } = true | select the rows whose isbn us record fuzzily matches to unknown . there is only one such row in the table . the title record of this unqiue row is mission to venus . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'isbn us_7': 7, 'unknown_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'mission to venus_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'isbn us_7': 'isbn us', 'unknown_8': 'unknown', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'mission to venus_10': 'mission to venus'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'isbn us_7': [0], 'unknown_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'mission to venus_10': [3]} | ['title', 'author', 'isbn uk', 'isbn us', 'tv companions featured'] | [['search for the doctor', 'dave martin', 'isbn 0 - 7278 - 2087 - 7', 'isbn 0 - 345 - 33224 - 5', 'k - 9'], ['crisis in space', 'michael holt', 'isbn 0 - 7278 - 2093 - 1', 'isbn 0 - 345 - 33225 - 3', 'peri brown , vislor turlough'], ['the garden of evil', 'dave martin', 'isbn 0 - 7278 - 2113 - x', 'n / a', 'none'], ['m... |
1973 ohio state buckeyes football team | https://en.wikipedia.org/wiki/1973_Ohio_State_Buckeyes_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17824926-1.html.csv | majority | the ohio state buckeyes team won all their games in the month of october during the 1973 football season . | {'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'october'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'result', 'w'], 'result': True, 'ind': 1, 'tointer': 'select the ... | all_eq { filter_eq { all_rows ; date ; october } ; result ; w } = true | select the rows whose date record fuzzily matches to october . for the result records of these rows , all of them fuzzily match to w . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'october_5': 5, 'result_6': 6, 'w_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'october_5': 'october', 'result_6': 'result', 'w_7': 'w'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'october_5': [0], 'result_6': [1], 'w_7': [1]} | ['date', 'opponent', 'rank', 'site', 'result', 'attendance'] | [['september 15', 'minnesota', '3', 'ohio stadium columbus , oh', 'w56 - 7', '86005'], ['september 29', 'tcu', '3', 'ohio stadium columbus , oh', 'w37 - 3', '87439'], ['october 6', 'washington state', '1', 'ohio stadium columbus , oh', 'w27 - 3', '87425'], ['october 13', 'wisconsin', '1', 'camp randall stadium madison ... |
richard gasquet | https://en.wikipedia.org/wiki/Richard_Gasquet | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1750635-8.html.csv | majority | a majority of richard gasquet 's matches took place on hard court . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'date', 'championship', 'surface', 'opponent', 'score'] | [['runner - up', '11 october 2004', 'open de moselle , metz , france', 'hard ( i )', 'jérôme haehnel', '6 - 7 ( 9 - 11 ) , 4 - 6'], ['runner - up', '9 may 2005', 'international german open , hamburg , germany', 'clay', 'roger federer', '3 - 6 , 5 - 7 , 6 - 7 ( 4 - 7 )'], ['winner', '13 june 2005', 'nottingham open , no... |
2007 - 08 washington capitals season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Washington_Capitals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11772462-4.html.csv | unique | the only game johnson was the decision was november 6 . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'johnson', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decision', 'johnson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decision record fuzzily matches to johnson .', 'tostr': 'filter_eq { all_rows ; decision ; johnson }'}], 'result': True, 'ind': 1, 'tostr'... | and { only { filter_eq { all_rows ; decision ; johnson } } ; eq { hop { filter_eq { all_rows ; decision ; johnson } ; date } ; november 6 } } = true | select the rows whose decision record fuzzily matches to johnson . there is only one such row in the table . the date record of this unqiue row is november 6 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'decision_7': 7, 'johnson_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'november 6_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'decision_7': 'decision', 'johnson_8': 'johnson', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'november 6_10': 'november 6'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'decision_7': [0], 'johnson_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'november 6_10': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 1', 'washington', '0 - 2', 'ny rangers', 'kolzig', '18200', '5 - 7 - 0'], ['november 2', 'philadelphia', '3 - 2', 'washington', 'kolzig', '16055', '5 - 8 - 0'], ['november 5', 'washington', '0 - 5', 'carolina', 'kolzig', '12171', '5 - 9 - 0'], ['november 6', 'washington', '1 - 2', 'atlanta', 'johnson', '155... |
