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list of records in the national youth competition ( rugby league ) | https://en.wikipedia.org/wiki/List_of_records_in_the_National_Youth_Competition_%28rugby_league%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16802194-3.html.csv | comparative | the game played on 6 june 2010 had a higher total score than the game played on 5 april 2008 . | {'row_1': '3', 'row_2': '1', 'col': '1', 'col_other': '6', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '6 june 2010 ( round 13 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 6 june 2010 ( round 13 ) .', 'tostr': 'filter_eq { all_rows ; date ; 6 june 2010 ( round 13 ) }'}, 'total'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 6 june 2010 ( round 13 ) } ; total }', 'tointer': 'select the rows whose date record fuzzily matches to 6 june 2010 ( round 13 ) . take the total record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '5 april 2008 ( round 4 )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 5 april 2008 ( round 4 ) .', 'tostr': 'filter_eq { all_rows ; date ; 5 april 2008 ( round 4 ) }'}, 'total'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 5 april 2008 ( round 4 ) } ; total }', 'tointer': 'select the rows whose date record fuzzily matches to 5 april 2008 ( round 4 ) . take the total record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; 6 june 2010 ( round 13 ) } ; total } ; hop { filter_eq { all_rows ; date ; 5 april 2008 ( round 4 ) } ; total } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 6 june 2010 ( round 13 ) . take the total record of this row . select the rows whose date record fuzzily matches to 5 april 2008 ( round 4 ) . take the total record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; 6 june 2010 ( round 13 ) } ; total } ; hop { filter_eq { all_rows ; date ; 5 april 2008 ( round 4 ) } ; total } } = true | select the rows whose date record fuzzily matches to 6 june 2010 ( round 13 ) . take the total record of this row . select the rows whose date record fuzzily matches to 5 april 2008 ( round 4 ) . 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, 'date_7': 7, '6 june 2010 (round 13)_8': 8, 'total_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '5 april 2008 (round 4)_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', 'date_7': 'date', '6 june 2010 (round 13)_8': '6 june 2010 ( round 13 )', 'total_9': 'total', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '5 april 2008 (round 4)_12': '5 april 2008 ( round 4 )', 'total_13': 'total'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '6 june 2010 (round 13)_8': [0], 'total_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '5 april 2008 (round 4)_12': [1], 'total_13': [3]} | ['total', 'score', 'winning team', 'losing team', 'venue', 'date'] | [['10', '6 - 4', 'st george illawarra dragons', 'cronulla sharks', 'anz stadium', '5 april 2008 ( round 4 )'], ['17', '9 - 8', 'cronulla sharks', 'manly sea eagles', 'toyota park', '12 july 2008 ( round 18 )'], ['19', '19 - 0', 'new zealand warriors', 'st george illawarra dragons', 'mt smart stadium', '6 june 2010 ( round 13 )'], ['24', '14 - 10', 'sydney roosters', 'south sydney rabbitohs', 'anz stadium', '14 march 2008 ( round 1 )'], ['24', '14 - 10', 'north queensland cowboys', 'melbourne storm', 'olympic park', '21 june 2008 ( round 15 )']] |
wheelchair tennis at the 2008 summer paralympics | https://en.wikipedia.org/wiki/Wheelchair_tennis_at_the_2008_Summer_Paralympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18403681-1.html.csv | count | four different nations won one bronze medal in wheelchair tennis , at the 2008 summer paralympics . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'bronze', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bronze record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; bronze ; 1 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; bronze ; 1 } }', 'tointer': 'select the rows whose bronze record is equal to 1 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; bronze ; 1 } } ; 4 } = true', 'tointer': 'select the rows whose bronze record is equal to 1 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; bronze ; 1 } } ; 4 } = true | select the rows whose bronze record is equal to 1 . 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, 'bronze_5': 5, '1_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', '1_6': '1', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '1_6': [0], '4_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'netherlands ( ned )', '2', '3', '1', '6'], ['2', 'france ( fra )', '1', '0', '2', '3'], ['3', 'great britain ( gbr )', '1', '0', '1', '2'], ['3', 'japan ( jpn )', '1', '0', '1', '2'], ['3', 'united states ( usa )', '1', '0', '1', '2'], ['6', 'sweden ( swe )', '0', '2', '0', '2'], ['7', 'israel ( isr )', '0', '1', '0', '1'], ['total', 'total', '6', '6', '6', '18']] |
united airways | https://en.wikipedia.org/wiki/United_Airways | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11529564-2.html.csv | comparative | united airway 's barisal and chittagong both have the same city of operation , bangladesh . | {'row_1': '2', 'row_2': '3', 'col': '2', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'barisal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city record fuzzily matches to barisal .', 'tostr': 'filter_eq { all_rows ; city ; barisal }'}, 'country'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; city ; barisal } ; country }', 'tointer': 'select the rows whose city record fuzzily matches to barisal . take the country record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'chittagong'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose city record fuzzily matches to chittagong .', 'tostr': 'filter_eq { all_rows ; city ; chittagong }'}, 'country'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; city ; chittagong } ; country }', 'tointer': 'select the rows whose city record fuzzily matches to chittagong . take the country record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; city ; barisal } ; country } ; hop { filter_eq { all_rows ; city ; chittagong } ; country } }', 'tointer': 'select the rows whose city record fuzzily matches to barisal . take the country record of this row . select the rows whose city record fuzzily matches to chittagong . take the country record of this row . the first record fuzzily matches to the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'barisal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city record fuzzily matches to barisal .', 'tostr': 'filter_eq { all_rows ; city ; barisal }'}, 'country'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; city ; barisal } ; country }', 'tointer': 'select the rows whose city record fuzzily matches to barisal . take the country record of this row .'}, 'bangladesh'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; city ; barisal } ; country } ; bangladesh }', 'tointer': 'the country record of the first row is bangladesh .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'chittagong'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose city record fuzzily matches to chittagong .', 'tostr': 'filter_eq { all_rows ; city ; chittagong }'}, 'country'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; city ; chittagong } ; country }', 'tointer': 'select the rows whose city record fuzzily matches to chittagong . take the country record of this row .'}, 'bangladesh'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; city ; chittagong } ; country } ; bangladesh }', 'tointer': 'the country record of the second row is bangladesh .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; city ; barisal } ; country } ; bangladesh } ; eq { hop { filter_eq { all_rows ; city ; chittagong } ; country } ; bangladesh } }', 'tointer': 'the country record of the first row is bangladesh . the country record of the second row is bangladesh .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; city ; barisal } ; country } ; hop { filter_eq { all_rows ; city ; chittagong } ; country } } ; and { eq { hop { filter_eq { all_rows ; city ; barisal } ; country } ; bangladesh } ; eq { hop { filter_eq { all_rows ; city ; chittagong } ; country } ; bangladesh } } } = true', 'tointer': 'select the rows whose city record fuzzily matches to barisal . take the country record of this row . select the rows whose city record fuzzily matches to chittagong . take the country record of this row . the first record fuzzily matches to the second record . the country record of the first row is bangladesh . the country record of the second row is bangladesh .'} | and { eq { hop { filter_eq { all_rows ; city ; barisal } ; country } ; hop { filter_eq { all_rows ; city ; chittagong } ; country } } ; and { eq { hop { filter_eq { all_rows ; city ; barisal } ; country } ; bangladesh } ; eq { hop { filter_eq { all_rows ; city ; chittagong } ; country } ; bangladesh } } } = true | select the rows whose city record fuzzily matches to barisal . take the country record of this row . select the rows whose city record fuzzily matches to chittagong . take the country record of this row . the first record fuzzily matches to the second record . the country record of the first row is bangladesh . the country record of the second row is bangladesh . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'city_11': 11, 'barisal_12': 12, 'country_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'city_15': 15, 'chittagong_16': 16, 'country_17': 17, 'and_7': 7, 'str_eq_5': 5, 'bangladesh_18': 18, 'str_eq_6': 6, 'bangladesh_19': 19} | {'and_8': 'and', 'result_9': 'true', 'str_eq_4': 'str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'city_11': 'city', 'barisal_12': 'barisal', 'country_13': 'country', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'city_15': 'city', 'chittagong_16': 'chittagong', 'country_17': 'country', 'and_7': 'and', 'str_eq_5': 'str_eq', 'bangladesh_18': 'bangladesh', 'str_eq_6': 'str_eq', 'bangladesh_19': 'bangladesh'} | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'city_11': [0], 'barisal_12': [0], 'country_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'city_15': [1], 'chittagong_16': [1], 'country_17': [3], 'and_7': [8], 'str_eq_5': [7], 'bangladesh_18': [5], 'str_eq_6': [7], 'bangladesh_19': [6]} | ['city', 'country', 'airport', 'iata', 'icao'] | [['bangkok', 'thailand', 'suvarnabhumi airport', 'bkk', 'vtbs'], ['barisal', 'bangladesh', 'barisal airport', 'bzl', 'vgbr'], ['chittagong', 'bangladesh', 'shah amanat international airport', 'cgp', 'vgeg'], ["cox 's bazar", 'bangladesh', "cox 's bazar airport", 'cxb', 'vgcb'], ['dhaka', 'bangladesh', 'shahjalal international airport', 'dac', 'vghs'], ['dubai', 'united arab emirates', 'dubai international airport', 'dxb', 'omdb'], ['ishwardi ( begins 18 november 2013 )', 'bangladesh', 'ishwardi airport', 'ird', 'vgis'], ['jeddah', 'saudi arabia', 'king abdulaziz international airport', 'jed', 'oejn'], ['jessore', 'bangladesh', 'jessore airport', 'jsr', 'vgjr'], ['kathmandu', 'nepal', 'tribhuvan international airport', 'ktm', 'vnkt'], ['kolkata', 'india', 'netaji subhash chandra bose international airport', 'ccu', 'vecc'], ['kuala lumpur', 'malaysia', 'kuala lumpur international airport', 'kul', 'wmkk'], ['london', 'united kingdom', 'gatwick airport', 'lgw', 'egkk'], ['muscat', 'oman', 'muscat international airport', 'mct', 'ooms'], ['rajshahi', 'bangladesh', 'shah makhdum airport', 'rjh', 'vgrj'], ['saidpur', 'bangladesh', 'saidpur airport', 'spd', 'vgsd'], ['singapore', 'singapore', 'singapore changi airport', 'sin', 'wsss'], ['sylhet', 'bangladesh', 'osmani international airport', 'zyl', 'vgsy']] |
thomas johansson | https://en.wikipedia.org/wiki/Thomas_Johansson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1408278-5.html.csv | aggregation | thomas johansson 's average final score in a game is five points . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score in the final'], 'result': '5', 'ind': 0, 'tostr': 'avg { all_rows ; score in the final }'}, '5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score in the final } ; 5 } = true', 'tointer': 'the average of the score in the final record of all rows is 5 .'} | round_eq { avg { all_rows ; score in the final } ; 5 } = true | the average of the score in the final record of all rows is 5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score in the final_4': 4, '5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score in the final_4': 'score in the final', '5_5': '5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score in the final_4': [0], '5_5': [1]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['winner', '10 march 1997', 'copenhagen , denmark', 'carpet ( i )', 'martin damm', '6 - 4 , 3 - 6 , 6 - 2'], ['winner', '17 march 1997', 'st petersburg , russia', 'carpet ( i )', 'renzo furlan', '6 - 3 , 6 - 4'], ['runner - up', '2 march 1998', 'rotterdam , netherlands', 'carpet ( i )', 'jan siemerink', '6 - 7 ( 2 - 7 ) , 2 - 6'], ['runner - up', '9 november 1998', 'stockholm , sweden', 'hard ( i )', 'todd martin', '3 - 6 , 4 - 6 , 4 - 6'], ['winner', '2 august 1999', 'montreal , canada', 'hard', 'yevgeny kafelnikov', '1 - 6 , 6 - 3 , 6 - 3'], ['winner', '20 november 2000', 'stockholm , sweden', 'hard ( i )', 'yevgeny kafelnikov', '6 - 2 , 6 - 4 , 6 - 4'], ['winner', '11 june 2001', 'halle , germany', 'grass', 'fabrice santoro', '6 - 3 , 6 - 7 ( 5 - 7 ) , 6 - 2'], ['winner', '18 june 2001', 'nottingham , uk', 'grass', 'harel levy', '7 - 5 , 6 - 3'], ['winner', '14 january 2002', 'australian open , melbourne , australia', 'hard', 'marat safin', '3 - 6 , 6 - 4 , 6 - 4 , 7 - 6 ( 7 - 4 )'], ['runner - up', '14 june 2004', 'nottingham , uk', 'grass', 'paradorn srichaphan', '6 - 1 , 6 - 7 ( 4 - 7 ) , 3 - 6'], ['winner', '25 october 2004', 'stockholm , sweden', 'hard ( i )', 'andre agassi', '3 - 6 , 6 - 3 , 7 - 6 ( 7 - 4 )'], ['winner', '24 october 2005', 'st petersburg , russia', 'carpet ( i )', 'nicolas kiefer', '6 - 4 , 6 - 2'], ['runner - up', '23 october 2006', 'st petersburg , russia', 'carpet ( i )', 'mario ančić', '5 - 7 , 6 - 7 ( 2 - 7 )'], ['runner - up', '8 october 2007', 'stockholm , sweden', 'hard ( i )', 'ivo karlović', '3 - 6 , 6 - 3 , 1 - 6']] |
1996 - 97 european challenge cup | https://en.wikipedia.org/wiki/1996%E2%80%9397_European_Challenge_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16770037-3.html.csv | ordinal | narbonne had the second to most wins in the 1996-97 european challenge cup . | {'row': '2', 'col': '3', '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', 'w', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; w ; 2 }'}, 'team'], 'result': 'narbonne', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; w ; 2 } ; team }'}, 'narbonne'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; w ; 2 } ; team } ; narbonne } = true', 'tointer': 'select the row whose w record of all rows is 2nd maximum . the team record of this row is narbonne .'} | eq { hop { nth_argmax { all_rows ; w ; 2 } ; team } ; narbonne } = true | select the row whose w record of all rows is 2nd maximum . the team record of this row is narbonne . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'w_5': 5, '2_6': 6, 'team_7': 7, 'narbonne_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', 'w_5': 'w', '2_6': '2', 'team_7': 'team', 'narbonne_8': 'narbonne'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'w_5': [0], '2_6': [0], 'team_7': [1], 'narbonne_8': [2]} | ['team', 'p', 'w', 'd', 'l', 'tries for', 'tries against', 'try diff', 'points for', 'points against', 'points diff', 'pts'] | [['castres olympique', '5', '5', '0', '0', '29', '6', '+ 23', '207', '71', '+ 136', '10'], ['narbonne', '5', '4', '0', '1', '21', '6', '+ 15', '161', '90', '+ 71', '8'], ['dinamo - bucureşti', '5', '2', '1', '2', '12', '32', '20', '109', '213', '104', '5'], ['bridgend', '4', '1', '1', '2', '10', '14', '4', '94', '120', '26', '3'], ['bristol shoguns', '5', '1', '0', '4', '11', '12', '1', '128', '99', '+ 29', '2'], ['treorchy', '4', '0', '0', '4', '10', '23', '13', '72', '178', '106', '0']] |
2000 masters tournament | https://en.wikipedia.org/wiki/2000_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514630-7.html.csv | majority | in the 2000 masters tournament , most of the us winners won at least 120000 . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '120000', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'most_greater_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'money', '120000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . for the money records of these rows , most of them are greater than or equal to 120000 .', 'tostr': 'most_greater_eq { filter_eq { all_rows ; country ; united states } ; money ; 120000 } = true'} | most_greater_eq { filter_eq { all_rows ; country ; united states } ; money ; 120000 } = true | select the rows whose country record fuzzily matches to united states . for the money records of these rows , most of them are greater than or equal to 120000 . | 2 | 2 | {'most_greater_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'united states_5': 5, 'money_6': 6, '120000_7': 7} | {'most_greater_eq_1': 'most_greater_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'united states_5': 'united states', 'money_6': 'money', '120000_7': '120000'} | {'most_greater_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'united states_5': [0], 'money_6': [1], '120000_7': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'vijay singh', 'fiji', '72 + 67 + 70 + 69 = 278', '- 10', '828000'], ['2', 'ernie els', 'south africa', '72 + 67 + 74 + 68 = 281', '- 7', '496800'], ['t3', 'david duval', 'united states', '73 + 65 + 74 + 70 = 282', '- 6', '266800'], ['t3', 'loren roberts', 'united states', '73 + 69 + 71 + 69 = 282', '- 6', '266800'], ['5', 'tiger woods', 'united states', '75 + 72 + 68 + 69 = 284', '- 4', '184000'], ['6', 'tom lehman', 'united states', '69 + 72 + 75 + 69 = 285', '- 3', '165600'], ['t7', 'carlos franco', 'paraguay', '79 + 68 + 70 + 69 = 286', '- 2', '143367'], ['t7', 'davis love iii', 'united states', '75 + 72 + 68 + 71 = 286', '- 2', '143367'], ['t7', 'phil mickelson', 'united states', '71 + 68 + 76 + 71 = 286', '- 2', '143367'], ['10', 'hal sutton', 'united states', '72 + 75 + 71 + 69 = 287', '- 1', '124200']] |
german submarine u - 402 | https://en.wikipedia.org/wiki/German_submarine_U-402 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18668500-1.html.csv | ordinal | in german submarine u - 402 , llangibby castle is the earliest among the damaged ships . | {'scope': 'subset', 'row': '1', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'damaged'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fate', 'damaged'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; fate ; damaged }', 'tointer': 'select the rows whose fate record fuzzily matches to damaged .'}, 'date', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; fate ; damaged } ; date ; 1 }'}, 'ship'], 'result': 'llangibby castle', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; fate ; damaged } ; date ; 1 } ; ship }'}, 'llangibby castle'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; fate ; damaged } ; date ; 1 } ; ship } ; llangibby castle } = true', 'tointer': 'select the rows whose fate record fuzzily matches to damaged . select the row whose date record of these rows is 1st minimum . the ship record of this row is llangibby castle .'} | eq { hop { nth_argmin { filter_eq { all_rows ; fate ; damaged } ; date ; 1 } ; ship } ; llangibby castle } = true | select the rows whose fate record fuzzily matches to damaged . select the row whose date record of these rows is 1st minimum . the ship record of this row is llangibby castle . | 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, 'fate_6': 6, 'damaged_7': 7, 'date_8': 8, '1_9': 9, 'ship_10': 10, 'llangibby castle_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', 'fate_6': 'fate', 'damaged_7': 'damaged', 'date_8': 'date', '1_9': '1', 'ship_10': 'ship', 'llangibby castle_11': 'llangibby castle'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'fate_6': [0], 'damaged_7': [0], 'date_8': [1], '1_9': [1], 'ship_10': [2], 'llangibby castle_11': [3]} | ['date', 'ship', 'nationality', 'tonnage', 'fate'] | [['16 may 1941', 'llangibby castle', 'great britain', '11951', 'damaged'], ['13 april 1942', 'empire progress', 'great britain', '5249', 'sunk'], ['30 april 1942', 'ashkhabad', 'soviet union', '5284', 'sunk'], ['2 may 1942', 'uss cythera', 'usa', '602', 'sunk'], ['2 november 1942', 'dalcroy', 'great britain', '4558', 'sunk'], ['2 november 1942', 'empire antelope', 'great britain', '4945', 'sunk'], ['2 november 1942', 'empire leopard', 'great britain', '5676', 'sunk'], ['2 november 1942', 'empire sunrise', 'great britain', '7459', 'damaged'], ['2 november 1942', 'rinos', 'greece', '4649', 'sunk'], ['7 february 1942', 'afrika', 'great britain', '8597', 'sunk'], ['7 february 1942', 'daghild', 'norway', '9272', 'damaged'], ['7 february 1942', 'henry r mallory', 'usa', '6063', 'sunk'], ['7 february 1942', 'kalliopi', 'greece', '4695', 'sunk'], ['7 february 1942', 'robert e hopkins', 'great britain', '6625', 'sunk'], ['7 february 1942', 'toward', 'great britain', '1571', 'sunk'], ['8 february 1942', 'newton ash', 'great britain', '1571', 'sunk'], ['11 may 1943', 'antigone', 'great britain', '4545', 'sunk'], ['11 may 1943', 'grado', 'norway', '3082', 'sunk']] |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16494599-17.html.csv | count | the are 3 players in with the position power forward on the memphis grizzlies all - time roster . | {'scope': 'all', 'criterion': 'equal', 'value': 'power forward', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'power forward'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to power forward .', 'tostr': 'filter_eq { all_rows ; position ; power forward }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; power forward } }', 'tointer': 'select the rows whose position record fuzzily matches to power forward . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; power forward } } ; 3 } = true', 'tointer': 'select the rows whose position record fuzzily matches to power forward . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; position ; power forward } } ; 3 } = true | select the rows whose position record fuzzily matches to power forward . 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, 'position_5': 5, 'power forward_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', 'position_5': 'position', 'power forward_6': 'power forward', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'power forward_6': [0], '3_7': [2]} | ['player', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['zach randolph', 'united states', 'power forward', '2009 - present', 'michigan state'], ['willie reed', 'united states', 'forward - center', '2012 - present', 'st louis'], ['bryant reeves', 'united states', 'center', '1995 - 2001', 'oklahoma state'], ['rodrick rhodes', 'united states', 'guard - forward', '1998 - 1999', 'usc'], ['jeremy richardson', 'united states', 'shooting guard', '2007 - 2008', 'delta state'], ['anthony roberson', 'united states', 'shooting guard', '2005 - 2006', 'florida'], ['lawrence roberts', 'united states', 'power forward', '2005 - 2007', 'mississippi state'], ['chris robinson', 'united states', 'shooting guard', '1996 - 1998', 'western kentucky'], ['larry robinson', 'united states', 'guard - forward', '1997 - 1998', 'centenary'], ['roy rogers', 'united states', 'power forward', '1996 - 1997', 'alabama']] |
dick stockton ( tennis ) | https://en.wikipedia.org/wiki/Dick_Stockton_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11084877-1.html.csv | ordinal | the merion is the earliest championship that dick stockton ( tennis ) joined in 1971 . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'championship'], 'result': 'merion , us', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; championship }'}, 'merion , us'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 1 } ; championship } ; merion , us } = true', 'tointer': 'select the row whose date record of all rows is 1st minimum . the championship record of this row is merion , us .'} | eq { hop { nth_argmin { all_rows ; date ; 1 } ; championship } ; merion , us } = true | select the row whose date record of all rows is 1st minimum . the championship record of this row is merion , us . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'championship_7': 7, 'merion , us_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '1_6': '1', 'championship_7': 'championship', 'merion , us_8': 'merion , us'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'championship_7': [1], 'merion , us_8': [2]} | ['outcome', 'date', 'championship', 'surface', 'opponent', 'score'] | [['runner - up', '1971', 'merion , us', 'hard', 'clark graebner', '2 - 6 , 4 - 6 , 7 - 6 , 5 - 7'], ['runner - up', '1973', 'miami wct , us', 'hard', 'rod laver', '6 - 7 , 3 - 6 , 5 - 7'], ['winner', '1974', 'atlanta wct , us', 'clay', 'jiří hřebec', '6 - 2 , 6 - 1'], ['runner - up', '1974', 'charlotte , us', 'clay', 'jeff borowiak', '4 - 6 , 7 - 5 , 6 - 7'], ['winner', '1974', 'adelaide , australia', 'grass', 'geoff masters', '6 - 2 , 6 - 3 , 6 - 2'], ['runner - up', '1975', 'fort worth wct , us', 'hard', 'john alexander', '6 - 7 , 6 - 4 , 3 - 6'], ['winner', '1975', 'san antonio wct , us', 'hard', 'stan smith', '7 - 5 , 2 - 6 , 7 - 6'], ['runner - up', '1975', 'washington indoor wct , us', 'carpet', 'mark cox', '2 - 6 , 6 - 7'], ['winner', '1976', 'lagos wct , nigeria', 'clay', 'arthur ashe', '6 - 3 , 6 - 2'], ['runner - up', '1976', 'sydney outdoor , australia', 'grass', 'tony roche', '3 - 6 , 6 - 3 , 3 - 6 , 4 - 6'], ['winner', '1977', 'philadelphia wct , us', 'carpet', 'jimmy connors', '3 - 6 , 6 - 4 , 3 - 6 , 6 - 1 , 6 - 2'], ['winner', '1977', 'toronto indoor wct , canada', 'carpet', 'jimmy connors', '5 - 6 , ret'], ['winner', '1977', 'rotterdam , netherlands', 'carpet', 'ilie năstase', '2 - 6 , 6 - 3 , 6 - 3'], ['runner - up', '1977', 'dallas wct , us - wct finals', 'carpet', 'jimmy connors', '7 - 6 , 1 - 6 , 4 - 6 , 3 - 6'], ['runner - up', '1978', 'birmingham wct , us', 'carpet', 'björn borg', '6 - 7 , 5 - 7'], ['winner', '1978', 'little rock , us', 'carpet', 'hank pfister', '6 - 4 , 3 - 5 , ret'], ['runner - up', '1978', 'san francisco , us', 'carpet', 'john mcenroe', '6 - 2 , 6 - 7 , 2 - 6'], ['runner - up', '1981', 'south orange , us', 'clay', 'shlomo glickstein', '3 - 6 , 7 - 5 , 4 - 6']] |
list of australian submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Australian_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16254861-1.html.csv | comparative | of australian submissions for the academy award for best foreign language film , the film ten canoes was submitted one year before the home song stories . | {'row_1': '3', 'row_2': '4', 'col': '1', '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 ( ceremony )', '2006 ( 79th )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2006 ( 79th ) .', 'tostr': 'filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) }'}, 'year ( ceremony )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) }', 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2006 ( 79th ) . take the year ( ceremony ) record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year ( ceremony )', '2007 ( 80th )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2007 ( 80th ) .', 'tostr': 'filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) }'}, 'year ( ceremony )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) }', 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2007 ( 80th ) . take the year ( ceremony ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) } ; hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) } }', 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2006 ( 79th ) . take the year ( ceremony ) record of this row . select the rows whose year ( ceremony ) record fuzzily matches to 2007 ( 80th ) . take the year ( ceremony ) record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year ( ceremony )', '2006 ( 79th )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2006 ( 79th ) .', 'tostr': 'filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) }'}, 'year ( ceremony )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) }', 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2006 ( 79th ) . take the year ( ceremony ) record of this row .'}, '2006 ( 79th )'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) } ; 2006 ( 79th ) }', 'tointer': 'the year ( ceremony ) record of the first row is 2006 ( 79th ) .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year ( ceremony )', '2007 ( 80th )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2007 ( 80th ) .', 'tostr': 'filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) }'}, 'year ( ceremony )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) }', 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2007 ( 80th ) . take the year ( ceremony ) record of this row .'}, '2007 ( 80th )'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) } ; 2007 ( 80th ) }', 'tointer': 'the year ( ceremony ) record of the second row is 2007 ( 80th ) .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) } ; 2006 ( 79th ) } ; eq { hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) } ; 2007 ( 80th ) } }', 'tointer': 'the year ( ceremony ) record of the first row is 2006 ( 79th ) . the year ( ceremony ) record of the second row is 2007 ( 80th ) .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) } ; hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) } } ; and { eq { hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) } ; 2006 ( 79th ) } ; eq { hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) } ; 2007 ( 80th ) } } } = true', 'tointer': 'select the rows whose year ( ceremony ) record fuzzily matches to 2006 ( 79th ) . take the year ( ceremony ) record of this row . select the rows whose year ( ceremony ) record fuzzily matches to 2007 ( 80th ) . take the year ( ceremony ) record of this row . the first record is less than the second record . the year ( ceremony ) record of the first row is 2006 ( 79th ) . the year ( ceremony ) record of the second row is 2007 ( 80th ) .'} | and { less { hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) } ; hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) } } ; and { eq { hop { filter_eq { all_rows ; year ( ceremony ) ; 2006 ( 79th ) } ; year ( ceremony ) } ; 2006 ( 79th ) } ; eq { hop { filter_eq { all_rows ; year ( ceremony ) ; 2007 ( 80th ) } ; year ( ceremony ) } ; 2007 ( 80th ) } } } = true | select the rows whose year ( ceremony ) record fuzzily matches to 2006 ( 79th ) . take the year ( ceremony ) record of this row . select the rows whose year ( ceremony ) record fuzzily matches to 2007 ( 80th ) . take the year ( ceremony ) record of this row . the first record is less than the second record . the year ( ceremony ) record of the first row is 2006 ( 79th ) . the year ( ceremony ) record of the second row is 2007 ( 80th ) . | 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 (ceremony)_11': 11, '2006 (79th)_12': 12, 'year (ceremony)_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'year (ceremony)_15': 15, '2007 (80th)_16': 16, 'year (ceremony)_17': 17, 'and_7': 7, 'str_eq_5': 5, '2006 (79th)_18': 18, 'str_eq_6': 6, '2007 (80th)_19': 19} | {'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 (ceremony)_11': 'year ( ceremony )', '2006 (79th)_12': '2006 ( 79th )', 'year (ceremony)_13': 'year ( ceremony )', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'year (ceremony)_15': 'year ( ceremony )', '2007 (80th)_16': '2007 ( 80th )', 'year (ceremony)_17': 'year ( ceremony )', 'and_7': 'and', 'str_eq_5': 'str_eq', '2006 (79th)_18': '2006 ( 79th )', 'str_eq_6': 'str_eq', '2007 (80th)_19': '2007 ( 80th )'} | {'and_8': [9], 'result_9': [], 'less_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'year (ceremony)_11': [0], '2006 (79th)_12': [0], 'year (ceremony)_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'year (ceremony)_15': [1], '2007 (80th)_16': [1], 'year (ceremony)_17': [3], 'and_7': [8], 'str_eq_5': [7], '2006 (79th)_18': [5], 'str_eq_6': [7], '2007 (80th)_19': [6]} | ['year ( ceremony )', 'film title used in nomination', 'language ( s )', 'director', 'result'] | [['1996 ( 69th )', 'floating life', 'cantonese , english , german', 'clara law', 'not nominated'], ['2001 ( 74th )', 'la spagnola', 'spanish , english , italian', 'steve jacobs', 'not nominated'], ['2006 ( 79th )', 'ten canoes', 'yolngu matha , gunwinggu , english', 'rolf de heer', 'not nominated'], ['2007 ( 80th )', 'the home song stories', 'cantonese , english , mandarin', 'tony ayres', 'not nominated'], ['2009 ( 82nd )', 'samson and delilah', 'warlpiri , english', 'warwick thornton', 'made january shortlist'], ['2012 ( 85th )', 'lore', 'german', 'cate shortland', 'not nominated'], ['2013 ( 86th )', 'the rocket', 'lao', 'kim mordaunt', 'tbd']] |
