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list of tvb series ( 1998 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%281998%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18493407-2.html.csv | superlative | the 1998 tvb series with the greatest number of episodes was " secret of the heart . " . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '2', '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', 'number of episodes'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; number of episodes }'}, 'english title ( chinese title )'], 'result': 'secret of the heart 天地豪情', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; number of episodes } ; english title ( chinese title ) }'}, 'secret of the heart 天地豪情'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; number of episodes } ; english title ( chinese title ) } ; secret of the heart 天地豪情 } = true', 'tointer': 'select the row whose number of episodes record of all rows is maximum . the english title ( chinese title ) record of this row is secret of the heart 天地豪情 .'} | eq { hop { argmax { all_rows ; number of episodes } ; english title ( chinese title ) } ; secret of the heart 天地豪情 } = true | select the row whose number of episodes record of all rows is maximum . the english title ( chinese title ) record of this row is secret of the heart 天地豪情 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'number of episodes_5': 5, 'english title (chinese title)_6': 6, 'secret of the heart 天地豪情_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'number of episodes_5': 'number of episodes', 'english title (chinese title)_6': 'english title ( chinese title )', 'secret of the heart 天地豪情_7': 'secret of the heart 天地豪情'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'number of episodes_5': [0], 'english title (chinese title)_6': [1], 'secret of the heart 天地豪情_7': [2]} | ['airing date', 'english title ( chinese title )', 'number of episodes', 'genre', 'official website'] | [['19 jan - 13 feb', 'a measure of love 緣來沒法擋', '20', 'modern drama', 'official website'], ['16 feb - 9 may', 'secret of the heart 天地豪情', '62', 'costume drama', 'official website'], ['11 may - 9 jun', 'crimes of passion 掃黃先鋒', '22', 'modern action', 'official website'], ['6 jul - 31 jul', 'armed reaction 陀槍師姐', '20', 'modern action', 'official website'], ['3 aug - 28 aug', 'rural hero 離島特警', '20', 'modern action', 'official website'], ['31 aug - 10 oct', 'healing hands 妙手仁心', '32', 'modern drama', 'official website'], ['12 oct - 4 dec', 'burning flame 烈火雄心', '43', 'modern action', 'official website'], ['7 dec 1998 - 1 jan 1999', 'till when do us part 冤家宜結不宜解', '20', 'modern drama', 'website']] |
b " uci road world championships - women 's road race " | https://en.wikipedia.org/wiki/UCI_Road_World_Championships_%E2%80%93_Women%27s_road_race | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1868008-2.html.csv | count | 17 nations were represented in the women 's uci road world championships . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '17', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'nation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record is arbitrary .', 'tostr': 'filter_all { all_rows ; nation }'}], 'result': '17', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; nation } }', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 17 .'}, '17'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; nation } } ; 17 } = true', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 17 .'} | eq { count { filter_all { all_rows ; nation } } ; 17 } = true | select the rows whose nation record is arbitrary . the number of such rows is 17 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'nation_5': 5, '17_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'nation_5': 'nation', '17_6': '17'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'nation_5': [0], '17_6': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'netherlands', '9', '12', '5', '26'], ['2', 'france', '9', '5', '2', '16'], ['3', 'belgium', '6', '6', '4', '16'], ['4', 'italy', '5', '6', '9', '20'], ['5', 'germany', '5', '1', '6', '12'], ['6', 'great britain', '4', '3', '3', '10'], ['7', 'russia +', '3', '7', '11', '21'], ['= 8', 'lithuania', '3', '2', '2', '7'], ['= 8', 'sweden', '3', '2', '2', '7'], ['10', 'united states', '2', '5', '3', '10'], ['11', 'switzerland', '1', '1', '0', '3'], ['12', 'luxembourg', '1', '0', '1', '2'], ['12', 'norway', '1', '0', '1', '2'], ['14', 'belarus', '1', '0', '0', '1'], ['15', 'australia', '0', '3', '1', '4'], ['16', 'canada', '0', '0', '2', '2'], ['17', 'spain', '0', '0', '1', '1']] |
1977 dallas cowboys season | https://en.wikipedia.org/wiki/1977_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15847691-2.html.csv | count | the dallas cowboys lost 2 games during the 1977 season . | {'scope': 'all', 'criterion': 'equal', 'value': 'loss', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'loss'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to loss .', 'tostr': 'filter_eq { all_rows ; result ; loss }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; loss } }', 'tointer': 'select the rows whose result record fuzzily matches to loss . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; loss } } ; 2 } = true', 'tointer': 'select the rows whose result record fuzzily matches to loss . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; result ; loss } } ; 2 } = true | select the rows whose result record fuzzily matches to loss . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'loss_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'loss_6': 'loss', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'loss_6': [0], '2_7': [2]} | ['week', 'date', 'result', 'record', 'opponent', 'points for', 'points against', 'first downs', 'attendance'] | [['1', 'september 18', 'win', '1 - 0', 'minnesota vikings', '16', '10', '16', '47678'], ['2', 'september 25', 'win', '2 - 0', 'new york giants', '41', '21', '25', '64215'], ['3', 'october 2', 'win', '3 - 0', 'tampa bay buccaneers', '23', '7', '23', '55316'], ['4', 'october 9', 'win', '4 - 0', 'st louis cardinals', '30', '24', '22', '50129'], ['5', 'october 16', 'win', '5 - 0', 'washington redskins', '34', '16', '23', '62115'], ['6', 'october 23', 'win', '6 - 0', 'philadelphia eagles', '16', '10', '17', '65507'], ['7', 'october 30', 'win', '7 - 0', 'detroit lions', '37', '0', '20', '63160'], ['8', 'november 6', 'win', '8 - 0', 'new york giants', '24', '10', '13', '74532'], ['9', 'november 14', 'loss', '8 - 1', 'st louis cardinals', '17', '24', '16', '64038'], ['10', 'november 20', 'loss', '8 - 2', 'pittsburgh steelers', '13', '28', '20', '49761'], ['11', 'november 27', 'win', '9 - 2', 'washington redskins', '14', '7', '19', '55031'], ['12', 'december 4', 'win', '10 - 2', 'philadelphia eagles', '24', '14', '19', '60289'], ['13', 'december 12', 'win', '11 - 2', 'san francisco 49ers', '42', '35', '24', '55851'], ['14', 'december 18', 'win', '12 - 2', 'denver broncos', '14', '6', '15', '63752']] |
1913 world wrestling championships | https://en.wikipedia.org/wiki/1913_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15980739-1.html.csv | unique | at the 1913 world wrestling championships , the only nation to win 5 total medals was germany . | {'scope': 'all', 'row': '2', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '5', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'total', '5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total record is equal to 5 .', 'tostr': 'filter_eq { all_rows ; total ; 5 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; total ; 5 } }', 'tointer': 'select the rows whose total record is equal to 5 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'total', '5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose total record is equal to 5 .', 'tostr': 'filter_eq { all_rows ; total ; 5 }'}, 'nation'], 'result': 'germany', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; total ; 5 } ; nation }'}, 'germany'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; total ; 5 } ; nation } ; germany }', 'tointer': 'the nation record of this unqiue row is germany .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; total ; 5 } } ; eq { hop { filter_eq { all_rows ; total ; 5 } ; nation } ; germany } } = true', 'tointer': 'select the rows whose total record is equal to 5 . there is only one such row in the table . the nation record of this unqiue row is germany .'} | and { only { filter_eq { all_rows ; total ; 5 } } ; eq { hop { filter_eq { all_rows ; total ; 5 } ; nation } ; germany } } = true | select the rows whose total record is equal to 5 . there is only one such row in the table . the nation record of this unqiue row is germany . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'total_7': 7, '5_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'germany_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'total_7': 'total', '5_8': '5', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'germany_10': 'germany'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'total_7': [0], '5_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'germany_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'sweden', '2', '2', '0', '4'], ['2', 'germany', '1', '1', '3', '5'], ['3', 'russia', '1', '0', '0', '1'], ['4', 'austria', '0', '1', '0', '1'], ['5', 'bohemia', '0', '0', '1', '1'], ['total', 'total', '4', '4', '4', '12']] |
icl 20s world series 2007 - 08 | https://en.wikipedia.org/wiki/ICL_20s_World_Series_2007%E2%80%9308 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17103566-1.html.csv | majority | the majority of matches were won by icl india by 4 wickets . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'icl india by 4 wickets', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'icl india by 4 wickets'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to icl india by 4 wickets .', 'tostr': 'most_eq { all_rows ; result ; icl india by 4 wickets } = true'} | most_eq { all_rows ; result ; icl india by 4 wickets } = true | for the result records of all rows , most of them fuzzily match to icl india by 4 wickets . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'icl india by 4 wickets_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'icl india by 4 wickets_4': 'icl india by 4 wickets'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'icl india by 4 wickets_4': [0]} | ['match number', 'date', 'venue', 'team 1', 'team 2', 'result', 'man of the match'] | [['1', 'april 9', 'hyderabad', 'icl world', 'icl india', 'icl world by 8 wickets', 'damien martyn ( icl world )'], ['2', 'april 10', 'hyderabad', 'icl pakistan', 'icl world', 'icl pakistan by 9 wickets', 'imran nazir ( icl pakistan )'], ['3', 'april 11', 'hyderabad', 'icl india', 'icl pakistan', 'icl india by 4 wickets', 'ibrahim khaleel ( icl india )'], ['4', 'april 12', 'hyderabad', 'icl india', 'icl world', 'icl india by 4 wickets', 'stuart binny ( icl india )'], ['5', 'april 13', 'hyderabad', 'icl india', 'icl pakistan', 'icl india by 4 wickets', 'tejinder pal singh ( icl india )']] |
indianapolis colts draft history | https://en.wikipedia.org/wiki/Indianapolis_Colts_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13312898-54.html.csv | superlative | joseph addai was the earliest drafted player for the indianapolis colts . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'round'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; round }'}, 'name'], 'result': 'joseph addai', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; round } ; name }'}, 'joseph addai'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; round } ; name } ; joseph addai } = true', 'tointer': 'select the row whose round record of all rows is minimum . the name record of this row is joseph addai .'} | eq { hop { argmin { all_rows ; round } ; name } ; joseph addai } = true | select the row whose round record of all rows is minimum . the name record of this row is joseph addai . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'round_5': 5, 'name_6': 6, 'joseph addai_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'round_5': 'round', 'name_6': 'name', 'joseph addai_7': 'joseph addai'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'round_5': [0], 'name_6': [1], 'joseph addai_7': [2]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '30', '30', 'joseph addai', 'running back', 'lsu'], ['2', '30', '62', 'tim jennings', 'cornerback', 'georgia'], ['3', '30', '94', 'freddie keiaho', 'linebacker', 'san diego state'], ['5', '29', '162', 'michael toudouze', 'guard', 'tcu'], ['6', '30', '199', 'charlie johnson', 'offensive tackle', 'oklahoma state'], ['6', '38', '207', 'antoine bethea', 'safety', 'howard'], ['7', '30', '238', 'tj rushing', 'cornerback', 'stanford']] |
lark rise to candleford ( tv series ) | https://en.wikipedia.org/wiki/Lark_Rise_to_Candleford_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15026994-5.html.csv | majority | the majority of the episodes from 1-5 had more than 7 million total viewers . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '7', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'viewing figure', '7'], 'result': True, 'ind': 0, 'tointer': 'for the viewing figure records of all rows , most of them are greater than 7 .', 'tostr': 'most_greater { all_rows ; viewing figure ; 7 } = true'} | most_greater { all_rows ; viewing figure ; 7 } = true | for the viewing figure records of all rows , most of them are greater than 7 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'viewing figure_3': 3, '7_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'viewing figure_3': 'viewing figure', '7_4': '7'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'viewing figure_3': [0], '7_4': [0]} | ['', 'episode', 'writer', 'director', 'original air date', 'viewing figure'] | [['35', 'episode 1', 'bill gallagher', 'sue tully', '9 january 2011', '7.68 million'], ['36', 'episode 2', 'bill gallagher', 'sue tully', '16 january 2011', '7.31 million'], ['37', 'episode 3', 'bill gallagher', 'sue tully', '23 january 2011', '7.02 million'], ['38', 'episode 4', 'rachel bennette', 'patrick lau', '30 january 2011', '6.90 million'], ['39', 'episode 5', 'bill gallagher', 'sue tully', '6 february 2011', '6.96 million']] |
liga mx | https://en.wikipedia.org/wiki/Liga_MX | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18143210-2.html.csv | ordinal | atlante had the third highest number of seasons in top division out of liga mix participants . | {'row': '2', 'col': '3', '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', 'number of seasons in top division', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; number of seasons in top division ; 3 }'}, 'club'], 'result': 'atlante', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; number of seasons in top division ; 3 } ; club }'}, 'atlante'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; number of seasons in top division ; 3 } ; club } ; atlante } = true', 'tointer': 'select the row whose number of seasons in top division record of all rows is 3rd maximum . the club record of this row is atlante .'} | eq { hop { nth_argmax { all_rows ; number of seasons in top division ; 3 } ; club } ; atlante } = true | select the row whose number of seasons in top division record of all rows is 3rd maximum . the club record of this row is atlante . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'number of seasons in top division_5': 5, '3_6': 6, 'club_7': 7, 'atlante_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', 'number of seasons in top division_5': 'number of seasons in top division', '3_6': '3', 'club_7': 'club', 'atlante_8': 'atlante'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'number of seasons in top division_5': [0], '3_6': [0], 'club_7': [1], 'atlante_8': [2]} | ['club', 'first season in top division', 'number of seasons in top division', 'first season of current spell in top division', 'number of seasons in liga mx', 'top division titles'] | [['américa', '1943 - 44', '89', '1943 - 44', '89', '11'], ['atlante', '1943 - 44', '87', '1991 - 92', '40', '3'], ['atlas', '1943 - 44', '86', '1979 - 80', '51', '1'], ['chiapas', '2002 - 03', '22', '2002 - 03', '22', '0'], ['cruz azul', '1964 - 65', '68', '1964 - 65', '68', '8'], ['guadalajara', '1943 - 44', '89', '1943 - 44', '89', '11'], ['león', '1944 - 45', '65', '2012 - 13', '2', '5'], ['monterrey', '1945 - 46', '74', '1960 - 61', '72', '4'], ['morelia', '1957 - 58', '61', '1981 - 82', '50', '1'], ['pachuca', '1967 - 68', '40', '1998 - 99', '30', '5'], ['puebla', '1944 - 45', '69', '2007 - 08', '12', '2'], ['querétaro', '1990 - 91', '18', '2009 - 10', '8', '0'], ['santos laguna', '1988 - 89', '42', '1988 - 89', '42', '4'], ['tijuana', '2011 - 12', '4', '2011 - 12', '4', '1'], ['toluca', '1953 - 54', '79', '1953 - 54', '79', '10'], ['uanl', '1974 - 75', '55', '1997 - 98', '32', '3'], ['unam', '1962 - 63', '70', '1962 - 63', '70', '7'], ['veracruz', '1943 - 44', '49', '2013 - 14', '0', '2']] |
2010 - 11 buffalo sabres season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Buffalo_Sabres_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27537870-3.html.csv | unique | game 6 was the only game in which the buffalo sabres decision was for lalime . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'lalime', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decision', 'lalime'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decision record fuzzily matches to lalime .', 'tostr': 'filter_eq { all_rows ; decision ; lalime }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; decision ; lalime } }', 'tointer': 'select the rows whose decision record fuzzily matches to lalime . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'decision', 'lalime'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose decision record fuzzily matches to lalime .', 'tostr': 'filter_eq { all_rows ; decision ; lalime }'}, 'game'], 'result': '6', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; decision ; lalime } ; game }'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; decision ; lalime } ; game } ; 6 }', 'tointer': 'the game record of this unqiue row is 6 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; decision ; lalime } } ; eq { hop { filter_eq { all_rows ; decision ; lalime } ; game } ; 6 } } = true', 'tointer': 'select the rows whose decision record fuzzily matches to lalime . there is only one such row in the table . the game record of this unqiue row is 6 .'} | and { only { filter_eq { all_rows ; decision ; lalime } } ; eq { hop { filter_eq { all_rows ; decision ; lalime } ; game } ; 6 } } = true | select the rows whose decision record fuzzily matches to lalime . there is only one such row in the table . the game record of this unqiue row is 6 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'decision_7': 7, 'lalime_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'game_9': 9, '6_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'decision_7': 'decision', 'lalime_8': 'lalime', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'game_9': 'game', '6_10': '6'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'decision_7': [0], 'lalime_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'game_9': [2], '6_10': [3]} | ['game', 'october', 'opponent', 'score', 'decision', 'location / attendance', 'record'] | [['1', '8', 'ottawa senators', '2 - 1', 'miller', 'scotiabank place / 19350', '1 - 0 - 0'], ['2', '9', 'new york rangers', '3 - 6', 'miller', 'hsbc arena / 18690', '1 - 1 - 0'], ['3', '11', 'chicago blackhawks', '3 - 4', 'miller', 'hsbc arena / 17896', '1 - 2 - 0'], ['4', '13', 'new jersey devils', '0 - 1 ( ot )', 'miller', 'hsbc arena / 18690', '1 - 2 - 1'], ['5', '15', 'montreal canadiens', '1 - 2', 'miller', 'hsbc arena / 17264', '1 - 3 - 1'], ['6', '16', 'chicago blackhawks', '3 - 4', 'lalime', 'united center / 21293', '1 - 4 - 1'], ['7', '20', 'atlanta thrashers', '4 - 1', 'miller', 'philips arena / 8820', '2 - 4 - 1'], ['8', '22', 'ottawa senators', '2 - 4', 'miller', 'hsbc arena / 18009', '2 - 5 - 1'], ['9', '23', 'new jersey devils', '6 - 1', 'miller', 'prudential center / 14228', '3 - 5 - 1'], ['10', '26', 'philadelphia flyers', '3 - 6', 'miller', 'wells fargo center / 19361', '3 - 6 - 1'], ['11', '29', 'atlanta thrashers', '3 - 4 ( ot )', 'miller', 'philips arena / 10172', '3 - 6 - 2']] |
fabio fognini | https://en.wikipedia.org/wiki/Fabio_Fognini | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11983898-4.html.csv | ordinal | the 2nd to last tournament for fabio fognini was when he faced federico delbonis in the final . | {'row': '4', 'col': '2', 'order': '4', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '4'], 'result': '21 july 2013', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 4 }', 'tointer': 'the 4th minimum date record of all rows is 21 july 2013 .'}, '21 july 2013'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; date ; 4 } ; 21 july 2013 }', 'tointer': 'the 4th minimum date record of all rows is 21 july 2013 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '4'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; date ; 4 }'}, 'opponent in the final'], 'result': 'federico delbonis', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; date ; 4 } ; opponent in the final }'}, 'federico delbonis'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 4 } ; opponent in the final } ; federico delbonis }', 'tointer': 'the opponent in the final record of the row with 4th minimum date record is federico delbonis .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; date ; 4 } ; 21 july 2013 } ; eq { hop { nth_argmin { all_rows ; date ; 4 } ; opponent in the final } ; federico delbonis } } = true', 'tointer': 'the 4th minimum date record of all rows is 21 july 2013 . the opponent in the final record of the row with 4th minimum date record is federico delbonis .'} | and { eq { nth_min { all_rows ; date ; 4 } ; 21 july 2013 } ; eq { hop { nth_argmin { all_rows ; date ; 4 } ; opponent in the final } ; federico delbonis } } = true | the 4th minimum date record of all rows is 21 july 2013 . the opponent in the final record of the row with 4th minimum date record is federico delbonis . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'date_8': 8, '4_9': 9, '21 july 2013_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'date_12': 12, '4_13': 13, 'opponent in the final_14': 14, 'federico delbonis_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'date_8': 'date', '4_9': '4', '21 july 2013_10': '21 july 2013', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'date_12': 'date', '4_13': '4', 'opponent in the final_14': 'opponent in the final', 'federico delbonis_15': 'federico delbonis'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'date_8': [0], '4_9': [0], '21 july 2013_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'date_12': [2], '4_13': [2], 'opponent in the final_14': [3], 'federico delbonis_15': [4]} | ['outcome', 'date', 'tournament', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '29 april 2012', 'brd năstase ţiriac trophy , bucharest , romania', 'clay', 'gilles simon', '4 - 6 , 3 - 6'], ['runner - up', '23 september 2012', 'st petersburg open , st petersburg , russia', 'hard ( i )', 'martin kližan', '2 - 6 , 3 - 6'], ['winner', '14 july 2013', 'stuttgart open , stuttgart , germany', 'clay', 'philipp kohlschreiber', '5 - 7 , 6 - 4 , 6 - 4'], ['winner', '21 july 2013', 'international german open , hamburg , germany', 'clay', 'federico delbonis', '4 - 6 , 7 - 6 ( 10 - 8 ) , 6 - 2'], ['runner - up', '28 july 2013', 'atp vegeta croatia open umag , umag , croatia', 'clay', 'tommy robredo', '0 - 6 , 3 - 6']] |
2008 - 09 segunda división b | https://en.wikipedia.org/wiki/2008%E2%80%9309_Segunda_Divisi%C3%B3n_B | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18160020-8.html.csv | superlative | of top five goalkeepers in the 2008-09 segunda división , orlando quintana played the most matches . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'matches'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; matches }'}, 'goalkeeper'], 'result': 'orlando quintana', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; matches } ; goalkeeper }'}, 'orlando quintana'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; matches } ; goalkeeper } ; orlando quintana } = true', 'tointer': 'select the row whose matches record of all rows is maximum . the goalkeeper record of this row is orlando quintana .'} | eq { hop { argmax { all_rows ; matches } ; goalkeeper } ; orlando quintana } = true | select the row whose matches record of all rows is maximum . the goalkeeper record of this row is orlando quintana . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'matches_5': 5, 'goalkeeper_6': 6, 'orlando quintana_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'matches_5': 'matches', 'goalkeeper_6': 'goalkeeper', 'orlando quintana_7': 'orlando quintana'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'matches_5': [0], 'goalkeeper_6': [1], 'orlando quintana_7': [2]} | ['goalkeeper', 'goals', 'matches', 'average', 'team'] | [['miguel zapata', '17', '28', '0.61', 'atlético ciudad'], ['rubén martínez', '24', '32', '0.75', 'cartagena'], ['orlando quintana', '29', '34', '0.85', 'lorca deportiva'], ['álvaro campos', '24', '28', '0.86', 'real murcia b'], ['matías garavano', '26', '30', '0.87', 'mérida']] |
