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wafj | https://en.wikipedia.org/wiki/WAFJ | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12499438-1.html.csv | unique | for wafj , when the class is d , the only time the city is sparta is when the frequency is 98.7 . | {'scope': 'subset', 'row': '5', 'col': '2', 'col_other': '3', 'criterion': 'equal', 'value': '98.7', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'd'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'd'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; class ; d }', 'tointer': 'select the rows whose class record fuzzily matches to d .'}, 'frequency mhz', '98.7'], 'res... | and { only { filter_eq { filter_eq { all_rows ; class ; d } ; frequency mhz ; 98.7 } } ; eq { hop { filter_eq { filter_eq { all_rows ; class ; d } ; frequency mhz ; 98.7 } ; city of license } ; sparta , georgia } } = true | select the rows whose class record fuzzily matches to d . among these rows , select the rows whose frequency mhz record is equal to 98.7 . there is only one such row in the table . the city of license record of this unqiue row is sparta , georgia . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'class_8': 8, 'd_9': 9, 'frequency mhz_10': 10, '98.7_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'city of license_12': 12, 'sparta , georgia_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'class_8': 'class', 'd_9': 'd', 'frequency mhz_10': 'frequency mhz', '98.7_11': '98.7', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'city of license_12': 'city of license', ... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'class_8': [0], 'd_9': [0], 'frequency mhz_10': [1], '98.7_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'city of license_12': [3], 'sparta , georgia_13': [4]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['wzae', '93.3', 'wadley , georgia', '4000', 'a', 'fcc'], ['w257bg', '99.3', 'statesboro , georgia', '80', 'd', 'fcc'], ['w252bh', '98.3', 'washington , georgia', '27', 'd', 'fcc'], ['w224be', '92.7', 'sylvania , georgia', '27', 'd', 'fcc'], ['w254bn', '98.7', 'sparta , georgia', '55', 'd', 'fcc'], ['w245an', '96.9', ... |
list of carnivàle episodes | https://en.wikipedia.org/wiki/List_of_Carniv%C3%A0le_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12722302-3.html.csv | unique | the only episode of carnivale that was directed by tucker gates , was the one titled " the road to damascus " . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'tucker gates', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'tucker gates'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to tucker gates .', 'tostr': 'filter_eq { all_rows ; directed by ; tucker gates }'}], 'result':... | and { only { filter_eq { all_rows ; directed by ; tucker gates } } ; eq { hop { filter_eq { all_rows ; directed by ; tucker gates } ; title } ; the road to damascus } } = true | select the rows whose directed by record fuzzily matches to tucker gates . there is only one such row in the table . the title record of this unqiue row is the road to damascus . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'directed by_7': 7, 'tucker gates_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'the road to damascus_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'directed by_7': 'directed by', 'tucker gates_8': 'tucker gates', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'the road to damascus_10': 'the road to damascus'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'directed by_7': [0], 'tucker gates_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'the road to damascus_10': [3]} | ['no', '-', 'title', 'directed by', 'written by', 'bens location', 'original air date', 'us viewers ( million )'] | [['13', '1', 'los moscos', 'jeremy podeswa', 'daniel knauf', 'loving , new mexico', 'january 9 , 2005', '1.81'], ['14', '2', 'alamogordo , nm', 'jack bender', 'william schmidt', 'alamogordo , new mexico', 'january 16 , 2005', 'n / a'], ['15', '3', 'ingram , tx', 'john patterson', 'john j mclaughlin', 'ingram , texas', ... |
new york state election , 1966 | https://en.wikipedia.org/wiki/New_York_state_election%2C_1966 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15558974-1.html.csv | count | in the 1966 new york state election , the social labor ticket did not run candidates in two races . | {'scope': 'all', 'criterion': 'equal', 'value': '( none )', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'socialist labor ticket', '( none )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose socialist labor ticket record fuzzily matches to ( none ) .', 'tostr': 'filter_eq { all_rows ; socialist labor ticket ; ( n... | eq { count { filter_eq { all_rows ; socialist labor ticket ; ( none ) } } ; 2 } = true | select the rows whose socialist labor ticket record fuzzily matches to ( none ) . 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, 'socialist labor ticket_5': 5, '(none)_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', 'socialist labor ticket_5': 'socialist labor ticket', '(none)_6': '( none )', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'socialist labor ticket_5': [0], '(none)_6': [0], '2_7': [2]} | ['office', 'republican ticket', 'democratic ticket', 'conservative ticket', 'liberal ticket', 'socialist labor ticket', 'socialist workers ticket'] | [['governor', 'nelson a rockefeller', "frank d o'connor", 'paul l adams', 'franklin d roosevelt , jr', 'milton herder', 'judith white'], ['lieutenant governor', 'malcolm wilson', 'howard j samuels', "kieran o'doherty", 'donald s harrington', 'doris ballantyne', 'richard garza'], ['comptroller', 'charles t lanigan', 'ar... |
1974 vfl season | https://en.wikipedia.org/wiki/1974_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10869646-9.html.csv | unique | only the richmond vs. collingwood game took place in mcg . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1,3', 'criterion': 'equal', 'value': 'mcg', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'mcg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to mcg .', 'tostr': 'filter_eq { all_rows ; venue ; mcg }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq {... | and { only { filter_eq { all_rows ; venue ; mcg } } ; and { eq { hop { filter_eq { all_rows ; venue ; mcg } ; home team } ; richmond } ; eq { hop { filter_eq { all_rows ; venue ; mcg } ; away team } ; collingwood } } } = true | select the rows whose venue record fuzzily matches to mcg . there is only one such row in the table . the home team record of this unqiue row is richmond . the away team record of this unqiue row is collingwood . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'venue_10': 10, 'mcg_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_12': 12, 'richmond_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'away team_14': 14, 'collingwood_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'venue_10': 'venue', 'mcg_11': 'mcg', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_12': 'home team', 'richmond_13': 'richmond', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', '... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'venue_10': [0], 'mcg_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'home team_12': [2], 'richmond_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'away team_14': [4], 'collingwood_15': [5]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '18.15 ( 123 )', 'st kilda', '10.16 ( 76 )', 'princes park', '12630', '1 june 1974'], ['geelong', '16.12 ( 108 )', 'south melbourne', '17.7 ( 109 )', 'kardinia park', '15664', '1 june 1974'], ['footscray', '13.16 ( 94 )', 'melbourne', '8.8 ( 56 )', 'western oval', '15415', '1 june 1974'], ['north melbourn... |
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 | unique | the game of the england national rugby union team against south africa was the only test game in 1961 . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'test match', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'test match'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to test match .', 'tostr': 'filter_eq { all_rows ; status ; test match }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; status ; test match } } ; eq { hop { filter_eq { all_rows ; status ; test match } ; opposing teams } ; south africa } } = true | select the rows whose status record fuzzily matches to test match . there is only one such row in the table . the opposing teams record of this unqiue row is south africa . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'status_7': 7, 'test match_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opposing teams_9': 9, 'south africa_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', 'test match_8': 'test match', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opposing teams_9': 'opposing teams', 'south africa_10': 'south africa'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'status_7': [0], 'test match_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opposing teams_9': [2], 'south africa_10': [3]} | ['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... |
iran at the asian games | https://en.wikipedia.org/wiki/Iran_at_the_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10882501-1.html.csv | aggregation | the average rank for iran in asian games they participated in was 5.53 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '5.53', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'rank'], 'result': '5.53', 'ind': 0, 'tostr': 'avg { all_rows ; rank }'}, '5.53'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; rank } ; 5.53 } = true', 'tointer': 'the average of the rank record of all rows is 5.53 .'} | round_eq { avg { all_rows ; rank } ; 5.53 } = true | the average of the rank record of all rows is 5.53 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'rank_4': 4, '5.53_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'rank_4': 'rank', '5.53_5': '5.53'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'rank_4': [0], '5.53_5': [1]} | ['games', 'gold', 'silver', 'bronze', 'total', 'rank'] | [['1951 new delhi', '8', '6', '2', '16', '3'], ['1954 manila', 'did not participate', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1958 tokyo', '7', '14', '11', '32', '4'], ['1962 jakarta', 'did not participate', 'did not participate', 'did not participate', 'did not pa... |
1972 vfl season | https://en.wikipedia.org/wiki/1972_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826385-12.html.csv | superlative | among away teams in the 1972 vfl season , footscray had the highest recorded score . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'away team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; away team score }'}, 'away team'], 'result': 'footscray', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; away team score } ; away team }'}, 'footscr... | eq { hop { argmax { all_rows ; away team score } ; away team } ; footscray } = true | select the row whose away team score record of all rows is maximum . the away team record of this row is footscray . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'away team score_5': 5, 'away team_6': 6, 'footscray_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'away team score_5': 'away team score', 'away team_6': 'away team', 'footscray_7': 'footscray'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'away team score_5': [0], 'away team_6': [1], 'footscray_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '7.8 ( 50 )', 'st kilda', '12.19 ( 91 )', 'arden street oval', '10681', '17 june 1972'], ['collingwood', '11.24 ( 90 )', 'richmond', '12.13 ( 85 )', 'victoria park', '28188', '17 june 1972'], ['melbourne', '11.10 ( 76 )', 'hawthorn', '11.9 ( 75 )', 'mcg', '31314', '17 june 1972'], ['geelong', '15.1... |
1989 all - ireland senior hurling championship | https://en.wikipedia.org/wiki/1989_All-Ireland_Senior_Hurling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12296897-3.html.csv | superlative | in the 1989 all - ireland senior hurling championship , finbarr delaney had the lowest total among all players with 8.00 average . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2,7', 'subset': {'col': '7', 'criterion': 'equal', 'value': '8.0'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'average', '8.0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; average ; 8.0 }', 'tointer': 'select the rows whose average record is equal to 8.0 .'}, 'total'], 'result': None, ... | eq { hop { argmin { filter_eq { all_rows ; average ; 8.0 } ; total } ; player } ; finbarr delaney } = true | select the rows whose average record is equal to 8.0 . select the row whose total record of these rows is minimum . the player record of this row is finbarr delaney . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'average_6': 6, '8.0_7': 7, 'total_8': 8, 'player_9': 9, 'finbarr delaney_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'average_6': 'average', '8.0_7': '8.0', 'total_8': 'total', 'player_9': 'player', 'finbarr delaney_10': 'finbarr delaney'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'average_6': [0], '8.0_7': [0], 'total_8': [1], 'player_9': [2], 'finbarr delaney_10': [3]} | ['rank', 'player', 'county', 'tally', 'total', 'matches', 'average'] | [['1', 'nicky english', 'tipperary', '4 - 38', '50', '4', '12.50'], ['2', 'adrian ronan', 'kilkenny', '1 - 21', '24', '3', '8.00'], ['2', 'mark corrigan', 'offaly', '4 - 12', '24', '3', '8.00'], ['4', 'finbarr delaney', 'cork', '1 - 19', '23', '2', '8.00'], ['5', 'pat fox', 'tipperary', '3 - 11', '20', '4', '5.00']] |
2008 - 09 kansas jayhawks men 's basketball team | https://en.wikipedia.org/wiki/2008%E2%80%9309_Kansas_Jayhawks_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17728794-2.html.csv | superlative | the heaviest player on the 09 kansas jayhawks men 's basketball team is matt kleinmen weighing 247 pounds . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '7', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'weight'], 'result': '247', 'ind': 0, 'tostr': 'max { all_rows ; weight }', 'tointer': 'the maximum weight record of all rows is 247 .'}, '247'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; weight } ; 247 }', 'tointer': ... | and { eq { max { all_rows ; weight } ; 247 } ; eq { hop { argmax { all_rows ; weight } ; name } ; matt kleinmann } } = true | the maximum weight record of all rows is 247 . the name record of the row with superlative weight record is matt kleinmann . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'weight_8': 8, '247_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'weight_11': 11, 'name_12': 12, 'matt kleinmann_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'weight_8': 'weight', '247_9': '247', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'weight_11': 'weight', 'name_12': 'name', 'matt kleinmann_13': 'matt kleinmann'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'weight_8': [0], '247_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'weight_11': [2], 'name_12': [3], 'matt kleinmann_13': [4]} | ['name', 'position', 'height', 'weight', 'year', 'home town'] | [['cole aldrich', 'center', '6 - 11', '245', 'sophomore', 'bloomington , mn'], ['tyrone appleton', 'guard', '6 - 3', '190', 'junior', 'midland , texas'], ['brennan bechard', 'guard', '6 - 0', '183', 'senior', 'lawrence , ks'], ['chase buford', 'guard', '6 - 3', '200', 'sophomore', 'san antonio , texas'], ['sherron coll... |
list of ottawa senators draft picks | https://en.wikipedia.org/wiki/List_of_Ottawa_Senators_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11803648-17.html.csv | aggregation | ottawa senators had a total number of 503 picks overall . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '503', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'overall'], 'result': '503', 'ind': 0, 'tostr': 'sum { all_rows ; overall }'}, '503'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; overall } ; 503 } = true', 'tointer': 'the sum of the overall record of all rows is 503 .'} | round_eq { sum { all_rows ; overall } ; 503 } = true | the sum of the overall record of all rows is 503 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'overall_4': 4, '503_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'overall_4': 'overall', '503_5': '503'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'overall_4': [0], '503_5': [1]} | ['round', 'overall', 'player', 'position', 'nationality', 'club team'] | [['1', '15', 'erik karlsson', 'defence', 'sweden', 'frãlunda hc ( gothenburg ) ( sweden )'], ['2', '42', 'patrick wiercioch', 'defence', 'canada', 'omaha ( ushl )'], ['3', '79', 'zack smith', 'center', 'canada', 'swift current broncos ( whl )'], ['4', '109', 'andre petersson', 'forward', 'sweden', 'hv71 ( sweden )'], [... |
telmex grand prix of monterrey | https://en.wikipedia.org/wiki/2004_Tecate/Telmex_Grand_Prix_of_Monterrey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16326318-1.html.csv | ordinal | sébastien bourdais had the second fastest time in the first qualifying race of the telmex grand prix of monterrey . | {'row': '1', 'col': '3', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'qual 1', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; qual 1 ; 2 }'}, 'name'], 'result': 'sébastien bourdais', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; qual 1 ; 2 } ; name }'}, 'sébastien ... | eq { hop { nth_argmin { all_rows ; qual 1 ; 2 } ; name } ; sébastien bourdais } = true | select the row whose qual 1 record of all rows is 2nd minimum . the name record of this row is sébastien bourdais . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'qual 1_5': 5, '2_6': 6, 'name_7': 7, 'sébastien bourdais_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', 'qual 1_5': 'qual 1', '2_6': '2', 'name_7': 'name', 'sébastien bourdais_8': 'sébastien bourdais'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'qual 1_5': [0], '2_6': [0], 'name_7': [1], 'sébastien bourdais_8': [2]} | ['name', 'team', 'qual 1', 'qual 2', 'best'] | [['sébastien bourdais', 'newman / haas racing', '1:15.978', '1:13.915', '1:13.915'], ['mario domínguez', 'herdez competition', '1:16.422', '1:14.343', '1:14.343'], ['justin wilson', 'mi - jack conquest racing', '1:16.087', '1:14.354', '1:14.354'], ['bruno junqueira', 'newman / haas racing', '1:15.834', '1:14.405', '1:1... |