1996 senior pga tour | https://en.wikipedia.org/wiki/1996_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11621873-4.html.csv | count | 3 players in the 1996 senior pga tour were from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 3 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; country ; united states } } ; 3 } = true | select the rows whose country record fuzzily matches to united states . 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, 'country_5': 5, 'united states_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', 'country_5': 'country', 'united states_6': 'united states', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '3_7': [2]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'lee trevino', 'united states', '6715649', '27'], ['2', 'bob charles', 'new zealand', '6621207', '23'], ['3', 'jim colbert', 'united states', '6570797', '18'], ['4', 'dave stockton', 'united states', '5781417', '13'], ['5', 'chi chi rodriguez', 'puerto rico', '5696544', '22']] |
list of ngc objects ( 5001 - 6000 ) | https://en.wikipedia.org/wiki/List_of_NGC_objects_%285001%E2%80%936000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11051845-5.html.csv | unique | the only ngc with an apparent magnitude under 10.0 is a spiral galaxy in ursa major . | {'scope': 'all', 'row': '2', 'col': '6', 'col_other': '2,3', 'criterion': 'less_than', 'value': '10.0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'apparent magnitude', '10.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose apparent magnitude record is less than 10.0 .', 'tostr': 'filter_less { all_rows ; apparent magnitude ; 10.0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; apparent magnitude ; 10.0 } }', 'tointer': 'select the rows whose apparent magnitude record is less than 10.0 . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'apparent magnitude', '10.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose apparent magnitude record is less than 10.0 .', 'tostr': 'filter_less { all_rows ; apparent magnitude ; 10.0 }'}, 'object type'], 'result': 'spiral galaxy', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; object type }'}, 'spiral galaxy'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; object type } ; spiral galaxy }', 'tointer': 'the object type record of this unqiue row is spiral galaxy .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'apparent magnitude', '10.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose apparent magnitude record is less than 10.0 .', 'tostr': 'filter_less { all_rows ; apparent magnitude ; 10.0 }'}, 'constellation'], 'result': 'ursa major', 'ind': 4, 'tostr': 'hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; constellation }'}, 'ursa major'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; constellation } ; ursa major }', 'tointer': 'the constellation record of this unqiue row is ursa major .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; object type } ; spiral galaxy } ; eq { hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; constellation } ; ursa major } }', 'tointer': 'the object type record of this unqiue row is spiral galaxy . the constellation record of this unqiue row is ursa major .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_less { all_rows ; apparent magnitude ; 10.0 } } ; and { eq { hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; object type } ; spiral galaxy } ; eq { hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; constellation } ; ursa major } } } = true', 'tointer': 'select the rows whose apparent magnitude record is less than 10.0 . there is only one such row in the table . the object type record of this unqiue row is spiral galaxy . the constellation record of this unqiue row is ursa major .'} | and { only { filter_less { all_rows ; apparent magnitude ; 10.0 } } ; and { eq { hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; object type } ; spiral galaxy } ; eq { hop { filter_less { all_rows ; apparent magnitude ; 10.0 } ; constellation } ; ursa major } } } = true | select the rows whose apparent magnitude record is less than 10.0 . there is only one such row in the table . the object type record of this unqiue row is spiral galaxy . the constellation record of this unqiue row is ursa major . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_less_0': 0, 'all_rows_9': 9, 'apparent magnitude_10': 10, '10.0_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'object type_12': 12, 'spiral galaxy_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'constellation_14': 14, 'ursa major_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_9': 'all_rows', 'apparent magnitude_10': 'apparent magnitude', '10.0_11': '10.0', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'object type_12': 'object type', 'spiral galaxy_13': 'spiral galaxy', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'constellation_14': 'constellation', 'ursa major_15': 'ursa major'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_less_0': [1, 2, 4], 'all_rows_9': [0], 'apparent magnitude_10': [0], '10.0_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'object type_12': [2], 'spiral galaxy_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'constellation_14': [4], 'ursa major_15': [5]} | ['ngc number', 'object type', 'constellation', 'right ascension ( j2000 )', 'declination ( j2000 )', 'apparent magnitude'] | [['5408', 'irregular galaxy', 'centaurus', '14h03 m21 .0 s', 'degree22 ′ 44 ″', '14.0'], ['5457', 'spiral galaxy', 'ursa major', '14h03 m12 .5 s', 'degree20 ′ 53 ″', '8.7'], ['5466', 'globular cluster', 'boötes', '14h05 m27 .4 s', 'degree32 ′ 04 ″', '10.5'], ['5474', 'spiral galaxy', 'ursa major', '14h05 m01 .5 s', 'degree39 ′ 45 ″', '11.9'], ['5477', 'irregular galaxy', 'ursa major', '14h05 m33 .1 s', 'degree27 ′ 40 ″', '14.5']] |
2008 - 09 coventry city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Coventry_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17978754-5.html.csv | aggregation | in the 2008 - 09 coventry city f.c. season , the average number of league cups is .2 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '.2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'league cup'], 'result': '.2', 'ind': 0, 'tostr': 'avg { all_rows ; league cup }'}, '.2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; league cup } ; .2 } = true', 'tointer': 'the average of the league cup record of all rows is .2 .'} | round_eq { avg { all_rows ; league cup } ; .2 } = true | the average of the league cup record of all rows is .2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'league cup_4': 4, '.2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'league cup_4': 'league cup', '.2_5': '.2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'league cup_4': [0], '.2_5': [1]} | ['name', 'championship', 'league cup', 'fa cup', 'total'] | [['aron gunnarsson', '9', '1', '2', '12'], ['daniel fox', '8', '1', '0', '9'], ['guillaume beuzelin', '7', '0', '2', '9'], ['scott dann', '8', '0', '0', '8'], ['clinton morrison', '8', '0', '0', '8'], ['stephen wright', '6', '1', '0', '7'], ['isaac osbourne', '6', '0', '0', '6'], ['jay tabb', '4', '0', '0', '4'], ['freddy eastwood', '3', '0', '1', '4'], ['keiren westwood', '3', '0', '1', '4'], ['michael doyle', '4', '0', '0', '4'], ['elliott ward', '3', '0', '1', '4'], ['leon mckenzie', '3', '0', '0', '3'], ['robbie simpson', '3', '0', '0', '3'], ['leon best', '2', '0', '0', '2'], ['jordan henderson', '2', '0', '0', '2'], ['marcus hall', '1', '1', '0', '2'], ['ben turner', '2', '0', '0', '2'], ['michael mifsud', '1', '0', '0', '1'], ['james mcpake', '1', '0', '0', '1']] |
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/1-1341738-19.html.csv | count | six of the louisiana incumbents in the 1968 united states house of representatives elections were re-elected . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 're - elected', 'result': '6', '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': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re - elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re - elected } } ; 6 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; result ; re - elected } } ; 6 } = true | select the rows whose result record fuzzily matches to re - elected . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're - elected_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're - elected_6': 're - elected', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're - elected_6': [0], '6_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['louisiana 1', 'f edward hebert', 'democratic', '1940', 're - elected', 'f edward hebert ( d ) unopposed'], ['louisiana 2', 'hale boggs', 'democratic', '1946', 're - elected', 'hale boggs ( d ) 51.2 % david c treen ( r ) 48.8 %'], ['louisiana 3', 'edwin e willis', 'democratic', '1948', 'lost renomination democratic hold', 'patrick t caffery ( d ) unopposed'], ['louisiana 4', 'joe waggonner', 'democratic', '1961', 're - elected', 'joe waggonner ( d ) unopposed'], ['louisiana 5', 'otto passman', 'democratic', '1946', 're - elected', 'otto passman ( d ) unopposed'], ['louisiana 6', 'john rarick', 'democratic', '1966', 're - elected', 'john rarick ( d ) 79.3 % loyd j rockhold ( r ) 20.7 %'], ['louisiana 7', 'edwin edwards', 'democratic', '1965', 're - elected', 'edwin edwards ( d ) 84.9 % vance w plauche ( r ) 15.1 %']] |
1970 kansas city chiefs season | https://en.wikipedia.org/wiki/1970_Kansas_City_Chiefs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12536159-2.html.csv | count | during their 1970 season , the kanas city chiefs ended two games in a tie . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 't', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 't'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to t .', 'tostr': 'filter_eq { all_rows ; result ; t }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; t } }', 'tointer': 'select the rows whose result record fuzzily matches to t . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; t } } ; 2 } = true', 'tointer': 'select the rows whose result record fuzzily matches to t . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; result ; t } } ; 2 } = true | select the rows whose result record fuzzily matches to t . 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, 't_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', 't_6': 't', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 't_6': [0], '2_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 20 , 1970', 'minnesota vikings', 'l 27 - 10', '47900'], ['2', 'september 28 , 1970', 'baltimore colts', 'w 44 - 24', '53911'], ['3', 'october 4 , 1970', 'denver broncos', 'l 26 - 13', '50705'], ['4', 'october 11 , 1970', 'boston patriots', 'w 23 - 10', '50698'], ['5', 'october 18 , 1970', 'cincinnati bengals', 'w 27 - 19', '57265'], ['6', 'october 25 , 1970', 'dallas cowboys', 'l 27 - 16', '51158'], ['7', 'november 1 , 1970', 'oakland raiders', 't 17 - 17', '51334'], ['8', 'november 8 , 1970', 'houston oilers', 'w 24 - 9', '49810'], ['9', 'november 15 , 1970', 'pittsburgh steelers', 'w 31 - 14', '50081'], ['10', 'november 22 , 1970', 'st louis cardinals', 't 6 - 6', '50711'], ['11', 'november 29 , 1970', 'san diego chargers', 'w 26 - 14', '50315'], ['12', 'december 6 , 1970', 'denver broncos', 'w 16 - 0', '50454'], ['13', 'december 12 , 1970', 'oakland raiders', 'l 20 - 6', '54596'], ['14', 'december 20 , 1970', 'san diego chargers', 'l 31 - 13', '41379']] |
sheffield shield | https://en.wikipedia.org/wiki/Sheffield_Shield | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1585656-13.html.csv | aggregation | in sheffield shield , when the venue was in melbourne , the average number of runs was 397 . | {'scope': 'subset', 'col': '2', 'type': 'average', 'result': '397', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'melbourne cricket ground , melbourne'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'melbourne cricket ground , melbourne'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; melbourne cricket ground , melbourne }', 'tointer': 'select the rows whose venue record fuzzily matches to melbourne cricket ground , melbourne .'}, 'runs'], 'result': '397', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; venue ; melbourne cricket ground , melbourne } ; runs }'}, '397'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; venue ; melbourne cricket ground , melbourne } ; runs } ; 397 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to melbourne cricket ground , melbourne . the average of the runs record of these rows is 397 .'} | round_eq { avg { filter_eq { all_rows ; venue ; melbourne cricket ground , melbourne } ; runs } ; 397 } = true | select the rows whose venue record fuzzily matches to melbourne cricket ground , melbourne . the average of the runs record of these rows is 397 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'melbourne cricket ground, melbourne_6': 6, 'runs_7': 7, '397_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'melbourne cricket ground, melbourne_6': 'melbourne cricket ground , melbourne', 'runs_7': 'runs', '397_8': '397'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'melbourne cricket ground, melbourne_6': [0], 'runs_7': [1], '397_8': [2]} | ['rank', 'runs', 'player', 'match', 'venue', 'season'] | [['1', '452', 'don bradman ( nsw )', 'new south wales v queensland', 'sydney cricket ground , sydney', '1929 - 30'], ['2', '437', 'bill ponsford ( vic )', 'victoria v queensland', 'melbourne cricket ground , melbourne', '1927 - 28'], ['3', '365', 'clem hill ( sa )', 'south australia v new south wales', 'adelaide oval , adalaide', '1900 - 01'], ['4', '359', 'bob simpson ( nsw )', 'new south wales v queensland', 'brisbane cricket ground , brisbane', '1963 - 64'], ['5', '357', 'don bradman ( sa )', 'south australia v victoria', 'melbourne cricket ground , melbourne', '1935 - 36']] |
1956 formula one season | https://en.wikipedia.org/wiki/1956_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1140112-1.html.csv | majority | in the 1956 formula one season , the majority of winning drivers with e tyre used ferrari as a constructor . | {'scope': 'subset', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ferrari', 'subset': {'col': '8', 'criterion': 'equal', 'value': 'e'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tyre', 'e'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; tyre ; e }', 'tointer': 'select the rows whose tyre record fuzzily matches to e .'}, 'constructor', 'ferrari'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose tyre record fuzzily matches to e . for the constructor records of these rows , most of them fuzzily match to ferrari .', 'tostr': 'most_eq { filter_eq { all_rows ; tyre ; e } ; constructor ; ferrari } = true'} | most_eq { filter_eq { all_rows ; tyre ; e } ; constructor ; ferrari } = true | select the rows whose tyre record fuzzily matches to e . for the constructor records of these rows , most of them fuzzily match to ferrari . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'tyre_4': 4, 'e_5': 5, 'constructor_6': 6, 'ferrari_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'tyre_4': 'tyre', 'e_5': 'e', 'constructor_6': 'constructor', 'ferrari_7': 'ferrari'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'tyre_4': [0], 'e_5': [0], 'constructor_6': [1], 'ferrari_7': [1]} | ['race', 'circuit', 'date', 'pole position', 'fastest lap', 'winning driver', 'constructor', 'tyre', 'report'] | [['argentine grand prix', 'buenos aires', '22 january', 'juan manuel fangio', 'juan manuel fangio', 'luigi musso juan manuel fangio', 'ferrari', 'e', 'report'], ['monaco grand prix', 'monaco', '13 may', 'juan manuel fangio', 'juan manuel fangio', 'stirling moss', 'maserati', 'p', 'report'], ['indianapolis 500', 'indianapolis', '30 may', 'pat flaherty', 'paul russo', 'pat flaherty', 'watson - offenhauser', 'f', 'report'], ['belgian grand prix', 'spa - francorchamps', '3 june', 'juan manuel fangio', 'stirling moss', 'peter collins', 'ferrari', 'e', 'report'], ['french grand prix', 'reims', '1 july', 'juan manuel fangio', 'juan manuel fangio', 'peter collins', 'ferrari', 'e', 'report'], ['british grand prix', 'silverstone', '14 july', 'stirling moss', 'stirling moss', 'juan manuel fangio', 'ferrari', 'e', 'report'], ['german grand prix', 'nã ¼ rburgring', '5 august', 'juan manuel fangio', 'juan manuel fangio', 'juan manuel fangio', 'ferrari', 'e', 'report'], ['italian grand prix', 'monza', '2 september', 'juan manuel fangio', 'stirling moss', 'stirling moss', 'maserati', 'p', 'report']] |
1970 in paleontology | https://en.wikipedia.org/wiki/1970_in_paleontology | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15678221-2.html.csv | majority | most of the specimens found in 1970 were found in the usa . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'usa', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'usa'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to usa .', 'tostr': 'most_eq { all_rows ; location ; usa } = true'} | most_eq { all_rows ; location ; usa } = true | for the location records of all rows , most of them fuzzily match to usa . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'usa_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'usa_4': 'usa'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'usa_4': [0]} | ['name', 'novelty', 'status', 'authors', 'unit', 'location'] | [['daspletosaurus', 'gen et sp nov', 'valid', 'russell', 'oldman formation', 'usa'], ['deinocheirus', 'fam , gen et sp nov', 'valid', 'osmã cubiclska & roniewicz', 'nemegt formation', 'mongolia'], ['dilophosaurus', 'gen nov', 'valid', 'welles', 'kayenta formation', 'usa'], ['likhoelesaurus', 'gen et sp nov', 'nomen nudum', 'ellenberger', 'lower elliot formation', 'south africa'], ['megadontosaurus', 'gen et sp nov', 'nomen nudum', 'brown vide : ostrom', 'cloverly formation', 'usa'], ['microvenator', 'gen et sp nov', 'valid', 'ostrom', 'cloverly formation', 'usa'], ['sauropelta', 'gen et sp nov', 'valid', 'ostrom', 'cloverly formation', 'usa'], ['staurikosaurus', 'gen et sp nov', 'valid', 'colbert', 'santa maria formation', 'brazil'], ['tenontosaurus', 'gen et sp nov', 'valid', 'ostrom', 'cloverly formation', 'usa']] |
2008 - 09 dallas mavericks season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Dallas_Mavericks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17288869-9.html.csv | ordinal | the dallas mavericks ' game against cleveland recorded their highest attendance of the 2008 - 09 season . | {'row': '15', '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': 'cleveland', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; 1 } ; team }'}, 'cleveland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; cleveland } = true', 'tointer': 'select the row whose location attendance record of all rows is 1st maximum . the team record of this row is cleveland .'} | eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; cleveland } = true | select the row whose location attendance record of all rows is 1st maximum . the team record of this row is cleveland . | 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, 'cleveland_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', 'cleveland_8': 'cleveland'} | {'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], 'cleveland_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 1', 'toronto', 'w 109 - 98 ( ot )', 'dirk nowitzki ( 24 )', 'james singleton ( 16 )', 'jason kidd ( 15 )', 'american airlines center 19688', '36 - 23'], ['60', 'march 2', 'oklahoma city', 'l 87 - 96 ( ot )', 'dirk nowitzki ( 28 )', 'james singleton ( 6 )', 'dirk nowitzki ( 6 )', 'ford center 18527', '36 - 24'], ['61', 'march 4', 'san antonio', 'w 107 - 102 ( ot )', 'josh howard ( 29 )', 'dirk nowitzki ( 12 )', 'jason kidd ( 9 )', 'american airlines center 20316', '37 - 24'], ['62', 'march 5', 'new orleans', 'l 88 - 104 ( ot )', 'dirk nowitzki ( 27 )', 'erick dampier ( 9 )', 'jason terry ( 4 )', 'new orleans arena 17230', '37 - 25'], ['63', 'march 7', 'washington', 'w 119 - 103 ( ot )', 'dirk nowitzki ( 34 )', 'dirk nowitzki ( 9 )', 'jason kidd ( 11 )', 'american airlines center 20150', '38 - 25'], ['64', 'march 10', 'phoenix', 'w 122 - 117 ( ot )', 'dirk nowitzki ( 34 )', 'dirk nowitzki ( 13 )', 'dirk nowitzki , josé juan barea ( 4 )', 'us airways center 18422', '39 - 25'], ['65', 'march 11', 'portland', 'w 93 - 89 ( ot )', 'dirk nowitzki ( 29 )', 'dirk nowitzki , jason kidd ( 10 )', 'jason kidd ( 10 )', 'rose garden 20286', '40 - 25'], ['66', 'march 13', 'golden state', 'l 110 - 119 ( ot )', 'dirk nowitzki ( 27 )', 'james singleton ( 11 )', 'jason kidd ( 11 )', 'oracle arena 18751', '40 - 26'], ['67', 'march 15', 'la lakers', 'l 100 - 107 ( ot )', 'jason terry ( 29 )', 'james singleton ( 10 )', 'jason kidd ( 9 )', 'staples center 18997', '40 - 27'], ['68', 'march 17', 'detroit', 'w 103 - 101 ( ot )', 'dirk nowitzki ( 30 )', 'erick dampier ( 13 )', 'josé juan barea ( 8 )', 'american airlines center 20427', '41 - 27'], ['69', 'march 19', 'atlanta', 'l 87 - 95 ( ot )', 'dirk nowitzki ( 23 )', 'dirk nowitzki ( 12 )', 'jason kidd ( 6 )', 'philips arena 17499', '41 - 28'], ['70', 'march 20', 'indiana', 'w 94 - 92 ( ot )', 'dirk nowitzki ( 23 )', 'james singleton ( 11 )', 'josé juan barea ( 6 )', 'conseco fieldhouse 17232', '42 - 28'], ['71', 'march 25', 'golden state', 'w 128 - 106 ( ot )', 'jason terry , dirk nowitzki ( 26 )', 'erick dampier ( 10 )', 'josé juan barea , jason kidd ( 7 )', 'american airlines center 19862', '43 - 28'], ['72', 'march 27', 'denver', 'l 101 - 103 ( ot )', 'dirk nowitzki ( 26 )', 'dirk nowitzki ( 11 )', 'josé juan barea , jason terry ( 4 )', 'american airlines center 20310', '43 - 29'], ['73', 'march 29', 'cleveland', 'l 74 - 102 ( ot )', 'dirk nowitzki ( 20 )', 'ryan hollins ( 12 )', 'jason kidd ( 8 )', 'quicken loans arena 20562', '43 - 30'], ['74', 'march 31', 'minnesota', 'w 108 - 88 ( ot )', 'dirk nowitzki ( 23 )', 'dirk nowitzki ( 12 )', 'jason kidd ( 13 )', 'target center 12111', '44 - 30']] |
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 | ordinal | the chicago white sox game played on october 16 had the 3rd highest attendance . | {'row': '5', 'col': '6', 'order': '3', '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', 'att', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; att ; 3 }'}, 'date'], 'result': 'october 16', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; att ; 3 } ; date }'}, 'october 16'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; att ; 3 } ; date } ; october 16 } = true', 'tointer': 'select the row whose att record of all rows is 3rd maximum . the date record of this row is october 16 .'} | eq { hop { nth_argmax { all_rows ; att ; 3 } ; date } ; october 16 } = true | select the row whose att record of all rows is 3rd maximum . the date record of this row is october 16 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'att_5': 5, '3_6': 6, 'date_7': 7, 'october 16_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', 'att_5': 'att', '3_6': '3', 'date_7': 'date', 'october 16_8': 'october 16'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'att_5': [0], '3_6': [0], 'date_7': [1], 'october 16_8': [2]} | ['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 ( 1 - 1 )', '2:46', '44857', '6 - 1 ( 3 - 1 )'], ['october 16', 'angels', '6 - 3', 'escobar ( 1 - 2 )', '3:11', '44712', '7 - 1 ( 4 - 1 )']] |
mid - southern conference of indiana | https://en.wikipedia.org/wiki/Mid-Southern_Conference_of_Indiana | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18833029-1.html.csv | comparative | the school in clarksville joined earlier than the one in ramsey . | {'row_1': '4', 'row_2': '7', 'col': '7', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'clarksville'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to clarksville .', 'tostr': 'filter_eq { all_rows ; location ; clarksville }'}, 'year joined'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; clarksville } ; year joined }', 'tointer': 'select the rows whose location record fuzzily matches to clarksville . take the year joined record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'ramsey'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to ramsey .', 'tostr': 'filter_eq { all_rows ; location ; ramsey }'}, 'year joined'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; location ; ramsey } ; year joined }', 'tointer': 'select the rows whose location record fuzzily matches to ramsey . take the year joined record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; location ; clarksville } ; year joined } ; hop { filter_eq { all_rows ; location ; ramsey } ; year joined } } = true', 'tointer': 'select the rows whose location record fuzzily matches to clarksville . take the year joined record of this row . select the rows whose location record fuzzily matches to ramsey . take the year joined record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; location ; clarksville } ; year joined } ; hop { filter_eq { all_rows ; location ; ramsey } ; year joined } } = true | select the rows whose location record fuzzily matches to clarksville . take the year joined record of this row . select the rows whose location record fuzzily matches to ramsey . take the year joined 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, 'location_7': 7, 'clarksville_8': 8, 'year joined_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'location_11': 11, 'ramsey_12': 12, 'year joined_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', 'location_7': 'location', 'clarksville_8': 'clarksville', 'year joined_9': 'year joined', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'location_11': 'location', 'ramsey_12': 'ramsey', 'year joined_13': 'year joined'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'location_7': [0], 'clarksville_8': [0], 'year joined_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'location_11': [1], 'ramsey_12': [1], 'year joined_13': [3]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county', 'year joined'] | [['austin', 'austin', 'eagles', '437', 'aa', '72 scott', '1958'], ['brownstown central', 'brownstown', 'braves', '611', 'aaa', '36 jackson', '1965'], ['charlestown', 'charlestown', 'pirates', '702', 'aaa', '10 clark', '1958'], ['clarksville', 'clarksville', 'generals', '530', 'aa', '10 clark', '1958'], ['corydon central', 'corydon', 'panthers', '819', 'aaa', '31 harrison', '1958'], ['eastern ( pekin )', 'new pekin', 'musketeers', '552', 'aa', '88 washington', '2003'], ['north harrison', 'ramsey', 'cougars', '702', 'aaa', '31 harrison', '1978'], ['salem', 'salem', 'lions', '656', 'aaa', '88 washington', '1958'], ['scottsburg', 'scottsburg', 'warriors', '865', 'aaa', '72 scott', '1958'], ['silver creek', 'sellersburg', 'dragons', '644', 'aaa', '10 clark', '1958']] |
athletics at the 1963 pan american games | https://en.wikipedia.org/wiki/Athletics_at_the_1963_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10648331-3.html.csv | superlative | at the 1963 pan american games , the united states was ranked the highest in athletics . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'rank'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; rank }'}, 'nation'], 'result': 'united states', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; rank } ; nation }'}, 'united states'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; rank } ; nation } ; united states } = true', 'tointer': 'select the row whose rank record of all rows is minimum . the nation record of this row is united states .'} | eq { hop { argmin { all_rows ; rank } ; nation } ; united states } = true | select the row whose rank record of all rows is minimum . the nation record of this row is united states . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, 'nation_6': 6, 'united states_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'rank_5': 'rank', 'nation_6': 'nation', 'united states_7': 'united states'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], 'nation_6': [1], 'united states_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '22', '15', '10', '47'], ['2', 'canada', '5', '5', '2', '12'], ['3', 'argentina', '2', '2', '1', '5'], ['4', 'venezuela', '1', '3', '3', '7'], ['5', 'cuba', '1', '3', '1', '5'], ['6', 'mexico', '1', '1', '1', '3'], ['7', 'chile', '1', '0', '0', '1'], ['8', 'brazil', '0', '2', '6', '8'], ['9', 'jamaica', '0', '1', '1', '2'], ['10', 'guatemala', '0', '1', '0', '1'], ['11', 'trinidad and tobago', '0', '0', '2', '2'], ['11', 'barbados', '0', '0', '2', '2'], ['13', 'panama', '0', '0', '1', '1'], ['13', 'puerto rico', '0', '0', '1', '1'], ['13', 'uruguay', '0', '0', '1', '1'], ['13', 'netherlands antilles', '0', '0', '1', '1']] |
list of australian football league pre - season and night series premiers | https://en.wikipedia.org/wiki/List_of_Australian_Football_League_pre-season_and_night_series_premiers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1139835-9.html.csv | comparative | the attendance when the runner up was sydney swans was 61861 less than when the runner up was hawthorn . | {'row_1': '1', 'row_2': '2', 'col': '6', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'yes', 'diff_result': {'diff_value': '61861', 'bigger': 'row2'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner up', 'sydney swans'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runner up record fuzzily matches to sydney swans .', 'tostr': 'filter_eq { all_rows ; runner up ; sydney swans }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance }', 'tointer': 'select the rows whose runner up record fuzzily matches to sydney swans . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner up', 'hawthorn'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose runner up record fuzzily matches to hawthorn .', 'tostr': 'filter_eq { all_rows ; runner up ; hawthorn }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance }', 'tointer': 'select the rows whose runner up record fuzzily matches to hawthorn . take the attendance record of this row .'}], 'result': '-61861', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance } ; hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance } }'}, '-61861'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance } ; hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance } } ; -61861 }', 'tointer': 'select the rows whose runner up record fuzzily matches to sydney swans . take the attendance record of this row . select the rows whose runner up record fuzzily matches to hawthorn . take the attendance record of this row . the second record is 61861 larger than the first record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner up', 'sydney swans'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose runner up record fuzzily matches to sydney swans .', 'tostr': 'filter_eq { all_rows ; runner up ; sydney swans }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance }', 'tointer': 'select the rows whose runner up record fuzzily matches to sydney swans . take the attendance record of this row .'}, '30824'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance } ; 30824 }', 'tointer': 'the attendance record of the first row is 30824 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'runner up', 'hawthorn'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose runner up record fuzzily matches to hawthorn .', 'tostr': 'filter_eq { all_rows ; runner up ; hawthorn }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance }', 'tointer': 'select the rows whose runner up record fuzzily matches to hawthorn . take the attendance record of this row .'}, '92685'], 'result': True, 'ind': 7, 'tostr': 'eq { hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance } ; 92685 }', 'tointer': 'the attendance record of the second row is 92685 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance } ; 30824 } ; eq { hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance } ; 92685 } }', 'tointer': 'the attendance record of the first row is 30824 . the attendance record of the second row is 92685 .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { diff { hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance } ; hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance } } ; -61861 } ; and { eq { hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance } ; 30824 } ; eq { hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance } ; 92685 } } } = true', 'tointer': 'select the rows whose runner up record fuzzily matches to sydney swans . take the attendance record of this row . select the rows whose runner up record fuzzily matches to hawthorn . take the attendance record of this row . the second record is 61861 larger than the first record . the attendance record of the first row is 30824 . the attendance record of the second row is 92685 .'} | and { eq { diff { hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance } ; hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance } } ; -61861 } ; and { eq { hop { filter_eq { all_rows ; runner up ; sydney swans } ; attendance } ; 30824 } ; eq { hop { filter_eq { all_rows ; runner up ; hawthorn } ; attendance } ; 92685 } } } = true | select the rows whose runner up record fuzzily matches to sydney swans . take the attendance record of this row . select the rows whose runner up record fuzzily matches to hawthorn . take the attendance record of this row . the second record is 61861 larger than the first record . the attendance record of the first row is 30824 . the attendance record of the second row is 92685 . | 14 | 10 | {'and_9': 9, 'result_10': 10, 'eq_5': 5, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_11': 11, 'runner up_12': 12, 'sydney swans_13': 13, 'attendance_14': 14, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_15': 15, 'runner up_16': 16, 'hawthorn_17': 17, 'attendance_18': 18, '-61861_19': 19, 'and_8': 8, 'eq_6': 6, '30824_20': 20, 'eq_7': 7, '92685_21': 21} | {'and_9': 'and', 'result_10': 'true', 'eq_5': 'eq', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_11': 'all_rows', 'runner up_12': 'runner up', 'sydney swans_13': 'sydney swans', 'attendance_14': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_15': 'all_rows', 'runner up_16': 'runner up', 'hawthorn_17': 'hawthorn', 'attendance_18': 'attendance', '-61861_19': '-61861', 'and_8': 'and', 'eq_6': 'eq', '30824_20': '30824', 'eq_7': 'eq', '92685_21': '92685'} | {'and_9': [10], 'result_10': [], 'eq_5': [9], 'diff_4': [5], 'num_hop_2': [4, 6], 'filter_str_eq_0': [2], 'all_rows_11': [0], 'runner up_12': [0], 'sydney swans_13': [0], 'attendance_14': [2], 'num_hop_3': [4, 7], 'filter_str_eq_1': [3], 'all_rows_15': [1], 'runner up_16': [1], 'hawthorn_17': [1], 'attendance_18': [3], '-61861_19': [5], 'and_8': [9], 'eq_6': [8], '30824_20': [6], 'eq_7': [8], '92685_21': [7]} | ['season', 'premier', 'runner up', 'score', 'venue', 'attendance', 'premiership'] | [['1984', 'essendon', 'sydney swans', '13.11 ( 89 ) - 5.8 ( 38 )', 'waverley park', '30824', 'night series'], ['1984', 'essendon', 'hawthorn', '14.21 ( 105 ) - 12.9 ( 81 )', 'mcg', '92685', 'vfl grand final'], ['1986', 'hawthorn', 'carlton', '9.12 ( 66 ) - 5.6 ( 36 )', 'waverley park', '19627', 'night series'], ['1986', 'hawthorn', 'carlton', '16.14 ( 110 ) - 9.14 ( 68 )', 'mcg', '101861', 'vfl grand final'], ['1988', 'hawthorn', 'geelong', '10.10 ( 70 ) - 9.13 ( 67 )', 'waverley park', '35803', 'pre - season cup'], ['1988', 'hawthorn', 'melbourne', '22.20 ( 152 ) - 6.20 ( 56 )', 'mcg', '93754', 'vfl grand final'], ['1993', 'essendon', 'richmond', '14.18 ( 102 ) - 11.13 ( 79 )', 'waverley park', '75533', 'pre - season cup'], ['1993', 'essendon', 'carlton carlton', '20.13 ( 133 ) - 13.11 ( 89 )', 'mcg', '96862', 'afl grand final'], ['2000', 'essendon', 'north melbourne', '16.21 ( 117 ) - 11.10 ( 76 )', 'mcg', '56720', 'pre - season cup'], ['2000', 'essendon', 'melbourne', '19.21 ( 135 ) - 11.9 ( 75 )', 'mcg', '96249', 'afl grand final'], ['2009', 'geelong', 'collingwood', '0.18.19 ( 127 ) - 1.6.6 ( 51 )', 'etihad stadium', '37277', 'pre - season cup']] |
