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2008 - 09 belgian first division | https://en.wikipedia.org/wiki/2008%E2%80%9309_Belgian_First_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17260623-1.html.csv | aggregation | the average stadium capacity for clubs in the belgian first division is 15684 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '15684', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'capacity'], 'result': '15684', 'ind': 0, 'tostr': 'avg { all_rows ; capacity }'}, '15684'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; capacity } ; 15684 } = true', 'tointer': 'the average of the capacity record of all rows is 1568... | round_eq { avg { all_rows ; capacity } ; 15684 } = true | the average of the capacity record of all rows is 15684 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'capacity_4': 4, '15684_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'capacity_4': 'capacity', '15684_5': '15684'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'capacity_4': [0], '15684_5': [1]} | ['club', 'location', 'current manager', 'team captain', 'stadium', 'capacity'] | [['standard liège', 'liège', 'lászló bölöni', 'steven defour', 'stade maurice dufrasne', '30000'], ['rsc anderlecht', 'anderlecht', 'ariel jacobs', 'olivier deschacht', 'constant vanden stock stadium', '28063'], ['club brugge kv', 'bruges', 'jacky mathijssen', 'philippe clement', 'jan breydel stadium', '29415'], ['cerc... |
list of the busiest airports in brazil | https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_Brazil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15494883-26.html.csv | aggregation | the top 15 busiest airports in brazil in 2004 averaged 4,773,780 total passengers . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '4773780', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total passengers'], 'result': '4773780', 'ind': 0, 'tostr': 'avg { all_rows ; total passengers }'}, '4773780'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total passengers } ; 4773780 } = true', 'tointer': 'the average of the total... | round_eq { avg { all_rows ; total passengers } ; 4773780 } = true | the average of the total passengers record of all rows is 4773780 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total passengers_4': 4, '4773780_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total passengers_4': 'total passengers', '4773780_5': '4773780'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total passengers_4': [0], '4773780_5': [1]} | ['rank', 'location', 'total passengers', 'annual change', 'capacity in use'] | [['1', 'são paulo', '13611227', '12.8 %', '113.4 %'], ['2', 'são paulo', '12940193', '11.7 %', '78.4 %'], ['3', 'brasília', '9926786', '45.1 %', '134.1 %'], ['4', 'rio de janeiro', '6024930', '30.4 %', '40.2 %'], ['5', 'rio de janeiro', '4887306', '9.2 %', '152.7 %'], ['6', 'salvador', '4145371', '20.0 %', '69.1 %'], [... |
2008 - 09 phoenix suns season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17340355-5.html.csv | majority | during november of the 2008 - 09 season , steve nash had the highest assist total in the majority of games for the phoenix suns . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'steve nash', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high assists', 'steve nash'], 'result': True, 'ind': 0, 'tointer': 'for the high assists records of all rows , most of them fuzzily match to steve nash .', 'tostr': 'most_eq { all_rows ; high assists ; steve nash } = true'} | most_eq { all_rows ; high assists ; steve nash } = true | for the high assists records of all rows , most of them fuzzily match to steve nash . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high assists_3': 3, 'steve nash_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high assists_3': 'high assists', 'steve nash_4': 'steve nash'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high assists_3': [0], 'steve nash_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['3', 'november 1', 'portland', 'w 107 - 96 ( ot )', "amar ' e stoudemire ( 23 )", "amar ' e stoudemire ( 13 )", 'steve nash ( 7 )', 'us airways center 18422', '2 - 1'], ['4', 'november 4', 'new jersey', 'w 114 - 86 ( ot )', 'raja bell ( 22 )', 'matt barnes ( 7 )', 'steve nash ( 11 )', 'izod center 15230', '3 - 1'], [... |
list of tennis stadiums by capacity | https://en.wikipedia.org/wiki/List_of_tennis_stadiums_by_capacity | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14476860-3.html.csv | unique | only one of the world 's largest tennis stadiums by capacity is in italy . | {'scope': 'all', 'row': '13', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'italy', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; country ; italy }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; c... | only { filter_eq { all_rows ; country ; italy } } = true | select the rows whose country record fuzzily matches to italy . 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, 'country_4': 4, 'italy_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'italy_5': 'italy'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'italy_5': [0]} | ['rank', 'stadium', 'capacity', 'city', 'country'] | [['1', 'queensland sport and athletics centre', '49000', 'brisbane', 'australia'], ['2', 'estadio olímpico de sevilla', '27200', 'seville', 'spain'], ['3', 'belgrade arena', '23000', 'belgrade', 'serbia'], ['4', 'las ventas', '21000', 'madrid', 'spain'], ['5', 'royal dublin society', '6000', 'dublin', 'ireland'], ['6',... |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-40.html.csv | unique | of the ones with the party republican , the only one with the results of retired republican hold had the incumbent of mark sanford . | {'scope': 'subset', 'row': '1', 'col': '5', 'col_other': '2,3', 'criterion': 'equal', 'value': 'retired republican hold', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'republican'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; party ; republican }', 'tointer': 'select the rows whose party record fuzzily matches to republican .'},... | and { only { filter_eq { filter_eq { all_rows ; party ; republican } ; results ; retired republican hold } } ; eq { hop { filter_eq { filter_eq { all_rows ; party ; republican } ; results ; retired republican hold } ; incumbent } ; mark sanford } } = true | select the rows whose party record fuzzily matches to republican . among these rows , select the rows whose results record fuzzily matches to retired republican hold . there is only one such row in the table . the incumbent record of this unqiue row is mark sanford . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'party_8': 8, 'republican_9': 9, 'results_10': 10, 'retired republican hold_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'incumbent_12': 12, 'mark sanford_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'party_8': 'party', 'republican_9': 'republican', 'results_10': 'results', 'retired republican hold_11': 'retired republican hold', 'str_eq_4': 'str_eq', 'str_hop_3':... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'party_8': [0], 'republican_9': [0], 'results_10': [1], 'retired republican hold_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'incumbent_12': [3], 'mark sanford_13': [4]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['south carolina 1', 'mark sanford', 'republican', '1994', 'retired republican hold', 'henry brown ( r ) 60 % andy brack ( d ) 36 %'], ['south carolina 2', 'floyd spence', 'republican', '1970', 're - elected', 'floyd spence ( r ) 58 % jane frederick ( d ) 41 %'], ['south carolina 3', 'lindsey graham', 'republican', '1... |
united states house of representatives elections , 1964 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1964 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341865-11.html.csv | count | 2 of the elections were first elected before the year 1950 . | {'scope': 'all', 'criterion': 'less_than', 'value': '1950', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'first elected', '1950'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is less than 1950 .', 'tostr': 'filter_less { all_rows ; first elected ; 1950 }'}], 'result': '2', 'ind': 1, 'tostr':... | eq { count { filter_less { all_rows ; first elected ; 1950 } } ; 2 } = true | select the rows whose first elected record is less than 1950 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1950_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '1950_6': '1950', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1950_6': [0], '2_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['florida 1', 'robert l f sikes', 'democratic', '1940', 're - elected', 'robert l f sikes ( d ) unopposed'], ['florida 3', 'claude pepper', 'democratic', '1962', 're - elected', "claude pepper ( d ) 65.7 % paul j o'neill ( r ) 34.3 %"], ['florida 4', 'dante fascell', 'democratic', '1954', 're - elected', 'dante fascel... |
2003 games of the small states of europe | https://en.wikipedia.org/wiki/2003_Games_of_the_Small_States_of_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11316160-1.html.csv | ordinal | cyprus had the second highest number of silver medals in the 2003 games of the small states of europe . | {'row': '1', 'col': '4', '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', 'silver', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; silver ; 2 }'}, 'nation'], 'result': 'cyprus', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; silver ; 2 } ; nation }'}, 'cyprus'], 'result'... | eq { hop { nth_argmax { all_rows ; silver ; 2 } ; nation } ; cyprus } = true | select the row whose silver record of all rows is 2nd maximum . the nation record of this row is cyprus . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, '2_6': 6, 'nation_7': 7, 'cyprus_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', 'silver_5': 'silver', '2_6': '2', 'nation_7': 'nation', 'cyprus_8': 'cyprus'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], '2_6': [0], 'nation_7': [1], 'cyprus_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'cyprus', '34', '20', '27', '81'], ['2', 'luxembourg', '21', '17', '15', '53'], ['3', 'iceland', '20', '24', '23', '67'], ['4', 'malta', '11', '18', '15', '44'], ['5', 'monaco', '7', '7', '10', '24'], ['6', 'san marino', '6', '10', '9', '25'], ['7', 'andorra', '4', '6', '8', '18'], ['8', 'liechtenstein', '2', '1... |
2008 indian premier league | https://en.wikipedia.org/wiki/2008_Indian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15734036-10.html.csv | aggregation | the total number of runs for players in the 2008 indian premier league is 1974 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '1974', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'runs'], 'result': '1974', 'ind': 0, 'tostr': 'sum { all_rows ; runs }'}, '1974'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; runs } ; 1974 } = true', 'tointer': 'the sum of the runs record of all rows is 1974 .'} | round_eq { sum { all_rows ; runs } ; 1974 } = true | the sum of the runs record of all rows is 1974 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'runs_4': 4, '1974_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'runs_4': 'runs', '1974_5': '1974'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'runs_4': [0], '1974_5': [1]} | ['player', 'team', 'inns', 'runs', 'balls'] | [['virender sehwag', 'delhi daredevils', '14', '406', '220'], ['yusuf pathan', 'rajasthan royals', '15', '435', '243'], ['sanath jayasuriya', 'mumbai indians', '14', '514', '309'], ['yuvraj singh', 'kings xi punjab', '14', '299', '184'], ['kumar sangakkara', 'kings xi punjab', '9', '320', '198']] |
2009 deutsche tourenwagen masters season | https://en.wikipedia.org/wiki/2009_Deutsche_Tourenwagen_Masters_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21321935-2.html.csv | ordinal | the second game of the deutch masters season in 2009 was played on may 31 . | {'row': '2', 'col': '3', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '2'], 'result': '31 may', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 2 }', 'tointer': 'the 2nd minimum date record of all rows is 31 may .'}, '31 may'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; date ; 2 } ; 31 may } = tru... | eq { nth_min { all_rows ; date ; 2 } ; 31 may } = true | the 2nd minimum date record of all rows is 31 may . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'date_4': 4, '2_5': 5, '31 may_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'date_4': 'date', '2_5': '2', '31 may_6': '31 may'} | {'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'date_4': [0], '2_5': [0], '31 may_6': [1]} | ['round', 'circuit', 'date', 'pole position', 'fastest lap', 'winning driver', 'winning team'] | [['1', 'hockenheimring', '17 may', 'mattias ekström', 'mattias ekström', 'tom kristensen', 'abt sportsline'], ['2', 'eurospeedway lausitz', '31 may', 'mattias ekström', 'jamie green', 'gary paffett', 'hwa team'], ['3', 'norisring , nuremberg', '28 june', 'timo scheider', 'katherine legge', 'jamie green', 'persson motor... |
2009 isle of man tt | https://en.wikipedia.org/wiki/2009_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21607058-1.html.csv | superlative | cameron donald 1000cc suzuki is the rider that recorded the fastest speed on thursday , june 4th of the 2009 isle of man tt . | {'scope': 'all', 'col_superlative': '6', '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', 'thurs 4 june'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; thurs 4 june }'}, 'rider'], 'result': 'cameron donald 1000cc suzuki', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; thurs 4 june } ; rider }'}, 'camer... | eq { hop { argmin { all_rows ; thurs 4 june } ; rider } ; cameron donald 1000cc suzuki } = true | select the row whose thurs 4 june record of all rows is minimum . the rider record of this row is cameron donald 1000cc suzuki . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'thurs 4 june_5': 5, 'rider_6': 6, 'cameron donald 1000cc suzuki_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'thurs 4 june_5': 'thurs 4 june', 'rider_6': 'rider', 'cameron donald 1000cc suzuki_7': 'cameron donald 1000cc suzuki'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'thurs 4 june_5': [0], 'rider_6': [1], 'cameron donald 1000cc suzuki_7': [2]} | ['rank', 'rider', 'mon 1 june', 'tue 2 june', 'wed 3 june', 'thurs 4 june', 'fri 5 june'] | [['1', 'cameron donald 1000cc suzuki', "18 ' 16.16 123.912 mph", "18 ' 15.21 124.020 mph", "19 ' 31.12 115.981 mph", "17 ' 13.25 131.457 mph", '-- no time'], ['2', 'john mcguinness 1000cc honda', "17 ' 40.60 128.067 mph", "17 ' 27.56 129.661 mph", "17 ' 23.46 130.171 mph", "17 ' 52.90 126.599 mph", '-- no time'], ['3',... |
peruvian segunda división | https://en.wikipedia.org/wiki/Peruvian_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12335018-1.html.csv | unique | deportivo coopsol is the only team in the pervian segunda division to have only 1 top division title . | {'scope': 'all', 'row': '6', 'col': '9', 'col_other': '1', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top division titles', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top division titles record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; top division titles ; 1 }'}], 'result': True, 'ind': 1, 'to... | and { only { filter_eq { all_rows ; top division titles ; 1 } } ; eq { hop { filter_eq { all_rows ; top division titles ; 1 } ; team } ; deportivo coopsol } } = true | select the rows whose top division titles record is equal to 1 . there is only one such row in the table . the team record of this unqiue row is deportivo coopsol . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'top division titles_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'deportivo coopsol_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'top division titles_7': 'top division titles', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'deportivo coopsol_10': 'deportivo coopsol'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'top division titles_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'deportivo coopsol_10': [3]} | ['team', 'city', 'founded', 'first season in segunda división', 'first season of current spell in segunda división', 'stadium', 'capacity', 'field', 'top division titles', 'last top division title'] | [['alfonso ugarte', 'puno', '1928', '2006', '2013', 'enrique torres belón', '20000', 'grass', '0', '-'], ['alianza universidad', 'huánuco', '1939', '2012', '2012', 'heraclio tapia', '15000', 'grass', '0', '-'], ['atlético minero', 'matucana', '1997', '2006', '2009', 'municipal de matucana', '5000', 'grass', '0', '-'], ... |
synchronized swimming at the 2008 summer olympics - women 's duet | https://en.wikipedia.org/wiki/Synchronized_swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_duet | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18789596-2.html.csv | unique | in the women 's duet in sychronized swimming at the 2008 summer olympics , the only athletes from italy were beatrice adelizzi & giulia lapi . | {'scope': 'all', 'row': '7', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'italy', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; country ; italy }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; country ; italy } } ; eq { hop { filter_eq { all_rows ; country ; italy } ; athlete } ; beatrice adelizzi & giulia lapi } } = true | select the rows whose country record fuzzily matches to italy . there is only one such row in the table . the athlete record of this unqiue row is beatrice adelizzi & giulia lapi . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'italy_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'athlete_9': 9, 'beatrice adelizzi & giulia lapi_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'italy_8': 'italy', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'athlete_9': 'athlete', 'beatrice adelizzi & giulia lapi_10': 'beatrice adelizzi & giulia lapi'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'italy_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'athlete_9': [2], 'beatrice adelizzi & giulia lapi_10': [3]} | ['country', 'athlete', 'technical', 'free', 'total'] | [['russia', 'anastasia davydova & anastasiya yermakova', '49.334', '49.917', '99.251'], ['spain', 'andrea fuentes & gemma mengual', '48.834', '49.500', '98.334'], ['japan', 'saho harada & emiko suzuki', '48.250', '48.917', '97.167'], ['china', 'jiang tingting & jiang wenwen', '48.084', '48.250', '96.334'], ['united sta... |