list of csi : ny characters | https://en.wikipedia.org/wiki/List_of_CSI%3A_NY_characters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11240028-3.html.csv | count | two characters on csi : ny were related to mac taylor . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'mac taylor', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'relationship', 'mac taylor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose relationship record fuzzily matches to mac taylor .', 'tostr': 'filter_eq { all_rows ; relationship ; mac taylor }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; relationship ; mac taylor } }', 'tointer': 'select the rows whose relationship record fuzzily matches to mac taylor . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; relationship ; mac taylor } } ; 2 } = true', 'tointer': 'select the rows whose relationship record fuzzily matches to mac taylor . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; relationship ; mac taylor } } ; 2 } = true | select the rows whose relationship record fuzzily matches to mac taylor . 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, 'relationship_5': 5, 'mac taylor_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', 'relationship_5': 'relationship', 'mac taylor_6': 'mac taylor', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'relationship_5': [0], 'mac taylor_6': [0], '2_7': [2]} | ['character', 'portrayed by', 'relationship', 'first appearance', 'last appearance'] | [['reed garrett', 'kyle gallner', "son of mac taylor 's late wife", 'consequences', 'pot of gold'], ['rikki sandoval', 'jacqueline piã ± ol', 'neighbor of danny messer', "child 's play", 'personal foul'], ['samantha flack', 'kathleen munroe', 'sister of don flack', 'veritas', 'misconceptions'], ['terrence davis', 'nelly', 'informant of don flack', 'turbulence', "cuckoo 's nest"], ['ellie danville', 'sydney park', 'adopted daughter of jo danville', 'do not pass go', '2918 miles'], ['russ josephson', 'david james elliott', 'ex - husband of jo danville', 'to what end', 'identity crisis'], ['claire conrad taylor', 'jaime ray newman', 'late wife of mac taylor', 'indelible', 'near death']] |
rógvi jacobsen | https://en.wikipedia.org/wiki/R%C3%B3gvi_Jacobsen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11559634-1.html.csv | aggregation | rogvi jacobsen scored a total of 12 points throughout the competitions listed in the table . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '12', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '12', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '12'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 12 } = true', 'tointer': 'the sum of the score record of all rows is 12 .'} | round_eq { sum { all_rows ; score } ; 12 } = true | the sum of the score record of all rows is 12 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '12_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '12_5': '12'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '12_5': [1]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', '10 february 2002', '1 - 1', '1 - 2', 'friendly'], ['2', '7 june 2003', '1 - 1', '1 - 2', '2004 euro qualifying'], ['3', '20 august 2003', '1 - 1', '1 - 2', '2004 euro qualifying'], ['4', '18 august 2004', '2 - 0', '3 - 2', 'friendly'], ['5', '9 october 2004', '2 - 1', '2 - 2', '2006 wc qualifying'], ['6', '5 june 2005', '1 - 1', '1 - 3', '2006 wc qualifying'], ['7', '28 march 2007', '1 - 2', '1 - 3', '2008 euro qualifying'], ['8', '2 june 2007', '1 - 2', '1 - 2', '2008 euro qualifying'], ['9', '12 september 2007', '1 - 2', '1 - 2', '2008 euro qualifying'], ['10', '21 november 2007', '1 - 3', '1 - 3', '2008 euro qualifying']] |
list of districts of west bengal | https://en.wikipedia.org/wiki/List_of_districts_of_West_Bengal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2527063-3.html.csv | unique | kolkata is the only district in west bengal that has a negative growth rate . | {'scope': 'all', 'row': '10', 'col': '4', 'col_other': '2', 'criterion': 'less_than', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'growth rate', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose growth rate record is less than 0 .', 'tostr': 'filter_less { all_rows ; growth rate ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; growth rate ; 0 } }', 'tointer': 'select the rows whose growth rate record is less than 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'growth rate', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose growth rate record is less than 0 .', 'tostr': 'filter_less { all_rows ; growth rate ; 0 }'}, 'district'], 'result': 'kolkata', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; growth rate ; 0 } ; district }'}, 'kolkata'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; growth rate ; 0 } ; district } ; kolkata }', 'tointer': 'the district record of this unqiue row is kolkata .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; growth rate ; 0 } } ; eq { hop { filter_less { all_rows ; growth rate ; 0 } ; district } ; kolkata } } = true', 'tointer': 'select the rows whose growth rate record is less than 0 . there is only one such row in the table . the district record of this unqiue row is kolkata .'} | and { only { filter_less { all_rows ; growth rate ; 0 } } ; eq { hop { filter_less { all_rows ; growth rate ; 0 } ; district } ; kolkata } } = true | select the rows whose growth rate record is less than 0 . there is only one such row in the table . the district record of this unqiue row is kolkata . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'growth rate_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'district_9': 9, 'kolkata_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'growth rate_7': 'growth rate', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_9': 'district', 'kolkata_10': 'kolkata'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'growth rate_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'district_9': [2], 'kolkata_10': [3]} | ['rank', 'district', 'population', 'growth rate', 'sex ratio', 'literacy', 'density / km'] | [['2', 'north 24 parganas', '10082852', '12.86', '949', '84.95', '2463'], ['6', 'south 24 parganas', '8153176', '18.05', '949', '78.57', '819'], ['7', 'barddhaman', '7723663', '12.01', '943', '77.15', '1100'], ['9', 'murshidabad', '7102430', '21.07', '957', '67.53', '1334'], ['14', 'west midnapore', '5943300', '14.44', '960', '79.04', '636'], ['16', 'hooghly', '5520389', '9.49', '958', '82.55', '1753'], ['18', 'nadia', '5168488', '12.24', '947', '75.58', '1316'], ['20', 'east midnapore', '5094238', '15.32', '936', '87.66', '1076'], ['23', 'haora', '4841638', '13.31', '935', '83.85', '3300'], ['35', 'kolkata', '4486679', '- 1.88', '899', '87.14', '24252'], ['58', 'maldah', '3997970', '21.50', '939', '62.71', '1071'], ['66', 'jalpaiguri', '3869675', '13.77', '954', '73.79', '621'], ['80', 'bankura', '3596292', '12.64', '954', '70.95', '523'], ['84', 'birbhum', '3502387', '16.15', '956', '70.90', '771'], ['124', 'north dinajpur', '3000849', '22.90', '936', '60.13', '956'], ['129', 'puruliya', '2927965', '15.43', '955', '65.38', '468'], ['136', 'kochbihar', '2822780', '13.86', '942', '75.49', '833'], ['257', 'darjiling', '1842034', '14.47', '971', '79.92', '585']] |
1970 in paleontology | https://en.wikipedia.org/wiki/1970_in_paleontology | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15678221-2.html.csv | count | six specimens were found in the united states in the year of 1970 . | {'scope': 'all', 'criterion': 'equal', 'value': 'usa', 'result': '6', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to usa .', 'tostr': 'filter_eq { all_rows ; location ; usa }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; usa } }', 'tointer': 'select the rows whose location record fuzzily matches to usa . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; usa } } ; 6 } = true', 'tointer': 'select the rows whose location record fuzzily matches to usa . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; location ; usa } } ; 6 } = true | select the rows whose location record fuzzily matches to usa . 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, 'location_5': 5, 'usa_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', 'location_5': 'location', 'usa_6': 'usa', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'usa_6': [0], '6_7': [2]} | ['name', 'novelty', 'status', 'authors', 'unit', 'location'] | [['daspletosaurus', 'gen et sp nov', 'valid', 'russell', 'oldman formation', 'usa'], ['deinocheirus', 'fam , gen et sp nov', 'valid', 'osmã cubiclska & roniewicz', 'nemegt formation', 'mongolia'], ['dilophosaurus', 'gen nov', 'valid', 'welles', 'kayenta formation', 'usa'], ['likhoelesaurus', 'gen et sp nov', 'nomen nudum', 'ellenberger', 'lower elliot formation', 'south africa'], ['megadontosaurus', 'gen et sp nov', 'nomen nudum', 'brown vide : ostrom', 'cloverly formation', 'usa'], ['microvenator', 'gen et sp nov', 'valid', 'ostrom', 'cloverly formation', 'usa'], ['sauropelta', 'gen et sp nov', 'valid', 'ostrom', 'cloverly formation', 'usa'], ['staurikosaurus', 'gen et sp nov', 'valid', 'colbert', 'santa maria formation', 'brazil'], ['tenontosaurus', 'gen et sp nov', 'valid', 'ostrom', 'cloverly formation', 'usa']] |
list of people in playboy 1990 - 99 | https://en.wikipedia.org/wiki/List_of_people_in_Playboy_1990%E2%80%9399 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1566850-6.html.csv | comparative | rhonda adams modeled for playboy magazine earlier than alicia rickter did . | {'row_1': '6', 'row_2': '10', 'col': '1', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '6 - 95'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 6 - 95 .', 'tostr': 'filter_eq { all_rows ; date ; 6 - 95 }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 6 - 95 } ; date }', 'tointer': 'select the rows whose date record fuzzily matches to 6 - 95 . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '10 - 95'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 10 - 95 .', 'tostr': 'filter_eq { all_rows ; date ; 10 - 95 }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 10 - 95 } ; date }', 'tointer': 'select the rows whose date record fuzzily matches to 10 - 95 . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; date ; 6 - 95 } ; date } ; hop { filter_eq { all_rows ; date ; 10 - 95 } ; date } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 6 - 95 . take the date record of this row . select the rows whose date record fuzzily matches to 10 - 95 . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; date ; 6 - 95 } ; date } ; hop { filter_eq { all_rows ; date ; 10 - 95 } ; date } } = true | select the rows whose date record fuzzily matches to 6 - 95 . take the date record of this row . select the rows whose date record fuzzily matches to 10 - 95 . 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, 'date_7': 7, '6 - 95_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '10 - 95_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', 'date_7': 'date', '6 - 95_8': '6 - 95', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '10 - 95_12': '10 - 95', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '6 - 95_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '10 - 95_12': [1], 'date_13': [3]} | ['date', 'cover model', 'centerfold model', 'interview subject', '20 questions'] | [['1 - 95', 'drew barrymore', 'melissa deanne holliday', 'jean - claude van damme', 'tom snyder'], ['2 - 95', 'victoria jacobs', 'lisa marie scott', 'tim robbins', 'david spade'], ['3 - 95', 'amber smith', 'stacy sanches', 'vladimir zhirinovsky', 'jon stewart'], ['4 - 95', 'shana hiatt', 'danelle folta', 'david mamet', 'samuel l jackson'], ['5 - 95', 'nancy sinatra', 'cynthia gwyn brown', 'camille paglia', 'david hasselhoff'], ['6 - 95', 'julie lynn cialini', 'rhonda adams', 'joycelyn elders', 'tom arnold'], ['7 - 95', 'sandra taylor', 'heidi mark', 'mel gibson', 'kurt loder'], ['8 - 95', 'shelly jones', 'rachel jeã ¡ n marteen', 'berry gordy', 'dawn steel'], ['9 - 95', 'kimberley conrad hefner', "donna d'errico", 'cindy crawford', 'sandra bullock'], ['10 - 95', 'lisa boyle', 'alicia rickter', 'snoop doggy dogg', 'bill maher'], ['11 - 95', 'tahnee welch', 'holly witt', 'harvey keitel', 'g gordon liddy'], ['12 - 95', 'farrah fawcett', 'samantha torres', 'george foreman', 'dominick dunne']] |
united states house of representatives elections , 1988 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1988 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341577-22.html.csv | count | three of the united states house of representatives incumbents were first elected in the 1970s . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '197', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first elected', '197'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record fuzzily matches to 197 .', 'tostr': 'filter_eq { all_rows ; first elected ; 197 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first elected ; 197 } }', 'tointer': 'select the rows whose first elected record fuzzily matches to 197 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first elected ; 197 } } ; 3 } = true', 'tointer': 'select the rows whose first elected record fuzzily matches to 197 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; first elected ; 197 } } ; 3 } = true | select the rows whose first elected record fuzzily matches to 197 . 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, 'first elected_5': 5, '197_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', 'first elected_5': 'first elected', '197_6': '197', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '197_6': [0], '3_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['massachusetts 1', 'silvio conte', 'republican', '1958', 're - elected', 'silvio conte ( r ) 82.7 % john r arden ( d ) 17.3 %'], ['massachusetts 2', 'edward boland', 'democratic', '1952', 'retired democratic hold', 'richard neal ( d ) 80.3 % louis r godena ( i ) 19.7 %'], ['massachusetts 3', 'joseph d early', 'democratic', '1974', 're - elected', 'joseph d early ( d ) unopposed'], ['massachusetts 4', 'barney frank', 'democratic', '1980', 're - elected', 'barney frank ( d ) 70.3 % debra r tucker ( r ) 29.7 %'], ['massachusetts 7', 'ed markey', 'democratic', '1976', 're - elected', 'ed markey ( d ) unopposed'], ['massachusetts 9', 'joe moakley', 'democratic', '1972', 're - elected', 'joe moakley ( d ) unopposed']] |
list of number - one singles of 2000 ( canada ) | https://en.wikipedia.org/wiki/List_of_number-one_singles_of_2000_%28Canada%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17507197-1.html.csv | aggregation | all songs in the number - one singles list of 2000 were on top for an average of around 3 weeks . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weeks on top'], 'result': '3', 'ind': 0, 'tostr': 'avg { all_rows ; weeks on top }'}, '3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weeks on top } ; 3 } = true', 'tointer': 'the average of the weeks on top record of all rows is 3 .'} | round_eq { avg { all_rows ; weeks on top } ; 3 } = true | the average of the weeks on top record of all rows is 3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weeks on top_4': 4, '3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weeks on top_4': 'weeks on top', '3_5': '3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weeks on top_4': [0], '3_5': [1]} | ['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist'] | [['70:8 - 9', '13 december - 3 january 2000 ÷', '2 ÷', 'blue', 'eiffel 65'], ['70:10 - 11', '10 january - 17 january', '2', 'i knew i loved you', 'savage garden'], ['70:12', '24 january', '1', 'what a girl wants', 'christina aguilera'], ['70:13 - 14', '31 january - 7 february', '2', 'i knew i loved you', 'savage garden'], ['70:15 - 16', '14 february - 21 february', '2', 'what a girl wants', 'christina aguilera'], ['70:17 - 18', '28 february - 6 march', '2', 'show me the meaning of being lonely', 'backstreet boys'], ['70:19', '13 march', '1', 'faded', 'souldecision'], ['70:20', '20 march', '1', 'bye bye bye', "'n sync"], ['70:21 - 23', '27 march - 10 april', '3', 'never let you go', 'third eye blind'], ['70:23', '17 april', '1', 'maria maria', 'santana featuring the product g & b'], ['70:24 - 25 , 71:1 - 3', '24 april - 22 may', '5', 'it feels so good', 'sonique'], ['71:4 - 9', '29 may - 3 july', '6', 'oops ! … i did it again', 'britney spears'], ['71:10 - 12', '10 july - 24 july', '3', "it 's gon na be me", "'n sync"], ['71:13 - 14', '31 july - 7 august', '2', 'bent', 'matchbox twenty'], ['71:15', '14 august', '1', 'bang bang boom', 'the moffatts'], ['71:16 - 18', '21 august - 4 september', '3', 'bent', 'matchbox twenty'], ['71:19 - 26', '11 september - 6 november', '9', 'music', 'madonna']] |
eurovision song contest 1985 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1985 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-185276-2.html.csv | ordinal | in the 1985 eurovision song contest , the 2nd highest number of points was for the song für alle . | {'row': '10', 'col': '6', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 2 }'}, 'song'], 'result': 'für alle', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 2 } ; song }'}, 'für alle'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points ; 2 } ; song } ; für alle } = true', 'tointer': 'select the row whose points record of all rows is 2nd maximum . the song record of this row is für alle .'} | eq { hop { nth_argmax { all_rows ; points ; 2 } ; song } ; für alle } = true | select the row whose points record of all rows is 2nd maximum . the song record of this row is für alle . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '2_6': 6, 'song_7': 7, 'für alle_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', '2_6': '2', 'song_7': 'song', 'für alle_8': 'für alle'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '2_6': [0], 'song_7': [1], 'für alle_8': [2]} | ['draw', 'language', 'song', 'english translation', 'place', 'points'] | [['01', 'english', 'wait until the weekend comes', '-', '6', '91'], ['02', 'finnish', 'eläköön elämä', 'long live life', '9', '58'], ['03', 'greek', 'to katalava arga ( το κατάλαβα αργά )', 'i realised it too late', '16', '15'], ['04', 'danish', "sku ' du spørg ' fra no'en", 'what business is it of yours', '11', '41'], ['05', 'spanish', 'la fiesta terminó', "the party 's over", '14', '36'], ['06', 'french', 'femme dans ses rêves aussi', 'woman in her dreams too', '10', '56'], ['07', 'turkish', 'didai didai dai', '-', '14', '36'], ['08', 'dutch', 'laat me nu gaan', 'let me go now', '19', '7'], ['09', 'portuguese', 'penso em ti , eu sei', 'thinking of you , i know', '18', '9'], ['10', 'german', 'für alle', 'for everyone', '2', '105'], ['11', 'hebrew', 'olé , olé ( עולה , עולה )', 'going up and up', '5', '93'], ['12', 'italian', 'magic oh magic', '-', '7', '78'], ['13', 'norwegian', 'la det swinge', 'let it swing', '1', '123'], ['14', 'english', 'love is', '-', '4', '100'], ['15', 'german', 'piano , piano', 'slowly , slowly', '12', '39'], ['16', 'swedish', 'bra vibrationer', 'good vibrations', '3', '103'], ['17', 'german', 'kinder dieser welt', 'children of this world', '8', '60'], ['18', 'french', 'children , kinder , enfants', 'children', '13', '37'], ['19', 'greek', 'miazoume ( μοιάζουμε )', 'we are alike', '16', '15']] |
1979 vfl season | https://en.wikipedia.org/wiki/1979_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823719-13.html.csv | ordinal | the game at princes park had the 2nd highest crowd in the 1979 vfl season . | {'row': '2', 'col': '6', 'order': '2', 'col_other': '5', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 2 }'}, 'venue'], 'result': 'princes park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 2 } ; venue }'}, 'princes park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; princes park } = true', 'tointer': 'select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is princes park .'} | eq { hop { nth_argmax { all_rows ; crowd ; 2 } ; venue } ; princes park } = true | select the row whose crowd record of all rows is 2nd maximum . the venue record of this row is princes park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '2_6': 6, 'venue_7': 7, 'princes park_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '2_6': '2', 'venue_7': 'venue', 'princes park_8': 'princes park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '2_6': [0], 'venue_7': [1], 'princes park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['collingwood', '25.19 ( 169 )', 'hawthorn', '8.16 ( 64 )', 'victoria park', '22903', '30 june 1979'], ['carlton', '21.12 ( 138 )', 'richmond', '12.10 ( 82 )', 'princes park', '21792', '30 june 1979'], ['north melbourne', '8.21 ( 69 )', 'footscray', '12.9 ( 81 )', 'arden street oval', '13925', '30 june 1979'], ['south melbourne', '15.20 ( 110 )', 'fitzroy', '20.16 ( 136 )', 'lake oval', '13850', '30 june 1979'], ['st kilda', '9.12 ( 66 )', 'essendon', '15.15 ( 105 )', 'moorabbin oval', '18802', '30 june 1979'], ['geelong', '16.12 ( 108 )', 'melbourne', '9.3 ( 57 )', 'vfl park', '13272', '30 june 1979']] |
1997 - 98 manchester united f.c. season | https://en.wikipedia.org/wiki/1997%E2%80%9398_Manchester_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13599021-7.html.csv | comparative | the match on 27 november 1997 had higher attendance than the match on 10 december 1997 . | {'row_1': '5', 'row_2': '6', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '27 november 1997'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 27 november 1997 .', 'tostr': 'filter_eq { all_rows ; date ; 27 november 1997 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 27 november 1997 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to 27 november 1997 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '10 december 1997'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 10 december 1997 .', 'tostr': 'filter_eq { all_rows ; date ; 10 december 1997 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 10 december 1997 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to 10 december 1997 . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; 27 november 1997 } ; attendance } ; hop { filter_eq { all_rows ; date ; 10 december 1997 } ; attendance } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 27 november 1997 . take the attendance record of this row . select the rows whose date record fuzzily matches to 10 december 1997 . take the attendance record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; 27 november 1997 } ; attendance } ; hop { filter_eq { all_rows ; date ; 10 december 1997 } ; attendance } } = true | select the rows whose date record fuzzily matches to 27 november 1997 . take the attendance record of this row . select the rows whose date record fuzzily matches to 10 december 1997 . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '27 november 1997_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '10 december 1997_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '27 november 1997_8': '27 november 1997', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '10 december 1997_12': '10 december 1997', 'attendance_13': 'attendance'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '27 november 1997_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '10 december 1997_12': [1], 'attendance_13': [3]} | ['date', 'opponents', 'result f - a', 'attendance', 'group position'] | [['17 september 1997', 'košice', '3 - 0', '9950', '2nd'], ['1 october 1997', 'juventus', '3 - 2', '53428', '1st'], ['22 october 1997', 'feyenoord', '2 - 1', '53188', '1st'], ['5 november 1997', 'feyenoord', '3 - 1', '51000', '1st'], ['27 november 1997', 'košice', '3 - 0', '53535', '1st'], ['10 december 1997', 'juventus', '0 - 1', '47786', '1st']] |