2007 - 08 fis ski jumping world cup | https://en.wikipedia.org/wiki/2007%E2%80%9308_FIS_Ski_Jumping_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14407512-16.html.csv | majority | most of the top five ski jumpers finished the fis world cup event with under 500 overall wc points . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '500', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'overall wc points ( rank )', '500'], 'result': True, 'ind': 0, 'tointer': 'for the overall wc points ( rank ) records of all rows , most of them are less than 500 .', 'tostr': 'most_less { all_rows ; overall wc points ( rank ) ; 500 } = true'} | most_less { all_rows ; overall wc points ( rank ) ; 500 } = true | for the overall wc points ( rank ) records of all rows , most of them are less than 500 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'overall wc points (rank)_3': 3, '500_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'overall wc points (rank)_3': 'overall wc points ( rank )', '500_4': '500'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'overall wc points (rank)_3': [0], '500_4': [0]} | ['rank', 'name', 'nationality', '1st ( m )', 'points', 'overall wc points ( rank )'] | [['1', 'anders bardal', 'nor', '137.0', '149.1', '461 ( 6 )'], ['2', 'thomas morgenstern', 'aut', '135.0', '145.0', '1255 ( 1 )'], ['3', 'simon ammann', 'sui', '136.5', '144.2', '448 ( 8 )'], ['4', 'adam małysz', 'pol', '133.5', '141.3', '386 ( 11 )'], ['5', 'andreas küttel', 'sui', '134.0', '141.2', '459 ( 7 )']] |
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 | comparative | edoardo piscopo scored more points during the formula renault 2.0 italy than during the italian formula 3 . | {'row_1': '3', 'row_2': '8', 'col': '8', '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', 'series', 'formula renault 2.0 italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series record fuzzily matches to formula renault 2.0 italy .', 'tostr': 'filter_eq { all_rows ; series ; formula re... | greater { hop { filter_eq { all_rows ; series ; formula renault 2.0 italy } ; points } ; hop { filter_eq { all_rows ; series ; italian formula three } ; points } } = true | select the rows whose series record fuzzily matches to formula renault 2.0 italy . take the points record of this row . select the rows whose series record fuzzily matches to italian formula three . take the points 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, 'series_7': 7, 'formula renault 2.0 italy_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'series_11': 11, 'italian formula three_12': 12, 'points_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', 'series_7': 'series', 'formula renault 2.0 italy_8': 'formula renault 2.0 italy', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows'... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'series_7': [0], 'formula renault 2.0 italy_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'series_11': [1], 'italian formula three_12': [1], 'points_13': [3]} | ['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... |
2009 - 10 a - league | https://en.wikipedia.org/wiki/2009%E2%80%9310_A-League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18793550-6.html.csv | unique | the round 20 game was the only one that was played in december . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'december', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to december .', 'tostr': 'filter_eq { all_rows ; date ; december }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; date ; december } } ; eq { hop { filter_eq { all_rows ; date ; december } ; round } ; 20 } } = true | select the rows whose date record fuzzily matches to december . there is only one such row in the table . the round record of this unqiue row is 20 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'december_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'round_9': 9, '20_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'december_8': 'december', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'round_9': 'round', '20_10': '20'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'date_7': [0], 'december_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'round_9': [2], '20_10': [3]} | ['attendance', 'round', 'date', 'home', 'score', 'away', 'venue', 'weekday', 'time of day'] | [['44560', 'grand final', '20 march 2010', 'melbourne victory', '1 - 1', 'sydney fc', 'etihad stadium', 'saturday', 'evening'], ['32792', 'finals wk 2', '7 march 2010', 'wellington phoenix', '3 - 1', 'newcastle jets', 'westpac stadium', 'sunday', 'afternoon'], ['30668', '10', '9 october 2009', 'melbourne victory', '0 -... |
südtirol | https://en.wikipedia.org/wiki/Politics_of_Trentino-Alto_Adige/S%C3%BCdtirol | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17305625-1.html.csv | majority | most of the mayors in the südtirol region are members of the democratic party . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democratic party', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic party'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic party .', 'tostr': 'most_eq { all_rows ; party ; democratic party } = true'} | most_eq { all_rows ; party ; democratic party } = true | for the party records of all rows , most of them fuzzily match to democratic party . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic party_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic party_4': 'democratic party'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic party_4': [0]} | ['municipality', 'inhabitants', 'mayor', 'party', 'election'] | [['trento', '116298', 'alessandro andreatta', 'democratic party', '2009'], ['rovereto', '38167', 'andrea miorandi', 'democratic party', '2010'], ['pergine valsugana', '20582', 'silvano corradi', 'union for trentino', '2009'], ['arco', '16901', 'paolo mattei', 'democratic party', '2010'], ['riva del garda', '16170', 'ad... |