list of tallest buildings in indianapolis | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Indianapolis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14565330-3.html.csv | ordinal | of the tallest buildings in indianapolis , the one with the 2nd highest number of floors is aul tower . | {'row': '4', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'floors', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; floors ; 2 }'}, 'name'], 'result': 'aul tower', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; floors ; 2 } ; name }'}, 'aul tower'], 'resul... | eq { hop { nth_argmax { all_rows ; floors ; 2 } ; name } ; aul tower } = true | select the row whose floors record of all rows is 2nd maximum . the name record of this row is aul tower . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'floors_5': 5, '2_6': 6, 'name_7': 7, 'aul tower_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', 'floors_5': 'floors', '2_6': '2', 'name_7': 'name', 'aul tower_8': 'aul tower'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'floors_5': [0], '2_6': [0], 'name_7': [1], 'aul tower_8': [2]} | ['name', 'street address', 'years as tallest', 'height ft ( m )', 'floors'] | [['indiana statehouse', '04.0 200 west washington street', '1888 - 1962', '255 ( 78 )', '4'], ['city - county building', '07.0 200 east washington street', '1962 - 1970', '372 ( 113 )', '28'], ['one indiana square', '01.0 1 indiana square', '1970 - 1982', '504 ( 154 )', '36'], ['aul tower', '07.0 200 north illinois str... |
2010 southeastern conference football season | https://en.wikipedia.org/wiki/2010_Southeastern_Conference_football_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26842217-6.html.csv | unique | of the 2010 southeastern conference football games played in tennessee , only one had an attendance over 100000 . | {'scope': 'subset', 'row': '7', 'col': '8', 'col_other': 'n/a', 'criterion': 'greater_than', 'value': '100000', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'tennessee'}} | {'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'tennessee'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; home team ; tennessee }', 'tointer': 'select the rows whose home team record fuzzily matches to tennessee .'}, 'attendance', ... | only { filter_greater { filter_eq { all_rows ; home team ; tennessee } ; attendance ; 100000 } } = true | select the rows whose home team record fuzzily matches to tennessee . among these rows , select the rows whose attendance record is greater than 100000 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'home team_5': 5, 'tennessee_6': 6, 'attendance_7': 7, '100000_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'home team_5': 'home team', 'tennessee_6': 'tennessee', 'attendance_7': 'attendance', '100000_8': '100000'} | {'only_2': [3], 'result_3': [], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'home team_5': [0], 'tennessee_6': [0], 'attendance_7': [1], '100000_8': [1]} | ['date', 'time', 'visiting team', 'home team', 'site', 'broadcast', 'result', 'attendance'] | [['september 9', '7:30 pm', '21 auburn', 'mississippi state', 'davis wade stadium starkville , ms', 'espn', 'aub 17 - 14', '54806'], ['september 11', '12:00 pm', '22 georgia', '24 south carolina', 'williams - brice stadium columbia , sc', 'espn', 'usc 17 - 6', '80974'], ['september 11', '12:21 pm', 'south florida', '8 ... |
1989 detroit lions season | https://en.wikipedia.org/wiki/1989_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15916193-2.html.csv | count | in the 1989 detroit lions season , among the games played in december , 3 of them drew more than 10,000 people . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '10000', 'result': '3', 'col': '5', 'subset': {'col': '2', 'criterion': 'greater_than_eq', 'value': 'december 3 , 1989'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'date', 'december 3 , 1989'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; date ; december 3 , 1989 }', 'tointer': 'select the rows whose date record is greater... | eq { count { filter_greater { filter_greater_eq { all_rows ; date ; december 3 , 1989 } ; attendance ; 10000 } } ; 3 } = true | select the rows whose date record is greater than or equal to december 3 , 1989 . among these rows , select the rows whose attendance record is greater than 10000 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'december 3 , 1989_7': 7, 'attendance_8': 8, '10000_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'december 3 , 1989_7': 'december 3 , 1989', 'attendance_8': 'attendance', '10000_9': '10000', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'december 3 , 1989_7': [0], 'attendance_8': [1], '10000_9': [1], '3_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 10 , 1989', 'phoenix cardinals', 'l 16 - 13', '36735'], ['2', 'september 17 , 1989', 'new york giants', 'l 24 - 14', '76021'], ['3', 'september 24 , 1989', 'chicago bears', 'l 47 - 27', '71418'], ['4', 'october 1 , 1989', 'pittsburgh steelers', 'l 23 - 3', '43804'], ['5', 'october 8 , 1989', 'minnesot... |
united states house of representatives elections , 1926 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1926 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342379-10.html.csv | unique | gordon lee was the only georgia incumbent who retired in the 1926 united states house of representatives elections . | {'scope': 'all', 'row': '7', 'col': '5', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'retired', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'retired'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to retired .', 'tostr': 'filter_eq { all_rows ; result ; retired }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; result ; retired } } ; eq { hop { filter_eq { all_rows ; result ; retired } ; incumbent } ; gordon lee } } = true | select the rows whose result record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is gordon lee . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'retired_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'gordon lee_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'retired_8': 'retired', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'gordon lee_10': 'gordon lee'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'retired_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'gordon lee_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['georgia 1', 'charles gordon edwards', 'democratic', '1924', 're - elected', 'charles gordon edwards ( d ) unopposed'], ['georgia 2', 'edward e cox', 'democratic', '1924', 're - elected', 'edward e cox ( d ) unopposed'], ['georgia 3', 'charles r crisp', 'democratic', '1912', 're - elected', 'charles r crisp ( d ) uno... |
shaun micheel | https://en.wikipedia.org/wiki/Shaun_Micheel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551537-3.html.csv | aggregation | shaun micheel had an average of around 3 cuts made in the various pga tournaments . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'cuts made'], 'result': '3', 'ind': 0, 'tostr': 'avg { all_rows ; cuts made }'}, '3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; cuts made } ; 3 } = true', 'tointer': 'the average of the cuts made record of all rows is 3 .'} | round_eq { avg { all_rows ; cuts made } ; 3 } = true | the average of the cuts made record of all rows is 3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'cuts made_4': 4, '3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'cuts made_4': 'cuts made', '3_5': '3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'cuts made_4': [0], '3_5': [1]} | ['tournament', 'wins', 'top - 5', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '0', '1', '5', '1'], ['us open', '0', '0', '1', '7', '3'], ['the open championship', '0', '0', '0', '4', '2'], ['pga championship', '1', '2', '3', '10', '6'], ['totals', '1', '2', '5', '26', '12']] |
1983 world judo championships | https://en.wikipedia.org/wiki/1983_World_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15807776-2.html.csv | count | there were only three nations that were awarded more than two medals in the 1983 world judo championships . | {'scope': 'all', 'criterion': 'greater_than', 'value': '2', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'total', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total record is greater than 2 .', 'tostr': 'filter_greater { all_rows ; total ; 2 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater... | eq { count { filter_greater { all_rows ; total ; 2 } } ; 3 } = true | select the rows whose total record is greater than 2 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'total_5': 'total', '2_6': '2', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], '3_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'japan', '4', '1', '2', '7'], ['2', 'soviet union', '2', '1', '2', '5'], ['3', 'east germany', '2', '0', '2', '4'], ['4', 'italy', '0', '1', '1', '2'], ['4', 'hungary', '0', '1', '1', '2'], ['6', 'france', '0', '1', '0', '1'], ['6', 'czech republic', '0', '1', '0', '1'], ['6', 'great britain', '0', '1', '0', '1'... |
wuji county | https://en.wikipedia.org/wiki/Wuji_County | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12425097-1.html.csv | aggregation | the average area of the towns and townships in wuji county is about 47km squared . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '47', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'area ( km square )'], 'result': '47', 'ind': 0, 'tostr': 'avg { all_rows ; area ( km square ) }'}, '47'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; area ( km square ) } ; 47 } = true', 'tointer': 'the average of the area ( km squa... | round_eq { avg { all_rows ; area ( km square ) } ; 47 } = true | the average of the area ( km square ) record of all rows is 47 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'area (km square)_4': 4, '47_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'area (km square)_4': 'area ( km square )', '47_5': '47'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'area (km square)_4': [0], '47_5': [1]} | ['name', 'hanzi', 'area ( km square )', 'population', 'villages'] | [['wuji town', '无极镇', '57', '76851', '25'], ['qiji town', '七汲镇', '54', '41584', '20'], ['zhangduangu town', '张段固镇', '51', '40916', '20'], ['beisu town', '北苏镇', '54', '54639', '18'], ['guozhuang town', '郭庄镇', '43', '43636', '23'], ['dachen town', '大陈镇', '42', '31297', '13'], ['haozhuang township', '郝庄乡', '55', '37786', ... |
united states house of representatives elections , 1922 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1922 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342426-5.html.csv | comparative | the candidates who took the seats in the 1922 united states house of representatives elections in both district 5 and district 6 of arkansas were placed due to the previous politician retiring . | {'row_1': '5', 'row_2': '6', 'col': '5', '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', 'district', 'arkansas 5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose district record fuzzily matches to arkansas 5 .', 'tostr': 'filter_eq { all_rows ; district ; arkansas 5... | and { eq { hop { filter_eq { all_rows ; district ; arkansas 5 } ; result } ; hop { filter_eq { all_rows ; district ; arkansas 6 } ; result } } ; and { eq { hop { filter_eq { all_rows ; district ; arkansas 5 } ; result } ; retired democratic hold } ; eq { hop { filter_eq { all_rows ; district ; arkansas 6 } ; result } ;... | select the rows whose district record fuzzily matches to arkansas 5 . take the result record of this row . select the rows whose district record fuzzily matches to arkansas 6 . take the result record of this row . the first record fuzzily matches to the second record . the result record of the first row is retired demo... | 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, 'district_11': 11, 'arkansas 5_12': 12, 'result_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'district_15': 15, 'arkansas 6_16': 16, 'result_17': 17, 'and_7': 7, 'str_eq_5': 5, 'retired democratic ho... | {'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', 'district_11': 'district', 'arkansas 5_12': 'arkansas 5', 'result_13': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'distr... | {'and_8': [9], 'result_9': [], 'str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'district_11': [0], 'arkansas 5_12': [0], 'result_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'district_15': [1], 'arkansas 6_16': [1], 'result_17': [3], 'and_7': [8], 'str_eq_... | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'william j driver', 'democratic', '1920', 're - elected', 'william j driver ( d ) unopposed'], ['arkansas 2', 'william a oldfield', 'democratic', '1908', 're - elected', 'william a oldfield ( d ) unopposed'], ['arkansas 3', 'john n tillman', 'democratic', '1914', 're - elected', 'john n tillman ( d ) un... |
thai clubs in the afc cup | https://en.wikipedia.org/wiki/Thai_clubs_in_the_AFC_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16707879-4.html.csv | majority | in the thai clubs in the afc club , most of the games did not have a score of 0:0 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': '0:0', 'subset': None} | {'func': 'most_str_not_eq', 'args': ['all_rows', 'score', '0:0'], 'result': True, 'ind': 0, 'tointer': 'for the score records of all rows , most of them do not match to 0:0 .', 'tostr': 'most_not_eq { all_rows ; score ; 0:0 } = true'} | most_not_eq { all_rows ; score ; 0:0 } = true | for the score records of all rows , most of them do not match to 0:0 . | 1 | 1 | {'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'score_3': 3, '0:0_4': 4} | {'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'score_3': 'score', '0:0_4': '0:0'} | {'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'score_3': [0], '0:0_4': [0]} | ['season', 'team 1', 'score', 'team 2', 'venue'] | [['2010', 'south china', '0:0', 'muangthong united', 'hong kong stadium , hong kong'], ['2010', 'muangthong united', '3:1', 'vb sports club', 'yamaha stadium ( thailand )'], ['2010', 'muangthong united', '4:1', 'persiwa wamena', 'yamaha stadium ( thailand )'], ['2010', 'vb sports club', '2:3', 'muangthong united', 'nat... |
1977 - 78 new york rangers season | https://en.wikipedia.org/wiki/1977%E2%80%9378_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17310913-3.html.csv | superlative | in november 1977 , the new york rangers ' highest score was 8 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'score'], 'result': '8 - 4', 'ind': 0, 'tostr': 'max { all_rows ; score }', 'tointer': 'the maximum score record of all rows is 8 - 4 .'}, '8 - 4'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; score } ; 8 - 4 } = true', 'tointer': 'the maximum s... | eq { max { all_rows ; score } ; 8 - 4 } = true | the maximum score record of all rows is 8 - 4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'score_4': 4, '8 - 4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'score_4': 'score', '8 - 4_5': '8 - 4'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'score_4': [0], '8 - 4_5': [1]} | ['game', 'november', 'opponent', 'score', 'record'] | [['11', '2', 'colorado rockies', '6 - 2', '4 - 6 - 1'], ['12', '4', 'vancouver canucks', '5 - 1', '5 - 6 - 1'], ['13', '5', 'los angeles kings', '3 - 1', '5 - 7 - 1'], ['14', '9', 'buffalo sabres', '8 - 4', '6 - 7 - 1'], ['15', '12', 'detroit red wings', '3 - 1', '6 - 8 - 1'], ['16', '13', 'atlanta flames', '5 - 2', '6... |
mars hill network | https://en.wikipedia.org/wiki/Mars_Hill_Network | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12454334-1.html.csv | unique | wmhr is the only mars hill network radio station licensed in the city of syracuse . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'syracuse , ny', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city of license', 'syracuse , ny'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city of license record fuzzily matches to syracuse , ny .', 'tostr': 'filter_eq { all_rows ; city of license ; syracuse , ny ... | and { only { filter_eq { all_rows ; city of license ; syracuse , ny } } ; eq { hop { filter_eq { all_rows ; city of license ; syracuse , ny } ; call sign } ; wmhr } } = true | select the rows whose city of license record fuzzily matches to syracuse , ny . there is only one such row in the table . the call sign record of this unqiue row is wmhr . | 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, 'syracuse , ny_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'call sign_9': 9, 'wmhr_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', 'syracuse , ny_8': 'syracuse , ny', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'call sign_9': 'call sign', 'wmhr_10': 'wmhr'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'city of license_7': [0], 'syracuse , ny_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'call sign_9': [2], 'wmhr_10': [3]} | ['call sign', 'frequency', 'city of license', 'facility id', 'erp / power w', 'height m ( ft )', 'class'] | [['wmhi', '94.7 fm', 'cape vincent , ny', '40435', '5800', '-', 'a'], ['wmhn', '89.3 fm', 'webster , ny', '40430', '1000', '-', 'a'], ['wmhq', '90.1 fm', 'malone , ny', '89863', '2700', '-', 'a'], ['wmhr', '102.9 fm', 'syracuse , ny', '40432', '20000', '-', 'b'], ['wmhu', '91.1 fm', 'cold brook , ny', '174468', '560', ... |
list of the largest trading partners of india | https://en.wikipedia.org/wiki/List_of_the_largest_trading_partners_of_India | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26160007-1.html.csv | superlative | the largest trading partner of india with the highest amount of imports is china . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '2', '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', 'imports'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; imports }'}, 'country'], 'result': 'china', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; imports } ; country }'}, 'china'], 'result': True, 'ind': 2, 'tos... | eq { hop { argmax { all_rows ; imports } ; country } ; china } = true | select the row whose imports record of all rows is maximum . the country record of this row is china . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'imports_5': 5, 'country_6': 6, 'china_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'imports_5': 'imports', 'country_6': 'country', 'china_7': 'china'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'imports_5': [0], 'country_6': [1], 'china_7': [2]} | ['country', 'exports', 'imports', 'total trade', 'trade balance'] | [['united arab emirates', '36265.15', '38436.47', '74701.61', '- 2171.32'], ['china', '13503.00', '54324.04', '67827.04', '- 40821.04'], ['united states', '36152.30', '24343.73', '60496.03', '11808.57'], ['saudi arabia', '9783.81', '34130.50', '43914.31', '- 24346.69'], ['switzerland', '1116.98', '29915.78', '31032.76'... |
telecommunications in moldova | https://en.wikipedia.org/wiki/Telecommunications_in_Moldova | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19246-1.html.csv | superlative | for telecommunicatoins in moldova , the largest connection speed by an orange carrier was 236.8 kbit / s. | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'orange'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'carrier', 'orange'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; carrier ; orange }', 'tointer': 'select the rows whose carrier record fuzzily matches to orange .'}, 'connection speed'], 'result': '236.8 kbit... | eq { max { filter_eq { all_rows ; carrier ; orange } ; connection speed } ; 236.8 kbit / s } = true | select the rows whose carrier record fuzzily matches to orange . the maximum connection speed record of these rows is 236.8 kbit / s . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'carrier_5': 5, 'orange_6': 6, 'connection speed_7': 7, '236.8 kbit / s_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'carrier_5': 'carrier', 'orange_6': 'orange', 'connection speed_7': 'connection speed', '236.8 kbit / s_8': '236.8 kbit / s'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'carrier_5': [0], 'orange_6': [0], 'connection speed_7': [1], '236.8 kbit / s_8': [2]} | ['carrier', 'standard', 'frequency', 'connection speed', 'launch date ( ddmmyyyy )'] | [['orange', 'gsm gprs', '900 mhz and 1800 mhz', '56 kbit / s', '14.09.2005'], ['orange', 'gsm edge', '900 mhz and 1800 mhz', '236.8 kbit / s', '17.04.2006'], ['moldcell', 'gsm gprs', '900 mhz and 1800 mhz', '56 kbit / s', '31.01.2005'], ['moldcell', 'gsm edge', '900 mhz and 1800 mhz', '236.8 kbit / s', '07.06.2005'], [... |