2007 - 08 chelsea f.c. season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Chelsea_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11927320-3.html.csv | count | chelsea was the runner-up in four of the competitions . | {'scope': 'all', 'criterion': 'equal', 'value': 'runner - up', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'final position / round', 'runner - up'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose final position / round record fuzzily matches to runner - up .', 'tostr': 'filter_eq { all_rows ; final position / round... | eq { count { filter_eq { all_rows ; final position / round ; runner - up } } ; 4 } = true | select the rows whose final position / round record fuzzily matches to runner - up . 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, 'final position / round_5': 5, 'runner - up_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', 'final position / round_5': 'final position / round', 'runner - up_6': 'runner - up', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'final position / round_5': [0], 'runner - up_6': [0], '4_7': [2]} | ['competition', 'current position / round', 'final position / round', 'first match', 'last match'] | [['fa community shield', '-', 'runner - up', '5 aug 2007', '5 aug 2007'], ['premier league', '-', 'runner - up', '12 aug 2007', '11 may 2008'], ['uefa champions league', '-', 'runner - up', '18 sep 2007', '21 may 2008'], ['football league cup', '-', 'runner - up', '24 sep 2007', '24 feb 2008'], ['fa cup', '-', 'quarter... |
list of fc barcelona records and statistics | https://en.wikipedia.org/wiki/List_of_FC_Barcelona_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14707564-7.html.csv | majority | the majority of players in the list of fc barcelona records and statistics have spain nationality . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'spain', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'spain'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to spain .', 'tostr': 'most_eq { all_rows ; nationality ; spain } = true'} | most_eq { all_rows ; nationality ; spain } = true | for the nationality records of all rows , most of them fuzzily match to spain . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'spain_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'spain_4': 'spain'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'spain_4': [0]} | ['ranking', 'nationality', 'name', 'goals', 'years'] | [['1', 'philippines', 'paulino alcántara', '369', '1912 - 1916 , 1918 - 1927'], ['2', 'argentina', 'lionel messi', '352', '2004 -'], ['3', 'spain', 'josep samitier', '333', '1919 - 1932'], ['4', 'spain', 'césar rodríguez', '301', '1942 - 1955'], ['5', 'hungary', 'ladislao kubala', '280', '1950 - 1961'], ['6', 'spain', ... |
1934 vfl season | https://en.wikipedia.org/wiki/1934_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790510-12.html.csv | count | one of the away team scores in the 1934 vfl season was less than 10 . | {'scope': 'all', 'criterion': 'less_than', 'value': '10', 'result': '1', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'away team score', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose away team score record is less than 10 .', 'tostr': 'filter_less { all_rows ; away team score ; 10 }'}], 'result': '1', 'ind': 1, 'tostr':... | eq { count { filter_less { all_rows ; away team score ; 10 } } ; 1 } = true | select the rows whose away team score record is less than 10 . the number of such rows is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'away team score_5': 5, '10_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'away team score_5': 'away team score', '10_6': '10', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'away team score_5': [0], '10_6': [0], '1_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '13.23 ( 101 )', 'richmond', '14.11 ( 95 )', 'mcg', '13805', '28 july 1934'], ['collingwood', '13.19 ( 97 )', 'south melbourne', '21.19 ( 145 )', 'victoria park', '28000', '28 july 1934'], ['carlton', '22.13 ( 145 )', 'hawthorn', '10.6 ( 66 )', 'princes park', '12000', '28 july 1934'], ['st kilda', '13.6... |
orlando magic all - time roster | https://en.wikipedia.org/wiki/Orlando_Magic_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15621965-2.html.csv | unique | michael bradley is the only player who played at villanova . | {'scope': 'all', 'row': '11', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'villanova', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'villanova'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to villanova .', 'tostr': 'filter_eq { all_rows ; school / club team ; villanova }'}... | and { only { filter_eq { all_rows ; school / club team ; villanova } } ; eq { hop { filter_eq { all_rows ; school / club team ; villanova } ; player } ; michael bradley } } = true | select the rows whose school / club team record fuzzily matches to villanova . there is only one such row in the table . the player record of this unqiue row is michael bradley . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / club team_7': 7, 'villanova_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'michael bradley_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / club team_7': 'school / club team', 'villanova_8': 'villanova', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'michael bradley_10': 'michael bradley'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / club team_7': [0], 'villanova_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'michael bradley_10': [3]} | ['player', 'no', 'nationality', 'position', 'years in orlando', 'school / club team'] | [['matt barnes', '22', 'united states', 'guard - forward', '2009 - 2010', 'ucla'], ['andre barrett', '11', 'united states', 'guard', '2005', 'seton hall'], ['brandon bass', '30', 'united states', 'forward', '2009 - 2011', 'louisiana state'], ['tony battie', '4', 'united states', 'forward - center', '2004 - 2009', 'texa... |
arsen avakov | https://en.wikipedia.org/wiki/Arsen_Avakov | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15532127-1.html.csv | count | arsen avakov won by a score of 5-0 three times . | {'scope': 'all', 'criterion': 'equal', 'value': '5 - 0', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '5 - 0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 5 - 0 .', 'tostr': 'filter_eq { all_rows ; result ; 5 - 0 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; result ; 5 - 0 } } ; 3 } = true | select the rows whose result record fuzzily matches to 5 - 0 . 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, 'result_5': 5, '5 - 0_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', 'result_5': 'result', '5 - 0_6': '5 - 0', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], '5 - 0_6': [0], '3_7': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['8 may 1996', 'dushanbe , tajikistan', '4 - 0', '4 - 0', '1996 afc asian cup qualification'], ['1 june 1997', 'ho chi minh city , vietnam', '0 - 3', '0 - 4', '1998 fifa world cup qualification'], ['22 june 1997', 'dushanbe , tajikistan', '1 - 0', '5 - 0', '1998 fifa world cup qualification'], ['22 june 1997', 'dushan... |
doctor who ( series 1 ) | https://en.wikipedia.org/wiki/Doctor_Who_%28series_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18012738-1.html.csv | aggregation | doctor who ( series 1 ) had a total of 96.41 million views in the uk . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '96.41', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'uk viewers ( million )'], 'result': '96.41', 'ind': 0, 'tostr': 'sum { all_rows ; uk viewers ( million ) }'}, '96.41'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; uk viewers ( million ) } ; 96.41 } = true', 'tointer': 'the sum of t... | round_eq { sum { all_rows ; uk viewers ( million ) } ; 96.41 } = true | the sum of the uk viewers ( million ) record of all rows is 96.41 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'uk viewers (million)_4': 4, '96.41_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'uk viewers (million)_4': 'uk viewers ( million )', '96.41_5': '96.41'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'uk viewers (million)_4': [0], '96.41_5': [1]} | ['story no', 'episode', 'title', 'directed by', 'written by', 'uk viewers ( million )', 'ai ( % )', 'original air date', 'production code'] | [['157', '1', 'rose', 'keith boak', 'russell t davies', '10.81', '81', '26 march 2005', '1.1'], ['158', '2', 'the end of the world', 'euros lyn', 'russell t davies', '7.97', '79', '2 april 2005', '1.2'], ['159', '3', 'the unquiet dead', 'euros lyn', 'mark gatiss', '8.86', '80', '9 april 2005', '1.3'], ['160a', '4', 'al... |
jj lehto | https://en.wikipedia.org/wiki/JJ_Lehto | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226476-5.html.csv | majority | a majority-3 - of jj lehto 's engines from 2003-2005 he used to race , were audi 3.6 l turbo v8 engines . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'audi 3.6 l turbo v8', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'engine', 'audi 3.6 l turbo v8'], 'result': True, 'ind': 0, 'tointer': 'for the engine records of all rows , most of them fuzzily match to audi 3.6 l turbo v8 .', 'tostr': 'most_eq { all_rows ; engine ; audi 3.6 l turbo v8 } = true'} | most_eq { all_rows ; engine ; audi 3.6 l turbo v8 } = true | for the engine records of all rows , most of them fuzzily match to audi 3.6 l turbo v8 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'engine_3': 3, 'audi 3.6l turbo v8_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'engine_3': 'engine', 'audi 3.6l turbo v8_4': 'audi 3.6 l turbo v8'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'engine_3': [0], 'audi 3.6l turbo v8_4': [0]} | ['year', 'entrant', 'class', 'chassis', 'engine', 'tyres', 'rank', 'points'] | [['1999', 'bmw motorsport', 'lmp', 'bmw v12 lmr', 'bmw s70 6.0 l v12', 'm', '4th', '123'], ['2000', 'bmw motorsport', 'lmp', 'bmw v12 lmr', 'bmw s70 6.0 l v12', 'm', '6th', '220'], ['2001', 'bmw motorsport', 'gt', 'bmw m3', 'bmw 3.2 l i6', 'm', '2nd', '180'], ['2001', 'bmw motorsport', 'gt', 'bmw m3 gtr', 'bmw 4.0 l v8... |
1987 masters tournament | https://en.wikipedia.org/wiki/1987_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16490473-1.html.csv | superlative | in the 1987 masters tournament , seve ballesteros ranked the highest . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; total }'}, 'player'], 'result': 'seve ballesteros', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; total } ; player }'}, 'seve ballesteros'], 'result': True, ... | eq { hop { argmin { all_rows ; total } ; player } ; seve ballesteros } = true | select the row whose total record of all rows is minimum . the player record of this row is seve ballesteros . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'total_5': 5, 'player_6': 6, 'seve ballesteros_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'total_5': 'total', 'player_6': 'player', 'seve ballesteros_7': 'seve ballesteros'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'total_5': [0], 'player_6': [1], 'seve ballesteros_7': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['seve ballesteros', 'spain', '1980 , 1983', '285', '3', 't2'], ['ben crenshaw', 'united states', '1984', '286', '2', 't4'], ['bernhard langer', 'west germany', '1985', '289', '+ 1', 't7'], ['jack nicklaus', 'united states', '1963 , 1965 , 1966 , 1972 , 1975 , 1986', '289', '+ 1', 't7'], ['tom watson', 'united states'... |
1939 - 40 new york rangers season | https://en.wikipedia.org/wiki/1939%E2%80%9340_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14473419-5.html.csv | count | the new york rangers played the detroit red wings three times in february . | {'scope': 'all', 'criterion': 'equal', 'value': 'detroit red wings', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'detroit red wings'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to detroit red wings .', 'tostr': 'filter_eq { all_rows ; opponent ; detroit red wings }'}], 're... | eq { count { filter_eq { all_rows ; opponent ; detroit red wings } } ; 3 } = true | select the rows whose opponent record fuzzily matches to detroit red wings . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'detroit red wings_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'detroit red wings_6': 'detroit red wings', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'detroit red wings_6': [0], '3_7': [2]} | ['game', 'february', 'opponent', 'score', 'record'] | [['32', '1', 'detroit red wings', '2 - 0', '20 - 5 - 7'], ['33', '4', 'montreal canadiens', '9 - 0', '21 - 5 - 7'], ['34', '6', 'boston bruins', '6 - 2', '21 - 6 - 7'], ['35', '8', 'toronto maple leafs', '2 - 1', '22 - 6 - 7'], ['36', '10', 'toronto maple leafs', '4 - 4 ot', '22 - 6 - 8'], ['37', '11', 'chicago black h... |
1959 vfl season | https://en.wikipedia.org/wiki/1959_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775038-4.html.csv | count | two of the venues have the word oval in their name . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'oval', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to oval .', 'tostr': 'filter_eq { all_rows ; venue ; oval }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_e... | eq { count { filter_eq { all_rows ; venue ; oval } } ; 2 } = true | select the rows whose venue record fuzzily matches to oval . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'oval_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'oval_6': 'oval', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'oval_6': [0], '2_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '19.14 ( 128 )', 'south melbourne', '13.19 ( 97 )', 'glenferrie oval', '25000', '16 may 1959'], ['essendon', '8.14 ( 62 )', 'north melbourne', '11.11 ( 77 )', 'windy hill', '22500', '16 may 1959'], ['carlton', '14.17 ( 101 )', 'richmond', '9.7 ( 61 )', 'princes park', '24500', '16 may 1959'], ['melbourne'... |
2006 - 07 manchester united f.c. season | https://en.wikipedia.org/wiki/2006%E2%80%9307_Manchester_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11115098-4.html.csv | aggregation | the average attendance for the 2006-07 manchester united fc was 57797 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '57797', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '57797', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '57797'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 57797 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 57797 } = true | the average of the attendance record of all rows is 57797 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '57797_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '57797_5': '57797'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '57797_5': [1]} | ['date', 'round', 'opponents', 'h / a', 'result f - a', 'attendance'] | [['7 january 2007', 'round 3', 'aston villa', 'h', '2 - 1', '74924'], ['27 january 2007', 'round 4', 'portsmouth', 'h', '2 - 1', '71137'], ['17 february 2007', 'round 5', 'reading', 'h', '1 - 1', '70608'], ['27 february 2007', 'round 5 replay', 'reading', 'a', '3 - 2', '23821'], ['10 march 2007', 'round 6', 'middlesbro... |
1993 - 94 philadelphia flyers season | https://en.wikipedia.org/wiki/1993%E2%80%9394_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14344407-2.html.csv | aggregation | in october of 1993 the philadelphia flyers scored an average of 4.67 goals over 12 games . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '4.67', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '4.67', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '4.67'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 4.67 } = true', 'tointer': 'the average of the score record of all rows is 4.67 .'} | round_eq { avg { all_rows ; score } ; 4.67 } = true | the average of the score record of all rows is 4.67 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '4.67_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '4.67_5': '4.67'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '4.67_5': [1]} | ['game', 'october', 'opponent', 'score', 'record', 'points'] | [['1', '5', 'pittsburgh penguins', '4 - 3', '1 - 0 - 0', '2'], ['2', '9', 'hartford whalers', '5 - 2', '2 - 0 - 0', '4'], ['3', '10', 'toronto maple leafs', '4 - 5', '2 - 1 - 0', '4'], ['4', '12', 'buffalo sabres', '5 - 3', '3 - 1 - 0', '6'], ['5', '15', 'washington capitals', '3 - 0', '4 - 1 - 0', '8'], ['6', '16', 'n... |
united states house of representatives elections , 1964 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1964 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341865-11.html.csv | majority | most of the elected representatives were unopposed during the election . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'unopposed', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': True, 'ind': 0, 'tointer': 'for the candidates records of all rows , most of them fuzzily match to unopposed .', 'tostr': 'most_eq { all_rows ; candidates ; unopposed } = true'} | most_eq { all_rows ; candidates ; unopposed } = true | for the candidates records of all rows , most of them fuzzily match to unopposed . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'candidates_3': 3, 'unopposed_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'candidates_3': 'candidates', 'unopposed_4': 'unopposed'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'candidates_3': [0], 'unopposed_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['florida 1', 'robert l f sikes', 'democratic', '1940', 're - elected', 'robert l f sikes ( d ) unopposed'], ['florida 3', 'claude pepper', 'democratic', '1962', 're - elected', "claude pepper ( d ) 65.7 % paul j o'neill ( r ) 34.3 %"], ['florida 4', 'dante fascell', 'democratic', '1954', 're - elected', 'dante fascel... |