list of via c3 microprocessors | https://en.wikipedia.org/wiki/List_of_VIA_C3_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16341329-2.html.csv | superlative | the highest frequency of any of the models is 1000 mhz . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '9', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'frequency'], 'result': '1000 mhz', 'ind': 0, 'tostr': 'max { all_rows ; frequency }', 'tointer': 'the maximum frequency record of all rows is 1000 mhz .'}, '1000 mhz'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; frequency } ; 1000 mhz } = true', 'tointer': 'the maximum frequency record of all rows is 1000 mhz .'} | eq { max { all_rows ; frequency } ; 1000 mhz } = true | the maximum frequency record of all rows is 1000 mhz . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'frequency_4': 4, '1000 mhz_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'frequency_4': 'frequency', '1000 mhz_5': '1000 mhz'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'frequency_4': [0], '1000 mhz_5': [1]} | ['model number', 'frequency', 'l2 - cache', 'front side bus', 'multiplier', 'voltage', 'socket'] | [['c3 800', '800 mhz', '64 kib', '100 mhz', '8', '1.35 v', 'socket 370'], ['c3 800', '800 mhz', '64 kib', '133 mhz', '6', '1.35 v', 'socket 370'], ['c3 800t', '800 mhz', '64kib', '133 mhz', '6', '1.35 v', 'socket 370'], ['c3 850', '850 mhz', '64kib', '100 mhz', '8.5', '1.35 v', 'socket 370'], ['c3 866', '866 mhz', '64 kib', '133 mhz', '6.5', '1.35 v', 'socket 370'], ['c3 866t', '866 mhz', '64 kib', '133 mhz', '6.5', '1.35 v', 'socket 370'], ['c3 900', '900 mhz', '64kib', '100 mhz', '9', '1.35 v', 'socket 370'], ['c3 933t', '933 mhz', '64kib', '133 mhz', '7', '1.35 v', 'socket 370'], ['c3 1.0 t', '1000 mhz', '64kib', '133 mhz', '7.5', '1.35 v', 'socket 370']] |
christian heritage party of canada candidates , 2008 canadian federal election | https://en.wikipedia.org/wiki/Christian_Heritage_Party_of_Canada_candidates%2C_2008_Canadian_federal_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12890254-6.html.csv | superlative | in the christian heritage party micheal mackay ranks the highest . | {'scope': 'all', 'col_superlative': '7', '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 }'}, "candidate 's name"], 'result': 'michael mackay', 'ind': 1, 'tostr': "hop { argmin { all_rows ; rank } ; candidate 's name }"}, 'michael mackay'], 'result': True, 'ind': 2, 'tostr': "eq { hop { argmin { all_rows ; rank } ; candidate 's name } ; michael mackay } = true", 'tointer': "select the row whose rank record of all rows is minimum . the candidate 's name record of this row is michael mackay ."} | eq { hop { argmin { all_rows ; rank } ; candidate 's name } ; michael mackay } = true | select the row whose rank record of all rows is minimum . the candidate 's name record of this row is michael mackay . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, "candidate 's name_6": 6, 'michael mackay_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', "candidate 's name_6": "candidate 's name", 'michael mackay_7': 'michael mackay'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], "candidate 's name_6": [1], 'michael mackay_7': [2]} | ['riding', "candidate 's name", 'gender', 'residence', 'occupation', 'votes', 'rank'] | [['central nova', 'michael mackay', 'm', 'west river station', 'retail', '427', '4th'], ['dartmouth-cole harbour', 'george campbell', 'm', 'dartmouth', 'minister', '219', '5th'], ['halifax west', 'trevor ennis', 'm', 'halifax', 'swimming pool salesman', '257', '5th'], ['kings-hants', 'jim hnatiuk', 'm', 'enfield', 'combat systems technician', '528', '5th'], ["south shore-st margaret 's", 'joe larkin', 'm', 'shag harbour', 'retired', '513', '5th']] |
1938 washington redskins season | https://en.wikipedia.org/wiki/1938_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15125111-1.html.csv | aggregation | in the 1938 washington redskins season , the total attendance for games in the month of september was 70000 . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '70000', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'september'}} | {'func': 'round_eq', 'args': [{'func': 'sum', '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 .'}, 'attendance'], 'result': '70000', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; september } ; attendance }'}, '70000'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; september } ; attendance } ; 70000 } = true', 'tointer': 'select the rows whose date record fuzzily matches to september . the sum of the attendance record of these rows is 70000 .'} | round_eq { sum { filter_eq { all_rows ; date ; september } ; attendance } ; 70000 } = true | select the rows whose date record fuzzily matches to september . the sum of the attendance record of these rows is 70000 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'september_6': 6, 'attendance_7': 7, '70000_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'september_6': 'september', 'attendance_7': 'attendance', '70000_8': '70000'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'september_6': [0], 'attendance_7': [1], '70000_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 11 , 1938', 'philadelphia eagles', 'w 26 - 23', '20000'], ['2', 'september 18 , 1938', 'brooklyn dodgers', 't 16 - 16', '23000'], ['3', 'september 25 , 1938', 'cleveland rams', 'w 37 - 13', '27000'], ['4', 'october 9 , 1938', 'new york giants', 'l 10 - 7', '37500'], ['5', 'october 16 , 1938', 'detroit lions', 'w 7 - 5', '42855'], ['6', 'october 23 , 1938', 'philadelphia eagles', 'w 20 - 14', '3000'], ['7', 'october 30 , 1938', 'brooklyn dodgers', 't 6 - 6', '29913'], ['8', 'november 6 , 1938', 'pittsburgh pirates', 'w 7 - 0', '12910'], ['9', 'november 13 , 1938', 'chicago bears', 'l 31 - 7', '21817'], ['10', 'november 27 , 1938', 'pittsburgh pirates', 'w 15 - 0', '12910'], ['11', 'december 4 , 1938', 'new york giants', 'l 36 - 0', '57461']] |
1956 - 57 fa cup | https://en.wikipedia.org/wiki/1956%E2%80%9357_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17540875-5.html.csv | aggregation | in the fourth round of the 1956 -57 fa cup , the home team scored an average of 2.375 goals . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '2.375', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '2.375', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '2.375'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 2.375 } = true', 'tointer': 'the average of the score record of all rows is 2.375 .'} | round_eq { avg { all_rows ; score } ; 2.375 } = true | the average of the score record of all rows is 2.375 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '2.375_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '2.375_5': '2.375'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '2.375_5': [1]} | ['tie no', 'home team', 'score', 'away team', 'date'] | [['1', 'blackpool', '6 - 2', 'fulham', '26 january 1957'], ['2', 'bristol city', '3 - 0', 'rhyl', '26 january 1957'], ['3', 'burnley', '9 - 0', 'new brighton', '26 january 1957'], ['4', 'wolverhampton wanderers', '0 - 1', 'bournemouth & boscombe athletic', '26 january 1957'], ['5', 'middlesbrough', '2 - 3', 'aston villa', '26 january 1957'], ['6', 'west bromwich albion', '4 - 2', 'sunderland', '26 january 1957'], ['7', 'everton', '2 - 1', 'west ham united', '26 january 1957'], ['8', 'wrexham', '0 - 5', 'manchester united', '26 january 1957'], ['9', 'tottenham hotspur', '4 - 0', 'chelsea', '26 january 1957'], ['10', 'bristol rovers', '1 - 4', 'preston north end', '26 january 1957'], ['11', 'portsmouth', '1 - 3', 'nottingham forest', '26 january 1957'], ['12', 'millwall', '2 - 1', 'newcastle united', '26 january 1957'], ['13', 'southend united', '1 - 6', 'birmingham city', '26 january 1957'], ['14', 'huddersfield town', '3 - 1', 'peterborough united', '26 january 1957'], ['15', 'cardiff city', '0 - 1', 'barnsley', '26 january 1957'], ['16', 'newport county', '0 - 2', 'arsenal', '26 january 1957']] |
ncc class a1 | https://en.wikipedia.org/wiki/NCC_Class_A1 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12113888-1.html.csv | majority | most of the things rebuilt by derby were completed before 1930 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1930', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'rebuilt', '1930'], 'result': True, 'ind': 0, 'tointer': 'for the rebuilt records of all rows , most of them are less than 1930 .', 'tostr': 'most_less { all_rows ; rebuilt ; 1930 } = true'} | most_less { all_rows ; rebuilt ; 1930 } = true | for the rebuilt records of all rows , most of them are less than 1930 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'rebuilt_3': 3, '1930_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'rebuilt_3': 'rebuilt', '1930_4': '1930'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'rebuilt_3': [0], '1930_4': [0]} | ['number', 'builder', 'built', 'rebuilt', 'name as rebuilt', 'scrapped / sold'] | [['33', 'york rd', '1902', '1928', 'binevanagh', '1949'], ['34', 'york rd', '1901', '1928', 'knocklayd', '1950'], ['58', 'york rd', '1907', '1934', 'lurigethan', '1954'], ['62', 'york rd', '1903', '1928', 'slemish', '1954'], ['64', 'derby', '1905', '1929', 'trostan', '1954'], ['65', 'derby', '1905', '1929', 'knockagh', '1950'], ['66', 'derby', '1905', '1930', 'ben madigan', '1954'], ['68', 'derby', '1908', '1927', 'slieve gallion', '1947']] |
zakspeed | https://en.wikipedia.org/wiki/Zakspeed | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219581-1.html.csv | count | the zakspeed motor racing team scored 0 points in four of the years . | {'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; points ; 0 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; points ; 0 } }', 'tointer': 'select the rows whose points record is equal to 0 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; points ; 0 } } ; 4 } = true', 'tointer': 'select the rows whose points record is equal to 0 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; points ; 0 } } ; 4 } = true | select the rows whose points record is equal to 0 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'points_5': 5, '0_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'points_5': 'points', '0_6': '0', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'points_5': [0], '0_6': [0], '4_7': [2]} | ['year', 'chassis', 'engine ( s )', 'tyres', 'points'] | [['1985', 'zakspeed 841', 'zakspeed s4 t / c', 'g', '0'], ['1986', 'zakspeed 861', 'zakspeed s4 t / c', 'g', '0'], ['1987', 'zakspeed 861 zakspeed 871', 'zakspeed s4 t / c', 'g', '2'], ['1988', 'zakspeed 881', 'zakspeed s4 t / c', 'g', '0'], ['1989', 'zakspeed 891', 'yamaha v8', 'p', '0']] |
world tourism rankings | https://en.wikipedia.org/wiki/World_Tourism_rankings | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14752049-4.html.csv | comparative | from 2011-2012 , brazil saw more growth in tourist arrivals than canada did . | {'row_1': '4', 'row_2': '3', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'brazil'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to brazil .', 'tostr': 'filter_eq { all_rows ; country ; brazil }'}, 'change ( 2011 to 2012 )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; brazil } ; change ( 2011 to 2012 ) }', 'tointer': 'select the rows whose country record fuzzily matches to brazil . take the change ( 2011 to 2012 ) record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'canada'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to canada .', 'tostr': 'filter_eq { all_rows ; country ; canada }'}, 'change ( 2011 to 2012 )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; canada } ; change ( 2011 to 2012 ) }', 'tointer': 'select the rows whose country record fuzzily matches to canada . take the change ( 2011 to 2012 ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; country ; brazil } ; change ( 2011 to 2012 ) } ; hop { filter_eq { all_rows ; country ; canada } ; change ( 2011 to 2012 ) } } = true', 'tointer': 'select the rows whose country record fuzzily matches to brazil . take the change ( 2011 to 2012 ) record of this row . select the rows whose country record fuzzily matches to canada . take the change ( 2011 to 2012 ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; country ; brazil } ; change ( 2011 to 2012 ) } ; hop { filter_eq { all_rows ; country ; canada } ; change ( 2011 to 2012 ) } } = true | select the rows whose country record fuzzily matches to brazil . take the change ( 2011 to 2012 ) record of this row . select the rows whose country record fuzzily matches to canada . take the change ( 2011 to 2012 ) record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'brazil_8': 8, 'change (2011 to 2012)_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'canada_12': 12, 'change (2011 to 2012)_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'brazil_8': 'brazil', 'change (2011 to 2012)_9': 'change ( 2011 to 2012 )', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'canada_12': 'canada', 'change (2011 to 2012)_13': 'change ( 2011 to 2012 )'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'brazil_8': [0], 'change (2011 to 2012)_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'canada_12': [1], 'change (2011 to 2012)_13': [3]} | ['rank', 'country', 'international tourist arrivals ( 2012 )', 'international tourist arrivals ( 2011 )', 'change ( 2011 to 2012 )', 'change ( 2010 to 2011 )'] | [['1', 'united states', '67.0 million', '62.7 million', '+ 6.8 %', '+ 4.9 %'], ['2', 'mexico', '23.4 million', '23.4 million', '+ 0.0 %', '+ 0.5 %'], ['3', 'canada', '16.3 million', '16.0 million', '+ 1.8 %', '- 1.3 %'], ['4', 'brazil', '5.6 million', '5.4 million', '+ 4.5 %', '+ 5.3 %'], ['5', 'argentina', '5.5 million', '5.7 million', '- 1.9 %', '+ 7.1 %'], ['6', 'dominican republic', '4.5 million', '4.3 million', '+ 5.9 %', '+ 4.4 %'], ['7', 'chile', '3.5 million', '3.1 million', '+ 13.3 %', '+ 12.0 %'], ['8', 'puerto rico', '3.0 million', '3.0 million', '+ 0.7 %', '- 4.3 %'], ['9', 'peru', '2.8 million', '2.5 million', '+ 9.5 %', '+ 13.0 %'], ['10', 'uruguay', '2.6 million', '2.8 million', '- 5.7 %', '+ 21.6 %']] |
2001 lff lyga | https://en.wikipedia.org/wiki/2001_LFF_Lyga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18018214-1.html.csv | ordinal | in the 2001 lff lyga , the club nevėžis kėdainiai had the 3rd most loses . | {'row': '7', 'col': '6', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'loses', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; loses ; 3 }'}, 'club'], 'result': 'nevėžis kėdainiai', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; loses ; 3 } ; club }'}, 'nevėžis kėdainiai'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; loses ; 3 } ; club } ; nevėžis kėdainiai } = true', 'tointer': 'select the row whose loses record of all rows is 3rd maximum . the club record of this row is nevėžis kėdainiai .'} | eq { hop { nth_argmax { all_rows ; loses ; 3 } ; club } ; nevėžis kėdainiai } = true | select the row whose loses record of all rows is 3rd maximum . the club record of this row is nevėžis kėdainiai . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'loses_5': 5, '3_6': 6, 'club_7': 7, 'nevėžis kėdainiai_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', 'loses_5': 'loses', '3_6': '3', 'club_7': 'club', 'nevėžis kėdainiai_8': 'nevėžis kėdainiai'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'loses_5': [0], '3_6': [0], 'club_7': [1], 'nevėžis kėdainiai_8': [2]} | ['position', 'club', 'games played', 'wins', 'draws', 'loses', 'goals scored', 'goals conceded', 'points'] | [['1', 'fbk kaunas', '36', '26', '7', '3', '76', '13', '85'], ['2', 'fk atlantas', '36', '19', '12', '5', '66', '29', '69'], ['3', 'fk žalgiris vilnius', '36', '20', '9', '7', '64', '39', '69'], ['4', 'fk ekranas', '36', '15', '10', '11', '58', '38', '55'], ['5', 'inkaras kaunas', '36', '11', '12', '13', '50', '44', '45'], ['6', 'geležinis vilkas vilnius', '36', '10', '6', '20', '42', '69', '36'], ['7', 'nevėžis kėdainiai', '36', '8', '11', '17', '33', '54', '35'], ['8', 'sakalas šiauliai', '36', '7', '13', '16', '32', '61', '34'], ['9', 'vėtra rūdiškės', '36', '7', '11', '18', '32', '57', '32']] |
jack fairman | https://en.wikipedia.org/wiki/Jack_Fairman | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235888-1.html.csv | aggregation | jack fairman scored a combined total of 5 championship points in his racing career . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '5', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 5 } = true', 'tointer': 'the sum of the points record of all rows is 5 .'} | round_eq { sum { all_rows ; points } ; 5 } = true | the sum of the points record of all rows is 5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '5_5': '5'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '5_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1953', 'hw motors', 'hwm 53', 'alta', '0'], ['1953', 'connaught engineering', 'connaught type a', 'lea francis', '0'], ['1955', 'connaught engineering', 'connaught type b', 'alta', '0'], ['1956', 'connaught engineering', 'connaught type b', 'alta', '5'], ['1957', 'owen racing organisation', 'brm p25', 'brm', '0'], ['1958', 'bc ecclestone', 'connaught type b', 'alta', '0'], ['1958', 'cooper car company', 'cooper t45', 'coventry climax', '0'], ['1959', 'high efficiency motors', 'cooper t45', 'coventry climax', '0'], ['1959', 'high efficiency motors', 'cooper t45', 'maserati', '0'], ['1960', 'ct atkins', 'cooper t51', 'coventry climax', '0'], ['1961', 'rob walker racing', 'ferguson p99', 'coventry climax', '0'], ['1961', 'fred tuck cars', 'cooper t45', 'coventry climax', '0']] |
1965 baltimore colts season | https://en.wikipedia.org/wiki/1965_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14977592-1.html.csv | aggregation | the baltimore colts scored an average of less than 15 points in games they lost during the 1965 season . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': 'less than 15 points', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'l'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; l }', 'tointer': 'select the rows whose result record fuzzily matches to l .'}, 'result'], 'result': 'less than 15 points', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; result ; l } ; result }'}, 'less than 15 points'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; result ; l } ; result } ; less than 15 points } = true', 'tointer': 'select the rows whose result record fuzzily matches to l . the average of the result record of these rows is less than 15 points .'} | round_eq { avg { filter_eq { all_rows ; result ; l } ; result } ; less than 15 points } = true | select the rows whose result record fuzzily matches to l . the average of the result record of these rows is less than 15 points . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'l_6': 6, 'result_7': 7, 'less than 15 points_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'l_6': 'l', 'result_7': 'result', 'less than 15 points_8': 'less than 15 points'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'l_6': [0], 'result_7': [1], 'less than 15 points_8': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 19 , 1965', 'minnesota vikings', 'w 35 - 16', '1 - 0', 'memorial stadium', '56562'], ['2', 'september 26 , 1965', 'green bay packers', 'l 17 - 20', '1 - 1', 'milwaukee county stadium', '48130'], ['3', 'october 3 , 1965', 'san francisco 49ers', 'w 27 - 24', '2 - 1', 'memorial stadium', '58609'], ['4', 'october 10 , 1965', 'detroit lions', 'w 31 - 7', '3 - 1', 'memorial stadium', '60238'], ['5', 'october 17 , 1965', 'washington redskins', 'w 38 - 7', '4 - 1', 'rfk stadium', '50405'], ['6', 'october 24 , 1965', 'los angeles rams', 'w 35 - 20', '5 - 1', 'memorial stadium', '45827'], ['7', 'october 31 , 1966', 'san francisco 49ers', 'w 34 - 28', '6 - 1', 'kezar stadium', '45827'], ['8', 'november 7 , 1965', 'chicago bears', 'w 26 - 21', '7 - 1', 'wrigley field', '45656'], ['9', 'november 14 , 1965', 'minnesota vikings', 'w 41 - 21', '8 - 1', 'metropolitan stadium', '47426'], ['10', 'november 21 , 1965', 'philadelphia eagles', 'w 34 - 24', '9 - 1', 'memorial stadium', '60238'], ['11', 'november 25 , 1965', 'detroit lions', 't 24 - 24', '9 - 1 - 1', 'tiger stadium', '55036'], ['12', 'december 5 , 1966', 'chicago bears', 'l 0 - 13', '9 - 2 - 1', 'memorial stadium', '60238'], ['13', 'december 12 , 1965', 'green bay packers', 'l 27 - 42', '9 - 3 - 1', 'memorial stadium', '60238'], ['14', 'december 18 , 1965', 'los angeles rams', 'w 20 - 17', '10 - 3 - 1', 'la memorial coliseum', '46636']] |
1989 pittsburgh steelers season | https://en.wikipedia.org/wiki/1989_Pittsburgh_Steelers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14563349-11.html.csv | count | in the 1989 pittsburgh steelers season , there were 8 games that were at three rivers stadium . | {'scope': 'all', 'criterion': 'equal', 'value': 'three rivers stadium', 'result': '8', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'three rivers stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to three rivers stadium .', 'tostr': 'filter_eq { all_rows ; location ; three rivers stadium }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; three rivers stadium } }', 'tointer': 'select the rows whose location record fuzzily matches to three rivers stadium . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; three rivers stadium } } ; 8 } = true', 'tointer': 'select the rows whose location record fuzzily matches to three rivers stadium . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; location ; three rivers stadium } } ; 8 } = true | select the rows whose location record fuzzily matches to three rivers stadium . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'three rivers stadium_6': 6, '8_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', 'three rivers stadium_6': 'three rivers stadium', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'three rivers stadium_6': [0], '8_7': [2]} | ['week', 'date', 'opponent', 'location', 'time ( et )', 'result', 'record'] | [['1', 'sun sep 10', 'cleveland browns', 'three rivers stadium', '4:00 pm', 'l 51 - 0', '0 - 1'], ['2', 'sun sep 17', 'cincinnati bengals', 'riverfront stadium', '1:00 pm', 'l 41 - 10', '0 - 2'], ['3', 'sun sep 24', 'minnesota vikings', 'three rivers stadium', '1:00 pm', 'w 27 - 14', '1 - 2'], ['4', 'sun oct 1', 'detroit lions', 'pontiac silverdome', '1:00 pm', 'w 23 - 3', '2 - 2'], ['5', 'sun oct 8', 'cincinnati bengals', 'three rivers stadium', '1:00 pm', 'l 26 - 16', '2 - 3'], ['6', 'sun oct 15', 'cleveland browns', 'cleveland municipal stadium', '4:00 pm', 'w 17 - 7', '3 - 3'], ['7', 'sun oct 22', 'houston oilers', 'astrodome', '1:00 pm', 'l 27 - 0', '3 - 4'], ['8', 'sun oct 29', 'kansas city chiefs', 'three rivers stadium', '1:00 pm', 'w 23 - 17', '4 - 4'], ['9', 'sun nov 5', 'denver broncos', 'mile high stadium', '4:00 pm', 'l 34 - 7', '4 - 5'], ['10', 'sun nov 12', 'chicago bears', 'three rivers stadium', '1:00 pm', 'l 20 - 0', '4 - 6'], ['11', 'sun nov 19', 'san diego chargers', 'three rivers stadium', '1:00 pm', 'w 20 - 17', '5 - 6'], ['12', 'sun nov 26', 'miami dolphins', 'joe robbie stadium', '1:00 pm', 'w 34 - 14', '6 - 6'], ['13', 'sun dec 3', 'houston oilers', 'three rivers stadium', '1:00 pm', 'l 23 - 16', '6 - 7'], ['14', 'sun dec 10', 'new york jets', 'giants stadium', '1:00 pm', 'w 13 - 0', '7 - 7'], ['15', 'sun dec 17', 'new england patriots', 'three rivers stadium', '1:00 pm', 'w 28 - 10', '8 - 7'], ['16', 'sun dec 24', 'tampa bay buccaneers', 'tampa stadium', '1:00 pm', 'w 31 - 22', '9 - 7']] |
