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rail transport in argentina | https://en.wikipedia.org/wiki/Rail_transport_in_Argentina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16456054-2.html.csv | aggregation | the total number of rail stations in argentina is 259 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '259', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'number of stations'], 'result': '259', 'ind': 0, 'tostr': 'sum { all_rows ; number of stations }'}, '259'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; number of stations } ; 259 } = true', 'tointer': 'the sum of the number of stati... | round_eq { sum { all_rows ; number of stations } ; 259 } = true | the sum of the number of stations record of all rows is 259 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'number of stations_4': 4, '259_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'number of stations_4': 'number of stations', '259_5': '259'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'number of stations_4': [0], '259_5': [1]} | ['line', 'operator', 'line length ( kilometres )', 'number of stations', 'annual ridership ( 1998 )', 'annual ridership ( 2008 )'] | [['mitre', 'ugoms', '185 , 5', '55', '84081493', '73207048'], ['belgrano norte', 'ferrovías', '54 , 3', '22', '35931801', '45830200'], ['belgrano sur', 'ugofe', '66 , 3', '30', '16219806', '11472416'], ['roca', 'ugofe', '237 , 2', '70', '152082063', '125556026'], ['san martín', 'ugofe', '56 , 3', '19', '25581310', '466... |
list of singaporean films | https://en.wikipedia.org/wiki/List_of_Singaporean_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1601229-7.html.csv | comparative | the film ' last life in the universe ' grossed more money than the film ' clouds in my coffee ' . | {'row_1': '2', 'row_2': '5', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'last life in the universe'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to last life in the universe .', 'tostr': 'filter_eq { all_rows ; title ; last life in ... | greater { hop { filter_eq { all_rows ; title ; last life in the universe } ; singapore gross } ; hop { filter_eq { all_rows ; title ; clouds in my coffee } ; singapore gross } } = true | select the rows whose title record fuzzily matches to last life in the universe . take the singapore gross record of this row . select the rows whose title record fuzzily matches to clouds in my coffee . take the singapore gross 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, 'title_7': 7, 'last life in the universe_8': 8, 'singapore gross_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'clouds in my coffee_12': 12, 'singapore gross_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', 'title_7': 'title', 'last life in the universe_8': 'last life in the universe', 'singapore gross_9': 'singapore gross', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'last life in the universe_8': [0], 'singapore gross_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'clouds in my coffee_12': [1], 'singapore gross_13': [3]} | ['date', 'title', 'director', 'production cost', 'singapore gross'] | [['2004', '2004', '2004', '2004', '2004'], ['february 2004', 'last life in the universe', 'pen - ek ratanaruang', 'us2000000', '65000'], ['march 2004', 'the eye 2', 'danny pang / oxide pang', 'us3000000', '1577000'], ['june 2004', 'the best bet ( 突然发财 )', 'jack neo', '1500000', '2664000'], ['august 2004', 'clouds in my... |
2008 - 09 lega pro seconda divisione | https://en.wikipedia.org/wiki/2008%E2%80%9309_Lega_Pro_Seconda_Divisione | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17702363-3.html.csv | superlative | the highest capacity for a venue in the 2008-09 lega pro seconda divisione was for stadio san vito . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; capacity }'}, 'stadium'], 'result': 'stadio san vito', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; capacity } ; stadium }'}, 'stadio san vito'], 'result... | eq { hop { argmax { all_rows ; capacity } ; stadium } ; stadio san vito } = true | select the row whose capacity record of all rows is maximum . the stadium record of this row is stadio san vito . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'stadium_6': 6, 'stadio san vito_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'stadium_6': 'stadium', 'stadio san vito_7': 'stadio san vito'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'stadium_6': [1], 'stadio san vito_7': [2]} | ['club', 'city', 'stadium', 'capacity', '200708 season'] | [['as andria bat', 'andria', 'stadio degli ulivi', '10500', '17th in serie c2 / c'], ['sf aversa normanna', 'aversa', 'stadio rinascita', '2000', '1st serie d / h'], ['ss barletta calcio', 'barletta', 'stadio cosimo puttilli', '5000', '2nd serie d / h'], ['ss cassino 1927', 'cassino', 'stadio gino salveti', '3700', '8t... |
athletics at the 1987 pan american games | https://en.wikipedia.org/wiki/Athletics_at_the_1987_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10649319-3.html.csv | aggregation | for athletics at the 1987 pan american games , the teams ranked in the top 3 had a total of 85 medals . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '85', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '3'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'rank', '3'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; rank ; 3 }', 'tointer': 'select the rows whose rank record is less than or equal to 3 .'}, 'total'], 'result': '85', 'ind': 1, 'tostr': 'su... | round_eq { sum { filter_less_eq { all_rows ; rank ; 3 } ; total } ; 85 } = true | select the rows whose rank record is less than or equal to 3 . the sum of the total record of these rows is 85 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'rank_5': 5, '3_6': 6, 'total_7': 7, '85_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '3_6': '3', 'total_7': 'total', '85_8': '85'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '3_6': [0], 'total_7': [1], '85_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states ( usa )', '26', '14', '15', '55'], ['2', 'cuba ( cub )', '6', '9', '8', '23'], ['3', 'mexico ( mex )', '5', '1', '1', '7'], ['4', 'brazil ( bra )', '3', '3', '2', '8'], ['5', 'jamaica ( jam )', '2', '3', '4', '9'], ['6', 'chile ( chi )', '1', '0', '1', '2'], ['7', 'canada ( can )', '0', '7', '3', ... |
2005 jeux de la francophonie | https://en.wikipedia.org/wiki/2005_Jeux_de_la_Francophonie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12402019-5.html.csv | comparative | lebanon won more total medals than the french community of belgium . | {'row_1': '1', 'row_2': '2', 'col': '6', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'lebanon'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to lebanon .', 'tostr': 'filter_eq { all_rows ; nation ; lebanon }'}, 'total'], 'result': None, 'ind': ... | greater { hop { filter_eq { all_rows ; nation ; lebanon } ; total } ; hop { filter_eq { all_rows ; nation ; french community of belgium } ; total } } = true | select the rows whose nation record fuzzily matches to lebanon . take the total record of this row . select the rows whose nation record fuzzily matches to french community of belgium . take the total 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, 'nation_7': 7, 'lebanon_8': 8, 'total_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'french community of belgium_12': 12, 'total_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', 'nation_7': 'nation', 'lebanon_8': 'lebanon', 'total_9': 'total', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'french commu... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'lebanon_8': [0], 'total_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'french community of belgium_12': [1], 'total_13': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'lebanon', '2', '1', '0', '3'], ['2', 'french community of belgium', '1', '0', '1', '2'], ['3', 'benin', '1', '0', '0', '1'], ['3', 'canada', '1', '0', '0', '1'], ['3', 'lithuania', '1', '0', '0', '1'], ['3', 'madagascar', '1', '0', '0', '1'], ['7', 'france', '0', '1', '1', '2'], ['7', 'niger', '0', '1', '1', '2... |
1953 - 54 segunda división | https://en.wikipedia.org/wiki/1953%E2%80%9354_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17416195-2.html.csv | aggregation | the average goals against for all the teams in the segunda division was 53 . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '53', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'goals against'], 'result': '53', 'ind': 0, 'tostr': 'avg { all_rows ; goals against }'}, '53'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; goals against } ; 53 } = true', 'tointer': 'the average of the goals against record of all r... | round_eq { avg { all_rows ; goals against } ; 53 } = true | the average of the goals against record of all rows is 53 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'goals against_4': 4, '53_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'goals against_4': 'goals against', '53_5': '53'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'goals against_4': [0], '53_5': [1]} | ['position', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', '30', '41', '17', '7', '6', '65', '42', '+ 23'], ['2', '30', '38', '17', '4', '9', '56', '36', '+ 20'], ['3', '30', '38', '16', '6', '8', '62', '44', '+ 18'], ['4', '30', '34', '15', '4', '11', '63', '46', '+ 17'], ['5', '30', '33', '12', '9', '9', '62', '48', '+ 14'], ['6', '30', '32', '14', '4', '12', '52', '5... |
1971 african cup of champions clubs | https://en.wikipedia.org/wiki/1971_African_Cup_of_Champions_Clubs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12423174-1.html.csv | comparative | young africans scored more total goals than secteur 6 in the 1971 african cup of champions . | {'row_1': '9', 'row_2': '8', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 1', 'young africans'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team 1 record fuzzily matches to young africans .', 'tostr': 'filter_eq { all_rows ; team 1 ; young africans }'}, 'agg'], 'res... | greater { hop { filter_eq { all_rows ; team 1 ; young africans } ; agg } ; hop { filter_eq { all_rows ; team 1 ; secteur 6 } ; agg } } = true | select the rows whose team 1 record fuzzily matches to young africans . take the agg record of this row . select the rows whose team 1 record fuzzily matches to secteur 6 . take the agg record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team 1_7': 7, 'young africans_8': 8, 'agg_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team 1_11': 11, 'secteur 6_12': 12, 'agg_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team 1_7': 'team 1', 'young africans_8': 'young africans', 'agg_9': 'agg', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team 1_11': 'team 1', 'se... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team 1_7': [0], 'young africans_8': [0], 'agg_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team 1_11': [1], 'secteur 6_12': [1], 'agg_13': [3]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['al - merrikh', '2 - 2 ( 5 - 4 pen )', 'tele sc asmara', '2 - 1', '0 - 1'], ['abaluhya united', '1 - 3', 'great olympics', '0 - 0', '1 - 3'], ['asc diaraf', '3 - 4', 'stade malien', '3 - 0', '0 - 4'], ['maseru united', '3 - 5', 'mmm tamatave', '1 - 2', '2 - 3'], ['as porto novo', '0 - 3', 'victoria club mokanda', '0 ... |
volleyball at the 2004 summer olympics - men 's team rosters | https://en.wikipedia.org/wiki/Volleyball_at_the_2004_Summer_Olympics_%E2%80%93_Men%27s_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15859432-3.html.csv | aggregation | the average weight of the men 's volleyball players at the 2004 sumer olympics was almost 88 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '88', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weight'], 'result': '88', 'ind': 0, 'tostr': 'avg { all_rows ; weight }'}, '88'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weight } ; 88 } = true', 'tointer': 'the average of the weight record of all rows is 88 .'} | round_eq { avg { all_rows ; weight } ; 88 } = true | the average of the weight record of all rows is 88 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weight_4': 4, '88_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weight_4': 'weight', '88_5': '88'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weight_4': [0], '88_5': [1]} | ['name', 'date of birth', 'height', 'weight', 'spike', 'block'] | [['giovane gávio', '07.09.1970', '196', '89', '340', '322'], ['andré heller', '17.12.1975', '199', '93', '339', '321'], ['mauricio lima', '27.01.1968', '184', '79', '321', '304'], ['gilberto godoy filho', '23.12.1976', '192', '85', '325', '312'], ['andré nascimento', '04.03.1979', '195', '95', '340', '320'], ['sérgio d... |
united states house of representatives elections , 1816 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1816 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668347-14.html.csv | count | 2 incumbents were re - elected during the 1816 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're - elected', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re - elected .', 'tostr': 'filter_eq { all_rows ; result ; re - elected }'}], 'result': '2', 'ind': 1,... | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 2 } = true | select the rows whose result record fuzzily matches to re - elected . 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, 'result_5': 5, 're - elected_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', 'result_5': 'result', 're - elected_6': 're - elected', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '2_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['new york 3', 'jonathan ward', 'democratic - republican', '1814', 'retired democratic - republican hold', 'caleb tompkins ( dr ) 56.8 % abraham odell ( f ) 42.8 %'], ['new york 6', 'james w wilkin', 'democratic - republican', '1815 ( special )', 're - elected', 'james w wilkin ( dr ) 55.4 % james burt ( f ) 44.6 %'],... |
1994 - 95 boston bruins season | https://en.wikipedia.org/wiki/1994%E2%80%9395_Boston_Bruins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16189062-8.html.csv | majority | in the majority of the play off games of boston bruins against the new jersey devils in the1994 - 95 season 5 goals were scored . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'new jersey devils', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'visitor', 'new jersey devils'], 'result': True, 'ind': 0, 'tointer': 'for the visitor records of all rows , most of them fuzzily match to new jersey devils .', 'tostr': 'most_eq { all_rows ; visitor ; new jersey devils } = true'} | most_eq { all_rows ; visitor ; new jersey devils } = true | for the visitor records of all rows , most of them fuzzily match to new jersey devils . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'visitor_3': 3, 'new jersey devils_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'visitor_3': 'visitor', 'new jersey devils_4': 'new jersey devils'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'visitor_3': [0], 'new jersey devils_4': [0]} | ['date', 'visitor', 'score', 'home', 'record'] | [['may 7', 'new jersey devils', '5 - 0', 'boston bruins', '0 - 1'], ['may 8', 'new jersey devils', '3 - 0', 'boston bruins', '0 - 2'], ['may 10', 'boston bruins', '3 - 2', 'new jersey devils', '1 - 2'], ['may 12', 'boston bruins', '0 - 1 ( ot )', 'new jersey devils', '1 - 3'], ['may 14', 'new jersey devils', '3 - 2', '... |
6th united states congress | https://en.wikipedia.org/wiki/6th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-224840-4.html.csv | majority | the majority of the 6th united states congress vacators resigned . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'resigned', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'reason for change', 'resigned'], 'result': True, 'ind': 0, 'tointer': 'for the reason for change records of all rows , most of them fuzzily match to resigned .', 'tostr': 'most_eq { all_rows ; reason for change ; resigned } = true'} | most_eq { all_rows ; reason for change ; resigned } = true | for the reason for change records of all rows , most of them fuzzily match to resigned . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'reason for change_3': 3, 'resigned_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'reason for change_3': 'reason for change', 'resigned_4': 'resigned'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'reason for change_3': [0], 'resigned_4': [0]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['new york 1st', 'jonathan havens ( dr )', 'died october 25 , 1799', 'john smith ( dr )', 'february 27 , 1800'], ['connecticut at - large', 'jonathan brace ( f )', 'resigned sometime in 1800', 'john cotton smith ( f )', 'november 17 , 1800'], ['virginia 13th', 'john marshall ( f )', 'resigned june 7 , 1800 to become s... |
phoenix suns all - time roster | https://en.wikipedia.org/wiki/Phoenix_Suns_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482079-2.html.csv | unique | dennis awtrey is the only player on the phoenix suns to come from santa clara . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'santa clara', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / country', 'santa clara'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / country record fuzzily matches to santa clara .', 'tostr': 'filter_eq { all_rows ; school / country ; santa clara }'}... | and { only { filter_eq { all_rows ; school / country ; santa clara } } ; eq { hop { filter_eq { all_rows ; school / country ; santa clara } ; player } ; dennis awtrey } } = true | select the rows whose school / country record fuzzily matches to santa clara . there is only one such row in the table . the player record of this unqiue row is dennis awtrey . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / country_7': 7, 'santa clara_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'dennis awtrey_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / country_7': 'school / country', 'santa clara_8': 'santa clara', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'dennis awtrey_10': 'dennis awtrey'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / country_7': [0], 'santa clara_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'dennis awtrey_10': [3]} | ['player', 'pos', 'from', 'school / country', 'rebs', 'asts'] | [['alvan adams', 'c / f', '1975', 'oklahoma', '6937', '4012'], ['rafael addison', 'g / f', '1986', 'syracuse', '106', '45'], ['danny ainge', 'sg', '1992', 'byu', '454', '650'], ['louis amundson', 'pf', '2008', 'unlv', '616', '59'], ['robert archibald', 'f / c', '2003', 'illinois', '1', '1'], ['dennis awtrey', 'c', '197... |