ingo schultz | https://en.wikipedia.org/wiki/Ingo_Schultz | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15186827-1.html.csv | unique | ingo schultz placed first one time in the 2002 european championships in the 400 meter dash . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '2,5', 'criterion': 'equal', 'value': '1st', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '1st'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 1st .', 'tostr': 'filter_eq { all_rows ; result ; 1st }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_e... | and { only { filter_eq { all_rows ; result ; 1st } } ; and { eq { hop { filter_eq { all_rows ; result ; 1st } ; tournament } ; european championships } ; eq { hop { filter_eq { all_rows ; result ; 1st } ; extra } ; 400 m } } } = true | select the rows whose result record fuzzily matches to 1st . there is only one such row in the table . the tournament record of this unqiue row is european championships . the extra record of this unqiue row is 400 m . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'result_10': 10, '1st_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_12': 12, 'european championships_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'extra_14': 14, '400 m_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'result_10': 'result', '1st_11': '1st', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_12': 'tournament', 'european championships_13': 'european championships', 'str_eq_5': 'st... | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'result_10': [0], '1st_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'tournament_12': [2], 'european championships_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'extra_14': [4], '400 m_15': [5]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['2000', 'european indoor championships', 'ghent , belgium', '2nd', '4x400 m relay'], ['2001', 'world championships', 'edmonton , canada', '2nd', '400 m'], ['2002', 'european championships', 'munich , germany', '1st', '400 m'], ['2002', 'european championships', 'munich , germany', '7th', '4x400 m relay'], ['2002', 'w... |
günter netzer | https://en.wikipedia.org/wiki/G%C3%BCnter_Netzer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1085623-1.html.csv | comparative | günter netzer scored a goal in athens , greece earlier than he did in oslo , norway . | {'row_1': '1', 'row_2': '3', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'athens , greece'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to athens , greece .', 'tostr': 'filter_eq { all_rows ; venue ; athens , greece }'}, 'date'], 'resul... | less { hop { filter_eq { all_rows ; venue ; athens , greece } ; date } ; hop { filter_eq { all_rows ; venue ; oslo , norway } ; date } } = true | select the rows whose venue record fuzzily matches to athens , greece . take the date record of this row . select the rows whose venue record fuzzily matches to oslo , norway . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'athens , greece_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'oslo , norway_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'athens , greece_8': 'athens , greece', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'oslo , n... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'athens , greece_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'oslo , norway_12': [1], 'date_13': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['22 november 1970', 'athens , greece', '1 - 0', '3 - 1', 'friendly'], ['12 june 1971', 'karlsruhe , germany', '1 - 0', '2 - 0', 'uefa euro 1972 qualifying'], ['22 june 1971', 'oslo , norway', '7 - 0', '7 - 1', 'friendly'], ['8 september 1971', 'hanover , germany', '4 - 0', '5 - 0', 'friendly'], ['29 april 1972', 'lon... |
liselotte neumann | https://en.wikipedia.org/wiki/Liselotte_Neumann | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1710991-1.html.csv | unique | the us women 's open was the only tournament in which liselotte neumann had a winning score of -7 . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': '- 7', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning score', '- 7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning score record fuzzily matches to - 7 .', 'tostr': 'filter_eq { all_rows ; winning score ; - 7 }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; winning score ; - 7 } } ; eq { hop { filter_eq { all_rows ; winning score ; - 7 } ; tournament } ; us women 's open } } = true | select the rows whose winning score record fuzzily matches to - 7 . there is only one such row in the table . the tournament record of this unqiue row is us women 's open . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'winning score_7': 7, '- 7_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, "us women 's open_10": 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'winning score_7': 'winning score', '- 7_8': '- 7', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', "us women 's open_10": "us women 's open"} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'winning score_7': [0], '- 7_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], "us women 's open_10": [3]} | ['date', 'tournament', 'winning score', 'margin of victory', 'runner ( s ) - up'] | [['7 sep 1988', "us women 's open", '- 7 ( 67 + 72 + 69 + 69 = 277 )', '3 strokes', 'patty sheehan'], ['10 nov 1991', 'mazda japan classic', '- 5 ( 70 + 72 + 69 = 211 )', '2 strokes', 'caroline keggi , dottie pepper'], ['12 jun 1994', 'minnesota lpga classic', '- 11 ( 68 + 71 + 66 = 205 )', '2 strokes', 'hiromi kobayas... |
2010 - 11 oklahoma city thunder season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Oklahoma_City_Thunder_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27712702-11.html.csv | unique | in the 2010 - 11 oklahoma city thunder season , the only game where the venue was fedex forum , was march 7th . | {'scope': 'all', 'row': '4', 'col': '8', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'fedexforum', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'fedexforum'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to fedexforum .', 'tostr': 'filter_eq { all_rows ; location attendance ; fedexfor... | and { only { filter_eq { all_rows ; location attendance ; fedexforum } } ; eq { hop { filter_eq { all_rows ; location attendance ; fedexforum } ; date } ; march 7 } } = true | select the rows whose location attendance record fuzzily matches to fedexforum . there is only one such row in the table . the date record of this unqiue row is march 7 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location attendance_7': 7, 'fedexforum_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'march 7_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location attendance_7': 'location attendance', 'fedexforum_8': 'fedexforum', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'march 7_10': 'march 7'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location attendance_7': [0], 'fedexforum_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'march 7_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 2', 'indiana', 'w 113 - 89 ( ot )', 'kevin durant , russell westbrook ( 21 )', 'serge ibaka ( 12 )', 'russell westbrook ( 9 )', 'oklahoma city arena 18203', '37 - 22'], ['60', 'march 4', 'atlanta', 'w 111 - 104 ( ot )', 'kevin durant ( 29 )', 'kevin durant ( 8 )', 'russell westbrook ( 9 )', 'philips aren... |
chiefs - raiders rivalry | https://en.wikipedia.org/wiki/Chiefs%E2%80%93Raiders_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11840325-4.html.csv | aggregation | the chiefs scored 59 points against the raiders in the 1979 season . | {'scope': 'subset', 'col': '4', 'type': 'sum', 'result': '59', 'subset': {'col': '1', 'criterion': 'equal', 'value': '1979'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'year', '1979'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 1979 }', 'tointer': 'select the rows whose year record is equal to 1979 .'}, 'result'], 'result': '59', 'ind': 1, 'tostr': 'sum { filter_eq... | round_eq { sum { filter_eq { all_rows ; year ; 1979 } ; result } ; 59 } = true | select the rows whose year record is equal to 1979 . the sum of the result record of these rows is 59 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'year_5': 5, '1979_6': 6, 'result_7': 7, '59_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'year_5': 'year', '1979_6': '1979', 'result_7': 'result', '59_8': '59'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'year_5': [0], '1979_6': [0], 'result_7': [1], '59_8': [2]} | ['year', 'date', 'winner', 'result', 'loser', 'location'] | [['1970', 'november 1', 'kansas city chiefs', '17 - 17', 'oakland raiders', 'municipal stadium'], ['1970', 'december 12', 'oakland raiders', '20 - 6', 'kansas city chiefs', 'oakland - alameda county coliseum'], ['1971', 'october 31', 'kansas city chiefs', '20 - 20', 'oakland raiders', 'oakland - alameda county coliseum... |
list of reality television show franchises | https://en.wikipedia.org/wiki/List_of_reality_television_show_franchises | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24224647-2.html.csv | comparative | among clash of the choirs franchisees , det store korslaget premiered after körslaget . | {'row_1': '8', 'row_2': '12', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'local name', 'det store korslaget'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose local name record fuzzily matches to det store korslaget .', 'tostr': 'filter_eq { all_rows ; local name ; det store ... | greater { hop { filter_eq { all_rows ; local name ; det store korslaget } ; year premiered } ; hop { filter_eq { all_rows ; local name ; körslaget } ; year premiered } } = true | select the rows whose local name record fuzzily matches to det store korslaget . take the year premiered record of this row . select the rows whose local name record fuzzily matches to körslaget . take the year premiered 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, 'local name_7': 7, 'det store korslaget_8': 8, 'year premiered_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'local name_11': 11, 'körslaget_12': 12, 'year premiered_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', 'local name_7': 'local name', 'det store korslaget_8': 'det store korslaget', 'year premiered_9': 'year premiered', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10'... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'local name_7': [0], 'det store korslaget_8': [0], 'year premiered_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'local name_11': [1], 'körslaget_12': [1], 'year premiered_13': [3]} | ['region / country', 'local name', 'main presenter', 'network', 'year premiered'] | [['china', '夢想合唱團 mengxiang hechang tuan', 'sa beining', 'cctv - 1', '2011'], ['denmark', 'allstars', 'lisbeth østergaard', 'tv2', '2008'], ['estonia', 'laululahing', 'tarmo leinatamm', 'etv', '2008'], ['finland', 'kuorosota', 'kristiina komulainen', 'nelonen', '2009'], ['france', 'la bataille des chorales', 'benjamin ... |
india national under - 23 football team results | https://en.wikipedia.org/wiki/India_national_under-23_football_team_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25428629-1.html.csv | count | 2 india national under-23 football team game locations occurred in india . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'india', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'india'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to india .', 'tostr': 'filter_eq { all_rows ; location ; india }'}], 'result': '2', 'ind': 1, 'tostr': 'coun... | eq { count { filter_eq { all_rows ; location ; india } } ; 2 } = true | select the rows whose location record fuzzily matches to india . 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, 'location_5': 5, 'india_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', 'location_5': 'location', 'india_6': 'india', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'india_6': [0], '2_7': [2]} | ['date', 'tournament', 'location', 'opponent', 'stadium', 'score', 'indian scorers'] | [['23 february 2011', '2012 olympic qualifier', 'pune , india', 'myanmar', 'balewadi sports complex', '2 - 1', 'jeje lalpekhlua , malsawmfela'], ['9 march 2011', '2012 olympic qualifier', 'yangon , myanmar', 'myanmar', 'thuwunna stadium', '1 - 1', 'chinadorai sabeeth'], ['19 june 2011', '2012 olympic qualifier', 'doha ... |
2005 st. louis cardinals season | https://en.wikipedia.org/wiki/2005_St._Louis_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11195757-1.html.csv | count | in the 2005 st. louis cardinals season , among the games played after april 8 , 2 of them drew more than 35,000 people . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '35000', 'result': '2', 'col': '5', 'subset': {'col': '1', 'criterion': 'greater_than', 'value': 'april 8'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'date', 'april 8'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; date ; april 8 }', 'tointer': 'select the rows whose date record is greater than april 8 .'}, 'attend... | eq { count { filter_greater { filter_greater { all_rows ; date ; april 8 } ; attendance ; 35000 } } ; 2 } = true | select the rows whose date record is greater than april 8 . among these rows , select the rows whose attendance record is greater than 35000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'date_6': 6, 'april 8_7': 7, 'attendance_8': 8, '35000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'date_6': 'date', 'april 8_7': 'april 8', 'attendance_8': 'attendance', '35000_9': '35000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'date_6': [0], 'april 8_7': [0], 'attendance_8': [1], '35000_9': [1], '2_10': [3]} | ['date', 'opponent', 'score', 'loss', 'attendance', 'record'] | [['april 5', 'astros 6:05 pm', '7 - 3', 'oswalt ( 0 - 1 )', '43567', '1 - 0'], ['april 6', 'astros 4:05 pm', '4 - 1', 'tavárez ( 0 - 1 )', '28496', '1 - 1'], ['april 8', 'phillies 1:15 pm', '6 - 5', 'madson ( 0 - 1 )', '50074', '2 - 1'], ['april 9', 'phillies 1:15 pm', '10 - 4', 'suppan ( 0 - 1 )', '39242', '2 - 2'], [... |
carlos kirmayr | https://en.wikipedia.org/wiki/Carlos_Kirmayr | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17262467-1.html.csv | majority | carlos kirmayr played on clay in most of the tournaments that he participated in . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , all of them fuzzily match to clay .', 'tostr': 'all_eq { all_rows ; surface ; clay } = true'} | all_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , all of them fuzzily match to clay . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '1976', 'santiago , chile', 'clay', 'josé higueras', '7 - 5 , 4 - 6 , 4 - 6'], ['runner - up', '1979', 'cairo , egypt', 'clay', 'peter feigl', '5 - 7 , 6 - 3 , 1 - 6'], ['runner - up', '1980', 'bogotá , colombia', 'clay', 'dominique bedel', '4 - 6 , 6 - 7'], ['runner - up', '1981', 'forest hills , us',... |
1981 vfl season | https://en.wikipedia.org/wiki/1981_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-1.html.csv | superlative | the largest crowd occurred when the venue was vfl park . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'vfl park', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'vfl park'], 'result': True, 'ind': 2, 'tostr':... | eq { hop { argmax { all_rows ; crowd } ; venue } ; vfl park } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is vfl park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'vfl park_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'vfl park_7': 'vfl park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'vfl park_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '21.19 ( 145 )', 'south melbourne', '12.25 ( 97 )', 'arden street oval', '19437', '28 march 1981'], ['footscray', '16.12 ( 108 )', 'st kilda', '23.19 ( 157 )', 'western oval', '19101', '28 march 1981'], ['melbourne', '16.16 ( 112 )', 'hawthorn', '23.15 ( 153 )', 'mcg', '32202', '28 march 1981'], ['... |
1945 - 46 huddersfield town f.c. season | https://en.wikipedia.org/wiki/1945%E2%80%9346_Huddersfield_Town_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19730892-1.html.csv | count | 12 players are listed as members of the huddersfield town f.c. during the 1945 - 46 season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '12', 'col': '1', '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': '12', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; name } }', 'to... | eq { count { filter_all { all_rows ; name } } ; 12 } = true | select the rows whose name record is arbitrary . the number of such rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'name_5': 5, '12_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'name_5': 'name', '12_6': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'name_5': [0], '12_6': [2]} | ['name', 'nation', 'position', 'fa cup apps', 'fa cup goals', 'total apps', 'total goals'] | [['graham bailey', 'england', 'df', '2', '0', '2', '0'], ['jeff barker', 'england', 'df', '2', '0', '2', '0'], ['albert bateman', 'england', 'mf', '2', '0', '2', '0'], ['eddie carr', 'england', 'mf', '1', '0', '1', '0'], ['don clegg', 'england', 'gk', '2', '0', '2', '0'], ['jimmy glazzard', 'england', 'fw', '2', '0', '... |
1968 san francisco 49ers season | https://en.wikipedia.org/wiki/1968_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17407008-2.html.csv | count | when the 49ers won during the 1968 season , the attendance exceeded 40000 four times . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '40000', 'result': '4', 'col': '5', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'w'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; w }', 'tointer': 'select the rows whose result record fuzzily matches to w .'}, 'attendance', '40000']... | eq { count { filter_greater { filter_eq { all_rows ; result ; w } ; attendance ; 40000 } } ; 4 } = true | select the rows whose result record fuzzily matches to w . among these rows , select the rows whose attendance record is greater than 40000 . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'result_6': 6, 'w_7': 7, 'attendance_8': 8, '40000_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'result_6': 'result', 'w_7': 'w', 'attendance_8': 'attendance', '40000_9': '40000', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'result_6': [0], 'w_7': [0], 'attendance_8': [1], '40000_9': [1], '4_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 15 , 1968', 'baltimore colts', 'l 27 - 10', '56864'], ['2', 'september 22 , 1968', 'st louis cardinals', 'w 35 - 17', '27557'], ['3', 'september 29 , 1968', 'atlanta falcons', 'w 28 - 13', '27477'], ['4', 'october 6 , 1968', 'los angeles rams', 'l 24 - 10', '69520'], ['5', 'october 13 , 1968', 'baltim... |