jackie oliver | https://en.wikipedia.org/wiki/Jackie_Oliver | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226463-1.html.csv | comparative | jackie oliver scored more points in 1968 than he did in 1973 . | {'row_1': '2', 'row_2': '12', 'col': '5', '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', 'year', '1968'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1968 .', 'tostr': 'filter_eq { all_rows ; year ; 1968 }'}, 'pts'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1968 } ; pts }', 'tointer': 'select the rows whose year record fuzzily matches to 1968 . take the pts record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1973'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1973 .', 'tostr': 'filter_eq { all_rows ; year ; 1973 }'}, 'pts'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1973 } ; pts }', 'tointer': 'select the rows whose year record fuzzily matches to 1973 . take the pts record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1968 } ; pts } ; hop { filter_eq { all_rows ; year ; 1973 } ; pts } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1968 . take the pts record of this row . select the rows whose year record fuzzily matches to 1973 . take the pts record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 1968 } ; pts } ; hop { filter_eq { all_rows ; year ; 1973 } ; pts } } = true | select the rows whose year record fuzzily matches to 1968 . take the pts record of this row . select the rows whose year record fuzzily matches to 1973 . take the pts 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, 'year_7': 7, '1968_8': 8, 'pts_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1973_12': 12, 'pts_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', 'year_7': 'year', '1968_8': '1968', 'pts_9': 'pts', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1973_12': '1973', 'pts_13': 'pts'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1968_8': [0], 'pts_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1973_12': [1], 'pts_13': [3]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1967', 'lotus components ltd', 'lotus 48 ( f2 )', 'cosworth straight - 4', '0'], ['1968', 'gold leaf team lotus', 'lotus 49', 'cosworth v8', '6'], ['1968', 'gold leaf team lotus', 'lotus 49b', 'cosworth v8', '6'], ['1969', 'owen racing organisation', 'brm p133', 'brm v12', '1'], ['1969', 'owen racing organisation', 'brm p138', 'brm v12', '1'], ['1969', 'owen racing organisation', 'brm p139', 'brm v12', '1'], ['1970', 'owen racing organisation', 'brm p153', 'brm v12', '2'], ['1970', 'yardley team brm', 'brm p153', 'brm v12', '2'], ['1971', 'bruce mclaren motor racing', 'mclaren m14a', 'cosworth v8', '0'], ['1971', 'bruce mclaren motor racing', 'mclaren m19a', 'cosworth v8', '0'], ['1972', 'marlboro brm', 'brm p160b', 'brm v12', '0'], ['1973', 'uop shadow racing team', 'shadow dn1', 'cosworth v8', '4'], ['1977', 'shadow racing team', 'shadow dn8', 'cosworth v8', '0']] |
2010 - 11 atlanta hawks season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27734577-11.html.csv | ordinal | during this period of the 2010-11 atlanta hawks season , the atlanta hawks experienced their second highest attendance on april 1st during their game against boston . | {'row': '1', 'col': '8', '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', 'location attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 2 }'}, 'date'], 'result': 'april 1', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; 2 } ; date }'}, 'april 1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; location attendance ; 2 } ; date } ; april 1 } = true', 'tointer': 'select the row whose location attendance record of all rows is 2nd maximum . the date record of this row is april 1 .'} | eq { hop { nth_argmax { all_rows ; location attendance ; 2 } ; date } ; april 1 } = true | select the row whose location attendance record of all rows is 2nd maximum . the date record of this row is april 1 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '2_6': 6, 'date_7': 7, 'april 1_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', '2_6': '2', 'date_7': 'date', 'april 1_8': 'april 1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '2_6': [0], 'date_7': [1], 'april 1_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 1', 'boston', 'w 88 - 83 ( ot )', 'jamal crawford ( 20 )', 'al horford ( 15 )', 'jamal crawford , al horford ( 4 )', 'philips arena 19763', '44 - 32'], ['77', 'april 3', 'houston', 'l 109 - 114 ( ot )', 'joe johnson ( 25 )', 'josh smith ( 11 )', 'joe johnson , josh smith ( 7 )', 'toyota center 15993', '44 - 33'], ['78', 'april 5', 'san antonio', 'l 90 - 97 ( ot )', 'joe johnson ( 21 )', 'al horford ( 9 )', 'al horford ( 5 )', 'philips arena 17277', '44 - 34'], ['79', 'april 8', 'indiana', 'l 102 - 114 ( ot )', 'jeff teague ( 21 )', 'zaza pachulia ( 11 )', 'jamal crawford ( 3 )', 'conseco fieldhouse 15879', '44 - 35'], ['80', 'april 9', 'washington', 'l 83 - 115 ( ot )', 'al horford ( 21 )', 'al horford ( 10 )', 'jeff teague ( 5 )', 'verizon center 19771', '44 - 36']] |
somerset county cricket club in 2009 | https://en.wikipedia.org/wiki/Somerset_County_Cricket_Club_in_2009 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27922491-8.html.csv | superlative | andrew caddick was the player with the highest average for the somerset county cricket club in 2009 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'average'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; average }'}, 'player'], 'result': 'andrew caddick', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; average } ; player }'}, 'andrew caddick'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; average } ; player } ; andrew caddick } = true', 'tointer': 'select the row whose average record of all rows is maximum . the player record of this row is andrew caddick .'} | eq { hop { argmax { all_rows ; average } ; player } ; andrew caddick } = true | select the row whose average record of all rows is maximum . the player record of this row is andrew caddick . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'average_5': 5, 'player_6': 6, 'andrew caddick_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'average_5': 'average', 'player_6': 'player', 'andrew caddick_7': 'andrew caddick'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'average_5': [0], 'player_6': [1], 'andrew caddick_7': [2]} | ['player', 'matches', 'innings', 'wickets', 'average', 'bbi', 'bbm', '5wi'] | [['charl willoughby', '16', '26', '54', '30.03', '5 / 56', '7 / 170', '3'], ['david stiff', '10', '18', '31', '36.12', '5 / 91', '5 / 93', '1'], ['alfonso thomas', '14', '22', '35', '37.62', '5 / 53', '8 / 152', '1'], ['ben phillips', '7', '11', '12', '38.00', '4 / 46', '4 / 73', '0'], ['arul suppiah', '16', '19', '15', '45.46', '3 / 58', '5 / 85', '0'], ['peter trego', '16', '25', '19', '46.78', '3 / 53', '3 / 74', '0'], ['andrew caddick', '5', '8', '10', '52.50', '3 / 53', '4 / 95', '0']] |
bitburger open | https://en.wikipedia.org/wiki/Bitburger_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12275654-1.html.csv | count | xu huaiwen has won the women 's singles at the bitburger open five times . | {'scope': 'all', 'criterion': 'equal', 'value': 'xu huaiwen', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', "women 's singles", 'xu huaiwen'], 'result': None, 'ind': 0, 'tointer': "select the rows whose women 's singles record fuzzily matches to xu huaiwen .", 'tostr': "filter_eq { all_rows ; women 's singles ; xu huaiwen }"}], 'result': '5', 'ind': 1, 'tostr': "count { filter_eq { all_rows ; women 's singles ; xu huaiwen } }", 'tointer': "select the rows whose women 's singles record fuzzily matches to xu huaiwen . the number of such rows is 5 ."}, '5'], 'result': True, 'ind': 2, 'tostr': "eq { count { filter_eq { all_rows ; women 's singles ; xu huaiwen } } ; 5 } = true", 'tointer': "select the rows whose women 's singles record fuzzily matches to xu huaiwen . the number of such rows is 5 ."} | eq { count { filter_eq { all_rows ; women 's singles ; xu huaiwen } } ; 5 } = true | select the rows whose women 's singles record fuzzily matches to xu huaiwen . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, "women 's singles_5": 5, 'xu huaiwen_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', "women 's singles_5": "women 's singles", 'xu huaiwen_6': 'xu huaiwen', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], "women 's singles_5": [0], 'xu huaiwen_6': [0], '5_7': [2]} | ['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles'] | [['1988', 'kim brodersen', 'katrin schmidt', 'markus keck robert neumann', 'katrin schmidt nicole baldewein', 'markus keck katrin schmidt'], ['1989', 'sörgard', 'katrin schmidt', 'stefan frey robert neumann', 'birgitta lehnert monica halim', 'chen jin katrin schmidt'], ['1998', 'yong yudianto', 'karolina ericsson', 'michael keck christian mohr', 'erica van den heuvel judith meulendijks', 'michael keck nicol pitro'], ['1999', 'oliver pongratz', 'zheng yaqiong', 'quinten van dalm dennis lens', 'britta andersen lene mork', 'chris bruil erica van den heuvel'], ['2000', 'xie yangchun', 'xu huaiwen', 'michael søgaard joachim fischer nielsen', 'claudia vogelgsang xu huaiwen', 'michael keck erica van den heuvel'], ['2001', 'niels christian kaldau', 'pi hongyan', 'michael søgaard michael lamp', 'neli boteva elena nozdran', 'chris bruil lotte bruil - jonathans'], ['2002', 'chen gang', 'pi hongyan', 'simon archer flandy limpele', 'mia audina lotte bruil - jonathans', 'nathan robertson gail emms'], ['2003', 'dicky palyama', 'xu huaiwen', 'michał łogosz robert mateusiak', 'nicole grether juliane schenk', 'frederik bergström johanna persson'], ['2004', 'niels christian kaldau', 'xu huaiwen', 'simon archer anthony clark', 'kamila augustyn nadieżda kostiuczyk', 'rasmus mangor andersen britta andersen'], ['2005', 'kasper ødum', 'xu huaiwen', 'tony gunawan halim haryanto', 'nicole grether juliane schenk', 'vladislav druzhchenko johanna persson'], ['2006', 'ronald susilo', 'xu huaiwen', 'michał łogosz robert mateusiak', 'jiang yanmei li yujia', 'robert mateusiak nadieżda kostiuczyk'], ['2007', 'lu yi', 'wang yihan', 'mathias boe carsten mogensen', 'yang wei zhang jiewen', 'kristof hopp birgit overzier'], ['2008', 'chetan anand', 'maria febe kusumastuti', 'mathias boe carsten mogensen', 'helle nielsen marie roepke', 'diju valiyaveetil jwala gutta'], ['2009', 'jan ø jørgensen', 'juliane schenk', 'rupesh kumar sanave thomas', 'helle nielsen marie roepke', 'mikkel delbo larsen mie schjoett - kristensen'], ['2010', 'chen long', 'liu xin', 'mathias boe carsten mogensen', 'pan pan tian qing', 'zhang nan zhao yunlei'], ['2011', 'hans - kristian vittinghus', 'li xuerui', 'bodin isara maneepong jongjit', 'mizuki fujii reika kakiiwa', 'chan peng soon goh liu ying'], ['2012', 'chou tien - chen', 'juliane schenk', 'ingo kindervater johannes schoettler', 'wang rong zhang zhibo', 'anders kristiansen julie houmann'], ['2013', 'chou tien - chen', 'nichaon jindapon', 'mads conrad - petersen mads pieler kolding', 'eefje muskens selena piek', 'michael fuchs birgit michels']] |
2008 issf world cup final ( rifle and pistol ) | https://en.wikipedia.org/wiki/2008_ISSF_World_Cup_Final_%28rifle_and_pistol%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18191407-15.html.csv | unique | among all of the shooters , eglis yaima cruz is the only one from cuba . | {'scope': 'all', 'row': '7', 'col': '1', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': '( cub )', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'shooter', '( cub )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose shooter record fuzzily matches to ( cub ) .', 'tostr': 'filter_eq { all_rows ; shooter ; ( cub ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; shooter ; ( cub ) } } = true', 'tointer': 'select the rows whose shooter record fuzzily matches to ( cub ) . there is only one such row in the table .'} | only { filter_eq { all_rows ; shooter ; ( cub ) } } = true | select the rows whose shooter record fuzzily matches to ( cub ) . 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, 'shooter_4': 4, '( cub )_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'shooter_4': 'shooter', '( cub )_5': '( cub )'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'shooter_4': [0], '( cub )_5': [0]} | ['shooter', 'prone', 'stand', 'kneel', 'qual'] | [['sonja pfeilschifter ( ger )', '199', '195', '196', '590'], ['olga dovgun ( kaz )', '200', '196', '193', '589'], ['lioubov galkina ( rus )', '199', '193', '194', '586'], ['yin wen ( chn )', '197', '195', '194', '586'], ['jamie beyerle ( usa )', '198', '188', '194', '580'], ['snježana pejčić ( cro )', '197', '193', '190', '580'], ['eglis yaima cruz ( cub )', '199', '186', '193', '578'], ['morgan hicks ( usa )', '196', '190', '192', '578'], ['du li ( chn )', '199', '189', '190', '578'], ['thanyalak chotphibunsin ( tha )', '197', '185', '194', '576'], ['kristina vestveit ( nor )', '195', '189', '191', '575'], ['adela sykorova ( cze )', '195', '187', '188', '570']] |
the mole ( tv series ) | https://en.wikipedia.org/wiki/The_Mole_%28TV_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-178242-7.html.csv | count | there were 14 different moles throughout the tv series , the mole . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '14', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'the mole'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose the mole record is arbitrary .', 'tostr': 'filter_all { all_rows ; the mole }'}], 'result': '14', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; the mole } }', 'tointer': 'select the rows whose the mole record is arbitrary . the number of such rows is 14 .'}, '14'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; the mole } } ; 14 } = true', 'tointer': 'select the rows whose the mole record is arbitrary . the number of such rows is 14 .'} | eq { count { filter_all { all_rows ; the mole } } ; 14 } = true | select the rows whose the mole record is arbitrary . the number of such rows is 14 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'the mole_5': 5, '14_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'the mole_5': 'the mole', '14_6': '14'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'the mole_5': [0], '14_6': [2]} | ['season', 'the mole', 'winner', 'runner - up', 'international destination'] | [['1999 / 2000', 'deborah', 'petra ( 37.437 , - )', 'robin', 'australia'], ['2001', 'nico', 'sigrid ( 31.765 , - )', 'yvonne', 'scotland'], ['2002', 'george', 'john ( 42.300 , - )', 'jantien', 'portugal'], ['2003', 'elise', 'ron ( 35.550 , - )', 'chandrika', 'canada'], ['2005', 'yvon', 'marc - marie ( 23.000 , - )', 'lottie', 'australia , indonesia ( bali )'], ['2006', 'milouska', 'frédérique ( 24.475 , - )', 'roderick', 'argentina'], ['2007', 'inge', 'paul ( 17.300 , - )', 'renate , eva', 'thailand'], ['2008', 'dennis', 'edo ( 20.375 , - )', 'regina', 'mexico'], ['2008 junior edition', 'amin', 'naomi', 'lara', 'netherlands ( zwolle )'], ['2009', 'jon', 'viviënne ( 22.650 , - )', 'anniek', 'northern ireland jordan'], ['2010', 'kim', 'frits ( 21.950 , - )', 'sanne', 'japan'], ['2011', 'patrick', 'art ( 19.540 , - )', 'soundos', 'el salvador nicaragua'], ['2012', 'anne - marie', 'hadewych ( 12.601 , - )', 'liesbeth', 'iceland spain ( andalusia )'], ['2013', 'kees', 'paulien ( 17.120 , - )', 'carolien', 'south africa']] |
fred funk | https://en.wikipedia.org/wiki/Fred_Funk | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1646050-1.html.csv | count | fred funk won a total of four tournaments with a margin of victory of 1 stroke . | {'scope': 'all', 'criterion': 'equal', 'value': '1 stroke', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'margin of victory', '1 stroke'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose margin of victory record fuzzily matches to 1 stroke .', 'tostr': 'filter_eq { all_rows ; margin of victory ; 1 stroke }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; margin of victory ; 1 stroke } }', 'tointer': 'select the rows whose margin of victory record fuzzily matches to 1 stroke . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; margin of victory ; 1 stroke } } ; 4 } = true', 'tointer': 'select the rows whose margin of victory record fuzzily matches to 1 stroke . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; margin of victory ; 1 stroke } } ; 4 } = true | select the rows whose margin of victory record fuzzily matches to 1 stroke . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'margin of victory_5': 5, '1 stroke_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'margin of victory_5': 'margin of victory', '1 stroke_6': '1 stroke', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'margin of victory_5': [0], '1 stroke_6': [0], '4_7': [2]} | ['date', 'tournament', 'winning score', 'margin of victory', 'runner ( s ) - up'] | [['may 1 , 1992', 'shell houston open', '- 16 ( 68 + 72 + 62 + 70 = 272 )', '2 strokes', 'kirk triplett'], ['jul 30 , 1995', 'ideon classic at pleasant valley', '- 20 ( 66 + 63 + 66 + 73 = 268 )', '1 stroke', 'jim mcgovern'], ['oct 6 , 1995', 'buick challenge', '- 16 ( 69 + 67 + 69 + 67 = 272 )', '1 stroke', 'john morse , loren roberts'], ['sep 21 , 1996', 'bc open 1', '- 19 ( 68 + 66 + 63 = 197 )', 'playoff', 'pete jordan'], ['jul 19 , 1998', 'deposit guaranty golf classic', '- 18 ( 69 + 64 + 69 + 68 = 270 )', '2 strokes', 'paul goydos , franklin langham , tim loustalot'], ['oct 3 , 2004', 'southern farm bureau classic', '- 22 ( 69 + 67 + 64 + 66 = 266 )', '1 stroke', 'ryan palmer'], ['mar 27 , 2005', 'the players championship', '- 9 ( 65 + 72 + 71 + 71 = 279 )', '1 stroke', 'luke donald , tom lehman , scott verplank'], ['feb 25 , 2007', 'mayakoba golf classic at riviera maya - cancun', '- 14 ( 62 + 69 + 64 + 71 = 266 )', 'playoff', 'josé cóceres']] |
1985 pga tour | https://en.wikipedia.org/wiki/1985_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14640372-4.html.csv | comparative | tom watson has more 1985 pga tour earnings than lee trevino . | {'row_1': '2', 'row_2': '3', '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', 'tom watson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to tom watson .', 'tostr': 'filter_eq { all_rows ; player ; tom watson }'}, 'earnings'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; tom watson } ; earnings }', 'tointer': 'select the rows whose player record fuzzily matches to tom watson . take the earnings record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'lee trevino'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to lee trevino .', 'tostr': 'filter_eq { all_rows ; player ; lee trevino }'}, 'earnings'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; lee trevino } ; earnings }', 'tointer': 'select the rows whose player record fuzzily matches to lee trevino . take the earnings record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; tom watson } ; earnings } ; hop { filter_eq { all_rows ; player ; lee trevino } ; earnings } } = true', 'tointer': 'select the rows whose player record fuzzily matches to tom watson . take the earnings record of this row . select the rows whose player record fuzzily matches to lee trevino . take the earnings record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; tom watson } ; earnings } ; hop { filter_eq { all_rows ; player ; lee trevino } ; earnings } } = true | select the rows whose player record fuzzily matches to tom watson . take the earnings record of this row . select the rows whose player record fuzzily matches to lee trevino . take the earnings 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, 'tom watson_8': 8, 'earnings_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'lee trevino_12': 12, 'earnings_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', 'tom watson_8': 'tom watson', 'earnings_9': 'earnings', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'lee trevino_12': 'lee trevino', 'earnings_13': 'earnings'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'tom watson_8': [0], 'earnings_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'lee trevino_12': [1], 'earnings_13': [3]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'jack nicklaus', 'united states', '4686280', '72'], ['2', 'tom watson', 'united states', '3806940', '36'], ['3', 'lee trevino', 'united states', '3177975', '29'], ['4', 'raymond floyd', 'united states', '2868951', '19'], ['5', 'hale irwin', 'united states', '2751050', '17']] |
transatlantic lines | https://en.wikipedia.org/wiki/TransAtlantic_Lines | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13580133-1.html.csv | majority | most of the ships used by transatlantic lines can move over 2000 gross tons . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'gross tonnage', '2000'], 'result': True, 'ind': 0, 'tointer': 'for the gross tonnage records of all rows , most of them are greater than 2000 .', 'tostr': 'most_greater { all_rows ; gross tonnage ; 2000 } = true'} | most_greater { all_rows ; gross tonnage ; 2000 } = true | for the gross tonnage records of all rows , most of them are greater than 2000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'gross tonnage_3': 3, '2000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'gross tonnage_3': 'gross tonnage', '2000_4': '2000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'gross tonnage_3': [0], '2000_4': [0]} | ['type', 'owns', 'length', 'delivery date', 'gross tonnage'] | [['general cargo ship', 'yes', '83.5152 m ( lbp )', '1 june 1980', '2266'], ['general cargo ship / container ship', 'yes', '100.59 100.59 m ( loa )', '1997 1997', '4276'], ['petroleum tanker', 'yes', '109.1 109.1 m ( loa )', '2001 2001', '3469'], ['deck cargo barge', 'yes', '76.2 76.2 m ( lbp )', '1983 1 september 1983', '2529'], ['tugboat', 'yes', '27.7764 27.7764 m ( lbp )', '1974 1 september 1974', '189']] |
list of iron chef episodes | https://en.wikipedia.org/wiki/List_of_Iron_Chef_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23982399-12.html.csv | ordinal | the first episode that chen kenichi appeared on originally aired on january 5 , 2000 . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'original airdate', '1'], 'result': 'january 5 , 2000', 'ind': 0, 'tostr': 'nth_min { all_rows ; original airdate ; 1 }', 'tointer': 'the 1st minimum original airdate record of all rows is january 5 , 2000 .'}, 'january 5 , 2000'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; original airdate ; 1 } ; january 5 , 2000 }', 'tointer': 'the 1st minimum original airdate record of all rows is january 5 , 2000 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'original airdate', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; original airdate ; 1 }'}, 'iron chef'], 'result': 'chen kenichi', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; original airdate ; 1 } ; iron chef }'}, 'chen kenichi'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; original airdate ; 1 } ; iron chef } ; chen kenichi }', 'tointer': 'the iron chef record of the row with 1st minimum original airdate record is chen kenichi .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; original airdate ; 1 } ; january 5 , 2000 } ; eq { hop { nth_argmin { all_rows ; original airdate ; 1 } ; iron chef } ; chen kenichi } } = true', 'tointer': 'the 1st minimum original airdate record of all rows is january 5 , 2000 . the iron chef record of the row with 1st minimum original airdate record is chen kenichi .'} | and { eq { nth_min { all_rows ; original airdate ; 1 } ; january 5 , 2000 } ; eq { hop { nth_argmin { all_rows ; original airdate ; 1 } ; iron chef } ; chen kenichi } } = true | the 1st minimum original airdate record of all rows is january 5 , 2000 . the iron chef record of the row with 1st minimum original airdate record is chen kenichi . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'original airdate_8': 8, '1_9': 9, 'january 5 , 2000_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'original airdate_12': 12, '1_13': 13, 'iron chef_14': 14, 'chen kenichi_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'original airdate_8': 'original airdate', '1_9': '1', 'january 5 , 2000_10': 'january 5 , 2000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'original airdate_12': 'original airdate', '1_13': '1', 'iron chef_14': 'iron chef', 'chen kenichi_15': 'chen kenichi'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'original airdate_8': [0], '1_9': [0], 'january 5 , 2000_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'original airdate_12': [2], '1_13': [2], 'iron chef_14': [3], 'chen kenichi_15': [4]} | ['special', 'original airdate', 'iron chef', 'challenger', 'challenger specialty', 'theme ingredient', 'winner'] | [['millennium cup', 'january 5 , 2000', 'chen kenichi', 'zhao renliang ( 趙仁良 chō jinryō )', 'chinese ( beijing )', 'abalone', 'chen kenichi'], ['millennium cup', 'january 5 , 2000', 'rokusaburo michiba', 'dominique bouchet', 'french', 'kobe beef', 'rokusaburo michiba'], ['new york special', 'march 28 , 2000', 'masaharu morimoto', 'bobby flay', 'southwestern', 'rock crab', 'masaharu morimoto'], ['21st century battles', 'january 2 , 2001', 'hiroyuki sakai', 'toshirō kandagawa', 'japanese', 'red snapper', 'toshirō kandagawa'], ['21st century battles', 'january 2 , 2001', 'masaharu morimoto', 'bobby flay', 'southwestern', 'spiny lobster', 'bobby flay'], ['japan cup', 'january 2 , 2002', 'chen kenichi', 'yūichirō ebisu ( 胡 雄一郎 )', 'italian', 'king crab', 'chen kenichi'], ['japan cup', 'january 2 , 2002', 'kimio nonaga ( 野永喜三夫 )', 'takeshi tanabe ( 田辺 猛 )', 'japanese ( nonaga ) , french ( tanabe )', 'pacific bluefin tuna', 'kimio nonaga']] |