1965 american football league draft | https://en.wikipedia.org/wiki/1965_American_Football_League_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-11.html.csv | count | two defensive backs were picked in the draft from picks 81-88 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'defensive back', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defensive back'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to defensive back .', 'tostr': 'filter_eq { all_rows ; position ; defensive back }'}], 'result': '2... | eq { count { filter_eq { all_rows ; position ; defensive back } } ; 2 } = true | select the rows whose position record fuzzily matches to defensive back . 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, 'defensive back_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', 'defensive back_6': 'defensive back', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'defensive back_6': [0], '2_7': [2]} | ['pick', 'team', 'player', 'position', 'college'] | [['81', 'denver broncos', 'tom vaughn', 'defensive back', 'iowa state'], ['82', 'houston oilers', 'kent mccloughan', 'cornerback', 'nebraska'], ['83', 'oakland raiders', 'bill minor', 'linebacker', 'illinois'], ['84', 'new york jets', 'jim gray', 'defensive back', 'toledo'], ['85', 'kansas city chiefs', 'al piraino', '... |
united states national rugby union team | https://en.wikipedia.org/wiki/United_States_national_rugby_union_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1145226-8.html.csv | count | 2 players on the united states national rugby union team used the san francisco venue . | {'scope': 'all', 'criterion': 'equal', 'value': 'san francisco', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'san francisco'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to san francisco .', 'tostr': 'filter_eq { all_rows ; venue ; san francisco }'}], 'result': '2', 'ind': 1,... | eq { count { filter_eq { all_rows ; venue ; san francisco } } ; 2 } = true | select the rows whose venue record fuzzily matches to san francisco . 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, 'san francisco_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', 'san francisco_6': 'san francisco', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'san francisco_6': [0], '2_7': [2]} | ['player', 'tries', 'conv', 'venue', 'date'] | [['dick hyland', '4', '0', 'colombes', '11 / 05 / 1924'], ['vaea anitoni', '4', '0', 'san francisco', '06 / 07 / 1996'], ['brian hightower', '4', '0', 'san francisco', '07 / 06 / 1997'], ['vaea anitoni', '4', '0', 'lisbon', '08 / 04 / 1998'], ['7 players on 3 tries', '7 players on 3 tries', '7 players on 3 tries', '7 p... |
1944 vfl season | https://en.wikipedia.org/wiki/1944_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809142-18.html.csv | comparative | in the 1944 vfl season , the crowd for the game at punt road oval was 4000 less than the crowed at kardinia park . | {'row_1': '5', 'row_2': '6', 'col': '6', 'col_other': '5', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '4000', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'punt road oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to punt road oval .', 'tostr': 'filter_eq { all_rows ; venue ; punt road oval... | eq { diff { hop { filter_eq { all_rows ; venue ; punt road oval } ; crowd } ; hop { filter_eq { all_rows ; venue ; kardinia park } ; crowd } } ; -4000 } = true | select the rows whose venue record fuzzily matches to punt road oval . take the crowd record of this row . select the rows whose venue record fuzzily matches to kardinia park . take the crowd record of this row . the second record is 4000 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'venue_8': 8, 'punt road oval_9': 9, 'crowd_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'venue_12': 12, 'kardinia park_13': 13, 'crowd_14': 14, '-4000_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'venue_8': 'venue', 'punt road oval_9': 'punt road oval', 'crowd_10': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'venue_12': 've... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'venue_8': [0], 'punt road oval_9': [0], 'crowd_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'venue_12': [1], 'kardinia park_13': [1], 'crowd_14': [3], '-4000_15': [5]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '17.24 ( 126 )', 'south melbourne', '6.8 ( 44 )', 'windy hill', '11000', '2 september 1944'], ['collingwood', '10.8 ( 68 )', 'richmond', '15.18 ( 108 )', 'victoria park', '14000', '2 september 1944'], ['carlton', '13.10 ( 88 )', 'footscray', '12.17 ( 89 )', 'princes park', '34000', '2 september 1944'], ['... |
list of list a cricket records | https://en.wikipedia.org/wiki/List_of_List_A_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11303072-9.html.csv | ordinal | considering the list a cricket records of most dismissals in career , the player adam gilchrist has the second highest number of catches . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'catches', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; catches ; 2 }'}, 'player'], 'result': 'adam gilchrist', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; catches ; 2 } ; player }'}, 'adam gi... | eq { hop { nth_argmax { all_rows ; catches ; 2 } ; player } ; adam gilchrist } = true | select the row whose catches record of all rows is 2nd maximum . the player record of this row is adam gilchrist . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'catches_5': 5, '2_6': 6, 'player_7': 7, 'adam gilchrist_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', 'catches_5': 'catches', '2_6': '2', 'player_7': 'player', 'adam gilchrist_8': 'adam gilchrist'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'catches_5': [0], '2_6': [0], 'player_7': [1], 'adam gilchrist_8': [2]} | ['rank', 'dismissals', 'player', 'nationality', 'catches', 'stumpings', 'career span'] | [['1', '661', 'steve rhodes', 'england', '532', '129', '1984 - 2004'], ['2', '591', 'adam gilchrist', 'australia', '526', '65', '1992 - 2010'], ['3', '563', 'jack russell', 'england', '465', '98', '1982 - 2004'], ['4', '541', 'kumar sangakkara', 'sri lanka', '435', '106', '1997 -'], ['5', '527', 'warren hegg', 'england... |
australia fed cup team | https://en.wikipedia.org/wiki/Australia_Fed_Cup_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11233323-12.html.csv | ordinal | the australian fed cup team had the best play on carpet with a 1-0 record . | {'row': '3', 'col': '5', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'carpet', '1'], 'result': '1 - 0', 'ind': 0, 'tostr': 'nth_max { all_rows ; carpet ; 1 }', 'tointer': 'the 1st maximum carpet record of all rows is 1 - 0 .'}, '1 - 0'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; carpet ; 1 } ; 1 - 0 } =... | eq { nth_max { all_rows ; carpet ; 1 } ; 1 - 0 } = true | the 1st maximum carpet record of all rows is 1 - 0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_max_0': 0, 'all_rows_3': 3, 'carpet_4': 4, '1_5': 5, '1 - 0_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_max_0': 'nth_max', 'all_rows_3': 'all_rows', 'carpet_4': 'carpet', '1_5': '1', '1 - 0_6': '1 - 0'} | {'eq_1': [2], 'result_2': [], 'nth_max_0': [1], 'all_rows_3': [0], 'carpet_4': [0], '1_5': [0], '1 - 0_6': [1]} | ['record', 'hard', 'clay', 'grass', 'carpet'] | [['2 - 0', '0 - 0', '1 - 0', '1 - 0', '0 - 0'], ['2 - 0', '2 - 0', '0 - 0', '0 - 0', '0 - 0'], ['2 - 0', '1 - 0', '0 - 0', '0 - 0', '1 - 0'], ['2 - 0', '0 - 0', '2 - 0', '0 - 0', '0 - 0'], ['2 - 1', '1 - 1', '1 - 0', '0 - 0', '0 - 0'], ['2 - 3', '0 - 0', '1 - 3', '1 - 0', '0 - 0'], ['1 - 0', '1 - 0', '0 - 0', '0 - 0', ... |
1983 world judo championships | https://en.wikipedia.org/wiki/1983_World_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15807776-2.html.csv | comparative | the united states and poland both did not receive any gold or silver medals and only one bronze medal each . | {'row_1': '13', 'row_2': '14', 'col': '5', 'col_other': '2', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; nation ; united states ... | and { eq { hop { filter_eq { all_rows ; nation ; united states } ; bronze } ; hop { filter_eq { all_rows ; nation ; poland } ; bronze } } ; and { eq { hop { filter_eq { all_rows ; nation ; united states } ; bronze } ; 1 } ; eq { hop { filter_eq { all_rows ; nation ; poland } ; bronze } ; 1 } } } = true | select the rows whose nation record fuzzily matches to united states . take the bronze record of this row . select the rows whose nation record fuzzily matches to poland . take the bronze record of this row . the first record is equal to the second record . the bronze record of the first row is 1 . the bronze record of... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'eq_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'nation_11': 11, 'united states_12': 12, 'bronze_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'nation_15': 15, 'poland_16': 16, 'bronze_17': 17, 'and_7': 7, 'eq_5': 5, '1_18': 18, 'eq_6': 6, '1_19': 19} | {'and_8': 'and', 'result_9': 'true', 'eq_4': 'eq', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'united states_12': 'united states', 'bronze_13': 'bronze', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'nation_15':... | {'and_8': [9], 'result_9': [], 'eq_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'nation_11': [0], 'united states_12': [0], 'bronze_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'nation_15': [1], 'poland_16': [1], 'bronze_17': [3], 'and_7': [8], 'eq_5': [7], '1_1... | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'japan', '4', '1', '2', '7'], ['2', 'soviet union', '2', '1', '2', '5'], ['3', 'east germany', '2', '0', '2', '4'], ['4', 'italy', '0', '1', '1', '2'], ['4', 'hungary', '0', '1', '1', '2'], ['6', 'france', '0', '1', '0', '1'], ['6', 'czech republic', '0', '1', '0', '1'], ['6', 'great britain', '0', '1', '0', '1'... |
zhang chunhui | https://en.wikipedia.org/wiki/Zhang_Chunhui | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11409274-2.html.csv | count | of the competitions zhang chunhui participated in , four of them were in hong kong . | {'scope': 'all', 'criterion': 'equal', 'value': 'hong kong', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'hong kong'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to hong kong .', 'tostr': 'filter_eq { all_rows ; venue ; hong kong }'}], 'result': '4', 'ind': 1, 'tostr': 'c... | eq { count { filter_eq { all_rows ; venue ; hong kong } } ; 4 } = true | select the rows whose venue record fuzzily matches to hong kong . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'hong kong_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'hong kong_6': 'hong kong', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'hong kong_6': [0], '4_7': [2]} | ['date', 'venue', 'result', 'goals', 'competition'] | [['14 january 2009', 'hong kong stadium , hong kong', '2 - 1', '0', 'friendly'], ['21 january 2009', 'hong kong stadium , hong kong', '1 - 3', '0', '2011 afc asian cup qualification'], ['28 january 2009', "ali muhesen stadium , sana'a , yemen", '0 - 1', '0', '2011 afc asian cup qualification'], ['27 august 2009', 'worl... |
ingo schultz | https://en.wikipedia.org/wiki/Ingo_Schultz | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15186827-1.html.csv | count | ingo schultz had most of his success in 2002 , placing four times that year . | {'scope': 'all', 'criterion': 'equal', 'value': '2002', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2002'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2002 .', 'tostr': 'filter_eq { all_rows ; year ; 2002 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ;... | eq { count { filter_eq { all_rows ; year ; 2002 } } ; 4 } = true | select the rows whose year record is equal to 2002 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '2002_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '2002_6': '2002', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '2002_6': [0], '4_7': [2]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['2000', 'european indoor championships', 'ghent , belgium', '2nd', '4x400 m relay'], ['2001', 'world championships', 'edmonton , canada', '2nd', '400 m'], ['2002', 'european championships', 'munich , germany', '1st', '400 m'], ['2002', 'european championships', 'munich , germany', '7th', '4x400 m relay'], ['2002', 'w... |
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/2-17323042-7.html.csv | majority | all games of the philadelphia 76ers ' in the 2008 - 09 season were played in the month of january . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'january', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'january'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to january .', 'tostr': 'all_eq { all_rows ; date ; january } = true'} | all_eq { all_rows ; date ; january } = true | for the date records of all rows , all of them fuzzily match to january . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'january_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'january_4': 'january'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'january_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['32', 'january 2', 'dallas', 'l 86 - 96 ( ot )', 'andre iguodala ( 22 )', 'andre miller ( 11 )', 'andre iguodala ( 5 )', 'american airlines center 20327', '13 - 19'], ['33', 'january 3', 'san antonio', 'l 106 - 108 ( ot )', 'andre miller ( 28 )', 'andre iguodala ( 8 )', 'andre iguodala ( 8 )', 'at & t center 18797', ... |
1963 baltimore colts season | https://en.wikipedia.org/wiki/1963_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14984103-1.html.csv | unique | the colts only score 40 or more points 1 time during the season . | {'scope': 'all', 'row': '13', 'col': '4', 'col_other': 'n/a', 'criterion': 'greater_than', 'value': '40', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'result', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record is greater than 40 .', 'tostr': 'filter_greater { all_rows ; result ; 40 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; resul... | only { filter_greater { all_rows ; result ; 40 } } = true | select the rows whose result record is greater than 40 . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'result_4': 4, '40_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'result_4': 'result', '40_5': '40'} | {'only_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'result_4': [0], '40_5': [0]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 15 , 1963', 'new york giants', 'l 28 - 37', '0 - 1', 'memorial stadium', '60029'], ['2', 'september 22 , 1963', 'san francisco 49ers', 'w 20 - 14', '1 - 1', 'kezar stadium', '31006'], ['3', 'september 29 , 1963', 'green bay packers', 'l 20 - 31', '1 - 2', 'lambeau field', '42327'], ['4', 'october 6 , ... |
1951 - 52 segunda división | https://en.wikipedia.org/wiki/1951%E2%80%9352_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17298923-2.html.csv | aggregation | the clubs in the 1951 - 52 segunda división recorded a combined total of 812 goals for . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '812', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'goals for'], 'result': '812', 'ind': 0, 'tostr': 'sum { all_rows ; goals for }'}, '812'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; goals for } ; 812 } = true', 'tointer': 'the sum of the goals for record of all rows is 812 .'} | round_eq { sum { all_rows ; goals for } ; 812 } = true | the sum of the goals for record of all rows is 812 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'goals for_4': 4, '812_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'goals for_4': 'goals for', '812_5': '812'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'goals for_4': [0], '812_5': [1]} | ['position', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', '30', '39', '16', '7', '7', '66', '29', '+ 37'], ['2', '30', '36', '15', '6', '9', '48', '40', '+ 8'], ['3', '30', '33', '11', '11', '8', '55', '44', '+ 11'], ['4', '30', '33', '13', '7', '10', '58', '44', '+ 14'], ['5', '30', '33', '13', '7', '10', '61', '32', '+ 29'], ['6', '30', '33', '12', '9', '9', '49', '4... |
1983 - 84 liverpool f.c. season | https://en.wikipedia.org/wiki/1983%E2%80%9384_Liverpool_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18269885-4.html.csv | count | in the 1983 - 84 liverpool f.c. season , among the games played against fulham , 2 of them had result 1-1 . | {'scope': 'subset', 'criterion': 'equal', 'value': '1-1', 'result': '2', 'col': '4', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'fulham'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponents', 'fulham'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponents ; fulham }', 'tointer': 'select the rows whose opponents record fuzzily matches to fulham .'},... | eq { count { filter_eq { filter_eq { all_rows ; opponents ; fulham } ; result ; 1-1 } } ; 2 } = true | select the rows whose opponents record fuzzily matches to fulham . among these rows , select the rows whose result record fuzzily matches to 1-1 . 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, 'opponents_6': 6, 'fulham_7': 7, 'result_8': 8, '1-1_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', 'opponents_6': 'opponents', 'fulham_7': 'fulham', 'result_8': 'result', '1-1_9': '1-1', '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], 'opponents_6': [0], 'fulham_7': [0], 'result_8': [1], '1-1_9': [1], '2_10': [3]} | ['date', 'opponents', 'venue', 'result', 'attendance', 'report 1'] | [['05 - oct - 83', 'brentford', 'a', '4 - 1', '17859', 'report'], ['25 - oct - 83', 'brentford', 'h', '4 - 0', '9902', 'report'], ['08 - nov - 83', 'fulham', 'a', '1 - 1', '20142', 'report'], ['22 - nov - 83', 'fulham', 'h', '1 - 1', '15783', 'report'], ['29 - nov - 83', 'fulham', 'a', '1 - 0', '20905', 'report'], ['20... |
2008 - 09 washington wizards season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Washington_Wizards_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17311812-7.html.csv | majority | caron butler recorded the majority of high assists performances in the 2008 - 09 washington wizards season . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'caron butler', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high assists', 'caron butler'], 'result': True, 'ind': 0, 'tointer': 'for the high assists records of all rows , most of them fuzzily match to caron butler .', 'tostr': 'most_eq { all_rows ; high assists ; caron butler } = true'} | most_eq { all_rows ; high assists ; caron butler } = true | for the high assists records of all rows , most of them fuzzily match to caron butler . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high assists_3': 3, 'caron butler_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high assists_3': 'high assists', 'caron butler_4': 'caron butler'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high assists_3': [0], 'caron butler_4': [0]} | ['game', 'date', 'team', 'score', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['31', 'january 2', 'boston', 'l 83 - 108 ( ot )', 'antawn jamison ( 9 )', 'caron butler ( 5 )', 'td banknorth garden 18624', '6 - 25'], ['32', 'january 4', 'cleveland', 'w 80 - 77 ( ot )', 'antawn jamison ( 13 )', 'andray blatche ( 4 )', 'verizon center 20173', '7 - 25'], ['33', 'january 6', 'orlando', 'l 80 - 89 ( o... |