sports in st. louis | https://en.wikipedia.org/wiki/Sports_in_St._Louis | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21564794-3.html.csv | superlative | the st. louis stars won the highest number of championships of former st. louis sports teams . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'championships in st louis'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; championships in st louis }'}, 'team'], 'result': 'st louis stars', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; championships in st lou... | eq { hop { argmax { all_rows ; championships in st louis } ; team } ; st louis stars } = true | select the row whose championships in st louis record of all rows is maximum . the team record of this row is st louis stars . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'championships in st louis_5': 5, 'team_6': 6, 'st louis stars_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'championships in st louis_5': 'championships in st louis', 'team_6': 'team', 'st louis stars_7': 'st louis stars'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'championships in st louis_5': [0], 'team_6': [1], 'st louis stars_7': [2]} | ['team', 'sport', 'league', 'established', 'began in st louis', 'venue', 'championships in st louis', 'left st louis'] | [['st louis stampede', 'arena football', 'arena football league', '1987', '1994', 'scottrade center', '0', '1995'], ['st louis browns', 'baseball', 'american league', '1894', '1902', "sportsman 's park", '0', '1954'], ['st louis stars', 'baseball', 'negro american league', '1937', '1939', 'stars park', '0', '1939'], ['... |
1959 cleveland browns season | https://en.wikipedia.org/wiki/1959_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10651674-1.html.csv | count | among the 1959 cleveland brown 's games in september , 2 of them had an attendance of more than 30000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '30000', 'result': '2', 'col': '5', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'september'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'september'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; september }', 'tointer': 'select the rows whose date record fuzzily matches to september .'}, 'att... | eq { count { filter_greater { filter_eq { all_rows ; date ; september } ; attendance ; 30000 } } ; 2 } = true | select the rows whose date record fuzzily matches to september . among these rows , select the rows whose attendance record is greater than 30000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'september_7': 7, 'attendance_8': 8, '30000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'september_7': 'september', 'attendance_8': 'attendance', '30000_9': '30000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'september_7': [0], 'attendance_8': [1], '30000_9': [1], '2_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 12 , 1959', 'pittsburgh steelers', 'l 34 - 20', '27432'], ['2', 'august 22 , 1959', 'detroit lions at akron', 'l 9 - 3', '22654'], ['3', 'august 30 , 1959', 'san francisco 49ers', 'l 17 - 14', '24737'], ['4', 'september 5 , 1959', 'los angeles rams', 'w 27 - 24', '55883'], ['5', 'september 13 , 1959', 'd... |
mark calcavecchia | https://en.wikipedia.org/wiki/Mark_Calcavecchia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1544297-7.html.csv | comparative | mark calcavecchia had more top 10 finishes in the masters tournament than in the us open . | {'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'masters tournament'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to masters tournament .', 'tostr': 'filter_eq { all_rows ; tournament ; masters tour... | greater { hop { filter_eq { all_rows ; tournament ; masters tournament } ; top - 5 } ; hop { filter_eq { all_rows ; tournament ; us open } ; top - 5 } } = true | select the rows whose tournament record fuzzily matches to masters tournament . take the top - 5 record of this row . select the rows whose tournament record fuzzily matches to us open . take the top - 5 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, 'tournament_7': 7, 'masters tournament_8': 8, 'top - 5_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'us open_12': 12, 'top - 5_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', 'tournament_7': 'tournament', 'masters tournament_8': 'masters tournament', 'top - 5_9': 'top - 5', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 't... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'masters tournament_8': [0], 'top - 5_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'us open_12': [1], 'top - 5_13': [3]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '2', '2', '10', '18', '13'], ['us open', '0', '0', '0', '6', '20', '10'], ['the open championship', '1', '1', '3', '9', '27', '19'], ['pga championship', '0', '1', '2', '4', '21', '14'], ['totals', '1', '4', '7', '29', '86', '56']] |
2007 open championship | https://en.wikipedia.org/wiki/2007_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12278571-4.html.csv | aggregation | in the 2007 open championship , athletes from the united states had an average score of 68.67 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '68.67', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'round_eq', 'args': [{'func': 'avg', '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'], 'resu... | round_eq { avg { filter_eq { all_rows ; country ; united states } ; score } ; 68.67 } = true | select the rows whose country record fuzzily matches to united states . the average of the score record of these rows is 68.67 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, 'score_7': 7, '68.67_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', 'score_7': 'score', '68.67_8': '68.67'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], 'score_7': [1], '68.67_8': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'sergio garcía', 'spain', '65', '- 6'], ['2', 'paul mcginley', 'ireland', '67', '- 4'], ['t3', 'markus brier', 'austria', '68', '- 3'], ['t3', 'ángel cabrera', 'argentina', '68', '- 3'], ['t3', 'michael campbell', 'new zealand', '68', '- 3'], ['t3', 'rory mcilroy ( a )', 'northern ireland', '68', '- 3'], ['t3', ... |
real salt lake | https://en.wikipedia.org/wiki/Real_Salt_Lake | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1053453-2.html.csv | aggregation | for real salt lake the total goals in which the nation was usa was 74 . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '74', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'usa'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'usa'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; nation ; usa }', 'tointer': 'select the rows whose nation record fuzzily matches to usa .'}, 'goals'], 'result': '74', 'ind': 1, 'tostr': 'su... | round_eq { sum { filter_eq { all_rows ; nation ; usa } ; goals } ; 74 } = true | select the rows whose nation record fuzzily matches to usa . the sum of the goals record of these rows is 74 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'nation_5': 5, 'usa_6': 6, 'goals_7': 7, '74_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'nation_5': 'nation', 'usa_6': 'usa', 'goals_7': 'goals', '74_8': '74'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nation_5': [0], 'usa_6': [0], 'goals_7': [1], '74_8': [2]} | ['rank', 'player', 'nation', 'games', 'goals', 'years'] | [['1', 'nick rimando', 'usa', '201', '0', '2007 - present'], ['2', 'andy williams', 'jam', '189', '14', '2005 - 2011'], ['3', 'kyle beckerman', 'usa', '177', '21', '2007 - present'], ['4', 'chris wingert', 'usa', '174', '1', '2007 - present'], ['5', 'nat borchers', 'usa', '173', '9', '2008 - present'], ['6', 'javier mo... |
sport in saint petersburg | https://en.wikipedia.org/wiki/Sport_in_Saint_Petersburg | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12978801-1.html.csv | unique | spartak st petersburg is the only basketball venue in saint petersburg . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'basketball', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'sport', 'basketball'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose sport record fuzzily matches to basketball .', 'tostr': 'filter_eq { all_rows ; sport ; basketball }'}], 'result': True, 'ind': 1, 'tostr'... | and { only { filter_eq { all_rows ; sport ; basketball } } ; eq { hop { filter_eq { all_rows ; sport ; basketball } ; club } ; spartak st petersburg } } = true | select the rows whose sport record fuzzily matches to basketball . there is only one such row in the table . the club record of this unqiue row is spartak st petersburg . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'sport_7': 7, 'basketball_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'spartak st petersburg_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'sport_7': 'sport', 'basketball_8': 'basketball', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'spartak st petersburg_10': 'spartak st petersburg'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'sport_7': [0], 'basketball_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'spartak st petersburg_10': [3]} | ['club', 'league', 'sport', 'venue', 'established'] | [['zenit st petersburg', 'rfpl', 'football', 'petrovsky stadium', '1926'], ['spartak st petersburg', 'pbl', 'basketball', 'yubileyny sports palace', '1935'], ['avtomobilist st petesburg', 'vsl', 'volleyball', 'platonov volleyball academy', '1935'], ['ska st petersburg', 'khl', 'ice hockey', 'ice palace', '1946'], ['pol... |
1994 miami dolphins season | https://en.wikipedia.org/wiki/1994_Miami_Dolphins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16023821-1.html.csv | superlative | the miami dolphins ' game on october 9 had the most attendance of their 1994 season . | {'scope': 'all', 'col_superlative': '6', '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': 'october 9 , 1994', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'october 9 , 1994'], 'resu... | eq { hop { argmax { all_rows ; attendance } ; date } ; october 9 , 1994 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is october 9 , 1994 . | 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, 'october 9 , 1994_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', 'october 9 , 1994_7': 'october 9 , 1994'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], 'october 9 , 1994_7': [2]} | ['week', 'date', 'opponent', 'result', 'tv time', 'attendance'] | [['1', 'september 4 , 1994', 'new england patriots', 'w 39 - 35', 'nbc 4:15 pm', '71023'], ['2', 'september 11 , 1994', 'green bay packers', 'w 24 - 14', 'nbc 1:00 pm', '55011'], ['3', 'september 18 , 1994', 'new york jets', 'w 28 - 14', 'nbc 1:00 pm', '68977'], ['4', 'september 25 , 1994', 'minnesota vikings', 'l 38 -... |
1961 ohio state buckeyes football team | https://en.wikipedia.org/wiki/1961_Ohio_State_Buckeyes_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17814506-1.html.csv | aggregation | the average rank for the 1961 ohio state buckeyes football team was 4.89 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '4.89', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'rank'], 'result': '4.89', 'ind': 0, 'tostr': 'avg { all_rows ; rank }'}, '4.89'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; rank } ; 4.89 } = true', 'tointer': 'the average of the rank record of all rows is 4.89 .'} | round_eq { avg { all_rows ; rank } ; 4.89 } = true | the average of the rank record of all rows is 4.89 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'rank_4': 4, '4.89_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'rank_4': 'rank', '4.89_5': '4.89'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'rank_4': [0], '4.89_5': [1]} | ['date', 'opponent', 'rank', 'site', 'result', 'attendance'] | [['september 30', 'texas christian', '3', 'ohio stadium columbus , oh', 't7 - 7', '82878'], ['october 7', 'ucla', '8', 'ohio stadium columbus , oh', 'w13 - 3', '82992'], ['october 14', 'illinois', '7', 'ohio stadium columbus , oh', 'w44 - 0', '82374'], ['october 21', 'northwestern', '7', 'dyche stadium evanston , il', ... |
1969 cleveland browns season | https://en.wikipedia.org/wiki/1969_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652161-2.html.csv | aggregation | the average attendance in the 1969 browns season was around 50000-53000 fans . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '50000-53000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '50000-53000', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '50000-53000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 50000-53000 } = true', 'tointer': 'the average of the attendance ... | round_eq { avg { all_rows ; attendance } ; 50000-53000 } = true | the average of the attendance record of all rows is 50000-53000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '50000-53000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '50000-53000_5': '50000-53000'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '50000-53000_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 10 , 1969', 'san francisco 49ers at seattle', 'w 24 - 19', '32219'], ['2', 'august 16 , 1969', 'los angeles rams', 'w 10 - 3', '54937'], ['3', 'august 23 , 1969', 'san diego chargers', 't 19 - 19', '36005'], ['4', 'august 30 , 1969', 'green bay packers', 'l 27 - 17', '85532'], ['5', 'september 6 , 1969',... |
1996 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1996_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162199-5.html.csv | ordinal | steve jones had the second lowest score value in the 1996 u.s. open golf tournament . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'score', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; score ; 2 }'}, 'player'], 'result': 'steve jones', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; score ; 2 } ; player }'}, 'steve jones'], '... | eq { hop { nth_argmin { all_rows ; score ; 2 } ; player } ; steve jones } = true | select the row whose score record of all rows is 2nd minimum . the player record of this row is steve jones . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'score_5': 5, '2_6': 6, 'player_7': 7, 'steve jones_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', 'score_5': 'score', '2_6': '2', 'player_7': 'player', 'steve jones_8': 'steve jones'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'score_5': [0], '2_6': [0], 'player_7': [1], 'steve jones_8': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'tom lehman', 'united states', '71 + 72 + 65 = 208', '- 2'], ['2', 'steve jones', 'united states', '74 + 66 + 69 = 209', '- 1'], ['t3', 'davis love iii', 'united states', '71 + 69 + 70 = 210', 'e'], ['t3', 'john morse', 'united states', '68 + 74 + 68 = 210', 'e'], ['t3', 'frank nobilo', 'new zealand', '69 + 71 +... |
spaceport | https://en.wikipedia.org/wiki/Spaceport | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-179174-2.html.csv | aggregation | in the list of spaceport and flights the total orbital launches from baikonur cosmodrome , kazakhstan is 123 . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '123', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'baikonur cosmodrome , kazakhstan'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'spaceport', 'baikonur cosmodrome , kazakhstan'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; spaceport ; baikonur cosmodrome , kazakhstan }', 'tointer': 'select the rows whose spaceport record fuzzily m... | round_eq { sum { filter_eq { all_rows ; spaceport ; baikonur cosmodrome , kazakhstan } ; flights } ; 123 } = true | select the rows whose spaceport record fuzzily matches to baikonur cosmodrome , kazakhstan . the sum of the flights record of these rows is 123 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'spaceport_5': 5, 'baikonur cosmodrome , kazakhstan_6': 6, 'flights_7': 7, '123_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'spaceport_5': 'spaceport', 'baikonur cosmodrome , kazakhstan_6': 'baikonur cosmodrome , kazakhstan', 'flights_7': 'flights', '123_8': '123'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'spaceport_5': [0], 'baikonur cosmodrome , kazakhstan_6': [0], 'flights_7': [1], '123_8': [2]} | ['spaceport', 'launch complex', 'launcher', 'spacecraft', 'flights', 'years'] | [['baikonur cosmodrome , kazakhstan', 'site 1', 'vostok ( r )', 'vostok 1 - 6', '6 orbital', '1961 - 1963'], ['baikonur cosmodrome , kazakhstan', 'site 1', 'voskhod ( r )', 'voskhod 1 - 2', '2 orbital', '1964 - 1965'], ['baikonur cosmodrome , kazakhstan', 'site 1 , 31', 'soyuz ( r )', 'soyuz 1 - 40', '37 orbital', '196... |
1970 - 71 coupe de france | https://en.wikipedia.org/wiki/1970%E2%80%9371_Coupe_de_France | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16305580-2.html.csv | count | a total of three games in the 1970 - 71 coupe de france 1st round endded with a score of 2 - 0 . | {'scope': 'all', 'criterion': 'equal', 'value': '2 - 0', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st round', '2 - 0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 1st round record fuzzily matches to 2 - 0 .', 'tostr': 'filter_eq { all_rows ; 1st round ; 2 - 0 }'}], 'result': '3', 'ind': 1, 'tostr': 'c... | eq { count { filter_eq { all_rows ; 1st round ; 2 - 0 } } ; 3 } = true | select the rows whose 1st round record fuzzily matches to 2 - 0 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, '1st round_5': 5, '2 - 0_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', '1st round_5': '1st round', '2 - 0_6': '2 - 0', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], '1st round_5': [0], '2 - 0_6': [0], '3_7': [2]} | ['team 1', 'score', 'team 2', '1st round', '2nd round'] | [['girondins de bordeaux ( d1 )', '3 - 2', 'as nancy ( d1 )', '2 - 0', '1 - 2'], ['fc sochaux - montbéliard ( d1 )', '3 - 1', 'fc nantes ( d1 )', '2 - 0', '1 - 1'], ['olympique de marseille ( d1 )', '2 - 0', 'red star ( d1 )', '1 - 0', '1 - 0'], ['as saint - étienne ( d1 )', '2 - 3', 'olympique lyonnais ( d1 )', '2 - 0... |