india national under - 23 football team results | https://en.wikipedia.org/wiki/India_national_under-23_football_team_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25428629-1.html.csv | majority | all of the games in the india national under-23 football team had a team score of at least 1 . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '1', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'score', '1'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , all of them fuzzily match to 1 .', 'tostr': 'all_eq { all_rows ; score ; 1 } = true'} | all_eq { all_rows ; score ; 1 } = true | for the score records of all rows , all of them fuzzily match to 1 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '1_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '1_4': '1'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '1_4': [0]} | ['date', 'tournament', 'location', 'opponent', 'stadium', 'score', 'indian scorers'] | [['23 february 2011', '2012 olympic qualifier', 'pune , india', 'myanmar', 'balewadi sports complex', '2 - 1', 'jeje lalpekhlua , malsawmfela'], ['9 march 2011', '2012 olympic qualifier', 'yangon , myanmar', 'myanmar', 'thuwunna stadium', '1 - 1', 'chinadorai sabeeth'], ['19 june 2011', '2012 olympic qualifier', 'doha ... |
doves discography | https://en.wikipedia.org/wiki/Doves_discography | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10537807-4.html.csv | unique | among the songs , here it comes is the only song that was released in august . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'august', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'release date', 'august'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose release date record fuzzily matches to august .', 'tostr': 'filter_eq { all_rows ; release date ; august }'}], 'result': True, 'ind': 1... | and { only { filter_eq { all_rows ; release date ; august } } ; eq { hop { filter_eq { all_rows ; release date ; august } ; song } ; here it comes } } = true | select the rows whose release date record fuzzily matches to august . there is only one such row in the table . the song record of this unqiue row is here it comes . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'release date_7': 7, 'august_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'song_9': 9, 'here it comes_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'release date_7': 'release date', 'august_8': 'august', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'song_9': 'song', 'here it comes_10': 'here it comes'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'release date_7': [0], 'august_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'song_9': [2], 'here it comes_10': [3]} | ['song', 'release date', 'release info', 'formats', 'album'] | [['here it comes', '2 august 1999', 'casino ( chip003 )', 'cd , 10 vinyl', 'here it comes ep'], ['the cedar room', '20 march 2000', 'heavenly ( hvn95 )', 'cd , 10 vinyl', 'lost souls'], ['catch the sun', '29 may 2000', 'heavenly ( hvn96 )', 'cd1 , cd2 , 10 vinyl', 'lost souls'], ['the man who told everything', '30 octo... |
list of longest suspension bridge spans | https://en.wikipedia.org/wiki/List_of_longest_suspension_bridge_spans | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1604842-2.html.csv | unique | hålogaland bridge is the only norwegian bridge to appear on the list of longest suspension bridge spans . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'norway', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'norway'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to norway .', 'tostr': 'filter_eq { all_rows ; country ; norway }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; country ; norway } } ; eq { hop { filter_eq { all_rows ; country ; norway } ; name } ; hålogaland bridge } } = true | select the rows whose country record fuzzily matches to norway . there is only one such row in the table . the name record of this unqiue row is hålogaland bridge . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'norway_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'hålogaland bridge_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', 'norway_8': 'norway', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'hålogaland bridge_10': 'hålogaland bridge'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'norway_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'hålogaland bridge_10': [3]} | ['name', 'main span metres', 'main span feet', 'year to open', 'country'] | [['izmit bay bridge', '1550', '5085', '2017', 'turkey'], ['yavuz sultan selim bridge', '1408', '4619', '2015', 'turkey'], ['longjiang river bridge', '1196', '3924', '2015', 'china'], ['longmen bridge ( guangxi )', '1160', '3806', '2016', 'china'], ['ulsan bridge', '1150', '3773', '2014', 'south korea'], ['hålogaland br... |
the sunday night project | https://en.wikipedia.org/wiki/The_Sunday_Night_Project | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1590967-2.html.csv | comparative | the episode with guest host jessie wallace aired 7 days before the episode with guest host trisha goddard . | {'row_1': '7', 'row_2': '8', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'guest host', 'jessie wallace'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose guest host record fuzzily matches to jessie wallace .', 'tostr': 'filter_eq { all_rows ; guest host ... | and { less { hop { filter_eq { all_rows ; guest host ; jessie wallace } ; air date } ; hop { filter_eq { all_rows ; guest host ; trisha goddard } ; air date } } ; and { eq { hop { filter_eq { all_rows ; guest host ; jessie wallace } ; air date } ; 17 february 2006 } ; eq { hop { filter_eq { all_rows ; guest host ; tris... | select the rows whose guest host record fuzzily matches to jessie wallace . take the air date record of this row . select the rows whose guest host record fuzzily matches to trisha goddard . take the air date record of this row . the first record is less than the second record . the air date record of the first row is ... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'guest host_11': 11, 'jessie wallace_12': 12, 'air date_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'guest host_15': 15, 'trisha goddard_16': 16, 'air date_17': 17, 'and_7': 7, 'str_eq_5': 5, '17 febr... | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'guest host_11': 'guest host', 'jessie wallace_12': 'jessie wallace', 'air date_13': 'air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_r... | {'and_8': [9], 'result_9': [], 'less_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'guest host_11': [0], 'jessie wallace_12': [0], 'air date_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'guest host_15': [1], 'trisha goddard_16': [1], 'air date_17': [3], 'and_7':... | ['episode number', 'air date', 'guest host', 'musical guest ( song performed )', 'who knows the most about the guest host panelists'] | [['1', '6 january 2006', 'billie piper', 'texas ( sleep )', 'jade goody and kenzie'], ['2', '13 january 2006', 'lorraine kelly', 'editors ( munich )', 'myleene klass and phil tufnell'], ['3', '20 january 2006', 'christian slater', "the kooks ( you do n't love me )", 'lady isabella hervey and fearne cotton'], ['4', '27 ... |
loonie | https://en.wikipedia.org/wiki/Loonie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18400-2.html.csv | aggregation | the total mintage of all the special loonies produced between 2002 - 2012 is 418918 coins . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '418918', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'mintage'], 'result': '418918', 'ind': 0, 'tostr': 'sum { all_rows ; mintage }'}, '418918'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; mintage } ; 418918 } = true', 'tointer': 'the sum of the mintage record of all rows is 418918 .'... | round_eq { sum { all_rows ; mintage } ; 418918 } = true | the sum of the mintage record of all rows is 418918 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'mintage_4': 4, '418918_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'mintage_4': 'mintage', '418918_5': '418918'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'mintage_4': [0], '418918_5': [1]} | ['year', 'theme', 'artist', 'mintage', 'issue price'] | [['2002', '15th anniversary loonie', 'dora de pãdery - hunt', '67672', '39.95'], ['2004', 'jack miner bird sanctuary', 'susan taylor', '46493', '39.95'], ['2005', 'tufted puffin', 'n / a', '39818', '39.95'], ['2006', 'snowy owl', 'glen loates', '39935', '44.95'], ['2007', 'trumpeter swan', 'kerri burnett', '40000', '45... |
ricardo páez | https://en.wikipedia.org/wiki/Ricardo_P%C3%A1ez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14394530-1.html.csv | unique | the match on sept 4 , 2001 was the only one taking place in chile . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'chile', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'chile'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to chile .', 'tostr': 'filter_eq { all_rows ; venue ; chile }'}], 'result': True, 'ind': 1, 'tostr': 'only { filte... | and { only { filter_eq { all_rows ; venue ; chile } } ; eq { hop { filter_eq { all_rows ; venue ; chile } ; date } ; september 4 , 2001 } } = true | select the rows whose venue record fuzzily matches to chile . there is only one such row in the table . the date record of this unqiue row is september 4 , 2001 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'chile_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'september 4 , 2001_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'chile_8': 'chile', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'september 4 , 2001_10': 'september 4 , 2001'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'chile_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'september 4 , 2001_10': [3]} | ['goal', 'date', 'venue', 'score', 'result', 'competition'] | [['1', 'september 4 , 2001', 'estadio nacional de chile , santiago , chile', '0 - 1', '0 - 2', '2002 world cup qualification'], ['2', 'november 20 , 2002', 'brígido iriarte , caracas , venezuela', '1 - 0', '1 - 0', 'friendly'], ['3', 'april 2 , 2003', 'brígido iriarte , caracas , venezuela', '2 - 0', '2 - 0', 'friendly... |
scottish parliament general election , 2007 | https://en.wikipedia.org/wiki/Scottish_Parliament_general_election%2C_2007 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11105214-1.html.csv | count | liberal democrats were the winning party in 2003 for 3 constituencies . | {'scope': 'all', 'criterion': 'equal', 'value': 'liberal democrats', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning party 2003', 'liberal democrats'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning party 2003 record fuzzily matches to liberal democrats .', 'tostr': 'filter_eq { all_rows ; winning party 2003... | eq { count { filter_eq { all_rows ; winning party 2003 ; liberal democrats } } ; 3 } = true | select the rows whose winning party 2003 record fuzzily matches to liberal democrats . 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, 'winning party 2003_5': 5, 'liberal democrats_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', 'winning party 2003_5': 'winning party 2003', 'liberal democrats_6': 'liberal democrats', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winning party 2003_5': [0], 'liberal democrats_6': [0], '3_7': [2]} | ['rank', 'constituency', 'winning party 2003', 'swing to gain', "labour 's place 2003", 'result'] | [['1', 'dundee east', 'snp', '0.17', '2nd', 'snp hold'], ['2', 'edinburgh south', 'liberal democrats', '0.26', '2nd', 'ld hold'], ['3', 'ochil', 'snp', '0.49', '2nd', 'snp hold'], ['4', 'strathkelvin and bearsden', 'independent', '0.62', '2nd', 'lab gain'], ['5', 'aberdeen north', 'snp', '0.92', '2nd', 'snp hold'], ['6... |