2000 belarusian premier league | https://en.wikipedia.org/wiki/2000_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14747235-1.html.csv | comparative | more people can fit in the stadium in minsk than the stadium that is located in lida . | {'row_1': '10', 'row_2': '13', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'minsk'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to minsk .', 'tostr': 'filter_eq { all_rows ; location ; minsk }'}, 'capacity'], 'result': None, 'ind... | greater { hop { filter_eq { all_rows ; location ; minsk } ; capacity } ; hop { filter_eq { all_rows ; location ; lida } ; capacity } } = true | select the rows whose location record fuzzily matches to minsk . take the capacity record of this row . select the rows whose location record fuzzily matches to lida . take the capacity 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, 'location_7': 7, 'minsk_8': 8, 'capacity_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'location_11': 11, 'lida_12': 12, 'capacity_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', 'location_7': 'location', 'minsk_8': 'minsk', 'capacity_9': 'capacity', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'location_11': 'location', 'li... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'location_7': [0], 'minsk_8': [0], 'capacity_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'location_11': [1], 'lida_12': [1], 'capacity_13': [3]} | ['team', 'location', 'venue', 'capacity', 'position in 1999'] | [['bate', 'borisov', 'city stadium , borisov', '5500', '1'], ['slavia', 'mozyr', 'yunost , mozyr', '5500', '2'], ['gomel', 'gomel', 'central , gomel', '11800', '3'], ['dnepr - transmash', 'mogilev', 'spartak , mogilev', '11200', '4'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '5'], ['dinamo minsk', 'minsk', 'dinam... |
naia independent football schools | https://en.wikipedia.org/wiki/NAIA_independent_football_schools | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15617076-1.html.csv | comparative | webber international university was founded several decades earlier than ave maria university . | {'row_1': '11', 'row_2': '1', 'col': '3', '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', 'institution', 'webber international university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to webber international university .', 'tostr': 'filter_eq { all_rows ; ... | less { hop { filter_eq { all_rows ; institution ; webber international university } ; founded } ; hop { filter_eq { all_rows ; institution ; ave maria university } ; founded } } = true | select the rows whose institution record fuzzily matches to webber international university . take the founded record of this row . select the rows whose institution record fuzzily matches to ave maria university . take the founded 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, 'institution_7': 7, 'webber international university_8': 8, 'founded_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'institution_11': 11, 'ave maria university_12': 12, 'founded_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', 'institution_7': 'institution', 'webber international university_8': 'webber international university', 'founded_9': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_ro... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'institution_7': [0], 'webber international university_8': [0], 'founded_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'institution_11': [1], 'ave maria university_12': [1], 'founded_13': [3]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'team', 'primary conference'] | [['ave maria university', 'ave maria , florida', '1998', 'private', '1200', 'gyrenes', 'the sun'], ['dakota state university', 'madison , south dakota', '1881', 'public', '3102', 'trojans', 'none'], ['edward waters college', 'jacksonville , florida', '1866', 'private', '800', 'tigers', 'gulf coast ( gcac )'], ['haskell... |
1998 icc knockout trophy | https://en.wikipedia.org/wiki/1998_ICC_KnockOut_Trophy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11950720-1.html.csv | unique | michael bevan was the only player with a left arm slow chinaman bowling style . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'left arm slow chinaman', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'bowling style', 'left arm slow chinaman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bowling style record fuzzily matches to left arm slow chinaman .', 'tostr': 'filter_eq { all_rows ; bowling style ; le... | and { only { filter_eq { all_rows ; bowling style ; left arm slow chinaman } } ; eq { hop { filter_eq { all_rows ; bowling style ; left arm slow chinaman } ; player } ; michael bevan } } = true | select the rows whose bowling style record fuzzily matches to left arm slow chinaman . there is only one such row in the table . the player record of this unqiue row is michael bevan . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'bowling style_7': 7, 'left arm slow chinaman_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'michael bevan_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'bowling style_7': 'bowling style', 'left arm slow chinaman_8': 'left arm slow chinaman', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'michael bevan_10': 'michael bevan'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'bowling style_7': [0], 'left arm slow chinaman_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'michael bevan_10': [3]} | ['player', 'date of birth', 'batting style', 'bowling style', 'first class team'] | [['steve waugh ( captain )', '2 june 1965', 'right hand bat', 'right arm medium', 'new south wales'], ['mark waugh ( vice - captain )', '2 june 1965', 'right hand bat', 'right arm medium right arm off break', 'new south wales'], ['michael bevan', '8 may 1970', 'left hand bat', 'left arm slow chinaman', 'new south wales... |
hughes hall college boat club | https://en.wikipedia.org/wiki/Hughes_Hall_College_Boat_Club | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18880596-2.html.csv | comparative | the hughes hall college boat club finished two positions better in 2009 than in 2008 . | {'row_1': '2', 'row_2': '1', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2009'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 2009 .', 'tostr': 'filter_eq { all_rows ; year ; 2009 }'}, 'finish position'], 'resul... | and { less { hop { filter_eq { all_rows ; year ; 2009 } ; finish position } ; hop { filter_eq { all_rows ; year ; 2008 } ; finish position } } ; and { eq { hop { filter_eq { all_rows ; year ; 2009 } ; finish position } ; 31st } ; eq { hop { filter_eq { all_rows ; year ; 2008 } ; finish position } ; 33rd } } } = true | select the rows whose year record fuzzily matches to 2009 . take the finish position record of this row . select the rows whose year record fuzzily matches to 2008 . take the finish position record of this row . the first record is less than the second record . the finish position record of the first row is 31st . the ... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'year_11': 11, '2009_12': 12, 'finish position_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'year_15': 15, '2008_16': 16, 'finish position_17': 17, 'and_7': 7, 'str_eq_5': 5, '31st_18': 18, 'str_eq_6':... | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '2009_12': '2009', 'finish position_13': 'finish position', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'year_15': '... | {'and_8': [9], 'result_9': [], 'less_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'year_11': [0], '2009_12': [0], 'finish position_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'year_15': [1], '2008_16': [1], 'finish position_17': [3], 'and_7': [8], 'str_eq_5': ... | ['year', 'finish position', '1st day', '2nd day', '3rd day', '4th day'] | [['2008', '33rd', 'bumped corpus christi / newnham', 'rowed - over', 'rowed - over', 'bumped wolfson'], ['2009', '31st', "bumped st edmund 's", 'rowed - over', 'bumped darwin', 'rowed - over'], ['2010', '31st', 'bumped by corpus christi', 'rowed - over', 'bumped caius', 'rowed - over'], ['2011', '27th', 'bumped anglia ... |
vivian girls | https://en.wikipedia.org/wiki/Vivian_Girls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18710512-3.html.csv | aggregation | the singles of the group vivian girls sold an average of 2250 copies per single . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '2250', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'other details'], 'result': '2250', 'ind': 0, 'tostr': 'avg { all_rows ; other details }'}, '2250'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; other details } ; 2250 } = true', 'tointer': 'the average of the other details record of... | round_eq { avg { all_rows ; other details } ; 2250 } = true | the average of the other details record of all rows is 2250 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'other details_4': 4, '2250_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'other details_4': 'other details', '2250_5': '2250'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'other details_4': [0], '2250_5': [1]} | ['date', 'single', 'backed with', 'record label', 'format', 'other details'] | [['2008', 'wild eyes', 'my baby wants me dead', 'plays with dolls / wild world', '7 single', '4000 copies'], ['2008', 'tell the world', 'i believe in nothing & damaged', 'woodsist', '7 single', '3000 copies'], ['2008', "i ca n't stay", 'blind spot', 'in the red', '7 single', '2000 copies'], ['2008', 'surfin away & seco... |
list of leverage episodes | https://en.wikipedia.org/wiki/List_of_Leverage_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20704243-3.html.csv | count | 2 episodes of the series leverage both had 3.69 us viewers in millions . | {'scope': 'all', 'criterion': 'equal', 'value': '3.69', 'result': '2', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'us viewers ( in millions )', '3.69'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( in millions ) record is equal to 3.69 .', 'tostr': 'filter_eq { all_rows ; us viewers ( in millions ) ; 3.69 }'}],... | eq { count { filter_eq { all_rows ; us viewers ( in millions ) ; 3.69 } } ; 2 } = true | select the rows whose us viewers ( in millions ) record is equal to 3.69 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'us viewers (in millions)_5': 5, '3.69_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'us viewers (in millions)_5': 'us viewers ( in millions )', '3.69_6': '3.69', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'us viewers (in millions)_5': [0], '3.69_6': [0], '2_7': [2]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( in millions )'] | [['14', '1', 'the beantown bailout job', 'dean devlin', 'john rogers', 'july 15 , 2009', '3.89'], ['15', '2', 'the tap - out job', 'marc roskin', 'albert kim', 'july 22 , 2009', '3.05'], ['16', '3', 'the order 23 job', 'rod hardy', 'chris downey', 'july 29 , 2009', '3.68'], ['17', '4', 'the fairy godparents job', 'jona... |
2007 - 08 san antonio spurs season | https://en.wikipedia.org/wiki/2007%E2%80%9308_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963601-6.html.csv | count | in the 2007 - 08 san antonio spurs season , among the games where spurs were visitors , 3 of them had attendance below 18,000 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '18000', 'result': '3', 'col': '6', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'spurs'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'spurs'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; visitor ; spurs }', 'tointer': 'select the rows whose visitor record fuzzily matches to spurs .'}, 'attendanc... | eq { count { filter_less { filter_eq { all_rows ; visitor ; spurs } ; attendance ; 18000 } } ; 3 } = true | select the rows whose visitor record fuzzily matches to spurs . among these rows , select the rows whose attendance record is less than 18000 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'visitor_6': 6, 'spurs_7': 7, 'attendance_8': 8, '18000_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'visitor_6': 'visitor', 'spurs_7': 'spurs', 'attendance_8': 'attendance', '18000_9': '18000', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'visitor_6': [0], 'spurs_7': [0], 'attendance_8': [1], '18000_9': [1], '3_10': [3]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['january 3 , 2008', 'spurs', '77 - 80', 'nuggets', 'two - way tie ( 20 )', '19155', '21 - 9'], ['january 4 , 2008', 'knicks', '93 - 97', 'spurs', 'bruce bowen ( 15 )', '18797', '22 - 9'], ['january 6 , 2008', 'spurs', '88 - 82', 'clippers', 'tony parker ( 26 )', '16623', '23 - 9'], ['january 7 , 2008', 'spurs', '121 ... |
water resources management in chile | https://en.wikipedia.org/wiki/Water_resources_management_in_Chile | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22854436-1.html.csv | ordinal | in the water resources management in chile , i - tarapacá is the administrative region with the highest average annual runoff ( mm ) among those with average annual rainfall ( mm ) less than 100 . | {'scope': 'subset', 'row': '1', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'less_than', 'value': '100'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'average annual rainfall ( mm )', '100'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; average annual rainfall ( mm ) ; 100 }', 'tointer': 'select the rows whose average ... | eq { hop { nth_argmax { filter_less { all_rows ; average annual rainfall ( mm ) ; 100 } ; average annual runoff ( mm ) ; 1 } ; administrative region } ; i - tarapacá } = true | select the rows whose average annual rainfall ( mm ) record is less than 100 . select the row whose average annual runoff ( mm ) record of these rows is 1st maximum . the administrative region record of this row is i - tarapacá . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'average annual rainfall (mm)_6': 6, '100_7': 7, 'average annual runoff (mm)_8': 8, '1_9': 9, 'administrative region_10': 10, 'i - tarapacá_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'average annual rainfall (mm)_6': 'average annual rainfall ( mm )', '100_7': '100', 'average annual runoff (mm)_8': 'average annual runoff ( mm )', '1_9': '1', 'admi... | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'average annual rainfall (mm)_6': [0], '100_7': [0], 'average annual runoff (mm)_8': [1], '1_9': [1], 'administrative region_10': [2], 'i - tarapacá_11': [3]} | ['administrative region', 'population ( 2002 census data )', 'surface km 2', 'main rivers', 'average annual rainfall ( mm )', 'average annual runoff ( mm )', 'per capita average annual renewable water resources m 3'] | [['i - tarapacá', '428594', '58698', 'azapa river , vítor river and camarones river', '93.6', '7.1', '972'], ['ii - antofagasta', '493984', '126444', 'loa river', '44.5', '0.2', '51'], ['iii - atacama', '254336', '75573', 'salado river', '82.4', '0.7', '208'], ['iv - coquimbo', '603210', '40656', 'elqui river , choapa ... |
1975 vfl season | https://en.wikipedia.org/wiki/1975_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10883333-3.html.csv | ordinal | princes park venue recorded the 2nd highest crowd participation during the 1975 vfl season . | {'row': '3', 'col': '6', 'order': '2', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'venue'], 'result': 'princes park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; venue }'}, 'princes park'], '... | eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; princes park } = true | select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is princes park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'venue_7': 7, 'princes park_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '2_6': '2', 'venue_7': 'venue', 'princes park_8': 'princes park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'venue_7': [1], 'princes park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '11.21 ( 87 )', 'south melbourne', '9.17 ( 71 )', 'moorabbin oval', '15736', '19 april 1975'], ['essendon', '16.21 ( 117 )', 'melbourne', '15.10 ( 100 )', 'windy hill', '22824', '19 april 1975'], ['carlton', '14.18 ( 102 )', 'north melbourne', '9.12 ( 66 )', 'princes park', '23824', '19 april 1975'], ['ge... |
2008 armenian cup | https://en.wikipedia.org/wiki/2008_Armenian_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17372848-1.html.csv | unique | the 1st leg match between mika and ararat-2 was the only match to end in a 7-0 score in the 2008 armenian cup . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '1,3', 'criterion': 'equal', 'value': '7 - 0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st leg', '7 - 0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1st leg record fuzzily matches to 7 - 0 .', 'tostr': 'filter_eq { all_rows ; 1st leg ; 7 - 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; 1st leg ; 7 - 0 } } ; and { eq { hop { filter_eq { all_rows ; 1st leg ; 7 - 0 } ; team 1 } ; mika } ; eq { hop { filter_eq { all_rows ; 1st leg ; 7 - 0 } ; team 2 } ; ararat - 2 } } } = true | select the rows whose 1st leg record fuzzily matches to 7 - 0 . there is only one such row in the table . the team 1 record of this unqiue row is mika . the team 2 record of this unqiue row is ararat - 2 . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, '1st leg_10': 10, '7 - 0_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'team 1_12': 12, 'mika_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'team 2_14': 14, 'ararat - 2_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', '1st leg_10': '1st leg', '7 - 0_11': '7 - 0', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team 1_12': 'team 1', 'mika_13': 'mika', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'team 2... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], '1st leg_10': [0], '7 - 0_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'team 1_12': [2], 'mika_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'team 2_14': [4], 'ararat - 2_15': [5]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['banants - 2', '2 - 6', 'ulisses', '1 - 4', '1 - 2'], ['pyunik', '15 - 2', 'patani', '11 - 2', '4 - 0'], ['gandzasar', '8 - 0', 'pyunik - 2', '3 - 0', '5 - 0'], ['kilikia', '5 - 2', 'mika - 2', '2 - 0', '3 - 2'], ['mika', '11 - 0', 'ararat - 2', '7 - 0', '4 - 0'], ['shengavit', '2 - 3', 'shirak', '1 - 3', '1 - 0']] |
1963 - 64 segunda división | https://en.wikipedia.org/wiki/1963%E2%80%9364_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17740819-4.html.csv | majority | all clubs which participated in the 1963 - 64 segunda división season games each played 30 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '30', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '30'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 30 .', 'tostr': 'all_eq { all_rows ; played ; 30 } = true'} | all_eq { all_rows ; played ; 30 } = true | for the played records of all rows , all of them are equal to 30 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '30_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '30_4': '30'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '30_4': [0]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'ud las palmas', '30', '40', '17', '6', '7', '45', '25', '+ 20'], ['2', 'hércules cf', '30', '38', '15', '8', '7', '48', '38', '+ 10'], ['3', 'rcd mallorca', '30', '37', '16', '5', '9', '52', '32', '+ 20'], ['4', 'cd mestalla', '30', '33', '13', '7', '10', '60', '38', '+ 22'], ['5', 'cd tenerife', '30', '32', '1... |