gold coast titans | https://en.wikipedia.org/wiki/Gold_Coast_Titans | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1613020-1.html.csv | unique | the 2013 nrl season was the only competition that the gold coast titans had a 9/16 ladder position . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '9 / 16', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'ladder position', '9 / 16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose ladder position record fuzzily matches to 9 / 16 .', 'tostr': 'filter_eq { all_rows ; ladder position ; 9 / 16 }'}], 'result': True,... | and { only { filter_eq { all_rows ; ladder position ; 9 / 16 } } ; eq { hop { filter_eq { all_rows ; ladder position ; 9 / 16 } ; competition } ; 2013 nrl season } } = true | select the rows whose ladder position record fuzzily matches to 9 / 16 . there is only one such row in the table . the competition record of this unqiue row is 2013 nrl season . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'ladder position_7': 7, '9 / 16_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'competition_9': 9, '2013 nrl season_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'ladder position_7': 'ladder position', '9 / 16_8': '9 / 16', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'competition_9': 'competition', '2013 nrl season_10': '2013 nrl season'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'ladder position_7': [0], '9 / 16_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'competition_9': [2], '2013 nrl season_10': [3]} | ['competition', 'ladder position', 'coach', 'captain ( s )', 'details'] | [['2007 nrl season', '12 / 16', 'john cartwright', 'luke bailey scott prince', '2007 gold coast titans season'], ['2008 nrl season', '13 / 16', 'john cartwright', 'luke bailey scott prince', '2008 gold coast titans season'], ['2009 nrl season', '3 / 16', 'john cartwright', 'luke bailey scott prince', '2009 gold coast t... |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-8.html.csv | majority | most of the games in round 8 of the 1941 victorian football season season had crowds above 3,000 people . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '3,000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'crowd', '3,000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 3,000 .', 'tostr': 'most_greater { all_rows ; crowd ; 3,000 } = true'} | most_greater { all_rows ; crowd ; 3,000 } = true | for the crowd records of all rows , most of them are greater than 3,000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '3,000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '3,000_4': '3,000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '3,000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '10.13 ( 73 )', 'st kilda', '6.11 ( 47 )', 'punt road oval', '6000', '21 june 1941'], ['hawthorn', '6.8 ( 44 )', 'melbourne', '12.12 ( 84 )', 'glenferrie oval', '2000', '21 june 1941'], ['collingwood', '8.12 ( 60 )', 'essendon', '7.10 ( 52 )', 'victoria park', '6000', '21 june 1941'], ['carlton', '10.17 (... |
california legislative lgbt caucus | https://en.wikipedia.org/wiki/California_Legislative_LGBT_Caucus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17769516-1.html.csv | count | for the california legislative lgbt caucus , when the years in assembly include 2008 , there were two times the residence was san francisco . | {'scope': 'subset', 'criterion': 'equal', 'value': 'san francisco', 'result': '2', 'col': '2', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': '2008'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'years in assembly', '2008'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; years in assembly ; 2008 }', 'tointer': 'select the rows whose years in assembly record fuzzily ma... | eq { count { filter_eq { filter_eq { all_rows ; years in assembly ; 2008 } ; residence ; san francisco } } ; 2 } = true | select the rows whose years in assembly record fuzzily matches to 2008 . among these rows , select the rows whose residence record fuzzily matches to san francisco . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'years in assembly_6': 6, '2008_7': 7, 'residence_8': 8, 'san francisco_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'years in assembly_6': 'years in assembly', '2008_7': '2008', 'residence_8': 'residence', 'san francisco_9': 'san francisco', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'years in assembly_6': [0], '2008_7': [0], 'residence_8': [1], 'san francisco_9': [1], '2_10': [3]} | ['name', 'residence', 'party', 'years in assembly', 'years in senate'] | [['mark leno', 'san francisco', 'democratic', '2002 - 2008', '2008 - present'], ['cathleen galgiani', 'livingston', 'democratic', '2006 - 2012 galgiani came out in november 2011', '2012 - present'], ['tom ammiano', 'san francisco', 'democratic', '2008 - present', '-'], ['john pérez', 'los angeles', 'democratic', '2008 ... |
taylor dent | https://en.wikipedia.org/wiki/Taylor_Dent | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551815-5.html.csv | unique | of all of the tournaments that taylor dent participated in , the only one on a grass surface was on july 2nd , 2002 . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'grass', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to grass .', 'tostr': 'filter_eq { all_rows ; surface ; grass }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; surface ; grass } } ; eq { hop { filter_eq { all_rows ; surface ; grass } ; date ( final ) } ; july 7 2002 } } = true | select the rows whose surface record fuzzily matches to grass . there is only one such row in the table . the date ( final ) record of this unqiue row is july 7 2002 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'grass_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date (final)_9': 9, 'july 7 2002_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'grass_8': 'grass', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date (final)_9': 'date ( final )', 'july 7 2002_10': 'july 7 2002'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'grass_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date (final)_9': [2], 'july 7 2002_10': [3]} | ['outcome', 'date ( final )', 'tournament', 'surface', 'opponent in the final', 'score'] | [['winner', 'july 7 2002', 'newport , united states', 'grass', 'james blake', '6 - 1 , 4 - 6 , 6 - 4'], ['winner', 'february 17 , 2003', 'memphis , united states', 'hard ( i )', 'andy roddick', '6 - 1 , 6 - 4'], ['winner', 'september 22 , 2003', 'bangkok , thailand', 'hard ( i )', 'juan carlos ferrero', '6 - 3 , 7 - 6 ... |
toronto raptors all - time roster | https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10015132-11.html.csv | majority | united states is the nationality of all players on the toronto raptors all - time roster . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'} | all_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'nationality', 'position', 'years in toronto', 'school / club team'] | [['antonio lang', 'united states', 'guard - forward', '1999 - 2000', 'duke'], ['voshon lenard', 'united states', 'guard', '2002 - 03', 'minnesota'], ['martin lewis', 'united states', 'guard - forward', '1996 - 97', 'butler cc ( ks )'], ['brad lohaus', 'united states', 'forward - center', '1996', 'iowa'], ['art long', '... |
2004 british grand prix | https://en.wikipedia.org/wiki/2004_British_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1123631-2.html.csv | superlative | at 2004 british grand prix , rubens barrichello was the slowest ferrari driver . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1,2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'ferrari'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constructor', 'ferrari'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; constructor ; ferrari }', 'tointer': 'select the rows whose constructor record fuzzily matches to ferr... | eq { hop { argmin { filter_eq { all_rows ; constructor ; ferrari } ; time / retired } ; driver } ; rubens barrichello } = true | select the rows whose constructor record fuzzily matches to ferrari . select the row whose time / retired record of these rows is minimum . the driver record of this row is rubens barrichello . | 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, 'constructor_6': 6, 'ferrari_7': 7, 'time / retired_8': 8, 'driver_9': 9, 'rubens barrichello_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', 'constructor_6': 'constructor', 'ferrari_7': 'ferrari', 'time / retired_8': 'time / retired', 'driver_9': 'driver', 'rubens barrichello_10': 'rubens barrichello'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'constructor_6': [0], 'ferrari_7': [0], 'time / retired_8': [1], 'driver_9': [2], 'rubens barrichello_10': [3]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['michael schumacher', 'ferrari', '60', '1:24:42.700', '4'], ['kimi räikkönen', 'mclaren - mercedes', '60', '+ 2.130', '1'], ['rubens barrichello', 'ferrari', '60', '+ 3.114', '2'], ['jenson button', 'bar - honda', '60', '+ 10.683', '3'], ['juan pablo montoya', 'williams - bmw', '60', '+ 12.173', '7'], ['giancarlo fis... |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-12.html.csv | unique | fred e busbey was the only illinois incumbent to lose re-election in the 1954 united states house of representatives elections . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'lost re - election democratic gain', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'lost re - election democratic gain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to lost re - election democratic gain .', 'tostr': 'filter_eq { all_rows ; result ;... | and { only { filter_eq { all_rows ; result ; lost re - election democratic gain } } ; eq { hop { filter_eq { all_rows ; result ; lost re - election democratic gain } ; incumbent } ; fred e busbey } } = true | select the rows whose result record fuzzily matches to lost re - election democratic gain . there is only one such row in the table . the incumbent record of this unqiue row is fred e busbey . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'lost re - election democratic gain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'fred e busbey_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', 'lost re - election democratic gain_8': 'lost re - election democratic gain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'fred e busbey_10': 'fred e b... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'lost re - election democratic gain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'fred e busbey_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 2', "barratt o'hara", 'democratic', '1952', 're - elected', "barratt o'hara ( d ) 61.6 % richard b vail ( r ) 38.4 %"], ['illinois 3', 'fred e busbey', 'republican', '1950', 'lost re - election democratic gain', 'james c murray ( d ) 53.8 % fred e busbey ( r ) 46.2 %'], ['illinois 14', 'chauncey w reed', 'r... |
sophus nielsen | https://en.wikipedia.org/wiki/Sophus_Nielsen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1580245-1.html.csv | majority | sophus nielsen scored the majority of his international goals in the 1908 olympics competition . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1908 olympics', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'competition', '1908 olympics'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to 1908 olympics .', 'tostr': 'most_eq { all_rows ; competition ; 1908 olympics } = true'} | most_eq { all_rows ; competition ; 1908 olympics } = true | for the competition records of all rows , most of them fuzzily match to 1908 olympics . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, '1908 olympics_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', '1908 olympics_4': '1908 olympics'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], '1908 olympics_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['1908 - 10 - 19', 'london , england', '9 - 0', '9 - 0', '1908 olympics'], ['1908 - 10 - 22', 'london , england', '1 - 0', '17 - 1', '1908 olympics'], ['1908 - 10 - 22', 'london , england', '2 - 0', '17 - 1', '1908 olympics'], ['1908 - 10 - 22', 'london , england', '3 - 0', '17 - 1', '1908 olympics'], ['1908 - 10 - 22... |
yugoslavian motorcycle grand prix | https://en.wikipedia.org/wiki/Yugoslavian_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16801125-1.html.csv | count | in the yugoslavian motorcycle grand prix , when the year is before 1990 , there were three times the 250 cc was sito pons . | {'scope': 'subset', 'criterion': 'equal', 'value': 'sito pons', 'result': '3', 'col': '3', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '1990'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'year', '1990'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; year ; 1990 }', 'tointer': 'select the rows whose year record is less than 1990 .'}, '250 cc', 'sito pons'], 'r... | eq { count { filter_eq { filter_less { all_rows ; year ; 1990 } ; 250 cc ; sito pons } } ; 3 } = true | select the rows whose year record is less than 1990 . among these rows , select the rows whose 250 cc record fuzzily matches to sito pons . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'year_6': 6, '1990_7': 7, '250 cc_8': 8, 'sito pons_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'year_6': 'year', '1990_7': '1990', '250 cc_8': '250 cc', 'sito pons_9': 'sito pons', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'year_6': [0], '1990_7': [0], '250 cc_8': [1], 'sito pons_9': [1], '3_10': [3]} | ['year', 'track', '250 cc', '500 cc', 'report'] | [['1990', 'rijeka', 'carlos cardãs', 'wayne rainey', 'report'], ['1989', 'rijeka', 'sito pons', 'kevin schwantz', 'report'], ['1988', 'rijeka', 'sito pons', 'wayne gardner', 'report'], ['1987', 'rijeka', 'carlos lavado', 'wayne gardner', 'report'], ['1986', 'rijeka', 'sito pons', 'eddie lawson', 'report'], ['1985', 'ri... |
1951 world wrestling championships | https://en.wikipedia.org/wiki/1951_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16853558-1.html.csv | superlative | in the 1951 world wrestling championships , turkey ranks the highest . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'rank'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; rank }'}, 'nation'], 'result': 'turkey', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; rank } ; nation }'}, 'turkey'], 'result': True, 'ind': 2, 'tostr': 'eq ... | eq { hop { argmin { all_rows ; rank } ; nation } ; turkey } = true | select the row whose rank record of all rows is minimum . the nation record of this row is turkey . | 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, 'turkey_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', 'turkey_7': 'turkey'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], 'nation_6': [1], 'turkey_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'turkey', '6', '0', '1', '7'], ['2', 'sweden', '2', '1', '3', '6'], ['3', 'finland', '0', '4', '0', '4'], ['4', 'iran', '0', '2', '2', '4'], ['5', 'italy', '0', '1', '1', '2'], ['6', 'west germany', '0', '0', '1', '1'], ['total', 'total', '8', '8', '8', '24']] |
tony lema | https://en.wikipedia.org/wiki/Tony_Lema | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1570274-4.html.csv | unique | the open championship is the only time tony lema recorded a win . | {'scope': 'all', 'row': '3', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'the open championship', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'the open championship'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to the open championship .', 'tostr': 'filter_eq { all_rows ; tournament ; the open cham... | and { only { filter_eq { all_rows ; tournament ; the open championship } } ; eq { hop { filter_eq { all_rows ; tournament ; the open championship } ; wins } ; 1 } } = true | select the rows whose tournament record fuzzily matches to the open championship . there is only one such row in the table . the wins record of this unqiue row is 1 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'the open championship_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'wins_9': 9, '1_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'the open championship_8': 'the open championship', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'wins_9': 'wins', '1_10': '1'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'tournament_7': [0], 'the open championship_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'wins_9': [2], '1_10': [3]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '1', '2', '4', '4', '4'], ['us open', '0', '2', '3', '4', '6', '5'], ['the open championship', '1', '2', '2', '2', '3', '3'], ['pga championship', '0', '0', '1', '2', '5', '4'], ['totals', '1', '5', '8', '12', '18', '16']] |
2010 - 11 dallas mavericks season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Dallas_Mavericks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27723526-17.html.csv | superlative | the dallas mavericks ' game on june 9 recorded the most attendance . | {'scope': 'all', 'col_superlative': '8', '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', 'location attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; location attendance }'}, 'date'], 'result': 'june 9', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; location attendance } ; date }'}, 'june 9']... | eq { hop { argmax { all_rows ; location attendance } ; date } ; june 9 } = true | select the row whose location attendance record of all rows is maximum . the date record of this row is june 9 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'date_6': 6, 'june 9_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'date_6': 'date', 'june 9_7': 'june 9'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'date_6': [1], 'june 9_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 31', 'miami', 'l 84 - 92 ( ot )', 'dirk nowitzki ( 27 )', 'shawn marion ( 10 )', 'jason kidd ( 6 )', 'american airlines arena 20003', '0 - 1'], ['2', 'june 2', 'miami', 'w 95 - 93 ( ot )', 'dirk nowitzki ( 24 )', 'dirk nowitzki ( 11 )', 'jason kidd , jason terry ( 5 )', 'american airlines arena 20003', '1 -... |
thai clubs in the afc champions league | https://en.wikipedia.org/wiki/Thai_clubs_in_the_AFC_Champions_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16593799-8.html.csv | aggregation | the average team 1 score of these teams was approximately 2.3 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '2.3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '2.3', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '2.3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 2.3 } = true', 'tointer': 'the average of the score record of all rows is 2.3 .'} | round_eq { avg { all_rows ; score } ; 2.3 } = true | the average of the score record of all rows is 2.3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '2.3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '2.3_5': '2.3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '2.3_5': [1]} | ['season', 'team 1', 'score', 'team 2', 'venue'] | [['2004', 'krung thai bank', '0 - 2', 'dalian shide', 'thai - japanese stadium , thailand'], ['2004', 'psm makassar', '2 - 3', 'krung thai bank', 'mattoangin stadium , indonesia'], ['2004', 'hoang anh gia lai', '0 - 1', 'krung thai bank', 'pleiku stadium , vietnam'], ['2004', 'krung thai bank', '2 - 2', 'hoang anh gia ... |