le tour de filipinas | https://en.wikipedia.org/wiki/Le_Tour_de_Filipinas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10694950-4.html.csv | comparative | the 2006 padyak pinot tour pilipinas has a longer distance than the 2002 fedex tour of calabarzon . | {'row_1': '5', 'row_2': '1', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'padyak pinoy tour pilipinas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to padyak pinoy tour pilipinas .', 'tostr': 'filter_eq { all_rows ; name ; padyak pinoy tour pilipinas }'}, 'distance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; padyak pinoy tour pilipinas } ; distance }', 'tointer': 'select the rows whose name record fuzzily matches to padyak pinoy tour pilipinas . take the distance record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'fedex tour of calabarzon'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to fedex tour of calabarzon .', 'tostr': 'filter_eq { all_rows ; name ; fedex tour of calabarzon }'}, 'distance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; fedex tour of calabarzon } ; distance }', 'tointer': 'select the rows whose name record fuzzily matches to fedex tour of calabarzon . take the distance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; padyak pinoy tour pilipinas } ; distance } ; hop { filter_eq { all_rows ; name ; fedex tour of calabarzon } ; distance } } = true', 'tointer': 'select the rows whose name record fuzzily matches to padyak pinoy tour pilipinas . take the distance record of this row . select the rows whose name record fuzzily matches to fedex tour of calabarzon . take the distance record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; padyak pinoy tour pilipinas } ; distance } ; hop { filter_eq { all_rows ; name ; fedex tour of calabarzon } ; distance } } = true | select the rows whose name record fuzzily matches to padyak pinoy tour pilipinas . take the distance record of this row . select the rows whose name record fuzzily matches to fedex tour of calabarzon . take the distance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'padyak pinoy tour pilipinas_8': 8, 'distance_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'fedex tour of calabarzon_12': 12, 'distance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'padyak pinoy tour pilipinas_8': 'padyak pinoy tour pilipinas', 'distance_9': 'distance', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'fedex tour of calabarzon_12': 'fedex tour of calabarzon', 'distance_13': 'distance'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'padyak pinoy tour pilipinas_8': [0], 'distance_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'fedex tour of calabarzon_12': [1], 'distance_13': [3]} | ['year', 'name', 'date', 'stages', 'distance', 'winner', 'time'] | [['2002', 'fedex tour of calabarzon', '30 may - 2 june', '4', '517.7 km', 'santi barnachea ( phi )', '12:41:13'], ['2003', 'air21 tour pilipinas', '16 april - 11 may', '15', '2849.8 km', 'arnel quirimit ( phi )', '55:29:20'], ['2004', 'air21 tour pilipinas', '15 april - 2 may', '17', '2849.8 km', 'rhyan tanguilig ( phi )', '70:28:59'], ['2005', 'golden tour 50 05', '26 may - 5 june', '10', '1492 km', 'warren davadilla ( phi )', '37:20:55'], ['2006', 'padyak pinoy tour pilipinas', '12 - 18 may', '8', '1219.4 km', 'santi barnachea ( phi )', '31:10:03'], ['2007', 'padyak pinoy', '17 - 29 may', '10', '1500 km', 'victor espiritu ( phi )', '33:02:38'], ['2008', 'cancelled', 'cancelled', 'cancelled', 'cancelled', 'cancelled', 'cancelled'], ['2009', 'padyak pinoy tour of champions', '8 - 15 may', '8', '1070 km', 'joel calderon ( phi )', '29:52:33'], ['2010', 'le tour de filipinas', '12 - 20 april', '4', '468.8 km', 'david mccann ( irl )', '11:29:20'], ['2011', 'le tour de filipinas', '16 - 19 april', '4', '468.8 km', 'rahim emami ( iri )', '12:15:34'], ['2012', 'le tour de filipinas', '14 - 17 april', '4', '502 km', 'baler ravina ( phi )', '13:20:32'], ['2013', 'le tour de filipinas', '13 - 16 april', '4', '616 km', 'ghader mizbani ( iri )', '16:38:37']] |
betty puskar golf classic | https://en.wikipedia.org/wiki/Betty_Puskar_Golf_Classic | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12743746-1.html.csv | aggregation | the total winner 's share for the betty puskar golf classic is 147,500 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '147500', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', "winner 's share"], 'result': '147500', 'ind': 0, 'tostr': "sum { all_rows ; winner 's share }"}, '147500'], 'result': True, 'ind': 1, 'tostr': "round_eq { sum { all_rows ; winner 's share } ; 147500 } = true", 'tointer': "the sum of the winner 's share record of all rows is 147500 ."} | round_eq { sum { all_rows ; winner 's share } ; 147500 } = true | the sum of the winner 's share record of all rows is 147500 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, "winner 's share_4": 4, '147500_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', "winner 's share_4": "winner 's share", '147500_5': '147500'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], "winner 's share_4": [0], '147500_5': [1]} | ['year', 'champion', 'country', 'score', 'purse', "winner 's share"] | [['2007', 'taylor leon', 'united states', '203 ( 13 )', '80000', '11200'], ['2006', 'kristy mcpherson', 'united states', '207 ( 9 )', '75000', '10500'], ['2005', 'sun young yoo', 'south korea', '204 ( 12 )', '70000', '9800'], ['2004', 'jimin kang', 'south korea', '209 ( 8 )', '70000', '9800'], ['2003', 'reilley rankin', 'united states', '134 ( 10 )', '70000', '9800'], ['2002', 'lorena ochoa', 'mexico', '207 ( 9 )', '70000', '9800'], ['2001', 'jenn brody', 'united states', '202 ( 14 )', '75000', '10500'], ['2000', 'heather zakhar', 'united states', '206 ( 10 )', '75000', '10500'], ['1999', 'grace park', 'south korea', '200 ( 16 )', '75000', '10500'], ['1998', 'aj eathorne', 'canada', '206 ( 10 )', '70000', '9700'], ['1997', 'becky iverson', 'united states', '282 ( 6 )', '70000', '9700'], ['1996', 'erika wicoff', 'united states', '212 ( 4 )', '65000', '9750'], ['1995', 'patty ehrhart', 'united states', '210 ( 6 )', '65000', '9750'], ['1994', 'tina paternostro', 'united states', '214 ( 2 )', '50000', '6800'], ['1993', 'missy tuck', 'united states', '216 ( e )', '50000', '6800'], ['1992', 'chela quintana', 'venezuela', '220 ( + 4 )', '20000', '2600']] |
2008 - 09 houston rockets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Houston_Rockets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17288825-6.html.csv | count | rafer alston had four high assists performances for the houston rockets . | {'scope': 'all', 'criterion': 'equal', 'value': 'rafer alston', 'result': '4', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'rafer alston'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to rafer alston .', 'tostr': 'filter_eq { all_rows ; high assists ; rafer alston }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high assists ; rafer alston } }', 'tointer': 'select the rows whose high assists record fuzzily matches to rafer alston . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high assists ; rafer alston } } ; 4 } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to rafer alston . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; high assists ; rafer alston } } ; 4 } = true | select the rows whose high assists record fuzzily matches to rafer alston . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'rafer alston_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'rafer alston_6': 'rafer alston', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'rafer alston_6': [0], '4_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['19', 'december 3', 'la clippers', 'w 103 - 96 ( ot )', 'yao ming ( 24 )', 'yao ming ( 10 )', 'rafer alston ( 7 )', 'toyota center 15358', '12 - 7'], ['20', 'december 5', 'golden state', 'w 131 - 112 ( ot )', 'yao ming ( 33 )', 'yao ming ( 14 )', 'yao ming , ron artest ( 5 )', 'toyota center 14438', '13 - 7'], ['21', 'december 8', 'memphis', 'l 97 - 109 ( ot )', 'luis scola , rafer alston ( 16 )', 'luis scola ( 15 )', 'rafer alston ( 8 )', 'fedexforum 10691', '13 - 8'], ['22', 'december 9', 'atlanta', 'w 92 - 84 ( ot )', 'yao ming ( 24 )', 'yao ming ( 19 )', 'rafer alston ( 6 )', 'toyota center 16439', '14 - 8'], ['23', 'december 12', 'golden state', 'w 119 - 108 ( ot )', 'tracy mcgrady ( 24 )', 'yao ming ( 14 )', 'tracy mcgrady ( 9 )', 'oracle arena 19276', '15 - 8'], ['24', 'december 13', 'la clippers', 'l 82 - 95 ( ot )', 'yao ming ( 24 )', 'yao ming ( 13 )', 'rafer alston ( 7 )', 'staples center 16203', '15 - 9'], ['25', 'december 16', 'denver', 'w 108 - 96 ( ot )', 'yao ming ( 32 )', 'tracy mcgrady ( 14 )', 'tracy mcgrady ( 10 )', 'toyota center 17737', '16 - 9'], ['26', 'december 19', 'sacramento', 'w 107 - 96 ( ot )', 'yao ming ( 30 )', 'carl landry ( 11 )', 'tracy mcgrady ( 8 )', 'toyota center 18271', '17 - 9'], ['27', 'december 20', 'minnesota', 'w 109 - 102 ( ot )', 'tracy mcgrady ( 23 )', 'aaron brooks , chuck hayes ( 10 )', 'tracy mcgrady , aaron brooks ( 5 )', 'target center 12115', '18 - 9'], ['28', 'december 22', 'new jersey', 'w 114 - 91 ( ot )', 'yao ming ( 24 )', 'yao ming ( 16 )', 'aaron brooks ( 6 )', 'izod center 16303', '19 - 9'], ['29', 'december 23', 'cleveland', 'l 90 - 99 ( ot )', 'rafer alston ( 20 )', 'luis scola ( 8 )', 'tracy mcgrady ( 6 )', 'quicken loans arena 20562', '19 - 10'], ['30', 'december 26', 'new orleans', 'l 79 - 88 ( ot )', 'yao ming ( 19 )', 'yao ming ( 12 )', 'tracy mcgrady ( 4 )', 'new orleans arena 18326', '19 - 11'], ['31', 'december 27', 'utah', 'w 120 - 115 ( 2ot )', 'ron artest ( 28 )', 'luis scola ( 14 )', 'ron artest , luis scola ( 4 )', 'toyota center 18245', '20 - 11'], ['32', 'december 29', 'washington', 'l 87 - 89 ( ot )', 'ron artest ( 20 )', 'yao ming ( 8 )', 'tracy mcgrady ( 7 )', 'toyota center 18278', '20 - 12'], ['33', 'december 31', 'milwaukee', 'w 85 - 81 ( ot )', 'yao ming ( 22 )', 'yao ming , luis scola ( 10 )', 'tracy mcgrady ( 10 )', 'toyota center 18228', '21 - 12']] |
2004 nba expansion draft | https://en.wikipedia.org/wiki/2004_NBA_Expansion_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15623086-3.html.csv | majority | the majority of players from the 2004 nba expansion draft were from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['pos', 'nationality', 'previous team', 'nba years', 'career with the franchise'] | [['f', 'united states', 'washington wizards', '2', '2006'], ['g', 'bosnia and herzegovina', 'golden state warriors', '2', '-'], ['c', 'slovenia', 'indiana pacers', '3', '2004 - 2007'], ['g', 'united states', 'new orleans hornets', '1', '-'], ['c', 'montenegro', 'los angeles clippers', '3', '-'], ['g / f', 'united states', 'portland trail blazers', '1', '-'], ['f', 'united states', 'chicago bulls', '4', '-'], ['g', 'united states', 'seattle supersonics', '1', '-'], ['f', 'united states', 'boston celtics', '1', '-'], ['f', 'united states', 'cleveland cavaliers', '1', '2004 - 2005'], ['c', 'georgia', 'orlando magic', '1', '-'], ['g / f', 'serbia', 'utah jazz', '1', '-'], ['f / c', 'united states', 'los angeles lakers', '2', '2004 - 2005'], ['g', 'united states', 'new jersey nets', '2', '2004 - 2005'], ['f', 'united states', 'memphis grizzlies', '1', '2004 - 2005'], ['g', 'united states', 'denver nuggets', '3', '-'], ['f', 'united states', 'sacramento kings', '3', '2004 - 2011'], ['f / c', 'united states', 'phoenix suns', '6', '2004 - 2005'], ['f / c', 'united states', 'miami heat', '3', '-']] |
wru division one north | https://en.wikipedia.org/wiki/WRU_Division_One_North | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14058433-1.html.csv | comparative | mold rfc was awarded one more loosing point than ruthin rfc in the wru division one north rugby union league for the season played in 2011-2012 . | {'row_1': '10', 'row_2': '9', 'col': '10', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'mold rfc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to mold rfc .', 'tostr': 'filter_eq { all_rows ; club ; mold rfc }'}, 'losing bonus'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; mold rfc } ; losing bonus }', 'tointer': 'select the rows whose club record fuzzily matches to mold rfc . take the losing bonus record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'ruthin rfc'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to ruthin rfc .', 'tostr': 'filter_eq { all_rows ; club ; ruthin rfc }'}, 'losing bonus'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; ruthin rfc } ; losing bonus }', 'tointer': 'select the rows whose club record fuzzily matches to ruthin rfc . take the losing bonus record of this row .'}], 'result': '-1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; club ; mold rfc } ; losing bonus } ; hop { filter_eq { all_rows ; club ; ruthin rfc } ; losing bonus } }'}, '-1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; club ; mold rfc } ; losing bonus } ; hop { filter_eq { all_rows ; club ; ruthin rfc } ; losing bonus } } ; -1 } = true', 'tointer': 'select the rows whose club record fuzzily matches to mold rfc . take the losing bonus record of this row . select the rows whose club record fuzzily matches to ruthin rfc . take the losing bonus record of this row . the second record is 1 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; club ; mold rfc } ; losing bonus } ; hop { filter_eq { all_rows ; club ; ruthin rfc } ; losing bonus } } ; -1 } = true | select the rows whose club record fuzzily matches to mold rfc . take the losing bonus record of this row . select the rows whose club record fuzzily matches to ruthin rfc . take the losing bonus record of this row . the second record is 1 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'club_8': 8, 'mold rfc_9': 9, 'losing bonus_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'club_12': 12, 'ruthin rfc_13': 13, 'losing bonus_14': 14, '-1_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', 'club_8': 'club', 'mold rfc_9': 'mold rfc', 'losing bonus_10': 'losing bonus', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'club_12': 'club', 'ruthin rfc_13': 'ruthin rfc', 'losing bonus_14': 'losing bonus', '-1_15': '-1'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'club_8': [0], 'mold rfc_9': [0], 'losing bonus_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'club_12': [1], 'ruthin rfc_13': [1], 'losing bonus_14': [3], '-1_15': [5]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus'], ['caernarfon rfc', '18', '0', '3', '524', '249', '72', '32', '8', '1'], ['nant conwy rfc', '18', '0', '4', '427', '177', '62', '19', '6', '2'], ['bro ffestiniog rfc', '18', '0', '5', '437', '246', '62', '30', '6', '5'], ['bethesda rfc', '18', '0', '6', '365', '208', '47', '21', '5', '5'], ['pwllheli rfc', '18', '0', '9', '344', '251', '50', '30', '3', '6'], ['bala rfc', '18', '0', '11', '242', '318', '30', '40', '2', '3'], ['llangefni rfc', '18', '0', '10', '271', '450', '28', '63', '0', '0'], ['ruthin rfc', '18', '0', '12', '311', '346', '39', '50', '2', '5'], ['mold rfc', '18', '0', '14', '247', '416', '31', '55', '2', '4'], ['llandudno rfc', '18', '0', '16', '204', '711', '25', '106', '0', '1']] |
2004 grand prix of road america | https://en.wikipedia.org/wiki/2004_Grand_Prix_of_Road_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16759619-2.html.csv | majority | most of the drivers completed the entire 48 laps of the 2004 grand prix . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '48', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'laps', '48'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are equal to 48 .', 'tostr': 'most_eq { all_rows ; laps ; 48 } = true'} | most_eq { all_rows ; laps ; 48 } = true | for the laps records of all rows , most of them are equal to 48 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '48_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '48_4': '48'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '48_4': [0]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['alex tagliani', 'rocketsports racing', '48', '1:45:07.288', '13', '33'], ['rodolfo lavín', 'forsythe racing', '48', '+ 1.855 secs', '10', '28'], ['sébastien bourdais', 'newman / haas racing', '48', '+ 2.767 secs', '1', '27'], ['ryan hunter - reay', 'herdez competition', '48', '+ 3.814 secs', '2', '24'], ['mario domínguez', 'herdez competition', '48', '+ 4.398 secs', '15', '21'], ['oriol servià', 'dale coyne racing', '48', '+ 6.390 secs', '8', '19'], ['justin wilson', 'mi - jack conquest racing', '48', '+ 8.500 secs', '9', '17'], ['jimmy vasser', 'pkv racing', '48', '+ 8.546 secs', '3', '15'], ['michel jourdain , jr', 'rusport', '48', '+ 9.056 secs', '11', '13'], ['guy smith', 'rocketsports racing', '48', '+ 9.997 secs', '16', '11'], ['mario haberfeld', 'walker racing', '48', '+ 16.725 secs', '12', '10'], ['paul tracy', 'forsythe racing', '48', '+ 26.616 secs', '6', '10'], ['a j allmendinger', 'rusport', '47', '+ 1 lap', '7', '8'], ['patrick carpentier', 'forsythe racing', '46', '+ 2 laps', '5', '7'], ['bruno junqueira', 'newman / haas racing', '46', '+ 2 laps', '4', '7'], ['roberto gonzález', 'pkv racing', '46', '+ 2 laps', '14', '5'], ['alex sperafico', 'mi - jack conquest racing', '46', '+ 2 laps', '17', '4'], ['gastón mazzacane', 'dale coyne racing', '29', 'off course', '18', '3']] |
list of white collar episodes | https://en.wikipedia.org/wiki/List_of_White_Collar_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24319661-5.html.csv | unique | the final episode of the season was the only one directed by john kretchmer . | {'scope': 'all', 'row': '15', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'john kretchmer', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'john kretchmer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to john kretchmer .', 'tostr': 'filter_eq { all_rows ; directed by ; john kretchmer }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; directed by ; john kretchmer } } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to john kretchmer . there is only one such row in the table .'} | only { filter_eq { all_rows ; directed by ; john kretchmer } } = true | select the rows whose directed by record fuzzily matches to john kretchmer . 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, 'directed by_4': 4, 'john kretchmer_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'directed by_4': 'directed by', 'john kretchmer_5': 'john kretchmer'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'directed by_4': [0], 'john kretchmer_5': [0]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'us viewers ( million )', 'original air date', 'production code'] | [['47', '1', 'wanted', 'paul holahan', 'jeff eastin', '3.21', 'july 10 , 2012', 'bcw401'], ['48', '2', 'most wanted', 'paul holahan', 'mark goffman', '2.98', 'july 17 , 2012', 'bcw402'], ['49', '3', 'diminishing returns', 'stefan schwartz', 'jim campolongo', '3.01', 'july 24 , 2012', 'bcw403'], ['50', '4', 'parting shots', 'robert duncan mcneill', 'alexandra mcnally', '2.82', 'july 31 , 2012', 'bcw404'], ['51', '5', 'honor among thieves', 'arlene sanford', 'joe henderson', '2.93', 'august 14 , 2012', 'bcw405'], ['52', '6', 'identity crisis', 'david straiton', 'channing powell', '3.89', 'august 21 , 2012', 'bcw406'], ['53', '7', 'compromising positions', 'paul holahan', 'matthew negrete', '3.36', 'august 28 , 2012', 'bcw407'], ['54', '8', 'ancient history', 'russell lee fine', 'daniel shattuck', '3.38', 'september 4 , 2012', 'bcw408'], ['55', '9', 'gloves off', 'renny harlin', 'mark goffman', '3.80', 'september 11 , 2012', 'bcw409'], ['56', '10', 'vested interest', 'russell lee fine', 'jeff eastin', '3.41', 'september 18 , 2012', 'bcw410'], ['57', '11', 'family business', 'paul holahan', 'joe henderson', '2.77', 'january 22 , 2013', 'bcw411'], ['58', '12', 'brass tacks', 'anton cropper', 'jim campolongo & alexandra mcnally', '2.61', 'january 29 , 2013', 'bcw412'], ['59', '13', 'empire city', 'tim dekay', 'channing powell & daniel shattuck', '2.28', 'february 5 , 2013', 'bcw413'], ['60', '14', 'shoot the moon', 'russell lee fine', 'matthew negrete & bob derosa', '2.42', 'february 19 , 2013', 'bcw414'], ['61', '15', 'the original', 'john kretchmer', 'mark goffman', '2.12', 'february 26 , 2013', 'bcw415']] |
massachusetts route 139 | https://en.wikipedia.org/wiki/Massachusetts_Route_139 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10568553-1.html.csv | count | one of these roads has an intersection with route 53 . | {'scope': 'all', 'criterion': 'equal', 'value': 'route 53', 'result': '1', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'roads intersected', 'route 53'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose roads intersected record fuzzily matches to route 53 .', 'tostr': 'filter_eq { all_rows ; roads intersected ; route 53 }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; roads intersected ; route 53 } }', 'tointer': 'select the rows whose roads intersected record fuzzily matches to route 53 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; roads intersected ; route 53 } } ; 1 } = true', 'tointer': 'select the rows whose roads intersected record fuzzily matches to route 53 . the number of such rows is 1 .'} | eq { count { filter_eq { all_rows ; roads intersected ; route 53 } } ; 1 } = true | select the rows whose roads intersected record fuzzily matches to route 53 . the number of such rows is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'roads intersected_5': 5, 'route 53_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'roads intersected_5': 'roads intersected', 'route 53_6': 'route 53', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'roads intersected_5': [0], 'route 53_6': [0], '1_7': [2]} | ['county', 'location', 'street names', 'milepost', 'roads intersected', 'notes'] | [['norfolk', 'stoughton', 'pleasant street turnpike street lindelof avenue', '3.0', 'route 24', 'route 24 exit 20'], ['norfolk', 'weymouth', 'anne street', '( no major junctions )', '( no major junctions )', '( no major junctions )'], ['plymouth', 'rockland', 'north avenue plain street market street', '12.2', 'route 123', 'western terminus of route 123 / 139 concurrency'], ['plymouth', 'rockland', 'north avenue plain street market street', '12.8', 'route 123', 'eastern terminus of route 123 / 139 concurrency'], ['plymouth', 'hanover', 'hanover street rockland street columbia road', '17.9', 'route 53', 'northern terminus of route 53 / 139 concurrency']] |
1926 in brazilian football | https://en.wikipedia.org/wiki/1926_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15385631-2.html.csv | ordinal | in 1926 in brazilian football , when there are over 10 points the 2nd highest number of losses is aa palmeiras . | {'scope': 'subset', 'row': '5', 'col': '6', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '3', 'criterion': 'greater_than', 'value': '10'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; points ; 10 }', 'tointer': 'select the rows whose points record is greater than 10 .'}, 'lost', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_greater { all_rows ; points ; 10 } ; lost ; 2 }'}, 'team'], 'result': 'aa palmeiras', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_greater { all_rows ; points ; 10 } ; lost ; 2 } ; team }'}, 'aa palmeiras'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_greater { all_rows ; points ; 10 } ; lost ; 2 } ; team } ; aa palmeiras } = true', 'tointer': 'select the rows whose points record is greater than 10 . select the row whose lost record of these rows is 2nd maximum . the team record of this row is aa palmeiras .'} | eq { hop { nth_argmax { filter_greater { all_rows ; points ; 10 } ; lost ; 2 } ; team } ; aa palmeiras } = true | select the rows whose points record is greater than 10 . select the row whose lost record of these rows is 2nd maximum . the team record of this row is aa palmeiras . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'points_6': 6, '10_7': 7, 'lost_8': 8, '2_9': 9, 'team_10': 10, 'aa palmeiras_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'points_6': 'points', '10_7': '10', 'lost_8': 'lost', '2_9': '2', 'team_10': 'team', 'aa palmeiras_11': 'aa palmeiras'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'points_6': [0], '10_7': [0], 'lost_8': [1], '2_9': [1], 'team_10': [2], 'aa palmeiras_11': [3]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'paulistano', '24', '14', '2', '1', '14', '41'], ['2', 'germnia', '18', '14', '2', '4', '28', '10'], ['3', 'independência', '17', '14', '3', '4', '30', '7'], ['4', 'antártica', '17', '14', '5', '3', '19', '6'], ['5', 'aa palmeiras', '15', '14', '3', '5', '24', '4'], ['6', 'atlético santista', '11', '14', '1', '8', '32', '- 2'], ['7', 'paulista', '8', '14', '4', '8', '46', '- 22'], ['8', 'britannia', '2', '14', '2', '12', '64', '- 44']] |