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 | superlative | yousef soltani competed in the heaviest weight division for iran at the 2007 asian indoor games . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '5', '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', 'event'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; event }'}, 'athlete'], 'result': 'yousef soltani', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; event } ; athlete }'}, 'yousef soltani'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; event } ; athlete } ; yousef soltani } = true', 'tointer': 'select the row whose event record of all rows is maximum . the athlete record of this row is yousef soltani .'} | eq { hop { argmax { all_rows ; event } ; athlete } ; yousef soltani } = true | select the row whose event record of all rows is maximum . the athlete record of this row is yousef soltani . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'event_5': 5, 'athlete_6': 6, 'yousef soltani_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'event_5': 'event', 'athlete_6': 'athlete', 'yousef soltani_7': 'yousef soltani'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'event_5': [0], 'athlete_6': [1], 'yousef soltani_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 kg', 'chu ( mac ) w knockout', 'el - kaissi ( lib ) w rsch', 'shukla ( ind ) w rsch'], ['yousef soltani', '81 kg', 'matsumoto ( jpn ) l 0 - 5', 'did not advance', 'did not advance']] |
2008 - 09 2 . bundesliga | https://en.wikipedia.org/wiki/2008%E2%80%9309_2._Bundesliga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17327260-3.html.csv | ordinal | thomas von heesen was the earliest outgoing manager in the 2008 - 09 2 . bundesliga season . | {'row': '1', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date of vacancy', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date of vacancy ; 1 }'}, 'outgoing manager'], 'result': 'thomas von heesen', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date of vacancy ; 1 } ; outgoing manager }'}, 'thomas von heesen'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date of vacancy ; 1 } ; outgoing manager } ; thomas von heesen } = true', 'tointer': 'select the row whose date of vacancy record of all rows is 1st minimum . the outgoing manager record of this row is thomas von heesen .'} | eq { hop { nth_argmin { all_rows ; date of vacancy ; 1 } ; outgoing manager } ; thomas von heesen } = true | select the row whose date of vacancy record of all rows is 1st minimum . the outgoing manager record of this row is thomas von heesen . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date of vacancy_5': 5, '1_6': 6, 'outgoing manager_7': 7, 'thomas von heesen_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date of vacancy_5': 'date of vacancy', '1_6': '1', 'outgoing manager_7': 'outgoing manager', 'thomas von heesen_8': 'thomas von heesen'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date of vacancy_5': [0], '1_6': [0], 'outgoing manager_7': [1], 'thomas von heesen_8': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment'] | [['1 . fc nuremberg', 'thomas von heesen', 'resigned', '28 august 2008', 'michael oenning', '5 september 2008'], ['msv duisburg', 'rudolf bommer', 'sacked', '9 november 2008', 'peter neururer', '16 november 2008'], ['fc hansa rostock', 'frank pagelsdorf', 'sacked', '10 november 2008', 'dieter eilts', '21 november 2008'], ['sv wehen wiesbaden', 'christian hock', 'sacked', '17 december 2008', 'wolfgang frank', '19 december 2008'], ['tsv 1860 munich', 'marco kurz', 'sacked', '24 february 2009', 'uwe wolf ( interim )', '24 february 2009'], ['rot weiss ahlen', 'christian wück', 'sacked', '3 march 2009', 'stefan emmerling', '16 april 2009'], ['fc hansa rostock', 'dieter eilts', 'sacked', '6 march 2009', 'andreas zachhuber', '8 march 2009'], ['sv wehen wiesbaden', 'wolfgang frank', 'sacked', '23 march 2009', 'sandro schwarz ( interim )', '23 march 2009'], ['fc augsburg', 'holger fach', 'sacked', '13 april 2009', 'jos luhukay', '14 april 2009'], ['fc ingolstadt 04', 'thorsten fink', 'sacked', '21 april 2009', 'horst köppel', '26 april 2009'], ['1 . fc kaiserslautern', 'milan šašić', 'sacked', '4 may 2009', 'alois schwartz ( interim )', '4 may 2009'], ['tsv 1860 munich', 'uwe wolf ( interim )', 'released from duties', '13 may 2009', 'ewald lienen', '13 may 2009']] |
1980 - 81 fa cup | https://en.wikipedia.org/wiki/1980%E2%80%9381_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17751859-6.html.csv | unique | only one game was played for the fa cup on march 11 . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': '11 march 1981', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '11 march 1981'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 11 march 1981 .', 'tostr': 'filter_eq { all_rows ; date ; 11 march 1981 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; 11 march 1981 } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 11 march 1981 . there is only one such row in the table .'} | only { filter_eq { all_rows ; date ; 11 march 1981 } } = true | select the rows whose date record fuzzily matches to 11 march 1981 . 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, 'date_4': 4, '11 march 1981_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', '11 march 1981_5': '11 march 1981'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], '11 march 1981_5': [0]} | ['tie no', 'home team', 'score', 'away team', 'date'] | [['1', 'nottingham forest', '3 - 3', 'ipswich town', '7 march 1981'], ['replay', 'ipswich town', '1 - 0', 'nottingham forest', '10 march 1981'], ['2', 'middlesbrough', '1 - 1', 'wolverhampton wanderers', '7 march 1981'], ['replay', 'wolverhampton wanderers', '3 - 1', 'middlesbrough', '10 march 1981'], ['3', 'everton', '2 - 2', 'manchester city', '7 march 1981'], ['replay', 'manchester city', '3 - 1', 'everton', '11 march 1981'], ['4', 'tottenham hotspur', '2 - 0', 'exeter city', '7 march 1981']] |
list of corporations by market capitalization | https://en.wikipedia.org/wiki/List_of_corporations_by_market_capitalization | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14094649-20.html.csv | majority | most of the corporations in the market are headquartered in 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', 'headquarters', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the headquarters records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; headquarters ; united states } = true'} | most_eq { all_rows ; headquarters ; united states } = true | for the headquarters 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, 'headquarters_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'headquarters_3': 'headquarters', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'headquarters_3': [0], 'united states_4': [0]} | ['rank', 'name', 'headquarters', 'primary industry', 'market value ( usd million )'] | [['1', 'microsoft', 'united states', 'software industry', '586197'], ['2', 'general electric', 'united states', 'conglomerate', '474956'], ['3', 'ntt docomo', 'japan', 'telecommunications', '366204'], ['4', 'cisco systems', 'united states', 'networking hardware', '348965'], ['5', 'wal - mart', 'united states', 'retail', '286153'], ['6', 'intel corporation', 'united states', 'computer hardware', '277096'], ['7', 'nippon telegraph and telephone', 'japan', 'telecommunications', '274905'], ['8', 'exxon mobil', 'united states', 'oil and gas', '265894'], ['9', 'lucent technologies', 'united states', 'telecommunications', '237668'], ['10', 'deutsche telekom', 'germany', 'telecommunications', '209628']] |
1958 green bay packers season | https://en.wikipedia.org/wiki/1958_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14656268-2.html.csv | ordinal | the second highest attendance occurred when the venue was memorial stadium . | {'row': '6', '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', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'venue'], 'result': 'memorial stadium', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; venue }'}, 'memorial stadium'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; venue } ; memorial stadium } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the venue record of this row is memorial stadium .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; venue } ; memorial stadium } = true | select the row whose attendance record of all rows is 2nd maximum . the venue record of this row is memorial stadium . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'venue_7': 7, 'memorial stadium_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'venue_7': 'venue', 'memorial stadium_8': 'memorial stadium'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'venue_7': [1], 'memorial stadium_8': [2]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance'] | [['1', 'september 28 , 1958', 'chicago bears', 'l 34 - 20', 'city stadium', '32150'], ['2', 'october 5 , 1958', 'detroit lions', 't 13 - 13', 'city stadium', '32053'], ['3', 'october 12 , 1958', 'baltimore colts', 'l 24 - 17', 'milwaukee county stadium', '24553'], ['4', 'october 19 , 1958', 'washington redskins', 'l 37 - 21', 'griffith stadium', '25228'], ['5', 'october 26 , 1958', 'philadelphia eagles', 'w 38 - 35', 'city stadium', '31043'], ['6', 'november 2 , 1958', 'baltimore colts', 'l 56 - 0', 'memorial stadium', '51333'], ['7', 'november 9 , 1958', 'chicago bears', 'l 24 - 10', 'wrigley field', '48424'], ['8', 'november 16 , 1958', 'los angeles rams', 'l 20 - 7', 'city stadium', '28051'], ['9', 'november 23 , 1958', 'san francisco 49ers', 'l 33 - 12', 'milwaukee county stadium', '19786'], ['10', 'november 27 , 1958', 'detroit lions', 'l 24 - 14', 'briggs stadium', '50971'], ['11', 'december 7 , 1958', 'san francisco 49ers', 'l 48 - 21', 'kezar stadium', '50793'], ['12', 'december 14 , 1958', 'los angeles rams', 'l 34 - 20', 'los angeles memorial coliseum', '54634']] |
no way out ( 2008 ) | https://en.wikipedia.org/wiki/No_Way_Out_%282008%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15325500-3.html.csv | superlative | jbl was the soonest eliminated contestant in wwe raw 's no way out in 2008 . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'eliminated'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; eliminated }'}, 'wrestler'], 'result': 'jbl', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; eliminated } ; wrestler }'}, 'jbl'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; eliminated } ; wrestler } ; jbl } = true', 'tointer': 'select the row whose eliminated record of all rows is minimum . the wrestler record of this row is jbl .'} | eq { hop { argmin { all_rows ; eliminated } ; wrestler } ; jbl } = true | select the row whose eliminated record of all rows is minimum . the wrestler record of this row is jbl . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'eliminated_5': 5, 'wrestler_6': 6, 'jbl_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'eliminated_5': 'eliminated', 'wrestler_6': 'wrestler', 'jbl_7': 'jbl'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'eliminated_5': [0], 'wrestler_6': [1], 'jbl_7': [2]} | ['eliminated', 'wrestler', 'entered', 'eliminated by', 'time'] | [['1', 'jbl', '4', 'jericho', '13:44'], ['2', 'umaga', '3', 'jericho', '19:45'], ['3', 'chris jericho', '1', 'hardy', '19:57'], ['4', 'shawn michaels', '2', 'triple h', '20:25'], ['5', 'jeff hardy', '6', 'triple h', '23:54'], ['winner', 'triple h', '5', 'n / a', 'n / a']] |
2010 - 11 detroit pistons season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Detroit_Pistons_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27755603-8.html.csv | majority | greg monroe had the high in rebounds for most of the games . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'greg monroe', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high rebounds', 'greg monroe'], 'result': True, 'ind': 0, 'tointer': 'for the high rebounds records of all rows , most of them fuzzily match to greg monroe .', 'tostr': 'most_eq { all_rows ; high rebounds ; greg monroe } = true'} | most_eq { all_rows ; high rebounds ; greg monroe } = true | for the high rebounds records of all rows , most of them fuzzily match to greg monroe . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high rebounds_3': 3, 'greg monroe_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high rebounds_3': 'high rebounds', 'greg monroe_4': 'greg monroe'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high rebounds_3': [0], 'greg monroe_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['34', 'january 3', 'utah', 'l 97 - 102 ( ot )', 'tayshaun prince ( 26 )', 'tracy mcgrady ( 9 )', 'tracy mcgrady ( 11 )', 'energysolutions arena 19911', '11 - 23'], ['35', 'january 4', 'la lakers', 'l 83 - 108 ( ot )', 'tracy mcgrady , greg monroe ( 14 )', 'greg monroe ( 11 )', 'tracy mcgrady ( 6 )', 'staples center 18997', '11 - 24'], ['36', 'january 8', 'philadelphia', 'w 112 - 109 ( ot )', 'tayshaun prince ( 23 )', 'greg monroe ( 13 )', 'tracy mcgrady ( 7 )', 'the palace of auburn hills 20038', '12 - 24'], ['37', 'january 10', 'chicago', 'l 82 - 95 ( ot )', 'tayshaun prince ( 15 )', 'greg monroe ( 11 )', 'rodney stuckey ( 4 )', 'united center 21407', '12 - 25'], ['38', 'january 12', 'memphis', 'l 99 - 107 ( ot )', 'ben gordon ( 25 )', 'greg monroe ( 11 )', 'rodney stuckey ( 6 )', 'the palace of auburn hills 13068', '12 - 26'], ['39', 'january 14', 'toronto', 'w 101 - 95 ( ot )', 'tracy mcgrady ( 22 )', 'chris wilcox ( 12 )', 'tracy mcgrady ( 5 )', 'air canada centre 16924', '13 - 26'], ['40', 'january 15', 'sacramento', 'w 110 - 106 ( ot )', 'tayshaun prince ( 21 )', 'greg monroe ( 7 )', 'will bynum ( 7 )', 'the palace of auburn hills 18784', '14 - 26'], ['41', 'january 17', 'dallas', 'w 103 - 89 ( ot )', 'rodney stuckey ( 20 )', 'greg monroe ( 9 )', 'rodney stuckey ( 6 )', 'the palace of auburn hills 12660', '15 - 26'], ['42', 'january 19', 'boston', 'l 82 - 86 ( ot )', 'rodney stuckey ( 15 )', 'greg monroe ( 9 )', 'tracy mcgrady ( 7 )', 'td garden 18624', '15 - 27'], ['43', 'january 21', 'new jersey', 'l 74 - 89 ( ot )', 'tayshaun prince ( 16 )', 'greg monroe ( 10 )', 'tracy mcgrady ( 6 )', 'prudential center 13316', '15 - 28'], ['44', 'january 22', 'phoenix', 'w 75 - 74 ( ot )', 'tayshaun prince ( 17 )', 'tayshaun prince ( 13 )', 'tayshaun prince ( 5 )', 'the palace of auburn hills 21326', '16 - 28'], ['45', 'january 24', 'orlando', 'w 103 - 96 ( ot )', 'austin daye , tracy mcgrady , tayshaun prince ( 20 )', 'ben wallace ( 11 )', 'tayshaun prince ( 6 )', 'amway center 19098', '17 - 28'], ['46', 'january 26', 'denver', 'l 100 - 109 ( ot )', 'will bynum ( 19 )', 'ben wallace ( 10 )', 'tracy mcgrady ( 8 )', 'the palace of auburn hills 16212', '17 - 29'], ['47', 'january 28', 'miami', 'l 87 - 88 ( ot )', 'ben gordon ( 21 )', 'chris wilcox ( 10 )', 'tracy mcgrady ( 10 )', 'american airlines arena 19805', '17 - 30']] |
athletics at the 2008 summer olympics - men 's 400 metres | https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_400_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569105-7.html.csv | unique | michael blackwood is the only athlete from jamaica that competed in the the men 's 400 metres during the 2008 summer olympics . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'jamaica', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'jamaica'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to jamaica .', 'tostr': 'filter_eq { all_rows ; nationality ; jamaica }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; jamaica } }', 'tointer': 'select the rows whose nationality record fuzzily matches to jamaica . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'jamaica'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to jamaica .', 'tostr': 'filter_eq { all_rows ; nationality ; jamaica }'}, 'athlete'], 'result': 'michael blackwood', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; jamaica } ; athlete }'}, 'michael blackwood'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; jamaica } ; athlete } ; michael blackwood }', 'tointer': 'the athlete record of this unqiue row is michael blackwood .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; jamaica } } ; eq { hop { filter_eq { all_rows ; nationality ; jamaica } ; athlete } ; michael blackwood } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to jamaica . there is only one such row in the table . the athlete record of this unqiue row is michael blackwood .'} | and { only { filter_eq { all_rows ; nationality ; jamaica } } ; eq { hop { filter_eq { all_rows ; nationality ; jamaica } ; athlete } ; michael blackwood } } = true | select the rows whose nationality record fuzzily matches to jamaica . there is only one such row in the table . the athlete record of this unqiue row is michael blackwood . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'jamaica_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'athlete_9': 9, 'michael blackwood_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'jamaica_8': 'jamaica', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'athlete_9': 'athlete', 'michael blackwood_10': 'michael blackwood'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'jamaica_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'athlete_9': [2], 'michael blackwood_10': [3]} | ['rank', 'lane', 'athlete', 'nationality', 'time', 'react'] | [['1', '7', 'andrew steele', 'great britain', '44.94', '0.248'], ['2', '5', 'renny quow', 'trinidad and tobago', '45.13', '0.266'], ['3', '6', 'michael mathieu', 'bahamas', '45.17', '0.193'], ['4', '8', 'michael blackwood', 'jamaica', '45.56', '0.204'], ['5', '2', 'tyler christopher', 'canada', '45.67', '0.172'], ['6', '3', 'joel phillip', 'grenada', '46.30', '0.198'], ['7', '9', 'félix martinez', 'puerto rico', '46.46', '0.347'], ['8', '4', 'daniel dąbrowski', 'poland', '47.83', '0.260']] |
united states house of representatives elections , 1970 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1970 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341718-34.html.csv | superlative | charles r. jonas had the highest percentage of re-elected candidates . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', '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', 'candidates'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; candidates }'}, 'incumbent'], 'result': 'charles r jonas', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; candidates } ; incumbent }'}, 'charles r jonas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; candidates } ; incumbent } ; charles r jonas } = true', 'tointer': 'select the row whose candidates record of all rows is maximum . the incumbent record of this row is charles r jonas .'} | eq { hop { argmax { all_rows ; candidates } ; incumbent } ; charles r jonas } = true | select the row whose candidates record of all rows is maximum . the incumbent record of this row is charles r jonas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'candidates_5': 5, 'incumbent_6': 6, 'charles r jonas_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', 'incumbent_6': 'incumbent', 'charles r jonas_7': 'charles r jonas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'candidates_5': [0], 'incumbent_6': [1], 'charles r jonas_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 4', 'nick galifianakis', 'democratic', '1966', 're - elected', 'nick galifianakis ( d ) 52.4 % jack hawke ( r ) 47.6 %'], ['north carolina 5', 'wilmer mizell', 'republican', '1968', 're - elected', 'wilmer mizell ( r ) 58.1 % james g white ( d ) 41.9 %'], ['north carolina 8', 'earl b ruth', 'republican', '1968', 're - elected', 'earl b ruth ( r ) 56.1 % h clifton blue ( d ) 43.9 %'], ['north carolina 9', 'charles r jonas', 'republican', '1952', 're - elected', 'charles r jonas ( r ) 66.6 % cy n bahakel ( d ) 33.4 %']] |
2004 - 05 greek cup | https://en.wikipedia.org/wiki/2004%E2%80%9305_Greek_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19130829-4.html.csv | ordinal | illsiakos had the seventh best aggragate score in the 2004-05 greek cup . | {'row': '5', 'col': '2', 'order': '7', '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', 'agg score', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; agg score ; 7 }'}, 'team 1'], 'result': 'ilisiakos', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; agg score ; 7 } ; team 1 }'}, 'ilisiakos'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; agg score ; 7 } ; team 1 } ; ilisiakos } = true', 'tointer': 'select the row whose agg score record of all rows is 7th maximum . the team 1 record of this row is ilisiakos .'} | eq { hop { nth_argmax { all_rows ; agg score ; 7 } ; team 1 } ; ilisiakos } = true | select the row whose agg score record of all rows is 7th maximum . the team 1 record of this row is ilisiakos . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'agg score_5': 5, '7_6': 6, 'team 1_7': 7, 'ilisiakos_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', 'agg score_5': 'agg score', '7_6': '7', 'team 1_7': 'team 1', 'ilisiakos_8': 'ilisiakos'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'agg score_5': [0], '7_6': [0], 'team 1_7': [1], 'ilisiakos_8': [2]} | ['team 1', 'agg score', 'team 2', '1st leg', '2nd leg'] | [['iraklis', '1 - 2', 'olympiacos', '1 - 0', '0 - 2'], ['kastoria', '4 - 2', 'ptolemaida - lignitorikhi', '2 - 0', '2 - 3'], ['aris', '4 - 2', 'ethnikos', '2 - 1', '2 - 1'], ['skoda xanthi', '1 - 0', 'egaleo', '1 - 0', '0 - 0'], ['ilisiakos', '0 - 2', 'panionios', '0 - 1', '0 - 1'], ['larissa', '3 - 2', 'chalkidon near east', '3 - 1', '0 - 1'], ['ofi', '1 - 1', 'apollon kalamaria', '1 - 1', '0 - 0']] |
2007 - 08 fis ski jumping world cup | https://en.wikipedia.org/wiki/2007%E2%80%9308_FIS_Ski_Jumping_World_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14407512-14.html.csv | ordinal | the second highest number of points in the 2007-08 fis ski jumping world cup was for tom hilde . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 2 }'}, 'name'], 'result': 'tom hilde', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 2 } ; name }'}, 'tom hilde'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points ; 2 } ; name } ; tom hilde } = true', 'tointer': 'select the row whose points record of all rows is 2nd maximum . the name record of this row is tom hilde .'} | eq { hop { nth_argmax { all_rows ; points ; 2 } ; name } ; tom hilde } = true | select the row whose points record of all rows is 2nd maximum . the name record of this row is tom hilde . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '2_6': 6, 'name_7': 7, 'tom hilde_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', 'points_5': 'points', '2_6': '2', 'name_7': 'name', 'tom hilde_8': 'tom hilde'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '2_6': [0], 'name_7': [1], 'tom hilde_8': [2]} | ['rank', 'name', 'nationality', '1st ( m )', 'points', 'overall wc points ( rank )'] | [['1', 'janne ahonen', 'fin', '199.5', '187.9', '810 ( 2 )'], ['2', 'tom hilde', 'nor', '193.0', '185.6', '682 ( 4 )'], ['3', 'anders jacobsen', 'nor', '191.0', '181.2', '283 ( 13 )'], ['4', 'dmitry vassiliev', 'rus', '191.0', '178.2', '236 ( 16 )'], ['5', 'thomas morgenstern', 'aut', '188.0', '177.6', '1115 ( 1 )']] |
houston rockets all - time roster | https://en.wikipedia.org/wiki/Houston_Rockets_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11734041-18.html.csv | unique | andre turner is the only player an height of less than 6 - 0 ft in the houston rockets all - time roster . | {'scope': 'all', 'row': '16', 'col': '3', 'col_other': '1', 'criterion': 'less_than', 'value': '6-0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'height in ft', '6-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height in ft record is less than 6-0 .', 'tostr': 'filter_less { all_rows ; height in ft ; 6-0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; height in ft ; 6-0 } }', 'tointer': 'select the rows whose height in ft record is less than 6-0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'height in ft', '6-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height in ft record is less than 6-0 .', 'tostr': 'filter_less { all_rows ; height in ft ; 6-0 }'}, 'player'], 'result': 'turner , andre andre turner', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; height in ft ; 6-0 } ; player }'}, 'turner , andre andre turner'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; height in ft ; 6-0 } ; player } ; turner , andre andre turner }', 'tointer': 'the player record of this unqiue row is turner , andre andre turner .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; height in ft ; 6-0 } } ; eq { hop { filter_less { all_rows ; height in ft ; 6-0 } ; player } ; turner , andre andre turner } } = true', 'tointer': 'select the rows whose height in ft record is less than 6-0 . there is only one such row in the table . the player record of this unqiue row is turner , andre andre turner .'} | and { only { filter_less { all_rows ; height in ft ; 6-0 } } ; eq { hop { filter_less { all_rows ; height in ft ; 6-0 } ; player } ; turner , andre andre turner } } = true | select the rows whose height in ft record is less than 6-0 . there is only one such row in the table . the player record of this unqiue row is turner , andre andre turner . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'height in ft_7': 7, '6-0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'turner , andre andre turner_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'height in ft_7': 'height in ft', '6-0_8': '6-0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'turner , andre andre turner_10': 'turner , andre andre turner'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'height in ft_7': [0], '6-0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'turner , andre andre turner_10': [3]} | ['player', 'no ( s )', 'height in ft', 'position', 'years for rockets', 'school / club team / country'] | [['tabak , zan zan tabak', '55', '7 - 0', 'center', '1994 - 95', 'croatia'], ['taylor , jeff jeff taylor', '13', '6 - 3', 'guard', '1982 - 83', 'texas tech'], ['taylor , jermaine jermaine taylor', '8', '6 - 4', 'guard', '2009 - 11', 'central florida'], ['taylor , maurice maurice taylor', '2', '6 - 9', 'forward', '2000 - 05', 'michigan'], ['teagle , terry terry teagle', '10 , 20', '6 - 6', 'guard', '1982 - 84 , 1993', 'baylor'], ['temple , garrett garrett temple', '2', '6 - 6', 'guard', '2010', 'louisiana state'], ['thabeet , hasheem hasheem thabeet', '32', '7 - 3', 'center', '2011 - 2012', 'university of connecticut'], ['thomas , kenny kenny thomas', '21', '6 - 7', 'forward', '1999 - 2002', 'new mexico'], ['thompson , bernard bernard thompson', '25', '6 - 6', 'guard', '1988 - 89', 'fresno state'], ['thorpe , otis otis thorpe', '33', '6 - 10', 'forward', '1988 - 94', 'providence'], ['threatt , sedale sedale threatt', '2', '6 - 2', 'guard', '1996 - 97', 'west virginia tech'], ['tomjanovich , rudy rudy tomjanovich', '45', '6 - 8', 'forward', '1970 - 81', 'michigan'], ['torres , oscar oscar torres', '18', '6 - 6', 'guard / forward', '2001 - 02', 'venezuela'], ['trapp , john john trapp', '31', '6 - 7', 'forward', '1968 - 71', 'unlv'], ['tsakalidis , jake jake tsakalidis', '25', '7 - 2', 'center', '2007', 'greece'], ['turner , andre andre turner', '13', '5 - 11', 'guard', '1987', 'memphis state']] |
royal canadian mint numismatic coins ( 2000s ) | https://en.wikipedia.org/wiki/Royal_Canadian_Mint_numismatic_coins_%282000s%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916083-28.html.csv | comparative | in reference to royal canadian mint numismatic coins from the 2000s , the great blue heron had an issue price of $ 2 more than the common eider . | {'row_1': '7', 'row_2': '6', 'col': '5', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '2', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'theme', 'great blue heron'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose theme record fuzzily matches to great blue heron .', 'tostr': 'filter_eq { all_rows ; theme ; great blue heron }'}, 'issue price'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; theme ; great blue heron } ; issue price }', 'tointer': 'select the rows whose theme record fuzzily matches to great blue heron . take the issue price record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'theme', 'common eider'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose theme record fuzzily matches to common eider .', 'tostr': 'filter_eq { all_rows ; theme ; common eider }'}, 'issue price'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; theme ; common eider } ; issue price }', 'tointer': 'select the rows whose theme record fuzzily matches to common eider . take the issue price record of this row .'}], 'result': '2', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; theme ; great blue heron } ; issue price } ; hop { filter_eq { all_rows ; theme ; common eider } ; issue price } }'}, '2'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; theme ; great blue heron } ; issue price } ; hop { filter_eq { all_rows ; theme ; common eider } ; issue price } } ; 2 } = true', 'tointer': 'select the rows whose theme record fuzzily matches to great blue heron . take the issue price record of this row . select the rows whose theme record fuzzily matches to common eider . take the issue price record of this row . the first record is 2 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; theme ; great blue heron } ; issue price } ; hop { filter_eq { all_rows ; theme ; common eider } ; issue price } } ; 2 } = true | select the rows whose theme record fuzzily matches to great blue heron . take the issue price record of this row . select the rows whose theme record fuzzily matches to common eider . take the issue price record of this row . the first record is 2 larger than the second 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, 'theme_8': 8, 'great blue heron_9': 9, 'issue price_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'theme_12': 12, 'common eider_13': 13, 'issue price_14': 14, '2_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'theme_8': 'theme', 'great blue heron_9': 'great blue heron', 'issue price_10': 'issue price', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'theme_12': 'theme', 'common eider_13': 'common eider', 'issue price_14': 'issue price', '2_15': '2'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'theme_8': [0], 'great blue heron_9': [0], 'issue price_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'theme_12': [1], 'common eider_13': [1], 'issue price_14': [3], '2_15': [5]} | ['year', 'theme', 'artist', 'mintage', 'issue price'] | [['2002', '15th anniversary loonie', 'dora de pãdery - hunt', '67672', '39.95'], ['2004', 'jack miner bird sanctuary', 'susan taylor', 'n / a', '39.95'], ['2005', 'tufted puffin', 'n / a', 'n / a', '39.95'], ['2006', 'snowy owl', 'glen loates', '20000', '39.95'], ['2007', 'trumpeter swan', 'kerri burnett', '40000', '45.95'], ['2008', 'common eider', 'mark hobson', '40000', '45.95'], ['2009', 'great blue heron', 'chris jordison', '40000', '47.95']] |