list of countries by electricity production from renewable sources | https://en.wikipedia.org/wiki/List_of_countries_by_electricity_production_from_renewable_sources | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17068413-1.html.csv | unique | russia was the only country that did n't produce any solar energy at all . | {'scope': 'all', 'row': '6', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'solar', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose solar record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; solar ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; solar... | and { only { filter_eq { all_rows ; solar ; 0 } } ; eq { hop { filter_eq { all_rows ; solar ; 0 } ; country } ; russia } } = true | select the rows whose solar record is equal to 0 . there is only one such row in the table . the country record of this unqiue row is russia . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'solar_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'russia_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'solar_7': 'solar', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'russia_10': 'russia'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'solar_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'russia_10': [3]} | ['country', 'year', 'total', 'hydroelectricity', 'wind power', 'biomass and waste', 'solar'] | [['china', '2011', '797.4', '687.1', '73.2', '34', '3'], ['european union', '2010', '699.3', '397.7', '149.1', '123.3', '23.1'], ['united states', '2011', '520.1', '325.1', '119.7', '56.7', '1.81'], ['brazil', '2011', '459.2', '424.3', '2.71', '32.2', '0.0002'], ['canada', '2011', '399.1', '372.6', '19.7', '6.4', '0.43... |
1986 dallas cowboys season | https://en.wikipedia.org/wiki/1986_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11309481-2.html.csv | majority | most of the dallas cowboys games in the 1986 season saw more than 50000 people in attendance . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '50000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'attendance', '50000'], 'result': True, 'ind': 0, 'tointer': 'for the attendance records of all rows , most of them are greater than 50000 .', 'tostr': 'most_greater { all_rows ; attendance ; 50000 } = true'} | most_greater { all_rows ; attendance ; 50000 } = true | for the attendance records of all rows , most of them are greater than 50000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'attendance_3': 3, '50000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'attendance_3': 'attendance', '50000_4': '50000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'attendance_3': [0], '50000_4': [0]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', 'september 8 , 1986', 'new york giants', 'w 31 - 28', 'texas stadium', '59804'], ['2', 'september 14 , 1986', 'detroit lions', 'w 31 - 7', 'pontiac silverdome', '73812'], ['3', 'september 21 , 1986', 'atlanta falcons', 'l 35 - 37', 'texas stadium', '62880'], ['4', 'september 29 , 1986', 'st louis cardinals', 'w ... |
list of rampage killers | https://en.wikipedia.org/wiki/List_of_rampage_killers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17794738-6.html.csv | count | there are a total of 6 perpetrators from the philippines . | {'scope': 'all', 'criterion': 'equal', 'value': 'philippines', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'philippines'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to philippines .', 'tostr': 'filter_eq { all_rows ; country ; philippines }'}], 'result': '6', 'ind': 1,... | eq { count { filter_eq { all_rows ; country ; philippines } } ; 6 } = true | select the rows whose country record fuzzily matches to philippines . 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, 'country_5': 5, 'philippines_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', 'country_5': 'country', 'philippines_6': 'philippines', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'philippines_6': [0], '6_7': [2]} | ['perpetrator', 'location', 'country', 'killed', 'injured'] | [['bryant , martin john , 28', 'port arthur , tas', 'australia', '35', '23'], ['unknown', 'siquijor', 'philippines', '32', '0.0'], ['wirjo , 42', 'banjarsari', 'indonesia', '20', '12'], ['formentera , arsenio', 'palompon', 'philippines', '17', '0.0'], ['hodeng', 'kampong tankulu', 'indonesia', '16', '01 1'], ['gz', 'gz... |
list of highest - grossing bollywood films | https://en.wikipedia.org/wiki/List_of_highest-grossing_Bollywood_films | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11872185-4.html.csv | comparative | in the set of the highest-grossing bollywood films , agneepath has a lower lifetime india distributor share than dabangg 2 . | {'row_1': '9', 'row_2': '5', 'col': '5', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'movie', 'agneepath'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose movie record fuzzily matches to agneepath .', 'tostr': 'filter_eq { all_rows ; movie ; agneepath }'}, 'lifetime india distributor share... | less { hop { filter_eq { all_rows ; movie ; agneepath } ; lifetime india distributor share } ; hop { filter_eq { all_rows ; movie ; dabangg 2 } ; lifetime india distributor share } } = true | select the rows whose movie record fuzzily matches to agneepath . take the lifetime india distributor share record of this row . select the rows whose movie record fuzzily matches to dabangg 2 . take the lifetime india distributor share record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'movie_7': 7, 'agneepath_8': 8, 'lifetime india distributor share_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'movie_11': 11, 'dabangg 2_12': 12, 'lifetime india distributor share_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'movie_7': 'movie', 'agneepath_8': 'agneepath', 'lifetime india distributor share_9': 'lifetime india distributor share', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10'... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'movie_7': [0], 'agneepath_8': [0], 'lifetime india distributor share_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'movie_11': [1], 'dabangg 2_12': [1], 'lifetime india distributor share_13': [3]} | ['rank', 'movie', 'year', 'studio ( s )', 'lifetime india distributor share'] | [['1', 'chennai express', '2013', 'red chillies entertainment', '114 , 25 , 00000'], ['2', 'ek tha tiger', '2012', 'yash raj films', '106 , 00 , 00000'], ['3', '3 idiots', '2009', 'vinod chopra productions', '99 , 02 , 00000'], ['4', 'yeh jawaani hai deewani', '2013', 'dharma productions', '91 , 00 , 00000'], ['5', 'da... |
2007 - 08 los angeles kings season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Los_Angeles_Kings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11821711-5.html.csv | majority | during the 2007 - 08 los angeles kings season most of their home games had an attendance of of 18118 . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '18118', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'los angeles'}} | {'func': 'most_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home', 'los angeles'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; home ; los angeles }', 'tointer': 'select the rows whose home record fuzzily matches to los angeles .'}, 'attendance', '18118'], 'result': True, 'ind': 1, 'toint... | most_eq { filter_eq { all_rows ; home ; los angeles } ; attendance ; 18118 } = true | select the rows whose home record fuzzily matches to los angeles . for the attendance records of these rows , most of them are equal to 18118 . | 2 | 2 | {'most_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'home_4': 4, 'los angeles_5': 5, 'attendance_6': 6, '18118_7': 7} | {'most_eq_1': 'most_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'home_4': 'home', 'los angeles_5': 'los angeles', 'attendance_6': 'attendance', '18118_7': '18118'} | {'most_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'home_4': [0], 'los angeles_5': [0], 'attendance_6': [1], '18118_7': [1]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 2', 'los angeles', '5 - 2', 'san jose', 'aubin', '17496', '7 - 7 - 0'], ['november 3', 'san jose', '3 - 1', 'los angeles', 'labarbera', '18118', '7 - 8 - 0'], ['november 10', 'dallas', '5 - 6', 'los angeles', 'aubin', '18118', '8 - 8 - 0'], ['november 13', 'los angeles', '3 - 4', 'anaheim', 'labarbera', '17... |
galatasaray s.k. ( superleague formula team ) | https://en.wikipedia.org/wiki/Galatasaray_S.K._%28Superleague_Formula_team%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23293785-3.html.csv | comparative | for galatasaray s.k. , the race in france took place one month before the one in belgium . | {'row_1': '1', 'row_2': '2', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'france'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to france .', 'tostr': 'filter_eq { all_rows ; country ; france }'}, 'date'], 'result': None, 'ind': 2, '... | less { hop { filter_eq { all_rows ; country ; france } ; date } ; hop { filter_eq { all_rows ; country ; belgium } ; date } } = true | select the rows whose country record fuzzily matches to france . take the date record of this row . select the rows whose country record fuzzily matches to belgium . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'france_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'belgium_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'france_8': 'france', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'belgium_12': 'belg... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'france_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'belgium_12': [1], 'date_13': [3]} | ['sf round', 'country', 'location', 'date', 'driver', 'race 1 ( pts )', 'race 2 ( pts )', 'race 3', 'race total ( pts )'] | [['1', 'france', 'circuit de nevers magny - cours', '28 june 2009', 'duncan tappy', '32', '16', 'dnq', '48'], ['2', 'belgium', 'zolder', '19 july 2009', 'duncan tappy', '20', '7', 'n / a', '75'], ['3', 'england', 'donington park', '2 august 2009', 'scott mansell', '12', '14', 'dnq', '101'], ['4', 'portugal', 'estoril c... |
lner thompson class b1 | https://en.wikipedia.org/wiki/LNER_Thompson_Class_B1 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2079664-3.html.csv | majority | the majority of lner thompson class b1 locomotive models were taken into deptal stock in 1963 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1963', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'taken into deptal stock', '1963'], 'result': True, 'ind': 0, 'tointer': 'for the taken into deptal stock records of all rows , most of them are equal to 1963 .', 'tostr': 'most_eq { all_rows ; taken into deptal stock ; 1963 } = true'} | most_eq { all_rows ; taken into deptal stock ; 1963 } = true | for the taken into deptal stock records of all rows , most of them are equal to 1963 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'taken into deptal stock_3': 3, '1963_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'taken into deptal stock_3': 'taken into deptal stock', '1963_4': '1963'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'taken into deptal stock_3': [0], '1963_4': [0]} | ['number', 'previous br no', 'taken into deptal stock', 'withdrawn', 'disposal'] | [['17', '61059', '1963', '1966', 'scrapped ( 1966 )'], ['18', '61181', '1963', '1965', 'scrapped ( 1966 )'], ['19', '61204', '1963', '1966', 'scrapped ( 1966 )'], ['20', '61205', '1963', '1965', 'scrapped ( 1966 )'], ['21', '61233', '1963', '1966', 'scrapped ( 1966 )'], ['22', '61252', '1963', '1964', 'scrapped ( 1966 ... |
portugal in the eurovision song contest 1996 | https://en.wikipedia.org/wiki/Portugal_in_the_Eurovision_Song_Contest_1996 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18994360-1.html.csv | comparative | in the 1996 eurovision song contest , pedro miguéis scored 20 more points than joão portugal . | {'row_1': '9', 'row_2': '10', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '20', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'singer', 'pedro miguéis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose singer record fuzzily matches to pedro miguéis .', 'tostr': 'filter_eq { all_rows ; singer ; pedro miguéis... | eq { diff { hop { filter_eq { all_rows ; singer ; pedro miguéis } ; points } ; hop { filter_eq { all_rows ; singer ; joão portugal } ; points } } ; 20 } = true | select the rows whose singer record fuzzily matches to pedro miguéis . take the points record of this row . select the rows whose singer record fuzzily matches to joão portugal . take the points record of this row . the first record is 20 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, 'singer_8': 8, 'pedro miguéis_9': 9, 'points_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'singer_12': 12, 'joão portugal_13': 13, 'points_14': 14, '20_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', 'singer_8': 'singer', 'pedro miguéis_9': 'pedro miguéis', 'points_10': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'singer_12': ... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'singer_8': [0], 'pedro miguéis_9': [0], 'points_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'singer_12': [1], 'joão portugal_13': [1], 'points_14': [3], '20_15': [5]} | ['draw', 'singer', 'song', 'points', 'place'] | [['1', 'vnia maroti', 'start stop', '33', '10'], ['2', 'tó leal', 'eu mesmo', '42', '8'], ['3', 'patricia antunes', 'canto em português', '91', '2'], ['4', 'barbara reis', 'a minha ilha', '43', '7'], ['5', 'elaisa', 'ai a noite', '49', '6'], ['6', 'somseis', 'a canção da paz', '76', '3'], ['7', 'cristina castro pereira... |
united states house of representatives elections , 1942 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1942 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342256-5.html.csv | comparative | david d terry was first elected earlier than ezekiel c gathings to the united states house of representatives . | {'row_1': '5', 'row_2': '1', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'david d terry'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to david d terry .', 'tostr': 'filter_eq { all_rows ; incumbent ; david d terry }'}, 'first el... | less { hop { filter_eq { all_rows ; incumbent ; david d terry } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; ezekiel c gathings } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to david d terry . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to ezekiel c gathings . take the first elected record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'incumbent_7': 7, 'david d terry_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'ezekiel c gathings_12': 12, 'first elected_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'incumbent_7': 'incumbent', 'david d terry_8': 'david d terry', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbe... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'david d terry_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'ezekiel c gathings_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'ezekiel c gathings', 'democratic', '1938', 're - elected', 'ezekiel c gathings ( d ) unopposed'], ['arkansas 2', 'wilbur mills', 'democratic', '1938', 're - elected', 'wilbur mills ( d ) unopposed'], ['arkansas 3', 'clyde t ellis', 'democratic', '1938', 'retired to run for u s senate democratic hold', ... |
uefa club competition records and statistics | https://en.wikipedia.org/wiki/UEFA_club_competition_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12307135-6.html.csv | unique | the only player to debut in europe in the uefa club competition in 1995 and play more than 160 games is raãl . | {'scope': 'subset', 'row': '2', 'col': '3', 'col_other': '2', 'criterion': 'greater_than', 'value': '160', 'subset': {'col': '6', 'criterion': 'equal', 'value': '1995'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'debut in europe', '1995'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; debut in europe ; 1995 }', 'tointer': 'select the rows whose debut in europe record is equal to 1995 .'... | and { only { filter_greater { filter_eq { all_rows ; debut in europe ; 1995 } ; games ; 160 } } ; eq { hop { filter_greater { filter_eq { all_rows ; debut in europe ; 1995 } ; games ; 160 } ; player } ; raãl } } = true | select the rows whose debut in europe record is equal to 1995 . among these rows , select the rows whose games record is greater than 160 . there is only one such row in the table . the player record of this unqiue row is raãl . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'debut in europe_8': 8, '1995_9': 9, 'games_10': 10, '160_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'player_12': 12, 'raãl_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'debut in europe_8': 'debut in europe', '1995_9': '1995', 'games_10': 'games', '160_11': '160', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'player_12': 'player', 'raãl_13... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'debut in europe_8': [0], '1995_9': [0], 'games_10': [1], '160_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'player_12': [3], 'raãl_13': [4]} | ['rank', 'player', 'games', 'goals', 'goal ratio', 'debut in europe'] | [['1', 'paolo maldini', '173', '3', '0.02', '1985'], ['2', 'raãl', '161', '76', '0.46', '1995'], ['3', 'clarence seedorf', '161', '15', '0.09', '1992'], ['4', 'javier zanetti', '159', '5', '0.03', '1995'], ['5', 'xavi', '154', '12', '0.08', '1999'], ['6', 'ryan giggs', '151', '29', '0.19', '1991'], ['7', 'jamie carragh... |
1973 - 74 football league cup | https://en.wikipedia.org/wiki/1973%E2%80%9374_Football_League_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24887326-6.html.csv | majority | most games of the 1973 - 74 football league cup were played in the month of october . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '10', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date', '10'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them fuzzily match to 10 .', 'tostr': 'most_eq { all_rows ; date ; 10 } = true'} | most_eq { all_rows ; date ; 10 } = true | for the date records of all rows , most of them fuzzily match to 10 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '10_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '10_4': '10'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '10_4': [0]} | ['tie no', 'home team', 'score 1', 'away team', 'attendance', 'date'] | [['1', 'hull city', '4 - 1', 'stockport county', '13753', '06 - 11 - 1973'], ['2', 'birmingham city', '2 - 2', 'newcastle united', '13025', '30 - 10 - 1973'], ['3', 'southampton', '3 - 0', 'chesterfield', '13663', '30 - 10 - 1973'], ['4', 'stoke city', '1 - 1', 'middlesbrough', '19194', '31 - 10 - 1973'], ['5', 'everto... |
1956 baltimore colts season | https://en.wikipedia.org/wiki/1956_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14984039-1.html.csv | aggregation | there were a total of 471,075 attendees during the 1956 baltimore colts season . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '471,075', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'attendance'], 'result': '471,075', 'ind': 0, 'tostr': 'sum { all_rows ; attendance }'}, '471,075'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; attendance } ; 471,075 } = true', 'tointer': 'the sum of the attendance record of all ro... | round_eq { sum { all_rows ; attendance } ; 471,075 } = true | the sum of the attendance record of all rows is 471,075 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '471,075_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '471,075_5': '471,075'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '471,075_5': [1]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 30 , 1956', 'chicago bears', 'w 28 - 21', '1 - 0', 'memorial stadium', '45221'], ['2', 'october 6 , 1956', 'detroit lions', 'l 14 - 31', '1 - 1', 'memorial stadium', '42622'], ['3', 'october 14 , 1956', 'green bay packers', 'l 33 - 38', '1 - 2', 'milwaukee county stadium', '24214'], ['4', 'october 21 ... |