b.g. discography | https://en.wikipedia.org/wiki/B.G._discography | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18519524-3.html.csv | count | b.g. discography had two us hot 100 songs from 1999 to 2010 . | {'scope': 'all', 'criterion': 'not_equal', 'value': '-', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_not_eq', 'args': ['all_rows', 'us hot 100', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us hot 100 record is not equal to - .', 'tostr': 'filter_not_eq { all_rows ; us hot 100 ; - }'}], 'result': '2', 'ind': 1, 'tostr': 'count { f... | eq { count { filter_not_eq { all_rows ; us hot 100 ; - } } ; 2 } = true | select the rows whose us hot 100 record is not equal to - . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_not_eq_0': 0, 'all_rows_4': 4, 'us hot 100_5': 5, '-_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_not_eq_0': 'filter_not_eq', 'all_rows_4': 'all_rows', 'us hot 100_5': 'us hot 100', '-_6': '-', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_not_eq_0': [1], 'all_rows_4': [0], 'us hot 100_5': [0], '-_6': [0], '2_7': [2]} | ['year', 'us hot 100', 'us r & b', 'us rap', 'album'] | [['1999', '36', '13', '10', 'chopper city in the ghetto'], ['1999', '-', '106', '-', 'chopper city in the ghetto'], ['2000', '-', '86', '-', 'checkmate'], ['2003', '-', '74', '-', "livin ' legend"], ['2003', '-', '-', '-', "livin ' legend"], ['2004', '-', '105', '-', 'life after cash money'], ['2005', '-', '65', '-', '... |
1950 vfl season | https://en.wikipedia.org/wiki/1950_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10701045-15.html.csv | count | there were 6 game venues used during the 1950 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', ... | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '15.14 ( 104 )', 'st kilda', '7.5 ( 47 )', 'arden street oval', '9000', '5 august 1950'], ['geelong', '13.14 ( 92 )', 'melbourne', '9.12 ( 66 )', 'kardinia park', '15500', '5 august 1950'], ['collingwood', '16.21 ( 117 )', 'hawthorn', '2.8 ( 20 )', 'victoria park', '9000', '5 august 1950'], ['south... |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-48.html.csv | majority | all incumbents of the 2006 house of representatives elections were re - elected . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 're - elected', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'results', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the results records of all rows , all of them fuzzily match to re - elected .', 'tostr': 'all_eq { all_rows ; results ; re - elected } = true'} | all_eq { all_rows ; results ; re - elected } = true | for the results records of all rows , all of them fuzzily match to re - elected . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'results_3': 3, 're - elected_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'results_3': 'results', 're - elected_4': 're - elected'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'results_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['washington 1', 'jay inslee', 'democratic', '1998', 're - elected'], ['washington 2', 'rick larsen', 'democratic', '2000', 're - elected'], ['washington 3', 'brian baird', 'democratic', '1998', 're - elected'], ['washington 4', 'doc hastings', 'republican', '1994', 're - elected'], ['washington 5', 'cathy mcmorris', ... |
just a closer walk with thee ( album ) | https://en.wikipedia.org/wiki/Just_a_Closer_Walk_with_Thee_%28album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13536392-2.html.csv | ordinal | on the album just a closer walk with thee , the song my lord what a mornin ' is the 3rd shortest . | {'row': '8', 'col': '5', 'order': '3', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'time', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; time ; 3 }'}, 'title'], 'result': "my lord what a mornin '", 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; time ; 3 } ; title }'}, "my lord w... | eq { hop { nth_argmin { all_rows ; time ; 3 } ; title } ; my lord what a mornin ' } = true | select the row whose time record of all rows is 3rd minimum . the title record of this row is my lord what a mornin ' . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, '3_6': 6, 'title_7': 7, "my lord what a mornin'_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', 'time_5': 'time', '3_6': '3', 'title_7': 'title', "my lord what a mornin'_8": "my lord what a mornin '"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], '3_6': [0], 'title_7': [1], "my lord what a mornin'_8": [2]} | ['track number', 'title', 'songwriter ( s )', 'recording date', 'time'] | [['1', 'swing low , sweet chariot', 'wallis willis ( adapted by malcolm dodds )', 'november 13 , 1959', '3:15'], ['2', 'steal away', '( adapted by malcolm dodds )', 'november 13 , 1959', '3:15'], ['3', 'little david', '( adapted by malcolm dodds )', 'january 28 , 1960', '2:20'], ['4', 'nobody knows', '( adapted by malc... |
colonial turf cup | https://en.wikipedia.org/wiki/Colonial_Turf_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11237859-1.html.csv | majority | the majority of these races had a distance in miles of 1-3 / 16 . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': '1-3 / 16', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'distance ( miles )', '1-3 / 16'], 'result': True, 'ind': 0, 'tointer': 'for the distance ( miles ) records of all rows , all of them fuzzily match to 1-3 / 16 .', 'tostr': 'all_eq { all_rows ; distance ( miles ) ; 1-3 / 16 } = true'} | all_eq { all_rows ; distance ( miles ) ; 1-3 / 16 } = true | for the distance ( miles ) records of all rows , all of them fuzzily match to 1-3 / 16 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'distance (miles)_3': 3, '1-3 / 16_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'distance (miles)_3': 'distance ( miles )', '1-3 / 16_4': '1-3 / 16'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'distance (miles)_3': [0], '1-3 / 16_4': [0]} | ['year', 'winner', 'jockey', 'trainer', 'owner', 'distance ( miles )', 'time'] | [['2011', 'rahystrada', 'sheldon russell', 'byron hughes', 'robert courtney', '1 - 3 / 16', '1:54.68'], ['2010', "paddy o'prado", 'kent desormeaux', 'dale romans', 'donegal racing', '1 - 3 / 16', '1:54.20'], ['2009', 'battle of hastings', 'tyler baze', 'jeff mullins', 'michael house', '1 - 3 / 16', '1:57.79'], ['2008',... |
weightlifting at the 2007 pan american games | https://en.wikipedia.org/wiki/Weightlifting_at_the_2007_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17703223-5.html.csv | majority | a majority of competitors in the weightlifting competition completed at least a 140 snatch . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '140', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'snatch', '140'], 'result': True, 'ind': 0, 'tointer': 'for the snatch records of all rows , most of them are greater than or equal to 140 .', 'tostr': 'most_greater_eq { all_rows ; snatch ; 140 } = true'} | most_greater_eq { all_rows ; snatch ; 140 } = true | for the snatch records of all rows , most of them are greater than or equal to 140 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'snatch_3': 3, '140_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'snatch_3': 'snatch', '140_4': '140'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'snatch_3': [0], '140_4': [0]} | ['name', 'bodyweight', 'snatch', 'clean & jerk', 'total ( kg )'] | [['josé oliver ruíz ( col )', '84.45', '160.0', '203.0', '363.0'], ['jadier valladares ( cub )', '84.50', '161.0', '202.0', '363.0'], ['herbys márquez ( ven )', '84.75', '155.0', '195.0', '350.0'], ['kendrick farris ( usa )', '84.15', '158.0', '191.0', '349.0'], ['juan quiterio ( dom )', '84.35', '145.0', '185.0', '330... |
list of counties and boroughs of the unreformed house of commons at 1800 | https://en.wikipedia.org/wiki/List_of_counties_and_boroughs_of_the_Unreformed_House_of_Commons_at_1800 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24329520-4.html.csv | aggregation | of the counties and boroughs of the unreformed house of commons at 1800 , the average number of times contested was 2.17 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '2.17', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'times contested'], 'result': '2.17', 'ind': 0, 'tostr': 'avg { all_rows ; times contested }'}, '2.17'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; times contested } ; 2.17 } = true', 'tointer': 'the average of the times contested r... | round_eq { avg { all_rows ; times contested } ; 2.17 } = true | the average of the times contested record of all rows is 2.17 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'times contested_4': 4, '2.17_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'times contested_4': 'times contested', '2.17_5': '2.17'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'times contested_4': [0], '2.17_5': [1]} | ['borough', 'county', 'franchise type', 'members', 'voters in 1800', 'times contested', 'fate in 1832'] | [['beaumaris', 'anglesey', 'corporation', '1', '24', '0', 'retained one seat'], ['brecon', 'brecknockshire', 'freemen', '1', '12', '0', 'retained one seat'], ['carmarthen', 'carmarthenshire', 'freemen', '1', '500', '5', 'retained one seat'], ['denbigh boroughs ( denbigh , holt , ruthin )', 'denbighshire', 'freemen', '1... |
list of tallest buildings in nashville | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Nashville | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12169960-1.html.csv | count | 18 buildings are included in the list of nashville 's tallest buildings . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '18', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'name'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record is arbitrary .', 'tostr': 'filter_all { all_rows ; name }'}], 'result': '18', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; name } }', 'to... | eq { count { filter_all { all_rows ; name } } ; 18 } = true | select the rows whose name record is arbitrary . the number of such rows is 18 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'name_5': 5, '18_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'name_5': 'name', '18_6': '18'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'name_5': [0], '18_6': [2]} | ['rank', 'name', 'height ft ( m )', 'floors', 'year'] | [['1', 'at & t building', '617 ( 188 )', '33', '1994'], ['2', 'fifth third center', '490 ( 149 )', '31', '1986'], ['3', 'william r snodgrass tennessee tower', '452 ( 138 )', '31', '1970'], ['4', 'pinnacle at symphony place', '417 ( 127 )', '28', '2010'], ['5', 'life and casualty tower', '409 ( 125 )', '30', '1957'], ['... |
1987 200 miles of norisring | https://en.wikipedia.org/wiki/1987_200_Miles_of_Norisring | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16861730-2.html.csv | unique | raul boesel was the only driver with a jaguar xjr - 8 type chassis - engine in the 1987 200 miles of norisring race . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'jaguar xjr - 8', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis - engine', 'jaguar xjr - 8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis - engine record fuzzily matches to jaguar xjr - 8 .', 'tostr': 'filter_eq { all_rows ; chassis - engine ; jaguar xj... | and { only { filter_eq { all_rows ; chassis - engine ; jaguar xjr - 8 } } ; eq { hop { filter_eq { all_rows ; chassis - engine ; jaguar xjr - 8 } ; driver } ; raul boesel } } = true | select the rows whose chassis - engine record fuzzily matches to jaguar xjr - 8 . there is only one such row in the table . the driver record of this unqiue row is raul boesel . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'chassis - engine_7': 7, 'jaguar xjr - 8_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'raul boesel_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'chassis - engine_7': 'chassis - engine', 'jaguar xjr - 8_8': 'jaguar xjr - 8', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'raul boesel_10': 'raul boesel'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'chassis - engine_7': [0], 'jaguar xjr - 8_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'raul boesel_10': [3]} | ['class', 'team', 'driver', 'chassis - engine', 'laps'] | [['c1', 'silk cut jaguar', 'raul boesel', 'jaguar xjr - 8', '77'], ['c1', 'liqui moly equipe', 'jonathan palmer', 'porsche 962 c', '77'], ['c1', 'brun motorsport', 'jochen mass', 'porsche 962 c', '76'], ['c1', 'joest racing', 'stanley dickens', 'porsche 962 c', '75'], ['c1', 'primagaz competition', 'pierre yver', 'pors... |
german submarine u - 404 | https://en.wikipedia.org/wiki/German_submarine_U-404 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17794265-1.html.csv | count | two ships were only damaged when attacked by the german u 404 . | {'scope': 'all', 'criterion': 'equal', 'value': 'damaged', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fate', 'damaged'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fate record fuzzily matches to damaged .', 'tostr': 'filter_eq { all_rows ; fate ; damaged }'}], 'result': '2', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_eq { all_rows ; fate ; damaged } } ; 2 } = true | select the rows whose fate record fuzzily matches to damaged . 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, 'fate_5': 5, 'damaged_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', 'fate_5': 'fate', 'damaged_6': 'damaged', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'fate_5': [0], 'damaged_6': [0], '2_7': [2]} | ['date', 'ship', 'nationality', 'tonnage', 'fate'] | [['5 march 1942', 'collamer', 'usa', '5112', 'sunk'], ['13 march 1942', 'tolten', 'chile', '1858', 'sunk'], ['14 march 1942', 'lemuel burrows', 'usa', '7610', 'sunk'], ['17 march 1942', 'san demitro', 'great britain', '8073', 'sunk'], ['30 may 1942', 'aloca shipper', 'usa', '5491', 'sunk'], ['1 june 1942', 'west notus'... |
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/1-15621965-10.html.csv | majority | most of the players in the roster are from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', '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 orlando', 'school / club team'] | [['mario kasun', '41', 'croatia', 'center', '2004 - 2006', 'gonzaga'], ['shawn kemp', '40', 'united states', 'forward', '2002 - 2003', 'concord hs'], ['tim kempton', '9', 'united states', 'forward - center', '2002 - 2004', 'notre dame'], ['jonathan kerner', '52', 'united states', 'center', '1998 - 1999', 'east carolina... |
color in chinese culture | https://en.wikipedia.org/wiki/Color_in_Chinese_culture | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15305217-1.html.csv | unique | only wood is associated with the color green in chinese culture . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'green', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'wood', 'green'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wood record fuzzily matches to green .', 'tostr': 'filter_eq { all_rows ; wood ; green }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; wood ; gre... | only { filter_eq { all_rows ; wood ; green } } = true | select the rows whose wood record fuzzily matches to green . 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, 'wood_4': 4, 'green_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'wood_4': 'wood', 'green_5': 'green'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'wood_4': [0], 'green_5': [0]} | ['element', 'wood', 'fire', 'earth', 'metal', 'water'] | [['color', 'green', 'red', 'yellow', 'white', 'black'], ['direction', 'east', 'south', 'center', 'west', 'north'], ['planet', 'jupiter', 'mars', 'saturn', 'venus', 'mercury'], ['heavenly creature', 'azure dragon 青龍', 'vermilion bird 朱雀', 'yellow dragon 黃龍', 'white tiger 白虎', 'black tortoise 玄武'], ['heavenly stems', '甲 ... |
united states house of representatives elections , 1994 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1994 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341522-24.html.csv | majority | in the 1994 united states house of representatives election , all of the incumbents were re-elected . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 're-elected', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'status', 're-elected'], 'result': True, 'ind': 0, 'tointer': 'for the status records of all rows , all of them fuzzily match to re-elected .', 'tostr': 'all_eq { all_rows ; status ; re-elected } = true'} | all_eq { all_rows ; status ; re-elected } = true | for the status records of all rows , all of them fuzzily match to re-elected . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'status_3': 3, 're-elected_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'status_3': 'status', 're-elected_4': 're-elected'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'status_3': [0], 're-elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'status', 'opponent'] | [['massachusetts1', 'john olver', 'democratic', '1991', 're - elected', 'john olver ( d ) unopposed'], ['massachusetts4', 'barney frank', 'democratic', '1980', 're - elected', 'barney frank ( d ) unopposed'], ['massachusetts5', 'marty meehan', 'democratic', '1992', 're - elected', 'marty meehan ( d ) 69.8 % david e col... |
the evian championship | https://en.wikipedia.org/wiki/The_Evian_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1529260-3.html.csv | ordinal | the second time laura davies was the champion of the evian championship , the margin of victory was 4 strokes . | {'scope': 'subset', 'row': '4', 'col': '1', 'order': '2', 'col_other': '3,7', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'laura davies'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'champion', 'laura davies'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; champion ; laura davies }', 'tointer': 'select the rows whose champion record fuzzily matches to... | eq { hop { nth_argmin { filter_eq { all_rows ; champion ; laura davies } ; year ; 2 } ; margin of victory } ; 4 strokes } = true | select the rows whose champion record fuzzily matches to laura davies . select the row whose year record of these rows is 2nd minimum . the margin of victory record of this row is 4 strokes . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'champion_6': 6, 'laura davies_7': 7, 'year_8': 8, '2_9': 9, 'margin of victory_10': 10, '4 strokes_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'champion_6': 'champion', 'laura davies_7': 'laura davies', 'year_8': 'year', '2_9': '2', 'margin of victory_10': 'margin of victory', '4 strokes_11': '4 strokes... | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'champion_6': [0], 'laura davies_7': [0], 'year_8': [1], '2_9': [1], 'margin of victory_10': [2], '4 strokes_11': [3]} | ['year', 'dates', 'champion', 'country', 'score', 'to par', 'margin of victory'] | [['1999', 'jun 9 - 12', 'catrin nilsmark', 'sweden', '69 + 70 + 72 + 68 = 279', '- 9', '2 strokes'], ['1998', 'jun 3 - 6', 'helen alfredsson', 'sweden', '70 + 69 + 73 + 65 = 277', '- 11', '4 strokes'], ['1997', 'jun 18 - 21', 'hiromi kobayashi', 'japan', '69 + 67 + 69 + 69 = 274', '- 14', 'playoff'], ['1996', 'jun 19 -... |