1990 england rugby union tour of argentina | https://en.wikipedia.org/wiki/1990_England_rugby_union_tour_of_Argentina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17058667-1.html.csv | unique | the 4 august 1990 match against argentina was the only one with the second test status . | {'scope': 'all', 'row': '7', 'col': '5', 'col_other': '1,3', 'criterion': 'equal', 'value': 'second test', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'second test'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to second test .', 'tostr': 'filter_eq { all_rows ; status ; second test }'}], 'result': True, 'ind': 1, '... | and { only { filter_eq { all_rows ; status ; second test } } ; and { eq { hop { filter_eq { all_rows ; status ; second test } ; opposing team } ; argentina } ; eq { hop { filter_eq { all_rows ; status ; second test } ; date } ; 4 august 1990 } } } = true | select the rows whose status record fuzzily matches to second test . there is only one such row in the table . the opposing team record of this unqiue row is argentina . the date record of this unqiue row is 4 august 1990 . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'status_10': 10, 'second test_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'opposing team_12': 12, 'argentina_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'date_14': 14, '4 august 1990_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'status_10': 'status', 'second test_11': 'second test', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opposing team_12': 'opposing team', 'argentina_13': 'argentina', 'str_eq_5': 'str_eq... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'status_10': [0], 'second test_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'opposing team_12': [2], 'argentina_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'date_14': [4], '4 august 1990_15': [5]} | ['opposing team', 'against', 'date', 'venue', 'status'] | [['banco nación', '29', '14 july 1990', 'buenos aires', 'tour match'], ['tucumán selection', '14', '18 july 1990', 'tucumán', 'tour match'], ['buenos aires selection', '26', '21 july 1990', 'buenos aires', 'tour match'], ['cuyo selection', '22', '24 july 1990', 'mendoza', 'tour match'], ['argentina', '12', '28 july 199... |
andy linden ( racing driver ) | https://en.wikipedia.org/wiki/Andy_Linden_%28racing_driver%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236025-1.html.csv | superlative | of all his races , andy lindens highest start came in the year 1952 . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'start'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; start }'}, 'year'], 'result': '1952', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; start } ; year }'}, '1952'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { a... | eq { hop { argmin { all_rows ; start } ; year } ; 1952 } = true | select the row whose start record of all rows is minimum . the year record of this row is 1952 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'start_5': 5, 'year_6': 6, '1952_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'start_5': 'start', 'year_6': 'year', '1952_7': '1952'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'start_5': [0], 'year_6': [1], '1952_7': [2]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1951', '31', '132.226', '26', '4', '200'], ['1952', '2', '137.002', '4', '33', '20'], ['1953', '5', '136.060', '19', '33', '3'], ['1954', '23', '137.820', '28', '25', '165'], ['1955', '8', '139.098', '22', '6', '200'], ['1956', '9', '143.056', '11', '27', '90'], ['1957', '12', '143.244', '5', '5', '200']] |
bms scuderia italia | https://en.wikipedia.org/wiki/BMS_Scuderia_Italia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226647-2.html.csv | unique | the 1991 racer was the only one to use a judd engine . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'judd', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine ( s )', 'judd'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine ( s ) record fuzzily matches to judd .', 'tostr': 'filter_eq { all_rows ; engine ( s ) ; judd }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; engine ( s ) ; judd } } ; eq { hop { filter_eq { all_rows ; engine ( s ) ; judd } ; year } ; 1991 } } = true | select the rows whose engine ( s ) record fuzzily matches to judd . there is only one such row in the table . the year record of this unqiue row is 1991 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'engine (s)_7': 7, 'judd_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1991_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'engine (s)_7': 'engine ( s )', 'judd_8': 'judd', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1991_10': '1991'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'engine (s)_7': [0], 'judd_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1991_10': [3]} | ['year', 'chassis', 'engine ( s )', 'tyres', 'points'] | [['1988', 'dallara 3087 dallara 188', 'ford dfz 3.5 v8', 'g', '0'], ['1989', 'dallara 189', 'ford dfr 3.5 v8', 'p', '8'], ['1990', 'dallara 190', 'ford dfr 3.5 v8', 'p', '0'], ['1991', 'dallara 191', 'judd gv 3.5 v10', 'p', '5'], ['1992', 'dallara 192', 'ferrari 037 3.5 v12', 'g', '2'], ['1993', 'lola t93 / 30', 'ferra... |
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/2-11105214-2.html.csv | majority | the labour party was the winning party in 2003 of the majority of constituencies in the scottish parliament general election . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'labour', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'winning party 2003', 'labour'], 'result': True, 'ind': 0, 'tointer': 'for the winning party 2003 records of all rows , most of them fuzzily match to labour .', 'tostr': 'most_eq { all_rows ; winning party 2003 ; labour } = true'} | most_eq { all_rows ; winning party 2003 ; labour } = true | for the winning party 2003 records of all rows , most of them fuzzily match to labour . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'winning party 2003_3': 3, 'labour_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'winning party 2003_3': 'winning party 2003', 'labour_4': 'labour'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'winning party 2003_3': [0], 'labour_4': [0]} | ['rank', 'constituency', 'winning party 2003', 'swing to gain', "snp 's place 2003", 'result'] | [['1', 'galloway & upper nithsdale', 'conservative', '0.17', '2nd', 'con hold'], ['2', 'tweeddale , ettrick & lauderdale', 'liberal democrats', '1.01', '2nd', 'ld hold'], ['3', 'cumbernauld & kilsyth', 'labour', '1.07', '2nd', 'lab hold'], ['4', 'kilmarnock & loudoun', 'labour', '1.92', '2nd', 'snp gain'], ['5', 'dunde... |
toronto raptors all - time roster | https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-3.html.csv | majority | most of the players have the united states as their nationality . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team'] | [['josé calderón', '8', 'spain', 'guard', '2005 - 2013', 'tau cerámica ( spain )'], ['marcus camby', '21', 'united states', 'center', '1996 - 98', 'massachusetts'], ['anthony carter', '25', 'united states', 'guard', '2011 - 12', 'hawaii'], ['vince carter', '15', 'united states', 'guard - forward', '1998 - 2004', 'north... |
2005 u.s. open ( golf ) | https://en.wikipedia.org/wiki/2005_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14064009-4.html.csv | count | seven players in the 2008 us open for golf went +1 over par . | {'scope': 'all', 'criterion': 'equal', 'value': '+1', 'result': '7', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'to par', '+1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose to par record fuzzily matches to +1 .', 'tostr': 'filter_eq { all_rows ; to par ; +1 }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq {... | eq { count { filter_eq { all_rows ; to par ; +1 } } ; 7 } = true | select the rows whose to par record fuzzily matches to +1 . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'to par_5': 5, '+1_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'to par_5': 'to par', '+1_6': '+1', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'to par_5': [0], '+1_6': [0], '7_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'olin browne', 'united states', '67 + 71 = 138', '- 2'], ['t1', 'retief goosen', 'south africa', '68 + 70 = 138', '- 2'], ['t1', 'jason gore', 'united states', '71 + 67 = 138', '- 2'], ['t4', 'k j choi', 'south korea', '69 + 70 = 139', '- 1'], ['t4', 'mark hensby', 'australia', '71 + 68 = 139', '- 1'], ['t6', '... |
i am ... ( ayumi hamasaki album ) | https://en.wikipedia.org/wiki/I_Am..._%28Ayumi_Hamasaki_album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1754908-3.html.csv | count | there are 8 track titles in the i am ... ( ayumi hamasaki album ) . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '8', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'title'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record is arbitrary .', 'tostr': 'filter_all { all_rows ; title }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; title } }', ... | eq { count { filter_all { all_rows ; title } } ; 8 } = true | select the rows whose title record is arbitrary . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'title_5': 5, '8_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'title_5': 'title', '8_6': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'title_5': [0], '8_6': [2]} | ['date', 'title', 'peak position', 'weeks', 'sales'] | [['december 13 , 2000', 'm', '1', '18 weeks', '1319070'], ['january 31 , 2001', 'evolution', '1', '17 weeks', '955250'], ['march 7 , 2001', 'never ever', '1', '12 weeks', '756980'], ['may 16 , 2001', 'endless sorrow', '1', '11 weeks', '768510'], ['july 11 , 2001', 'unite !', '1', '17 weeks', '571110'], ['september 27 ,... |
1996 in film | https://en.wikipedia.org/wiki/1996_in_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-169568-1.html.csv | ordinal | " mission : impossible " was the third highest grossing film worldwide in 1996 . | {'row': '3', 'col': '5', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'worldwide gross', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; worldwide gross ; 3 }'}, 'title'], 'result': 'mission : impossible', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; worldwide gross... | eq { hop { nth_argmax { all_rows ; worldwide gross ; 3 } ; title } ; mission : impossible } = true | select the row whose worldwide gross record of all rows is 3rd maximum . the title record of this row is mission : impossible . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'worldwide gross_5': 5, '3_6': 6, 'title_7': 7, 'mission : impossible_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', 'worldwide gross_5': 'worldwide gross', '3_6': '3', 'title_7': 'title', 'mission : impossible_8': 'mission : impossible'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'worldwide gross_5': [0], '3_6': [0], 'title_7': [1], 'mission : impossible_8': [2]} | ['rank', 'title', 'studio', 'director', 'worldwide gross'] | [['1', 'independence day', '20th century fox', 'roland emmerich', '817400891'], ['2', 'twister', 'warner bros / universal studios', 'jan de bont', '494471524'], ['3', 'mission : impossible', 'paramount pictures', 'brian de palma', '457696359'], ['4', 'the rock', 'hollywood pictures', 'michael bay', '335062621'], ['5', ... |
list of covert affairs episodes | https://en.wikipedia.org/wiki/List_of_Covert_Affairs_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25740548-3.html.csv | ordinal | for the list of covert affairs episodes in with an original air date in june the episode title begin the begin had the highest viewers . | {'scope': 'subset', 'row': '1', 'col': '8', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'june'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'june'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; june }', 'tointer': 'select the rows whose original air date record fuzzily... | eq { hop { nth_argmax { filter_eq { all_rows ; original air date ; june } ; us viewers ( million ) ; 1 } ; title } ; begin the begin } = true | select the rows whose original air date record fuzzily matches to june . select the row whose us viewers ( million ) record of these rows is 1st maximum . the title record of this row is begin the begin . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'original air date_6': 6, 'june_7': 7, 'us viewers (million)_8': 8, '1_9': 9, 'title_10': 10, 'begin the begin_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'original air date_6': 'original air date', 'june_7': 'june', 'us viewers (million)_8': 'us viewers ( million )', '1_9': '1', 'title_10': 'title', 'begin the beg... | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'original air date_6': [0], 'june_7': [0], 'us viewers (million)_8': [1], '1_9': [1], 'title_10': [2], 'begin the begin_11': [3]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['12', '1', 'begin the begin', 'kate woods', 'matt corman & chris ord', 'june 7 , 2011', 'ca201', '4.56'], ['13', '2', 'good advices', 'ken girotti', 'stephen hootstein', 'june 14 , 2011', 'ca202', '3.92'], ['14', '3', 'bang and blame', 'allan kroeker', 'erica shelton', 'june 21 , 2011', 'ca203', '4.03'], ['15', '4', ... |
mattia pasini | https://en.wikipedia.org/wiki/Mattia_Pasini | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13985563-1.html.csv | ordinal | mattia pasini competed in his 2nd fewest races during his 2010 season . | {'row': '7', 'col': '2', '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', 'races', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; races ; 2 }'}, 'season'], 'result': '2010', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; races ; 2 } ; season }'}, '2010'], 'result': True,... | eq { hop { nth_argmin { all_rows ; races ; 2 } ; season } ; 2010 } = true | select the row whose races record of all rows is 2nd minimum . the season record of this row is 2010 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'races_5': 5, '2_6': 6, 'season_7': 7, '2010_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', 'races_5': 'races', '2_6': '2', 'season_7': 'season', '2010_8': '2010'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'races_5': [0], '2_6': [0], 'season_7': [1], '2010_8': [2]} | ['season', 'races', 'podiums', 'pole', 'flap'] | [['2004', '16', '0', '0', '0'], ['2005', '15', '6', '0', '0'], ['2006', '16', '6', '2', '2'], ['2007', '17', '5', '9', '2'], ['2008', '16', '4', '0', '0'], ['2009', '16', '5', '0', '0'], ['2010', '8', '0', '0', '0'], ['2011', '17', '0', '0', '0'], ['2012', '14', '0', '0', '0'], ['2012', '1', '0', '0', '0'], ['2013', '1... |
clear lake ( oregon ) | https://en.wikipedia.org/wiki/Clear_Lake_%28Oregon%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12484336-1.html.csv | ordinal | clear lake of coos county , oregon is the body of water that has the second highest gnis id . | {'row': '12', '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', 'gnis id', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; gnis id ; 2 }'}, 'name'], 'result': 'clear lake ( coos county , oregon )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; gnis id ; 2 } ; n... | eq { hop { nth_argmax { all_rows ; gnis id ; 2 } ; name } ; clear lake ( coos county , oregon ) } = true | select the row whose gnis id record of all rows is 2nd maximum . the name record of this row is clear lake ( coos county , oregon ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'gnis id_5': 5, '2_6': 6, 'name_7': 7, 'clear lake (coos county , oregon)_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', 'gnis id_5': 'gnis id', '2_6': '2', 'name_7': 'name', 'clear lake (coos county , oregon)_8': 'clear lake ( coos county , oregon )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'gnis id_5': [0], '2_6': [0], 'name_7': [1], 'clear lake (coos county , oregon)_8': [2]} | ['name', 'type', 'elevation', 'usgs map', 'gnis id'] | [['clear lake ( douglas county , oregon )', 'lake', 'feet ( m )', 'winchester bay', '1139800'], ['clear lake ( wasco county , oregon )', 'reservoir', 'feet ( m )', 'wapinitia pass', '1139803'], ['clear lake ( amazon creek , oregon )', 'lake', 'feet ( m )', 'eugene west', '1119000'], ['clear lake ( marion county , orego... |
kansas jayhawk community college conference | https://en.wikipedia.org/wiki/Kansas_Jayhawk_Community_College_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12434380-2.html.csv | count | four of the colleges use white color as part of their school color . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'white', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school colors', 'white'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school colors record fuzzily matches to white .', 'tostr': 'filter_eq { all_rows ; school colors ; white }'}], 'result': '4', 'ind': 1,... | eq { count { filter_eq { all_rows ; school colors ; white } } ; 4 } = true | select the rows whose school colors record fuzzily matches to white . 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, 'school colors_5': 5, 'white_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', 'school colors_5': 'school colors', 'white_6': 'white', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'school colors_5': [0], 'white_6': [0], '4_7': [2]} | ['institution', 'main campus location', 'founded', 'mascot', 'school colors'] | [['barton community college', 'great bend', '1969', 'cougars', 'blue & gold'], ['butler community college', 'el dorado', '1927', 'grizzlies', 'purple & vegas gold'], ['cloud county community college', 'concordia', '1965', 'thunderbirds', 'black & gold'], ['colby community college', 'colby', '1964', 'trojans', 'blue & w... |
1993 washington redskins season | https://en.wikipedia.org/wiki/1993_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14610099-1.html.csv | superlative | the game played on week 9 of the 1993 washington redskins season drew the highest attendance . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'week'], 'result': '9', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; week }'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq ... | eq { hop { argmax { all_rows ; attendance } ; week } ; 9 } = true | select the row whose attendance record of all rows is maximum . the week record of this row is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'week_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'week_6': 'week', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'week_6': [1], '9_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 6 , 1993', 'dallas cowboys', 'w 35 - 16', '56345'], ['2', 'september 12 , 1993', 'phoenix cardinals', 'l 17 - 10', '53525'], ['3', 'september 19 , 1993', 'philadelphia eagles', 'l 34 - 31', '65435'], ['5', 'october 4 , 1993', 'miami dolphins', 'l 17 - 10', '68568'], ['6', 'october 10 , 1993', 'new yor... |