list of how it 's made episodes | https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15187735-6.html.csv | unique | in netflix list of how it 's made s03e25 is the only tv series that has recorded 77 episodes . | {'scope': 'all', 'row': '12', 'col': '2', 'col_other': '3', 'criterion': 'equal', 'value': '77', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'episode', '77'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episode record is equal to 77 .', 'tostr': 'filter_eq { all_rows ; episode ; 77 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_row... | and { only { filter_eq { all_rows ; episode ; 77 } } ; eq { hop { filter_eq { all_rows ; episode ; 77 } ; netflix } ; s03e25 } } = true | select the rows whose episode record is equal to 77 . there is only one such row in the table . the netflix record of this unqiue row is s03e25 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'episode_7': 7, '77_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'netflix_9': 9, 's03e25_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'episode_7': 'episode', '77_8': '77', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'netflix_9': 'netflix', 's03e25_10': 's03e25'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'episode_7': [0], '77_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'netflix_9': [2], 's03e25_10': [3]} | ['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d'] | [['6 - 01', '66', 's03e14', 'three wheeled vehicles', 'baseball bats', 'artificial bonsai', 's trombone'], ['6 - 02', '67', 's03e15', 's spring', 's paver', 's piano ( part 1 )', 's piano ( part 2 )'], ['6 - 03', '68', 's03e16', 's rope', 's billiard table', 's sailboard', 's cymbal'], ['6 - 04', '69', 's03e17', 's sea... |
1959 toronto argonauts season | https://en.wikipedia.org/wiki/1959_Toronto_Argonauts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24136814-3.html.csv | comparative | the game played on week 8 drew a higher attendance than the game played on week 10 . | {'row_1': '10', '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', 'week', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose week record fuzzily matches to 8 .', 'tostr': 'filter_eq { all_rows ; week ; 8 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { ... | greater { hop { filter_eq { all_rows ; week ; 8 } ; attendance } ; hop { filter_eq { all_rows ; week ; 10 } ; attendance } } = true | select the rows whose week record fuzzily matches to 8 . take the attendance record of this row . select the rows whose week record fuzzily matches to 10 . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'week_7': 7, '8_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'week_11': 11, '10_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'week_7': 'week', '8_8': '8', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'week_11': 'week', '10_12': '10', 'attenda... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'week_7': [0], '8_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'week_11': [1], '10_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'location', 'final score', 'attendance', 'record'] | [['1', 'august 18', 'rough riders', 'landsdowne park', 'w 21 - 20', '20675', '1 - 0 - 0'], ['1', 'august 21', 'tiger - cats', 'exhibition stadium', 'l 16 - 7', '27554', '1 - 1 - 0'], ['2', 'august 28', 'alouettes', 'molson stadium', 'l 24 - 6', '23927', '1 - 2 - 0'], ['3', 'september 7', 'tiger - cats', 'civic stadium'... |
1979 new york jets season | https://en.wikipedia.org/wiki/1979_New_York_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13834389-1.html.csv | comparative | the game against the new england patriots had higher attendance than the game against the cleveland browns . | {'row_1': '2', 'row_2': '1', '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', 'new england patriots'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to new england patriots .', 'tostr': 'filter_eq { all_rows ; opponent ; new england pa... | greater { hop { filter_eq { all_rows ; opponent ; new england patriots } ; attendance } ; hop { filter_eq { all_rows ; opponent ; cleveland browns } ; attendance } } = true | select the rows whose opponent record fuzzily matches to new england patriots . take the attendance record of this row . select the rows whose opponent record fuzzily matches to cleveland browns . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'new england patriots_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'cleveland browns_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'new england patriots_8': 'new england patriots', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_row... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'new england patriots_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'cleveland browns_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', '1979 - 09 - 02', 'cleveland browns', 'l 25 - 22 ( ot )', 'shea stadium', '48472'], ['2', '1979 - 09 - 09', 'new england patriots', 'l 56 - 3', 'schafer stadium', '53113'], ['3', '1979 - 09 - 16', 'detroit lions', 'w 31 - 10', 'shea stadium', '49612'], ['4', '1979 - 09 - 23', 'buffalo bills', 'l 46 - 31', 'rich ... |