2007 gran premio tecate | https://en.wikipedia.org/wiki/2007_Gran_Premio_Tecate | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14171191-2.html.csv | superlative | in the 2007 gran premio tecate , when the driver was part of minardi team usa , the highest number of laps is by robert doornbos . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '16', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'minardi team usa'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'minardi team usa'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; minardi team usa }', 'tointer': 'select the rows whose team record fuzzily matches to minardi team usa .'}, 'laps'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; team ; minardi team usa } ; laps }'}, 'driver'], 'result': 'robert doornbos', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; team ; minardi team usa } ; laps } ; driver }'}, 'robert doornbos'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; team ; minardi team usa } ; laps } ; driver } ; robert doornbos } = true', 'tointer': 'select the rows whose team record fuzzily matches to minardi team usa . select the row whose laps record of these rows is maximum . the driver record of this row is robert doornbos .'} | eq { hop { argmax { filter_eq { all_rows ; team ; minardi team usa } ; laps } ; driver } ; robert doornbos } = true | select the rows whose team record fuzzily matches to minardi team usa . select the row whose laps record of these rows is maximum . the driver record of this row is robert doornbos . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'team_6': 6, 'minardi team usa_7': 7, 'laps_8': 8, 'driver_9': 9, 'robert doornbos_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'team_6': 'team', 'minardi team usa_7': 'minardi team usa', 'laps_8': 'laps', 'driver_9': 'driver', 'robert doornbos_10': 'robert doornbos'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'team_6': [0], 'minardi team usa_7': [0], 'laps_8': [1], 'driver_9': [2], 'robert doornbos_10': [3]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['sébastien bourdais', 'n / h / l racing', '64', '1:45:02.885', '2', '32'], ['will power', 'team australia', '64', '+ 1.906', '1', '29'], ['oriol servià', 'pkv racing', '64', '+ 3.364', '4', '25'], ['graham rahal', 'n / h / l racing', '64', '+ 7.346', '7', '23'], ['paul tracy', 'forsythe racing', '64', '+ 8.593', '8', '21'], ['simon pagenaud', 'team australia', '64', '+ 9.638', '6', '19'], ['bruno junqueira', 'dale coyne racing', '64', '+ 15.823', '12', '17'], ['mario domínguez', 'pacific coast motorsports', '64', '+ 16.077', '15', '16'], ['neel jani', 'pkv racing', '64', '+ 16.199', '11', '13'], ['justin wilson', 'rusport', '64', '+ 16.954', '5', '11'], ['alex figge', 'pacific coast motorsports', '63', '+ 1 lap', '17', '10'], ['nelson philippe', 'conquest racing', '63', '+ 1 lap', '13', '9'], ['alex tagliani', 'rocketsports racing', '62', '+ 2 laps', '14', '8'], ['david martínez', 'forsythe racing', '58', '+ 6 laps', '10', '7'], ['katherine legge', 'dale coyne racing', '56', 'mechanical', '16', '6'], ['robert doornbos', 'minardi team usa', '12', 'mechanical', '3', '6'], ['dan clarke', 'minardi team usa', '0', 'mechanical', '9', '4']] |
ana jovanović | https://en.wikipedia.org/wiki/Ana_Jovanovi%C4%87 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12326046-2.html.csv | majority | in most of the tournaments that ana jovanović participated in , the clay surface was used . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', '13 october 2002', 'ain alsouknha', 'clay', 'aurelija miseviciute', '6 - 4 , 6 - 1'], ['winner', '27 october 2002', 'al mansoura', 'clay', 'ema janašková', '4 - 6 , 6 - 3 , 6 - 2'], ['winner', '4 july 2004', 'bibione', 'clay', 'sabrina jolk', '6 - 3 , 6 - 3'], ['ru', '27 march 2005', 'rome', 'clay', 'romina oprandi', '4 - 6 , 6 ( 4 ) - 7'], ['ru', '24 july 2005', 'palić', 'clay', 'miljana adanko', '5 - 7 , 1 - 6'], ['not played', '30 april 2006', 'herceg novi', 'clay', 'zorica petrov', 'np'], ['winner', '14 may 2006', 'mostar', 'clay', 'ani mijačika', '6 - 2 , 6 - 4'], ['winner', '25 march 2007', 'athens', 'hard', 'neuza silva', '6 - 3 , 4 - 6 , 6 - 3'], ['winner', '24 june 2007', 'sarajevo', 'clay', 'davinia lobbinger', '6 - 4 , 6 - 4'], ['winner', '5 august 2007', 'bad saulgau', 'clay', 'kathrin wörle', '7 - 5 , 4 - 6 , 7 - 5'], ['ru', '7 june 2009', 'sarajevo', 'clay', 'ivana lisjak', '0 - 6 , 6 ( 10 ) - 7'], ['ru', '2 august 2009', 'bad saulgau', 'clay', 'andrea hlaváčková', '4 - 6 , 4 - 6'], ['ru', '22 november 2009', 'opole', 'carpet ( i )', 'sandra záhlavová', '0 - 6 , 2 - 6']] |
2008 kentucky wildcats football team | https://en.wikipedia.org/wiki/2008_Kentucky_Wildcats_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14624447-32.html.csv | count | 11 players are listed as members of the 2008 kentucky wildcats football team . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '11', 'col': '3', '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': '11', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; name } }', 'tointer': 'select the rows whose name record is arbitrary . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; name } } ; 11 } = true', 'tointer': 'select the rows whose name record is arbitrary . the number of such rows is 11 .'} | eq { count { filter_all { all_rows ; name } } ; 11 } = true | select the rows whose name record is arbitrary . the number of such rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'name_5': 5, '11_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'name_5': 'name', '11_6': '11'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'name_5': [0], '11_6': [2]} | ['position', 'number', 'name', 'height', 'weight', 'class', 'hometown', 'games ↑'] | [['qb', '5', 'mike hartline', "6 ' 6", "' 205", 'so', 'canton , ohio', '5'], ['tb', '28', 'tony dixon', "' 5 ' 9", '203', 'sr', 'parrish , alabama', '5'], ['fb', '38', 'john conner', "5 ' 11", '230', 'jr', 'west chester , ohio', '5'], ['wr', '12', 'dicky lyons', "5 ' 11", '190', 'sr', 'new orleans , louisiana', '5'], ['wr', '17', 'ej adams', "6 ' 0", '197', 'jr', 'stone mountain , georgia', '3'], ['te', '80', 'tc drake', "6 ' 6 '", '242', 'jr', 'bardstown , kentucky', '4'], ['lt', '79', 'garry williams', "6 ' 3", '300', 'sr', 'louisville , kentucky', '3'], ['lg', '72', 'zipp duncan', "6 ' 5", '295', 'jr', 'magnolia , kentucky', '5'], ['c', '61', 'jorge gonzález', "6 ' 3", '303', 'jr', 'tampa bay , florida', '5'], ['rg', '73', 'jess beets', "6 ' 2", '293', 'sr', 'dove canyon , california', '5'], ['rt', '72', 'brad durham', "6 ' 4", '310', 'so', 'mount vernon , kentucky', '1']] |
1967 vfl season | https://en.wikipedia.org/wiki/1967_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808681-3.html.csv | aggregation | total attendance of vfl matches on 29 april 1967 was 137,849 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '137,849', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '137,849', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '137,849'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 137,849 } = true', 'tointer': 'the sum of the crowd record of all rows is 137,849 .'} | round_eq { sum { all_rows ; crowd } ; 137,849 } = true | the sum of the crowd record of all rows is 137,849 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '137,849_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '137,849_5': '137,849'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '137,849_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '11.15 ( 81 )', 'hawthorn', '7.5 ( 47 )', 'kardinya park', '17227', '29 april 1967'], ['footscray', '6.5 ( 41 )', 'south melbourne', '11.13 ( 79 )', 'western oval', '18283', '29 april 1967'], ['carlton', '10.13 ( 73 )', 'north melbourne', '8.9 ( 57 )', 'princes park', '19041', '29 april 1967'], ['st kilda', '9.13 ( 67 )', 'melbourne', '10.9 ( 69 )', 'moorabbin oval', '27760', '29 april 1967'], ['richmond', '11.12 ( 78 )', 'fitzroy', '7.11 ( 53 )', 'mcg', '20938', '29 april 1967'], ['essendon', '8.6 ( 54 )', 'collingwood', '10.16 ( 76 )', 'windy hill', '34600', '29 april 1967']] |
1962 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1962_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277219-5.html.csv | count | in the 1962 us open , three players tied for fourth place . | {'scope': 'all', 'criterion': 'equal', 'value': 't4', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'place', 't4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose place record fuzzily matches to t4 .', 'tostr': 'filter_eq { all_rows ; place ; t4 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; place ; t4 } }', 'tointer': 'select the rows whose place record fuzzily matches to t4 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; place ; t4 } } ; 3 } = true', 'tointer': 'select the rows whose place record fuzzily matches to t4 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; place ; t4 } } ; 3 } = true | select the rows whose place record fuzzily matches to t4 . 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, 'place_5': 5, 't4_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', 'place_5': 'place', 't4_6': 't4', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'place_5': [0], 't4_6': [0], '3_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'arnold palmer', 'united states', '71 + 68 = 139', '- 3'], ['t1', 'bob rosburg', 'united states', '70 + 69 = 139', '- 3'], ['3', 'billy maxwell', 'united states', '71 + 70 = 141', '- 1'], ['t4', 'bobby nichols', 'united states', '70 + 72 = 142', 'e'], ['t4', 'jack nicklaus', 'united states', '72 + 70 = 142', 'e'], ['t4', 'gary player', 'south africa', '71 + 71 = 142', 'e'], ['t7', 'miller barber', 'united states', '73 + 70 = 143', '+ 1'], ['t7', 'gene littler', 'united states', '69 + 74 = 143', '+ 1'], ['t9', 'phil rodgers', 'united states', '74 + 70 = 144', '+ 2'], ['t9', 'don whitt', 'united states', '73 + 71 = 144', '+ 2']] |
2005 new england patriots season | https://en.wikipedia.org/wiki/2005_New_England_Patriots_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10716255-4.html.csv | unique | week 7 was the only week that a game was not played in the 2005 new england patriots season . | {'scope': 'all', 'row': '7', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '-', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to - .', 'tostr': 'filter_eq { all_rows ; date ; - }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; - } }', 'tointer': 'select the rows whose date record is equal to - . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'date', '-'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is equal to - .', 'tostr': 'filter_eq { all_rows ; date ; - }'}, 'week'], 'result': '7', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; - } ; week }'}, '7'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 7 }', 'tointer': 'the week record of this unqiue row is 7 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; date ; - } } ; eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 7 } } = true', 'tointer': 'select the rows whose date record is equal to - . there is only one such row in the table . the week record of this unqiue row is 7 .'} | and { only { filter_eq { all_rows ; date ; - } } ; eq { hop { filter_eq { all_rows ; date ; - } ; week } ; 7 } } = true | select the rows whose date record is equal to - . there is only one such row in the table . the week record of this unqiue row is 7 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '-_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'week_9': 9, '7_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '-_8': '-', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'week_9': 'week', '7_10': '7'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'date_7': [0], '-_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'week_9': [2], '7_10': [3]} | ['week', 'kickoff', 'date', 'opponent', 'result', 'record', 'game site', 'nflcom recap'] | [['1', '9:00 pm edt', 'september 8 , 2005', 'oakland raiders', 'w 30 - 20', '1 - 0', 'gillette stadium', 'recap'], ['2', '1:00 pm edt', 'september 18 , 2005', 'carolina panthers', 'l 17 - 27', '1 - 1', 'bank of america stadium', 'recap'], ['3', '4:15 pm edt', 'september 25 , 2005', 'pittsburgh steelers', 'w 23 - 20', '2 - 1', 'heinz field', 'recap'], ['4', '1:00 pm edt', 'october 2 , 2005', 'san diego chargers', 'l 17 - 41', '2 - 2', 'gillette stadium', 'recap'], ['5', '1:00 pm edt', 'october 9 , 2005', 'atlanta falcons', 'w 31 - 28', '3 - 2', 'georgia dome', 'recap'], ['6', '4:15 pm edt', 'october 16 , 2005', 'denver broncos', 'l 20 - 28', '3 - 3', 'invesco field at mile high', 'recap'], ['7', '-', '-', '-', '-', '-', '-', ''], ['8', '8:30 pm est', 'october 30 , 2005', 'buffalo bills', 'w 21 - 16', '4 - 3', 'gillette stadium', 'recap'], ['9', '9:00 pm est', 'november 7 , 2005', 'indianapolis colts', 'l 21 - 40', '4 - 4', 'gillette stadium', 'recap'], ['10', '1:00 pm est', 'november 13 , 2005', 'miami dolphins', 'w 23 - 16', '5 - 4', 'dolphins stadium', 'recap'], ['11', '1:00 pm est', 'november 20 , 2005', 'new orleans saints', 'w 24 - 17', '6 - 4', 'gillette stadium', 'recap'], ['12', '1:00 pm est', 'november 27 , 2005', 'kansas city chiefs', 'l 16 - 26', '6 - 5', 'arrowhead stadium', 'recap'], ['13', '4:15 pm est', 'december 4 , 2005', 'new york jets', 'w 16 - 3', '7 - 5', 'gillette stadium', 'recap'], ['14', '1:00 pm est', 'december 11 , 2005', 'buffalo bills', 'w 35 - 7', '8 - 5', 'ralph wilson stadium', 'recap'], ['15', '1:30 pm est', 'december 17 , 2005', 'tampa bay buccaneers', 'w 28 - 0', '9 - 5', 'gillette stadium', 'recap'], ['16', '9:00 pm est', 'december 26 , 2005', 'new york jets', 'w 31 - 21', '10 - 5', 'giants stadium', 'recap'], ['17', '1:00 pm est', 'january 1 , 2006', 'miami dolphins', 'l 26 - 28', '10 - 6', 'gillette stadium', 'recap']] |
1953 washington redskins season | https://en.wikipedia.org/wiki/1953_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15123292-1.html.csv | superlative | the game played on november 1 , 1953 drew the highest crowd attendance in the 1953 washington redskins season . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'november 1 , 1953', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'november 1 , 1953'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; november 1 , 1953 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is november 1 , 1953 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; november 1 , 1953 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is november 1 , 1953 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, 'november 1 , 1953_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', 'date_6': 'date', 'november 1 , 1953_7': 'november 1 , 1953'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'november 1 , 1953_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 27 , 1953', 'chicago cardinals', 'w 24 - 13', '16055'], ['2', 'october 2 , 1953', 'philadelphia eagles', 't 21 - 21', '19099'], ['3', 'october 11 , 1953', 'new york giants', 'w 13 - 9', '26241'], ['4', 'october 18 , 1953', 'cleveland browns', 'l 30 - 14', '33963'], ['5', 'october 25 , 1953', 'baltimore colts', 'l 27 - 17', '34031'], ['6', 'november 1 , 1953', 'cleveland browns', 'l 27 - 3', '47845'], ['7', 'november 8 , 1953', 'chicago cardinals', 'w 28 - 17', '19654'], ['8', 'november 15 , 1953', 'chicago bears', 'l 27 - 24', '21392'], ['9', 'november 22 , 1953', 'new york giants', 'w 24 - 21', '16887'], ['10', 'november 29 , 1953', 'pittsburgh steelers', 'w 17 - 9', '17026'], ['11', 'december 6 , 1953', 'philadelphia eagles', 'w 10 - 0', '21579'], ['12', 'december 13 , 1953', 'pittsburgh steelers', 'l 14 - 13', '22057']] |
2010 - 11 pittsburgh panthers men 's basketball team | https://en.wikipedia.org/wiki/2010%E2%80%9311_Pittsburgh_Panthers_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29050051-3.html.csv | count | there are four men on the panther 's men 's basketball team that weigh under two hundred pounds . | {'scope': 'all', 'criterion': 'less_than', 'value': '200', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'weight ( lb )', '200'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weight ( lb ) record is less than 200 .', 'tostr': 'filter_less { all_rows ; weight ( lb ) ; 200 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; weight ( lb ) ; 200 } }', 'tointer': 'select the rows whose weight ( lb ) record is less than 200 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; weight ( lb ) ; 200 } } ; 4 } = true', 'tointer': 'select the rows whose weight ( lb ) record is less than 200 . the number of such rows is 4 .'} | eq { count { filter_less { all_rows ; weight ( lb ) ; 200 } } ; 4 } = true | select the rows whose weight ( lb ) record is less than 200 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'weight ( lb )_5': 5, '200_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'weight ( lb )_5': 'weight ( lb )', '200_6': '200', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'weight ( lb )_5': [0], '200_6': [0], '4_7': [2]} | ['name', '-', 'position', 'height', 'weight ( lb )', 'year', 'hometown', 'previous school'] | [['gilbert brown', '5', 'forward', 'ft6in ( m )', '215', '2 senior ( rs )', 'harrisburg , pa', 'south kent school'], ['isaiah epps', '2', 'guard', 'ft2in ( m )', '175', '2 freshman', 'plainfield , nj', 'hargrave military academy / plainfield hs'], ['ashton gibbs', '12', 'guard', 'ft2in ( m )', '190', '1 junior', 'scotch plains , nj', 'seton hall prep'], ['gary mcghee', '52', 'center', 'ft11in ( m )', '250', '2 senior', 'anderson , in', 'highland hs'], ['jj moore', '44', 'forward', 'ft6in ( m )', '200', '2 freshman', 'brentwood , ny', 'south kent school / brentwood hs'], ['aron nwankwo', '15', 'forward', 'ft7in ( m )', '200', '2 freshman', 'baltimore , md', 'baltimore city college'], ['lamar patterson', '21', 'guard / forward', 'ft5in ( m )', '220', '1 freshman ( rs )', 'lancaster , pa', "st benedict 's prep / jp mccaskey hs"], ['jj richardson', '55', 'forward / center', 'ft7in ( m )', '235', '1 sophomore', 'missouri city , tx', 'fort bend hightower hs'], ['nick rivers', '14', 'guard', 'ft0in ( m )', '180', '1 senior', 'phoenix , az', 'brophy college prep'], ['nasir robinson', '35', 'forward', 'ft5in ( m )', '220', '1 junior', 'chester , pa', 'chester hs'], ['dante taylor', '11', 'forward', 'ft9in ( m )', '240', '1 sophomore', 'greenburgh , ny', 'national christian academy ( md )'], ['brad wanamaker', '22', 'guard', 'ft4in ( m )', '210', '2 senior', 'philadelphia , pa', 'roman catholic hs'], ['travon woodall', '1', 'guard', 'ft11in ( m )', '190', '1 sophomore ( rs )', 'brooklyn , ny - paterson , nj', 'st anthony hs'], ['cameron wright', '3', 'guard', 'ft4in ( m )', '200', '1 freshman', 'cleveland , oh', 'benedictine hs']] |
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/2-11964047-9.html.csv | majority | all games of the portland trail blazers ' in the 2007 - 08 season were scheduled for the month of march . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'march', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'march'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to march .', 'tostr': 'all_eq { all_rows ; date ; march } = true'} | all_eq { all_rows ; date ; march } = true | for the date records of all rows , all of them fuzzily match to march . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'march_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'march_4': 'march'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'march_4': [0]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record', 'streak'] | [['march 2', 'portland trail blazers', 'l 104 - 110', 'golden state warriors', 'jackson : 29', 'oracle arena 19596', '31 - 29', 'l1'], ['march 4', 'phoenix suns', 'l 97 - 92', 'portland trail blazers', 'roy : 25', 'rose garden 20595', '31 - 30', 'l2'], ['march 7', 'portland trail blazers', 'w 103 - 101', 'milwaukee bucks', 'aldridge : 29', 'bradley center 15537', '32 - 30', 'w1'], ['march 8', 'portland trail blazers', 'w 120 - 114 ot', 'new york knicks', 'robinson : 45', 'madison square garden 19763', '33 - 30', 'w2'], ['march 10', 'portland trail blazers', 'l 80 - 88', 'cleveland cavaliers', 'aldridge : 25', 'quicken loans arena 20213', '33 - 31', 'l1'], ['march 11', 'portland trail blazers', 'w 103 - 96', 'minnesota timberwolves', 'roy : 27', 'target center 13433', '34 - 31', 'w1'], ['march 13', 'portland trail blazers', 'l 85 - 96', 'sacramento kings', 'artest : 22', 'arco arena 13333', '34 - 32', 'l1'], ['march 15', 'minnesota timberwolves', 'w 96 - 107', 'portland trail blazers', 'aldridge : 26', 'rose garden 20079', '35 - 32', 'w1'], ['march 18', 'phoenix suns', 'l 111 - 98', 'portland trail blazers', 'aldridge : 31', 'rose garden 20580', '35 - 33', 'l1'], ['march 21', 'los angeles clippers', 'w 102 - 107', 'portland trail blazers', 'mobley : 24', 'rose garden 19980', '36 - 33', 'w1'], ['march 22', 'portland trail blazers', 'w 83 - 72', 'los angeles clippers', 'roy : 23', 'staples center 18248', '37 - 33', 'w2'], ['march 24', 'portland trail blazers', 'l 84 - 97', 'seattle supersonics', 'durant : 23', 'keyarena 11292', '37 - 34', 'l1'], ['march 25', 'washington wizards', 'w 82 - 102', 'portland trail blazers', 'webster : 23', 'rose garden 19980', '38 - 34', 'w1'], ['march 27', 'portland trail blazers', 'l 95 - 111', 'golden state warriors', 'jackson : 24', 'oracle arena 19732', '38 - 35', 'l1'], ['march 29', 'charlotte bobcats', 'l 93 - 85', 'portland trail blazers', 'outlaw : 26', 'rose garden 19980', '38 - 36', 'l2']] |
1944 vfl season | https://en.wikipedia.org/wiki/1944_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809142-10.html.csv | unique | the geelong v north melbourne game in kardinia park is the only game in the 1944 vfl season to draw a crowd fewer than 10000 . | {'scope': 'all', 'row': '3', 'col': '6', 'col_other': '1,3,5', 'criterion': 'less_than', 'value': '10000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is less than 10000 .', 'tostr': 'filter_less { all_rows ; crowd ; 10000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; crowd ; 10000 } }', 'tointer': 'select the rows whose crowd record is less than 10000 . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is less than 10000 .', 'tostr': 'filter_less { all_rows ; crowd ; 10000 }'}, 'home team'], 'result': 'geelong', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; crowd ; 10000 } ; home team }'}, 'geelong'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; geelong }', 'tointer': 'the home team record of this unqiue row is geelong .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is less than 10000 .', 'tostr': 'filter_less { all_rows ; crowd ; 10000 }'}, 'away team'], 'result': 'north melbourne', 'ind': 4, 'tostr': 'hop { filter_less { all_rows ; crowd ; 10000 } ; away team }'}, 'north melbourne'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_less { all_rows ; crowd ; 10000 } ; away team } ; north melbourne }', 'tointer': 'the away team record of this unqiue row is north melbourne .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is less than 10000 .', 'tostr': 'filter_less { all_rows ; crowd ; 10000 }'}, 'venue'], 'result': 'kardinia park', 'ind': 6, 'tostr': 'hop { filter_less { all_rows ; crowd ; 10000 } ; venue }'}, 'kardinia park'], 'result': True, 'ind': 7, 'tostr': 'eq { hop { filter_less { all_rows ; crowd ; 10000 } ; venue } ; kardinia park }', 'tointer': 'the venue record of this unqiue row is kardinia park .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; away team } ; north melbourne } ; eq { hop { filter_less { all_rows ; crowd ; 10000 } ; venue } ; kardinia park } }', 'tointer': 'the away team record of this unqiue row is north melbourne . the venue record of this unqiue row is kardinia park .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; geelong } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; away team } ; north melbourne } ; eq { hop { filter_less { all_rows ; crowd ; 10000 } ; venue } ; kardinia park } } }', 'tointer': 'the home team record of this unqiue row is geelong . the away team record of this unqiue row is north melbourne . the venue record of this unqiue row is kardinia park .'}], 'result': True, 'ind': 10, 'tostr': 'and { only { filter_less { all_rows ; crowd ; 10000 } } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; geelong } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; away team } ; north melbourne } ; eq { hop { filter_less { all_rows ; crowd ; 10000 } ; venue } ; kardinia park } } } } = true', 'tointer': 'select the rows whose crowd record is less than 10000 . there is only one such row in the table . the home team record of this unqiue row is geelong . the away team record of this unqiue row is north melbourne . the venue record of this unqiue row is kardinia park .'} | and { only { filter_less { all_rows ; crowd ; 10000 } } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; home team } ; geelong } ; and { eq { hop { filter_less { all_rows ; crowd ; 10000 } ; away team } ; north melbourne } ; eq { hop { filter_less { all_rows ; crowd ; 10000 } ; venue } ; kardinia park } } } } = true | select the rows whose crowd record is less than 10000 . there is only one such row in the table . the home team record of this unqiue row is geelong . the away team record of this unqiue row is north melbourne . the venue record of this unqiue row is kardinia park . | 14 | 11 | {'and_10': 10, 'result_11': 11, 'only_1': 1, 'filter_less_0': 0, 'all_rows_12': 12, 'crowd_13': 13, '10000_14': 14, 'and_9': 9, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_15': 15, 'geelong_16': 16, 'and_8': 8, 'str_eq_5': 5, 'str_hop_4': 4, 'away team_17': 17, 'north melbourne_18': 18, 'str_eq_7': 7, 'str_hop_6': 6, 'venue_19': 19, 'kardinia park_20': 20} | {'and_10': 'and', 'result_11': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_12': 'all_rows', 'crowd_13': 'crowd', '10000_14': '10000', 'and_9': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_15': 'home team', 'geelong_16': 'geelong', 'and_8': 'and', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'away team_17': 'away team', 'north melbourne_18': 'north melbourne', 'str_eq_7': 'str_eq', 'str_hop_6': 'str_hop', 'venue_19': 'venue', 'kardinia park_20': 'kardinia park'} | {'and_10': [11], 'result_11': [], 'only_1': [10], 'filter_less_0': [1, 2, 4, 6], 'all_rows_12': [0], 'crowd_13': [0], '10000_14': [0], 'and_9': [10], 'str_eq_3': [9], 'str_hop_2': [3], 'home team_15': [2], 'geelong_16': [3], 'and_8': [9], 'str_eq_5': [8], 'str_hop_4': [5], 'away team_17': [4], 'north melbourne_18': [5], 'str_eq_7': [8], 'str_hop_6': [7], 'venue_19': [6], 'kardinia park_20': [7]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '10.10 ( 70 )', 'south melbourne', '9.13 ( 67 )', 'punt road oval', '10000', '8 july 1944'], ['hawthorn', '11.9 ( 75 )', 'richmond', '13.16 ( 94 )', 'glenferrie oval', '11000', '8 july 1944'], ['geelong', '13.9 ( 87 )', 'north melbourne', '21.14 ( 140 )', 'kardinia park', '6500', '8 july 1944'], ['essendon', '14.16 ( 100 )', 'footscray', '8.13 ( 61 )', 'windy hill', '13000', '8 july 1944'], ['carlton', '11.15 ( 81 )', 'fitzroy', '6.15 ( 51 )', 'princes park', '17000', '8 july 1944'], ['st kilda', '17.11 ( 113 )', 'collingwood', '6.9 ( 45 )', 'junction oval', '10000', '8 july 1944']] |
carlos menditeguy | https://en.wikipedia.org/wiki/Carlos_Menditeguy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1228256-1.html.csv | majority | most of the entrants got 0 points in carlos menditeguy . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'points', '0'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; points ; 0 } = true'} | most_eq { all_rows ; points ; 0 } = true | for the points records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '0_4': [0]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1953', 'equipe gordini', 'gordini type 16', 'gordini straight - 6', '0'], ['1954', 'onofre marimã cubicn', 'maserati a6 gcm / 250f', 'maserati straight - 6', '0'], ['1955', 'officine alfieri maserati', 'maserati 250f', 'maserati straight - 6', '2'], ['1956', 'officine alfieri maserati', 'maserati 250f', 'maserati straight - 6', '0'], ['1957', 'officine alfieri maserati', 'maserati 250f', 'maserati straight - 6', '4'], ['1958', 'scuderia sud americana', 'maserati 250f', 'maserati straight - 6', '0'], ['1960', 'scuderia centro sud', 'cooper t51', 'maserati straight - 4', '3']] |
nfl international series | https://en.wikipedia.org/wiki/NFL_International_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15558076-1.html.csv | comparative | the dolphins had a game in the nfl international series before the saints did . | {'row_1': '1', 'row_2': '2', 'col': '1', 'col_other': '5', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'designated home', 'miami dolphins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose designated home record fuzzily matches to miami dolphins .', 'tostr': 'filter_eq { all_rows ; designated home ; miami dolphins }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; designated home ; miami dolphins } ; year }', 'tointer': 'select the rows whose designated home record fuzzily matches to miami dolphins . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'designated home', 'new orleans saints'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose designated home record fuzzily matches to new orleans saints .', 'tostr': 'filter_eq { all_rows ; designated home ; new orleans saints }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; designated home ; new orleans saints } ; year }', 'tointer': 'select the rows whose designated home record fuzzily matches to new orleans saints . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; designated home ; miami dolphins } ; year } ; hop { filter_eq { all_rows ; designated home ; new orleans saints } ; year } } = true', 'tointer': 'select the rows whose designated home record fuzzily matches to miami dolphins . take the year record of this row . select the rows whose designated home record fuzzily matches to new orleans saints . take the year record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; designated home ; miami dolphins } ; year } ; hop { filter_eq { all_rows ; designated home ; new orleans saints } ; year } } = true | select the rows whose designated home record fuzzily matches to miami dolphins . take the year record of this row . select the rows whose designated home record fuzzily matches to new orleans saints . take the year record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'designated home_7': 7, 'miami dolphins_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'designated home_11': 11, 'new orleans saints_12': 12, 'year_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'designated home_7': 'designated home', 'miami dolphins_8': 'miami dolphins', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'designated home_11': 'designated home', 'new orleans saints_12': 'new orleans saints', 'year_13': 'year'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'designated home_7': [0], 'miami dolphins_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'designated home_11': [1], 'new orleans saints_12': [1], 'year_13': [3]} | ['year', 'date', 'television', 'designated visitors', 'designated home', 'stadium', 'city'] | [['2007', 'october 28', 'fox', 'new york giants', 'miami dolphins', 'wembley stadium', 'london'], ['2008', 'october 26', 'cbs', 'san diego chargers', 'new orleans saints', 'wembley stadium', 'london'], ['2009', 'october 25', 'cbs', 'new england patriots', 'tampa bay buccaneers', 'wembley stadium', 'london'], ['2010', 'october 31', 'cbs', 'denver broncos', 'san francisco 49ers', 'wembley stadium', 'london'], ['2011', 'october 23', 'fox', 'chicago bears', 'tampa bay buccaneers', 'wembley stadium', 'london'], ['2012', 'october 28', 'cbs', 'new england patriots', 'st louis rams', 'wembley stadium', 'london'], ['2013', 'september 29', 'cbs', 'pittsburgh steelers', 'minnesota vikings', 'wembley stadium', 'london'], ['2013', 'october 27', 'fox', 'san francisco 49ers', 'jacksonville jaguars', 'wembley stadium', 'london'], ['2014', 'tba', 'tba', 'detroit lions', 'atlanta falcons', 'wembley stadium', 'london'], ['2014', 'tba', 'tba', 'dallas cowboys', 'jacksonville jaguars', 'wembley stadium', 'london'], ['2014', 'tba', 'tba', 'miami dolphins', 'oakland raiders', 'wembley stadium', 'london'], ['2015', 'tba', 'tba', 'tba', 'jacksonville jaguars', 'wembley stadium', 'london'], ['2016', 'tba', 'tba', 'tba', 'jacksonville jaguars', 'wembley stadium', 'london']] |