1979 world figure skating championships | https://en.wikipedia.org/wiki/1979_World_Figure_Skating_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11312764-6.html.csv | superlative | the duo of natalia linichuk / gennadi karponosov scored the highest number of points in the 1979 world figure skating championships . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'name'], 'result': 'natalia linichuk / gennadi karponosov', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; name }'}, 'natalia linichuk... | eq { hop { argmax { all_rows ; points } ; name } ; natalia linichuk / gennadi karponosov } = true | select the row whose points record of all rows is maximum . the name record of this row is natalia linichuk / gennadi karponosov . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'name_6': 6, 'natalia linichuk / gennadi karponosov_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', 'name_6': 'name', 'natalia linichuk / gennadi karponosov_7': 'natalia linichuk / gennadi karponosov'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'name_6': [1], 'natalia linichuk / gennadi karponosov_7': [2]} | ['rank', 'name', 'nation', 'points', 'places'] | [['1', 'natalia linichuk / gennadi karponosov', 'soviet union', '207.86', '9'], ['2', 'krisztina regőczy / andrás sallay', 'hungary', '204.10', '22'], ['3', 'irina moiseeva / andrei minenkov', 'soviet union', '203.74', '23'], ['4', 'liliana rehakova / stanislav drastich', 'czechoslovakia', '196.94', '36'], ['5', 'janet... |
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 | unique | the 1st round between as angoulême and fc sochaux - montbéliard was the only one that ended with a 0-0 score . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '1,3', 'criterion': 'equal', 'value': '0-0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st round', '0-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1st round record fuzzily matches to 0-0 .', 'tostr': 'filter_eq { all_rows ; 1st round ; 0-0 }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; 1st round ; 0-0 } } ; and { eq { hop { filter_eq { all_rows ; 1st round ; 0-0 } ; team 1 } ; as angoulême ( d2 ) } ; eq { hop { filter_eq { all_rows ; 1st round ; 0-0 } ; team 2 } ; fc sochaux - montbéliard ( d1 ) } } } = true | select the rows whose 1st round record fuzzily matches to 0-0 . there is only one such row in the table . the team 1 record of this unqiue row is as angoulême ( d2 ) . the team 2 record of this unqiue row is fc sochaux - montbéliard ( d1 ) . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, '1st round_10': 10, '0-0_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'team 1_12': 12, 'as angoulême (d2)_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'team 2_14': 14, 'fc sochaux - montbéliard (d1)_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', '1st round_10': '1st round', '0-0_11': '0-0', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team 1_12': 'team 1', 'as angoulême (d2)_13': 'as angoulême ( d2 )', 'str_eq_5': 'str_eq', 'st... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], '1st round_10': [0], '0-0_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'team 1_12': [2], 'as angoulême (d2)_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'team 2_14': [4], 'fc sochaux - montbéliard (d1)_15': [5]} | ['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 ( ... |
1994 - 95 philadelphia flyers season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14022127-7.html.csv | aggregation | the average attendance of the philadelphia flyers games was 16325 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '16325', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '16325', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '16325'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 16325 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 16325 } = true | the average of the attendance record of all rows is 16325 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '16325_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '16325_5': '16325'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '16325_5': [1]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'series'] | [['may 7', 'buffalo', '3 - 4', 'philadelphia', 'hextall', '17380', 'flyers lead 1 - 0'], ['may 8', 'buffalo', '1 - 3', 'philadelphia', 'hextall', '17380', 'flyers lead 2 - 0'], ['may 10', 'philadelphia', '1 - 3', 'buffalo', 'hextall', '13256', 'flyers lead 2 - 1'], ['may 12', 'philadelphia', '4 - 2', 'buffalo', 'hextal... |
fred astaire chronology of performances | https://en.wikipedia.org/wiki/Fred_Astaire_chronology_of_performances | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15186990-3.html.csv | ordinal | in the chronology of fred astaire 's performances , the love letter is the title of the earliest partnered dance . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'title'], 'result': 'the love letter', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; title }'}, 'the love letter']... | eq { hop { nth_argmin { all_rows ; date ; 1 } ; title } ; the love letter } = true | select the row whose date record of all rows is 1st minimum . the title record of this row is the love letter . | 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, 'title_7': 7, 'the love letter_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', 'title_7': 'title', 'the love letter_8': 'the love letter'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'title_7': [1], 'the love letter_8': [2]} | ['title', 'date', 'theatre', 'role', 'dance partner', 'director', 'lyrics', 'music'] | [['the love letter', 'oct 4 1921', 'globe', 'richard kolner', 'adele astaire', 'edward royce', 'william lebaron', 'victor jacobi'], ['for goodness sake', 'feb 20 1922', 'lyric', 'teddy lawrence', 'adele astaire', 'priestley morrison', 'arthur jackson', 'william daly paul lannin'], ['the bunch and judy', 'nov 28 1922', ... |
united states house of representatives elections , 1986 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1986 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341586-19.html.csv | majority | most of the louisiana representatives in the seventies and eighties were democrats . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'democratic', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic .', 'tostr': 'most_eq { all_rows ; party ; democratic } = true'} | most_eq { all_rows ; party ; democratic } = true | for the party records of all rows , most of them fuzzily match to democratic . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', 'bob livingston', 'republican', '1977', 're - elected', 'bob livingston ( r ) unopposed'], ['louisiana 2', 'lindy boggs', 'democratic', '1973', 're - elected', 'lindy boggs ( d ) unopposed'], ['louisiana 3', 'billy tauzin', 'democratic', '1980', 're - elected', 'billy tauzin ( d ) unopposed'], ['louisi... |
list of tallest buildings in tampa | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Tampa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17983290-2.html.csv | count | in the list of tallest buildings in tampa , 2 of the buildings in north franklin street has a height ft of more than 200 ft. | {'scope': 'subset', 'criterion': 'greater_than', 'value': '200', 'result': '2', 'col': '4', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'north franklin street'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'street address', 'north franklin street'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; street address ; north franklin street }', 'tointer': 'select the rows whose street... | eq { count { filter_greater { filter_eq { all_rows ; street address ; north franklin street } ; height ft ( m ) ; 200 } } ; 2 } = true | select the rows whose street address record fuzzily matches to north franklin street . among these rows , select the rows whose height ft ( m ) record is greater than 200 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'street address_6': 6, 'north franklin street_7': 7, 'height ft (m)_8': 8, '200_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'street address_6': 'street address', 'north franklin street_7': 'north franklin street', 'height ft (m)_8': 'height ft ( m )', '200_9': '200', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'street address_6': [0], 'north franklin street_7': [0], 'height ft (m)_8': [1], '200_9': [1], '2_10': [3]} | ['name', 'street address', 'years as tallest', 'height ft ( m )', 'floors'] | [['citizens bank building', '701 north franklin street', '1913 - 1915', '145 ( 44 )', '12'], ['tampa city hall', '315 john f kennedy boulevard', '1915 - 1926', '160 ( 49 )', '10'], ['floridan hotel', '905 franklin street', '1926 - 1966', '204 ( 62 )', '17'], ['franklin exchange building', '655 north franklin street', '... |
thierry boutsen | https://en.wikipedia.org/wiki/Thierry_Boutsen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1114709-3.html.csv | aggregation | in thierry boutsen 's races where he finished , he completed a total of 1359 laps . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '1359', 'subset': {'col': '7', 'criterion': 'not_equal', 'value': 'dnf'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'pos', 'dnf'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; pos ; dnf }', 'tointer': 'select the rows whose pos record does not match to dnf .'}, 'laps'], 'result': '1359', 'ind': 1, 'tostr': 'sum... | round_eq { sum { filter_not_eq { all_rows ; pos ; dnf } ; laps } ; 1359 } = true | select the rows whose pos record does not match to dnf . the sum of the laps record of these rows is 1359 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'pos_5': 5, 'dnf_6': 6, 'laps_7': 7, '1359_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'pos_5': 'pos', 'dnf_6': 'dnf', 'laps_7': 'laps', '1359_8': '1359'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'pos_5': [0], 'dnf_6': [0], 'laps_7': [1], '1359_8': [2]} | ['year', 'class', 'tyres', 'team', 'co - drivers', 'laps', 'pos', 'class pos'] | [['1981', 'c', 'm', 'wm aerem', 'serge saulnier michel pignard', '15', 'dnf', 'dnf'], ['1983', 'c', 'm', 'ford france', 'henri pescarolo', '174', 'dnf', 'dnf'], ['1986', 'c1', 'm', 'brun motorsport', 'didier theys alain fertã', '89', 'dnf', 'dnf'], ['1993', 'c1', 'm', 'peugeot talbot sport', 'yannick dalmas teo fabi', ... |
list of kentucky derby broadcasters | https://en.wikipedia.org/wiki/List_of_Kentucky_Derby_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22514845-4.html.csv | comparative | eddie arcaro was an s analyst for the kentucky derby earlier than bill hartack . | {'row_1': '9', 'row_2': '7', 'col': '1', 'col_other': '5', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 's analyst', 'eddie arcaro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose s analyst record fuzzily matches to eddie arcaro .', 'tostr': 'filter_eq { all_rows ; s analyst ; eddie arcaro }'}, 'year'], 're... | less { hop { filter_eq { all_rows ; s analyst ; eddie arcaro } ; year } ; hop { filter_eq { all_rows ; s analyst ; bill hartack } ; year } } = true | select the rows whose s analyst record fuzzily matches to eddie arcaro . take the year record of this row . select the rows whose s analyst record fuzzily matches to bill hartack . 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, 's analyst_7': 7, 'eddie arcaro_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 's analyst_11': 11, 'bill hartack_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', 's analyst_7': 's analyst', 'eddie arcaro_8': 'eddie arcaro', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 's analyst_11': 's analyst',... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 's analyst_7': [0], 'eddie arcaro_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 's analyst_11': [1], 'bill hartack_12': [1], 'year_13': [3]} | ['year', 'network', 'race caller', 's host', 's analyst', 'reporters', 'trophy presentation'] | [['1989', 'abc', 'dave johnson', 'jim mckay and al michaels', 'charlsie cantey and dave johnson', 'jack whitaker and lynn swann', 'jim mckay'], ['1988', 'abc', 'dave johnson', 'jim mckay and al michaels', 'charlsie cantey and dave johnson', 'jack whitaker and lynn swann', 'jim mckay'], ['1987', 'abc', 'dave johnson', '... |
list of argumental episodes | https://en.wikipedia.org/wiki/List_of_Argumental_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19930660-2.html.csv | superlative | episode 2x10 of argumental was the episode in which the blue team recorded their highest score . | {'scope': 'all', 'col_superlative': '5', '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', 'winner'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; winner }'}, 'episode'], 'result': '2x10', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; winner } ; episode }'}, '2x10'], 'result': True, 'ind': 2, 'tostr': ... | eq { hop { argmax { all_rows ; winner } ; episode } ; 2x10 } = true | select the row whose winner record of all rows is maximum . the episode record of this row is 2x10 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'winner_5': 5, 'episode_6': 6, '2x10_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'winner_5': 'winner', 'episode_6': 'episode', '2x10_7': '2x10'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'winner_5': [0], 'episode_6': [1], '2x10_7': [2]} | ['episode', 'first broadcast', 'rufus guest', 'marcus guest', 'winner'] | [['2x01', '23 march 2009', 'chris addison', 'dara ó briain', 'red ( 3 - 2 )'], ['2x02', '30 march 2009', 'mark watson', "ardal o'hanlon", 'red ( 2 - 2 )'], ['2x03', '6 april 2009', 'jo caulfield', 'katy brand', 'red ( 3 - 2 )'], ['2x05', '27 april 2009', 'reginald d hunter', 'sean hughes', 'blue ( 3 - 2 )'], ['2x06', '... |
valentino rossi | https://en.wikipedia.org/wiki/Valentino_Rossi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-180306-2.html.csv | aggregation | valentino rossi 's podium placements from 1996 to present averages 48 per race class . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '48', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'podiums'], 'result': '48', 'ind': 0, 'tostr': 'avg { all_rows ; podiums }'}, '48'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; podiums } ; 48 } = true', 'tointer': 'the average of the podiums record of all rows is 48 .'} | round_eq { avg { all_rows ; podiums } ; 48 } = true | the average of the podiums record of all rows is 48 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'podiums_4': 4, '48_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'podiums_4': 'podiums', '48_5': '48'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'podiums_4': [0], '48_5': [1]} | ['class', 'seas', '1st gp', '1st pod', '1st win', 'race', 'podiums', 'pole', 'flap', 'wchmp'] | [['125 cc', '1996 - 1997', '1996 malaysia', '1996 austria', '1996 czech rep', '30', '15', '5', '9', '1'], ['250 cc', '1998 - 1999', '1998 japan', '1998 spain', '1998 dutch', '30', '21', '5', '11', '1'], ['500 cc', '2000 - 2001', '2000 south af', '2000 spain', '2000 british', '32', '23', '4', '15', '1'], ['motogp', '200... |
1984 winter olympics | https://en.wikipedia.org/wiki/1984_Winter_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-113362-4.html.csv | count | in the 1984 winter olympics , among the nations that won 2 gold medals , 2 of them won 4 medals in total each . | {'scope': 'subset', 'criterion': 'equal', 'value': '4', 'result': '2', 'col': '6', 'subset': {'col': '3', 'criterion': 'equal', 'value': '2'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '2'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; gold ; 2 }', 'tointer': 'select the rows whose gold record is equal to 2 .'}, 'total', '4'], 'result': None, 'ind': 1, 'to... | eq { count { filter_eq { filter_eq { all_rows ; gold ; 2 } ; total ; 4 } } ; 2 } = true | select the rows whose gold record is equal to 2 . among these rows , select the rows whose total record is equal to 4 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'gold_6': 6, '2_7': 7, 'total_8': 8, '4_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'gold_6': 'gold', '2_7': '2', 'total_8': 'total', '4_9': '4', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'gold_6': [0], '2_7': [0], 'total_8': [1], '4_9': [1], '2_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'east germany ( gdr )', '9', '9', '6', '24'], ['2', 'soviet union ( urs )', '6', '10', '9', '25'], ['3', 'united states ( usa )', '4', '4', '0', '8'], ['4', 'finland ( fin )', '4', '3', '6', '13'], ['5', 'sweden ( swe )', '4', '2', '2', '8'], ['6', 'norway ( nor )', '3', '2', '4', '9'], ['7', 'switzerland ( sui ... |
2007 kansas lottery indy 300 | https://en.wikipedia.org/wiki/2007_Kansas_Lottery_Indy_300 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17693171-1.html.csv | majority | most of the drivers had 0 as their lap led values during the 2007 kansas lottery indy 300 . | {'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'laps led', '0'], 'result': True, 'ind': 0, 'tointer': 'for the laps led records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; laps led ; 0 } = true'} | most_eq { all_rows ; laps led ; 0 } = true | for the laps led records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps led_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps led_3': 'laps led', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps led_3': [0], '0_4': [0]} | ['fin pos', 'car no', 'driver', 'team', 'laps', 'time / retired', 'grid', 'laps led', 'points'] | [['1', '10', 'dan wheldon', 'target chip ganassi', '200', '1:36:56.0586', '4', '177', '50 + 3'], ['2', '27', 'dario franchitti', 'andretti green', '200', '+ 18.4830', '6', '0', '40'], ['3', '3', 'hãlio castroneves', 'team penske', '200', '+ 33.2280', '3', '0', '35'], ['4', '9', 'scott dixon', 'target chip ganassi', '20... |
1947 world series | https://en.wikipedia.org/wiki/1947_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1332364-1.html.csv | majority | most of the games in the 1947 world series were played at yankee stadium , giving the new york yankees the home field advantage during the series . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'yankee stadium', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'yankee stadium'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to yankee stadium .', 'tostr': 'most_eq { all_rows ; location ; yankee stadium } = true'} | most_eq { all_rows ; location ; yankee stadium } = true | for the location records of all rows , most of them fuzzily match to yankee stadium . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'yankee stadium_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'yankee stadium_4': 'yankee stadium'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'yankee stadium_4': [0]} | ['game', 'date', 'score', 'location', 'time', 'attendance'] | [['1', 'september 30', 'brooklyn dodgers - 3 , new york yankees - 5', 'yankee stadium ( i )', '2:20', '73365'], ['2', 'october 1', 'brooklyn dodgers - 3 , new york yankees - 10', 'yankee stadium ( i )', '2:36', '69865'], ['3', 'october 2', 'new york yankees - 8 , brooklyn dodgers - 9', 'ebbets field', '3:05', '33098'],... |