fringe ( season 1 ) | https://en.wikipedia.org/wiki/Fringe_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24648983-1.html.csv | unique | the only episode to have more than 12 million viewers was the transformation . | {'scope': 'all', 'row': '11', 'col': '7', 'col_other': '2', 'criterion': 'greater_than', 'value': '12', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( million )', '12'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is greater than 12 .', 'tostr': 'filter_greater { all_rows ; us viewers ( million ) ; 12 }'}], 're... | and { only { filter_greater { all_rows ; us viewers ( million ) ; 12 } } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 12 } ; title } ; the transformation } } = true | select the rows whose us viewers ( million ) record is greater than 12 . there is only one such row in the table . the title record of this unqiue row is the transformation . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'us viewers (million)_7': 7, '12_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'the transformation_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'us viewers (million)_7': 'us viewers ( million )', '12_8': '12', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'the transformation_10': 'the transformation'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'us viewers (million)_7': [0], '12_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'the transformation_10': [3]} | ['-', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['1', 'pilot', 'alex graves', 'j j abrams & alex kurtzman & roberto orci', 'september 9 , 2008', '276038', '9.13'], ['3', 'the ghost network', 'frederick e o toye', 'david h goodman & j r orci', 'september 23 , 2008', '3t7652', '9.42'], ['4', 'the arrival', 'paul edwards', 'j j abrams & jeff pinkner', 'september 30 , ... |
lamine ouahab | https://en.wikipedia.org/wiki/Lamine_Ouahab | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16981551-2.html.csv | majority | most of the tournaments that lamine ouahab participated in were on a clay surface . | {'scope': 'all', 'col': '3', '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]} | ['date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['11 may 2003', 'sidi fredj', 'clay', 'sasa tuksar', '6 - 4 , 6 - 2'], ['21 december 2003', 'kish island', 'clay', 'sebastian fitz', '6 - 4 , 5 - 7 , 6 - 1'], ['4 april 2004', 'syros', 'hard', 'pavel šnobel', '6 - 4 , 6 - 4'], ['21 may 2005', 'agadir', 'clay', 'tres davis', '6 - 1 , 6 - 2'], ['28 may 2005', 'marrakech... |
united states house of representatives elections , 1946 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1946 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342233-3.html.csv | majority | all of the incumbents in the election of 1946 for united states house of representatives , were from the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , all of them fuzzily match to democratic .', 'tostr': 'all_eq { all_rows ; party ; democratic } = true'} | all_eq { all_rows ; party ; democratic } = true | for the party records of all rows , all of them fuzzily match to democratic . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['alabama 1', 'frank w boykin', 'democratic', '1935', 're - elected', 'frank w boykin ( d ) unopposed'], ['alabama 2', 'george m grant', 'democratic', '1938', 're - elected', 'george m grant ( d ) unopposed'], ['alabama 3', 'george w andrews', 'democratic', '1944', 're - elected', 'george w andrews ( d ) unopposed'], ... |
durham county cricket club | https://en.wikipedia.org/wiki/Durham_County_Cricket_Club | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1176371-1.html.csv | aggregation | the durham county cricket club played a total of 15 t20 matches . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '15', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 't20 matches'], 'result': '15', 'ind': 0, 'tostr': 'sum { all_rows ; t20 matches }'}, '15'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; t20 matches } ; 15 } = true', 'tointer': 'the sum of the t20 matches record of all rows is 15 .'... | round_eq { sum { all_rows ; t20 matches } ; 15 } = true | the sum of the t20 matches record of all rows is 15 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 't20 matches_4': 4, '15_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 't20 matches_4': 't20 matches', '15_5': '15'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 't20 matches_4': [0], '15_5': [1]} | ['name of ground', 'location', 'year', 'fc matches', 'la matches', 't20 matches', 'total'] | [['riverside ground', 'chester - le - street', '1995 - present', '102', '124', '15', '241'], ['feethams', 'darlington', '1964 - 2003', '10', '14', '0', '24'], ['grangefield road', 'stockton - on - tees', '1992 - 2006', '12', '11', '0', '23'], ['the racecourse', 'durham city', '1992 - 1994', '11', '7', '0', '18'], ['par... |
1994 foster 's cup | https://en.wikipedia.org/wiki/1994_Foster%27s_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16387953-1.html.csv | superlative | of all the games played in the first round of the 1994 foster 's cup , sydney acquired the highest points in their game against footscray . | {'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', 'home team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; home team score }'}, 'home team'], 'result': 'sydney', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; home team score } ; home team }'}, 'sydney'], ... | eq { hop { argmax { all_rows ; home team score } ; home team } ; sydney } = true | select the row whose home team score record of all rows is maximum . the home team record of this row is sydney . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'home team score_5': 5, 'home team_6': 6, 'sydney_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'home team score_5': 'home team score', 'home team_6': 'home team', 'sydney_7': 'sydney'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'home team score_5': [0], 'home team_6': [1], 'sydney_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date', 'time'] | [['collingwood', '13.14 ( 92 )', 'north melbourne', '13.13 ( 91 )', 'waverley park', '25708', 'saturday , 19 february 1994', '8:00 pm'], ['st kilda', '14.12 ( 96 )', 'richmond', '17.14 ( 116 )', 'waverley park', '18662', 'monday , 21 february 1994', '8:00 pm'], ['adelaide', '16.17 ( 113 )', 'west coast', '14.10 ( 94 )'... |
1990 - 91 seattle supersonics season | https://en.wikipedia.org/wiki/1990%E2%80%9391_Seattle_SuperSonics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17382360-6.html.csv | count | m cage had the high rebounds on three occasions . | {'scope': 'all', 'criterion': 'equal', 'value': 'm cage', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high rebounds', 'm cage'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high rebounds record fuzzily matches to m cage .', 'tostr': 'filter_eq { all_rows ; high rebounds ; m cage }'}], 'result': '3', 'ind':... | eq { count { filter_eq { all_rows ; high rebounds ; m cage } } ; 3 } = true | select the rows whose high rebounds record fuzzily matches to m cage . 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, 'high rebounds_5': 5, 'm cage_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', 'high rebounds_5': 'high rebounds', 'm cage_6': 'm cage', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high rebounds_5': [0], 'm cage_6': [0], '3_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['28', 'january 3', 'philadelphia 76ers', 'w 127 - 99', 'd mckey ( 24 )', 'm cage ( 12 )', 'g payton ( 11 )', 'seattle center coliseum 13048', '13 - 15'], ['29', 'january 4', 'miami heat', 'w 112 - 86', 's threatt ( 30 )', 'm cage ( 13 )', 'g payton ( 12 )', 'seattle center coliseum 12074', '14 - 15'], ['30', 'january... |
list of space telescopes | https://en.wikipedia.org/wiki/List_of_space_telescopes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15951109-4.html.csv | count | of all of the space telescopes , there are 3 whose space agency is nasa . | {'scope': 'all', 'criterion': 'equal', 'value': 'nasa', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'space agency', 'nasa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose space agency record fuzzily matches to nasa .', 'tostr': 'filter_eq { all_rows ; space agency ; nasa }'}], 'result': '3', 'ind': 1, 'tost... | eq { count { filter_eq { all_rows ; space agency ; nasa } } ; 3 } = true | select the rows whose space agency record fuzzily matches to nasa . 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, 'space agency_5': 5, 'nasa_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', 'space agency_5': 'space agency', 'nasa_6': 'nasa', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'space agency_5': [0], 'nasa_6': [0], '3_7': [2]} | ['name', 'space agency', 'launch date', 'terminated', 'location'] | [['corot', 'cnes & esa', '27 december 2006', '2013', 'earth orbit ( 872 - 884 km )'], ['hipparcos', 'esa', '8 august 1989', 'march 1993', 'earth orbit ( 223 - 35632 km )'], ['hubble space telescope', 'nasa', '24 april 1990', '-', 'earth orbit ( 586.47 - 610.44 km )'], ['kepler mission', 'nasa', '6 march 2009', '-', 'ea... |
2007 - 08 scottish second division | https://en.wikipedia.org/wiki/2007%E2%80%9308_Scottish_Second_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11206787-5.html.csv | ordinal | somerset park has the second highest seating capacity of stadiums in the 2007 - 08 scottish second division . | {'row': '3', 'col': '3', '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', 'capacity', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; capacity ; 2 }'}, 'stadium'], 'result': 'somerset park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; capacity ; 2 } ; stadium }'}, 'som... | eq { hop { nth_argmax { all_rows ; capacity ; 2 } ; stadium } ; somerset park } = true | select the row whose capacity record of all rows is 2nd maximum . the stadium record of this row is somerset park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, '2_6': 6, 'stadium_7': 7, 'somerset park_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', '2_6': '2', 'stadium_7': 'stadium', 'somerset park_8': 'somerset park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], '2_6': [0], 'stadium_7': [1], 'somerset park_8': [2]} | ['team', 'stadium', 'capacity', 'highest', 'lowest', 'average'] | [['ross county', 'victoria park', '6700', '3716', '1511', '2247'], ['raith rovers', "stark 's park", '10104', '2357', '1349', '1759'], ['ayr united', 'somerset park', '11998', '1345', '971', '1137'], ['airdrie united', 'new broomfield', '10171', '1645', '611', '981'], ["queen 's park", 'hampden park', '52500', '1211', ... |
big brother ( albania ) | https://en.wikipedia.org/wiki/Big_Brother_%28Albania%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15984770-1.html.csv | unique | season 3 was the only season to last a total of more than 110 days from start to finish . | {'scope': 'all', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'greater_than', 'value': '110', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'days', '110'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose days record is greater than 110 .', 'tostr': 'filter_greater { all_rows ; days ; 110 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_grea... | and { only { filter_greater { all_rows ; days ; 110 } } ; eq { hop { filter_greater { all_rows ; days ; 110 } ; series } ; season 3 } } = true | select the rows whose days record is greater than 110 . there is only one such row in the table . the series record of this unqiue row is season 3 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'days_7': 7, '110_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'series_9': 9, 'season 3_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'days_7': 'days', '110_8': '110', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'series_9': 'series', 'season 3_10': 'season 3'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'days_7': [0], '110_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'series_9': [2], 'season 3_10': [3]} | ['series', 'host', 'launch date', 'finale date', 'days', 'winner', 'prize'] | [['season 1', 'arbana osmani', '23 february 2008', '31 may 2008', '100', 'arbër çepani', '50000'], ['season 2', 'arbana osmani', '7 february 2009', '16 may 2009', '99', 'qetsor ferunaj', '70000'], ['season 3', 'arbana osmani', '23 january 2010', '15 may 2010', '113', 'jetmir salaj', '75000'], ['season 4', 'arbana osman... |
sebastian prödl | https://en.wikipedia.org/wiki/Sebastian_Pr%C3%B6dl | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12253254-1.html.csv | aggregation | the average score in sebastion prödl 's cometitions is about 2-0 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '2-0', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '2-0', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '2-0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 2-0 } = true', 'tointer': 'the average of the score record of all rows is 2-0 .'} | round_eq { avg { all_rows ; score } ; 2-0 } = true | the average of the score record of all rows is 2-0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '2-0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '2-0_5': '2-0'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '2-0_5': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['26 march 2008', 'ernst - happel - stadion , vienna , austria', '2 - 0', '3 - 4', 'friendly'], ['26 march 2008', 'ernst - happel - stadion , vienna , austria', '3 - 0', '3 - 4', 'friendly'], ['8 october 2010', 'ernst - happel - stadion , vienna , austria', '1 - 0', '3 - 0', 'uefa euro 2012 qualifying'], ['15 october ... |
united states house of representatives elections in georgia , 1998 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Georgia%2C_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27021001-1.html.csv | superlative | the person in the georgia house of representatives to be elected the earliest was john lewis . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', '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', 'elected'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; elected }'}, 'incumbent'], 'result': 'john lewis', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; elected } ; incumbent }'}, 'john lewis'], 'result': True, ... | eq { hop { argmin { all_rows ; elected } ; incumbent } ; john lewis } = true | select the row whose elected record of all rows is minimum . the incumbent record of this row is john lewis . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'elected_5': 5, 'incumbent_6': 6, 'john lewis_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'elected_5': 'elected', 'incumbent_6': 'incumbent', 'john lewis_7': 'john lewis'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'elected_5': [0], 'incumbent_6': [1], 'john lewis_7': [2]} | ['district', 'incumbent', 'party', 'elected', 'status', 'result'] | [["georgia 's 1st", 'jack kingston', 'republican', '1992', 're - elected', 'jack kingston ( r ) unopposed'], ["georgia 's 2nd", 'sanford bishop', 'democratic', '1992', 're - elected', 'sanford bishop ( d ) 57 % joseph mccormick ( r ) 43 %'], ["georgia 's 3rd", 'mac collins', 'republican', '1992', 're - elected', 'mac c... |
1955 washington redskins season | https://en.wikipedia.org/wiki/1955_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15123196-1.html.csv | unique | during the washington redskins ' 1955 season , the only game they lost after november 1 was on december 4 . | {'scope': 'subset', 'row': '11', 'col': '4', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': 'november 1 , 1955'}} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'date', 'november 1 , 1955'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; date ; november 1 , 1955 }', 'tointer': 'select the rows whose date record is greater than november 1 , 1955 .'}, 're... | only { filter_eq { filter_greater { all_rows ; date ; november 1 , 1955 } ; result ; l } } = true | select the rows whose date record is greater than november 1 , 1955 . among these rows , select the rows whose result record fuzzily matches to l . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'date_5': 5, 'november 1, 1955_6': 6, 'result_7': 7, 'l_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'date_5': 'date', 'november 1, 1955_6': 'november 1 , 1955', 'result_7': 'result', 'l_8': 'l'} | {'only_2': [3], 'result_3': [], 'filter_str_eq_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'date_5': [0], 'november 1, 1955_6': [0], 'result_7': [1], 'l_8': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 25 , 1955', 'cleveland browns', 'w 27 - 17', '30041'], ['2', 'october 1 , 1955', 'philadelphia eagles', 'w 31 - 30', '31891'], ['3', 'october 9 , 1955', 'chicago cardinals', 'l 24 - 10', '26337'], ['4', 'october 16 , 1955', 'cleveland browns', 'l 24 - 14', '29168'], ['5', 'october 23 , 1955', 'baltimo... |
savannah braves | https://en.wikipedia.org/wiki/Savannah_Braves | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18893381-2.html.csv | majority | the savannah braves were for the most part not eligible for the playoffs . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'not eligible', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'playoffs', 'not eligible'], 'result': True, 'ind': 0, 'tointer': 'for the playoffs records of all rows , most of them fuzzily match to not eligible .', 'tostr': 'most_eq { all_rows ; playoffs ; not eligible } = true'} | most_eq { all_rows ; playoffs ; not eligible } = true | for the playoffs records of all rows , most of them fuzzily match to not eligible . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'playoffs_3': 3, 'not eligible_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'playoffs_3': 'playoffs', 'not eligible_4': 'not eligible'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'playoffs_3': [0], 'not eligible_4': [0]} | ['year', 'record', 'finish', 'manager', 'playoffs'] | [['1971', '57 - 84', '5th', 'eddie haas', 'not eligible'], ['1972', '80 - 59', '2nd', 'clint courtney', 'not eligible'], ['1973', '71 - 68', '3rd', 'clint courtney ( 34 - 23 ) / tommie aaron ( 37 - 45 )', 'not eligible'], ['1974', '73 - 65', '4th', 'tommie aaron', 'not eligible'], ['1975', '70 - 64', '3rd ( t )', 'tomm... |