what a lemon | https://en.wikipedia.org/wiki/What_a_Lemon | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16752996-2.html.csv | unique | the only version of what a lemon formatted in a double cd was the version from scandinavia in 2002 . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '1,2', 'criterion': 'equal', 'value': 'double cd', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'double cd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose format record fuzzily matches to double cd .', 'tostr': 'filter_eq { all_rows ; format ; double cd }'}], 'result': True, 'ind': 1, 'tostr'... | and { only { filter_eq { all_rows ; format ; double cd } } ; and { eq { hop { filter_eq { all_rows ; format ; double cd } ; region } ; scandinavia } ; eq { hop { filter_eq { all_rows ; format ; double cd } ; date } ; 2002 } } } = true | select the rows whose format record fuzzily matches to double cd . there is only one such row in the table . the region record of this unqiue row is scandinavia . the date record of this unqiue row is 2002 . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'format_10': 10, 'double cd_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'region_12': 12, 'scandinavia_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'date_14': 14, '2002_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'format_10': 'format', 'double cd_11': 'double cd', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'region_12': 'region', 'scandinavia_13': 'scandinavia', 'str_eq_5': 'str_eq', 'str_hop_4'... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'format_10': [0], 'double cd_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'region_12': [2], 'scandinavia_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'date_14': [4], '2002_15': [5]} | ['region', 'date', 'label', 'format', 'catalog'] | [['united states', '1 august 1976', 'epic records', 'stereo lp', 'pe 34149'], ['europe', '1 august 1976', 'epic records', 'stereo lp', 'epc 81436'], ['australia', '15 november 1976', 'epic records', 'stereo lp', 'elps 3781'], ['japan', '1976', 'epic records', 'stereo lp', '25ap 301'], ['scandinavia', '2002', 'sony musi... |
atlanta falcons draft history | https://en.wikipedia.org/wiki/Atlanta_Falcons_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15198842-20.html.csv | comparative | mike gann was drafted in an earlier round by the atlanta falcons than brent martin . | {'row_1': '2', 'row_2': '8', 'col': '1', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'mike gann'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to mike gann .', 'tostr': 'filter_eq { all_rows ; name ; mike gann }'}, 'round'], 'result': None, 'ind': 2, ... | less { hop { filter_eq { all_rows ; name ; mike gann } ; round } ; hop { filter_eq { all_rows ; name ; brent martin } ; round } } = true | select the rows whose name record fuzzily matches to mike gann . take the round record of this row . select the rows whose name record fuzzily matches to brent martin . take the round record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'mike gann_8': 8, 'round_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'brent martin_12': 12, 'round_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'mike gann_8': 'mike gann', 'round_9': 'round', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'brent martin_12': 'bre... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'mike gann_8': [0], 'round_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'brent martin_12': [1], 'round_13': [3]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '2', '2', 'bill fralic', 'guard', 'pittsburgh'], ['2', '17', '45', 'mike gann', 'defensive end', 'notre dame'], ['4', '5', '89', 'emile harry', 'wide receiver', 'stanford'], ['6', '12', '152', 'reggie pleasant', 'defensive back', 'clemson'], ['8', '5', '201', 'ashley lee', 'defensive back', 'virginia tech'], ['8... |
2010 - 11 temple owls men 's basketball team | https://en.wikipedia.org/wiki/2010%E2%80%9311_Temple_Owls_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29556461-8.html.csv | majority | the majority of games at liacouras center during the 2010 - 11 temple owls men 's basketball team season had an attendance over 5000 . | {'scope': 'subset', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '5000', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'liacouras center'}} | {'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'liacouras center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; liacouras center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to liacouras cen... | most_greater { filter_eq { all_rows ; location attendance ; liacouras center } ; location attendance ; 5000 } = true | select the rows whose location attendance record fuzzily matches to liacouras center . for the location attendance records of these rows , most of them are greater than 5000 . | 2 | 2 | {'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location attendance_4': 4, 'liacouras center_5': 5, 'location attendance_6': 6, '5000_7': 7} | {'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location attendance_4': 'location attendance', 'liacouras center_5': 'liacouras center', 'location attendance_6': 'location attendance', '5000_7': '5000'} | {'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location attendance_4': [0], 'liacouras center_5': [0], 'location attendance_6': [1], '5000_7': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['21', 'february 2', 'la salle', 'w 71 - 67', 'wyatt - 18', 'allen - 7', 'moore - 5', 'tom gola arena , philadelphia , pa ( 3121 )', '16 - 5 ( 6 - 2 )'], ['22', 'february 5', 'rhode island', 'w 80 - 67', 'randall - 27', 'allen - 10', 'moore / fernandez - 6', 'liacouras center , philadelphia , pa ( 8679 )', '17 - 5 ( 7... |