vehicles & animals | https://en.wikipedia.org/wiki/Vehicles_%26_Animals | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1546629-3.html.csv | unique | the version of the album vehicles & animals from the label astralwerks was the only release of the album in the united states . | {'scope': 'all', 'row': '4', 'col': '1', 'col_other': '3', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': True, 'i... | and { only { filter_eq { all_rows ; country ; united states } } ; eq { hop { filter_eq { all_rows ; country ; united states } ; label } ; astralwerks } } = true | select the rows whose country record fuzzily matches to united states . there is only one such row in the table . the label record of this unqiue row is astralwerks . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'united states_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'label_9': 9, 'astralwerks_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', 'united states_8': 'united states', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'label_9': 'label', 'astralwerks_10': 'astralwerks'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'united states_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'label_9': [2], 'astralwerks_10': [3]} | ['country', 'date', 'label', 'format', 'catalog'] | [['united kingdom', '7 april 2003', 'parlophone', 'lp', '582 2911'], ['united kingdom', '7 april 2003', 'parlophone', 'cd', '582 2912'], ['united kingdom', '7 april 2003', 'parlophone', 'cd digipak', '584 2112'], ['united states', '18 may 2004', 'astralwerks', 'cd', 'asw 82291'], ['australia', '14 march 2005', 'capitol... |
combined associated schools | https://en.wikipedia.org/wiki/Combined_Associated_Schools | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1553749-1.html.csv | aggregation | average enrollment of anglican combined associated schools in 1929 was 1,833.33 . | {'scope': 'subset', 'col': '3', 'type': 'average', 'result': '1,833.33', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'anglican'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'denomination', 'anglican'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; denomination ; anglican }', 'tointer': 'select the rows whose denomination record fuzzily matches to anglican .'}, 'enrolment'], '... | round_eq { avg { filter_eq { all_rows ; denomination ; anglican } ; enrolment } ; 1,833.33 } = true | select the rows whose denomination record fuzzily matches to anglican . the average of the enrolment record of these rows is 1,833.33 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'denomination_5': 5, 'anglican_6': 6, 'enrolment_7': 7, '1,833.33_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'denomination_5': 'denomination', 'anglican_6': 'anglican', 'enrolment_7': 'enrolment', '1,833.33_8': '1,833.33'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'denomination_5': [0], 'anglican_6': [0], 'enrolment_7': [1], '1,833.33_8': [2]} | ['school', 'location', 'enrolment', 'founded', 'denomination', 'boys / girls', 'day / boarding', 'year entered competition', 'school colors'] | [["st aloysius ' college", 'milsons point', '1200', '1879', 'catholic', 'boys', 'day', '1929', 'royal blue and gold'], ['barker college', 'hornsby', '2300', '1890', 'anglican', 'boys only to yr 9 co - ed year 10 to 12', 'day & boarding', '1929', 'red & blue'], ['cranbrook school', 'bellevue hill', '1000', '1918', 'angl... |
wuji county | https://en.wikipedia.org/wiki/Wuji_County | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12425097-1.html.csv | majority | the majority of the towns or townships have an area larger than 40km squared . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '40', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'area ( km square )', '40'], 'result': True, 'ind': 0, 'tointer': 'for the area ( km square ) records of all rows , most of them are greater than 40 .', 'tostr': 'most_greater { all_rows ; area ( km square ) ; 40 } = true'} | most_greater { all_rows ; area ( km square ) ; 40 } = true | for the area ( km square ) records of all rows , most of them are greater than 40 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'area (km square)_3': 3, '40_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'area (km square)_3': 'area ( km square )', '40_4': '40'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'area (km square)_3': [0], '40_4': [0]} | ['name', 'hanzi', 'area ( km square )', 'population', 'villages'] | [['wuji town', '无极镇', '57', '76851', '25'], ['qiji town', '七汲镇', '54', '41584', '20'], ['zhangduangu town', '张段固镇', '51', '40916', '20'], ['beisu town', '北苏镇', '54', '54639', '18'], ['guozhuang town', '郭庄镇', '43', '43636', '23'], ['dachen town', '大陈镇', '42', '31297', '13'], ['haozhuang township', '郝庄乡', '55', '37786', ... |
1965 vfl season | https://en.wikipedia.org/wiki/1965_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10788451-14.html.csv | aggregation | the average crowd attendance for the vfl games played was 23360 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '23360', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '23360', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '23360'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 23360 } = true', 'tointer': 'the average of the crowd record of all rows is 23360 .'} | round_eq { avg { all_rows ; crowd } ; 23360 } = true | the average of the crowd record of all rows is 23360 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '23360_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '23360_5': '23360'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '23360_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '10.17 ( 77 )', 'north melbourne', '5.4 ( 34 )', 'kardinia park', '19658', '31 july 1965'], ['essendon', '13.18 ( 96 )', 'footscray', '6.11 ( 47 )', 'windy hill', '16800', '31 july 1965'], ['carlton', '9.19 ( 73 )', 'south melbourne', '13.12 ( 90 )', 'princes park', '20744', '31 july 1965'], ['st kilda', '... |
1935 vfl season | https://en.wikipedia.org/wiki/1935_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790651-2.html.csv | aggregation | the average crowd in attendance at a 1935 vfl season match was 22250 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '22250', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '22250', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '22250'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 22250 } = true', 'tointer': 'the average of the crowd record of all rows is 22250 .'} | round_eq { avg { all_rows ; crowd } ; 22250 } = true | the average of the crowd record of all rows is 22250 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '22250_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '22250_5': '22250'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '22250_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '14.20 ( 104 )', 'melbourne', '16.6 ( 102 )', 'corio oval', '11000', '4 may 1935'], ['essendon', '13.17 ( 95 )', 'st kilda', '13.14 ( 92 )', 'windy hill', '21500', '4 may 1935'], ['richmond', '14.11 ( 95 )', 'north melbourne', '10.12 ( 72 )', 'punt road oval', '14000', '4 may 1935'], ['south melbourne', '1... |
howard county delegation | https://en.wikipedia.org/wiki/Howard_County_Delegation | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14009909-1.html.csv | ordinal | the 7th candidate to be elected represents the republican party . | {'row': '2', 'col': '5', 'order': '7', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 7 }'}, 'party'], 'result': 'republican', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 7 } ; party }... | eq { hop { nth_argmin { all_rows ; first elected ; 7 } ; party } ; republican } = true | select the row whose first elected record of all rows is 7th minimum . the party record of this row is republican . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '7_6': 6, 'party_7': 7, 'republican_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '7_6': '7', 'party_7': 'party', 'republican_8': 'republican'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '7_6': [0], 'party_7': [1], 'republican_8': [2]} | ['district', 'counties represented', 'delegate', 'party', 'first elected', 'committee'] | [['09.1 9a', 'howard', 'bates , gail h gail h bates', 'republican', '2002', 'appropriations'], ['09.1 9a', 'howard', 'miller , warren e warren e miller', 'republican', '2003', 'economic matters'], ['12.1 12a', 'baltimore county , howard', 'deboy , steven j sr steven j deboy , sr', 'democratic', '2002', 'appropriations'... |
list of tallest buildings in saudi arabia | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Saudi_Arabia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11606138-2.html.csv | count | 7 of the tallest buildings in saudi arabia are located in the city of jeddah . | {'scope': 'all', 'criterion': 'equal', 'value': 'jeddah', 'result': '7', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'jeddah'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city record fuzzily matches to jeddah .', 'tostr': 'filter_eq { all_rows ; city ; jeddah }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; city ; jeddah } } ; 7 } = true | select the rows whose city record fuzzily matches to jeddah . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'city_5': 5, 'jeddah_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'city_5': 'city', 'jeddah_6': 'jeddah', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'city_5': [0], 'jeddah_6': [0], '7_7': [2]} | ['rank', 'name', 'city', 'height', 'floors'] | [['1', 'kingdom tower', 'jeddah', '-', '186'], ['2', 'diamond tower', 'jeddah', '-', '93'], ['3', 'capital market authority headquarters', 'riyadh', '-', '77'], ['4', 'lamar tower 1', 'jeddah', '-', '87'], ['5', 'burj rafal', 'riyadh', '-', '68'], ['6', 'kafd world trade centre', 'riyadh', '-', '67'], ['7', 'lamar towe... |
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 | count | in the 1997-98 philadelphia flyers season , four of the players were from canada . | {'scope': 'all', 'criterion': 'equal', 'value': 'canada', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'canada'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; nationality ; canada }'}], 'result': '4', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; nationality ; canada } } ; 4 } = true | select the rows whose nationality record fuzzily matches to canada . 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, 'nationality_5': 5, 'canada_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', 'nationality_5': 'nationality', 'canada_6': 'canada', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'canada_6': [0], '4_7': [2]} | ['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... |
eurobasket 1967 | https://en.wikipedia.org/wiki/EuroBasket_1967 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13843829-3.html.csv | unique | position 7 was the only position to have a total of two points . | {'scope': 'all', 'row': '7', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 2 .', 'tostr': 'filter_eq { all_rows ; points ; 2 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; po... | and { only { filter_eq { all_rows ; points ; 2 } } ; eq { hop { filter_eq { all_rows ; points ; 2 } ; pos } ; 7 } } = true | select the rows whose points record is equal to 2 . there is only one such row in the table . the pos record of this unqiue row is 7 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'points_7': 7, '2_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'pos_9': 9, '7_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'points_7': 'points', '2_8': '2', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'pos_9': 'pos', '7_10': '7'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '2_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'pos_9': [2], '7_10': [3]} | ['pos', 'matches', 'wins', 'loses', 'results', 'points', 'diff'] | [['1', '7', '6', '1', '550:461', '12', '+ 89'], ['2', '7', '6', '1', '554:485', '12', '+ 69'], ['3', '7', '5', '2', '479:449', '10', '+ 30'], ['4', '7', '4', '3', '493:497', '8', '4'], ['5', '7', '4', '3', '523:507', '8', '+ 16'], ['6', '7', '2', '5', '526:579', '4', '53'], ['7', '7', '1', '6', '500:581', '2', '81'], [... |
henlopen conference | https://en.wikipedia.org/wiki/Henlopen_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-18.html.csv | unique | of all the teams at the henlopen conference , the indians are the only team that won div ii state championship . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'won div ii state championship', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season outcome', 'won div ii state championship'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season outcome record fuzzily matches to won div ii state championship .', 'tostr': 'filter_eq { all_rows ; se... | and { only { filter_eq { all_rows ; season outcome ; won div ii state championship } } ; eq { hop { filter_eq { all_rows ; season outcome ; won div ii state championship } ; team } ; indians } } = true | select the rows whose season outcome record fuzzily matches to won div ii state championship . there is only one such row in the table . the team record of this unqiue row is indians . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'season outcome_7': 7, 'won div ii state championship_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'indians_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'season outcome_7': 'season outcome', 'won div ii state championship_8': 'won div ii state championship', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'indians_10': 'indians'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'season outcome_7': [0], 'won div ii state championship_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'indians_10': [3]} | ['school', 'team', 'division record', 'overall record', 'season outcome'] | [['indian river', 'indians', '6 - 0', '12 - 0', 'won div ii state championship'], ['delmar', 'wildcats', '5 - 1', '9 - 2', 'loss in first round of div ii playoffs'], ['laurel', 'bulldogs', '4 - 2', '4 - 6', 'failed to make playoffs'], ['lake forest', 'spartans', '3 - 3', '5 - 5', 'failed to make playoffs'], ['polytech'... |
list of cities in the far east by population | https://en.wikipedia.org/wiki/List_of_cities_in_the_Far_East_by_population | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16478687-5.html.csv | unique | of the list of cities in the far east with the highest population , the only one in burma is yangon . | {'scope': 'all', 'row': '15', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'burma', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'burma'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to burma .', 'tostr': 'filter_eq { all_rows ; country ; burma }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; country ; burma } } ; eq { hop { filter_eq { all_rows ; country ; burma } ; city } ; yangon } } = true | select the rows whose country record fuzzily matches to burma . there is only one such row in the table . the city record of this unqiue row is yangon . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'burma_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'city_9': 9, 'yangon_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', 'burma_8': 'burma', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'city_9': 'city', 'yangon_10': 'yangon'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'burma_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'city_9': [2], 'yangon_10': [3]} | ['rank', 'city', 'population', 'definition', 'country'] | [['1', 'shanghai', '13831900', 'core districts + inner suburbs', 'china'], ['2', 'seoul', '10456034', 'special city', 'south korea'], ['3', 'beijing', '10123000', 'core districts + inner suburbs', 'china'], ['4', 'tokyo', '8795000', '23 special wards area', 'japan'], ['5', 'jakarta', '8489910', 'special capital distric... |
2007 volta a catalunya | https://en.wikipedia.org/wiki/2007_Volta_a_Catalunya | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11355733-15.html.csv | count | two of the competitors had a time of +40 in the 2007 volta a catalunya . | {'scope': 'all', 'criterion': 'equal', 'value': '+40', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time', '+40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time record fuzzily matches to +40 .', 'tostr': 'filter_eq { all_rows ; time ; +40 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { al... | eq { count { filter_eq { all_rows ; time ; +40 } } ; 2 } = true | select the rows whose time record fuzzily matches to +40 . 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, 'time_5': 5, '+40_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', 'time_5': 'time', '+40_6': '+40', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'time_5': [0], '+40_6': [0], '2_7': [2]} | ['cyclist', 'country', 'team', 'time', 'uci points'] | [['vladimir karpets', 'russia', "caisse d'epargne", "22h 21 ' 05", '50'], ['denis menchov', 'russia', 'rabobank', '+ 40', '40'], ['michael rogers', 'australia', 't - mobile team', '+ 40', '35'], ['christophe moreau', 'france', 'ag2r prévoyance', "+ 1 ' 34", '30'], ['óscar sevilla', 'spain', 'relax - gam', "+ 1 ' 34", '... |
nicolas lapierre | https://en.wikipedia.org/wiki/Nicolas_Lapierre | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1628448-4.html.csv | count | from 2007 to 2013 , nicolas lapierre raced two times for toyota racing . | {'scope': 'all', 'criterion': 'equal', 'value': 'toyota racing', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'toyota racing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to toyota racing .', 'tostr': 'filter_eq { all_rows ; team ; toyota racing }'}], 'result': '2', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; team ; toyota racing } } ; 2 } = true | select the rows whose team record fuzzily matches to toyota racing . 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, 'team_5': 5, 'toyota racing_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', 'team_5': 'team', 'toyota racing_6': 'toyota racing', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'toyota racing_6': [0], '2_7': [2]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2007', 'team oreca', 'stéphane ortelli soheil ayari', 'gt1', '318', '16th', '9th'], ['2009', 'team oreca - matmut aim', 'olivier panis soheil ayari', 'lmp1', '370', '5th', '5th'], ['2010', 'team oreca - matmut', 'olivier panis loïc duval', 'lmp1', '373', 'dnf', 'dnf'], ['2011', 'team oreca - matmut', 'olivier panis ... |