2008 pga tour | https://en.wikipedia.org/wiki/2008_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14473512-2.html.csv | comparative | phil mickelson played in more events of the 2008 pga tour than tiger woods . | {'row_1': '3', 'row_2': '2', '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', 'player', 'phil mickelson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to phil mickelson .', 'tostr': 'filter_eq { all_rows ; player ; phil mickelson }'}, 'events'], '... | greater { hop { filter_eq { all_rows ; player ; phil mickelson } ; events } ; hop { filter_eq { all_rows ; player ; tiger woods } ; events } } = true | select the rows whose player record fuzzily matches to phil mickelson . take the events record of this row . select the rows whose player record fuzzily matches to tiger woods . take the events 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, 'phil mickelson_8': 8, 'events_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'tiger woods_12': 12, 'events_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', 'phil mickelson_8': 'phil mickelson', 'events_9': 'events', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'phil mickelson_8': [0], 'events_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'tiger woods_12': [1], 'events_13': [3]} | ['rank', 'player', 'country', 'events', 'prize money'] | [['1', 'vijay singh', 'fiji', '23', '6601094'], ['2', 'tiger woods', 'united states', '6', '5775000'], ['3', 'phil mickelson', 'united states', '21', '5118875'], ['4', 'sergio garcía', 'spain', '19', '4858224'], ['5', 'kenny perry', 'united states', '26', '4663794'], ['6', 'anthony kim', 'united states', '22', '4656265... |
2009 - 10 new york knicks season | https://en.wikipedia.org/wiki/2009%E2%80%9310_New_York_Knicks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23248869-6.html.csv | majority | david lee recorded the majority of high rebounds performances for the new york knicks . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'david lee', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high rebounds', 'david lee'], 'result': True, 'ind': 0, 'tointer': 'for the high rebounds records of all rows , most of them fuzzily match to david lee .', 'tostr': 'most_eq { all_rows ; high rebounds ; david lee } = true'} | most_eq { all_rows ; high rebounds ; david lee } = true | for the high rebounds records of all rows , most of them fuzzily match to david lee . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high rebounds_3': 3, 'david lee_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high rebounds_3': 'high rebounds', 'david lee_4': 'david lee'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high rebounds_3': [0], 'david lee_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['18', 'december 1', 'phoenix', 'w 126 - 99 ( ot )', 'danilo gallinari ( 27 )', 'danilo gallinari ( 10 )', 'larry hughes ( 12 )', 'madison square garden 19763', '4 - 14'], ['19', 'december 2', 'orlando', 'l 104 - 118 ( ot )', 'wilson chandler ( 24 )', 'danilo gallinari ( 7 )', 'danilo gallinari , larry hughes ( 3 )', ... |
adriano buzaid | https://en.wikipedia.org/wiki/Adriano_Buzaid | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23128286-1.html.csv | aggregation | adriano buzaid recorded a total number of 18 podium finishes in his races . | {'scope': 'all', 'col': '8', 'type': 'sum', 'result': '18', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'podiums'], 'result': '18', 'ind': 0, 'tostr': 'sum { all_rows ; podiums }'}, '18'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; podiums } ; 18 } = true', 'tointer': 'the sum of the podiums record of all rows is 18 .'} | round_eq { sum { all_rows ; podiums } ; 18 } = true | the sum of the podiums record of all rows is 18 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'podiums_4': 4, '18_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'podiums_4': 'podiums', '18_5': '18'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'podiums_4': [0], '18_5': [1]} | ['season', 'series', 'team name', 'races', 'wins', 'poles', 'flaps', 'podiums', 'points', 'final placing'] | [['2006', 'formula ford uk', 'eau rouge motorsport', '17', '1', '0', '1', '1', '186', '13th'], ['2006', 'formula renault uk winter series', 'aka lemac', '4', '0', '0', '0', '1', '58', '7th'], ['2007', 'formula renault uk', 'eucatex', '20', '0', '0', '0', '2', '166', '13th'], ['2007', 'formula renault uk winter series',... |
serbia national football team | https://en.wikipedia.org/wiki/Serbia_national_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1011001-10.html.csv | aggregation | the serbian national football teams average attendance was 19,807 for its belgrade contests . | {'scope': 'subset', 'col': '8', 'type': 'average', 'result': '19,807', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'belgrade'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'belgrade'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; city ; belgrade }', 'tointer': 'select the rows whose city record fuzzily matches to belgrade .'}, 'average attendance'], 'result': '19,80... | round_eq { avg { filter_eq { all_rows ; city ; belgrade } ; average attendance } ; 19,807 } = true | select the rows whose city record fuzzily matches to belgrade . the average of the average attendance record of these rows is 19,807 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'city_5': 5, 'belgrade_6': 6, 'average attendance_7': 7, '19,807_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'city_5': 'city', 'belgrade_6': 'belgrade', 'average attendance_7': 'average attendance', '19,807_8': '19,807'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'city_5': [0], 'belgrade_6': [0], 'average attendance_7': [1], '19,807_8': [2]} | ['venue', 'city', 'first international', 'last international', 'played', 'draw', 'lost', 'average attendance'] | [['red star stadium', 'belgrade', '31 march 1995 1 - 0 vs', '6 september 2013 1 - 1 vs', '44', '16', '4', '26222'], ['partizan stadium', 'belgrade', '5 september 1999 3 - 1 vs', '6 september 2011 3 - 1 vs', '12', '2', '2', '13393'], ['karađorđe stadium', 'novi sad', '11 september 2012 6 - 1 vs', '12 october 2013 2 - 0 ... |
carleton county , new brunswick | https://en.wikipedia.org/wiki/Carleton_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-170961-2.html.csv | ordinal | in carleton county , new brunswick , the parish of woodstock has the third highest population among the county parishes . | {'row': '3', 'col': '4', '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', 'population', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ; 3 }'}, 'official name'], 'result': 'woodstock', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population ; 3 } ; official ... | eq { hop { nth_argmax { all_rows ; population ; 3 } ; official name } ; woodstock } = true | select the row whose population record of all rows is 3rd maximum . the official name record of this row is woodstock . | 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, 'official name_7': 7, 'woodstock_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', 'official name_7': 'official name', 'woodstock_8': 'woodstock'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population_5': [0], '3_6': [0], 'official name_7': [1], 'woodstock_8': [2]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['wakefield', 'parish', '196.42', '2703', '1079 of 5008'], ['kent', 'parish', '839.79', '2361', '1184 of 5008'], ['woodstock', 'parish', '197.45', '2148', '1258 of 5008'], ['brighton', 'parish', '508.30', '1834', '1402 of 5008'], ['wicklow', 'parish', '195.50', '1753', '1441 of 5008'], ['northampton', 'parish', '243.3... |
united states intelligence budget | https://en.wikipedia.org/wiki/United_States_intelligence_budget | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17198719-1.html.csv | comparative | the cia spends more on data collection than the defense intelligence program does . | {'row_1': '1', 'row_2': '5', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'administrating agencies by nip funds only', '0 central intelligence agency program'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose administrating agencies by nip funds only record fuzzily matches to ... | greater { hop { filter_eq { all_rows ; administrating agencies by nip funds only ; 0 central intelligence agency program } ; data collection } ; hop { filter_eq { all_rows ; administrating agencies by nip funds only ; 0 defense intelligence program } ; data collection } } = true | select the rows whose administrating agencies by nip funds only record fuzzily matches to 0 central intelligence agency program . take the data collection record of this row . select the rows whose administrating agencies by nip funds only record fuzzily matches to 0 defense intelligence program . take the data collect... | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'administrating agencies by nip funds only_7': 7, '0 central intelligence agency program_8': 8, 'data collection_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'administrating agencies by nip funds only_11': 11, '0 d... | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'administrating agencies by nip funds only_7': 'administrating agencies by nip funds only', '0 central intelligence agency program_8': '0 central intelligence agency program', 'data collect... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'administrating agencies by nip funds only_7': [0], '0 central intelligence agency program_8': [0], 'data collection_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'administrating agencies by nip fund... | ['administrating agencies by nip funds only', 'management and support', 'data collection', 'data processing and exploitation', 'total'] | [['0 central intelligence agency program', '1 , 8', '11 , 5', '00 0387', '14787'], ['0 consolidated cryptologic program', '5 , 2', '0 2 , 5', '1 , 6', '10 , 8'], ['0 national reconnaissance program', '1 , 8', '0 6 , 0', '2 , 5', '10 , 3'], ['0 national geospatial - intelligence program', '2 , 0', '000 0537', '1 , 4', '... |
1951 - 52 illinois fighting illini men 's basketball team | https://en.wikipedia.org/wiki/1951%E2%80%9352_Illinois_Fighting_Illini_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22824312-1.html.csv | count | a total of three players on the 1951 - 52 illinois fighting illini men 's basketball team were in the freshman class . | {'scope': 'all', 'criterion': 'equal', 'value': 'freshman', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'freshman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class record fuzzily matches to freshman .', 'tostr': 'filter_eq { all_rows ; class ; freshman }'}], 'result': '3', 'ind': 1, 'tostr': 'coun... | eq { count { filter_eq { all_rows ; class ; freshman } } ; 3 } = true | select the rows whose class record fuzzily matches to freshman . 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, 'class_5': 5, 'freshman_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', 'class_5': 'class', 'freshman_6': 'freshman', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'class_5': [0], 'freshman_6': [0], '3_7': [2]} | ['no', 'player', 'position', 'height', 'weight', 'class', 'hometown'] | [['9', 'elmer plew', 'guard', '6 - 0', '170', 'freshman', 'paris , illinois'], ['11', 'jim dutcher', 'forward', '6 - 3', '185', 'freshman', 'downers grove , illinois'], ['16', 'jim wright', 'guard', '6 - 0', '160', 'sophomore', 'lawrenceville , illinois'], ['19', 'james bredar', 'guard', '5 - 11', '167', 'junior', 'sal... |
neuza silva | https://en.wikipedia.org/wiki/Neuza_Silva | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16893837-4.html.csv | ordinal | neuza silva had their second match in 2003 on a clay surface . | {'row': '2', 'col': '3', 'order': '2', 'col_other': '6', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'surface'], 'result': 'clay', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; surface }'}, 'clay'], 'result': True, ... | eq { hop { nth_argmin { all_rows ; date ; 2 } ; surface } ; clay } = true | select the row whose date record of all rows is 2nd minimum . the surface record of this row is clay . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'surface_7': 7, 'clay_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'surface_7': 'surface', 'clay_8': 'clay'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'surface_7': [1], 'clay_8': [2]} | ['edition', 'round', 'date', 'partnering', 'against', 'surface', 'opponents', 'result'] | [['2002 fed cup europe / africa group i', 'rr', '26 april 2002', 'angela cardoso', 'georgia', 'clay', 'margalita chakhnashvili salome devidze', '4 - 6 , 3 - 6'], ['2003 fed cup europe / africa group ii', 'rr', '29 april - 1 may 2003', 'ana catarina nogueira', 'norway', 'clay', 'karoline borgersen ina sartz', '6 - 0 , 6... |
1956 cleveland browns season | https://en.wikipedia.org/wiki/1956_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10651573-1.html.csv | aggregation | the average attendance for games during the 1956 cleveland browns season was 43174 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '43174', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '43174', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '43174'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 43174 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 43174 } = true | the average of the attendance record of all rows is 43174 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '43174_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '43174_5': '43174'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '43174_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 10 , 1956', 'college all - stars at chicago', 'w 26 - 0', '75000'], ['2', 'august 19 , 1956', 'san francisco 49ers', 'l 28 - 17', '38741'], ['3', 'august 24 , 1956', 'los angeles rams', 'l 17 - 6', '40175'], ['4', 'september 1 , 1956', 'green bay packers', 'l 21 - 20', '15456'], ['5', 'september 7 , 1956... |
the chicago code | https://en.wikipedia.org/wiki/The_Chicago_Code | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27401228-1.html.csv | count | davey holmes wrote 2 episodes of the chicago code . | {'scope': 'all', 'criterion': 'equal', 'value': 'davey holmes', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'davey holmes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to davey holmes .', 'tostr': 'filter_eq { all_rows ; written by ; davey holmes }'}], 'result': '2... | eq { count { filter_eq { all_rows ; written by ; davey holmes } } ; 2 } = true | select the rows whose written by record fuzzily matches to davey holmes . 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, 'written by_5': 5, 'davey holmes_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', 'written by_5': 'written by', 'davey holmes_6': 'davey holmes', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'davey holmes_6': [0], '2_7': [2]} | ['no', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['1', 'pilot', 'charles mcdougall', 'shawn ryan', 'february 7 , 2011', '1ata79', '9.43'], ['2', 'hog butcher', 'clark johnson', 'patrick massett & john zinman', 'february 14 , 2011', '1ata01', '7.35'], ['3', 'gillis , chase & babyface', 'guy ferland', 'davey holmes', 'february 21 , 2011', '1ata09', '7.87'], ['4', 'cab... |
1989 masters tournament | https://en.wikipedia.org/wiki/1989_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514242-1.html.csv | count | three players had a to par count of +5 . | {'scope': 'all', 'criterion': 'equal', 'value': '+5', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'to par', '+5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose to par record fuzzily matches to +5 .', 'tostr': 'filter_eq { all_rows ; to par ; +5 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq {... | eq { count { filter_eq { all_rows ; to par ; +5 } } ; 3 } = true | select the rows whose to par record fuzzily matches to +5 . 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, 'to par_5': 5, '+5_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', 'to par_5': 'to par', '+5_6': '+5', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'to par_5': [0], '+5_6': [0], '3_7': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['ben crenshaw', 'united states', '1984', '284', '- 4', 't3'], ['seve ballesteros', 'spain', '1980 , 1983', '285', '- 3', 't5'], ['tom watson', 'united states', '1977 , 1981', '290', '+ 2', 't14'], ['jack nicklaus', 'united states', '1963 , 1965 , 1966 , 1984 , 1975 , 1986', '291', '+ 3', '18'], ['bernhard langer', 'w... |
wwfm | https://en.wikipedia.org/wiki/WWFM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12472016-2.html.csv | unique | w230aa is the only call sign with an erp w of 27 . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '27', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'erp w', '27'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose erp w record is equal to 27 .', 'tostr': 'filter_eq { all_rows ; erp w ; 27 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; er... | and { only { filter_eq { all_rows ; erp w ; 27 } } ; eq { hop { filter_eq { all_rows ; erp w ; 27 } ; call sign } ; w230aa } } = true | select the rows whose erp w record is equal to 27 . there is only one such row in the table . the call sign record of this unqiue row is w230aa . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'erp w_7': 7, '27_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'call sign_9': 9, 'w230aa_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'erp w_7': 'erp w', '27_8': '27', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'call sign_9': 'call sign', 'w230aa_10': 'w230aa'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'erp w_7': [0], '27_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'call sign_9': [2], 'w230aa_10': [3]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k216fw', '91.1 fm', 'steamboat springs , colorado', '10', 'd', 'fcc'], ['w224au', '92.7 fm', 'allentown , pennsylvania', '8', 'd', 'fcc'], ['w226aa', '93.1 fm', 'easton , pennsylvania', '150', 'd', 'fcc'], ['w245ac', '96.9 fm', 'harmony township , new jersey', '10', 'd', 'fcc'], ['w300ac', '107.9 fm', 'chatsworth , ... |
alexander kudryavtsev | https://en.wikipedia.org/wiki/Alexander_Kudryavtsev | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18621753-7.html.csv | unique | the eckental tournament was the only one in which alexander kudryavtsev used a carpet surface . | {'scope': 'all', 'row': '8', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'carpet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; tournament } ; eckental , germany } } = true | select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the tournament record of this unqiue row is eckental , germany . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'eckental , germany_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'carpet_8': 'carpet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'eckental , germany_10': 'eckental , germany'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'eckental , germany_10': [3]} | ['date', 'tournament', 'surface', 'partner', 'opponent in final', 'score'] | [['11 july 2004', 'oberstaufen , germany', 'clay', 'vadim davletshin', 'valentino pest alexander waske', '4 - 6 , 6 - 3 , 7 - 6'], ['27 may 2006', 'kiev , ukraine', 'clay', 'alexander krasnorutskiy', 'andrei stoliarov aleksandr yarmola', '6 - 3 , 3 - 6 , 6 - 2'], ['4 june 2006', 'cherkasy , ukraine', 'clay', 'alexander... |
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