list of sri lanka one day international cricket records | https://en.wikipedia.org/wiki/List_of_Sri_Lanka_One_Day_International_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26041144-11.html.csv | count | for the sri lanka one day international cricket records , when there are over 200 matches , there were 3 players with over 250 innings . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '250', 'result': '3', 'col': '5', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '200'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'matches', '200'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; matches ; 200 }', 'tointer': 'select the rows whose matches record is greater than 200 .'}, 'innings',... | eq { count { filter_greater { filter_greater { all_rows ; matches ; 200 } ; innings ; 250 } } ; 3 } = true | select the rows whose matches record is greater than 200 . among these rows , select the rows whose innings record is greater than 250 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'matches_6': 6, '200_7': 7, 'innings_8': 8, '250_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'matches_6': 'matches', '200_7': '200', 'innings_8': 'innings', '250_9': '250', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'matches_6': [0], '200_7': [0], 'innings_8': [1], '250_9': [1], '3_10': [3]} | ['rank', 'average', 'player', 'matches', 'innings', 'period'] | [['1', '39.69', 'kumar sangakkara', '351', '328', '2000 - pre'], ['2', '37.57', 'marvan atapattu', '268', '259', '1990 - 2007'], ['3', '36.74', 'tillakaratne dilshan', '264', '239', '1999 - pre'], ['4', '35.84', 'arjuna ranatunga', '269', '255', '1982 - 1999'], ['5', '35.26', 'russel arnold', '180', '155', '1997 - 2007... |
ireland in the eurovision song contest 1980 | https://en.wikipedia.org/wiki/Ireland_in_the_Eurovision_Song_Contest_1980 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18682634-1.html.csv | superlative | in the 1980 eurovision song contest , ireland 's song what 's another year won first place . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'place'], 'result': '1st', 'ind': 0, 'tostr': 'min { all_rows ; place }', 'tointer': 'the minimum place record of all rows is 1st .'}, '1st'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; place } ; 1st }', 'tointer': 'the... | and { eq { min { all_rows ; place } ; 1st } ; eq { hop { argmin { all_rows ; place } ; song } ; what 's another year } } = true | the minimum place record of all rows is 1st . the song record of the row with superlative place record is what 's another year . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'min_0': 0, 'all_rows_7': 7, 'place_8': 8, '1st_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmin_2': 2, 'all_rows_10': 10, 'place_11': 11, 'song_12': 12, "what 's another year_13": 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'min_0': 'min', 'all_rows_7': 'all_rows', 'place_8': 'place', '1st_9': '1st', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmin_2': 'argmin', 'all_rows_10': 'all_rows', 'place_11': 'place', 'song_12': 'song', "what 's another year_13": "what 's another year"} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'min_0': [1], 'all_rows_7': [0], 'place_8': [0], '1st_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmin_2': [3], 'all_rows_10': [2], 'place_11': [2], 'song_12': [3], "what 's another year_13": [4]} | ['draw', 'song', 'artist', 'points', 'place'] | [['1', "loving wo n't let you down", 'roy taylor & karen black', '13', '3rd'], ['2', 'take me back again', 'the straw hat and garter company', '2', '8th'], ['3', 'the saddest show on earth', 'eileen reid', '10', '4th'], ['4', "you 're so cheeky", 'charlie chapman & the miami', '5', '5th'], ['5', "what 's another year",... |
2008 chicago sky season | https://en.wikipedia.org/wiki/2008_Chicago_Sky_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17118657-10.html.csv | unique | chicago 's game on september 12 is the only that recorded more than one player with high rebounds . | {'scope': 'all', 'row': '5', 'col': '6', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': ',', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', ','], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high rebounds record fuzzily matches to , .', 'tostr': 'filter_eq { all_rows ; high rebounds ; , }'}], 'result': True, 'ind': 1, 'tostr': '... | and { only { filter_eq { all_rows ; high rebounds ; , } } ; eq { hop { filter_eq { all_rows ; high rebounds ; , } ; date } ; september 12 } } = true | select the rows whose high rebounds record fuzzily matches to , . there is only one such row in the table . the date record of this unqiue row is september 12 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'high rebounds_7': 7, ',_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'september 12_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'high rebounds_7': 'high rebounds', ',_8': ',', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'september 12_10': 'september 12'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'high rebounds_7': [0], ',_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'september 12_10': [3]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['29', 'september 4', 'seattle', '62 - 70', 'perkins ( 22 )', 'dupree ( 6 )', 'canty ( 6 )', 'uic pavilion 3829', '11 - 18'], ['30', 'september 5', 'connecticut', '75 - 80', 'perkins ( 18 )', 'fowles ( 6 )', 'canty ( 7 )', 'mohegan sun arena 8088', '11 - 19'], ['31', 'september 7', 'new york', '61 - 69', 'perkins ( 18... |
2007 japanese television dramas | https://en.wikipedia.org/wiki/2007_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539861-3.html.csv | aggregation | the 2007 japanese television dramas drew an average viewership rating of 11.76 % . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '11.76 %', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'average ratings'], 'result': '11.76 %', 'ind': 0, 'tostr': 'avg { all_rows ; average ratings }'}, '11.76 %'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; average ratings } ; 11.76 % } = true', 'tointer': 'the average of the average ... | round_eq { avg { all_rows ; average ratings } ; 11.76 % } = true | the average of the average ratings record of all rows is 11.76 % . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'average ratings_4': 4, '11.76%_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'average ratings_4': 'average ratings', '11.76%_5': '11.76 %'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'average ratings_4': [0], '11.76%_5': [1]} | ['japanese title', 'romaji title', 'tv station', 'episodes', 'average ratings'] | [['スシ王子 ！', 'sushi ouji !', 'tv asahi', '8', '7.5 %'], ['菊次郎とさき 3', 'kikujirou to saki 3', 'tv asahi', '11', '9.3 %'], ['牛に願いを love & farm', 'ushi ni negai wo - love & farm', 'fuji tv', '11', '8.7 %'], ['ライフ', 'life', 'fuji tv', '11', '12.16 %'], ['受験の神様', 'juken no kamisama', 'ntv', '9', '9.5 %'], ['パパとムスメの7日間', 'papa... |
2008 pga tour | https://en.wikipedia.org/wiki/2008_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14473512-2.html.csv | aggregation | players in the 2008 pga tour golf series won an average prize money of 4831665 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '4831665', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'prize money'], 'result': '4831665', 'ind': 0, 'tostr': 'avg { all_rows ; prize money }'}, '4831665'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; prize money } ; 4831665 } = true', 'tointer': 'the average of the prize money record o... | round_eq { avg { all_rows ; prize money } ; 4831665 } = true | the average of the prize money record of all rows is 4831665 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'prize money_4': 4, '4831665_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'prize money_4': 'prize money', '4831665_5': '4831665'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'prize money_4': [0], '4831665_5': [1]} | ['rank', 'player', 'country', 'events', 'prize money'] | [['1', 'vijay singh', 'fiji', '23', '6601094'], ['2', 'tiger woods', 'united states', '6', '5775000'], ['3', 'phil mickelson', 'united states', '21', '5118875'], ['4', 'sergio garcía', 'spain', '19', '4858224'], ['5', 'kenny perry', 'united states', '26', '4663794'], ['6', 'anthony kim', 'united states', '22', '4656265... |
acc - big ten challenge | https://en.wikipedia.org/wiki/ACC%E2%80%93Big_Ten_Challenge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1672976-6.html.csv | superlative | the acc - big ten challenge game that was played at kohl center madison , wi had the largest attendance . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'location'], 'result': 'kohl center madison , wi', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; location }'}, 'kohl cent... | eq { hop { argmax { all_rows ; attendance } ; location } ; kohl center madison , wi } = true | select the row whose attendance record of all rows is maximum . the location record of this row is kohl center madison , wi . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'location_6': 6, 'kohl center madison , wi_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'location_6': 'location', 'kohl center madison , wi_7': 'kohl center madison , wi'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'location_6': [1], 'kohl center madison , wi_7': [2]} | ['date', 'time', 'acc team', 'big ten team', 'location', 'television', 'attendance', 'winner', 'challenge leader'] | [['mon , nov 29', '7:00 pm', 'virginia', '13 minnesota', 'williams arena minneapolis , mn', 'espn2', '12089', 'virginia ( 87 - 79 )', 'acc ( 1 - 0 )'], ['tue , nov 30', '7:00 pm', 'wake forest', 'iowa', 'ljvm coliseum winston - salem , nc', 'espnu', '9086', 'wake forest ( 76 - 73 )', 'acc ( 2 - 0 )'], ['tue , nov 30', ... |
christian vietoris | https://en.wikipedia.org/wiki/Christian_Vietoris | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10705060-1.html.csv | superlative | the 2006 race was the only one christian vietoris finished in 1st in his career between 2005 and 2012 . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'position'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; position }'}, 'season'], 'result': '2006', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; position } ; season }'}, '2006'], 'result': True, 'ind': 2, 'tost... | eq { hop { argmin { all_rows ; position } ; season } ; 2006 } = true | select the row whose position record of all rows is minimum . the season record of this row is 2006 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'position_5': 5, 'season_6': 6, '2006_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'position_5': 'position', 'season_6': 'season', '2006_7': '2006'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'position_5': [0], 'season_6': [1], '2006_7': [2]} | ['season', 'series', 'team name', 'races', 'poles', 'wins', 'points', 'position'] | [['2005', 'formula bmw adac', 'eifelland racing', '19', '0', '0', '17', '16th'], ['2006', 'formula bmw adac', 'josef kaufmann racing', '18', '9', '9', '277', '1st'], ['2007', 'german formula three', 'josef kaufmann racing', '12', '2', '1', '62', '6th'], ['2008', 'formula 3 euro series', 'mücke motorsport', '20', '1', '... |
2005 chicago white sox season | https://en.wikipedia.org/wiki/2005_Chicago_White_Sox_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12569321-11.html.csv | comparative | the chicago white sox game played on october 15 had a longer time than the game played on october 12 . | {'row_1': '4', 'row_2': '2', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october 15'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to october 15 .', 'tostr': 'filter_eq { all_rows ; date ; october 15 }'}, 'time'], 'result': None, 'ind'... | greater { hop { filter_eq { all_rows ; date ; october 15 } ; time } ; hop { filter_eq { all_rows ; date ; october 12 } ; time } } = true | select the rows whose date record fuzzily matches to october 15 . take the time record of this row . select the rows whose date record fuzzily matches to october 12 . take the time record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'october 15_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'october 12_12': 12, 'time_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'october 15_8': 'october 15', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'october 12_12': ... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'october 15_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'october 12_12': [1], 'time_13': [3]} | ['date', 'opponent', 'score', 'loss', 'time', 'att', 'record'] | [['october 11', 'angels', '2 - 3', 'contreras ( 1 - 1 )', '2:47', '40659', '3 - 1 ( 0 - 1 )'], ['october 12', 'angels', '2 - 1', 'escobar ( 1 - 1 )', '2:34', '41013', '4 - 1 ( 1 - 1 )'], ['october 14', 'angels', '5 - 2', 'lackey ( 0 - 1 )', '2:42', '44725', '5 - 1 ( 2 - 1 )'], ['october 15', 'angels', '8 - 2', 'santana... |
cycling at the 2008 summer olympics - men 's bmx | https://en.wikipedia.org/wiki/Cycling_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_BMX | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18603914-3.html.csv | comparative | marc willers had a larger first run than mike day . | {'row_1': '2', 'row_2': '1', 'col': '3', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'marc willers ( nzl )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to marc willers ( nzl ) .', 'tostr': 'filter_eq { all_rows ; name ; marc willers ( nzl ) }'}, ... | greater { hop { filter_eq { all_rows ; name ; marc willers ( nzl ) } ; 1st run } ; hop { filter_eq { all_rows ; name ; mike day ( usa ) } ; 1st run } } = true | select the rows whose name record fuzzily matches to marc willers ( nzl ) . take the 1st run record of this row . select the rows whose name record fuzzily matches to mike day ( usa ) . take the 1st run record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'marc willers ( nzl )_8': 8, '1st run_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'mike day ( usa )_12': 12, '1st run_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'marc willers ( nzl )_8': 'marc willers ( nzl )', '1st run_9': '1st run', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11':... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'marc willers ( nzl )_8': [0], '1st run_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'mike day ( usa )_12': [1], '1st run_13': [3]} | ['rank', 'name', '1st run', '2nd run', '3rd run', 'total'] | [['1', 'mike day ( usa )', '36.170 ( 1 )', '36.080 ( 1 )', '36.122 ( 1 )', '3'], ['2', 'marc willers ( nzl )', '47.614 ( 4 )', '36.253 ( 3 )', '36.278 ( 2 )', '9'], ['3', 'donny robinson ( usa )', '48.906 ( 6 )', '36.235 ( 2 )', '36.490 ( 3 )', '11'], ['4', 'andrés jiménez caicedo ( col )', '36.619 ( 2 )', '36.939 ( 5 ... |
2007 - 08 four hills tournament | https://en.wikipedia.org/wiki/2007%E2%80%9308_Four_Hills_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14948647-1.html.csv | aggregation | the average of the total points during the 2007 – 08 four hills tournament was 962.2 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '962.2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total points'], 'result': '962.2', 'ind': 0, 'tostr': 'avg { all_rows ; total points }'}, '962.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total points } ; 962.2 } = true', 'tointer': 'the average of the total points record of ... | round_eq { avg { all_rows ; total points } ; 962.2 } = true | the average of the total points record of all rows is 962.2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total points_4': 4, '962.2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total points_4': 'total points', '962.2_5': '962.2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total points_4': [0], '962.2_5': [1]} | ['rank', 'name', 'nationality', 'total points', 'oberstdorf ( rk )', 'ga - pa ( rk )', 'bhofen1 ( rk )', 'bhofen2 ( rk )'] | [['1', 'janne ahonen', 'fin', '1085.8', '279.0 ( 3 )', '272.7 ( 2 )', '282.5 ( 1 )', '251.6 ( 1 )'], ['2', 'thomas morgenstern', 'aut', '1066.0', '295.9 ( 1 )', '256.0 ( 9 )', '271.4 ( 2 )', '242.7 ( 3 )'], ['3', 'michael neumayer', 'ger', '994.6', '259.5 ( 7 )', '258.6 ( 3 )', '249.9 ( 7 )', '226.9 ( 10 )'], ['4', 'ad... |
saulo roston | https://en.wikipedia.org/wiki/Saulo_Roston | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27614707-1.html.csv | majority | in the television show ídolos brazil , saulo roston was safe for most of the episodes . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'safe', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'safe'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to safe .', 'tostr': 'most_eq { all_rows ; result ; safe } = true'} | most_eq { all_rows ; result ; safe } = true | for the result records of all rows , most of them fuzzily match to safe . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'safe_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'safe_4': 'safe'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'safe_4': [0]} | ['week', 'theme', 'song choice', 'original artist', 'order', 'result'] | [['audition', "auditioner 's choice", 'bem que se quis', 'marisa monte', 'n / a', 'advanced'], ['theater', 'first solo', 'n / a', 'n / a', 'n / a', 'advanced'], ['top 24', 'top 12 men', 'como vai você', 'roberto carlos', '7', 'advanced'], ['top 12', 'sing your idol', 'beija eu', 'marisa monte', '4', 'safe'], ['top 11',... |
cale yarborough | https://en.wikipedia.org/wiki/Cale_Yarborough | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1145778-1.html.csv | unique | 1972 was the only year in which cale yarborough finished in 10th place . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'finish', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose finish record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; finish ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ;... | and { only { filter_eq { all_rows ; finish ; 10 } } ; eq { hop { filter_eq { all_rows ; finish ; 10 } ; year } ; 1972 } } = true | select the rows whose finish record is equal to 10 . there is only one such row in the table . the year record of this unqiue row is 1972 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'finish_7': 7, '10_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1972_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'finish_7': 'finish', '10_8': '10', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1972_10': '1972'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'finish_7': [0], '10_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1972_10': [3]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1966', '24', '159.794', '15', '28', '0'], ['1967', '20', '162.830', '30', '17', '176'], ['1971', '14', '170.770', '19', '16', '140'], ['1972', '32', '178.864', '33', '10', '193']] |