2003 - 04 new york rangers season | https://en.wikipedia.org/wiki/2003%E2%80%9304_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14532362-7.html.csv | ordinal | the new york rangers ' game against the vancouver canucks was the earliest in the 2003 - 04 season . | {'row': '1', 'col': '2', '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', 'february', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; february ; 1 }'}, 'opponent'], 'result': 'vancouver canucks', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; february ; 1 } ; opponent }'}... | eq { hop { nth_argmin { all_rows ; february ; 1 } ; opponent } ; vancouver canucks } = true | select the row whose february record of all rows is 1st minimum . the opponent record of this row is vancouver canucks . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'february_5': 5, '1_6': 6, 'opponent_7': 7, 'vancouver canucks_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', 'february_5': 'february', '1_6': '1', 'opponent_7': 'opponent', 'vancouver canucks_8': 'vancouver canucks'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'february_5': [0], '1_6': [0], 'opponent_7': [1], 'vancouver canucks_8': [2]} | ['game', 'february', 'opponent', 'score', 'record'] | [['54', '2', 'vancouver canucks', '4 - 3', '20 - 23 - 7 - 4'], ['55', '4', 'minnesota wild', '4 - 3', '20 - 24 - 7 - 4'], ['56', '11', 'new jersey devils', '3 - 1', '21 - 24 - 7 - 4'], ['57', '12', 'philadelphia flyers', '2 - 1', '21 - 25 - 7 - 4'], ['58', '14', 'philadelphia flyers', '6 - 2', '21 - 26 - 7 - 4'], ['59'... |
liselotte neumann | https://en.wikipedia.org/wiki/Liselotte_Neumann | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1710991-1.html.csv | superlative | liselotte neumann 's highest margin of victory was by 11 strokes . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'margin of victory'], 'result': '11 strokes', 'ind': 0, 'tostr': 'max { all_rows ; margin of victory }', 'tointer': 'the maximum margin of victory record of all rows is 11 strokes .'}, '11 strokes'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; m... | eq { max { all_rows ; margin of victory } ; 11 strokes } = true | the maximum margin of victory record of all rows is 11 strokes . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'margin of victory_4': 4, '11 strokes_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'margin of victory_4': 'margin of victory', '11 strokes_5': '11 strokes'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'margin of victory_4': [0], '11 strokes_5': [1]} | ['date', 'tournament', 'winning score', 'margin of victory', 'runner ( s ) - up'] | [['7 sep 1988', "us women 's open", '- 7 ( 67 + 72 + 69 + 69 = 277 )', '3 strokes', 'patty sheehan'], ['10 nov 1991', 'mazda japan classic', '- 5 ( 70 + 72 + 69 = 211 )', '2 strokes', 'caroline keggi , dottie pepper'], ['12 jun 1994', 'minnesota lpga classic', '- 11 ( 68 + 71 + 66 = 205 )', '2 strokes', 'hiromi kobayas... |
2003 bridgeport barrage season | https://en.wikipedia.org/wiki/2003_Bridgeport_Barrage_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12101799-1.html.csv | count | of the games in the 2003 bridgeport barrage season , 6 of them were home games . | {'scope': 'all', 'criterion': 'equal', 'value': 'home', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home / away', 'home'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home / away record fuzzily matches to home .', 'tostr': 'filter_eq { all_rows ; home / away ; home }'}], 'result': '6', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; home / away ; home } } ; 6 } = true | select the rows whose home / away record fuzzily matches to home . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'home / away_5': 5, 'home_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'home / away_5': 'home / away', 'home_6': 'home', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'home / away_5': [0], 'home_6': [0], '6_7': [2]} | ['date', 'opponent', 'home / away', 'field', 'result'] | [['may 31', 'rattlers', 'away', 'bishop kearney field', 'l 13 - 23'], ['june 6', 'cannons', 'home', 'the ballpark at harbor yard', 'l 17 - 23'], ['june 12', 'bayhawks', 'home', 'the ballpark at harbor yard', 'l 14 - 21'], ['june 14', 'pride', 'away', 'commerce bank ballpark', 'l 9 - 16'], ['june 27', 'lizards', 'away',... |
2008 wnba draft | https://en.wikipedia.org/wiki/2008_WNBA_draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14122892-3.html.csv | majority | all of the women drafted to the wnba in 2008 were from the us . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'} | all_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['pick', 'player', 'nationality', 'wnba team', 'school / club team'] | [['1', 'candace parker', 'united states', 'los angeles sparks', 'tennessee'], ['2', 'sylvia fowles', 'united states', 'chicago sky', 'lsu'], ['3', 'candice wiggins', 'united states', 'minnesota lynx', 'stanford'], ['4', 'alexis hornbuckle', 'united states', 'detroit shock ( from atl , via sea )', 'tennessee'], ['5', 'm... |
1973 - 74 philadelphia flyers season | https://en.wikipedia.org/wiki/1973%E2%80%9374_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13908182-10.html.csv | aggregation | total attendance at philadelphia flyers games was 120,528 during the 1973 - 1974 season . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '120528', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '120528', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '120528'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 120528 } = true', 'tointer': 'the sum of the attendance record of all rows ... | round_eq { sum { all_rows ; attendance } ; 120528 } = true | the sum of the attendance record of all rows is 120528 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '120528_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '120528_5': '120528'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '120528_5': [1]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'series'] | [['april 20', 'ny rangers', '0 - 4', 'philadelphia', 'parent', '17007', 'flyers lead 1 - 0'], ['april 23', 'ny rangers', '2 - 5', 'philadelphia', 'parent', '17007', 'flyers lead 2 - 0'], ['april 25', 'philadelphia', '3 - 5', 'ny rangers', 'parent', '17500', 'flyers lead 2 - 1'], ['april 28', 'philadelphia', '1 - 2', 'n... |
high - temperature superconductivity | https://en.wikipedia.org/wiki/High-temperature_superconductivity | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-101336-1.html.csv | majority | the majority of t c ( k ) is over 80 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '80', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 't c ( k )', '80'], 'result': True, 'ind': 0, 'tointer': 'for the t c ( k ) records of all rows , most of them are greater than 80 .', 'tostr': 'most_greater { all_rows ; t c ( k ) ; 80 } = true'} | most_greater { all_rows ; t c ( k ) ; 80 } = true | for the t c ( k ) records of all rows , most of them are greater than 80 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 't c (k)_3': 3, '80_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 't c (k)_3': 't c ( k )', '80_4': '80'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 't c (k)_3': [0], '80_4': [0]} | ['formula', 'notation', 't c ( k )', 'no of cu - o planes in unit cell', 'crystal structure'] | [['yba 2 cu 3 o 7', '123', '92', '2', 'orthorhombic'], ['bi 2 sr 2 cuo 6', 'bi - 2201', '20', '1', 'tetragonal'], ['bi 2 sr 2 cacu 2 o 8', 'bi - 2212', '85', '2', 'tetragonal'], ['bi 2 sr 2 ca 2 cu 3 o 6', 'bi - 2223', '110', '3', 'tetragonal'], ['tl 2 ba 2 cuo 6', 'tl - 2201', '80', '1', 'tetragonal'], ['tl 2 ba 2 cac... |
2005 japanese television dramas | https://en.wikipedia.org/wiki/2005_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18540104-1.html.csv | majority | most of the 2005 japanese television dramas had eleven episodes . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '11', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'episodes', '11'], 'result': True, 'ind': 0, 'tointer': 'for the episodes records of all rows , most of them are equal to 11 .', 'tostr': 'most_eq { all_rows ; episodes ; 11 } = true'} | most_eq { all_rows ; episodes ; 11 } = true | for the episodes records of all rows , most of them are equal to 11 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'episodes_3': 3, '11_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'episodes_3': 'episodes', '11_4': '11'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'episodes_3': [0], '11_4': [0]} | ['japanese title', 'romaji title', 'tv station', 'theme song ( s )', 'episodes', 'average ratings'] | [['恋におちたら ～ 僕の成功の秘密 ～', 'koi ni ochitara ~ boku no seikou no himitsu ~', 'fuji tv', 'crystal kay 恋におちたら ( koi ni ochitara )', '11', '16.3 %'], ['離婚弁護士ii ～ ハンサムウーマン ～', 'rikon bengoshi ii ~ handsome woman ~', 'fuji tv', 'hoshimura mai every', '11', '13.2 %'], ['エンジン', 'engine', 'fuji tv', 'jimmy cliff i can see clearly ... |
amanda overmyer | https://en.wikipedia.org/wiki/Amanda_Overmyer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15796072-1.html.csv | comparative | amanda overmyer had a lower order number for the 1960s theme week than for the 1970s theme week . | {'row_1': '3', 'row_2': '4', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'week', 'top 24 ( 12 women )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose week record fuzzily matches to top 24 ( 12 women ) .', 'tostr': 'filter_eq { all_rows ; week ; top 24 ( 12 women ) }'}, 'order... | less { hop { filter_eq { all_rows ; week ; top 24 ( 12 women ) } ; order } ; hop { filter_eq { all_rows ; week ; top 20 ( 10 women ) } ; order } } = true | select the rows whose week record fuzzily matches to top 24 ( 12 women ) . take the order record of this row . select the rows whose week record fuzzily matches to top 20 ( 10 women ) . take the order 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, 'week_7': 7, 'top 24 (12 women)_8': 8, 'order_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'week_11': 11, 'top 20 (10 women)_12': 12, 'order_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', 'week_7': 'week', 'top 24 (12 women)_8': 'top 24 ( 12 women )', 'order_9': 'order', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'week_11': 'week', 'top ... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'week_7': [0], 'top 24 (12 women)_8': [0], 'order_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'week_11': [1], 'top 20 (10 women)_12': [1], 'order_13': [3]} | ['week', 'theme', 'song choice', 'original artist', 'order', 'result'] | [['hollywood', 'n / a', 'light my fire', 'the doors', 'n / a', 'advanced'], ['hollywood', 'n / a', 'piece of my heart', 'erma franklin', 'n / a', 'advanced'], ['top 24 ( 12 women )', '1960s', "baby , please do n't go", 'big joe williams', '4', 'safe'], ['top 20 ( 10 women )', '1970s', 'carry on wayward son', 'kansas', ... |
peak water | https://en.wikipedia.org/wiki/Peak_water | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15909409-3.html.csv | aggregation | the average total freshwater withdrawal for the listed countries is 60.34 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '60.34', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total freshwater withdrawal'], 'result': '60.34', 'ind': 0, 'tostr': 'avg { all_rows ; total freshwater withdrawal }'}, '60.34'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total freshwater withdrawal } ; 60.34 } = true', 'tointer'... | round_eq { avg { all_rows ; total freshwater withdrawal } ; 60.34 } = true | the average of the total freshwater withdrawal record of all rows is 60.34 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total freshwater withdrawal_4': 4, '60.34_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total freshwater withdrawal_4': 'total freshwater withdrawal', '60.34_5': '60.34'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total freshwater withdrawal_4': [0], '60.34_5': [1]} | ['', 'total freshwater withdrawal', 'per capita withdrawal', 'domestic use', 'industrial use', 'agricultural use'] | [['turkmenistan', '24.65', '5104', '2', '1', '98'], ['kazakhstan', '35', '2360', '2', '17', '82'], ['uzbekistan', '58.34', '2194', '5', '2', '93'], ['guyana', '1.64', '2187', '2', '1', '98'], ['hungary', '21.03', '2082', '9', '59', '32'], ['azerbaijan', '17.25', '2051', '5', '28', '68'], ['kyrgyzstan', '10.08', '1916',... |
1992 - 93 argentine primera división | https://en.wikipedia.org/wiki/1992%E2%80%9393_Argentine_Primera_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17968282-1.html.csv | comparative | in the 1992 - 93 argentine primera división , the team vélez sársfield had more points than the team newell 's old boys . | {'row_1': '3', 'row_2': '7', 'col': '3', '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', 'team', 'vélez sársfield'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to vélez sársfield .', 'tostr': 'filter_eq { all_rows ; team ; vélez sársfield }'}, 'points'], 'res... | greater { hop { filter_eq { all_rows ; team ; vélez sársfield } ; points } ; hop { filter_eq { all_rows ; team ; newell 's old boys } ; points } } = true | select the rows whose team record fuzzily matches to vélez sársfield . take the points record of this row . select the rows whose team record fuzzily matches to newell 's old boys . 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, 'team_7': 7, 'vélez sársfield_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, "newell 's old boys_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', 'team_7': 'team', 'vélez sársfield_8': 'vélez sársfield', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', "ne... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'vélez sársfield_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], "newell 's old boys_12": [1], 'points_13': [3]} | ['team', 'average', 'points', 'played', '1991 - 92', '1992 - 93', '1993 - 94'] | [['boca juniors', '1.307', '149', '114', '51', '50', '48'], ['river plate', '1.281', '146', '114', '45', '55', '46'], ['vélez sársfield', '1.237', '141', '114', '45', '48', '48'], ['san lorenzo', '1.088', '124', '114', '45', '45', '45'], ['huracán', '1.061', '121', '114', '40', '38', '43'], ['independiente', '1.026', '... |
netherlands at the 2008 summer paralympics | https://en.wikipedia.org/wiki/Netherlands_at_the_2008_Summer_Paralympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18602462-9.html.csv | unique | for the netherlands at the 2008 summer paralympics , in the championship test , the only athlete with the horse donna dm is sabine peters . | {'scope': 'subset', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'donna dm', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'championship test'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'championship test'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; event ; championship test }', 'tointer': 'select the rows whose event record fuzzily matches to c... | and { only { filter_eq { filter_eq { all_rows ; event ; championship test } ; horse ; donna dm } } ; eq { hop { filter_eq { filter_eq { all_rows ; event ; championship test } ; horse ; donna dm } ; athlete } ; sabine peters } } = true | select the rows whose event record fuzzily matches to championship test . among these rows , select the rows whose horse record fuzzily matches to donna dm . there is only one such row in the table . the athlete record of this unqiue row is sabine peters . | 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, 'event_8': 8, 'championship test_9': 9, 'horse_10': 10, 'donna dm_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'athlete_12': 12, 'sabine peters_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', 'event_8': 'event', 'championship test_9': 'championship test', 'horse_10': 'horse', 'donna dm_11': 'donna dm', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'athlete_... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'event_8': [0], 'championship test_9': [0], 'horse_10': [1], 'donna dm_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'athlete_12': [3], 'sabine peters_13': [4]} | ['athlete', 'class', 'horse', 'event', 'result', 'rank'] | [['ineke de groot', 'grade iv', 'indo', 'championship test', '63.161', '7'], ['ineke de groot', 'grade iv', 'indo', 'freestyle test', '58.955', '13'], ['sabine peters', 'grade iv', 'donna dm', 'championship test', '62.516', '8'], ['sabine peters', 'grade iv', 'donna dm', 'freestyle test', '65.863', '9'], ['petra van de... |
television in italy | https://en.wikipedia.org/wiki/Television_in_Italy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15887683-16.html.csv | majority | of the television stations of italy , most have televendita as the content . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'televendita', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'content', 'televendita'], 'result': True, 'ind': 0, 'tointer': 'for the content records of all rows , most of them fuzzily match to televendita .', 'tostr': 'most_eq { all_rows ; content ; televendita } = true'} | most_eq { all_rows ; content ; televendita } = true | for the content records of all rows , most of them fuzzily match to televendita . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'content_3': 3, 'televendita_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'content_3': 'content', 'televendita_4': 'televendita'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'content_3': [0], 'televendita_4': [0]} | ['n degree', 'television service', 'country', 'language', 'content', 'dar', 'hdtv', 'package / option'] | [['861', 'telemarket', 'italy', 'italian', 'televendita', '4:3', 'no', 'no ( fta )'], ['862', 'noello sat', 'italy', 'italian', 'televendita', '4:3', 'no', 'no ( fta )'], ['863', 'elite shopping tv', 'italy', 'italian', 'televendita', '4:3', 'no', 'no ( fta )'], ['864', 'juwelo', 'italy', 'italian', 'televendita', '4:3... |