wwfm | https://en.wikipedia.org/wiki/WWFM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12472016-2.html.csv | ordinal | w300ac has the 2nd highest erp w among all call signs . | {'row': '5', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'erp w', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; erp w ; 2 }'}, 'call sign'], 'result': 'w300ac', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; erp w ; 2 } ; call sign }'}, 'w300ac'], 'resu... | eq { hop { nth_argmax { all_rows ; erp w ; 2 } ; call sign } ; w300ac } = true | select the row whose erp w record of all rows is 2nd maximum . the call sign record of this row is w300ac . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'erp w_5': 5, '2_6': 6, 'call sign_7': 7, 'w300ac_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', 'erp w_5': 'erp w', '2_6': '2', 'call sign_7': 'call sign', 'w300ac_8': 'w300ac'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'erp w_5': [0], '2_6': [0], 'call sign_7': [1], 'w300ac_8': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k216fw', '91.1 fm', 'steamboat springs , colorado', '10', 'd', 'fcc'], ['w224au', '92.7 fm', 'allentown , pennsylvania', '8', 'd', 'fcc'], ['w226aa', '93.1 fm', 'easton , pennsylvania', '150', 'd', 'fcc'], ['w245ac', '96.9 fm', 'harmony township , new jersey', '10', 'd', 'fcc'], ['w300ac', '107.9 fm', 'chatsworth , ... |
mohammed nasser shakroun | https://en.wikipedia.org/wiki/Mohammed_Nasser_Shakroun | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13607991-4.html.csv | majority | all of mohammed nasser shakroun 's international goals were scored in friendly matches . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'friendly match', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'competition', 'friendly match'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , all of them fuzzily match to friendly match .', 'tostr': 'all_eq { all_rows ; competition ; friendly match } = true'} | all_eq { all_rows ; competition ; friendly match } = true | for the competition records of all rows , all of them fuzzily match to friendly match . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly match_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly match_4': 'friendly match'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly match_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['26 march 2005', 'telstra stadium , sydney', '1 - 0', '1 - 2', 'friendly match'], ['7 august 2005', 'bahrain national stadium , manama', '1 - 2', '2 - 2', 'friendly match'], ['13 august 2005', 'tsirion stadium , limassol', '1 - 0', '2 - 1', 'friendly match'], ['15 march 2006', 'prince abdullah al - faisal stadium , j... |
2007 georgia force season | https://en.wikipedia.org/wiki/2007_Georgia_Force_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11710574-4.html.csv | count | there were four members of the georgia force that had at least three rushing touchdowns during the 2007 season . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '3', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', "td 's", '3'], 'result': None, 'ind': 0, 'tointer': "select the rows whose td 's record is greater than or equal to 3 .", 'tostr': "filter_greater_eq { all_rows ; td 's ; 3 }"}], 'result': '4', 'ind': 1, 'tostr': "coun... | eq { count { filter_greater_eq { all_rows ; td 's ; 3 } } ; 4 } = true | select the rows whose td 's record is greater than or equal to 3 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, "td 's_5": 5, '3_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', "td 's_5": "td 's", '3_6': '3', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], "td 's_5": [0], '3_6': [0], '4_7': [2]} | ['player', 'car', 'yards', 'avg', "td 's", 'long'] | [['matt huebner', '34', '122', '3.6', '5', '24'], ['troy bergeron', '10', '81', '8.1', '0', '19'], ['john ritcher', '20', '58', '2.9', '2', '21'], ['chris greisen', '14', '25', '1.8', '6', '12'], ['chris jackson', '9', '19', '2.1', '4', '8'], ['jarrick hillery', '11', '9', '8', '3', '4'], ['derek lee', '1', '2', '2', '... |
2007 - 08 segunda división | https://en.wikipedia.org/wiki/2007%E2%80%9308_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11828307-4.html.csv | ordinal | out of all goalkeepers of the 2007-08 segunda division , jacobo had the 2nd best average . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'average', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; average ; 2 }'}, 'goalkeeper'], 'result': 'jacobo', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; average ; 2 } ; goalkeeper }'}, 'jacobo'... | eq { hop { nth_argmin { all_rows ; average ; 2 } ; goalkeeper } ; jacobo } = true | select the row whose average record of all rows is 2nd minimum . the goalkeeper record of this row is jacobo . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'average_5': 5, '2_6': 6, 'goalkeeper_7': 7, 'jacobo_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', 'average_5': 'average', '2_6': '2', 'goalkeeper_7': 'goalkeeper', 'jacobo_8': 'jacobo'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'average_5': [0], '2_6': [0], 'goalkeeper_7': [1], 'jacobo_8': [2]} | ['goalkeeper', 'goals', 'matches', 'average', 'team'] | [['carlos sánchez', '27', '33', '0.82', 'cd castellón'], ['jacobo', '29', '32', '0.91', 'cd numancia'], ['asier riesgo', '39', '42', '0.93', 'real sociedad'], ['roberto', '39', '41', '0.95', 'sporting de gijón'], ['iñaki goitia', '41', '40', '1.02', 'málaga cf'], ['pedro contreras', '37', '36', '1.03', 'cádiz cf'], ['w... |