1965 - 66 boston celtics season | https://en.wikipedia.org/wiki/1965%E2%80%9366_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17342287-8.html.csv | ordinal | the march 13 game against the baltimore bullets was the second highest score recorded by the boston celtics in the 1965 - 66 boston celtics season . | {'row': '8', 'col': '4', 'order': '2', 'col_other': '2,3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'score', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; score ; 2 }'}, 'date'], 'result': 'march 13', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; score ; 2 } ; date }'},... | and { eq { hop { nth_argmax { all_rows ; score ; 2 } ; date } ; march 13 } ; eq { hop { nth_argmax { all_rows ; score ; 2 } ; opponent } ; baltimore bullets } } = true | select the row whose score record of all rows is 2nd maximum . the date record of this row is march 13 . the opponent record of this row is baltimore bullets . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_7': 7, 'score_8': 8, '2_9': 9, 'date_10': 10, 'march 13_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'opponent_12': 12, 'baltimore bullets_13': 13} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_7': 'all_rows', 'score_8': 'score', '2_9': '2', 'date_10': 'date', 'march 13_11': 'march 13', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'opponent_12': 'opponent', 'baltimore bullets_13': 'balti... | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'nth_argmax_0': [1, 3], 'all_rows_7': [0], 'score_8': [0], '2_9': [0], 'date_10': [1], 'march 13_11': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'opponent_12': [3], 'baltimore bullets_13': [4]} | ['game', 'date', 'opponent', 'score', 'location / attendance', 'record'] | [['70', 'march 1', 'st louis hawks', '120 - 95', 'kiel auditorium', '47 - 23'], ['71', 'march 2', 'new york knickerbockers', '140 - 104', 'boston garden', '48 - 23'], ['72', 'march 4', 'st louis hawks', '112 - 132', 'providence , ri', '48 - 24'], ['73', 'march 5', 'philadelphia 76ers', '85 - 102', 'convention hall', '4... |
kristine kunce | https://en.wikipedia.org/wiki/Kristine_Kunce | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14803173-3.html.csv | unique | kristine kunce played on a grass surface on one occasion . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'grass', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to grass .', 'tostr': 'filter_eq { all_rows ; surface ; grass }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; s... | only { filter_eq { all_rows ; surface ; grass } } = true | select the rows whose surface record fuzzily matches to grass . 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, 'surface_4': 4, 'grass_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'surface_4': 'surface', 'grass_5': 'grass'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'surface_4': [0], 'grass_5': [0]} | ['date', 'tournament', 'surface', 'partnering', 'opponents in the final', 'score'] | [['19 april 1993', 'kuala lumpar , malaysia', 'hard ( i )', 'nicole arendt', 'patty fendick meredith mcgrath', '6 - 4 , 7 - 6 ( 2 )'], ['4 october 1993', 'taiwan', 'hard', 'jo - anne faull', 'yayuk basuki nana miyagi', '6 - 4 , 6 - 2'], ['18 april 1994', 'kallang , singapore', 'hard', 'nicole arendt', 'patty fendick me... |
1963 new york jets season | https://en.wikipedia.org/wiki/1963_New_York_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13983625-1.html.csv | aggregation | in the 1963 jets season , there were a total of 26748 people attendance for the games against the bills . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '26748', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'buffalo bills'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'buffalo bills'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; buffalo bills }', 'tointer': 'select the rows whose opponent record fuzzily matches to buffalo bills .'}, 'attendance'... | round_eq { sum { filter_eq { all_rows ; opponent ; buffalo bills } ; attendance } ; 26748 } = true | select the rows whose opponent record fuzzily matches to buffalo bills . the sum of the attendance record of these rows is 26748 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'buffalo bills_6': 6, 'attendance_7': 7, '26748_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'buffalo bills_6': 'buffalo bills', 'attendance_7': 'attendance', '26748_8': '26748'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'buffalo bills_6': [0], 'attendance_7': [1], '26748_8': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', '1963 - 09 - 08', 'boston patriots', 'l 38 - 14', 'fenway park', '24120'], ['3', '1963 - 09 - 22', 'houston oilers', 'w 24 - 17', 'polo grounds', '9336'], ['4', '1963 - 09 - 28', 'oakland raiders', 'w 10 - 7', 'polo grounds', '17100'], ['5', '1963 - 10 - 05', 'boston patriots', 'w 31 - 24', 'polo grounds', '1676... |
maurício gugelmin | https://en.wikipedia.org/wiki/Maur%C3%ADcio_Gugelmin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226502-2.html.csv | superlative | the highest number of points was received by leyton house march racing team . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'pts'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; pts }'}, 'entrant'], 'result': 'leyton house march racing team', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; pts } ; entrant }'}, 'leyton house march racing ... | eq { hop { argmax { all_rows ; pts } ; entrant } ; leyton house march racing team } = true | select the row whose pts record of all rows is maximum . the entrant record of this row is leyton house march racing team . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'pts_5': 5, 'entrant_6': 6, 'leyton house march racing team_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'pts_5': 'pts', 'entrant_6': 'entrant', 'leyton house march racing team_7': 'leyton house march racing team'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'pts_5': [0], 'entrant_6': [1], 'leyton house march racing team_7': [2]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1988', 'leyton house march racing team', 'march 881', 'judd v8', '5'], ['1989', 'leyton house racing', 'march 881', 'judd v8', '4'], ['1989', 'leyton house racing', 'march cg891', 'judd v8', '4'], ['1990', 'leyton house', 'leyton house cg901', 'judd v8', '1'], ['1991', 'leyton house', 'leyton house cg911', 'ilmor v1... |
nfl europe | https://en.wikipedia.org/wiki/NFL_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-160994-4.html.csv | superlative | the oldest stadium used by nfl europe opened in 1877 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '13', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'opened'], 'result': '1877', 'ind': 0, 'tostr': 'min { all_rows ; opened }', 'tointer': 'the minimum opened record of all rows is 1877 .'}, '1877'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; opened } ; 1877 }', 'tointe... | and { eq { min { all_rows ; opened } ; 1877 } ; eq { hop { argmin { all_rows ; opened } ; stadium } ; stamford bridge } } = true | the minimum opened record of all rows is 1877 . the stadium record of the row with superlative opened record is stamford bridge . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'min_0': 0, 'all_rows_7': 7, 'opened_8': 8, '1877_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmin_2': 2, 'all_rows_10': 10, 'opened_11': 11, 'stadium_12': 12, 'stamford bridge_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'min_0': 'min', 'all_rows_7': 'all_rows', 'opened_8': 'opened', '1877_9': '1877', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmin_2': 'argmin', 'all_rows_10': 'all_rows', 'opened_11': 'opened', 'stadium_12': 'stadium', 'stamford bridge_13': 'stamford bridge'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'min_0': [1], 'all_rows_7': [0], 'opened_8': [0], '1877_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmin_2': [3], 'all_rows_10': [2], 'opened_11': [2], 'stadium_12': [3], 'stamford bridge_13': [4]} | ['team', 'stadium', 'capacity', 'opened', 'city'] | [['amsterdam admirals', 'amsterdam arena', '51859', '1996', 'amsterdam , the netherlands'], ['amsterdam admirals', 'olympisch stadion', '31600', '1928', 'amsterdam , the netherlands'], ['barcelona dragons', 'mini estadi', '15276', '1982', 'barcelona , spain'], ['barcelona dragons', 'estadi olímpic lluís companys', '560... |
2008 - 09 detroit red wings season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Red_Wings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17371135-3.html.csv | count | there were two games in this time span where one of the teams went scoreless . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '0', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 0 .', 'tostr': 'filter_eq { all_rows ; score ; 0 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_r... | eq { count { filter_eq { all_rows ; score ; 0 } } ; 2 } = true | select the rows whose score record fuzzily matches to 0 . 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, 'score_5': 5, '0_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', 'score_5': 'score', '0_6': '0', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'score_5': [0], '0_6': [0], '2_7': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'record'] | [['september 24', 'montreal', '3 - 2', 'detroit', 'howard', '0 - 0 - 1'], ['september 25', 'detroit', '4 - 3', 'boston', 'larsson', '1 - 0 - 1'], ['september 26', 'boston', '2 - 1', 'detroit', 'conklin', '1 - 1 - 1'], ['september 28', 'atlanta', '0 - 4', 'detroit', 'osgood', '2 - 1 - 1'], ['september 30', 'detroit', '1... |
1987 in film | https://en.wikipedia.org/wiki/1987_in_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-171293-2.html.csv | comparative | dirty dancing had a higher gross than good morning , vietnam . | {'row_1': '3', 'row_2': '6', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'dirty dancing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to dirty dancing .', 'tostr': 'filter_eq { all_rows ; title ; dirty dancing }'}, 'gross'], 'result'... | greater { hop { filter_eq { all_rows ; title ; dirty dancing } ; gross } ; hop { filter_eq { all_rows ; title ; good morning , vietnam } ; gross } } = true | select the rows whose title record fuzzily matches to dirty dancing . take the gross record of this row . select the rows whose title record fuzzily matches to good morning , vietnam . take the gross 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, 'title_7': 7, 'dirty dancing_8': 8, 'gross_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'good morning , vietnam_12': 12, 'gross_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', 'title_7': 'title', 'dirty dancing_8': 'dirty dancing', 'gross_9': 'gross', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'good... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'dirty dancing_8': [0], 'gross_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'good morning , vietnam_12': [1], 'gross_13': [3]} | ['rank', 'title', 'studio', 'director', 'gross'] | [['1', 'fatal attraction', 'paramount', 'adrian lyne', '320145693'], ['2', 'beverly hills cop ii', 'paramount', 'tony scott', '299965036'], ['3', 'dirty dancing', 'vestron', 'emile ardolino', '213954274'], ['4', 'the living daylights', 'united artists', 'john glen', '191200000'], ['5', 'three men and a baby', 'touchsto... |
moon landing | https://en.wikipedia.org/wiki/Moon_landing | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1558077-2.html.csv | aggregation | the average mass in kilograms of the 7 combined ranger us missions was 340 . | {'scope': 'subset', 'col': '2', 'type': 'average', 'result': '340', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'ranger'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'us mission', 'ranger'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; us mission ; ranger }', 'tointer': 'select the rows whose us mission record fuzzily matches to ranger .'}, 'mass ( kg )'], 'result': '... | round_eq { avg { filter_eq { all_rows ; us mission ; ranger } ; mass ( kg ) } ; 340 } = true | select the rows whose us mission record fuzzily matches to ranger . the average of the mass ( kg ) record of these rows is 340 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'us mission_5': 5, 'ranger_6': 6, 'mass (kg)_7': 7, '340_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'us mission_5': 'us mission', 'ranger_6': 'ranger', 'mass (kg)_7': 'mass ( kg )', '340_8': '340'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'us mission_5': [0], 'ranger_6': [0], 'mass (kg)_7': [1], '340_8': [2]} | ['us mission', 'mass ( kg )', 'launch vehicle', 'launched', 'mission goal', 'mission result'] | [['pioneer 0', '38', 'thor - able', '17 august 1958', 'lunar orbit', 'failure - first stage explosion , destroyed'], ['pioneer 1', '34', 'thor - able', '11 october 1958', 'lunar orbit', 'failure - software error , reentry'], ['pioneer 2', '39', 'thor - able', '8 november 1958', 'lunar orbit', 'failure - third stage mis... |
list of los angeles lakers broadcasters | https://en.wikipedia.org/wiki/List_of_Los_Angeles_Lakers_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16701360-6.html.csv | count | three channels have alan massengale as the studio host for the los angeles lakers . | {'scope': 'all', 'criterion': 'equal', 'value': 'alan massengale', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'studio host', 'alan massengale'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose studio host record fuzzily matches to alan massengale .', 'tostr': 'filter_eq { all_rows ; studio host ; alan massengale }'}], ... | eq { count { filter_eq { all_rows ; studio host ; alan massengale } } ; 3 } = true | select the rows whose studio host record fuzzily matches to alan massengale . 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, 'studio host_5': 5, 'alan massengale_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', 'studio host_5': 'studio host', 'alan massengale_6': 'alan massengale', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'studio host_5': [0], 'alan massengale_6': [0], '3_7': [2]} | ['channel', 'play - by - play', 'color commentator ( s )', 'studio host', 'studio analysts'] | [['kcal - tv', 'chick hearn', 'stu lantz', 'alan massengale', 'james worthy'], ['fox sports net west', 'chick hearn', 'stu lantz', 'paul sunderland', 'jack haley'], ['kcal - tv', 'paul sunderland', 'stu lantz', 'alan massengale', 'james worthy'], ['fox sports net west', 'paul sunderland', 'stu lantz', 'bill macdonald',... |
miss usa 1980 | https://en.wikipedia.org/wiki/Miss_USA_1980 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15532342-2.html.csv | majority | the majority of miss usa 1980 contestants scored under 9 in the preliminary average . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '9.0', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'preliminary average', '9.0'], 'result': True, 'ind': 0, 'tointer': 'for the preliminary average records of all rows , most of them are less than 9.0 .', 'tostr': 'most_less { all_rows ; preliminary average ; 9.0 } = true'} | most_less { all_rows ; preliminary average ; 9.0 } = true | for the preliminary average records of all rows , most of them are less than 9.0 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'preliminary average_3': 3, '9.0_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'preliminary average_3': 'preliminary average', '9.0_4': '9.0'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'preliminary average_3': [0], '9.0_4': [0]} | ['state', 'preliminary average', 'interview', 'swimsuit', 'evening gown', 'semifinal average'] | [['nebraska', '8.450 ( 5 )', '7.938 ( 10 )', '7.489 ( 11 )', '7.832 ( 8 )', '7.753 ( 10 )'], ['arizona', '8.317 ( 8 )', '8.950 ( 4 )', '8.670 ( 4 )', '8.701 ( 2 )', '8.774 ( 2 )'], ['south carolina', '9.086 ( 1 )', '9.082 ( 1 )', '9.097 ( 1 )', '9.567 ( 1 )', '9.249 ( 1 )'], ['minnesota', '8.083 ( 12 )', '7.858 ( 11 )'... |
2003 belarusian premier league | https://en.wikipedia.org/wiki/2003_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14748588-1.html.csv | aggregation | the average capacity of the venues in the belarusian premier league is 9037 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '9037', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '9037', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '9037'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 9037 } = true', 'tointer': 'the average of the capacity record of all rows is 9037 .'... | round_eq { avg { all_rows ; capacity } ; 9037 } = true | the average of the capacity record of all rows is 9037 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '9037_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '9037_5': '9037'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '9037_5': [1]} | ['team', 'location', 'venue', 'capacity', 'position in 2002'] | [['bate', 'borisov', 'city stadium , borisov', '5500', '1'], ['neman', 'grodno', 'neman', '6300', '2'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '3'], ['torpedo - ska', 'minsk', 'torpedo , minsk', '5200', '4'], ['torpedo', 'zhodino', 'torpedo , zhodino', '3020', '5'], ['gomel', 'gomel', 'central', '11800', '6'], ... |
2008 indian premier league | https://en.wikipedia.org/wiki/2008_Indian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15734036-10.html.csv | superlative | sanath jayasuriya was the 2008 indian premier league player who recorded the highest number of balls . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', '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', 'balls'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; balls }'}, 'player'], 'result': 'sanath jayasuriya', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; balls } ; player }'}, 'sanath jayasuriya'], 'result': True... | eq { hop { argmax { all_rows ; balls } ; player } ; sanath jayasuriya } = true | select the row whose balls record of all rows is maximum . the player record of this row is sanath jayasuriya . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'balls_5': 5, 'player_6': 6, 'sanath jayasuriya_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'balls_5': 'balls', 'player_6': 'player', 'sanath jayasuriya_7': 'sanath jayasuriya'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'balls_5': [0], 'player_6': [1], 'sanath jayasuriya_7': [2]} | ['player', 'team', 'inns', 'runs', 'balls'] | [['virender sehwag', 'delhi daredevils', '14', '406', '220'], ['yusuf pathan', 'rajasthan royals', '15', '435', '243'], ['sanath jayasuriya', 'mumbai indians', '14', '514', '309'], ['yuvraj singh', 'kings xi punjab', '14', '299', '184'], ['kumar sangakkara', 'kings xi punjab', '9', '320', '198']] |