list of vancouver canucks draft picks | https://en.wikipedia.org/wiki/List_of_Vancouver_Canucks_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11636955-20.html.csv | unique | paul constantin was the only lake superior state university player picked . | {'scope': 'all', 'row': '9', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'lake superior state university ( ncaa )', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team ( league )', 'lake superior state university ( ncaa )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team ( league ) record fuzzily matches to lake superior state university ( ncaa ) .', 'tostr': 'filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) } }', 'tointer': 'select the rows whose team ( league ) record fuzzily matches to lake superior state university ( ncaa ) . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team ( league )', 'lake superior state university ( ncaa )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team ( league ) record fuzzily matches to lake superior state university ( ncaa ) .', 'tostr': 'filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) }'}, 'player'], 'result': 'paul constantin', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) } ; player }'}, 'paul constantin'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) } ; player } ; paul constantin }', 'tointer': 'the player record of this unqiue row is paul constantin .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) } } ; eq { hop { filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) } ; player } ; paul constantin } } = true', 'tointer': 'select the rows whose team ( league ) record fuzzily matches to lake superior state university ( ncaa ) . there is only one such row in the table . the player record of this unqiue row is paul constantin .'} | and { only { filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) } } ; eq { hop { filter_eq { all_rows ; team ( league ) ; lake superior state university ( ncaa ) } ; player } ; paul constantin } } = true | select the rows whose team ( league ) record fuzzily matches to lake superior state university ( ncaa ) . there is only one such row in the table . the player record of this unqiue row is paul constantin . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team (league)_7': 7, 'lake superior state university (ncaa)_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'paul constantin_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team (league)_7': 'team ( league )', 'lake superior state university (ncaa)_8': 'lake superior state university ( ncaa )', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'paul constantin_10': 'paul constantin'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'team (league)_7': [0], 'lake superior state university (ncaa)_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'paul constantin_10': [3]} | ['rd', 'pick', 'player', 'team ( league )', 'reg gp', 'pl gp'] | [['1', '2', 'trevor linden', 'medicine hat tigers ( whl )', '1140', '118'], ['2', '33', 'leif rohlin', 'vik v채ster책s hk ( swe )', '95', '5'], ['3', '44', 'dane jackson', 'vernon lakers ( bcjhl )', '15', '6'], ['6', '107', "corrie d'alessio", 'cornell university ( ncaa )', '0', '0'], ['6', '122', 'phil von stefenelli', 'boston university ( ncaa )', '0', '0'], ['7', '128', 'dixon ward', 'university of north dakota ( ncaa )', '103', '9'], ['8', '149', 'greg geldart', 'st albert saints ( ajhl )', '0', '0'], ['9', '170', 'roger akerstrom', 'lule책 hf ( swe )', '0', '0'], ['10', '191', 'paul constantin', 'lake superior state university ( ncaa )', '0', '0'], ['11', '212', 'chris wolanin', 'university of illinois ( ncaa )', '0', '0'], ['12', '233', 'stefan nilsson', 'f채rjestad bk ( swe )', '0', '0']] |
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/2-18652198-4.html.csv | unique | between the 25th and 32nd picks , george donelly was the only defensive back that was drafted . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'defensive back', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', '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': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; defensive back } }', 'tointer': 'select the rows whose position record fuzzily matches to defensive back . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', '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 }'}, 'player'], 'result': 'george donnelly', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; defensive back } ; player }'}, 'george donnelly'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; defensive back } ; player } ; george donnelly }', 'tointer': 'the player record of this unqiue row is george donnelly .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; defensive back } } ; eq { hop { filter_eq { all_rows ; position ; defensive back } ; player } ; george donnelly } } = true', 'tointer': 'select the rows whose position record fuzzily matches to defensive back . there is only one such row in the table . the player record of this unqiue row is george donnelly .'} | and { only { filter_eq { all_rows ; position ; defensive back } } ; eq { hop { filter_eq { all_rows ; position ; defensive back } ; player } ; george donnelly } } = true | select the rows whose position record fuzzily matches to defensive back . there is only one such row in the table . the player record of this unqiue row is george donnelly . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'defensive back_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'george donnelly_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'defensive back_8': 'defensive back', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'george donnelly_10': 'george donnelly'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'defensive back_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'george donnelly_10': [3]} | ['pick', 'team', 'player', 'position', 'college'] | [['25', 'denver broncos', 'george donnelly', 'defensive back', 'illinois'], ['26', 'houston oilers', 'bobby maples', 'center', 'baylor'], ['27', 'oakland raiders', 'gus otto', 'linebacker', 'missouri'], ['28', 'new york jets', 'bob schweickert', 'quarterback', 'virginia tech'], ['29', 'kansas city chiefs', 'otis taylor', 'linebacker', 'prairie view a & m'], ['30', 'san diego chargers', 'steve tensi', 'quarterback', 'florida state'], ['31', 'boston patriots', 'ellis johnson', 'halfback', 'southeastern louisiana'], ['32', 'kansas city chiefs ( from buffalo bills )', 'frank pitts', 'wide receiver', 'saginaw valley state']] |
list of radio stations in tamaulipas | https://en.wikipedia.org/wiki/List_of_radio_stations_in_Tamaulipas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17982829-17.html.csv | unique | la poderosa is the only radio station in santa elena . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'santa elena', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city of license', 'santa elena'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city of license record fuzzily matches to santa elena .', 'tostr': 'filter_eq { all_rows ; city of license ; santa elena }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; city of license ; santa elena } }', 'tointer': 'select the rows whose city of license record fuzzily matches to santa elena . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city of license', 'santa elena'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city of license record fuzzily matches to santa elena .', 'tostr': 'filter_eq { all_rows ; city of license ; santa elena }'}, 'brand'], 'result': 'la poderosa', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; city of license ; santa elena } ; brand }'}, 'la poderosa'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; city of license ; santa elena } ; brand } ; la poderosa }', 'tointer': 'the brand record of this unqiue row is la poderosa .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; city of license ; santa elena } } ; eq { hop { filter_eq { all_rows ; city of license ; santa elena } ; brand } ; la poderosa } } = true', 'tointer': 'select the rows whose city of license record fuzzily matches to santa elena . there is only one such row in the table . the brand record of this unqiue row is la poderosa .'} | and { only { filter_eq { all_rows ; city of license ; santa elena } } ; eq { hop { filter_eq { all_rows ; city of license ; santa elena } ; brand } ; la poderosa } } = true | select the rows whose city of license record fuzzily matches to santa elena . there is only one such row in the table . the brand record of this unqiue row is la poderosa . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'city of license_7': 7, 'santa elena_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'brand_9': 9, 'la poderosa_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'city of license_7': 'city of license', 'santa elena_8': 'santa elena', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'brand_9': 'brand', 'la poderosa_10': 'la poderosa'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'city of license_7': [0], 'santa elena_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'brand_9': [2], 'la poderosa_10': [3]} | ['frequency', 'callsign', 'brand', 'city of license', 'type'] | [['580', 'xehp', 'la mas prendida', 'ciudad victoria', 'norteño'], ['640', 'xetam', 'la poderosa', 'santa elena', 'norteño'], ['970', 'xebj - am', 'radio 970', 'ciudad victoria', 'contemporary'], ['1340', 'xerpv - am', 'la cotorra', 'ciudad victoria', 'norteño'], ['1380', 'xegw', 'planeta w 1380', 'ciudad victoria', 'christian pop'], ['1480', 'xevic', 'radio tamaulipas', 'ciudad victoria', 'state government']] |
2001 ansett australia cup | https://en.wikipedia.org/wiki/2001_Ansett_Australia_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16388439-2.html.csv | majority | most of the games in the 2001 ansett australia cup were played on fridays . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friday', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date', 'friday'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them fuzzily match to friday .', 'tostr': 'most_eq { all_rows ; date ; friday } = true'} | most_eq { all_rows ; date ; friday } = true | for the date records of all rows , most of them fuzzily match to friday . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'friday_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'friday_4': 'friday'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'friday_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'date', 'crowd'] | [['collingwood', '12.14 ( 86 )', 'st kilda', '10.8 ( 68 )', 'colonial stadium', 'friday , 16 february', '30072'], ['west coast', '6.11 ( 47 )', 'kangaroos', '14.12 ( 96 )', 'subiaco oval', 'friday , 16 february', '16905'], ['kangaroos', '14.12 ( 96 )', 'st kilda', '12.9 ( 81 )', 'manuka oval', 'saturday , 24 february', '8157'], ['west coast', '12.6 ( 78 )', 'collingwood', '12.8 ( 80 )', 'subiaco oval', 'saturday , 24 february', '16090'], ['st kilda', '19.9 ( 123 )', 'west coast', '15.7 ( 97 )', 'colonial stadium', 'friday , 2 march', '8642']] |
1982 vfl season | https://en.wikipedia.org/wiki/1982_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10824095-11.html.csv | unique | in the 1982 vfl season , when the crowd is over 20000 , the only time the venue was victoria park was when the home team is collingwood . | {'scope': 'subset', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'victoria park', 'subset': {'col': '6', 'criterion': 'greater_than', 'value': '20000'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '20000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; crowd ; 20000 }', 'tointer': 'select the rows whose crowd record is greater than 20000 .'}, 'venue', 'victoria park'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to victoria park .', 'tostr': 'filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park } }', 'tointer': 'select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to victoria park . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '20000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; crowd ; 20000 }', 'tointer': 'select the rows whose crowd record is greater than 20000 .'}, 'venue', 'victoria park'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to victoria park .', 'tostr': 'filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park }'}, 'home team'], 'result': 'collingwood', 'ind': 3, 'tostr': 'hop { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park } ; home team }'}, 'collingwood'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park } ; home team } ; collingwood }', 'tointer': 'the home team record of this unqiue row is collingwood .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park } } ; eq { hop { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park } ; home team } ; collingwood } } = true', 'tointer': 'select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to victoria park . there is only one such row in the table . the home team record of this unqiue row is collingwood .'} | and { only { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park } } ; eq { hop { filter_eq { filter_greater { all_rows ; crowd ; 20000 } ; venue ; victoria park } ; home team } ; collingwood } } = true | select the rows whose crowd record is greater than 20000 . among these rows , select the rows whose venue record fuzzily matches to victoria park . there is only one such row in the table . the home team record of this unqiue row is collingwood . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_7': 7, 'crowd_8': 8, '20000_9': 9, 'venue_10': 10, 'victoria park_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'home team_12': 12, 'collingwood_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', '20000_9': '20000', 'venue_10': 'venue', 'victoria park_11': 'victoria park', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'home team_12': 'home team', 'collingwood_13': 'collingwood'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_greater_0': [1], 'all_rows_7': [0], 'crowd_8': [0], '20000_9': [0], 'venue_10': [1], 'victoria park_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'home team_12': [3], 'collingwood_13': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '20.14 ( 134 )', 'swans', '18.25 ( 133 )', 'mcg', '28216', '5 june 1982'], ['hawthorn', '26.22 ( 178 )', 'melbourne', '14.15 ( 99 )', 'princes park', '14087', '5 june 1982'], ['collingwood', '26.16 ( 172 )', 'st kilda', '21.10 ( 136 )', 'victoria park', '26657', '5 june 1982'], ['geelong', '10.11 ( 71 )', 'essendon', '17.9 ( 111 )', 'kardinia park', '29884', '5 june 1982'], ['north melbourne', '13.18 ( 96 )', 'carlton', '15.15 ( 105 )', 'arden street oval', '26206', '5 june 1982'], ['fitzroy', '23.22 ( 160 )', 'footscray', '16.12 ( 108 )', 'vfl park', '13908', '5 june 1982']] |
2009 open championship | https://en.wikipedia.org/wiki/2009_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811509-5.html.csv | aggregation | in the 2009 open championship , the average number of strokes to par was 3 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'to par'], 'result': '3', 'ind': 0, 'tostr': 'avg { all_rows ; to par }'}, '3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; to par } ; 3 } = true', 'tointer': 'the average of the to par record of all rows is 3 .'} | round_eq { avg { all_rows ; to par } ; 3 } = true | the average of the to par record of all rows is 3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'to par_4': 4, '3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '3_5': '3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'to par_4': [0], '3_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'steve marino', 'united states', '67 + 68 = 135', '5'], ['t1', 'tom watson', 'united states', '65 + 70 = 135', '5'], ['3', 'mark calcavecchia', 'united states', '67 + 69 = 136', '4'], ['t4', 'ross fisher', 'england', '69 + 68 = 137', '3'], ['t4', 'retief goosen', 'south africa', '67 + 70 = 137', '3'], ['t4', 'miguel ángel jiménez', 'spain', '64 + 73 = 137', '3'], ['t4', 'kenichi kuboya', 'japan', '65 + 72 = 137', '3'], ['t4', 'vijay singh', 'fiji', '67 + 70 = 137', '3'], ['t9', 'stewart cink', 'united states', '66 + 72 = 138', '2'], ['t9', 'j b holmes', 'united states', '68 + 70 = 138', '2'], ['t9', 'mathew goggin', 'australia', '66 + 72 = 138', '2'], ['t9', 'james kingston', 'south africa', '67 + 71 = 138', '2'], ['t9', 'lee westwood', 'england', '68 + 70 = 138', '2']] |
1982 world series | https://en.wikipedia.org/wiki/1982_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1218008-1.html.csv | majority | the majority of games in the 1982 world series were played at busch stadium . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'busch stadium', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'busch stadium'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to busch stadium .', 'tostr': 'most_eq { all_rows ; location ; busch stadium } = true'} | most_eq { all_rows ; location ; busch stadium } = true | for the location records of all rows , most of them fuzzily match to busch stadium . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'busch stadium_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'busch stadium_4': 'busch stadium'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'busch stadium_4': [0]} | ['game', 'date', 'score', 'location', 'time', 'attendance'] | [['1', 'october 12', 'milwaukee brewers - 10 , st louis cardinals - 0', 'busch stadium ( ii )', '2:30', '53723'], ['2', 'october 13', 'milwaukee brewers - 4 , st louis cardinals - 5', 'busch stadium ( ii )', '2:54', '53723'], ['3', 'october 15', 'st louis cardinals - 6 , milwaukee brewers - 2', 'county stadium', '2:53', '56556'], ['4', 'october 16', 'st louis cardinals - 5 , milwaukee brewers - 7', 'county stadium', '3:04', '56560'], ['5', 'october 17', 'st louis cardinals - 4 , milwaukee brewers - 6', 'county stadium', '3:02', '56562'], ['6', 'october 19', 'milwaukee brewers - 1 , st louis cardinals - 13', 'busch stadium ( ii )', '2:21', '53723'], ['7', 'october 20', 'milwaukee brewers - 3 , st louis cardinals - 6', 'busch stadium ( ii )', '2:50', '53723']] |
dexter ( season 3 ) | https://en.wikipedia.org/wiki/Dexter_%28season_3%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24132054-1.html.csv | majority | the majority of episodes of dexter season 3 us viewer totals are n/a . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'n / a', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'us viewers ( millions )', 'n / a'], 'result': True, 'ind': 0, 'tointer': 'for the us viewers ( millions ) records of all rows , most of them fuzzily match to n / a .', 'tostr': 'most_eq { all_rows ; us viewers ( millions ) ; n / a } = true'} | most_eq { all_rows ; us viewers ( millions ) ; n / a } = true | for the us viewers ( millions ) records of all rows , most of them fuzzily match to n / a . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'us viewers (millions)_3': 3, 'n / a_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'us viewers (millions)_3': 'us viewers ( millions )', 'n / a_4': 'n / a'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'us viewers (millions)_3': [0], 'n / a_4': [0]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['25', '1', 'our father', 'keith gordon', 'clyde phillips', 'september 28 , 2008', 'n / a'], ['26', '2', 'finding freebo', 'marcos siega', 'melissa rosenberg', 'october 5 , 2008', '0.79'], ['27', '3', 'the lion sleeps tonight', 'john dahl', 'scott buck', 'october 12 , 2008', 'n / a'], ['28', '4', 'all in the family', 'keith gordon', 'adam e fierro', 'october 19 , 2008', '0.86'], ['29', '5', 'turning biminese', 'marcos siega', 'tim schlattmann', 'october 26 , 2008', 'n / a'], ['30', '6', 'sã\xad se puede', 'ernest dickerson', 'charles h eglee', 'november 2 , 2008', 'n / a'], ['31', '7', 'easy as pie', 'steve shill', 'lauren gussis', 'november 9 , 2008', 'n / a'], ['32', '8', 'the damage a man can do', 'marcos siega', 'scott buck', 'november 16 , 2008', 'n / a'], ['34', '10', 'go your own way', 'john dahl', 'tim schlattmann', 'november 30 , 2008', 'n / a'], ['35', '11', 'i had a dream', 'marcos siega', 'charles h eglee and lauren gussis', 'december 7 , 2008', 'n / a']] |
1975 - 76 phoenix suns season | https://en.wikipedia.org/wiki/1975%E2%80%9376_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30047613-14.html.csv | aggregation | the suns scored over 200 points when they played in the arizona veterans memorial coliseum . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '200', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'arizona veterans memorial coliseum'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'arizona veterans memorial coliseum'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; arizona veterans memorial coliseum }', 'tointer': 'select the rows whose location attendance record fuzzily matches to arizona veterans memorial coliseum .'}, 'score'], 'result': '200', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; location attendance ; arizona veterans memorial coliseum } ; score }'}, '200'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; location attendance ; arizona veterans memorial coliseum } ; score } ; 200 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to arizona veterans memorial coliseum . the sum of the score record of these rows is 200 .'} | round_eq { sum { filter_eq { all_rows ; location attendance ; arizona veterans memorial coliseum } ; score } ; 200 } = true | select the rows whose location attendance record fuzzily matches to arizona veterans memorial coliseum . the sum of the score record of these rows is 200 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'arizona veterans memorial coliseum_6': 6, 'score_7': 7, '200_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'arizona veterans memorial coliseum_6': 'arizona veterans memorial coliseum', 'score_7': 'score', '200_8': '200'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'arizona veterans memorial coliseum_6': [0], 'score_7': [1], '200_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'location attendance', 'series', 'streak'] | [['1', 'may 23', 'boston', 'l 87 - 98', 'alvan adams ( 26 )', 'curtis perry ( 10 )', 'boston garden 15320', '0 - 1', 'l 1'], ['2', 'may 27', 'boston', 'l 90 - 105', 'paul westphal ( 28 )', 'alvan adams ( 15 )', 'boston garden 15320', '0 - 2', 'l 2'], ['3', 'may 30', 'boston', 'w 105 - 98', 'alvan adams ( 33 )', 'alvan adams ( 14 )', 'arizona veterans memorial coliseum 12884', '1 - 2', 'w 1'], ['4', 'june 2', 'boston', 'w 109 - 107', 'paul westphal ( 28 )', 'gar heard ( 15 )', 'arizona veterans memorial coliseum 13306', '2 - 2', 'w 2'], ['5', 'june 4', 'boston', 'l 126 - 128 ( 3ot )', 'ricky sobers , paul westphal ( 25 )', 'curtis perry ( 15 )', 'boston garden 15320', '2 - 3', 'l 1']] |
new york state election , 1930 | https://en.wikipedia.org/wiki/New_York_state_election%2C_1930 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15563525-1.html.csv | majority | the majority of office positions in the ny state 1930 elections had a man listed as the socialist ticket . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'man', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'socialist ticket', 'man'], 'result': True, 'ind': 0, 'tointer': 'for the socialist ticket records of all rows , most of them fuzzily match to man .', 'tostr': 'most_eq { all_rows ; socialist ticket ; man } = true'} | most_eq { all_rows ; socialist ticket ; man } = true | for the socialist ticket records of all rows , most of them fuzzily match to man . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'socialist ticket_3': 3, 'man_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'socialist ticket_3': 'socialist ticket', 'man_4': 'man'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'socialist ticket_3': [0], 'man_4': [0]} | ['office', 'democratic ticket', 'republican ticket', 'law preservation ticket', 'socialist ticket', 'socialist labor ticket'] | [['governor', 'franklin d roosevelt', 'charles h tuttle', 'robert p carroll', 'louis waldman', 'jeremiah d crowley'], ['lieutenant governor', 'herbert h lehman', 'caleb h baumes', '( none )', 'elizabeth c roth', 'charles m carlson'], ['comptroller', 'morris s tremaine', 'daniel h conway', '( none )', 'william h hilsdorf', 'john e delee'], ['attorney general', 'john j bennett , jr', 'isadore bookstein', '( none )', 'william karlin', 'august gillhaus'], ['judge of the court of appeals', 'cuthbert w pound', 'cuthbert w pound', '( none )', 'darwin j meserole', 'belle j rosen']] |
2005 japanese television dramas | https://en.wikipedia.org/wiki/2005_Japanese_television_dramas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18540104-1.html.csv | superlative | rikon bengoshi ii ~ handsome woman ~ is the 2005 japanese tv drama with the lowest average rating on fuji tv . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'fuji tv'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tv station', 'fuji tv'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; tv station ; fuji tv }', 'tointer': 'select the rows whose tv station record fuzzily matches to fuji tv .'}, 'average ratings'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; tv station ; fuji tv } ; average ratings }'}, 'romaji title'], 'result': 'rikon bengoshi ii ~ handsome woman ~', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; tv station ; fuji tv } ; average ratings } ; romaji title }'}, 'rikon bengoshi ii ~ handsome woman ~'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; tv station ; fuji tv } ; average ratings } ; romaji title } ; rikon bengoshi ii ~ handsome woman ~ } = true', 'tointer': 'select the rows whose tv station record fuzzily matches to fuji tv . select the row whose average ratings record of these rows is minimum . the romaji title record of this row is rikon bengoshi ii ~ handsome woman ~ .'} | eq { hop { argmin { filter_eq { all_rows ; tv station ; fuji tv } ; average ratings } ; romaji title } ; rikon bengoshi ii ~ handsome woman ~ } = true | select the rows whose tv station record fuzzily matches to fuji tv . select the row whose average ratings record of these rows is minimum . the romaji title record of this row is rikon bengoshi ii ~ handsome woman ~ . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'tv station_6': 6, 'fuji tv_7': 7, 'average ratings_8': 8, 'romaji title_9': 9, 'rikon bengoshi ii ~handsome woman~_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'tv station_6': 'tv station', 'fuji tv_7': 'fuji tv', 'average ratings_8': 'average ratings', 'romaji title_9': 'romaji title', 'rikon bengoshi ii ~handsome woman~_10': 'rikon bengoshi ii ~ handsome woman ~'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'tv station_6': [0], 'fuji tv_7': [0], 'average ratings_8': [1], 'romaji title_9': [2], 'rikon bengoshi ii ~handsome woman~_10': [3]} | ['japanese title', 'romaji title', 'tv station', 'theme song ( s )', 'episodes', 'average ratings'] | [['恋におちたら ～ 僕の成功の秘密 ～', 'koi ni ochitara ~ boku no seikou no himitsu ~', 'fuji tv', 'crystal kay 恋におちたら ( koi ni ochitara )', '11', '16.3 %'], ['離婚弁護士ii ～ ハンサムウーマン ～', 'rikon bengoshi ii ~ handsome woman ~', 'fuji tv', 'hoshimura mai every', '11', '13.2 %'], ['エンジン', 'engine', 'fuji tv', 'jimmy cliff i can see clearly now', '11', '22.4 %'], ['曲がり角の彼女', 'magarikado no kanojo', 'fuji tv', 'shela dear my friends', '11', '14.5 %'], ['夢で逢いましょう', 'yume de aimashou', 'tbs', 'yumi matsutouya ついてゆくわ ( tsuiteyuku wa )', '11', '11.6 %'], ['汚れた舌', 'kegareta shita', 'tbs', 'dorlis 肌のすきま ( hada no sukima )', '11', '10.0 %'], ['あいくるしい', 'ai kurushii', 'tbs', 'michael jackson ben', '11', '11.6 %'], ['タイガー & ドラゴン', 'tiger & dragon', 'tbs', 'v6 utao - utao', '11', '12.8 %'], ['雨と夢のあとに', 'ame to yume no ato ni', 'tv asahi', 'miwako okuda 雨と夢のあとに ( ame to yume no ato ni )', '10', '9.8 %'], ['アタックno1', 'attack no1', 'tv asahi', 'aya ueto 夢のチカラ ( yume no chikara )', '11', '13.1 %'], ['瑠璃の島', 'ruri no shima', 'ntv', 'kobukuro ここにしか咲かない花 ( koko ni shika sakanai hana )', '10', '12.6 %']] |
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 | aggregation | the average enrollment of naia independent football schools is 1,285 students . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1,285', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'enrollment'], 'result': '1,285', 'ind': 0, 'tostr': 'avg { all_rows ; enrollment }'}, '1,285'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; enrollment } ; 1,285 } = true', 'tointer': 'the average of the enrollment record of all rows is 1,285 .'} | round_eq { avg { all_rows ; enrollment } ; 1,285 } = true | the average of the enrollment record of all rows is 1,285 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '1,285_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '1,285_5': '1,285'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '1,285_5': [1]} | ['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 indian nations university', 'lawrence , kansas', '1884', 'tribal', '1000', 'fighting indians', 'mcac'], ['jamestown college', 'jamestown , north dakota', '1883', 'private', '967', 'jimmies', 'none'], ['lindenwood universitybelleville', 'belleville , illinois', '2003', 'private', '2600', 'lynx', 'none'], ['mayville state university', 'mayville , north dakota', '1889', 'public', '825', 'comets', 'none'], ['menlo college', 'atherton , california', '1927', 'private', '650', 'oaks', 'calpac'], ['point university', 'west point , georgia', '1937', 'private', '1035', 'skyhawks', 'aac'], ['valley city state university', 'valley city , north dakota', '1890', 'public', '1340', 'vikings', 'none'], ['webber international university', 'babson park , florida', '1927', 'private', '616', 'warriors', 'the sun']] |
imperial vicar | https://en.wikipedia.org/wiki/Imperial_vicar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11071897-1.html.csv | aggregation | all imperial vicars have an average interregnum duration of around 6 months 7 days . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '6 months 7 days', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'duration'], 'result': '6 months 7 days', 'ind': 0, 'tostr': 'avg { all_rows ; duration }'}, '6 months 7 days'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; duration } ; 6 months 7 days } = true', 'tointer': 'the average of the duration record of all rows is 6 months 7 days .'} | round_eq { avg { all_rows ; duration } ; 6 months 7 days } = true | the average of the duration record of all rows is 6 months 7 days . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'duration_4': 4, '6 months 7 days_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'duration_4': 'duration', '6 months 7 days_5': '6 months 7 days'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'duration_4': [0], '6 months 7 days_5': [1]} | ['interregnum began', 'interregnum ended', 'duration', 'count palatine of saxony', 'count palatine of the rhine'] | [['9 december 1437 death of sigismund', '18 march 1438 election of albert ii', '3 months , 9 days', 'frederick ii , elector of saxony', 'louis iv , elector palatine'], ['27 october 1439 death of albert ii', '2 february 1440 election of frederick iii', '3 months , 6 days', 'frederick ii , elector of saxony', 'louis iv , elector palatine'], ['12 january 1519 death of maximilian i', '17 june 1519 election of charles v', '5 months , 5 days', 'frederick iii , elector of saxony', 'louis v , elector palatine'], ['20 january 1612 death of rudolph ii', '13 june 1612 election of matthias', '4 months , 24 days', 'john george i , elector of saxony', 'frederick v , elector palatine'], ['20 march 1619 death of matthias', '28 august 1619 election of ferdinand ii', '5 months , 8 days', 'john george i , elector of saxony', 'frederick v , elector palatine'], ['2 april 1657 death of ferdinand iii', '18 july 1658 election of leopold i', '15 months , 16 days', 'john george ii , elector of saxony', 'ferdinand maria , elector of bavaria'], ['17 april 1711 death of joseph i', '12 october 1711 election of charles vi', '5 months , 25 days', 'frederick augustus i , elector of saxony', 'john william , elector palatine'], ['20 october 1740 death of charles vi', '14 january 1742 election of charles vii', '14 months , 25 days', 'frederick augustus ii , elector of saxony', 'charles albert , elector of bavaria'], ['20 january 1745 death of charles vii', '13 september 1745 election of francis i', '7 months , 24 days', 'frederick augustus ii , elector of saxony', 'maximilian iii , elector of bavaria'], ['20 february 1790 death of joseph ii', '30 september 1790 election of leopold ii', '7 months , 10 days', 'frederick augustus iii , elector of saxony', 'charles theodore , elector of bavaria']] |