2008 - 09 segunda división | https://en.wikipedia.org/wiki/2008%E2%80%9309_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12951990-4.html.csv | count | a total of two goalkeepers played exactly 40 matches in the 2008 - 09 segunda división . | {'scope': 'all', 'criterion': 'equal', 'value': '40', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'matches', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose matches record is equal to 40 .', 'tostr': 'filter_eq { all_rows ; matches ; 40 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; matches ; 40 } }', 'tointer': 'select the rows whose matches record is equal to 40 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; matches ; 40 } } ; 2 } = true', 'tointer': 'select the rows whose matches record is equal to 40 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; matches ; 40 } } ; 2 } = true | select the rows whose matches record is equal to 40 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'matches_5': 5, '40_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'matches_5': 'matches', '40_6': '40', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'matches_5': [0], '40_6': [0], '2_7': [2]} | ['goalkeeper', 'goals', 'matches', 'average', 'team'] | [['david cobeño', '35', '40', '0.88', 'rayo vallecano'], ['claudio bravo', '28', '32', '0.88', 'real sociedad'], ['chema', '41', '41', '1', 'xerez cd'], ['carlos sánchez', '34', '34', '1', 'cd castellón'], ['alberto cifuentes', '34', '33', '1.03', 'ud salamanca'], ['juan calatayud', '42', '40', '1.05', 'hércules cf'], ['eduardo navarro', '39', '36', '1.08', 'sd huesca'], ['wilfredo caballero', '40', '36', '1.11', 'elche cf'], ['rubén pérez', '38', '33', '1.15', 'gimnàstic de tarragona'], ['roberto santamaría', '45', '39', '1.15', 'ud las palmas']] |
abancourt , oise | https://en.wikipedia.org/wiki/Abancourt%2C_Oise | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15902689-1.html.csv | count | abancourt , oise had more than a month 's worth of foggy days 4 times . | {'scope': 'all', 'criterion': 'greater_than', 'value': '30', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'fog ( days / year )', '30'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fog ( days / year ) record is greater than 30 .', 'tostr': 'filter_greater { all_rows ; fog ( days / year ) ; 30 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; fog ( days / year ) ; 30 } }', 'tointer': 'select the rows whose fog ( days / year ) record is greater than 30 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; fog ( days / year ) ; 30 } } ; 4 } = true', 'tointer': 'select the rows whose fog ( days / year ) record is greater than 30 . the number of such rows is 4 .'} | eq { count { filter_greater { all_rows ; fog ( days / year ) ; 30 } } ; 4 } = true | select the rows whose fog ( days / year ) record is greater than 30 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'fog (days / year)_5': 5, '30_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'fog (days / year)_5': 'fog ( days / year )', '30_6': '30', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'fog (days / year)_5': [0], '30_6': [0], '4_7': [2]} | ['sunshine ( hrs / year )', 'rain ( mm / year )', 'snow ( days / year )', 'storms ( days / year )', 'fog ( days / year )'] | [['1973', '770', '14', '22', '40'], ['1650', '657', '17', '18', '54'], ['1 630', '642', '15', '19', '13'], ['2 668', '767', '1', '31', '1'], ['1 633', '610', '30', '29', '65'], ['1 492', '1 109', '9', '11', '74']] |
1982 - 83 north west counties football league | https://en.wikipedia.org/wiki/1982%E2%80%9383_North_West_Counties_Football_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17716055-3.html.csv | ordinal | ashton athletic recorded the highest number of goals against in the 1982 - 83 north west counties football league . | {'row': '18', 'col': '7', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'goals against', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; goals against ; 1 }'}, 'team'], 'result': 'ashton athletic', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; goals against ; 1 } ; team }'}, 'ashton athletic'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; goals against ; 1 } ; team } ; ashton athletic } = true', 'tointer': 'select the row whose goals against record of all rows is 1st maximum . the team record of this row is ashton athletic .'} | eq { hop { nth_argmax { all_rows ; goals against ; 1 } ; team } ; ashton athletic } = true | select the row whose goals against record of all rows is 1st maximum . the team record of this row is ashton athletic . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'goals against_5': 5, '1_6': 6, 'team_7': 7, 'ashton athletic_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', 'goals against_5': 'goals against', '1_6': '1', 'team_7': 'team', 'ashton athletic_8': 'ashton athletic'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'goals against_5': [0], '1_6': [0], 'team_7': [1], 'ashton athletic_8': [2]} | ['position', 'team', 'played', 'drawn', 'lost', 'goals for', 'goals against', 'goal difference', 'points 1'] | [['1', 'colne dynamoes', '34', '5', '4', '95', '37', '+ 58', '55'], ['2', 'warrington town', '34', '6', '4', '83', '33', '+ 50', '54'], ['3', 'clitheroe', '34', '7', '5', '87', '35', '+ 52', '51'], ['4', 'prestwich heys', '34', '11', '5', '70', '37', '+ 33', '47'], ['5', 'vulcan newton', '34', '10', '11', '70', '65', '+ 5', '36'], ['6', 'blackpool mechanics', '34', '13', '10', '67', '56', '+ 11', '35'], ['7', 'bacup borough', '34', '7', '13', '53', '45', '+ 8', '35'], ['8', 'atherton collieries', '34', '11', '11', '55', '57', '2', '35'], ['9', 'whitworth valley', '34', '9', '12', '54', '65', '11', '35'], ['10', 'nelson', '34', '16', '11', '49', '56', '7', '28'], ['11', 'daisy hill', '34', '10', '14', '47', '58', '11', '30'], ['12', 'maghull', '34', '9', '15', '56', '61', '5', '29'], ['13', 'ashton town', '34', '5', '17', '53', '73', '20', '29'], ['14', 'newton', '34', '12', '14', '59', '62', '3', '28'], ['15', 'oldham dew', '34', '8', '16', '48', '61', '13', '28'], ['16', 'bolton st', '34', '6', '19', '50', '84', '34', '24'], ['17', 'wigan rovers', '34', '7', '22', '35', '72', '37', '17'], ['18', 'ashton athletic', '34', '8', '23', '18', '92', '74', '14']] |
1987 k league | https://en.wikipedia.org/wiki/1987_K_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14479112-3.html.csv | majority | the majority of the top 7 ranked players scored more than 10 goals . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '7'}} | {'func': 'most_greater', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'rank', '7'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; rank ; 7 }', 'tointer': 'select the rows whose rank record is less than or equal to 7 .'}, 'goals', '10'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose rank record is less than or equal to 7 . for the goals records of these rows , most of them are greater than 10 .', 'tostr': 'most_greater { filter_less_eq { all_rows ; rank ; 7 } ; goals ; 10 } = true'} | most_greater { filter_less_eq { all_rows ; rank ; 7 } ; goals ; 10 } = true | select the rows whose rank record is less than or equal to 7 . for the goals records of these rows , most of them are greater than 10 . | 2 | 2 | {'most_greater_1': 1, 'result_2': 2, 'filter_less_eq_0': 0, 'all_rows_3': 3, 'rank_4': 4, '7_5': 5, 'goals_6': 6, '10_7': 7} | {'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_3': 'all_rows', 'rank_4': 'rank', '7_5': '7', 'goals_6': 'goals', '10_7': '10'} | {'most_greater_1': [2], 'result_2': [], 'filter_less_eq_0': [1], 'all_rows_3': [0], 'rank_4': [0], '7_5': [0], 'goals_6': [1], '10_7': [1]} | ['rank', 'scorer', 'club', 'goals', 'matches'] | [['1', 'choi sang - kuk', 'posco atoms', '15', '30'], ['2', 'lee heung - sil', 'posco atoms', '12', '29'], ['2', 'noh soo - jin', 'yukong elephants', '12', '30'], ['4', 'kim joo - sung', 'daewoo royals', '10', '28'], ['5', 'kim hong - woon', 'posco atoms', '9', '26'], ['6', 'lee sang - cheol', 'hyundai horang - i', '8', '28'], ['7', 'park hang - seo', 'lucky - goldstar hwangso', '7', '28'], ['8', '3 players', '3 players', '6', '-'], ['11', '2 players', '2 players', '5', '-'], ['13', '5 players', '5 players', '4', '-'], ['18', '12 players', '12 players', '3', '-'], ['30', '12 players', '12 players', '2', '-'], ['42', '15 players', '15 players', '1', '-'], ['own goals', 'own goals', 'own goals', '3', '-']] |
melissa reid | https://en.wikipedia.org/wiki/Melissa_Reid | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29506171-2.html.csv | superlative | the least amount of cuts that melissa reid made in years when she played more than 15 tournaments was 12 . | {'scope': 'subset', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': 'n/a', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '15'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'tournaments played', '15'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; tournaments played ; 15 }', 'tointer': 'select the rows whose tournaments played record is greater than 15 .'}, 'cuts made'], 'result': '12', 'ind': 1, 'tostr': 'min { filter_greater { all_rows ; tournaments played ; 15 } ; cuts made }', 'tointer': 'select the rows whose tournaments played record is greater than 15 . the minimum cuts made record of these rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_greater { all_rows ; tournaments played ; 15 } ; cuts made } ; 12 } = true', 'tointer': 'select the rows whose tournaments played record is greater than 15 . the minimum cuts made record of these rows is 12 .'} | eq { min { filter_greater { all_rows ; tournaments played ; 15 } ; cuts made } ; 12 } = true | select the rows whose tournaments played record is greater than 15 . the minimum cuts made record of these rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'tournaments played_5': 5, '15_6': 6, 'cuts made_7': 7, '12_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'tournaments played_5': 'tournaments played', '15_6': '15', 'cuts made_7': 'cuts made', '12_8': '12'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'tournaments played_5': [0], '15_6': [0], 'cuts made_7': [1], '12_8': [2]} | ['year', 'tournaments played', 'cuts made', 'wins', '2nd', '3rd', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank', 'rolex ranking'] | [['2006', '1', '1', '0', '0', '0', '0', 't12', 'n / a', 'n / a', '72.33', 'n / a', '658'], ['2007', '3', '3', '0', '0', '0', '1', '9', '4050 1', 'n / a', '73.18', 'n / a', '307'], ['2008', '16', '12', '0', '3', '1', '7', '2', '136606', '12', '71.96', '26', '169'], ['2009', '14', '13', '0', '1', '2', '8', '2', '168749', '7', '71.12', '6', '128'], ['2010', '21', '20', '1', '2', '1', '10', '1', '270871', '3', '71.21', '7', '58'], ['2011', '19', '19', '2', '1', '3', '10', '1', '286578', '2', '70.83', '11', '45']] |
2008 - 09 west ham united f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_West_Ham_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539546-8.html.csv | ordinal | mccartney was the player that commanded the second highest transfer fee in the 2008 - 09 west ham united f.c. season . | {'row': '7', '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', 'transfer fee', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; transfer fee ; 2 }'}, 'name'], 'result': 'mccartney', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; transfer fee ; 2 } ; name }'}, 'mccartney'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; transfer fee ; 2 } ; name } ; mccartney } = true', 'tointer': 'select the row whose transfer fee record of all rows is 2nd maximum . the name record of this row is mccartney .'} | eq { hop { nth_argmax { all_rows ; transfer fee ; 2 } ; name } ; mccartney } = true | select the row whose transfer fee record of all rows is 2nd maximum . the name record of this row is mccartney . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'transfer fee_5': 5, '2_6': 6, 'name_7': 7, 'mccartney_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', 'transfer fee_5': 'transfer fee', '2_6': '2', 'name_7': 'name', 'mccartney_8': 'mccartney'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'transfer fee_5': [0], '2_6': [0], 'name_7': [1], 'mccartney_8': [2]} | ['name', 'country', 'status', 'moving to', 'transfer fee'] | [['solano', 'per', 'transferred', 'released', 'free'], ['zamora', 'eng', 'transferred', 'fulham', '4.8 m'], ['paintsil', 'gha', 'transferred', 'fulham', '1.5 m'], ['wright', 'eng', 'transferred', 'ipswich town', '0.5 m'], ['ljungberg', 'swe', 'transferred', 'released', 'free'], ['ferdinand', 'eng', 'transferred', 'sunderland', '8 m'], ['mccartney', 'nir', 'transferred', 'sunderland', '6 m'], ['blackmore', 'eng', 'loaned', 'thurrock', 'n / a'], ['jeffery', 'eng', 'loaned', 'leyton orient', 'n / a'], ['payne', 'eng', 'loaned', 'cheltenham town', 'n / a'], ['quashie', 'sco', 'loaned', 'birmingham city', 'n / a'], ['miller', 'eng', 'loaned', "bishop 's stortford", 'n / a'], ["n'gala", 'eng', 'loaned', 'mk dons', 'n / a'], ['spence', 'eng', 'loaned', 'leyton orient', 'n / a'], ['reid', 'eng', 'loaned', 'blackpool', 'n / a'], ['walker', 'eng', 'loaned', 'colchester united', 'n / a'], ['tomkins', 'eng', 'loaned', 'derby county', 'n / a'], ['stanislas', 'eng', 'loaned', 'southend', 'n / a'], ['etherington', 'eng', 'transferred', 'stoke', 'undisclosed']] |
2007 critérium du dauphiné libéré | https://en.wikipedia.org/wiki/2007_Crit%C3%A9rium_du_Dauphin%C3%A9_Lib%C3%A9r%C3%A9 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11667521-16.html.csv | count | spain had a total of three cyclists in the 2007 critérium du dauphiné libéré . | {'scope': 'all', 'criterion': 'equal', 'value': 'spain', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'spain'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to spain .', 'tostr': 'filter_eq { all_rows ; nation ; spain }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nation ; spain } }', 'tointer': 'select the rows whose nation record fuzzily matches to spain . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nation ; spain } } ; 3 } = true', 'tointer': 'select the rows whose nation record fuzzily matches to spain . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; nation ; spain } } ; 3 } = true | select the rows whose nation record fuzzily matches to spain . 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, 'nation_5': 5, 'spain_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', 'nation_5': 'nation', 'spain_6': 'spain', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nation_5': [0], 'spain_6': [0], '3_7': [2]} | ['cyclist', 'nation', 'team', 'time', 'uci protour points'] | [['christophe moreau', 'france', 'ag2r prévoyance', "29h 50 ' 35", '50'], ['cadel evans', 'australia', 'predictor - lotto', '+ 14', '40'], ['andrey kashechkin', 'kazakhstan', 'astana', "+ 1 ' 27", '35'], ['denis menchov', 'russia', 'rabobank', "+ 1 ' 52", '30'], ['david zabriskie', 'united states', 'team csc', "+ 2 ' 16", '25'], ['alberto contador', 'spain', 'discovery channel', "+ 4 ' 24", '20'], ['mikel astarloza', 'spain', 'eus', "+ 5 ' 00", '15'], ['manuel beltrán', 'spain', 'liquigas', "+ 5 ' 01", '10'], ['tadej valjavec', 'slovenia', 'lampre - fondital', "+ 5 ' 17", '5'], ['sylvain chavanel', 'france', 'cofidis', "+ 5 ' 38", '2']] |
1953 detroit lions season | https://en.wikipedia.org/wiki/1953_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15955525-1.html.csv | aggregation | the 1953 detroit lions season had an average attendance of 47850 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '47850', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '47850', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '47850'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 47850 } = true', 'tointer': 'the average of the attendance record of all rows is 47850 .'} | round_eq { avg { all_rows ; attendance } ; 47850 } = true | the average of the attendance record of all rows is 47850 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '47850_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '47850_5': '47850'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '47850_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 27 , 1953', 'pittsburgh steelers', 'w 38 - 21', '44587'], ['2', 'october 3 , 1953', 'baltimore colts', 'w 27 - 17', '25159'], ['3', 'october 11 , 1953', 'san francisco 49ers', 'w 24 - 21', '58079'], ['4', 'october 18 , 1953', 'los angeles rams', 'l 31 - 19', '55772'], ['5', 'october 25 , 1953', 'san francisco 49ers', 'w 14 - 10', '54662'], ['6', 'november 1 , 1953', 'los angeles rams', 'l 37 - 24', '93751'], ['7', 'november 7 , 1953', 'baltimore colts', 'w 17 - 7', '46208'], ['8', 'november 15 , 1953', 'green bay packers', 'w 14 - 7', '20834'], ['9', 'november 22 , 1953', 'chicago bears', 'w 20 - 16', '36165'], ['10', 'november 26 , 1953', 'green bay packers', 'w 34 - 15', '52547'], ['11', 'december 6 , 1953', 'chicago bears', 'w 13 - 7', '58056'], ['12', 'december 13 , 1953', 'new york giants', 'w 27 - 16', '28390']] |
eliseo salazar | https://en.wikipedia.org/wiki/Eliseo_Salazar | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219773-2.html.csv | unique | the 1989 24 hours of le mans race that eliseo salazar competed in was the only one that he finished in all of the 24 hours of le mans races that he entered . | {'scope': 'all', 'row': '4', 'col': '7', 'col_other': '1', 'criterion': 'not_equal', 'value': 'dnf', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'pos', 'dnf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record does not match to dnf .', 'tostr': 'filter_not_eq { all_rows ; pos ; dnf }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; pos ; dnf } }', 'tointer': 'select the rows whose pos record does not match to dnf . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'pos', 'dnf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record does not match to dnf .', 'tostr': 'filter_not_eq { all_rows ; pos ; dnf }'}, 'year'], 'result': '1989', 'ind': 2, 'tostr': 'hop { filter_not_eq { all_rows ; pos ; dnf } ; year }'}, '1989'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_not_eq { all_rows ; pos ; dnf } ; year } ; 1989 }', 'tointer': 'the year record of this unqiue row is 1989 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_not_eq { all_rows ; pos ; dnf } } ; eq { hop { filter_not_eq { all_rows ; pos ; dnf } ; year } ; 1989 } } = true', 'tointer': 'select the rows whose pos record does not match to dnf . there is only one such row in the table . the year record of this unqiue row is 1989 .'} | and { only { filter_not_eq { all_rows ; pos ; dnf } } ; eq { hop { filter_not_eq { all_rows ; pos ; dnf } ; year } ; 1989 } } = true | select the rows whose pos record does not match to dnf . there is only one such row in the table . the year record of this unqiue row is 1989 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'pos_7': 7, 'dnf_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1989_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_6': 'all_rows', 'pos_7': 'pos', 'dnf_8': 'dnf', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1989_10': '1989'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'pos_7': [0], 'dnf_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1989_10': [3]} | ['year', 'class', 'tyres', 'team', 'co - drivers', 'laps', 'pos', 'class pos'] | [['1982', 'c', 'd', 'dome co ltd', 'chris craft', '85', 'dnf', 'dnf'], ['1983', 'c', 'd', 'dome racing', 'chris craft nick mason', '75', 'dnf', 'dnf'], ['1988', 'c2', 'g', 'spice engineering', 'almo coppelli thorkild thyrring', '281', 'dnf', 'dnf'], ['1989', 'c1', 'd', 'silk cut jaguar tom walkinshaw racing', 'alain ferté michel ferté', '368', '8th', '7th'], ['1990', 'c1', 'g', 'silk cut jaguar tom walkinshaw racing', 'davy jones michel ferté', '282', 'dnf', 'dnf'], ['1997', 'lmp', 'p', 'pacific racing ltd', 'harri toivonen jesús pareja', '6', 'dnf', 'dnf']] |
1992 - 93 belarusian premier league | https://en.wikipedia.org/wiki/1992%E2%80%9393_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14744744-1.html.csv | comparative | in the 1992 - 93 belarusian premier league , dinamo minsk had a higher position than dinamo brest . | {'row_1': '1', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'dinamo minsk'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to dinamo minsk .', 'tostr': 'filter_eq { all_rows ; team ; dinamo minsk }'}, 'position in 1992'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; dinamo minsk } ; position in 1992 }', 'tointer': 'select the rows whose team record fuzzily matches to dinamo minsk . take the position in 1992 record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'dinamo brest'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to dinamo brest .', 'tostr': 'filter_eq { all_rows ; team ; dinamo brest }'}, 'position in 1992'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; dinamo brest } ; position in 1992 }', 'tointer': 'select the rows whose team record fuzzily matches to dinamo brest . take the position in 1992 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; team ; dinamo minsk } ; position in 1992 } ; hop { filter_eq { all_rows ; team ; dinamo brest } ; position in 1992 } } = true', 'tointer': 'select the rows whose team record fuzzily matches to dinamo minsk . take the position in 1992 record of this row . select the rows whose team record fuzzily matches to dinamo brest . take the position in 1992 record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; team ; dinamo minsk } ; position in 1992 } ; hop { filter_eq { all_rows ; team ; dinamo brest } ; position in 1992 } } = true | select the rows whose team record fuzzily matches to dinamo minsk . take the position in 1992 record of this row . select the rows whose team record fuzzily matches to dinamo brest . take the position in 1992 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, 'team_7': 7, 'dinamo minsk_8': 8, 'position in 1992_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'dinamo brest_12': 12, 'position in 1992_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', 'team_7': 'team', 'dinamo minsk_8': 'dinamo minsk', 'position in 1992_9': 'position in 1992', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'dinamo brest_12': 'dinamo brest', 'position in 1992_13': 'position in 1992'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'dinamo minsk_8': [0], 'position in 1992_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'dinamo brest_12': [1], 'position in 1992_13': [3]} | ['team', 'location', 'venue', 'capacity', 'position in 1992'] | [['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '1'], ['dnepr', 'mogilev', 'spartak', '11200', '2'], ['dinamo brest', 'brest', 'dinamo , brest', '10080', '3'], ['fandok', 'bobruisk', 'spartak , bobruisk', '3550', '4'], ['neman', 'grodno', 'neman', '6300', '5'], ['kim', 'vitebsk', 'central , vitebsk', '8300', '6'], ['torpedo mogilev', 'mogilev', 'torpedo , mogilev', '3500', '7'], ['vedrich', 'rechytsa', 'central , rechytsa', '3550', '8'], ['molodechno', 'molodechno', 'city stadium , molodechno', '5500', '9'], ['torpedo minsk', 'minsk', 'torpedo , minsk', '5200', '10'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '11'], ['obuvshchik', 'lida', 'city stadium , lida', '4000', '12'], ['torpedo zhodino', 'zhodino', 'torpedo , zhodino', '3020', '13'], ['stroitel', 'starye dorogi', 'stroitel', '2000', '14'], ['lokomotiv', 'vitebsk', 'central , vitebsk', '8300', '15'], ['gomselmash', 'gomel', 'central , gomel', '11800', '16'], ['belarus', 'minsk', 'dinamo , minsk', '41040', 'first league , 1']] |