1934 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1934_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18007167-2.html.csv | aggregation | in the 1934 u.s golf open , the total price money won by all the players was $ 4014 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '4014', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'money'], 'result': '4014', 'ind': 0, 'tostr': 'sum { all_rows ; money }'}, '4014'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; money } ; 4014 } = true', 'tointer': 'the sum of the money record of all rows is 4014 .'} | round_eq { sum { all_rows ; money } ; 4014 } = true | the sum of the money record of all rows is 4014 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'money_4': 4, '4014_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'money_4': 'money', '4014_5': '4014'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'money_4': [0], '4014_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'olin dutra', 'united states', '76 + 74 + 71 + 72 = 293', '+ 13', '1000'], ['2', 'gene sarazen', 'united states', '73 + 72 + 73 + 76 = 294', '+ 14', '750'], ['t3', 'harry cooper', 'england united states', '76 + 74 + 74 + 71 = 295', '+ 15', '400'], ['t3', 'wiffy cox', 'united states', '71 + 75 + 74 + 75 = 295', '... |
1966 atlanta falcons season | https://en.wikipedia.org/wiki/1966_Atlanta_Falcons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16710917-2.html.csv | count | in the 1966 atlanta falcons season , among the games with attendance over 50,000 , two of them were played in december . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'december', 'result': '2', 'col': '2', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '50000'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '50000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; attendance ; 50000 }', 'tointer': 'select the rows whose attendance record is greater than 50000 .... | eq { count { filter_eq { filter_greater { all_rows ; attendance ; 50000 } ; date ; december } } ; 2 } = true | select the rows whose attendance record is greater than 50000 . among these rows , select the rows whose date record fuzzily matches to december . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'attendance_6': 6, '50000_7': 7, 'date_8': 8, 'december_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'attendance_6': 'attendance', '50000_7': '50000', 'date_8': 'date', 'december_9': 'december', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'attendance_6': [0], '50000_7': [0], 'date_8': [1], 'december_9': [1], '2_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 11 , 1966', 'los angeles rams', 'l 19 - 14', '54418'], ['2', 'september 18 , 1966', 'philadelphia eagles', 'l 23 - 10', '54049'], ['3', 'september 25 , 1966', 'detroit lions', 'l 28 - 10', '47615'], ['4', 'october 2 , 1966', 'dallas cowboys', 'l 47 - 14', '56990'], ['5', 'october 9 , 1966', 'washingto... |
2001 cfl draft | https://en.wikipedia.org/wiki/2001_CFL_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15817998-2.html.csv | count | there were 2 wr 's picked from picks 9-16 in the 2001 cfl draft . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'wr', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'wr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to wr .', 'tostr': 'filter_eq { all_rows ; position ; wr }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; position ; wr } } ; 2 } = true | select the rows whose position record fuzzily matches to wr . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'wr_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'wr_6': 'wr', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'wr_6': [0], '2_7': [2]} | ['pick', 'cfl team', 'player', 'position', 'college'] | [['9', 'saskatchewan roughriders', 'jason french', 'wr', 'murray state'], ['10', 'calgary stampeders', 'lawrence deck', 'db', 'fresno state'], ['11', 'montreal alouettes', 'pat woodcock', 'wr', 'syracuse'], ['12', 'hamilton tiger - cats', 'karim grant', 'lb', 'acadia'], ['13', 'edmonton eskimos', 'fabian burke', 'cb', ... |
2005 rhein fire season | https://en.wikipedia.org/wiki/2005_Rhein_Fire_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25380472-2.html.csv | ordinal | the game on april 30th for the 2005 rhein fire season had the third highest attendance . | {'row': '5', 'col': '8', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 3 }'}, 'date'], 'result': 'saturday , april 30', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 3 } ; date }'}... | eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; saturday , april 30 } = true | select the row whose attendance record of all rows is 3rd maximum . the date record of this row is saturday , april 30 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'date_7': 7, 'saturday , april 30_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '3_6': '3', 'date_7': 'date', 'saturday , april 30_8': 'saturday , april 30'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'date_7': [1], 'saturday , april 30_8': [2]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , april 2', '7:00 pm', 'amsterdam admirals', 'l 14 - 24', '0 - 1', 'amsterdam arena', '10234'], ['2', 'sunday , april 10', '4:00 pm', 'cologne centurions', 'l 10 - 23', '0 - 2', 'ltu arena', '25304'], ['3', 'saturday , april 16', '7:00 pm', 'hamburg sea devils', 'l 24 - 31', '0 - 3', 'aol arena', '1986... |
1969 vfl season | https://en.wikipedia.org/wiki/1969_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809157-13.html.csv | aggregation | in the 1969 vfl season , for games with a crowd size of under 10,000 , the average crowd was 7005 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '7005', 'subset': {'col': '6', 'criterion': 'less_than', 'value': '10000'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; crowd ; 10000 }', 'tointer': 'select the rows whose crowd record is less than 10000 .'}, 'crowd'], 'result': '7005', 'ind': 1, 'tostr': 'avg... | round_eq { avg { filter_less { all_rows ; crowd ; 10000 } ; crowd } ; 7005 } = true | select the rows whose crowd record is less than 10000 . the average of the crowd record of these rows is 7005 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '10000_6': 6, 'crowd_7': 7, '7005_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '10000_6': '10000', 'crowd_7': 'crowd', '7005_8': '7005'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '10000_6': [0], 'crowd_7': [1], '7005_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['fitzroy', '18.21 ( 129 )', 'south melbourne', '11.14 ( 80 )', 'princes park', '7540', '5 july 1969'], ['north melbourne', '19.16 ( 130 )', 'melbourne', '19.13 ( 127 )', 'arden street oval', '6470', '5 july 1969'], ['st kilda', '12.15 ( 87 )', 'footscray', '12.5 ( 77 )', 'moorabbin oval', '14995', '5 july 1969'], ['g... |
cryengine | https://en.wikipedia.org/wiki/CryEngine | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1241866-4.html.csv | count | bethesda softworks was the publisher of two games made using the cryengine . | {'scope': 'all', 'criterion': 'equal', 'value': 'bethesda softworks', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'publisher', 'bethesda softworks'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose publisher record fuzzily matches to bethesda softworks .', 'tostr': 'filter_eq { all_rows ; publisher ; bethesda softworks }'}... | eq { count { filter_eq { all_rows ; publisher ; bethesda softworks } } ; 2 } = true | select the rows whose publisher record fuzzily matches to bethesda softworks . 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, 'publisher_5': 5, 'bethesda softworks_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', 'publisher_5': 'publisher', 'bethesda softworks_6': 'bethesda softworks', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'publisher_5': [0], 'bethesda softworks_6': [0], '2_7': [2]} | ['title', 'year', 'developer', 'publisher', 'platform'] | [['homefront 2', '2014', 'crytek uk', 'crytek', 'tba'], ['ryse : son of rome', '2013', 'crytek gmbh', 'microsoft studios', 'xbox one'], ['star citizen', '2014', 'cloud imperium games corporation', 'cloud imperium games corporation', 'microsoft windows'], ['unannounced arkane studios title', 'tba', 'arkane studios', 'be... |
pablo andújar | https://en.wikipedia.org/wiki/Pablo_And%C3%BAjar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16949333-3.html.csv | majority | all of pablo andujar 's matches were played on a clay surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , all of them fuzzily match to clay .', 'tostr': 'all_eq { all_rows ; surface ; clay } = true'} | all_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , all of them fuzzily match to clay . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', 'september 26 , 2010', 'brd năstase ţiriac trophy , bucharest , romania', 'clay', 'juan ignacio chela', '5 - 7 , 1 - 6'], ['winner', 'april 10 , 2011', 'grand prix hassan ii , casablanca , morocco ( 1 )', 'clay', 'potito starace', '6 - 1 , 6 - 2'], ['runner - up', 'july 17 , 2011', 'mercedescup , stutt... |
spaceport | https://en.wikipedia.org/wiki/Spaceport | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-179174-2.html.csv | unique | in the list of spaceport and flights the only launcher for lunar flights was the saturn v. | {'scope': 'all', 'row': '12', 'col': '3', 'col_other': '5', 'criterion': 'equal', 'value': 'saturn v', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'launcher', 'saturn v'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose launcher record fuzzily matches to saturn v .', 'tostr': 'filter_eq { all_rows ; launcher ; saturn v }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; launcher ; saturn v } } ; eq { hop { filter_eq { all_rows ; launcher ; saturn v } ; flights } ; 10 lun / or } } = true | select the rows whose launcher record fuzzily matches to saturn v . there is only one such row in the table . the flights record of this unqiue row is 10 lun / or . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'launcher_7': 7, 'saturn v_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'flights_9': 9, '10 lun / or_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'launcher_7': 'launcher', 'saturn v_8': 'saturn v', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'flights_9': 'flights', '10 lun / or_10': '10 lun / or'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'launcher_7': [0], 'saturn v_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'flights_9': [2], '10 lun / or_10': [3]} | ['spaceport', 'launch complex', 'launcher', 'spacecraft', 'flights', 'years'] | [['baikonur cosmodrome , kazakhstan', 'site 1', 'vostok ( r )', 'vostok 1 - 6', '6 orbital', '1961 - 1963'], ['baikonur cosmodrome , kazakhstan', 'site 1', 'voskhod ( r )', 'voskhod 1 - 2', '2 orbital', '1964 - 1965'], ['baikonur cosmodrome , kazakhstan', 'site 1 , 31', 'soyuz ( r )', 'soyuz 1 - 40', '37 orbital', '196... |
1926 vfl season | https://en.wikipedia.org/wiki/1926_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10746808-12.html.csv | aggregation | the average crowd attendance for all the games was 16000 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '16000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '16000', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '16000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 16000 } = true', 'tointer': 'the average of the crowd record of all rows is 16000 .'} | round_eq { avg { all_rows ; crowd } ; 16000 } = true | the average of the crowd record of all rows is 16000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '16000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '16000_5': '16000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '16000_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '10.15 ( 75 )', 'south melbourne', '16.12 ( 108 )', 'punt road oval', '27000', '17 july 1926'], ['footscray', '7.14 ( 56 )', 'geelong', '15.17 ( 107 )', 'western oval', '17000', '17 july 1926'], ['collingwood', '18.16 ( 124 )', 'fitzroy', '11.16 ( 82 )', 'victoria park', '16000', '17 july 1926'], ['carlto... |
2008 - 09 united states network television schedule | https://en.wikipedia.org/wiki/2008%E2%80%9309_United_States_network_television_schedule | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15708593-12.html.csv | unique | parks and recreation only has one 30 minute time slot . | {'scope': 'all', 'row': '9', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'parks and recreation', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '8:30', 'parks and recreation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 8:30 record fuzzily matches to parks and recreation .', 'tostr': 'filter_eq { all_rows ; 8:30 ; parks and recreation }'}], 'result': True, 'ind': 1, 'tost... | only { filter_eq { all_rows ; 8:30 ; parks and recreation } } = true | select the rows whose 8:30 record fuzzily matches to parks and recreation . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, '8:30_4': 4, 'parks and recreation_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', '8:30_4': '8:30', 'parks and recreation_5': 'parks and recreation'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], '8:30_4': [0], 'parks and recreation_5': [0]} | ['8:00', '8:30', '9:00', '9:30', '10:00'] | [['in the motherhood', 'samantha who', "grey 's anatomy", "grey 's anatomy", 'private practice'], ['ugly betty', 'ugly betty', "grey 's anatomy", "grey 's anatomy", 'private practice'], ['survivor : tocantins - the brazilian highlands', 'survivor : tocantins - the brazilian highlands', 'csi : crime scene investigation'... |
1970 detroit lions season | https://en.wikipedia.org/wiki/1970_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18733362-2.html.csv | aggregation | the 1970 detroit lions scored 25.5 points per game . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '25.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'result'], 'result': '25.5', 'ind': 0, 'tostr': 'avg { all_rows ; result }'}, '25.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; result } ; 25.5 } = true', 'tointer': 'the average of the result record of all rows is 25.5 .'} | round_eq { avg { all_rows ; result } ; 25.5 } = true | the average of the result record of all rows is 25.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'result_4': 4, '25.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'result_4': 'result', '25.5_5': '25.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'result_4': [0], '25.5_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 20 , 1970', 'green bay packers', 'w 40 - 0', '56263'], ['2', 'september 27 , 1970', 'cincinnati bengals', 'w 38 - 3', '58202'], ['3', 'october 5 , 1970', 'chicago bears', 'w 28 - 14', '58210'], ['4', 'october 11 , 1970', 'washington redskins', 'l 31 - 10', '50414'], ['5', 'october 18 , 1970', 'clevela... |
2006 - 07 coventry city f.c. season | https://en.wikipedia.org/wiki/2006%E2%80%9307_Coventry_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12808457-2.html.csv | superlative | in the 2006 - 07 coventry city f.c. season , kevin kyle had the most total . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'name'], 'result': 'kevin kyle', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; name }'}, 'kevin kyle'], 'result': True, 'ind': 2, 'tostr... | eq { hop { argmax { all_rows ; total } ; name } ; kevin kyle } = true | select the row whose total record of all rows is maximum . the name record of this row is kevin kyle . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'name_6': 6, 'kevin kyle_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'name_6': 'name', 'kevin kyle_7': 'kevin kyle'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'name_6': [1], 'kevin kyle_7': [2]} | ['name', 'championship', 'league cup', 'fa cup', 'total'] | [['kevin kyle', '11', '0', '1', '12'], ['robert page', '10', '0', '0', '10'], ['michael doyle', '8', '0', '2', '10'], ['andrew whing', '6', '1', '0', '7'], ['david mcnamee', '6', '0', '0', '6'], ['marcus hall', '5', '0', '0', '5'], ['leon mckenzie', '5', '0', '0', '5'], ['jay tabb', '5', '0', '0', '5'], ['elliott ward'... |
the apprentice new zealand | https://en.wikipedia.org/wiki/The_Apprentice_New_Zealand | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26263322-1.html.csv | superlative | of the candidates in the apprentice new zealand , kirsty parkhill is the oldest . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '12', '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', 'age'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; age }'}, 'candidate'], 'result': 'kirsty parkhill', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; age } ; candidate }'}, 'kirsty parkhill'], 'result': True, 'i... | eq { hop { argmax { all_rows ; age } ; candidate } ; kirsty parkhill } = true | select the row whose age record of all rows is maximum . the candidate record of this row is kirsty parkhill . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'age_5': 5, 'candidate_6': 6, 'kirsty parkhill_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'age_5': 'age', 'candidate_6': 'candidate', 'kirsty parkhill_7': 'kirsty parkhill'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'age_5': [0], 'candidate_6': [1], 'kirsty parkhill_7': [2]} | ['candidate', 'background', 'original team', 'age', 'hometown', 'result'] | [['thomas ben', 'divisional manager', 'number 8', '34', 'auckland', 'hired by serepisos'], ['david wyatt', 'self - employed - media agency', 'number 8', '27', 'auckland', 'fired in the season finale'], ['catherine livingstone', 'self - employed - concierge service', 'athena', '33', 'auckland', 'fired in week 12'], ['ka... |