2007 - 08 portland trail blazers season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Portland_Trail_Blazers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11964047-10.html.csv | superlative | during this period of the 2007-08 portland trail blazers season , the portland trailblazers experienced their highest attendance on april 8th in their game against the los angeles lakers . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,2,4', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'april 8', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'april 8']... | and { eq { hop { argmax { all_rows ; attendance } ; date } ; april 8 } ; and { eq { hop { argmax { all_rows ; attendance } ; visitor } ; los angeles lakers } ; eq { hop { argmax { all_rows ; attendance } ; home } ; portland trail blazers } } } = true | select the row whose attendance record of all rows is maximum . the date record of this row is april 8 . the visitor record of this row is los angeles lakers . the home record of this row is portland trail blazers . | 11 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_10': 10, 'attendance_11': 11, 'date_12': 12, 'april 8_13': 13, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'visitor_14': 14, 'los angeles lakers_15': 15, 'str_eq_6': 6, 'str_hop_5': 5, 'home_16': 16, 'portland trail blazers_17': 17} | {'and_8': 'and', 'result_9': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_10': 'all_rows', 'attendance_11': 'attendance', 'date_12': 'date', 'april 8_13': 'april 8', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'visitor_14': 'visitor', 'los angeles lakers_15': '... | {'and_8': [9], 'result_9': [], 'str_eq_2': [8], 'str_hop_1': [2], 'argmax_0': [1, 3, 5], 'all_rows_10': [0], 'attendance_11': [0], 'date_12': [1], 'april 8_13': [2], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'visitor_14': [3], 'los angeles lakers_15': [4], 'str_eq_6': [7], 'str_hop_5': [6], 'home_16': [5], 'port... | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record', 'streak'] | [['april 2', 'portland trail blazers', 'l 91 - 104', 'los angeles lakers', 'bryant : 36', 'staples center 18997', '38 - 37', 'l3'], ['april 3', 'houston rockets', 'l 95 - 86', 'portland trail blazers', 'mcgrady : 35', 'rose garden 19980', '38 - 38', 'l4'], ['april 6', 'san antonio spurs', 'l 72 - 65', 'portland trail b... |
1962 - 63 segunda división | https://en.wikipedia.org/wiki/1962%E2%80%9363_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17724929-2.html.csv | superlative | the club real sociedad had the greatest positive goal difference of +33 in 1962 - 63 segunda división . | {'scope': 'all', 'col_superlative': '10', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'goal difference'], 'result': '+ 33', 'ind': 0, 'tostr': 'max { all_rows ; goal difference }', 'tointer': 'the maximum goal difference record of all rows is + 33 .'}, '+ 33'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; ... | and { eq { max { all_rows ; goal difference } ; + 33 } ; eq { hop { argmax { all_rows ; goal difference } ; club } ; real sociedad } } = true | the maximum goal difference record of all rows is + 33 . the club record of the row with superlative goal difference record is real sociedad . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'goal difference_8': 8, '+ 33_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'goal difference_11': 11, 'club_12': 12, 'real sociedad_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'goal difference_8': 'goal difference', '+ 33_9': '+ 33', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'goal difference_11': 'goal difference', 'club_12': 'club', 'real sociedad... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'goal difference_8': [0], '+ 33_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'goal difference_11': [2], 'club_12': [3], 'real sociedad_13': [4]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'pontevedra cf', '30', '41', '16', '9', '5', '44', '31', '+ 13'], ['2', 'rcd español', '30', '39', '17', '5', '8', '40', '24', '+ 16'], ['3', 'real santander', '30', '37', '15', '7', '8', '53', '39', '+ 14'], ['4', 'real sociedad', '30', '35', '14', '7', '9', '77', '44', '+ 33'], ['5', 'real gijón', '30', '34', ... |
chinese units of measurement | https://en.wikipedia.org/wiki/Chinese_units_of_measurement | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-147235-16.html.csv | comparative | the loeng2 chinese unit of measurement has a lower imperial value than the daam3 chinese unit of measurement . | {'row_1': '4', 'row_2': '6', 'col': '6', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'jyutping', 'loeng2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose jyutping record fuzzily matches to loeng2 .', 'tostr': 'filter_eq { all_rows ; jyutping ; loeng2 }'}, 'imperial value'], 'result': None... | less { hop { filter_eq { all_rows ; jyutping ; loeng2 } ; imperial value } ; hop { filter_eq { all_rows ; jyutping ; daam3 } ; imperial value } } = true | select the rows whose jyutping record fuzzily matches to loeng2 . take the imperial value record of this row . select the rows whose jyutping record fuzzily matches to daam3 . take the imperial value record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'jyutping_7': 7, 'loeng2_8': 8, 'imperial value_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'jyutping_11': 11, 'daam3_12': 12, 'imperial value_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'jyutping_7': 'jyutping', 'loeng2_8': 'loeng2', 'imperial value_9': 'imperial value', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'jyutping_11': 'jyutpi... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'jyutping_7': [0], 'loeng2_8': [0], 'imperial value_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'jyutping_11': [1], 'daam3_12': [1], 'imperial value_13': [3]} | ['jyutping', 'character', 'portuguese', 'relative value', 'metric value', 'imperial value'] | [['lei4', '厘', 'liz', '1 / 1600', '37.79931 mg', '~ 0.2133 dr'], ['fan1', '分', 'condorim', '1 / 1600', '377.9936375 mg', '~ 0.2133 dr'], ['cin4', '錢', 'maz', '1 / 160', '3.779936375 g', '~ 2.1333 dr'], ['loeng2', '兩', 'tael', '1 / 16', '37.79936375 g', '~ 1.3333 oz'], ['gan1', '斤', 'cate', '1', '604.78982 g', '~ 1.3333... |
colts - patriots rivalry | https://en.wikipedia.org/wiki/Colts%E2%80%93Patriots_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13342861-3.html.csv | aggregation | in 1978 the new england patriots scored a total of 62 points against the baltimore colts . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '62', 'subset': {'col': '1', 'criterion': 'equal', 'value': '1978'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1978'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 1978 }', 'tointer': 'select the rows whose year record is equal to 1978 .'}, 'result'], 'result': '62', 'ind': 1, 'tostr': 'sum { filter_eq... | round_eq { sum { filter_eq { all_rows ; year ; 1978 } ; result } ; 62 } = true | select the rows whose year record is equal to 1978 . the sum of the result record of these rows is 62 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '1978_6': 6, 'result_7': 7, '62_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '1978_6': '1978', 'result_7': 'result', '62_8': '62'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '1978_6': [0], 'result_7': [1], '62_8': [2]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['1970', 'october 4', 'baltimore colts', '14 - 6', 'boston patriots', 'harvard stadium'], ['1970', 'october 25', 'baltimore colts', '27 - 3', 'boston patriots', 'memorial stadium ( baltimore )'], ['1971', 'october 3', 'baltimore colts', '23 - 3', 'new england patriots', 'schaefer stadium'], ['1971', 'december 19', 'ne... |
iran at the 2007 asian indoor games | https://en.wikipedia.org/wiki/Iran_at_the_2007_Asian_Indoor_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14350710-31.html.csv | count | three competitors for iran at the 2007 asian indoor games did not advance to the final . | {'scope': 'all', 'criterion': 'equal', 'value': 'did not advance', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'final', 'did not advance'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose final record fuzzily matches to did not advance .', 'tostr': 'filter_eq { all_rows ; final ; did not advance }'}], 'result': '3', 'in... | eq { count { filter_eq { all_rows ; final ; did not advance } } ; 3 } = true | select the rows whose final record fuzzily matches to did not advance . 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, 'final_5': 5, 'did not advance_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', 'final_5': 'final', 'did not advance_6': 'did not advance', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'final_5': [0], 'did not advance_6': [0], '3_7': [2]} | ['athlete', 'event', 'quarterfinal', 'semifinal', 'final'] | [['ali ekranpour', '63.5 kg', 'did not advance', 'did not advance', 'did not advance'], ['jalal motamedi', '67 kg', 'ng ( mac ) w 5 - 0', 'kahhorov ( uzb ) l 0 - 5', 'did not advance'], ['vahid roshani', '71 kg', 'jawad ( irq ) w 5 - 0', 'shetty ( ind ) w rsch', 'kadirkulov ( uzb ) l 1 - 4'], ['mostafa abdollahi', '75 ... |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-22.html.csv | ordinal | john conyers jr recorded the highest percentage ratio among all candidates of the 2000 house of representatives elections . | {'row': '10', 'col': '6', 'order': '1', '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', 'candidates', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; candidates ; 1 }'}, 'incumbent'], 'result': 'john conyers jr', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbe... | eq { hop { nth_argmax { all_rows ; candidates ; 1 } ; incumbent } ; john conyers jr } = true | select the row whose candidates record of all rows is 1st maximum . the incumbent record of this row is john conyers jr . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, '1_6': 6, 'incumbent_7': 7, 'john conyers jr_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', 'candidates_5': 'candidates', '1_6': '1', 'incumbent_7': 'incumbent', 'john conyers jr_8': 'john conyers jr'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], '1_6': [0], 'incumbent_7': [1], 'john conyers jr_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['michigan 1', 'bart stupak', 'democratic', '1992', 're - elected', 'bart stupak ( d ) 59 % chuck yob ( r ) 41 %'], ['michigan 2', 'pete hoekstra', 'republican', '1992', 're - elected', 'pete hoekstra ( r ) 65 % bob shrauger ( d ) 34 %'], ['michigan 3', 'vern ehlers', 'republican', '1993', 're - elected', 'vern ehlers... |
2008 - 09 detroit pistons season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Detroit_Pistons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17325937-5.html.csv | aggregation | the average number of points the detroit pistons scored in the 2008-09 season was 97.3 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '97.3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '97.3', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '97.3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 97.3 } = true', 'tointer': 'the average of the score record of all rows is 97.3 .'} | round_eq { avg { all_rows ; score } ; 97.3 } = true | the average of the score record of all rows is 97.3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '97.3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '97.3_5': '97.3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '97.3_5': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['2', 'november 1', 'washington', 'w 117 - 109 ( ot )', 'richard hamilton ( 24 )', 'rasheed wallace ( 12 )', 'chauncey billups ( 8 )', 'the palace of auburn hills 22076', '2 - 0'], ['3', 'november 3', 'charlotte', 'w 101 - 83 ( ot )', 'richard hamilton ( 19 )', 'kwame brown ( 9 )', 'richard hamilton ( 5 )', 'time warn... |
united states house of representatives elections , 1968 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1968 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341738-34.html.csv | count | there were two districts in north carolina that did not have a current incumbent for the 1968 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 'none ( district created )', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'none ( district created )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to none ( district created ) .', 'tostr': 'filter_eq { all_rows ; incumbent ; none ( d... | eq { count { filter_eq { all_rows ; incumbent ; none ( district created ) } } ; 2 } = true | select the rows whose incumbent record fuzzily matches to none ( district created ) . 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, 'incumbent_5': 5, 'none (district created)_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', 'incumbent_5': 'incumbent', 'none (district created)_6': 'none ( district created )', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'incumbent_5': [0], 'none (district created)_6': [0], '2_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'lawrence h fountain', 'democratic', '1952', 're - elected', 'lawrence h fountain ( d ) unopposed'], ['north carolina 2', 'james carson gardner redistricted from 4th', 'republican', '1966', 'retired to run for governor republican loss', 'lawrence h fountain ( d ) unopposed'], ['north carolina 4', ... |
2008 - 09 atlanta hawks season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17311759-9.html.csv | ordinal | the atlanta hawks ' game against orlando recorded the highest attendance of the 2008 - 09 season . | {'row': '2', 'col': '8', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'location attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 1 }'}, 'team'], 'result': 'orlando', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ;... | eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; orlando } = true | select the row whose location attendance record of all rows is 1st maximum . the team record of this row is orlando . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '1_6': 6, 'team_7': 7, 'orlando_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', 'location attendance_5': 'location attendance', '1_6': '1', 'team_7': 'team', 'orlando_8': 'orlando'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '1_6': [0], 'team_7': [1], 'orlando_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 3', 'boston', 'l 92 - 104 ( ot )', 'ronald murray ( 21 )', 'josh smith ( 10 )', 'mike bibby ( 6 )', 'td banknorth garden 18624', '43 - 33'], ['77', 'april 4', 'orlando', 'l 82 - 88 ( ot )', 'joe johnson ( 21 )', 'al horford ( 13 )', 'mike bibby ( 5 )', 'philips arena 19608', '43 - 34'], ['78', 'april 7',... |
adriano leite ribeiro | https://en.wikipedia.org/wiki/Adriano_Leite_Ribeiro | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1142467-2.html.csv | superlative | adriano leite ribeiro 's highest scoring season was in 2005-2006 with 8 goals . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', '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', 'goals'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; goals }'}, 'season'], 'result': '2005 - 2006', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; goals } ; season }'}, '2005 - 2006'], 'result': True, 'ind': 2, ... | eq { hop { argmax { all_rows ; goals } ; season } ; 2005 - 2006 } = true | select the row whose goals record of all rows is maximum . the season record of this row is 2005 - 2006 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'goals_5': 5, 'season_6': 6, '2005 - 2006_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'goals_5': 'goals', 'season_6': 'season', '2005 - 2006_7': '2005 - 2006'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'goals_5': [0], 'season_6': [1], '2005 - 2006_7': [2]} | ['national team', 'club', 'season', 'apps', 'goals'] | [['brazil', 'flamengo', '2000', '1', '0'], ['brazil', 'flamengo', '2001', '0', '0'], ['brazil', 'internazionale', '2001 - 2002', '0', '0'], ['brazil', 'fiorentina', '2001 - 2002', '0', '0'], ['brazil', 'parma', '2002 - 2003', '5', '3'], ['brazil', 'parma', '2003 - 2004', '1', '0'], ['brazil', 'internazionale', '2003 - ... |
list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-2.html.csv | superlative | novi sad is the urban settlement in vojvodina that had the highest population in 2002 . | {'scope': 'all', 'col_superlative': '6', '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', 'population ( 2002 )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; population ( 2002 ) }'}, 'urban settlement'], 'result': 'novi sad', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; population ( 2002 ) } ; urban... | eq { hop { argmax { all_rows ; population ( 2002 ) } ; urban settlement } ; novi sad } = true | select the row whose population ( 2002 ) record of all rows is maximum . the urban settlement record of this row is novi sad . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'population (2002)_5': 5, 'urban settlement_6': 6, 'novi sad_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'population (2002)_5': 'population ( 2002 )', 'urban settlement_6': 'urban settlement', 'novi sad_7': 'novi sad'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'population (2002)_5': [0], 'urban settlement_6': [1], 'novi sad_7': [2]} | ['urban settlement', 'cyrillic name', 'city / municipality', 'district', 'population ( 1991 )', 'population ( 2002 )', 'population ( 2011 )'] | [['bač', 'бач', 'bač', 'south bačka', '6046', '6087', '5399'], ['bačka palanka', 'бачка паланка', 'bačka palanka', 'south bačka', '26780', '29449', '28239'], ['bački jarak', 'бачки јарак', 'temerin', 'south bačka', '5426', '6049', '5687'], ['bački petrovac', 'бачки петровац', 'bački petrovac', 'south bačka', '7236', '6... |
jean - pierre beltoise | https://en.wikipedia.org/wiki/Jean-Pierre_Beltoise | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226341-2.html.csv | majority | in most of the years that jean - pierre beltoise competed , he was ranked lowered than 10th . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'rank', '10'], 'result': True, 'ind': 0, 'tointer': 'for the rank records of all rows , most of them are greater than 10 .', 'tostr': 'most_greater { all_rows ; rank ; 10 } = true'} | most_greater { all_rows ; rank ; 10 } = true | for the rank records of all rows , most of them are greater than 10 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'rank_3': 3, '10_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'rank_3': 'rank', '10_4': '10'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'rank_3': [0], '10_4': [0]} | ['year', 'class', 'team', 'points', 'rank', 'wins'] | [['1962', '250cc', 'moto morini', '2', '20th', '0'], ['1963', '50cc', 'kreidler', '3', '11th', '0'], ['1963', '125cc', 'bultaco', '1', '20th', '0'], ['1964', '50cc', 'kreidler', '6', '6th', '0'], ['1964', '125cc', 'bultaco', '4', '13th', '0']] |
2007 bombardier learjet 550 | https://en.wikipedia.org/wiki/2007_Bombardier_Learjet_550 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17319931-1.html.csv | superlative | sam hornish , jr was the driver that led the highest amount of laps in the 2007 bombardier learjet 550 . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'laps led'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; laps led }'}, 'driver'], 'result': 'sam hornish , jr', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; laps led } ; driver }'}, 'sam hornish , jr'], 'result... | eq { hop { argmax { all_rows ; laps led } ; driver } ; sam hornish , jr } = true | select the row whose laps led record of all rows is maximum . the driver record of this row is sam hornish , jr . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'laps led_5': 5, 'driver_6': 6, 'sam hornish , jr_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'laps led_5': 'laps led', 'driver_6': 'driver', 'sam hornish , jr_7': 'sam hornish , jr'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'laps led_5': [0], 'driver_6': [1], 'sam hornish , jr_7': [2]} | ['fin pos', 'car no', 'driver', 'team', 'laps', 'time / retired', 'grid', 'laps led', 'points'] | [['1', '6', 'sam hornish , jr', 'team penske', '228', '1:52:15.2873', '2', '159', '50 + 3'], ['2', '11', 'tony kanaan', 'andretti green', '228', '+ 0.0786', '4', '1', '40'], ['3', '7', 'danica patrick', 'andretti green', '228', '+ 0.3844', '6', '2', '35'], ['4', '27', 'dario franchitti', 'andretti green', '228', '+ 3.9... |