2010 - 11 uefa champions league | https://en.wikipedia.org/wiki/2010%E2%80%9311_UEFA_Champions_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18255941-8.html.csv | unique | of the teams 2 ’s that had 1-0 in the first leg , the only one with 0-0 in the second leg was jeunesse esch . | {'scope': 'subset', 'row': '15', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': '0-0', 'subset': {'col': '4', 'criterion': 'equal', 'value': '1 - 0'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st leg', '1 - 0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; 1st leg ; 1 - 0 }', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 0 .'}, '2nd leg', '0-0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 0 . among these rows , select the rows whose 2nd leg record fuzzily matches to 0-0 .', 'tostr': 'filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } }', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 0 . among these rows , select the rows whose 2nd leg record fuzzily matches to 0-0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '1st leg', '1 - 0'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; 1st leg ; 1 - 0 }', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 0 .'}, '2nd leg', '0-0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 0 . among these rows , select the rows whose 2nd leg record fuzzily matches to 0-0 .', 'tostr': 'filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 }'}, 'team 2'], 'result': 'jeunesse esch', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } ; team 2 }'}, 'jeunesse esch'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } ; team 2 } ; jeunesse esch }', 'tointer': 'the team 2 record of this unqiue row is jeunesse esch .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } ; team 2 } ; jeunesse esch } } = true', 'tointer': 'select the rows whose 1st leg record fuzzily matches to 1 - 0 . among these rows , select the rows whose 2nd leg record fuzzily matches to 0-0 . there is only one such row in the table . the team 2 record of this unqiue row is jeunesse esch .'} | and { only { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; 1st leg ; 1 - 0 } ; 2nd leg ; 0-0 } ; team 2 } ; jeunesse esch } } = true | select the rows whose 1st leg record fuzzily matches to 1 - 0 . among these rows , select the rows whose 2nd leg record fuzzily matches to 0-0 . there is only one such row in the table . the team 2 record of this unqiue row is jeunesse esch . | 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, '1st leg_8': 8, '1 - 0_9': 9, '2nd leg_10': 10, '0-0_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'team 2_12': 12, 'jeunesse esch_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', '1st leg_8': '1st leg', '1 - 0_9': '1 - 0', '2nd leg_10': '2nd leg', '0-0_11': '0-0', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'team 2_12': 'team 2', 'jeunesse esch_13': 'jeunesse esch'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], '1st leg_8': [0], '1 - 0_9': [0], '2nd leg_10': [1], '0-0_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'team 2_12': [3], 'jeunesse esch_13': [4]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['liepājas metalurgs', '0 - 5', 'sparta prague', '0 - 3', '0 - 2'], ['aktobe', '3 - 1', 'olimpi rustavi', '2 - 0', '1 - 1'], ['levadia', '3 - 4', 'debrecen', '1 - 1', '2 - 3'], ['partizan', '4 - 1', 'pyunik', '3 - 1', '1 - 0'], ['inter baku', '1 - 1 ( 8 - 9 p )', 'lech poznań', '0 - 1', '1 - 0 ( aet )'], ['dinamo zagreb', '5 - 4', 'koper', '5 - 1', '0 - 3'], ['litex lovech', '5 - 0', 'rudar pljevlja', '1 - 0', '4 - 0'], ['birkirkara', '1 - 3', 'žilina', '1 - 0', '0 - 3'], ['sheriff tiraspol', '3 - 2', 'dinamo tirana', '3 - 1', '0 - 1'], ['hapoel tel aviv', '6 - 0', 'željezničar', '5 - 0', '1 - 0'], ['omonia', '5 - 0', 'renova', '3 - 0', '2 - 0'], ['red bull salzburg', '5 - 1', 'hb tórshavn', '5 - 0', '0 - 1'], ['bohemians', '1 - 4', 'the new saints', '1 - 0', '0 - 4'], ['bate', '6 - 1', 'fh', '5 - 1', '1 - 0'], ['aik', '1 - 0', 'jeunesse esch', '1 - 0', '0 - 0'], ['linfield', '0 - 2', 'rosenborg', '0 - 0', '0 - 2'], ['ekranas', '1 - 2', 'hjk helsinki', '1 - 0', '0 - 2 ( aet )']] |
1943 vfl season | https://en.wikipedia.org/wiki/1943_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808346-8.html.csv | count | in the 1943 vfl season , two games had more than 10000 people in attendance . | {'scope': 'all', 'criterion': 'greater_than', 'value': '10000', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; crowd ; 10000 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; crowd ; 10000 } }', 'tointer': 'select the rows whose crowd record is greater than 10000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; crowd ; 10000 } } ; 2 } = true', 'tointer': 'select the rows whose crowd record is greater than 10000 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; crowd ; 10000 } } ; 2 } = true | select the rows whose crowd record is greater than 10000 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '10000_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '10000_6': '10000', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '10000_6': [0], '2_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '10.11 ( 71 )', 'south melbourne', '6.14 ( 50 )', 'western oval', '7500', '26 june 1943'], ['collingwood', '10.21 ( 81 )', 'melbourne', '13.9 ( 87 )', 'victoria park', '5000', '26 june 1943'], ['carlton', '15.16 ( 106 )', 'fitzroy', '9.13 ( 67 )', 'princes park', '12000', '26 june 1943'], ['richmond', '15.16 ( 106 )', 'hawthorn', '8.14 ( 62 )', 'punt road oval', '16000', '26 june 1943'], ['st kilda', '15.8 ( 98 )', 'essendon', '20.19 ( 139 )', 'toorak park', '6000', '26 june 1943']] |
2007 san jose sabercats season | https://en.wikipedia.org/wiki/2007_San_Jose_SaberCats_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11786687-3.html.csv | aggregation | in the 2007 san jose sabercats season , the players scored a combined total of 192 yards . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '192', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'yards'], 'result': '192', 'ind': 0, 'tostr': 'sum { all_rows ; yards }'}, '192'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; yards } ; 192 } = true', 'tointer': 'the sum of the yards record of all rows is 192 .'} | round_eq { sum { all_rows ; yards } ; 192 } = true | the sum of the yards record of all rows is 192 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'yards_4': 4, '192_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'yards_4': 'yards', '192_5': '192'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'yards_4': [0], '192_5': [1]} | ['player', 'car', 'yards', 'avg', "td 's", 'long'] | [['brian johnson', '44', '100', '2.3', '9', '20'], ['matt kinsinger', '25', '47', '1.9', '6', '16'], ['mark grieb', '7', '27', '3.9', '2', '10'], ['phil dwyain glover', '12', '10', '8', '5', '3'], ['rodney bernard wright , jr', '9', '8', '9', '2', '3'], ['jason geathers', '2', '0', '0', '0', '1'], ['craig whelihan', '1', '0', '0', '0', '0']] |
irish presidential election , 2011 | https://en.wikipedia.org/wiki/Irish_presidential_election%2C_2011 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15684434-4.html.csv | aggregation | across the four red c polls for the 2011 irish election , davis polled at an average of 7 % . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '7 %', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'red c'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'polling agency', 'red c'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; polling agency ; red c }', 'tointer': 'select the rows whose polling agency record fuzzily matches to red c .'}, 'davis'], 'result': '7 %', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; polling agency ; red c } ; davis }'}, '7 %'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; polling agency ; red c } ; davis } ; 7 % } = true', 'tointer': 'select the rows whose polling agency record fuzzily matches to red c . the average of the davis record of these rows is 7 % .'} | round_eq { avg { filter_eq { all_rows ; polling agency ; red c } ; davis } ; 7 % } = true | select the rows whose polling agency record fuzzily matches to red c . the average of the davis record of these rows is 7 % . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'polling agency_5': 5, 'red c_6': 6, 'davis_7': 7, '7%_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'polling agency_5': 'polling agency', 'red c_6': 'red c', 'davis_7': 'davis', '7%_8': '7 %'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'polling agency_5': [0], 'red c_6': [0], 'davis_7': [1], '7%_8': [2]} | ['date', 'source', 'polling agency', 'davis', 'gallagher', 'higgins', 'mcguinness', 'mitchell', 'norris', 'scallon'] | [['25 september 2011', 'the sunday business post', 'red c', '13 %', '11 %', '18 %', '16 %', '13 %', '21 %', '6 %'], ['6 october 2011', 'the irish times', 'ipsos mrbi', '12 %', '20 %', '23 %', '19 %', '9 %', '11 %', '6 %'], ['6 october 2011', 'paddy power', 'red c', '9 %', '21 %', '25 %', '16 %', '10 %', '14 %', '5 %'], ['16 october 2011', 'the sunday business post', 'red c', '4 %', '39 %', '27 %', '13 %', '8 %', '7 %', '2 %'], ['22 october 2011', 'the sunday business post', 'red c', '2 %', '40 %', '26 %', '13 %', '6 %', '10 %', '3 %'], ['23 october 2011', 'the irish times', 'ipsos mrbi', '3 %', '40 %', '25 %', '15 %', '6 %', '8 %', '3 %']] |
british rail classes 253 , 254 and 255 | https://en.wikipedia.org/wiki/British_Rail_Classes_253%2C_254_and_255 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1131463-1.html.csv | ordinal | the class 254 had a higher number of cars per set compared to the class 253 among the british rail classes 253 , 254 and 255 . | {'row': '4', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'cars per set', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; cars per set ; 1 }'}, 'class'], 'result': 'class 254', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; cars per set ; 1 } ; class }'}, 'class 254'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; cars per set ; 1 } ; class } ; class 254 } = true', 'tointer': 'select the row whose cars per set record of all rows is 1st maximum . the class record of this row is class 254 .'} | eq { hop { nth_argmax { all_rows ; cars per set ; 1 } ; class } ; class 254 } = true | select the row whose cars per set record of all rows is 1st maximum . the class record of this row is class 254 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'cars per set_5': 5, '1_6': 6, 'class_7': 7, 'class 254_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', 'cars per set_5': 'cars per set', '1_6': '1', 'class_7': 'class', 'class 254_8': 'class 254'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'cars per set_5': [0], '1_6': [0], 'class_7': [1], 'class 254_8': [2]} | ['class', 'operator', 'number', 'year built', 'cars per set', 'unit numbers'] | [['class 253', 'br western region', '27', '1975 - 1977', '9', '253001 - 253027'], ['class 253', 'br western region', '13', '1978 - 1979', '9', '253028 - 253040'], ['class 253', 'br cross country', '18', '1981 - 1982', '9', '253041 - 253058'], ['class 254', 'br eastern region br scottish region', '32', '1977 - 1979', '10', '254001 - 254032'], ['class 254', 'br eastern region br scottish region', '4', '1982', '10', '254033 - 254037']] |
list of active sumo wrestlers | https://en.wikipedia.org/wiki/List_of_active_sumo_wrestlers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1557974-1.html.csv | ordinal | among active sumo wrestlers , kyokushūhō kōki had the third most recent debut . | {'row': '4', 'col': '3', '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', 'debut', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; debut ; 3 }'}, 'ring name'], 'result': 'kyokushūhō kōki', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; debut ; 3 } ; ring name }'}, 'kyokushūhō kōki'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; debut ; 3 } ; ring name } ; kyokushūhō kōki } = true', 'tointer': 'select the row whose debut record of all rows is 3rd maximum . the ring name record of this row is kyokushūhō kōki .'} | eq { hop { nth_argmax { all_rows ; debut ; 3 } ; ring name } ; kyokushūhō kōki } = true | select the row whose debut record of all rows is 3rd maximum . the ring name record of this row is kyokushūhō kōki . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'debut_5': 5, '3_6': 6, 'ring name_7': 7, 'kyokushūhō kōki_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', 'debut_5': 'debut', '3_6': '3', 'ring name_7': 'ring name', 'kyokushūhō kōki_8': 'kyokushūhō kōki'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'debut_5': [0], '3_6': [0], 'ring name_7': [1], 'kyokushūhō kōki_8': [2]} | ['ring name', 'current rank', 'debut', 'stable', 'birthplace', 'career and other notes'] | [['chiyonokuni toshiki', 'f0 jūryō 3 west', '2006 - 5', 'kokonoe', 'mie', 'former maegashira 8 , jūryō champion'], ['ikioi shōta', 'e0 maegashira 6 west', '2005 - 3', 'isenoumi', 'os ōsaka', 'former maegashira 1 , jūryō champion'], ['kimikaze toshiji', 'g1 makushita 13 west', '2009 - 1', 'oguruma', 'tokyo', 'former maegashira 13 , jūryō champion'], ['kyokushūhō kōki', 'e1 maegashira 14 east', '2007 - 5', 'o ōshima', 'z mongolia', 'former maegashira 12'], ['tamaasuka daisuke', 'e1 maegashira 16 west', '1998 - 3', 'kataonami', 'aichi', 'former maegashira 9 , two time jūryō winner'], ['tochinoshin tsuyoshi', 'f1 jūryō 14 west', '2006 - 3', 'kasugano', 'z mtskheta , georgia', 'many time komusubi , fellow countryman of kokkai'], ['tochiōzan yūichirō', 'c sekiwake west', '2005 - 1', 'kasugano', 'kōchi', 'many time sekiwake , longtime rival of gōeidō'], ['tokitenkū yoshiaki', 'e1 maegashira 10 east', '2002 - 7', 'tokitsukaze', 'z töv aimag , mongolia', 'former komusubi , consistent maegashira performer'], ['tokushōryū makota', 'e1 maegashira 14 west', '2009 - 1', 'kise', 'nara', 'former maegashira 10']] |
akapusi qera | https://en.wikipedia.org/wiki/Akapusi_Qera | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11470402-1.html.csv | count | akapusi qera played in a non-cap friendly competition 2 times . | {'scope': 'all', 'criterion': 'equal', 'value': 'non - cap friendly', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'non - cap friendly'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose competition record fuzzily matches to non - cap friendly .', 'tostr': 'filter_eq { all_rows ; competition ; non - cap friendly }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; competition ; non - cap friendly } }', 'tointer': 'select the rows whose competition record fuzzily matches to non - cap friendly . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; competition ; non - cap friendly } } ; 2 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to non - cap friendly . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; competition ; non - cap friendly } } ; 2 } = true | select the rows whose competition record fuzzily matches to non - cap friendly . 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, 'competition_5': 5, 'non - cap friendly_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', 'competition_5': 'competition', 'non - cap friendly_6': 'non - cap friendly', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'non - cap friendly_6': [0], '2_7': [2]} | ['date', 'venue', 'opponent', 'result', 'competition'] | [['01 / 07 / 06', 'nagai stadium , osaka', 'japan', 'win - 15 - 29', 'pacific nations cup'], ['14 / 07 / 06', 'adelaide oval , adelaide', 'australia a', 'loss - 47 - 18', 'non - cap friendly'], ['26 / 05 / 07', 'churchill park , lautoka', 'japan', 'win - 30 - 15', 'pacific nations cup'], ['25 / 08 / 07', 'stade municipal , camares', 'sc albi', 'win - 24 - 47', 'non - cap friendly'], ['12 / 09 / 07', 'stadium de toulouse , toulouse', 'japan', 'win - 35 - 31', '2007 rugby world cup'], ['29 / 09 / 07', 'stade de la beaujoire , nantes', 'wales', 'win - 38 - 34', '2007 rugby world cup'], ['05 / 06 / 13', 'twin elm rugby park , nepean', 'canada', 'loss - 20 - 18', 'pacific nations cup']] |
shaun murphy ( snooker player ) | https://en.wikipedia.org/wiki/Shaun_Murphy_%28snooker_player%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1795208-10.html.csv | unique | the world series - berlin event was the only time graeme dott was the opponent in the final . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'graeme dott', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent in the final', 'graeme dott'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent in the final record fuzzily matches to graeme dott .', 'tostr': 'filter_eq { all_rows ; opponent in the final ; graeme dott }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; opponent in the final ; graeme dott } }', 'tointer': 'select the rows whose opponent in the final record fuzzily matches to graeme dott . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent in the final', 'graeme dott'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent in the final record fuzzily matches to graeme dott .', 'tostr': 'filter_eq { all_rows ; opponent in the final ; graeme dott }'}, 'championship'], 'result': 'world series - berlin event', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent in the final ; graeme dott } ; championship }'}, 'world series - berlin event'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent in the final ; graeme dott } ; championship } ; world series - berlin event }', 'tointer': 'the championship record of this unqiue row is world series - berlin event .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; opponent in the final ; graeme dott } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; graeme dott } ; championship } ; world series - berlin event } } = true', 'tointer': 'select the rows whose opponent in the final record fuzzily matches to graeme dott . there is only one such row in the table . the championship record of this unqiue row is world series - berlin event .'} | and { only { filter_eq { all_rows ; opponent in the final ; graeme dott } } ; eq { hop { filter_eq { all_rows ; opponent in the final ; graeme dott } ; championship } ; world series - berlin event } } = true | select the rows whose opponent in the final record fuzzily matches to graeme dott . there is only one such row in the table . the championship record of this unqiue row is world series - berlin event . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent in the final_7': 7, 'graeme dott_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'championship_9': 9, 'world series - berlin event_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent in the final_7': 'opponent in the final', 'graeme dott_8': 'graeme dott', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'championship_9': 'championship', 'world series - berlin event_10': 'world series - berlin event'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'opponent in the final_7': [0], 'graeme dott_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'championship_9': [2], 'world series - berlin event_10': [3]} | ['outcome', 'year', 'championship', 'opponent in the final', 'score'] | [['runner - up', '2008', 'world series - berlin event', 'graeme dott', '1 - 6'], ['winner', '2008', 'paul hunter classic', 'mark selby', '4 - 0'], ['winner', '2009', 'world series - grand final', 'john higgins', '6 - 2'], ['winner', '2009', 'world series - champion of champions challenge', 'jimmy white', '5 - 1'], ['winner', '2009', 'paul hunter classic', 'jimmy white', '4 - 0']] |
jazzy b | https://en.wikipedia.org/wiki/Jazzy_B | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15217634-1.html.csv | majority | a majority of jazzy b 's records were put together by sukshinder shinda . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sukshinder shinda', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'music', 'sukshinder shinda'], 'result': True, 'ind': 0, 'tointer': 'for the music records of all rows , most of them fuzzily match to sukshinder shinda .', 'tostr': 'most_eq { all_rows ; music ; sukshinder shinda } = true'} | most_eq { all_rows ; music ; sukshinder shinda } = true | for the music records of all rows , most of them fuzzily match to sukshinder shinda . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'music_3': 3, 'sukshinder shinda_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'music_3': 'music', 'sukshinder shinda_4': 'sukshinder shinda'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'music_3': [0], 'sukshinder shinda_4': [0]} | ['year', 'album', 'record label', 'info', 'music'] | [['2013', 'cut like a diamond', 'replay music / sony music india', 'tracks 10', 'partners in rhyme'], ['2011', 'maharajas', 'moviebox / speed records / music waves', 'tracks 12', 'sukshinder shinda'], ['2008', 'rambo', 'moviebox / speed records / planet recordz', 'tracks 11', 'sukshinder shinda'], ['2005', 'romeo', 'moviebox / tips / music waves', 'tracks 10', 'sukshinder shinda'], ['2002', 'tera roop', 'moviebox / tips / music waves', 'tracks 9', 'sukshinder shinda'], ['2001', 'oh kedi oh kehri', 'moviebox / music waves / tips', 'tracks 8 tracks 8', 'sukshinder shinda'], ['2000', "stayin ' real surma", 'kiss records / music waves / tips', 'tracks 9 tracks 8', 'sukshinder shinda sukshinder shinda'], ['1999', 'all eyez on me', 'kiss records / supertone melodies / music waves', 'tracks 9', 'sukshinder shinda'], ['1997', 'folkal attraction', 'kiss records / supertone melodies / music waves', 'tracks 8', 'sukshinder shinda'], ['1995', "folk 'n funky", 'kiss records / supertone melodies / music waves', 'tracks 8', 'sukshinder shinda'], ['1994', 'the canadian spice', 'supertone melodies', 'tracks 11', 'sukshinder shinda'], ['1993', 'ghugian da jorra', 'kiss records / supertone melodies', 'tracks 8', 'sukshinder shinda']] |
khym | https://en.wikipedia.org/wiki/KHYM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14993391-1.html.csv | count | four of the khym radio channels operate with an erp wattage of 170 . | {'scope': 'all', 'criterion': 'equal', 'value': '170', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'erp w', '170'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose erp w record is equal to 170 .', 'tostr': 'filter_eq { all_rows ; erp w ; 170 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; erp w ; 170 } }', 'tointer': 'select the rows whose erp w record is equal to 170 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; erp w ; 170 } } ; 4 } = true', 'tointer': 'select the rows whose erp w record is equal to 170 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; erp w ; 170 } } ; 4 } = true | select the rows whose erp w record is equal to 170 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'erp w_5': 5, '170_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'erp w_5': 'erp w', '170_6': '170', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'erp w_5': [0], '170_6': [0], '4_7': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k297al', '107.3', 'dighton , kansas', '170', 'd', 'fcc'], ['k236 am', '95.1', 'elkhart , kansas', '170', 'd', 'fcc'], ['k207et', '89.3', 'healy , kansas', '75', 'd', 'fcc'], ['k239ax', '95.7', 'larned , kansas', '170', 'd', 'fcc'], ['k211ch', '90.5', 'leoti , kansas', '250', 'd', 'fcc'], ['k232dh', '94.3', 'ulysses , kansas', '170', 'd', 'fcc']] |
2007 - 08 english premiership ( rugby union ) | https://en.wikipedia.org/wiki/2007%E2%80%9308_English_Premiership_%28rugby_union%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10234157-2.html.csv | comparative | the player ryan lamb did more tries in the 2007 - 08 english premiership ( rugby union ) compared to shane drahm , when considering the top scorers from that season . | {'row_1': '6', 'row_2': '8', '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', 'name', 'ryan lamb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to ryan lamb .', 'tostr': 'filter_eq { all_rows ; name ; ryan lamb }'}, 'tries'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; ryan lamb } ; tries }', 'tointer': 'select the rows whose name record fuzzily matches to ryan lamb . take the tries record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'shane drahm'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to shane drahm .', 'tostr': 'filter_eq { all_rows ; name ; shane drahm }'}, 'tries'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; shane drahm } ; tries }', 'tointer': 'select the rows whose name record fuzzily matches to shane drahm . take the tries record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; ryan lamb } ; tries } ; hop { filter_eq { all_rows ; name ; shane drahm } ; tries } } = true', 'tointer': 'select the rows whose name record fuzzily matches to ryan lamb . take the tries record of this row . select the rows whose name record fuzzily matches to shane drahm . take the tries record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; ryan lamb } ; tries } ; hop { filter_eq { all_rows ; name ; shane drahm } ; tries } } = true | select the rows whose name record fuzzily matches to ryan lamb . take the tries record of this row . select the rows whose name record fuzzily matches to shane drahm . take the tries 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, 'name_7': 7, 'ryan lamb_8': 8, 'tries_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'shane drahm_12': 12, 'tries_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', 'name_7': 'name', 'ryan lamb_8': 'ryan lamb', 'tries_9': 'tries', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'shane drahm_12': 'shane drahm', 'tries_13': 'tries'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'ryan lamb_8': [0], 'tries_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'shane drahm_12': [1], 'tries_13': [3]} | ['points', 'name', 'club', 'tries', 'drop'] | [['207', 'andy goode', 'leicester tigers', '1', '4'], ['201', 'charlie hodgson', 'sale sharks', '0', '9'], ['192', 'danny cipriani', 'london wasps', '6', '0'], ['179', 'glen jackson', 'saracens', '2', '2'], ['178', 'olly barkley', 'bath rugby', '3', '0'], ['152', 'ryan lamb', 'gloucester rugby', '4', '1'], ['127', 'alberto di bernardo', 'leeds carnegie', '0', '5'], ['118', 'shane drahm', 'worcester warriors', '1', '1'], ['115', 'adrian jarvis', 'harlequins', '0', '0'], ['107', 'chris malone', 'harlequins', '2', '2']] |