jack mcgrath | https://en.wikipedia.org/wiki/Jack_McGrath | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236208-1.html.csv | unique | in 1949 there was the fewest laps with only 39 total laps . | {'scope': 'all', 'row': '2', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '39', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '39'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is equal to 39 .', 'tostr': 'filter_eq { all_rows ; laps ; 39 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; laps ... | and { only { filter_eq { all_rows ; laps ; 39 } } ; eq { hop { filter_eq { all_rows ; laps ; 39 } ; year } ; 1949 } } = true | select the rows whose laps record is equal to 39 . there is only one such row in the table . the year record of this unqiue row is 1949 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'laps_7': 7, '39_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1949_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'laps_7': 'laps', '39_8': '39', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1949_10': '1949'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'laps_7': [0], '39_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1949_10': [3]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1948', '13', '124.580', '16', '21', '70'], ['1949', '3', '128.884', '8', '26', '39'], ['1950', '6', '131.868', '10', '14', '131'], ['1951', '3', '134.303', '8', '3', '200'], ['1952', '3', '136.664', '5', '11', '200'], ['1953', '3', '136.602', '13', '5', '200'], ['1954', '1', '141.033', '1', '3', '200'], ['1955', '3'... |
2008 - 09 philadelphia 76ers season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Philadelphia_76ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17323042-11.html.csv | count | in the 2008 - 09 philadelphia 76ers season , among the games played in amway arena , two of them featured andre iguodala as a high pointer . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'andre iguodala', 'result': '2', 'col': '5', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'amway arena'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'amway arena'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; amway arena }', 'tointer': 'select the rows whose location attendan... | eq { count { filter_eq { filter_eq { all_rows ; location attendance ; amway arena } ; high points ; andre iguodala } } ; 2 } = true | select the rows whose location attendance record fuzzily matches to amway arena . among these rows , select the rows whose high points record fuzzily matches to andre iguodala . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location attendance_6': 6, 'amway arena_7': 7, 'high points_8': 8, 'andre iguodala_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location attendance_6': 'location attendance', 'amway arena_7': 'amway arena', 'high points_8': 'high points', 'andre iguodala_9': 'andre iguodala', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location attendance_6': [0], 'amway arena_7': [0], 'high points_8': [1], 'andre iguodala_9': [1], '2_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['1', 'april 19', 'orlando', 'w 100 - 98 ( ot )', 'andre iguodala ( 20 )', 'andre iguodala ( 8 )', 'andre iguodala ( 8 )', 'amway arena 17461', '1 - 0'], ['2', 'april 22', 'orlando', 'l 87 - 96 ( ot )', 'andre miller ( 30 )', 'andre iguodala , theo ratliff ( 8 )', 'andre iguodala ( 7 )', 'amway arena 17461', '1 - 1'],... |
2005 - 06 toronto raptors season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15873014-7.html.csv | count | chris bosh had the most rebounds in 9 games in march of the 2005 - 06 toronto raptors season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'chris bosh', 'result': '9', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'chris bosh'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high rebounds record fuzzily matches to chris bosh .', 'tostr': 'filter_eq { all_rows ; high rebounds ; chris bosh }'}], 'result':... | eq { count { filter_eq { all_rows ; high rebounds ; chris bosh } } ; 9 } = true | select the rows whose high rebounds record fuzzily matches to chris bosh . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high rebounds_5': 5, 'chris bosh_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high rebounds_5': 'high rebounds', 'chris bosh_6': 'chris bosh', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'chris bosh_6': [0], '9_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['57', 'march 1', 'atlanta', 'l 111 - 113 ( ot )', 'chris bosh ( 27 )', 'charlie villanueva ( 11 )', 'chris bosh ( 5 )', 'air canada centre 15137', '20 - 37'], ['58', 'march 4', 'new jersey', 'l 100 - 105 ( ot )', 'morris peterson ( 25 )', 'chris bosh , charlie villanueva ( 11 )', 'mike james ( 7 )', 'continental airl... |
list of ngc objects ( 2001 - 3000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%282001%E2%80%933000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11097664-6.html.csv | ordinal | in the list of ngc objects ( 2001 - 3000 ) hydra has the 2nd highest apparent magnitude among open cluster object type . | {'scope': 'subset', 'row': '8', 'col': '6', 'order': '2', 'col_other': '2,3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'open cluster'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'object type', 'open cluster'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; object type ; open cluster }', 'tointer': 'select the rows whose object type record fuzzily m... | eq { hop { nth_argmax { filter_eq { all_rows ; object type ; open cluster } ; apparent magnitude ; 2 } ; constellation } ; hydra } = true | select the rows whose object type record fuzzily matches to open cluster . select the row whose apparent magnitude record of these rows is 2nd maximum . the constellation record of this row is hydra . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'object type_6': 6, 'open cluster_7': 7, 'apparent magnitude_8': 8, '2_9': 9, 'constellation_10': 10, 'hydra_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'object type_6': 'object type', 'open cluster_7': 'open cluster', 'apparent magnitude_8': 'apparent magnitude', '2_9': '2', 'constellation_10': 'constellation', ... | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'object type_6': [0], 'open cluster_7': [0], 'apparent magnitude_8': [1], '2_9': [1], 'constellation_10': [2], 'hydra_11': [3]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )', 'apparent magnitude'] | [['2516', 'open cluster', 'carina', '07h58 m', 'degree45 ′', '3.8'], ['2535', 'spiral galaxy', 'cancer', '08h11 m13 .6 s', 'degree12 ′ 24 ″', '13.0'], ['2536', 'spiral galaxy', 'cancer', '08h11 m16 .1 s', 'degree10 ′ 45 ″', '14.5'], ['2537', 'irregular galaxy', 'lynx', '08h13 m14 .6 s', 'degree59 ′ 30 ″', '11.7'], ['25... |
wobbe index | https://en.wikipedia.org/wiki/Wobbe_index | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1868929-1.html.csv | superlative | the fuel with the highest upper index kcal / nm was n-butane . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '8', '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', 'upper index kcal / nm 3'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; upper index kcal / nm 3 }'}, 'fuel gas'], 'result': 'n - butane', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; upper index kcal / nm 3 } ;... | eq { hop { argmax { all_rows ; upper index kcal / nm 3 } ; fuel gas } ; n - butane } = true | select the row whose upper index kcal / nm 3 record of all rows is maximum . the fuel gas record of this row is n - butane . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'upper index kcal / nm 3_5': 5, 'fuel gas_6': 6, 'n - butane_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'upper index kcal / nm 3_5': 'upper index kcal / nm 3', 'fuel gas_6': 'fuel gas', 'n - butane_7': 'n - butane'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'upper index kcal / nm 3_5': [0], 'fuel gas_6': [1], 'n - butane_7': [2]} | ['fuel gas', 'upper index kcal / nm 3', 'lower index kcal / nm 3', 'upper index mj / nm 3', 'lower index mj / nm 3'] | [['hydrogen', '11528', '9715', '48.23', '40.65'], ['methane', '12735', '11452', '53.28', '47.91'], ['ethane', '16298', '14931', '68.19', '62.47'], ['ethylene', '15253', '14344', '63.82', '60.01'], ['natural gas', '12837', '11597', '53.71', '48.52'], ['propane', '19376', '17817', '81.07', '74.54'], ['propylene', '18413'... |
usa today all - usa high school basketball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11677760-5.html.csv | majority | most of the players participated in the 1987 draft . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1987 draft', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nba draft', '1987 draft'], 'result': True, 'ind': 0, 'tointer': 'for the nba draft records of all rows , most of them fuzzily match to 1987 draft .', 'tostr': 'most_eq { all_rows ; nba draft ; 1987 draft } = true'} | most_eq { all_rows ; nba draft ; 1987 draft } = true | for the nba draft records of all rows , most of them fuzzily match to 1987 draft . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nba draft_3': 3, '1987 draft_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nba draft_3': 'nba draft', '1987 draft_4': '1987 draft'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nba draft_3': [0], '1987 draft_4': [0]} | ['player', 'height', 'school', 'hometown', 'college', 'nba draft'] | [['reggie williams', '6 - 7', 'dunbar high school', 'baltimore , md', 'georgetown', '1st round - 4th pick of 1987 draft ( clippers )'], ['dwayne washington', '6 - 2', 'boys and girls high school', 'brooklyn , ny', 'syracuse', '1st round - 13th pick of 1986 draft ( nets )'], ['dave popson', '6 - 10', "bishop o ' reilly ... |
list of birmingham city f.c. records and statistics | https://en.wikipedia.org/wiki/List_of_Birmingham_City_F.C._records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15702100-2.html.csv | comparative | joe bradford began playing for birmingham city f. c. 50 years before trevor francis . | {'row_1': '1', 'row_2': '2', 'col': '2', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '50 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'joe bradford'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to joe bradford .', 'tostr': 'filter_eq { all_rows ; name ; joe bradford }'}, 'ye... | eq { diff { hop { filter_eq { all_rows ; name ; joe bradford } ; years } ; hop { filter_eq { all_rows ; name ; trevor francis } ; years } } ; -50 years } = true | select the rows whose name record fuzzily matches to joe bradford . take the years record of this row . select the rows whose name record fuzzily matches to trevor francis . take the years record of this row . the second record is 50 years larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'name_8': 8, 'joe bradford_9': 9, 'years_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'name_12': 12, 'trevor francis_13': 13, 'years_14': 14, '-50 years_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'name_8': 'name', 'joe bradford_9': 'joe bradford', 'years_10': 'years', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'name_12': 'n... | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'name_8': [0], 'joe bradford_9': [0], 'years_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'name_12': [1], 'trevor francis_13': [1], 'years_14': [3], '-50 years_15': [5]} | ['name', 'years', 'league a', 'fa cup', 'league cup', 'other b', 'total'] | [['joe bradford', '1920 - 1935', '249 ( 414 )', '18 ( 31 )', '0 ( 0 )', '0 ( 0 )', '267 ( 445 )'], ['trevor francis', '1970 - 1979', '119 ( 280 )', '6 ( 20 )', '4 ( 19 )', '4 ( 10 )', '133 ( 329 )'], ['peter murphy', '1952 - 1960', '107 ( 245 )', '16 ( 24 )', '0 ( 0 )', '4 ( 9 )', '127 ( 278 )'], ['fred wheldon', '1890... |
2008 - 09 dallas mavericks season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Dallas_Mavericks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17288869-9.html.csv | majority | all games of the 2008 - 09 dallas mavericks ' season were scheduled for the month of march . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'march', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'march'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to march .', 'tostr': 'all_eq { all_rows ; date ; march } = true'} | all_eq { all_rows ; date ; march } = true | for the date records of all rows , all of them fuzzily match to march . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'march_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'march_4': 'march'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'march_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 1', 'toronto', 'w 109 - 98 ( ot )', 'dirk nowitzki ( 24 )', 'james singleton ( 16 )', 'jason kidd ( 15 )', 'american airlines center 19688', '36 - 23'], ['60', 'march 2', 'oklahoma city', 'l 87 - 96 ( ot )', 'dirk nowitzki ( 28 )', 'james singleton ( 6 )', 'dirk nowitzki ( 6 )', 'ford center 18527', '36 ... |
1986 icf canoe sprint world championships | https://en.wikipedia.org/wiki/1986_ICF_Canoe_Sprint_World_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18715280-4.html.csv | count | 5 nations competing in the 1986 icf canoe sprint world championships won exactly 2 bronze medals . | {'scope': 'all', 'criterion': 'equal', 'value': '2', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'bronze', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bronze record is equal to 2 .', 'tostr': 'filter_eq { all_rows ; bronze ; 2 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; br... | eq { count { filter_eq { all_rows ; bronze ; 2 } } ; 5 } = true | select the rows whose bronze record is equal to 2 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '2_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', '2_6': '2', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '2_6': [0], '5_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'hungary', '7', '3', '1', '11'], ['2', 'soviet union', '1', '6', '3', '10'], ['3', 'romania', '3', '3', '2', '8'], ['4', 'east germany', '2', '3', '2', '7'], ['5', 'poland', '1', '1', '1', '3'], ['6', 'bulgaria', '1', '0', '2', '3'], ['7', 'west germany', '1', '0', '2', '3'], ['8', 'united kingdom', '2', '0', '0... |
kei nishikori | https://en.wikipedia.org/wiki/Kei_Nishikori | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12299543-2.html.csv | unique | of the finals that kei nishikori participated in , the one on april 10 , 2011 was the only one on a clay surface . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}], 'result': True, 'ind': 1, 'tostr': 'only { fi... | and { only { filter_eq { all_rows ; surface ; clay } } ; eq { hop { filter_eq { all_rows ; surface ; clay } ; date } ; 10 april 2011 } } = true | select the rows whose surface record fuzzily matches to clay . there is only one such row in the table . the date record of this unqiue row is 10 april 2011 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'clay_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '10 april 2011_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'clay_8': 'clay', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '10 april 2011_10': '10 april 2011'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'clay_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '10 april 2011_10': [3]} | ['outcome', 'date', 'surface', 'opponent in the final', 'score in the final'] | [['winner', '11 february 2008', 'hard', 'james blake', '3 - 6 , 6 - 1 , 6 - 4'], ['runner - up', '10 april 2011', 'clay', 'ryan sweeting', '4 - 6 , 6 - 7 ( 3 - 7 )'], ['runner - up', '6 november 2011', 'hard ( i )', 'roger federer', '1 - 6 , 3 - 6'], ['winner', '7 october 2012', 'hard', 'milos raonic', '7 - 6 ( 7 - 5 )... |
list of mountains in norway by prominence | https://en.wikipedia.org/wiki/List_of_mountains_in_Norway_by_prominence | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12280396-1.html.csv | majority | all of the mountains in norway have an elevation that is higher than 1000 meters . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'greater_than', 'value': '1000', 'subset': None} | {'func': 'all_greater', 'args': ['all_rows', 'elevation ( m )', '1000'], 'result': True, 'ind': 0, 'tointer': 'for the elevation ( m ) records of all rows , all of them are greater than 1000 .', 'tostr': 'all_greater { all_rows ; elevation ( m ) ; 1000 } = true'} | all_greater { all_rows ; elevation ( m ) ; 1000 } = true | for the elevation ( m ) records of all rows , all of them are greater than 1000 . | 1 | 1 | {'all_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'elevation (m)_3': 3, '1000_4': 4} | {'all_greater_0': 'all_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'elevation (m)_3': 'elevation ( m )', '1000_4': '1000'} | {'all_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'elevation (m)_3': [0], '1000_4': [0]} | ['peak', 'elevation ( m )', 'prominence ( m )', 'isolation ( km )', 'municipality', 'county'] | [['galdhøpiggen', '2469', '2372', '1570', 'lom', 'oppland'], ['jiehkkevárri', '1833', '1741', '140', 'lyngen , tromsø', 'troms'], ['snøhetta', '2286', '1675', '83', 'dovre', 'oppland'], ['store lenangstind', '1625', '1576', '47', 'lyngen', 'troms'], ['gjegnen / blånibba', '1670', '1460', '47', 'bremanger', 'sogn og fjo... |
no way out ( 2009 ) | https://en.wikipedia.org/wiki/No_Way_Out_%282009%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18438494-3.html.csv | superlative | the match between kane and rey mysterio was the shortest match at no way out 2009 . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2,4', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'wrestler'], 'result': 'kane', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; wrestler }'}, 'kane'], 'result': True... | and { eq { hop { argmin { all_rows ; time } ; wrestler } ; kane } ; eq { hop { argmin { all_rows ; time } ; eliminated by } ; rey mysterio } } = true | select the row whose time record of all rows is minimum . the wrestler record of this row is kane . the eliminated by record of this row is rey mysterio . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_7': 7, 'time_8': 8, 'wrestler_9': 9, 'kane_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'eliminated by_11': 11, 'rey mysterio_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_7': 'all_rows', 'time_8': 'time', 'wrestler_9': 'wrestler', 'kane_10': 'kane', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'eliminated by_11': 'eliminated by', 'rey mysterio_12': 'rey mysterio'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmin_0': [1, 3], 'all_rows_7': [0], 'time_8': [0], 'wrestler_9': [1], 'kane_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'eliminated by_11': [3], 'rey mysterio_12': [4]} | ['eliminated', 'wrestler', 'entered', 'eliminated by', 'method of elimination', 'time'] | [['1', 'kane', '3', 'rey mysterio', 'pinned after a seated senton from the top of a pod', '09:37'], ['2', 'mike knox', '4', 'chris jericho', 'pinned after a codebreaker', '14:42'], ['3', 'cena', '6', 'edge', 'pinned after a spear', '22:22'], ['4', 'jericho', '2', 'rey mysterio', 'pinned when mysterio reversed the walls... |
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