ohio river valley conference | https://en.wikipedia.org/wiki/Ohio_River_Valley_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18717975-2.html.csv | ordinal | north ( madison ) was the first school to leave the ohio river valley conference . | {'row': '2', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year left', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year left ; 1 }'}, 'school'], 'result': 'north ( madison )', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year left ; 1 } ; school }'},... | eq { hop { nth_argmin { all_rows ; year left ; 1 } ; school } ; north ( madison ) } = true | select the row whose year left record of all rows is 1st minimum . the school record of this row is north ( madison ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year left_5': 5, '1_6': 6, 'school_7': 7, 'north (madison)_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', 'year left_5': 'year left', '1_6': '1', 'school_7': 'school', 'north (madison)_8': 'north ( madison )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year left_5': [0], '1_6': [0], 'school_7': [1], 'north (madison)_8': [2]} | ['school', 'location', 'mascot', 'county', 'year joined', 'year left', 'conference joined'] | [['hanover', 'hanover', 'bulldogs', '39 jefferson', '1952', '1960', 'none ( consolidated into southwestern )'], ['north ( madison )', 'madison', 'tigers', '39 jefferson', '1952', '1953', 'none ( colsolidated into madison )'], ['osgood', 'osgood', 'cowboys', '69 ripley', '1952', '1960', 'none ( consolidated into jac - c... |
mohammed nasser shakroun | https://en.wikipedia.org/wiki/Mohammed_Nasser_Shakroun | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13607991-4.html.csv | ordinal | mohammed nasser shakroun scored his second international goal at the bahrain national stadium . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'venue'], 'result': 'bahrain national stadium , manama', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; venue }'}, ... | eq { hop { nth_argmin { all_rows ; date ; 2 } ; venue } ; bahrain national stadium , manama } = true | select the row whose date record of all rows is 2nd minimum . the venue record of this row is bahrain national stadium , manama . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'venue_7': 7, 'bahrain national stadium , manama_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'venue_7': 'venue', 'bahrain national stadium , manama_8': 'bahrain national stadium , manama'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'venue_7': [1], 'bahrain national stadium , manama_8': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['26 march 2005', 'telstra stadium , sydney', '1 - 0', '1 - 2', 'friendly match'], ['7 august 2005', 'bahrain national stadium , manama', '1 - 2', '2 - 2', 'friendly match'], ['13 august 2005', 'tsirion stadium , limassol', '1 - 0', '2 - 1', 'friendly match'], ['15 march 2006', 'prince abdullah al - faisal stadium , j... |
baltimore clippers | https://en.wikipedia.org/wiki/Baltimore_Clippers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2817196-1.html.csv | aggregation | between 1973 and 1976 , the baltimore clippers won a total of 77 games . | {'scope': 'subset', 'col': '3', 'type': 'sum', 'result': '77', 'subset': {'col': '1', 'criterion': 'greater_than_eq', 'value': '1973'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'season', '1973'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; season ; 1973 }', 'tointer': 'select the rows whose season record is greater than or equal to 1973 .'}, 'won'], 'result': '77', ... | round_eq { sum { filter_greater_eq { all_rows ; season ; 1973 } ; won } ; 77 } = true | select the rows whose season record is greater than or equal to 1973 . the sum of the won record of these rows is 77 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'season_5': 5, '1973_6': 6, 'won_7': 7, '77_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'season_5': 'season', '1973_6': '1973', 'won_7': 'won', '77_8': '77'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'season_5': [0], '1973_6': [0], 'won_7': [1], '77_8': [2]} | ['season', 'games', 'won', 'lost', 'tied', 'points', 'goals for', 'goals against', 'standing', 'head coaches'] | [['1962 - 63', '72', '35', '30', '7', '77', '226', '244', '3rd , east', 'red sullivan / aldo guidolin'], ['1963 - 64', '72', '32', '37', '3', '67', '200', '220', '4th , east', 'aldo guidolin'], ['1964 - 65', '72', '35', '32', '5', '75', '275', '249', '3rd , east', 'john crawford'], ['1965 - 66', '72', '27', '43', '2', ... |
1991 - 92 in argentine football | https://en.wikipedia.org/wiki/1991%E2%80%9392_in_Argentine_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14390413-1.html.csv | ordinal | the boca juniors team recorded the 2nd highest average in the 1991 - 92 argentine football season . | {'row': '2', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'average', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; average ; 2 }'}, 'team'], 'result': 'boca juniors', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; average ; 2 } ; team }'}, 'boca juniors'... | eq { hop { nth_argmax { all_rows ; average ; 2 } ; team } ; boca juniors } = true | select the row whose average record of all rows is 2nd maximum . the team record of this row is boca juniors . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'average_5': 5, '2_6': 6, 'team_7': 7, 'boca juniors_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', 'average_5': 'average', '2_6': '2', 'team_7': 'team', 'boca juniors_8': 'boca juniors'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'average_5': [0], '2_6': [0], 'team_7': [1], 'boca juniors_8': [2]} | ['team', 'average', 'points', 'played', '1989 - 90', '1990 - 91', '1991 - 1992'] | [['river plate', '1.342', '153', '114', '53', '45', '55'], ['boca juniors', '1.263', '144', '114', '43', '51', '50'], ['vélez sársfield', '1.184', '135', '114', '42', '45', '48'], ["newell 's old boys", '1.123', '128', '114', '36', '48', '44'], ['independiente', '1.070', '122', '114', '46', '40', '36'], ['racing club',... |
utah jazz all - time roster | https://en.wikipedia.org/wiki/Utah_Jazz_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11545282-13.html.csv | majority | all of the players on the utah jazz all - time roster are from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', '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]} | ['player', 'nationality', 'position', 'years for jazz', 'school / club team'] | [['jeff malone', 'united states', 'shooting guard', '1991 - 94', 'mississippi state'], ['karl malone', 'united states', 'power forward', '1985 - 03', 'louisiana tech'], ['danny manning', 'united states', 'combo forward', '2000 - 01', 'kansas'], ['pace mannion', 'united states', 'guard - forward', '1984 - 86', 'utah'], ... |
1971 vfl season | https://en.wikipedia.org/wiki/1971_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10826072-22.html.csv | ordinal | hawthorn had the 2nd highest home team score in the 1971 vfl season . | {'row': '1', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'home team score', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; home team score ; 2 }'}, 'home team'], 'result': 'hawthorn', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; home team score ; 2 } ;... | eq { hop { nth_argmax { all_rows ; home team score ; 2 } ; home team } ; hawthorn } = true | select the row whose home team score record of all rows is 2nd maximum . the home team record of this row is hawthorn . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'home team score_5': 5, '2_6': 6, 'home team_7': 7, 'hawthorn_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', 'home team score_5': 'home team score', '2_6': '2', 'home team_7': 'home team', 'hawthorn_8': 'hawthorn'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'home team score_5': [0], '2_6': [0], 'home team_7': [1], 'hawthorn_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '18.16 ( 124 )', 'melbourne', '8.17 ( 65 )', 'glenferrie oval', '14809', '28 august 1971'], ['footscray', '10.14 ( 74 )', 'st kilda', '12.18 ( 90 )', 'western oval', '16707', '28 august 1971'], ['essendon', '12.12 ( 84 )', 'fitzroy', '13.17 ( 95 )', 'windy hill', '12865', '28 august 1971'], ['carlton', '1... |
2003 u.s. open ( golf ) | https://en.wikipedia.org/wiki/2003_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16292316-1.html.csv | comparative | tom watson had won a u.s. open ( golf ) championship earlier than retief goosen . | {'row_1': '3', 'row_2': '4', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'tom watson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to tom watson .', 'tostr': 'filter_eq { all_rows ; player ; tom watson }'}, 'year ( s ) won'], 'result'... | less { hop { filter_eq { all_rows ; player ; tom watson } ; year ( s ) won } ; hop { filter_eq { all_rows ; player ; retief goosen } ; year ( s ) won } } = true | select the rows whose player record fuzzily matches to tom watson . take the year ( s ) won record of this row . select the rows whose player record fuzzily matches to retief goosen . take the year ( s ) won record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'tom watson_8': 8, 'year (s) won_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'retief goosen_12': 12, 'year (s) won_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'tom watson_8': 'tom watson', 'year (s) won_9': 'year ( s ) won', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'tom watson_8': [0], 'year (s) won_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'retief goosen_12': [1], 'year (s) won_13': [3]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['ernie els', 'south africa', '1994 , 1997', '280', 'e', 't5'], ['tiger woods', 'united states', '2000 , 2002', '283', '+ 3', 't20'], ['tom watson', 'united states', '1982', '284', '+ 4', 't28'], ['retief goosen', 'south africa', '2001', '286', '+ 6', 't42'], ['lee janzen', 'united states', '1993 , 1998', '289', '+ 9'... |
list of highest - grossing bollywood films | https://en.wikipedia.org/wiki/List_of_highest-grossing_Bollywood_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11872185-1.html.csv | superlative | ek tha tiger was the highest-grossing bollywood film of 2012 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': {'col': '3', 'criterion': 'equal', 'value': '2012'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2012'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 2012 }', 'tointer': 'select the rows whose year record is equal to 2012 .'}, 'worldwide gross'], 'result': No... | eq { hop { argmax { filter_eq { all_rows ; year ; 2012 } ; worldwide gross } ; movie } ; ek tha tiger } = true | select the rows whose year record is equal to 2012 . select the row whose worldwide gross record of these rows is maximum . the movie record of this row is ek tha tiger . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_eq_0': 0, 'all_rows_5': 5, 'year_6': 6, '2012_7': 7, 'worldwide gross_8': 8, 'movie_9': 9, 'ek tha tiger_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_eq_0': 'filter_eq', 'all_rows_5': 'all_rows', 'year_6': 'year', '2012_7': '2012', 'worldwide gross_8': 'worldwide gross', 'movie_9': 'movie', 'ek tha tiger_10': 'ek tha tiger'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_eq_0': [1], 'all_rows_5': [0], 'year_6': [0], '2012_7': [0], 'worldwide gross_8': [1], 'movie_9': [2], 'ek tha tiger_10': [3]} | ['rank', 'movie', 'year', 'worldwide gross', 'director', 'verdict'] | [['1', '3 idiots', '2009', '392 crore', 'rajkumar hirani', 'all time blockbuster'], ['2', 'chennai express', '2013', '314 crore', 'rohit shetty', 'blockbuster'], ['3', 'ek tha tiger', '2012', '310 crore', 'kabir khan', 'blockbuster'], ['4', 'yeh jawaani hai deewani', '2013', '301 crore', 'ayan mukerji', 'blockbuster'],... |
united states house of representatives elections , 1950 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1950 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342198-36.html.csv | majority | all of the incumbents in the 1950 house of representatives elections were from the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'} | all_eq { all_rows ; party ; democratic } = true | for the party records of all rows , all of them fuzzily match to democratic . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['oklahoma 1', 'dixie gilmer', 'democratic', '1948', 'lost re - election republican gain', 'george b schwabe ( r ) 52.9 % dixie gilmer ( d ) 47.1 %'], ['oklahoma 2', 'william g stigler', 'democratic', '1944', 're - elected', 'william g stigler ( d ) 66.2 % cleo crain ( r ) 33.8 %'], ['oklahoma 3', 'carl albert', 'demo... |
1979 miami dolphins season | https://en.wikipedia.org/wiki/1979_Miami_Dolphins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18847736-2.html.csv | superlative | the new york jets scored the most points against the dolphins . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '16', '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', 'opponents'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; opponents }'}, 'opponent'], 'result': 'new york jets', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; opponents } ; opponent }'}, 'new york jets'], 'resul... | eq { hop { argmax { all_rows ; opponents } ; opponent } ; new york jets } = true | select the row whose opponents record of all rows is maximum . the opponent record of this row is new york jets . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'opponents_5': 5, 'opponent_6': 6, 'new york jets_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'opponents_5': 'opponents', 'opponent_6': 'opponent', 'new york jets_7': 'new york jets'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'opponents_5': [0], 'opponent_6': [1], 'new york jets_7': [2]} | ['game', 'date', 'opponent', 'result', 'dolphins points', 'opponents', 'record', 'attendance'] | [['1', 'sept 2', 'buffalo bills', 'win', '9', '7', '1 - 0', '69441'], ['2', 'sept 9', 'seattle seahawks', 'win', '19', '10', '2 - 0', '56233'], ['3', 'sept 16', 'minnesota vikings', 'win', '27', '12', '3 - 0', '46187'], ['4', 'sept 23', 'chicago bears', 'win', '31', '16', '4 - 0', '66011'], ['5', 'sept 30', 'new york j... |
1963 vfl season | https://en.wikipedia.org/wiki/1963_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10783853-8.html.csv | superlative | essendon had the highest scoring game out of all the teams . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'home team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; home team score }'}, 'home team'], 'result': 'essendon', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; home team score } ; home team }'}, 'essendon... | eq { hop { argmax { all_rows ; home team score } ; home team } ; essendon } = true | select the row whose home team score record of all rows is maximum . the home team record of this row is essendon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'home team score_5': 5, 'home team_6': 6, 'essendon_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'home team score_5': 'home team score', 'home team_6': 'home team', 'essendon_7': 'essendon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'home team score_5': [0], 'home team_6': [1], 'essendon_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '13.11 ( 89 )', 'richmond', '7.5 ( 47 )', 'windy hill', '21200', '8 june 1963'], ['carlton', '6.8 ( 44 )', 'collingwood', '6.10 ( 46 )', 'princes park', '38698', '8 june 1963'], ['st kilda', '8.13 ( 61 )', 'hawthorn', '9.11 ( 65 )', 'junction oval', '34900', '8 june 1963'], ['footscray', '6.16 ( 52 )', 's... |
arkansas rimrockers | https://en.wikipedia.org/wiki/Arkansas_RimRockers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1806054-1.html.csv | comparative | the arkansas rimrockers recorded a higher number of wins in the 2005-06 season than they did in the 2006-07 season . | {'row_1': '3', 'row_2': '4', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2005 - 06'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2005 - 06 .', 'tostr': 'filter_eq { all_rows ; season ; 2005 - 06 }'}, 'wins'], 'result': None, 'i... | greater { hop { filter_eq { all_rows ; season ; 2005 - 06 } ; wins } ; hop { filter_eq { all_rows ; season ; 2006 - 07 } ; wins } } = true | select the rows whose season record fuzzily matches to 2005 - 06 . take the wins record of this row . select the rows whose season record fuzzily matches to 2006 - 07 . take the wins 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, 'season_7': 7, '2005 - 06_8': 8, 'wins_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2006 - 07_12': 12, 'wins_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', 'season_7': 'season', '2005 - 06_8': '2005 - 06', 'wins_9': 'wins', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2006 - 07_... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2005 - 06_8': [0], 'wins_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2006 - 07_12': [1], 'wins_13': [3]} | ['season', 'league', 'finish', 'wins', 'losses', 'pct'] | [['arkansas rimrockers', 'arkansas rimrockers', 'arkansas rimrockers', 'arkansas rimrockers', 'arkansas rimrockers', 'arkansas rimrockers'], ['2004 - 05', 'aba', '1st', '28', '5', '848'], ['2005 - 06', 'd - league', '5th', '24', '24', '500'], ['2006 - 07', 'd - league', '6th', '16', '34', '320'], ['regular season', 're... |
1922 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1922_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18007045-1.html.csv | count | in the 1922 u.s. open , two of the players were from scotland . | {'scope': 'all', 'criterion': 'equal', 'value': 'scotland', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'scotland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to scotland .', 'tostr': 'filter_eq { all_rows ; country ; scotland }'}], 'result': '2', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; country ; scotland } } ; 2 } = true | select the rows whose country record fuzzily matches to scotland . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'scotland_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'scotland_6': 'scotland', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'scotland_6': [0], '2_7': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'gene sarazen', 'united states', '72 + 73 + 75 + 68 = 288', '+ 8', '500'], ['t2', 'john black', 'scotland', '71 + 71 + 75 + 72 = 289', '+ 9', '300'], ['t2', 'bobby jones ( a )', 'united states', '74 + 72 + 70 + 73 = 289', '+ 9', '0'], ['4', 'bill mehlhorn', 'united states', '73 + 71 + 72 + 74 = 290', '+ 10', '20... |
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