list of post - secondary institutions in malaysia | https://en.wikipedia.org/wiki/List_of_post-secondary_institutions_in_Malaysia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18144241-2.html.csv | majority | most of the post-secondary institutions in malaysia do not have an acronym . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '-', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'acronym', '-'], 'result': True, 'ind': 0, 'tointer': 'for the acronym records of all rows , most of them fuzzily match to - .', 'tostr': 'most_eq { all_rows ; acronym ; - } = true'} | most_eq { all_rows ; acronym ; - } = true | for the acronym records of all rows , most of them fuzzily match to - . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'acronym_3': 3, '-_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'acronym_3': 'acronym', '-_4': '-'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'acronym_3': [0], '-_4': [0]} | ['name in english', 'name in malay', 'acronym', 'foundation', 'location'] | [['alor setar professional institute', 'institut profesional alor setar', '-', '-', 'alor setar'], ['a n s technological institute , alor setar', 'institut teknologi a n s alor setar', '-', '-', 'alor setar'], ['bandar darulaman community college', 'kolej komuniti bandar darulaman', '-', '-', 'jitra'], ['daya ilmu tech... |
monica niculescu | https://en.wikipedia.org/wiki/Monica_Niculescu | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15272343-4.html.csv | majority | the majority of the matches were played on a hard surface . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'date', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', '17 august 2008', 'hard', 'sorana cîrstea', 'květa peschke lisa raymond', '6 - 4 , 5 - 7 ,'], ['winner', '12 july 2009', 'clay', 'alisa kleybanova', 'alona bondarenko kateryna bondarenko', '6 - 4 , 7 - 6 ( 7 - 5 )'], ['runner - up', '2 august 2009', 'hard', 'chan yung - jan', 'serena williams venus wil... |
1996 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1996_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162199-5.html.csv | count | two of the players in the 1996 u.s. open golf tournament were from the country of scotland . | {'scope': 'all', 'criterion': 'equal', 'value': 'scotland', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'scotland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to scotland .', 'tostr': 'filter_eq { all_rows ; country ; scotland }'}], 'result': '2', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; country ; scotland } } ; 2 } = true | select the rows whose country record fuzzily matches to scotland . 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, 'country_5': 5, 'scotland_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', 'country_5': 'country', 'scotland_6': 'scotland', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'scotland_6': [0], '2_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'tom lehman', 'united states', '71 + 72 + 65 = 208', '- 2'], ['2', 'steve jones', 'united states', '74 + 66 + 69 = 209', '- 1'], ['t3', 'davis love iii', 'united states', '71 + 69 + 70 = 210', 'e'], ['t3', 'john morse', 'united states', '68 + 74 + 68 = 210', 'e'], ['t3', 'frank nobilo', 'new zealand', '69 + 71 +... |
1977 - 78 coupe de france | https://en.wikipedia.org/wiki/1977%E2%80%9378_Coupe_de_France | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17905518-1.html.csv | superlative | fc nantes was the team that scored the highest number of goals in the 1977-78 coupe de france . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '7', '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', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'team 1'], 'result': 'fc nantes ( d1 )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; team 1 }'}, 'fc nantes ( d1 )'], 'result': True, ... | eq { hop { argmax { all_rows ; score } ; team 1 } ; fc nantes ( d1 ) } = true | select the row whose score record of all rows is maximum . the team 1 record of this row is fc nantes ( d1 ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'team 1_6': 6, 'fc nantes (d1)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'team 1_6': 'team 1', 'fc nantes (d1)_7': 'fc nantes ( d1 )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'team 1_6': [1], 'fc nantes (d1)_7': [2]} | ['team 1', 'score', 'team 2', '1st round', '2nd round'] | [['stade de reims ( d1 )', '1 - 3', 'sc bastia ( d1 )', '0 - 1', '1 - 2'], ['fc metz ( d1 )', '0 - 5', 'ogc nice ( d1 )', '0 - 2', '0 - 3'], ['olympique de marseille ( d1 )', '3 - 0', 'girondins de bordeaux ( d1 )', '1 - 0', '2 - 0'], ['as nancy ( d1 )', '3 - 1', 'fc martigues ( d2 )', '2 - 0', '1 - 1'], ['lille osc ( ... |
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