fiba world olympic qualifying tournament for men 2008 squads | https://en.wikipedia.org/wiki/FIBA_World_Olympic_Qualifying_Tournament_for_Men_2008_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18228282-1.html.csv | majority | most of the men in the fiba olympic qualifying tournament for men in 2008 were over 1.90 in height . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '1.9', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'height', '1.9'], 'result': True, 'ind': 0, 'tointer': 'for the height records of all rows , most of them are greater than 1.9 .', 'tostr': 'most_greater { all_rows ; height ; 1.9 } = true'} | most_greater { all_rows ; height ; 1.9 } = true | for the height records of all rows , most of them are greater than 1.9 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'height_3': 3, '1.9_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'height_3': 'height', '1.9_4': '1.9'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'height_3': [0], '1.9_4': [0]} | ['player', 'height', 'position', 'year born ( age )', 'current club'] | [['marcelo magalhães machado', '2.00', 'sf', 'april 12 , 1975 ( age38 )', 'flamengo'], ['eduardo magalhães machado', '1.91', 'sf', 'september 10 , 1982 ( age31 )', 'menorca bàsquet'], ['murilo da rosa', '2.11', 'f / c', 'july 14 , 1983 ( age30 )', 'maccabi tel aviv'], ['ricardo probst', '2.00', 'sf', 'april 13 , 1976 ( age37 )', 'conti / assis'], ['fulvio chiantia de assis', '1.87', 'g', 'august 15 , 1981 ( age32 )', 'paulistano'], ['marcelinho huertas', '1.91', 'pg', 'may 25 , 1983 ( age30 )', 'fortitudo bologna'], ['alex garcia', '1.91', 'sg', 'march 4 , 1980 ( age33 )', 'maccabi tel aviv'], ['marcus vinicius urban toledo dos reis', '2.03', 'f', 'july 10 , 1986 ( age27 )', 'plus pujol lleida'], ['rafael araújo', '2.11', 'c', 'august 12 , 1980 ( age33 )', 'spartak saint petersburg'], ['joão paulo batista', '2.08', 'c', 'october 29 , 1981 ( age32 )', 'barons lmt'], ['jonathan tavernari', '1.96', 'f', 'june 18 , 1987 ( age26 )', 'brigham young university'], ['tiago splitter', '2.11', 'pf / c', 'january 1 , 1985 ( age29 )', 'tau cerámica']] |
shim eun - ha | https://en.wikipedia.org/wiki/Shim_Eun-ha | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11266821-1.html.csv | ordinal | the first film that shim eun - ha appeared in was my old sweetheart . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 1 }'}, 'english title'], 'result': 'my old sweetheart', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 1 } ; english title }'}, 'my old sweetheart'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 1 } ; english title } ; my old sweetheart } = true', 'tointer': 'select the row whose year record of all rows is 1st minimum . the english title record of this row is my old sweetheart .'} | eq { hop { nth_argmin { all_rows ; year ; 1 } ; english title } ; my old sweetheart } = true | select the row whose year record of all rows is 1st minimum . the english title record of this row is my old sweetheart . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '1_6': 6, 'english title_7': 7, 'my old sweetheart_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_5': 'year', '1_6': '1', 'english title_7': 'english title', 'my old sweetheart_8': 'my old sweetheart'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '1_6': [0], 'english title_7': [1], 'my old sweetheart_8': [2]} | ['year', 'english title', 'korean title', 'romanization', 'role', 'director'] | [['1995', 'my old sweetheart', '아찌 아빠', 'ajji appa', 'nam yoo - ri', 'shin seung - soo'], ['1996', 'born to kill', '본 투 킬', 'bon tu kil', 'jung soo - ha', 'jang hyun - soo'], ['1998', 'christmas in august', '8월의 크리스마스', 'palweolui keuriseumaseu', 'kim da - rim', 'hur jin - ho'], ['1998', 'art museum by the zoo', '미술관 옆 동물원', 'misulgwan yup dongmulwon', 'lee choon - hee', 'lee jeong - hyang'], ['1999', 'the uprising', '이재수의 난', 'lee jae - su - eui nan', 'il sook - hwa', 'park kwang - su'], ['1999', 'tell me something', '텔 미 썸딩', 'telmisseomding', 'chae soo - yeon', 'jang yoon - hyun'], ['2000', 'interview', '인터뷰', 'in - teo - byoo', 'lee young - hee', 'byun hyuk ( daniel h byun )']] |
canonicus - class monitor | https://en.wikipedia.org/wiki/Canonicus-class_monitor | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12592074-1.html.csv | majority | for the canonicus - class monitors that were commissioned or completed in 1864 , they were all were laid down in 1862 . | {'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '1862', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': '1864'}} | {'func': 'all_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'commissioned or completed', '1864'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; commissioned or completed ; 1864 }', 'tointer': 'select the rows whose commissioned or completed record fuzzily matches to 1864 .'}, 'laid down', '1862'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose commissioned or completed record fuzzily matches to 1864 . for the laid down records of these rows , all of them are equal to 1862 .', 'tostr': 'all_eq { filter_eq { all_rows ; commissioned or completed ; 1864 } ; laid down ; 1862 } = true'} | all_eq { filter_eq { all_rows ; commissioned or completed ; 1864 } ; laid down ; 1862 } = true | select the rows whose commissioned or completed record fuzzily matches to 1864 . for the laid down records of these rows , all of them are equal to 1862 . | 2 | 2 | {'all_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'commissioned or completed_4': 4, '1864_5': 5, 'laid down_6': 6, '1862_7': 7} | {'all_eq_1': 'all_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'commissioned or completed_4': 'commissioned or completed', '1864_5': '1864', 'laid down_6': 'laid down', '1862_7': '1862'} | {'all_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'commissioned or completed_4': [0], '1864_5': [0], 'laid down_6': [1], '1862_7': [1]} | ['ship', 'builder', 'namesake', 'renamed', 'laid down', 'launched', 'commissioned or completed'] | [['ajax', 'snowden & mason , pittsburgh , pennsylvania', 'manayunk , philadelphia', 'manayunk , 1862 , ajax , 15 june 1869', '1862', '18 december 1864', '27 september 1865'], ['canonicus', 'harrison loring , boston , massachusetts', 'canonicus', 'scylla , 15 june 1869 , canonicus , 10 august 1869', '1862', '1 august 1863', '16 april 1864'], ['catawba', 'alexander swift & company , cincinnati , ohio', 'catawba river', 'atahualpa', '1862', '13 april 1864', '10 june 1865'], ['mahopac', 'secor & co , jersey city , new jersey', 'lake mahopac', 'castor , 15 june 1869 , mahopac , 10 august 1869', '1862', '17 may 1864', '22 september 1864'], ['manhattan', 'perine , secor & co , jersey city , new jersey', 'manhattan indians', 'neptune , 15 june 1869 , manhattan , 10 august 1869', '1862', '14 october 1863', '6 june 1864'], ['oneota', 'alexander swift & company , cincinnati , ohio', 'oneota tribe of the sioux indians', 'manco cã ¡ pac', '1862', '21 may 1864', '10 june 1865'], ['saugus', 'harlan & hollingsworth , wilmington , delaware', 'saugus , massachusetts', 'centaur , 15 june 1869 , saugus , 10 august 1869', '1862', '8 february 1864', '27 august 1864'], ['tecumseh', 'charles secor & co , jersey city , new jersey', 'tecumseh', 'not applicable', '1862', '12 september 1863', '19 april 1864']] |
1980 open championship | https://en.wikipedia.org/wiki/1980_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18171018-7.html.csv | aggregation | players from the united states totaled -40 to par in the 1980 open championship . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '-40', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'to par'], 'result': '-40', 'ind': 0, 'tostr': 'sum { all_rows ; to par }'}, '-40'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; to par } ; -40 } = true', 'tointer': 'the sum of the to par record of all rows is -40 .'} | round_eq { sum { all_rows ; to par } ; -40 } = true | the sum of the to par record of all rows is -40 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'to par_4': 4, '-40_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'to par_4': 'to par', '-40_5': '-40'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'to par_4': [0], '-40_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'tom watson', 'united states', '68 + 70 + 64 + 69 = 271', '- 13', '25000'], ['2', 'lee trevino', 'united states', '68 + 67 + 71 + 69 = 275', '- 9', '17500'], ['3', 'ben crenshaw', 'united states', '70 + 70 + 68 + 69 = 277', '- 7', '13500'], ['t4', 'carl mason', 'england', '72 + 69 + 70 + 69 = 280', '- 4', '9250'], ['t4', 'jack nicklaus', 'united states', '73 + 67 + 71 + 69 = 280', '- 4', '9250'], ['t6', 'andy bean', 'united states', '71 + 69 + 70 + 72 = 282', '- 2', '7250'], ['t6', 'ken brown', 'scotland', '70 + 68 + 68 + 76 = 282', '- 2', '7250'], ['t6', 'hubert green', 'united states', '77 + 69 + 64 + 72 = 282', '- 2', '7250'], ['t6', 'craig stadler', 'united states', '72 + 70 + 69 + 71 = 282', '- 2', '7250'], ['t10', 'gil morgan', 'united states', '70 + 70 + 71 + 72 = 283', '- 1', '5750'], ['t10', 'jack newton', 'australia', '69 + 71 + 73 + 70 = 283', '- 1', '5750']] |
1989 open championship | https://en.wikipedia.org/wiki/1989_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18135501-4.html.csv | count | in the 1989 open championship , when the player is from the united states , there were 2 players who had a score of 137 . | {'scope': 'subset', 'criterion': 'equal', 'value': '137', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'score', '137'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record is equal to 137 .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 137 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 137 } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record is equal to 137 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 137 } } ; 2 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record is equal to 137 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 137 } } ; 2 } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record is equal to 137 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'score_8': 8, '137_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'score_8': 'score', '137_9': '137', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'score_8': [1], '137_9': [1], '2_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'wayne grady', 'australia', '68 + 67 = 135', '- 9'], ['t2', 'payne stewart', 'united states', '72 + 65 = 137', '- 7'], ['t2', 'tom watson', 'united states', '69 + 68 = 137', '- 7'], ['t4', 'david feherty', 'northern ireland', '71 + 67 = 138', '- 6'], ['t4', 'eduardo romero', 'argentina', '68 + 70 = 138', '- 6'], ['t4', 'wayne stephens', 'england', '66 + 72 = 138', '- 6'], ['t7', 'mark calcavecchia', 'united states', '71 + 68 = 139', '- 5'], ['t7', 'derrick cooper', 'england', '69 + 70 = 139', '- 5'], ['t7', 'fred couples', 'united states', '68 + 71 = 139', '- 5'], ['t7', 'mark james', 'england', '69 + 70 = 139', '- 5'], ['t7', 'mark mccumber', 'united states', '71 + 68 = 139', '- 5'], ['t7', 'greg norman', 'australia', '69 + 70 = 139', '- 5'], ['t7', 'steve pate', 'united states', '69 = 70 = 139', '- 5'], ['t7', 'scott simpson', 'united states', '73 + 66 = 139', '- 5']] |
bedford blues | https://en.wikipedia.org/wiki/Bedford_Blues | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1620305-1.html.csv | majority | most supplies come from kooga , from 2006 to 2011 . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'kooga', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'supplier', 'kooga'], 'result': True, 'ind': 0, 'tointer': 'for the supplier records of all rows , most of them fuzzily match to kooga .', 'tostr': 'most_eq { all_rows ; supplier ; kooga } = true'} | most_eq { all_rows ; supplier ; kooga } = true | for the supplier records of all rows , most of them fuzzily match to kooga . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'supplier_3': 3, 'kooga_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'supplier_3': 'supplier', 'kooga_4': 'kooga'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'supplier_3': [0], 'kooga_4': [0]} | ['year', 'supplier', 'chest', 'sleeves', 'back'] | [['unknown', 'gilbert', 'unknown', 'unknown', 'unknown'], ['2006 - 2008', 'kooga', 'autoglass', 'wells bombardier', 'lifesure'], ['2008 - 2010', 'kooga', 'autoglass', 'wells bombardier', 'lifesure'], ['2010 - 2011', 'kooga', 'autoglass', 'wells bombardier', 'lifesure'], ['2011 - 2014', 'zoo sport ltd', 'autoglass', 'wells bombardier', 'lifesure']] |
list of west indies test wicket - keepers | https://en.wikipedia.org/wiki/List_of_West_Indies_Test_wicket-keepers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27771406-1.html.csv | comparative | player alfred binns had a higher number of total dismissals than ivor mendonca . | {'row_1': '4', 'row_2': '10', 'col': '8', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'alfred binns'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to alfred binns .', 'tostr': 'filter_eq { all_rows ; player ; alfred binns }'}, 'total dismissals'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; alfred binns } ; total dismissals }', 'tointer': 'select the rows whose player record fuzzily matches to alfred binns . take the total dismissals record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'ivor mendonca'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to ivor mendonca .', 'tostr': 'filter_eq { all_rows ; player ; ivor mendonca }'}, 'total dismissals'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; ivor mendonca } ; total dismissals }', 'tointer': 'select the rows whose player record fuzzily matches to ivor mendonca . take the total dismissals record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; alfred binns } ; total dismissals } ; hop { filter_eq { all_rows ; player ; ivor mendonca } ; total dismissals } } = true', 'tointer': 'select the rows whose player record fuzzily matches to alfred binns . take the total dismissals record of this row . select the rows whose player record fuzzily matches to ivor mendonca . take the total dismissals record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; alfred binns } ; total dismissals } ; hop { filter_eq { all_rows ; player ; ivor mendonca } ; total dismissals } } = true | select the rows whose player record fuzzily matches to alfred binns . take the total dismissals record of this row . select the rows whose player record fuzzily matches to ivor mendonca . take the total dismissals 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, 'player_7': 7, 'alfred binns_8': 8, 'total dismissals_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'ivor mendonca_12': 12, 'total dismissals_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', 'player_7': 'player', 'alfred binns_8': 'alfred binns', 'total dismissals_9': 'total dismissals', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'ivor mendonca_12': 'ivor mendonca', 'total dismissals_13': 'total dismissals'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'alfred binns_8': [0], 'total dismissals_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'ivor mendonca_12': [1], 'total dismissals_13': [3]} | ['no', 'player', 'club', 'test career', 'tests', 'catches', 'stumpings', 'total dismissals'] | [['2', 'errol hunte', 'trinidad and tobago', '1930', '3', '5', '0', '5'], ['3', 'ivan barrow', 'jamaica', '1930 - 1939', '11', '17', '5', '22'], ['4', 'cyril christiani', 'british guiana', '1935', '4', '6', '1', '7'], ['8', 'alfred binns', 'jamaica', '1953 - 1956', '5', '14', '3', '17'], ['9', 'ralph legall', 'trinidad and tobago', '1953', '4', '8', '1', '9'], ['10', 'clifford mcwatt', 'british guiana', '1954 - 1955', '6', '8', '1', '9'], ['11', 'clairmonte depeiaza', 'barbados', '1955 - 1956', '5', '7', '4', '11'], ['13', 'gerry alexander', 'jamaica', '1957 - 1961', '25', '85', '5', '90'], ['14', 'jackie hendriks', 'jamaica', '1962 - 1969', '20', '42', '5', '47'], ['15', 'ivor mendonca', 'guyana', '1962', '2', '8', '2', '10'], ['16', 'david allan', 'barbados', '1962 - 1966', '5', '15', '3', '18'], ['18', 'mike findlay', 'windward islands', '1969 - 1973', '10', '19', '2', '21']] |
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 | majority | the majority of the time the colts won . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [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 , 1963', 'chicago bears', 'l 3 - 10', '1 - 3', 'wrigley field', '48998'], ['5', 'october 13 , 1963', 'san francisco 49ers', 'w 20 - 3', '2 - 3', 'memorial stadium', '56962'], ['6', 'october 20 , 1963', 'detroit lions', 'w 25 - 21', '3 - 3', 'tiger stadium', '51901'], ['7', 'october 27 , 1963', 'green bay packers', 'l 20 - 34', '3 - 4', 'memorial stadium', '60065'], ['8', 'november 3 , 1963', 'chicago bears', 'l 7 - 17', '3 - 5', 'memorial stadium', '60065'], ['9', 'november 10 , 1963', 'detroit lions', 'w 24 - 21', '4 - 5', 'memorial stadium', '59758'], ['10', 'november 17 , 1963', 'minnesota vikings', 'w 37 - 34', '5 - 5', 'metropolitan stadium', '33136'], ['11', 'november 24 , 1963', 'los angeles rams', 'l 16 - 17', '5 - 6', 'los angeles memorial coliseum', '48555'], ['12', 'december 1 , 1963', 'washington redskins', 'w 36 - 20', '6 - 6', 'rfk stadium', '44006'], ['13', 'december 8 , 1963', 'minnesota vikings', 'w 41 - 10', '7 - 6', 'memorial stadium', '54122']] |
kansas jayhawk community college conference | https://en.wikipedia.org/wiki/Kansas_Jayhawk_Community_College_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12434380-1.html.csv | unique | allen community college is the only college with scarlet as a school color . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'scarlet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school colors', 'scarlet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school colors record fuzzily matches to scarlet .', 'tostr': 'filter_eq { all_rows ; school colors ; scarlet }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; school colors ; scarlet } }', 'tointer': 'select the rows whose school colors record fuzzily matches to scarlet . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school colors', 'scarlet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school colors record fuzzily matches to scarlet .', 'tostr': 'filter_eq { all_rows ; school colors ; scarlet }'}, 'institution'], 'result': 'allen community college', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school colors ; scarlet } ; institution }'}, 'allen community college'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; school colors ; scarlet } ; institution } ; allen community college }', 'tointer': 'the institution record of this unqiue row is allen community college .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; school colors ; scarlet } } ; eq { hop { filter_eq { all_rows ; school colors ; scarlet } ; institution } ; allen community college } } = true', 'tointer': 'select the rows whose school colors record fuzzily matches to scarlet . there is only one such row in the table . the institution record of this unqiue row is allen community college .'} | and { only { filter_eq { all_rows ; school colors ; scarlet } } ; eq { hop { filter_eq { all_rows ; school colors ; scarlet } ; institution } ; allen community college } } = true | select the rows whose school colors record fuzzily matches to scarlet . there is only one such row in the table . the institution record of this unqiue row is allen community college . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school colors_7': 7, 'scarlet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'institution_9': 9, 'allen community college_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school colors_7': 'school colors', 'scarlet_8': 'scarlet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'institution_9': 'institution', 'allen community college_10': 'allen community college'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school colors_7': [0], 'scarlet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'institution_9': [2], 'allen community college_10': [3]} | ['institution', 'main campus location', 'founded', 'mascot', 'school colors'] | [['allen community college', 'iola', '1923', 'red devils', 'scarlet & black'], ['coffeyville community college', 'coffeyville', '1923', 'red ravens', 'red & white'], ['cowley college', 'arkansas city', '1922', 'tigers', 'orange & black'], ['fort scott community college', 'fort scott', '1919', 'greyhounds', 'maroon & grey'], ['highland community college', 'highland', '1858', 'scotties', 'navy & gold'], ['independence community college', 'independence', '1925', 'pirates', 'navy blue & vegas gold'], ['johnson county community college', 'overland park', '1967', 'cavaliers', 'maroon & gold'], ['kansas city kansas community college', 'kansas city', '1923', 'blue devils', 'blue , red & white'], ['labette community college', 'parsons', '1923', 'cardinals', 'red & white'], ['neosho county community college', 'chanute', '1936', 'panthers', 'orange & black']] |
list of vancouver canucks draft picks | https://en.wikipedia.org/wiki/List_of_Vancouver_Canucks_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11636955-17.html.csv | ordinal | of the vancouver canucks draft picks , the player picked second to last was igor larionov . | {'row': '11', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'pick', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; pick ; 2 }'}, 'player'], 'result': 'igor larionov', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; pick ; 2 } ; player }'}, 'igor larionov'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; igor larionov } = true', 'tointer': 'select the row whose pick record of all rows is 2nd maximum . the player record of this row is igor larionov .'} | eq { hop { nth_argmax { all_rows ; pick ; 2 } ; player } ; igor larionov } = true | select the row whose pick record of all rows is 2nd maximum . the player record of this row is igor larionov . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'pick_5': 5, '2_6': 6, 'player_7': 7, 'igor larionov_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'pick_5': 'pick', '2_6': '2', 'player_7': 'player', 'igor larionov_8': 'igor larionov'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'pick_5': [0], '2_6': [0], 'player_7': [1], 'igor larionov_8': [2]} | ['rd', 'pick', 'player', 'team ( league )', 'reg gp', 'pl gp'] | [['1', '4', 'jim sandlak', 'london knights ( ohl )', '509', '33'], ['2', '25', 'troy gamble', 'medicine hat tigers ( whl )', '72', '4'], ['3', '46', 'shane doyle', 'belleville bulls ( ohl )', '0', '0'], ['4', '67', 'randy siska', 'medicine hat tigers ( whl )', '0', '0'], ['5', '88', 'robert kron', 'brno zkl ( czech )', '144', '11'], ['6', '109', 'martin hrstka', 'hc dukla trenčín ( slovak )', '0', '0'], ['7', '130', 'brian mcfarlane', 'seattle breakers ( whl )', '0', '0'], ['8', '151', 'hakan ahlund', 'malmö if ( swe )', '0', '0'], ['9', '172', 'curtis hunt', 'prince albert raiders ( whl )', '0', '0'], ['10', '193', 'carl valimont', 'university of lowell ( ncaa )', '0', '0'], ['11', '214', 'igor larionov', 'hc cska moscow ( rus )', '210', '19'], ['12', '235', 'darren taylor', 'calgary wranglers ( whl )', '0', '0']] |
1971 green bay packers season | https://en.wikipedia.org/wiki/1971_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14655917-1.html.csv | comparative | the attendance on october 3rd had 8306 more people than the game on september 26th . | {'row_1': '3', 'row_2': '2', 'col': '7', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '8306', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october 3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to october 3 .', 'tostr': 'filter_eq { all_rows ; date ; october 3 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; october 3 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to october 3 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'september 26'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to september 26 .', 'tostr': 'filter_eq { all_rows ; date ; september 26 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; september 26 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to september 26 . take the attendance record of this row .'}], 'result': '8306', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; date ; october 3 } ; attendance } ; hop { filter_eq { all_rows ; date ; september 26 } ; attendance } }'}, '8306'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; date ; october 3 } ; attendance } ; hop { filter_eq { all_rows ; date ; september 26 } ; attendance } } ; 8306 } = true', 'tointer': 'select the rows whose date record fuzzily matches to october 3 . take the attendance record of this row . select the rows whose date record fuzzily matches to september 26 . take the attendance record of this row . the first record is 8306 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; date ; october 3 } ; attendance } ; hop { filter_eq { all_rows ; date ; september 26 } ; attendance } } ; 8306 } = true | select the rows whose date record fuzzily matches to october 3 . take the attendance record of this row . select the rows whose date record fuzzily matches to september 26 . take the attendance record of this row . the first record is 8306 larger than the second 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, 'date_8': 8, 'october 3_9': 9, 'attendance_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'date_12': 12, 'september 26_13': 13, 'attendance_14': 14, '8306_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', 'date_8': 'date', 'october 3_9': 'october 3', 'attendance_10': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'date_12': 'date', 'september 26_13': 'september 26', 'attendance_14': 'attendance', '8306_15': '8306'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'date_8': [0], 'october 3_9': [0], 'attendance_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'date_12': [1], 'september 26_13': [1], 'attendance_14': [3], '8306_15': [5]} | ['week', 'date', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'september 19', 'new york giants', 'l 40 - 42', '0 - 1', 'lambeau field', '56263'], ['2', 'september 26', 'denver broncos', 'w 34 - 13', '1 - 1', 'milwaukee county stadium', '47957'], ['3', 'october 3', 'cincinnati bengals', 'w 20 - 17', '2 - 1', 'lambeau field', '56263'], ['4', 'october 10', 'detroit lions', 'l 28 - 31', '2 - 2', 'tiger stadium', '54418'], ['5', 'october 17', 'minnesota vikings', 'l 13 - 24', '2 - 3', 'lambeau field', '56263'], ['6', 'october 24', 'los angeles rams', 'l 13 - 30', '2 - 4', 'los angeles memorial coliseum', '75531'], ['7', 'november 1', 'detroit lions', 't 14 - 14', '2 - 4 - 1', 'milwaukee county stadium', '47961'], ['8', 'november 7', 'chicago bears', 'w 17 - 14', '3 - 4 - 1', 'soldier field', '55049'], ['9', 'november 14', 'minnesota vikings', 'l 0 - 3', '3 - 5 - 1', 'metropolitan stadium', '49784'], ['10', 'november 22', 'atlanta falcons', 'l 21 - 28', '3 - 6 - 1', 'atlanta stadium', '58850'], ['11', 'november 28', 'new orleans saints', 'l 21 - 29', '3 - 7 - 1', 'milwaukee county stadium', '48035'], ['12', 'december 5', 'st louis cardinals', 't 16 - 16', '3 - 7 - 2', 'busch stadium', '50443'], ['13', 'december 12', 'chicago bears', 'w 31 - 10', '4 - 7 - 2', 'lambeau field', '56263']] |
2005 african judo championships | https://en.wikipedia.org/wiki/2005_African_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10642140-3.html.csv | superlative | algeria had the most number of gold medals in the 2005 african judo championships . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'gold'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gold }'}, 'nation'], 'result': 'algeria', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gold } ; nation }'}, 'algeria'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; gold } ; nation } ; algeria } = true', 'tointer': 'select the row whose gold record of all rows is maximum . the nation record of this row is algeria .'} | eq { hop { argmax { all_rows ; gold } ; nation } ; algeria } = true | select the row whose gold record of all rows is maximum . the nation record of this row is algeria . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'nation_6': 6, 'algeria_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'nation_6': 'nation', 'algeria_7': 'algeria'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'nation_6': [1], 'algeria_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'algeria', '9', '2', '5', '16'], ['2', 'tunisia', '4', '6', '6', '16'], ['3', 'egypt', '3', '3', '1', '7'], ['4', 'senegal', '1', '2', '4', '7'], ['5', 'angola', '1', '0', '0', '1'], ['6', 'south africa', '0', '3', '1', '4'], ['7', 'nigeria', '0', '1', '2', '3'], ['8', 'niger', '0', '1', '0', '1'], ['9', 'morocco', '0', '0', '7', '7'], ['10 =', 'burkina faso', '0', '0', '1', '1'], ['10 =', 'ivory coast', '0', '0', '1', '1'], ['10 =', 'gabon', '0', '0', '1', '1'], ['10 =', 'madagascar', '0', '0', '1', '1']] |
list of world number one male golfers | https://en.wikipedia.org/wiki/List_of_World_Number_One_male_golfers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10753786-4.html.csv | unique | of the men who have been ranked as the world 's number one male golfer , tiger woods is the only one who has been ranked as such for more than 600 weeks . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'greater_than', 'value': '600', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'weeks', '600'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weeks record is greater than 600 .', 'tostr': 'filter_greater { all_rows ; weeks ; 600 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; weeks ; 600 } }', 'tointer': 'select the rows whose weeks record is greater than 600 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'weeks', '600'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose weeks record is greater than 600 .', 'tostr': 'filter_greater { all_rows ; weeks ; 600 }'}, 'player'], 'result': 'tiger woods', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; weeks ; 600 } ; player }'}, 'tiger woods'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; weeks ; 600 } ; player } ; tiger woods }', 'tointer': 'the player record of this unqiue row is tiger woods .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; weeks ; 600 } } ; eq { hop { filter_greater { all_rows ; weeks ; 600 } ; player } ; tiger woods } } = true', 'tointer': 'select the rows whose weeks record is greater than 600 . there is only one such row in the table . the player record of this unqiue row is tiger woods .'} | and { only { filter_greater { all_rows ; weeks ; 600 } } ; eq { hop { filter_greater { all_rows ; weeks ; 600 } ; player } ; tiger woods } } = true | select the rows whose weeks record is greater than 600 . there is only one such row in the table . the player record of this unqiue row is tiger woods . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'weeks_7': 7, '600_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'tiger woods_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'weeks_7': 'weeks', '600_8': '600', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'tiger woods_10': 'tiger woods'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'weeks_7': [0], '600_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'tiger woods_10': [3]} | ['rank', 'player', 'country', 'weeks', 'order', 'majors'] | [['1', 'tiger woods', 'united states', '656', '9', '14'], ['2', 'greg norman', 'australia', '331', '3', '2'], ['3', 'nick faldo', 'england', '97', '4', '6'], ['4', 'seve ballesteros', 'spain', '61', '2', '5'], ['5', 'luke donald', 'england', '56', '15', '0'], ['6', 'ian woosnam', 'wales', '50', '5', '1'], ['7', 'nick price', 'zimbabwe', '44', '7', '3'], ['8', 'rory mcilroy', 'northern ireland', '39', '16', '2'], ['9', 'vijay singh', 'fiji', '32', '12', '3'], ['10', 'lee westwood', 'england', '22', '13', '0'], ['11', 'fred couples', 'united states', '16', '6', '1'], ['12', 'david duval', 'united states', '15', '11', '1'], ['13', 'ernie els', 'south africa', '9', '10', '4'], ['14', 'martin kaymer', 'germany', '8', '14', '1'], ['15', 'bernhard langer', 'west germany', '3', '1', '2'], ['16', 'tom lehman', 'united states', '1', '8', '1']] |
2005 connecticut sun season | https://en.wikipedia.org/wiki/2005_Connecticut_Sun_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18904831-5.html.csv | superlative | the june 20 game of the 2005 connecticut sun season had the largest number of high points . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'high points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; high points }'}, 'date'], 'result': 'june 20', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; high points } ; date }'}, 'june 20'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; high points } ; date } ; june 20 } = true', 'tointer': 'select the row whose high points record of all rows is maximum . the date record of this row is june 20 .'} | eq { hop { argmax { all_rows ; high points } ; date } ; june 20 } = true | select the row whose high points record of all rows is maximum . the date record of this row is june 20 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'high points_5': 5, 'date_6': 6, 'june 20_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'high points_5': 'high points', 'date_6': 'date', 'june 20_7': 'june 20'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'date_6': [1], 'june 20_7': [2]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location', 'record'] | [['4', 'june 4', 'san antonio', 'w 80 - 69', 'douglas , dydek , mcwilliams - franklin ( 15 )', 'jones ( 7 )', 'douglas , whalen ( 6 )', 'mohegan sun arena 6252', '3 - 1'], ['5', 'june 7', 'seattle', 'w 81 - 69', 'douglas ( 20 )', 'dydek ( 14 )', 'whalen ( 8 )', 'mohegan sun arena 7080', '4 - 1'], ['6', 'june 10', 'houston', 'w 77 - 57', 'sales ( 21 )', 'dydek ( 12 )', 'whalen ( 6 )', 'toyota center 5736', '5 - 1'], ['7', 'june 11', 'san antonio', 'w 78 - 69', 'mcwilliams - franklin ( 17 )', 'douglas , mcwilliams - franklin ( 9 )', 'whalen ( 6 )', 'at & t center 9772', '6 - 1'], ['8', 'june 18', 'detroit', 'w 73 - 63', 'sales ( 17 )', 'mcwilliams - franklin ( 10 )', 'whalen ( 6 )', 'mohegan sun arena 7427', '7 - 1'], ['9', 'june 20', 'los angeles', 'w 90 - 70', 'sales ( 26 )', 'dydek ( 10 )', 'douglas , whalen ( 6 )', 'staples center 7246', '8 - 1'], ['10', 'june 22', 'seattle', 'l 86 - 95', 'mcwilliams - franklin ( 21 )', 'dydek , mcwilliams - franklin , whalen ( 5 )', 'whalen ( 6 )', 'keyarena 8120', '8 - 2'], ['11', 'june 24', 'sacramento', 'w 61 - 50', 'mcwilliams - franklin ( 15 )', 'mcwilliams - franklin ( 14 )', 'whalen ( 3 )', 'arco arena 10067', '9 - 2'], ['12', 'june 25', 'phoenix', 'w 77 - 69', 'sales ( 22 )', 'wyckoff ( 9 )', 'sales , wyckoff ( 3 )', 'us airways center 8091', '10 - 2'], ['13', 'june 28', 'sacramento', 'w 70 - 66', 'sales ( 19 )', 'mcwilliams - franklin ( 7 )', 'whalen ( 5 )', 'mohegan sun arena 6789', '11 - 2'], ['14', 'june 30', 'minnesota', 'w 71 - 56', 'sales ( 18 )', 'mcwilliams - franklin ( 9 )', 'whalen ( 6 )', 'mohegan sun arena 6869', '12 - 2']] |
1971 - 72 st. louis blues season | https://en.wikipedia.org/wiki/1971%E2%80%9372_St._Louis_Blues_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22402438-7.html.csv | comparative | gene carr was picked by the blues before bernie doan was . | {'row_1': '1', 'row_2': '5', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'gene carr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to gene carr .', 'tostr': 'filter_eq { all_rows ; player ; gene carr }'}, 'pick'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; gene carr } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to gene carr . take the pick record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'bernie doan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to bernie doan .', 'tostr': 'filter_eq { all_rows ; player ; bernie doan }'}, 'pick'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; bernie doan } ; pick }', 'tointer': 'select the rows whose player record fuzzily matches to bernie doan . take the pick record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; player ; gene carr } ; pick } ; hop { filter_eq { all_rows ; player ; bernie doan } ; pick } } = true', 'tointer': 'select the rows whose player record fuzzily matches to gene carr . take the pick record of this row . select the rows whose player record fuzzily matches to bernie doan . take the pick record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; player ; gene carr } ; pick } ; hop { filter_eq { all_rows ; player ; bernie doan } ; pick } } = true | select the rows whose player record fuzzily matches to gene carr . take the pick record of this row . select the rows whose player record fuzzily matches to bernie doan . take the pick 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, 'gene carr_8': 8, 'pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'bernie doan_12': 12, 'pick_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', 'gene carr_8': 'gene carr', 'pick_9': 'pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'bernie doan_12': 'bernie doan', 'pick_13': 'pick'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'gene carr_8': [0], 'pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'bernie doan_12': [1], 'pick_13': [3]} | ['pick', 'player', 'position', 'nationality', 'nhl team', 'college / junior / club team'] | [['4', 'gene carr', 'centre', 'canada', 'st louis blues', 'flin flon bombers ( wchl )'], ['38', 'john garrett', 'goaltender', 'canada', 'st louis blues', 'peterborough petes ( oha )'], ['52', 'derek harker', 'defence', 'canada', 'st louis blues', 'edmonton oil kings ( wchl )'], ['66', 'wayne gibbs', 'defence', 'canada', 'st louis blues', 'calgary centennials ( wchl )'], ['80', 'bernie doan', 'defence', 'canada', 'st louis blues', 'calgary centennials ( wchl )'], ['94', 'dave smith', 'defence', 'canada', 'st louis blues', 'regina pats ( wchl )']] |
united states house of representatives elections , 1828 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1828 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668243-25.html.csv | unique | john floyd is the only incumbent whose result was ' retired jacksonian hold ' . | {'scope': 'all', 'row': '16', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'retired jacksonian hold', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired jacksonian hold'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired jacksonian hold .', 'tostr': 'filter_eq { all_rows ; result ; retired jacksonian hold }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; result ; retired jacksonian hold } }', 'tointer': 'select the rows whose result record fuzzily matches to retired jacksonian hold . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired jacksonian hold'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired jacksonian hold .', 'tostr': 'filter_eq { all_rows ; result ; retired jacksonian hold }'}, 'incumbent'], 'result': 'john floyd', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; result ; retired jacksonian hold } ; incumbent }'}, 'john floyd'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; result ; retired jacksonian hold } ; incumbent } ; john floyd }', 'tointer': 'the incumbent record of this unqiue row is john floyd .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; result ; retired jacksonian hold } } ; eq { hop { filter_eq { all_rows ; result ; retired jacksonian hold } ; incumbent } ; john floyd } } = true', 'tointer': 'select the rows whose result record fuzzily matches to retired jacksonian hold . there is only one such row in the table . the incumbent record of this unqiue row is john floyd .'} | and { only { filter_eq { all_rows ; result ; retired jacksonian hold } } ; eq { hop { filter_eq { all_rows ; result ; retired jacksonian hold } ; incumbent } ; john floyd } } = true | select the rows whose result record fuzzily matches to retired jacksonian hold . there is only one such row in the table . the incumbent record of this unqiue row is john floyd . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'retired jacksonian hold_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'john floyd_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'retired jacksonian hold_8': 'retired jacksonian hold', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'john floyd_10': 'john floyd'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'retired jacksonian hold_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'john floyd_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['virginia 2', 'james trezvant', 'jacksonian', '1825', 're - elected', 'james trezvant ( j ) 100 %'], ['virginia 3', 'william s archer', 'jacksonian', '1820 ( special )', 're - elected', 'william s archer ( j ) 100 %'], ['virginia 4', 'mark alexander', 'jacksonian', '1819', 're - elected', 'mark alexander ( j ) 100 %'], ['virginia 6', 'thomas davenport', 'jacksonian', '1825', 're - elected', 'thomas davenport ( j ) 100 %'], ['virginia 7', 'nathaniel h claiborne', 'jacksonian', '1825', 're - elected', 'nathaniel h claiborne ( j ) 100 %'], ['virginia 9', 'andrew stevenson', 'jacksonian', '1821', 're - elected', 'andrew stevenson ( j ) 100 %'], ['virginia 10', 'william c rives', 'jacksonian', '1823', 're - elected', 'william c rives ( j ) 100 %'], ['virginia 11', 'philip p barbour', 'jacksonian', '1815 1827', 're - elected', 'philip p barbour ( j ) 100 %'], ['virginia 12', 'john roane', 'jacksonian', '1809 1827', 're - elected', 'john roane ( j ) 100 %'], ['virginia 13', 'john taliaferro', 'anti - jacksonian', '1824 ( special )', 're - elected', 'john taliaferro ( aj ) 61.8 % willoughby newton 38.2 %'], ['virginia 14', 'charles f mercer', 'anti - jacksonian', '1817', 're - elected', 'charles f mercer ( aj ) 82.0 % john gibson 18.0 %'], ['virginia 15', 'john s barbour', 'jacksonian', '1823', 're - elected', 'john s barbour ( j ) 100 %'], ['virginia 16', 'william armstrong', 'anti - jacksonian', '1825', 're - elected', 'william armstrong ( aj ) 100 %'], ['virginia 17', 'robert allen', 'jacksonian', '1827', 're - elected', 'robert allen ( j ) 61.5 % samuel kerceval 38.5 %'], ['virginia 19', 'william mccoy', 'jacksonian', '1811', 're - elected', 'william mccoy ( j ) 100 %'], ['virginia 20', 'john floyd', 'jacksonian', '1817', 'retired jacksonian hold', 'robert craig ( j ) 55.0 % fleming b miller 45.0 %']] |
schoolhouse rock ! | https://en.wikipedia.org/wiki/Schoolhouse_Rock%21 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-191105-4.html.csv | unique | only the great american melting pot has an uncertain first air date . | {'scope': 'all', 'row': '3', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'or', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first aired', 'or'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first aired record fuzzily matches to or .', 'tostr': 'filter_eq { all_rows ; first aired ; or }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; first aired ; or } }', 'tointer': 'select the rows whose first aired record fuzzily matches to or . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first aired', 'or'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first aired record fuzzily matches to or .', 'tostr': 'filter_eq { all_rows ; first aired ; or }'}, 'episode title'], 'result': 'the great american melting pot', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; first aired ; or } ; episode title }'}, 'the great american melting pot'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; first aired ; or } ; episode title } ; the great american melting pot }', 'tointer': 'the episode title record of this unqiue row is the great american melting pot .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; first aired ; or } } ; eq { hop { filter_eq { all_rows ; first aired ; or } ; episode title } ; the great american melting pot } } = true', 'tointer': 'select the rows whose first aired record fuzzily matches to or . there is only one such row in the table . the episode title record of this unqiue row is the great american melting pot .'} | and { only { filter_eq { all_rows ; first aired ; or } } ; eq { hop { filter_eq { all_rows ; first aired ; or } ; episode title } ; the great american melting pot } } = true | select the rows whose first aired record fuzzily matches to or . there is only one such row in the table . the episode title record of this unqiue row is the great american melting pot . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'first aired_7': 7, 'or_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'episode title_9': 9, 'the great american melting pot_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'first aired_7': 'first aired', 'or_8': 'or', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'episode title_9': 'episode title', 'the great american melting pot_10': 'the great american melting pot'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'first aired_7': [0], 'or_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'episode title_9': [2], 'the great american melting pot_10': [3]} | ['episode title', 'subject', 'music by', 'lyrics by', 'performed by', 'first aired'] | [['elbow room', 'us territorial expansion', 'lynn ahrens', 'lynn ahrens', 'sue manchester', '1975'], ['fireworks', 'declaration of independence', 'lynn ahrens', 'lynn ahrens', 'grady tate', '1976'], ['the great american melting pot', 'immigration / diversity', 'lynn ahrens', 'lynn ahrens', 'lori lieberman', '1977 , or may 1 , 1976'], ["i 'm just a bill", 'legislative process', 'dave frishberg', 'dave frishberg', 'jack sheldon', '1975'], ['no more kings', 'american independence', 'lynn ahrens', 'lynn ahrens', 'lynn ahrens & bob dorough', '1975'], ['preamble', 'united states constitution', 'lynn ahrens', 'lynn ahrens', 'lynn ahrens', '1975'], ["the shot heard ' round the world", 'american revolutionary war', 'bob dorough', 'bob dorough', 'bob dorough', '1976'], ["sufferin ' 'til suffrage", "women 's suffrage", 'bob dorough', 'tom yohe', 'essra mohawk', '1976'], ['three ring government', 'separation of powers', 'lynn ahrens', 'lynn ahrens', 'lynn ahrens', '1979'], ["i 'm gon na send your vote to college", 'electoral college', 'george r newall and bob dorough', 'george r newall and bob dorough', 'jack sheldon and bob dorough', '2002']] |
1970 baltimore colts season | https://en.wikipedia.org/wiki/1970_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14966537-1.html.csv | ordinal | in the 1970 season , the baltimore colts ' week 5 game had their 2nd highest attendance . | {'row': '5', 'col': '7', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'week'], 'result': '5', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; week }'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; week } ; 5 } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the week record of this row is 5 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; week } ; 5 } = true | select the row whose attendance record of all rows is 2nd maximum . the week record of this row is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'week_7': 7, '5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'week_7': 'week', '5_8': '5'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'week_7': [1], '5_8': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 20 , 1970', 'san diego chargers', 'w 16 - 14', '1 - 0', 'san diego stadium', '47782'], ['2', 'september 28 , 1970', 'kansas city chiefs', 'l 24 - 44', '1 - 1', 'memorial stadium', '53911'], ['3', 'october 4 , 1970', 'boston patriots', 'w 14 - 6', '2 - 1', 'harvard stadium', '38235'], ['4', 'october 11 , 1970', 'houston oilers', 'w 24 - 20', '3 - 1', 'astrodome', '48050'], ['5', 'october 18 , 1970', 'new york jets', 'w 29 - 22', '4 - 1', 'shea stadium', '63301'], ['6', 'october 25 , 1970', 'boston patriots', 'w 27 - 3', '5 - 1', 'memorial stadium', '60240'], ['7', 'november 1 , 1970', 'miami dolphins', 'w 35 - 0', '6 - 1', 'memorial stadium', '60240'], ['8', 'november 9 , 1970', 'green bay packers', 'w 13 - 10', '7 - 1', 'milwaukee county stadium', '48063'], ['9', 'november 15 , 1970', 'buffalo bills', 't 17 - 17', '7 - 1 - 1', 'memorial stadium', '60240'], ['10', 'november 22 , 1970', 'miami dolphins', 'l 17 - 34', '7 - 2 - 1', 'miami orange bowl', '67699'], ['11', 'november 29 , 1970', 'chicago bears', 'w 21 - 20', '8 - 2 - 1', 'memorial stadium', '60240'], ['12', 'december 6 , 1970', 'philadelphia eagles', 'w 29 - 10', '9 - 2 - 1', 'memorial stadium', '60240'], ['13', 'december 13 , 1970', 'buffalo bills', 'w 20 - 14', '10 - 2 - 1', 'war memorial stadium', '34346']] |
v - league 5th season 1st conference | https://en.wikipedia.org/wiki/V-League_5th_Season_1st_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16348031-4.html.csv | comparative | the ateneo de manila university won more sets than the college of saint benilde did . | {'row_1': '4', 'row_2': '6', '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', 'team', 'ateneo de manila university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to ateneo de manila university .', 'tostr': 'filter_eq { all_rows ; team ; ateneo de manila university }'}, 'sets won'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; ateneo de manila university } ; sets won }', 'tointer': 'select the rows whose team record fuzzily matches to ateneo de manila university . take the sets won record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'college of saint benilde'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to college of saint benilde .', 'tostr': 'filter_eq { all_rows ; team ; college of saint benilde }'}, 'sets won'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; college of saint benilde } ; sets won }', 'tointer': 'select the rows whose team record fuzzily matches to college of saint benilde . take the sets won record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; ateneo de manila university } ; sets won } ; hop { filter_eq { all_rows ; team ; college of saint benilde } ; sets won } } = true', 'tointer': 'select the rows whose team record fuzzily matches to ateneo de manila university . take the sets won record of this row . select the rows whose team record fuzzily matches to college of saint benilde . take the sets won record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; team ; ateneo de manila university } ; sets won } ; hop { filter_eq { all_rows ; team ; college of saint benilde } ; sets won } } = true | select the rows whose team record fuzzily matches to ateneo de manila university . take the sets won record of this row . select the rows whose team record fuzzily matches to college of saint benilde . take the sets won record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'ateneo de manila university_8': 8, 'sets won_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'college of saint benilde_12': 12, 'sets won_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'ateneo de manila university_8': 'ateneo de manila university', 'sets won_9': 'sets won', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'college of saint benilde_12': 'college of saint benilde', 'sets won_13': 'sets won'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'ateneo de manila university_8': [0], 'sets won_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'college of saint benilde_12': [1], 'sets won_13': [3]} | ['rank', 'team', 'loss', 'sets won', 'sets lost', 'percentage'] | [['1', 'san sebastian college - recoletos', '1', '27', '3', '90 %'], ['2', 'adamson university', '1', '27', '6', '81 %'], ['3', 'lyceum of the philippines university', '3', '16', '22', '42 %'], ['4', 'ateneo de manila university', '4', '16', '23', '41 %'], ['5', 'far eastern university', '6', '15', '25', '38 %'], ['6', 'college of saint benilde', '10', '4', '30', '12 %']] |
2007 - 08 new orleans hornets season | https://en.wikipedia.org/wiki/2007%E2%80%9308_New_Orleans_Hornets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11963536-4.html.csv | ordinal | the third game that the new orleans hornets lost had an attendance of 11741 . | {'scope': 'subset', 'row': '11', 'col': '1', 'order': '3', 'col_other': '6', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'l'}} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'l'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; l }', 'tointer': 'select the rows whose score record fuzzily matches to l .'}, 'date', '3'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; score ; l } ; date ; 3 }'}, 'attendance'], 'result': '11741', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; score ; l } ; date ; 3 } ; attendance }'}, '11741'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; score ; l } ; date ; 3 } ; attendance } ; 11741 } = true', 'tointer': 'select the rows whose score record fuzzily matches to l . select the row whose date record of these rows is 3rd minimum . the attendance record of this row is 11741 .'} | eq { hop { nth_argmin { filter_eq { all_rows ; score ; l } ; date ; 3 } ; attendance } ; 11741 } = true | select the rows whose score record fuzzily matches to l . select the row whose date record of these rows is 3rd minimum . the attendance record of this row is 11741 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'num_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'score_6': 6, 'l_7': 7, 'date_8': 8, '3_9': 9, 'attendance_10': 10, '11741_11': 11} | {'eq_3': 'eq', 'result_4': 'true', 'num_hop_2': 'num_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'score_6': 'score', 'l_7': 'l', 'date_8': 'date', '3_9': '3', 'attendance_10': 'attendance', '11741_11': '11741'} | {'eq_3': [4], 'result_4': [], 'num_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'score_6': [0], 'l_7': [0], 'date_8': [1], '3_9': [1], 'attendance_10': [2], '11741_11': [3]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['2 november 2007', 'trail blazers', 'w 113 - 93 ( ot )', 'hornets', 'chris paul ( 19 )', '9817', '2 - 0'], ['4 november 2007', 'hornets', 'w 93 - 88 ( ot )', 'nuggets', 'david west ( 17 )', '13156', '3 - 0'], ['6 november 2007', 'hornets', 'w 118 - 104 ( ot )', 'lakers', 'peja stojakovic ( 36 )', '18997', '4 - 0'], ['7 november 2007', 'hornets', 'l 90 - 93 ( ot )', 'trail blazers', 'david west ( 34 )', '19980', '4 - 1'], ['9 november 2007', 'spurs', 'l 85 - 97 ( ot )', 'hornets', 'chris paul ( 18 )', '15297', '4 - 2'], ['11 november 2007', 'hornets', 'w 93 - 72 ( ot )', '76ers', 'two - way tie ( 16 )', '10014', '5 - 2'], ['12 november 2007', 'hornets', 'w 84 - 82 ( ot )', 'nets', 'chris paul ( 27 )', '12832', '6 - 2'], ['14 november 2007', '76ers', 'w 95 - 76 ( ot )', 'hornets', 'morris peterson ( 27 )', '8302', '7 - 2'], ['16 november 2007', 'hornets', 'w 120 - 118 ( ot )', 'grizzlies', 'david west ( 40 )', '13271', '8 - 2'], ['17 november 2007', 'hornets', 'w 100 - 82 ( ot )', 'timberwolves', 'peja stojakovic ( 22 )', '15324', '9 - 2'], ['19 november 2007', 'magic', 'l 88 - 95 ( ot )', 'hornets', 'peja stojakovic ( 21 )', '11741', '9 - 3'], ['21 november 2007', 'pacers', 'l 93 - 105 ( ot )', 'hornets', 'david west ( 23 )', '11609', '9 - 4'], ['23 november 2007', 'hornets', 'l 71 - 99 ( ot )', 'jazz', 'david west ( 18 )', '19911', '9 - 5'], ['24 november 2007', 'hornets', 'w 98 - 89 ( ot )', 'clippers', 'peja stojakovic ( 22 )', '15601', '10 - 5'], ['26 november 2007', 'timberwolves', 'l 94 - 103 ( ot )', 'hornets', 'chris paul ( 31 )', '8393', '10 - 6'], ['30 november 2007', 'hornets', 'w 92 - 86 ( ot )', 'hawks', 'david west ( 22 )', '14186', '11 - 6']] |
usa south athletic conference | https://en.wikipedia.org/wiki/USA_South_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-255188-3.html.csv | superlative | the college of charleston was founded earlier than any of the other schools in the usa south athletic conference . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', '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', 'founded'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; founded }'}, 'institution'], 'result': 'college of charleston', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; founded } ; institution }'}, 'college of charleston'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; founded } ; institution } ; college of charleston } = true', 'tointer': 'select the row whose founded record of all rows is minimum . the institution record of this row is college of charleston .'} | eq { hop { argmin { all_rows ; founded } ; institution } ; college of charleston } = true | select the row whose founded record of all rows is minimum . the institution record of this row is college of charleston . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'founded_5': 5, 'institution_6': 6, 'college of charleston_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'founded_5': 'founded', 'institution_6': 'institution', 'college of charleston_7': 'college of charleston'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'founded_5': [0], 'institution_6': [1], 'college of charleston_7': [2]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined', 'left', 'current conference'] | [['chowan university', 'murfreesboro , north carolina', 'hawks', '1848', 'private', '1260', '2000', '2004', 'ciaa ( ncaa division ii )'], ['christopher newport university', 'newport news , virginia', 'captains', '1960', 'public', '4793', '1972', '2013', 'capital'], ['college of charleston', 'charleston , south carolina', 'cougars', '1770', 'private', '11320', '1963', '1970', 'caa ( ncaa division i )'], ['lynchburg college', 'lynchburg , virginia', 'fighting hornets', '1903', 'private', '2500', '1963', '1976', 'odac'], ['shenandoah university', 'winchester , virginia', 'hornets', '1875', 'private', '1767', '1992', '2012', 'odac'], ['st andrews presbyterian university', 'laurinburg , north carolina', 'knights', '1958', 'private', '600', '1963', '1988', 'aac ( naia )'], ['university of north carolina at charlotte', 'charlotte , north carolina', '49ers', '1961', 'public', '25227', '1963', '1970', 'c - usa ( ncaa division i )'], ['university of north carolina at greensboro', 'greensboro , north carolina', 'spartans', '1891', 'public', '18502', '1968', '1988', 'socon ( ncaa division i )']] |
sandro cortese | https://en.wikipedia.org/wiki/Sandro_Cortese | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16710541-2.html.csv | majority | in the majority of seasons , sandro cortese did n't have any wins . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'wins', '0'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; wins ; 0 } = true'} | most_eq { all_rows ; wins ; 0 } = true | for the wins records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '0_4': [0]} | ['season', 'class', 'team', 'motorcycle', 'type', 'races', 'wins', 'podiums', 'poles', 'fastest laps', 'pts', 'position'] | [['2005', '125cc', 'kiefer - bos - castrol honda', 'honda', 'honda rs125r', '16', '0', '0', '0', '0', '8', '26th'], ['2006', '125cc', 'elit - caffè latte', 'honda', 'honda rs125r', '16', '0', '0', '0', '0', '23', '17th'], ['2007', '125cc', 'emmi - caffè latte', 'aprilia', 'aprilia rs 125', '17', '0', '0', '0', '0', '66', '14th'], ['2008', '125cc', 'emmi - caffè latte', 'aprilia', 'aprilia rsa 125', '17', '0', '0', '0', '1', '141', '8th'], ['2009', '125cc', 'ajo interwetten', 'derbi', 'derbi rsa 125', '16', '0', '3', '1', '2', '130', '6th'], ['2010', '125cc', 'ajo motorsport', 'derbi', 'derbi rs 125 r', '17', '0', '2', '1', '2', '143', '7th'], ['2011', '125cc', 'intact - racing team germany', 'aprilia', 'aprilia rsa 125', '17', '2', '6', '1', '2', '225', '4th'], ['2012', 'moto3', 'red bull ktm ajo', 'ktm', 'ktm m32', '17', '5', '15', '7', '4', '325', '1st'], ['2013', 'moto2', 'dynavolt intact gp', 'kalex', 'kalex moto2', '16', '0', '0', '0', '0', '19', '20th']] |
uk film council completion fund | https://en.wikipedia.org/wiki/UK_Film_Council_Completion_Fund | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12181447-7.html.csv | ordinal | the 2nd highest award for the uk film council completion fund was for the film mercy . | {'row': '1', 'col': '6', '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', 'award', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; award ; 2 }'}, 'film'], 'result': 'mercy', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; award ; 2 } ; film }'}, 'mercy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; award ; 2 } ; film } ; mercy } = true', 'tointer': 'select the row whose award record of all rows is 2nd maximum . the film record of this row is mercy .'} | eq { hop { nth_argmax { all_rows ; award ; 2 } ; film } ; mercy } = true | select the row whose award record of all rows is 2nd maximum . the film record of this row is mercy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'award_5': 5, '2_6': 6, 'film_7': 7, 'mercy_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', 'award_5': 'award', '2_6': '2', 'film_7': 'film', 'mercy_8': 'mercy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'award_5': [0], '2_6': [0], 'film_7': [1], 'mercy_8': [2]} | ['film', 'director ( s )', 'writer ( s )', 'recipient', 'date', 'award'] | [['mercy', 'candida scott knight', 'tina walker', 'maya vision international ltd', '3 / 3 / 04', '7800'], ['no deposit , no return', 'dallas campbell', 'dallas campbell , john edwards', 'rocliffe ltd', '3 / 3 / 04', '4360'], ['6.6.04', 'simon hook', 'simon hook , jayne kirkham', 'andrew wilson', '3 / 3 / 04', '1939'], ['bushido : the way of the warrior', 'susan jacobson', 'susan jacobson , anna reeves', 'pistachio pictures ltd', '3 / 3 / 04', '3386'], ['jamaica', 'martin scanlan', 'martin scanlan', 'prussia lane productions ltd', '3 / 3 / 04', '6947'], ['flowers and coins', 'joshua neale', 'neil henry , joshua neale', 'joshua neale', '3 / 3 / 04', '3740'], ['moving on', 'albert kodagolian', 'dusan tolmac', 'albert kodagolian', '3 / 3 / 04', '6504'], ['stalin , my neighbour', 'carol morley', 'carol morley', 'cannon and morley productions ltd', '3 / 3 / 04', '5750'], ['hotel infinity', 'amanda boyle', 'amanda boyle', 'picture farm ltd', '3 / 3 / 04', '9549'], ['traffic warden', 'donald rice', 'donald rice', 'clockwork pictures ltd', '3 / 3 / 04', '6947']] |
family guy ( season 7 ) | https://en.wikipedia.org/wiki/Family_Guy_%28season_7%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22261877-1.html.csv | superlative | baby not on board recieved the most viewers of family guy season . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '4', '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', 'us viewers ( million )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( million ) }'}, 'title'], 'result': 'baby not on board', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( million ) } ; title }'}, 'baby not on board'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; baby not on board } = true', 'tointer': 'select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is baby not on board .'} | eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; baby not on board } = true | select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is baby not on board . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (million)_5': 5, 'title_6': 6, 'baby not on board_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (million)_5': 'us viewers ( million )', 'title_6': 'title', 'baby not on board_7': 'baby not on board'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (million)_5': [0], 'title_6': [1], 'baby not on board_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['111', '1', 'love , blactually', 'cyndi tang', 'mike henry', 'september 28 , 2008', '6acx03', '9.20'], ['112', '2', 'i dream of jesus', 'mike kim', 'brian scully', 'october 5 , 2008', '6acx05', '8.42'], ['113', '3', 'road to germany', 'greg colton', 'patrick meighan', 'october 19 , 2008', '6acx08', '9.07'], ['114', '4', 'baby not on board', 'julius wu', 'mark hentemann', 'november 2 , 2008', '6acx07', '9.97'], ['115', '5', 'the man with two brians', 'dominic bianchi', 'john viener', 'november 9 , 2008', '6acx09', '8.60'], ['116', '6', 'tales of a third grade nothing', 'jerry langford', 'alex carter', 'november 16 , 2008', '6acx10', '8.52'], ['117', '7', "ocean 's three and a half", 'john holmquist', 'cherry chevapravatdumrong', 'february 15 , 2009', '6acx11', '7.33'], ['118', '8', 'family gay', 'brian iles', 'richard appel', 'march 8 , 2009', '6acx12', '7.18'], ['119', '9', 'the juice is loose', 'cyndi tang', 'andrew goldberg', 'march 15 , 2009', '6acx13', '7.21'], ['120', '10', 'fox - y lady', 'pete michels', 'matt fleckenstein', 'march 22 , 2009', '6acx14', '7.45'], ['121', '11', 'not all dogs go to heaven', 'greg colton', 'danny smith', 'march 29 , 2009', '6acx17', '8.20'], ['122', '12', 'episode 420', 'julius wu', 'patrick meighan', 'april 19 , 2009', '6acx16', '7.40'], ['123', '13', 'stew - roids', 'jerry langford', 'alec sulkin', 'april 26 , 2009', '6acx18', '6.80'], ['124', '14', 'we love you , conrad', 'john holmquist', 'cherry chevapravatdumrong', 'may 3 , 2009', '6acx19', '6.67'], ['125', '15', 'three kings', 'dominic bianchi', 'alec sulkin', 'may 10 , 2009', '6acx15', '6.47']] |
shweta mohan | https://en.wikipedia.org/wiki/Shweta_Mohan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18550192-2.html.csv | unique | of these songs , nee maatalo was the only one to be released in 2011 . | {'scope': 'all', 'row': '4', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': '2011', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2011'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2011 .', 'tostr': 'filter_eq { all_rows ; year ; 2011 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; year ; 2011 } }', 'tointer': 'select the rows whose year record is equal to 2011 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '2011'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record is equal to 2011 .', 'tostr': 'filter_eq { all_rows ; year ; 2011 }'}, 'song title'], 'result': 'nee maatalo', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 2011 } ; song title }'}, 'nee maatalo'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; year ; 2011 } ; song title } ; nee maatalo }', 'tointer': 'the song title record of this unqiue row is nee maatalo .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; year ; 2011 } } ; eq { hop { filter_eq { all_rows ; year ; 2011 } ; song title } ; nee maatalo } } = true', 'tointer': 'select the rows whose year record is equal to 2011 . there is only one such row in the table . the song title record of this unqiue row is nee maatalo .'} | and { only { filter_eq { all_rows ; year ; 2011 } } ; eq { hop { filter_eq { all_rows ; year ; 2011 } ; song title } ; nee maatalo } } = true | select the rows whose year record is equal to 2011 . there is only one such row in the table . the song title record of this unqiue row is nee maatalo . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '2011_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'song title_9': 9, 'nee maatalo_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '2011_8': '2011', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'song title_9': 'song title', 'nee maatalo_10': 'nee maatalo'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'year_7': [0], '2011_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'song title_9': [2], 'nee maatalo_10': [3]} | ['year', 'song title', 'film', 'co - singer', 'music - director'] | [['2010', 'amma thale', 'puli ( soundtrack )', 'naresh iyer', 'a r rahman'], ['2010', 'piliche', 'khaleja', 'hemachandra', 'mani sharma'], ['2010', 'boom boom robo ra', 'enthiran', 'tanvi shah', 'a r rahman'], ['2011', 'nee maatalo', '180 ( 2011 indian film )', 'karthik', 'sharreth'], ['2012', 'dil se', 'gabbar singh ( film )', 'hemachandra', 'devi sri prasad'], ['2012', 'aagipo', 'ko antey koti', 'karthik , chinnaponnu', 'shakti kanth'], ['2012', 'kaatuka kallu', 'sarocharu', 'khushi murali', 'devi sri prasad'], ['2013', 'hey po', 'okkadine', 'solo', 'karthik'], ['2013', 'neetho edo', 'paisa ( film )', 'solo', 'sai karthik'], ['2013', 'nemmadiga', 'bhai ( 2013 film )', 'venu srirangam', 'devi sri prasad']] |
helmut bradl | https://en.wikipedia.org/wiki/Helmut_Bradl | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14860663-4.html.csv | superlative | 1991 was the best year for helmut bradl , as he won 5 races . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'wins'], 'result': '5', 'ind': 0, 'tostr': 'max { all_rows ; wins }', 'tointer': 'the maximum wins record of all rows is 5 .'}, '5'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; wins } ; 5 }', 'tointer': 'the maximum wins record of all rows is 5 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'wins'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; wins }'}, 'year'], 'result': '1991', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; wins } ; year }'}, '1991'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; wins } ; year } ; 1991 }', 'tointer': 'the year record of the row with superlative wins record is 1991 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; wins } ; 5 } ; eq { hop { argmax { all_rows ; wins } ; year } ; 1991 } } = true', 'tointer': 'the maximum wins record of all rows is 5 . the year record of the row with superlative wins record is 1991 .'} | and { eq { max { all_rows ; wins } ; 5 } ; eq { hop { argmax { all_rows ; wins } ; year } ; 1991 } } = true | the maximum wins record of all rows is 5 . the year record of the row with superlative wins record is 1991 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'wins_8': 8, '5_9': 9, 'eq_4': 4, 'num_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'wins_11': 11, 'year_12': 12, '1991_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'wins_8': 'wins', '5_9': '5', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'wins_11': 'wins', 'year_12': 'year', '1991_13': '1991'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'wins_8': [0], '5_9': [1], 'eq_4': [5], 'num_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'wins_11': [2], 'year_12': [3], '1991_13': [4]} | ['year', 'class', 'team', 'points', 'wins'] | [['1986', '250cc', 'honda', '0', '0'], ['1987', '250cc', 'honda', '0', '0'], ['1988', '250cc', 'honda', '27', '0'], ['1989', '250cc', 'hb - honda', '88', '0'], ['1990', '250cc', 'hb - honda', '150', '0'], ['1991', '250cc', 'hb - honda', '220', '5'], ['1992', '250cc', 'hb - honda', '89', '0'], ['1993', '250cc', 'hb - honda', '126', '0']] |
heartland collegiate athletic conference | https://en.wikipedia.org/wiki/Heartland_Collegiate_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-255205-1.html.csv | ordinal | in the heartland collegiate athletic conference , the institution with the 2nd highest enrollment is college of mount st. joseph . | {'row': '3', 'col': '6', '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', 'enrollment', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; enrollment ; 2 }'}, 'institution'], 'result': 'college of mount st joseph', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; enrollment ; 2 } ; institution }'}, 'college of mount st joseph'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; institution } ; college of mount st joseph } = true', 'tointer': 'select the row whose enrollment record of all rows is 2nd maximum . the institution record of this row is college of mount st joseph .'} | eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; institution } ; college of mount st joseph } = true | select the row whose enrollment record of all rows is 2nd maximum . the institution record of this row is college of mount st joseph . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '2_6': 6, 'institution_7': 7, 'college of mount st joseph_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', '2_6': '2', 'institution_7': 'institution', 'college of mount st joseph_8': 'college of mount st joseph'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '2_6': [0], 'institution_7': [1], 'college of mount st joseph_8': [2]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined'] | [['anderson university', 'anderson , indiana', 'ravens', '1917', 'private / church of god', '3065', '1987'], ['bluffton university', 'bluffton , ohio', 'beavers', '1899', 'private / mennonite', '1191', '1998'], ['college of mount st joseph', 'cincinnati , ohio', 'lions', '1920', 'private / catholic', '2259', '1998'], ['defiance college', 'defiance , ohio', 'yellow jackets', '1850', 'private / united church of christ', '1000', '2000'], ['earlham college', 'richmond , indiana', 'quakers', '1847', 'private / quaker', '1194', '2010'], ['franklin college', 'franklin , indiana', 'grizzlies', '1834', 'private / baptist', '1000', '1987'], ['hanover college', 'hanover , indiana', 'panthers', '1827', 'private / presbyterian', '1062', '1987'], ['manchester university', 'north manchester , indiana', 'spartans', '1860', 'private / church of the brethren', '1250', '1987'], ['rose - hulman institute of technology', 'terre haute , indiana', "fightin ' engineers", '1874', 'private / non - sectarian', '1970', '1988 1']] |
peanut oil | https://en.wikipedia.org/wiki/Peanut_oil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1195910-1.html.csv | count | only three of the peanut oils listed have less than 100 g of total fat . | {'scope': 'all', 'criterion': 'less_than', 'value': '100 g', 'result': '3', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'total fat', '100 g'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total fat record is less than 100 g .', 'tostr': 'filter_less { all_rows ; total fat ; 100 g }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; total fat ; 100 g } }', 'tointer': 'select the rows whose total fat record is less than 100 g . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; total fat ; 100 g } } ; 3 } = true', 'tointer': 'select the rows whose total fat record is less than 100 g . the number of such rows is 3 .'} | eq { count { filter_less { all_rows ; total fat ; 100 g } } ; 3 } = true | select the rows whose total fat record is less than 100 g . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'total fat_5': 5, '100 g_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'total fat_5': 'total fat', '100 g_6': '100 g', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'total fat_5': [0], '100 g_6': [0], '3_7': [2]} | ['total fat', 'saturated fat', 'monounsaturated fat', 'polyunsaturated fat', 'smoke point'] | [['100 g', '11 g', '20 g ( 84 g in high oleic variety )', '69 g ( 4 g in high oleic variety )', 'degree'], ['100 g', '16 g', '23 g', '58 g', 'degree'], ['100 g', '7 g', '63 g', '28 g', 'degree'], ['100 g', '14 g', '73 g', '11 g', 'degree'], ['100 g', '15 g', '30 g', '55 g', 'degree'], ['100 g', '17 g', '46 g', '32 g', 'degree'], ['100 g', '25 g', '38 g', '37 g', 'degree'], ['71 g', '23 g ( 34 % )', '8 g ( 11 % )', '37 g ( 52 % )', 'degree'], ['100 g', '39 g', '45 g', '11 g', 'degree'], ['94 g', '52 g ( 55 % )', '32 g ( 34 % )', '3 g ( 3 % )', '200degree ( 400degree )'], ['81 g', '51 g ( 63 % )', '21 g ( 26 % )', '3 g ( 4 % )', 'degree']] |
list of actors who played president of the united states | https://en.wikipedia.org/wiki/List_of_actors_who_played_President_of_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1673723-13.html.csv | count | martin sheen won five awards for playing the part of josiah bartlet . | {'scope': 'all', 'criterion': 'equal', 'value': 'josiah bartlet', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'president', 'josiah bartlet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose president record fuzzily matches to josiah bartlet .', 'tostr': 'filter_eq { all_rows ; president ; josiah bartlet }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; president ; josiah bartlet } }', 'tointer': 'select the rows whose president record fuzzily matches to josiah bartlet . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; president ; josiah bartlet } } ; 5 } = true', 'tointer': 'select the rows whose president record fuzzily matches to josiah bartlet . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; president ; josiah bartlet } } ; 5 } = true | select the rows whose president record fuzzily matches to josiah bartlet . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'president_5': 5, 'josiah bartlet_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'president_5': 'president', 'josiah bartlet_6': 'josiah bartlet', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'president_5': [0], 'josiah bartlet_6': [0], '5_7': [2]} | ['year', 'category', 'president', 'nominee', 'film or television series or miniseries'] | [['1964', 'best actor - motion picture drama', 'jordan lyman', 'fredric march', 'seven days in may'], ['1999', 'best actor - television series drama', 'josiah bartlet', 'martin sheen', 'the west wing'], ['2000', 'best actor - television series drama', 'josiah bartlet', 'martin sheen', 'the west wing'], ['2001', 'best actor - television series drama', 'josiah bartlet', 'martin sheen', 'the west wing'], ['2002', 'best actor - television series drama', 'josiah bartlet', 'martin sheen', 'the west wing'], ['2003', 'best actor - television series drama', 'josiah bartlet', 'martin sheen', 'the west wing'], ['2006', 'best actress - television series drama', 'mackenzie allen', 'geena davis', 'commander in chief']] |
stephanie vogt | https://en.wikipedia.org/wiki/Stephanie_Vogt | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16306899-6.html.csv | count | stephanie vogt played a total of two tournaments in the netherlands . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'netherlands', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'netherlands'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to netherlands .', 'tostr': 'filter_eq { all_rows ; tournament ; netherlands }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tournament ; netherlands } }', 'tointer': 'select the rows whose tournament record fuzzily matches to netherlands . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tournament ; netherlands } } ; 2 } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to netherlands . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; tournament ; netherlands } } ; 2 } = true | select the rows whose tournament record fuzzily matches to netherlands . 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, 'tournament_5': 5, 'netherlands_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', 'tournament_5': 'tournament', 'netherlands_6': 'netherlands', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tournament_5': [0], 'netherlands_6': [0], '2_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', '24 june 2007', 'davos , switzerland', 'clay', 'jessica moore', '6 - 4 , 4 - 6 , 6 - 3'], ['runner - up', '19 august 2007', 'pesaro , italy', 'clay', 'polona hercog', '2 - 6 , 6 - 2 , 1 - 6'], ['runner - up', '28 october 2007', 'mexico city , mexico', 'hard', 'olivia sanchez', '6 - 2 , 2 - 6 , 2 - 6'], ['runner - up', '16 february 2008', 'majora , spain', 'clay', 'polona hercog', '6 - 4 , 1 - 6 , 3 - 6'], ['winner', '4 may 2008', 'makarska , croatia', 'clay', 'anastasia pivovarova', '6 - 2 , 6 - 3'], ['winner', '29 may 2010', 'velenje , slovenia', 'clay', 'pavla šmídová', '6 - 1 , 6 - 2'], ['winner', '31 october 2010', 'cairo , egypt', 'clay', 'maša zec peškirič', '6 - 1 , 6 - 3'], ['runner - up', '23 january 2011', 'andrézieux - bouthéon , france', 'hard', 'mona barthel', '3 - 6 , 6 - 3 , 4 - 6'], ['runner - up', '10 july 2011', 'aschaffenburg , germany', 'clay', 'florencia molinero', '6 - 7 ( 6 - 8 ) , 1 - 6'], ['winner', '11 september 2011', 'alphen aan den rijn , netherlands', 'clay', 'katarzyna piter', '6 - 2 , 6 - 4'], ['runner - up', '18 september 2011', 'rotterdam , netherlands', 'clay', 'dinah pfizenmaier', '6 - 3 , 1 - 6 , 1 - 6'], ['runner - up', '3 november 2012', 'netanya , israel', 'hard', 'anna karolína schmiedlová', '6 - 0 , 3 - 6 , 4 - 6'], ['winner', '10 march 2013', 'sutton , united kingdom', 'hard ( i )', 'carina witthöft', '3 - 6 , 6 - 4 , 6 - 3'], ['winner', '17 march 2013', 'bath , united kingdom', 'hard ( i )', 'an - sophie mestach', '7 - 6 ( 7 - 3 ) , 6 - 3'], ['winner', '13 july 2013', 'biarritz , france', 'clay', 'anna karolína schmiedlová', '1 - 6 , 6 - 3 , 6 - 2'], ['winner', '15 september 2013', 'podgorica , montenegro', 'clay', 'anett kontaveit', '6 - 4 , 6 - 3']] |
list of california golden seals draft picks | https://en.wikipedia.org/wiki/List_of_California_Golden_Seals_draft_picks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18272351-4.html.csv | superlative | ken hicks was the earliest pick made by the california golden seals during this time frame . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'pick'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; pick }'}, 'player'], 'result': 'ken hicks', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; pick } ; player }'}, 'ken hicks'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; pick } ; player } ; ken hicks } = true', 'tointer': 'select the row whose pick record of all rows is minimum . the player record of this row is ken hicks .'} | eq { hop { argmin { all_rows ; pick } ; player } ; ken hicks } = true | select the row whose pick record of all rows is minimum . the player record of this row is ken hicks . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'pick_5': 5, 'player_6': 6, 'ken hicks_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'pick_5': 'pick', 'player_6': 'player', 'ken hicks_7': 'ken hicks'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'pick_5': [0], 'player_6': [1], 'ken hicks_7': [2]} | ['draft', 'round', 'pick', 'player', 'nationality'] | [['1967', '1', '3', 'ken hicks', 'canada'], ['1967', '2', '12', 'gary wood', 'usa'], ['1967', '3', '18', 'kevin smith', 'canada'], ['1968', '2', '13', 'doug smith', 'canada'], ['1968', '3', '20', 'jim trewin', 'canada'], ['1969', '1', '7', 'tony featherstone', 'canada'], ['1969', '2', '18', 'ron stackhouse', 'canada'], ['1969', '3', '29', "don o'donoghue", 'canada'], ['1969', '4', '41', 'pierre farmer', 'canada'], ['1969', '5', '53', 'warren harrison', 'canada'], ['1969', '6', '65', 'neil nicholson', 'canada'], ['1969', '7', '76', 'pete vipond', 'canada'], ['1970', '1', '10', 'chris oddleifson', 'canada'], ['1970', '2', '19', 'pete laframboise', 'canada'], ['1970', '3', '33', 'randy rota', 'canada']] |
rowing at the 2008 summer olympics - men 's single sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_single_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662643-5.html.csv | aggregation | the average time for the top 3 in the men 's single sculls at the 2008 summer olympics was 7:30.63 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '7:30.63', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '3'}} | {'func': 'round_eq', 'args': [{'func': 'avg', '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 .'}, 'time'], 'result': '7:30.63', 'ind': 1, 'tostr': 'avg { filter_less_eq { all_rows ; rank ; 3 } ; time }'}, '7:30.63'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less_eq { all_rows ; rank ; 3 } ; time } ; 7:30.63 } = true', 'tointer': 'select the rows whose rank record is less than or equal to 3 . the average of the time record of these rows is 7:30.63 .'} | round_eq { avg { filter_less_eq { all_rows ; rank ; 3 } ; time } ; 7:30.63 } = true | select the rows whose rank record is less than or equal to 3 . the average of the time record of these rows is 7:30.63 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'rank_5': 5, '3_6': 6, 'time_7': 7, '7:30.63_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '3_6': '3', 'time_7': 'time', '7:30.63_8': '7:30.63'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '3_6': [0], 'time_7': [1], '7:30.63_8': [2]} | ['rank', 'athlete', 'country', 'time', 'notes'] | [['1', 'ondå ™ ej synek', 'czech republic', '7:23.94', 'q'], ['2', 'mindaugas griskonis', 'lithuania', '7:28.05', 'q'], ['3', 'bajrang lal takhar', 'india', '7:39.91', 'q'], ['4', 'mathias raymond', 'monaco', '7:51.69', 'q'], ['5', 'chaouki dries', 'algeria', '7:57.65', 'se / f']] |
list of cities in the far east by population | https://en.wikipedia.org/wiki/List_of_cities_in_the_Far_East_by_population | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16478687-5.html.csv | ordinal | the city with the third highest population in the far east is beijing . | {'row': '3', 'col': '3', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'population', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ; 3 }'}, 'city'], 'result': 'beijing', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population ; 3 } ; city }'}, 'beijing'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; population ; 3 } ; city } ; beijing } = true', 'tointer': 'select the row whose population record of all rows is 3rd maximum . the city record of this row is beijing .'} | eq { hop { nth_argmax { all_rows ; population ; 3 } ; city } ; beijing } = true | select the row whose population record of all rows is 3rd maximum . the city record of this row is beijing . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population_5': 5, '3_6': 6, 'city_7': 7, 'beijing_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', 'population_5': 'population', '3_6': '3', 'city_7': 'city', 'beijing_8': 'beijing'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population_5': [0], '3_6': [0], 'city_7': [1], 'beijing_8': [2]} | ['rank', 'city', 'population', 'definition', 'country'] | [['1', 'shanghai', '13831900', 'core districts + inner suburbs', 'china'], ['2', 'seoul', '10456034', 'special city', 'south korea'], ['3', 'beijing', '10123000', 'core districts + inner suburbs', 'china'], ['4', 'tokyo', '8795000', '23 special wards area', 'japan'], ['5', 'jakarta', '8489910', 'special capital district', 'indonesia'], ['6', 'wuhan', '8001541 ( 2006 - 12 - 31 )', 'core districts', 'china'], ['7', 'ho chi minh city', '7123340', 'province - level municipality', 'vietnam'], ['8', 'bangkok', '7025000', 'administrative area', 'thailand'], ['9', 'hong kong', '7008900', 'the entire territory', 'hong kong'], ['10', 'guangzhou', '6172839 ( 2006 - 12 - 31 )', 'core districts', 'china'], ['11', 'tianjin', '5800000', 'core districts + inner suburbs', 'china'], ['12', 'singapore', '4839400', 'country', 'singapore'], ['13', 'chongqing', '4776027', 'core districts', 'china'], ['14', 'shenyang', '4101197 ( 2006 - 12 - 31 )', 'core districts', 'china'], ['15', 'yangon', '4088000', 'urban agglomeration', 'burma'], ['16', 'yokohama', '3670000', 'city proper', 'japan'], ['17', 'busan', '3596076', 'metropolitan city', 'south korea'], ['18', 'pyongyang', '3255388', 'directly governed city', 'north korea']] |
turkmenistan fed cup team | https://en.wikipedia.org/wiki/Turkmenistan_Fed_Cup_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11311764-4.html.csv | aggregation | the players on the turkmenistan fed cup team had a combined total of 64 ties . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '64', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'ties'], 'result': '64', 'ind': 0, 'tostr': 'sum { all_rows ; ties }'}, '64'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; ties } ; 64 } = true', 'tointer': 'the sum of the ties record of all rows is 64 .'} | round_eq { sum { all_rows ; ties } ; 64 } = true | the sum of the ties record of all rows is 64 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'ties_4': 4, '64_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'ties_4': 'ties', '64_5': '64'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'ties_4': [0], '64_5': [1]} | ['name', 'tkm career', 'ties', 'dou w / l', 'sin w / l'] | [['anastasiya prenko', '2008 -', '18', '9 - 6', '10 - 7'], ['jenneta halliyeva', '2004 - 2013', '18', '5 - 6', '4 - 5'], ['ummarahmat hummetova', '2004 - 2012', '13', '3 - 8', '1 - 7'], ['ayna ereshova', '2011', '1', '1 - 0', '0 - 0'], ['guljahan kadryova', '2013', '2', '1 - 0', '0 - 1'], ['amangul mollayeva', '2011', '4', '1 - 0', '0 - 3'], ['jahana bayramova', '2013 -', '5', '1 - 1', '1 - 4'], ['veronika babayan', '2004', '3', '1 - 2', '0 - 1']] |
list of the listener episodes | https://en.wikipedia.org/wiki/List_of_The_Listener_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25131572-2.html.csv | count | three episodes of the listener originally aired in canada in august of 2009 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'august', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original canadian air date', 'august'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original canadian air date record fuzzily matches to august .', 'tostr': 'filter_eq { all_rows ; original canadian air date ; august }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; original canadian air date ; august } }', 'tointer': 'select the rows whose original canadian air date record fuzzily matches to august . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; original canadian air date ; august } } ; 3 } = true', 'tointer': 'select the rows whose original canadian air date record fuzzily matches to august . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; original canadian air date ; august } } ; 3 } = true | select the rows whose original canadian air date record fuzzily matches to august . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'original canadian air date_5': 5, 'august_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'original canadian air date_5': 'original canadian air date', 'august_6': 'august', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original canadian air date_5': [0], 'august_6': [0], '3_7': [2]} | ['series', 'season', 'title', 'directed by', 'written by', 'original canadian air date', 'fox int channels air date'] | [['1', '1', "i 'm an adult now", 'clement virgo', 'michael amo', 'june 3 , 2009', 'march 3 , 2009'], ['2', '2', 'emotional rescue', 'ken girotti', 'russ cochrane', 'june 4 , 2009', 'march 10 , 2009'], ['3', '3', 'a voice in the dark', 'clement virgo', 'michael amo', 'june 11 , 2009', 'march 17 , 2009'], ['4', '4', 'some kind of love', 'clement virgo', 'larry lalonde , phil bedard', 'june 18 , 2009', 'march 24 , 2009'], ['5', '5', 'lisa says', 'kari skogland', 'dennis heaton', 'july 2 , 2009', 'march 31 , 2009'], ['6', '6', 'foggy notion', 'clement virgo', 'jeremy boxen', 'july 9 , 2009', 'april 7 , 2009'], ['7', '7', 'iris', 'stephen surjik', 'michael amo', 'july 16 , 2009', 'april 14 , 2009'], ['10', '8', 'one way or another', 'stephen surjik', 'dennis heaton', 'july 23 , 2009', 'april 21 , 2009'], ['9', '9', 'inside the man', 'clement virgo', 'michael amo', 'july 30 , 2009', 'april 28 , 2009'], ['10', '10', 'missing', 'tj scott', 'avrum jacobson', 'august 6 , 2009', 'may 5 , 2009'], ['11', '11', 'beginning to see the light', 'clement virgo', 'avrum jacobson story by : travis mcdonald', 'august 13 , 2009', 'may 12 , 2009'], ['12', '12', "the 13th juror / my sister 's keeper", 'kari skogland', 'ross cochrane', 'august 20 , 2009', 'may 19 , 2009']] |
list of auto racing tracks in the united states | https://en.wikipedia.org/wiki/List_of_auto_racing_tracks_in_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14688681-4.html.csv | ordinal | the indianapolis speedway racetrack was the second earliest figure eight race track to be built in the united states . | {'row': '4', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'opened ( closing date if defunct )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; opened ( closing date if defunct ) ; 2 }'}, 'track'], 'result': 'indianapolis speedrome', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; opened ( closing date if defunct ) ; 2 } ; track }'}, 'indianapolis speedrome'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; opened ( closing date if defunct ) ; 2 } ; track } ; indianapolis speedrome } = true', 'tointer': 'select the row whose opened ( closing date if defunct ) record of all rows is 2nd minimum . the track record of this row is indianapolis speedrome .'} | eq { hop { nth_argmin { all_rows ; opened ( closing date if defunct ) ; 2 } ; track } ; indianapolis speedrome } = true | select the row whose opened ( closing date if defunct ) record of all rows is 2nd minimum . the track record of this row is indianapolis speedrome . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'opened (closing date if defunct)_5': 5, '2_6': 6, 'track_7': 7, 'indianapolis speedrome_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', 'opened (closing date if defunct)_5': 'opened ( closing date if defunct )', '2_6': '2', 'track_7': 'track', 'indianapolis speedrome_8': 'indianapolis speedrome'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'opened (closing date if defunct)_5': [0], '2_6': [0], 'track_7': [1], 'indianapolis speedrome_8': [2]} | ['track', 'city', 'state', 'opened ( closing date if defunct )', 'surface', 'length'] | [['altamont motorsports park', 'tracy', 'california', '1966 - 2008', 'asphalt', 'miles ( km )'], ['evergreen speedway', 'monroe', 'washington', '1954', 'asphalt', 'miles ( km )'], ['holland speedway', 'holland', 'new york', '1960', 'concrete', 'miles ( km )'], ['indianapolis speedrome', 'indianapolis', 'indiana', '1945', 'asphalt', 'miles ( km )'], ['little valley speedway', 'little valley', 'new york', '1932 - 2011 ( figure 8 track )', 'clay', 'miles ( km )'], ['manzanita speedway', 'phoenix', 'arizona', '1951 - 2010', 'asphalt', 'miles ( km )'], ['riverhead raceway', 'riverhead', 'new york', '1951', 'asphalt', 'miles ( km )'], ['slinger speedway', 'slinger', 'wisconsin', '1974', 'asphalt', 'miles ( km )']] |
mid - states football association | https://en.wikipedia.org/wiki/Mid-States_Football_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-262560-2.html.csv | majority | all type of the mid - states football association was private . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'private', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'type', 'private'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , all of them fuzzily match to private .', 'tostr': 'all_eq { all_rows ; type ; private } = true'} | all_eq { all_rows ; type ; private } = true | for the type records of all rows , all of them fuzzily match to private . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'private_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'private_4': 'private'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'private_4': [0]} | ['institution', 'location', 'founded', 'type', 'enrollment', 'joined', 'left', 'nickname', 'primary conference when joining the msfa', 'current primary conference'] | [['university of findlay', 'findlay , ohio', '1882', 'private', '4600', '1994 - 95', '1997 - 98', 'oilers', 'american mideast', 'gliac ( ncaa division ii )'], ['geneva college', 'beaver falls , pennsylvania', '1848', 'private', '1791', '1994 - 95', '2006 - 07', 'golden tornadoes', 'american mideast', "presidents ' ( pac ) ( ncaa division iii )"], ['iowa wesleyan college', 'mount pleasant , iowa', '1842', 'private', '850', '1996 - 97', '2011 - 12', 'tigers', 'mcc', 'ncaa d - iii independent'], ['lindenwood university', 'st charles , missouri', '1827', 'private', '17351', '1994 - 95', '1995 - 96', 'lions', 'american midwest', 'miaa ( ncaa division ii )'], ['malone university', 'canton , ohio', '1892', 'private', '2559', '1994 - 95', '2010 - 11', 'pioneers', 'american mideast', 'gliac ( ncaa division ii )'], ['mckendree university', 'lebanon , illinois', '1828', 'private', '3220', '1998 - 99', '2010 - 11', 'bearcats', 'american midwest', 'glvc ( ncaa division ii )'], ['ohio dominican university', 'columbus , ohio', '1911', 'private', '3052', '2004 - 05', '2008 - 09', 'panthers', 'american mideast', 'gliac ( ncaa division ii )'], ['quincy university', 'quincy , illinois', '1860', 'private', '1169', '2003 - 04', '2011 - 12', 'hawks', 'glvc ( ncaa division ii )', 'glvc ( ncaa division ii )'], ['tiffin university', 'tiffin , ohio', '1888', 'private', '6816', '1994 - 95', '2001 - 02', 'dragons', 'american mideast', 'gliac ( ncaa division ii )'], ['trine university', 'angola , indiana', '1884', 'private', '1779', '1996 - 97', '2002 - 03', 'thunder', 'whac', 'miaa ( ncaa division iii )'], ['urbana university', 'urbana , ohio', '1850', 'private', '1505', '1994 - 95', '2007 - 08', 'blue knights', 'american mideast', 'g - mac ( ncaa division ii )'], ['walsh university', 'north canton , ohio', '1960', 'private', '2500', '1996 - 97', '2010 - 11', 'cavaliers', 'american mideast', 'gliac ( ncaa division ii )']] |
1980 indycar season | https://en.wikipedia.org/wiki/1980_IndyCar_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10527215-2.html.csv | count | 2 races were held in the month of june during the 1980 indycar season . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'june', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'june'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to june .', 'tostr': 'filter_eq { all_rows ; date ; june }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; june } }', 'tointer': 'select the rows whose date record fuzzily matches to june . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; june } } ; 2 } = true', 'tointer': 'select the rows whose date record fuzzily matches to june . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; date ; june } } ; 2 } = true | select the rows whose date record fuzzily matches to june . 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, 'date_5': 5, 'june_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', 'date_5': 'date', 'june_6': 'june', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'june_6': [0], '2_7': [2]} | ['sanctioning', 'race name', 'circuit', 'city / location', 'date'] | [['joint cart / usac ( crl )', 'datsun twin 200', 'ontario motor speedway', 'ontario , california', 'april 13'], ['joint cart / usac ( crl )', 'indianapolis 500 - mile race', 'indianapolis motor speedway', 'indianapolis , indiana', 'may 26'], ['joint cart / usac ( crl )', 'gould rex mays classic 150', 'milwaukee mile', 'west allis , wisconsin', 'june 8'], ['joint cart / usac ( crl )', 'true value 500', 'pocono raceway', 'long pond , pennsylvania', 'june 22'], ['joint cart / usac ( crl )', 'red roof inns 150', 'mid - ohio sports car course', 'lexington , ohio', 'july 13'], ['cart', 'norton 200', 'michigan international speedway', 'brooklyn , michigan', 'july 20'], ['cart', 'kent oil 150', 'watkins glen international', 'watkins glen , new york', 'august 3'], ['cart', 'tony bettenhausen 200', 'milwaukee mile', 'west allis , wisconsin', 'august 10'], ['cart', 'california 500', 'ontario motor speedway', 'ontario , california', 'august 31'], ['cart', 'gould grand prix 150', 'michigan international speedway', 'brooklyn , michigan', 'september 20'], ['cart', 'i copa méxico 150', 'autódromo hermanos rodríguez', 'mexico city , mexico', 'october 26'], ['cart', 'miller high life 150', 'phoenix international raceway', 'avondale , arizona', 'november 8']] |
1972 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1972_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245554-3.html.csv | aggregation | the average score of players in the 1972 u.s. open was 145 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '145', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '145', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '145'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 145 } = true', 'tointer': 'the average of the score record of all rows is 145 .'} | round_eq { avg { all_rows ; score } ; 145 } = true | the average of the score record of all rows is 145 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '145_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '145_5': '145'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '145_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'jack nicklaus', 'united states', '71 + 73 = 144', 'e'], ['t1', 'bruce crampton', 'australia', '74 + 70 = 144', 'e'], ['t1', 'kermit zarley', 'united states', '71 + 73 = 144', 'e'], ['t1', 'lanny wadkins', 'united states', '76 + 68 = 144', 'e'], ['t1', 'homero blancas', 'united states', '74 + 70 = 144', 'e'], ['t1', 'cesar sanudo', 'united states', '72 + 72 = 144', 'e'], ['7', 'arnold palmer', 'united states', '77 + 68 = 145', '+ 1'], ['t8', 'lee trevino', 'united states', '74 + 72 = 146', '+ 2'], ['t8', 'lee elder', 'united states', '75 + 71 = 146', '+ 2'], ['t8', 'ralph johnston', 'united states', '74 + 72 = 146', '+ 2'], ['t8', 'rod funseth', 'united states', '73 + 73 = 146', '+ 2'], ['t8', 'gary player', 'south africa', '72 + 74 = 146', '+ 2'], ['t8', 'chi - chi rodrã\xadguez', 'united states', '71 + 75 = 146', '+ 2']] |
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