1980 world series | https://en.wikipedia.org/wiki/1980_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1218070-1.html.csv | count | three of the matches in the 1980 world series were held at the royals stadium . | {'scope': 'all', 'criterion': 'equal', 'value': 'royals stadium', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'royals stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to royals stadium .', 'tostr': 'filter_eq { all_rows ; location ; royals stadium }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; royals stadium } }', 'tointer': 'select the rows whose location record fuzzily matches to royals stadium . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; royals stadium } } ; 3 } = true', 'tointer': 'select the rows whose location record fuzzily matches to royals stadium . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; location ; royals stadium } } ; 3 } = true | select the rows whose location record fuzzily matches to royals stadium . 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, 'location_5': 5, 'royals stadium_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', 'location_5': 'location', 'royals stadium_6': 'royals stadium', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'royals stadium_6': [0], '3_7': [2]} | ['game', 'date', 'location', 'time', 'attendance'] | [['1', 'october 14', 'veterans stadium', '3:01', '65791'], ['2', 'october 15', 'veterans stadium', '3:01', '65775'], ['3', 'october 17', 'royals stadium', '3:19', '42380'], ['4', 'october 18', 'royals stadium', '2:37', '42363'], ['5', 'october 19', 'royals stadium', '2:51', '42369'], ['6', 'october 21', 'veterans stadium', '3:00', '65838']] |
matt johnson ( tv presenter ) | https://en.wikipedia.org/wiki/Matt_Johnson_%28TV_presenter%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28352386-1.html.csv | aggregation | the average score given to matt johnson by julian clary is 8 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'julian clary'], 'result': '8', 'ind': 0, 'tostr': 'avg { all_rows ; julian clary }'}, '8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; julian clary } ; 8 } = true', 'tointer': 'the average of the julian clary record of all rows is 8 .'} | round_eq { avg { all_rows ; julian clary } ; 8 } = true | the average of the julian clary record of all rows is 8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'julian clary_4': 4, '8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'julian clary_4': 'julian clary', '8_5': '8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'julian clary_4': [0], '8_5': [1]} | ['week', 'portraying', 'song', 'julian clary', 'emma bunton', 'guest judge', 'bonus points', 'total', 'result'] | [['1', 'jon bon jovi', "livin ' on a prayer", '7', '8', '7', '0', '22', 'not in top 3'], ['2', 'taylor swift', 'we are never ever getting back together', '7', '5', '7', '5', '24', 'not in top 3'], ['4', 'freddie mercury', "do n't stop me now", '10', '10', '10', '5', '35', 'winner'], ['5', 'rod stewart', "da ya think i 'm sexy", '8', '8', '8', '0', '24', 'runner - up'], ['6', 'bruce springsteen', 'born in the usa', 'n / a', 'n / a', 'n / a', 'n / a', 'n / a', 'runner - up']] |
aquatics at the 1982 commonwealth games | https://en.wikipedia.org/wiki/Aquatics_at_the_1982_Commonwealth_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13049944-3.html.csv | superlative | the nation that won the most metals in total in the aquatics at the 1982 commonwealth games , was australia . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'nation'], 'result': 'australia', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; nation }'}, 'australia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; nation } ; australia } = true', 'tointer': 'select the row whose total record of all rows is maximum . the nation record of this row is australia .'} | eq { hop { argmax { all_rows ; total } ; nation } ; australia } = true | select the row whose total record of all rows is maximum . the nation record of this row is australia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'nation_6': 6, 'australia_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'nation_6': 'nation', 'australia_7': 'australia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'nation_6': [1], 'australia_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'australia', '13', '13', '8', '34'], ['2', 'canada', '9', '6', '9', '24'], ['3', 'england', '7', '7', '8', '22'], ['4', 'scotland', '-', '3', '3', '6'], ['5', 'new zealand', '-', '13', '9', '1'], ['total', 'total', '29', '29', '29', '87']] |
andy dalton | https://en.wikipedia.org/wiki/Andy_Dalton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12857517-1.html.csv | count | andy dalton played for texas christian university all five years between 2006 and 2010 . | {'scope': 'all', 'criterion': 'equal', 'value': 'tcu', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'tcu'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to tcu .', 'tostr': 'filter_eq { all_rows ; team ; tcu }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; tcu } }', 'tointer': 'select the rows whose team record fuzzily matches to tcu . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; tcu } } ; 5 } = true', 'tointer': 'select the rows whose team record fuzzily matches to tcu . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; team ; tcu } } ; 5 } = true | select the rows whose team record fuzzily matches to tcu . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'tcu_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'tcu_6': 'tcu', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'tcu_6': [0], '5_7': [2]} | ['year', 'team', 'attempts', 'completions', 'completion %', 'yards'] | [['2006', 'tcu', 'redshirt', 'redshirt', 'redshirt', 'redshirt'], ['2007', 'tcu', '371', '222', '59.8 %', '2459'], ['2008', 'tcu', '307', '182', '59.3 %', '2242'], ['2009', 'tcu', '323', '199', '61.6 %', '2756'], ['2010', 'tcu', '316', '209', '66.1 %', '2857'], ['college totals', 'college totals', '1317', '812', '61.7 %', '10314']] |
geoff lees | https://en.wikipedia.org/wiki/Geoff_Lees | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1228378-2.html.csv | aggregation | from the years 1978 to 1982 , geoff lees earned an average of zero points in the formula one world championship . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '0', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '0', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 0 } = true', 'tointer': 'the average of the points record of all rows is 0 .'} | round_eq { avg { all_rows ; points } ; 0 } = true | the average of the points record of all rows is 0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '0_5': '0'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '0_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1978', 'mario deliotti racing', 'ensign n175', 'ford v8', '0'], ['1979', 'candy tyrrell team', 'tyrrell 009', 'ford v8', '0'], ['1980', 'shadow cars', 'shadow dn11', 'ford v8', '0'], ['1980', 'shadow cars', 'shadow dn12', 'ford v8', '0'], ['1980', 'unipart racing team', 'ensign n180', 'ford v8', '0'], ['1980', 'ram theodore', 'williams fw07b', 'ford v8', '0'], ['1982', 'theodore racing team', 'theodore ty02', 'ford v8', '0'], ['1982', 'john player team lotus', 'lotus 91', 'ford v8', '0']] |
2002 - 03 san antonio spurs season | https://en.wikipedia.org/wiki/2002%E2%80%9303_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13667936-7.html.csv | count | tim duncan was the spur 's leading scorer 7 times in the 2002-2003 season . | {'scope': 'all', 'criterion': 'equal', 'value': 'tim duncan', 'result': '7', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'leading scorer', 'tim duncan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose leading scorer record fuzzily matches to tim duncan .', 'tostr': 'filter_eq { all_rows ; leading scorer ; tim duncan }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; leading scorer ; tim duncan } }', 'tointer': 'select the rows whose leading scorer record fuzzily matches to tim duncan . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; leading scorer ; tim duncan } } ; 7 } = true', 'tointer': 'select the rows whose leading scorer record fuzzily matches to tim duncan . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; leading scorer ; tim duncan } } ; 7 } = true | select the rows whose leading scorer record fuzzily matches to tim duncan . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'leading scorer_5': 5, 'tim duncan_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'leading scorer_5': 'leading scorer', 'tim duncan_6': 'tim duncan', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'leading scorer_5': [0], 'tim duncan_6': [0], '7_7': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'record'] | [['1 february 2003', 'spurs', '67 - 65', 'heat', 'tony parker ( 18 )', '31 - 16'], ['5 february 2003', 'spurs', '103 - 99', 'warriors', 'tim duncan ( 30 )', '32 - 16'], ['6 february 2003', 'spurs', '83 - 74', 'nuggets', 'tim duncan ( 25 )', '33 - 16'], ['11 february 2003', 'spurs', '116 - 111', 'blazers', 'tim duncan ( 36 )', '34 - 16'], ['14 february 2003', 'spurs', '103 - 95', 'lakers', 'tim duncan ( 28 )', '35 - 16'], ['16 february 2003', 'spurs', '104 - 101', 'kings', 'tim duncan ( 34 )', '36 - 16'], ['18 february 2003', 'nuggets', '76 - 101', 'spurs', 'bruce bowen ( 18 )', '37 - 16'], ['20 february 2003', 'spurs', '87 - 95', 'mavericks', 'malik rose ( 25 )', '37 - 17'], ['22 february 2003', 'pacers', '96 - 105', 'spurs', 'tim duncan ( 21 )', '38 - 17'], ['25 february 2003', 'heat', '69 - 84', 'spurs', 'tim duncan ( 17 )', '39 - 17']] |
rowing at the 2008 summer olympics - men 's coxless pair | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_coxless_pair | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662689-7.html.csv | aggregation | the average finish time of the teams in the 2008 summer olympic men 's coxless pairs was 6:40.52 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '6:40.52', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '6:40.52', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '6:40.52'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 6:40.52 } = true', 'tointer': 'the average of the time record of all rows is 6:40.52 .'} | round_eq { avg { all_rows ; time } ; 6:40.52 } = true | the average of the time record of all rows is 6:40.52 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '6:40.52_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '6:40.52_5': '6:40.52'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '6:40.52_5': [1]} | ['rank', 'athlete', 'country', 'time', 'notes'] | [['1', 'drew ginn , duncan free', 'australia', '6:34.29', 'fa'], ['2', 'tyler winklevoss , cameron winklevoss', 'united states', '6:36.65', 'fa'], ['3', 'tom lehmann , felix drahotta', 'germany', '6:37.26', 'fa'], ['4', 'goran jagar , nikola stojiä ‡', 'serbia', '6:38.96', 'fb'], ['5', 'giuseppe de vita , raffaello leonardo', 'italy', '6:47.30', 'fb'], ['6', 'morten nielsen , thomas larsen', 'denmark', '6:48.65', 'fb']] |
2007 - 08 st. louis blues season | https://en.wikipedia.org/wiki/2007%E2%80%9308_St._Louis_Blues_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11801649-5.html.csv | majority | all games of the st. louis blues ' in the 2007 - 08 season were played in the month of december . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'december', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to december .', 'tostr': 'all_eq { all_rows ; date ; december } = true'} | all_eq { all_rows ; date ; december } = true | for the date records of all rows , all of them fuzzily match to december . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'december_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'december_4': 'december'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'december_4': [0]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['december 1', 'chicago', '1 - 3', 'st louis', 'toivonen', '19150', '15 - 8 - 1'], ['december 4', 'st louis', '1 - 3', 'calgary', 'toivonen', '19289', '15 - 9 - 1'], ['december 7', 'st louis', '4 - 3', 'edmonton', 'toivonen', '16839', '16 - 9 - 1'], ['december 9', 'st louis', '5 - 9', 'colorado', 'toivonen', '15476', '16 - 10 - 1'], ['december 11', 'edmonton', '5 - 4', 'st louis', 'toivonen', '14329', '16 - 10 - 2'], ['december 13', 'florida', '1 - 0', 'st louis', 'legace', '14088', '16 - 11 - 2'], ['december 16', 'calgary', '5 - 3', 'st louis', 'legace', '16733', '16 - 12 - 2'], ['december 20', 'detroit', '2 - 3', 'st louis', 'legace', '19150', '17 - 12 - 2'], ['december 22', 'st louis', '4 - 1', 'boston', 'legace', '14200', '18 - 12 - 2'], ['december 23', 'atlanta', '3 - 2', 'st louis', 'legace', '17731', '18 - 12 - 3'], ['december 26', 'detroit', '5 - 0', 'st louis', 'legace', '19250', '18 - 13 - 3'], ['december 28', 'san jose', '1 - 0', 'st louis', 'legace', '19250', '18 - 14 - 3'], ['december 29', 'st louis', '4 - 5', 'dallas', 'toivonen', '18532', '18 - 14 - 4'], ['december 31', 'st louis', '2 - 0', 'detroit', 'legace', '20066', '19 - 14 - 4']] |
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 | majority | all of the carriers in moldova with gsm standard use frequencies of 900 mhz and 1800 mhz . | {'scope': 'subset', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '900 mhz and 1800 mhz', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'gsm'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'standard', 'gsm'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; standard ; gsm }', 'tointer': 'select the rows whose standard record fuzzily matches to gsm .'}, 'frequency', '900 mhz and 1800 mhz'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose standard record fuzzily matches to gsm . for the frequency records of these rows , all of them fuzzily match to 900 mhz and 1800 mhz .', 'tostr': 'all_eq { filter_eq { all_rows ; standard ; gsm } ; frequency ; 900 mhz and 1800 mhz } = true'} | all_eq { filter_eq { all_rows ; standard ; gsm } ; frequency ; 900 mhz and 1800 mhz } = true | select the rows whose standard record fuzzily matches to gsm . for the frequency records of these rows , all of them fuzzily match to 900 mhz and 1800 mhz . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'standard_4': 4, 'gsm_5': 5, 'frequency_6': 6, '900 mhz and 1800 mhz_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'standard_4': 'standard', 'gsm_5': 'gsm', 'frequency_6': 'frequency', '900 mhz and 1800 mhz_7': '900 mhz and 1800 mhz'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'standard_4': [0], 'gsm_5': [0], 'frequency_6': [1], '900 mhz and 1800 mhz_7': [1]} | ['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'], ['unitã', 'cdma 1x', '450 mhz', '153 kbit / s', '01.03.2007'], ['idc', 'cdma 1x', '800 mhz', '153 kbit / s', '09.09.1999']] |
mohammed nasser shakroun | https://en.wikipedia.org/wiki/Mohammed_Nasser_Shakroun | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13607991-4.html.csv | comparative | mohammed nasser shakroun scored his international goal at tsirion stadium before he scored at king abdullah stadium . | {'row_1': '3', 'row_2': '5', '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', 'tsirion stadium , limassol'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to tsirion stadium , limassol .', 'tostr': 'filter_eq { all_rows ; venue ; tsirion stadium , limassol }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; tsirion stadium , limassol } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to tsirion stadium , limassol . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'king abdullah stadium , amman'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to king abdullah stadium , amman .', 'tostr': 'filter_eq { all_rows ; venue ; king abdullah stadium , amman }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; king abdullah stadium , amman } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to king abdullah stadium , amman . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; venue ; tsirion stadium , limassol } ; date } ; hop { filter_eq { all_rows ; venue ; king abdullah stadium , amman } ; date } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to tsirion stadium , limassol . take the date record of this row . select the rows whose venue record fuzzily matches to king abdullah stadium , amman . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; venue ; tsirion stadium , limassol } ; date } ; hop { filter_eq { all_rows ; venue ; king abdullah stadium , amman } ; date } } = true | select the rows whose venue record fuzzily matches to tsirion stadium , limassol . take the date record of this row . select the rows whose venue record fuzzily matches to king abdullah stadium , amman . 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, 'tsirion stadium , limassol_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'king abdullah stadium , amman_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', 'tsirion stadium , limassol_8': 'tsirion stadium , limassol', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'king abdullah stadium , amman_12': 'king abdullah stadium , amman', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'tsirion stadium , limassol_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'king abdullah stadium , amman_12': [1], 'date_13': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['26 march 2005', 'telstra stadium , sydney', '1 - 0', '1 - 2', 'friendly match'], ['7 august 2005', 'bahrain national stadium , manama', '1 - 2', '2 - 2', 'friendly match'], ['13 august 2005', 'tsirion stadium , limassol', '1 - 0', '2 - 1', 'friendly match'], ['15 march 2006', 'prince abdullah al - faisal stadium , jeddah', '2 - 0', '2 - 2', 'friendly match'], ['17 august 2006', 'king abdullah stadium , amman', '3 - 0', '3 - 0', 'friendly match'], ['27 december 2008', 'tahnoun bin mohamed stadium , al ain', '1 - 1', '2 - 2', 'friendly match']] |
2008 twenty20 cup | https://en.wikipedia.org/wiki/2008_Twenty20_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17900317-4.html.csv | aggregation | the players in the 2008 twenty20 cup scored a combined total of 3423 runs . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '3423', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'runs'], 'result': '3423', 'ind': 0, 'tostr': 'sum { all_rows ; runs }'}, '3423'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; runs } ; 3423 } = true', 'tointer': 'the sum of the runs record of all rows is 3423 .'} | round_eq { sum { all_rows ; runs } ; 3423 } = true | the sum of the runs record of all rows is 3423 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'runs_4': 4, '3423_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'runs_4': 'runs', '3423_5': '3423'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'runs_4': [0], '3423_5': [1]} | ['player', 'team', 'matches', 'inns', 'runs', 'balls', 's / rate', '100s', 'average'] | [['joe denly', 'kent spitfires', '13', '13', '451', '379', '118.99', '0', '34.69'], ['anthony mcgrath', 'yorkshire carnegie', '9', '9', '392', '296', '132.43', '0', '56.00'], ['murray goodwin', 'sussex sharks', '10', '10', '345', '273', '126.37', '0', '43.13'], ['robert key', 'kent spitfires', '13', '13', '345', '258', '133.72', '0', '26.53'], ['michael carberry', 'hampshire hawks', '10', '10', '334', '268', '124.62', '0', '37.11'], ['graham napier', 'essex eagles', '12', '11', '326', '167', '195.20', '1', '32.60'], ['michael lumb', 'hampshire hawks', '10', '10', '315', '209', '150.71', '0', '31.50'], ['marcus trescothick', 'somerset sabres', '8', '8', '306', '185', '165.40', '1', '38.25'], ['dawid malan', 'middlesex crusaders', '12', '10', '306', '220', '139.09', '1', '61.20'], ['phil mustard', 'durham dynamos', '11', '11', '303', '224', '135.26', '0', '27.54']] |
myrtle beach 250 | https://en.wikipedia.org/wiki/Myrtle_Beach_250 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23015396-1.html.csv | count | ford was the manufacturer for three winners of the myrtle beach 250 race . | {'scope': 'all', 'criterion': 'equal', 'value': 'ford', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manufacturer', 'ford'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manufacturer record fuzzily matches to ford .', 'tostr': 'filter_eq { all_rows ; manufacturer ; ford }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; manufacturer ; ford } }', 'tointer': 'select the rows whose manufacturer record fuzzily matches to ford . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; manufacturer ; ford } } ; 3 } = true', 'tointer': 'select the rows whose manufacturer record fuzzily matches to ford . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; manufacturer ; ford } } ; 3 } = true | select the rows whose manufacturer record fuzzily matches to ford . 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, 'manufacturer_5': 5, 'ford_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', 'manufacturer_5': 'manufacturer', 'ford_6': 'ford', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manufacturer_5': [0], 'ford_6': [0], '3_7': [2]} | ['year', 'date', 'driver', 'manufacturer', 'laps', '-', 'race time', 'average speed ( mph )'] | [['1988', 'july 2', 'rob moroso', 'oldsmobile', '200', '107.6 ( 173.165 )', '1:36:04', '66.971'], ['1989', 'july 4', 'jimmy spencer', 'buick', '200', '107.6 ( 173.165 )', '1:25:01', '75.938'], ['1990', 'june 30', 'mark martin', 'ford', '200', '107.6 ( 173.165 )', '1:24:52', '76.072'], ['1991', 'june 22', 'chuck bown', 'pontiac', '250', '134.5 ( 216.456 )', '1:49:15', '73.867'], ['1992', 'june 20', 'jimmy spencer', 'oldsmobile', '250', '134.5 ( 216.456 )', '2:21:14', '57.139'], ['1993', 'june 12', 'jeff burton', 'ford', '250', '134.5 ( 216.456 )', '1:56:59', '68.984'], ['1994', 'june 11', 'elton sawyer', 'ford', '250', '134.5 ( 216.456 )', '2:01:18', '66.529'], ['1995', 'june 10', 'larry pearson', 'chevrolet', '250', '134.5 ( 216.456 )', '1:41:23', '79.599'], ['1996', 'june 22', 'david green', 'chevrolet', '250', '134.5 ( 216.456 )', '1:53:35', '71.049'], ['1997', 'july 12', 'elliott sadler', 'chevrolet', '250', '134.5 ( 216.456 )', '1:39:07', '81.419'], ['1998', 'july 11', 'randy lajoie', 'chevrolet', '250', '134.5 ( 216.456 )', '1:36:56', '80.754'], ['1999', 'july 17', 'jeff green', 'chevrolet', '250', '134.5 ( 216.456 )', '1:35:52', '84.179']] |
list of sons of anarchy episodes | https://en.wikipedia.org/wiki/List_of_Sons_of_Anarchy_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20726262-2.html.csv | ordinal | of the sons of anarchy episodes , the one with the 2nd earliest air date was the one titled " seeds . " . | {'row': '2', 'col': '5', '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', 'originalairdate', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; originalairdate ; 2 }'}, 'title'], 'result': 'seeds', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; originalairdate ; 2 } ; title }'}, 'seeds'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; originalairdate ; 2 } ; title } ; seeds } = true', 'tointer': 'select the row whose originalairdate record of all rows is 2nd minimum . the title record of this row is seeds .'} | eq { hop { nth_argmin { all_rows ; originalairdate ; 2 } ; title } ; seeds } = true | select the row whose originalairdate record of all rows is 2nd minimum . the title record of this row is seeds . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'originalairdate_5': 5, '2_6': 6, 'title_7': 7, 'seeds_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', 'originalairdate_5': 'originalairdate', '2_6': '2', 'title_7': 'title', 'seeds_8': 'seeds'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'originalairdate_5': [0], '2_6': [0], 'title_7': [1], 'seeds_8': [2]} | ['no in series', 'title', 'directedby', 'writtenby', 'originalairdate', 'production code'] | [['1', 'pilot', 'allen coulter & michael dinner', 'kurt sutter', 'september 3 , 2008', '1wab79'], ['2', 'seeds', 'charles haid', 'kurt sutter', 'september 10 , 2008', '1wab01'], ['3', 'fun town', 'stephen kay', 'kurt sutter', 'september 17 , 2008', '1wab02'], ['4', 'patch over', 'paris barclay', 'james d parriott', 'september 24 , 2008', '1wab03'], ['5', 'giving back', 'tim hunter', 'jack logiudice', 'october 1 , 2008', '1wab04'], ['6', 'ak - 51', 'seith mann', 'nichole beattie', 'october 8 , 2008', '1wab05'], ['7', 'old bones', 'gwyneth horder - payton', 'dave erickson', 'october 15 , 2008', '1wab06'], ['8', 'the pull', 'guy ferland', 'kurt sutter & jack logiudice', 'october 22 , 2008', '1wab07'], ['9', 'hell followed', 'billy gierhart', 'brett conrad', 'october 29 , 2008', '1wab08'], ['10', 'better half', 'mario van peebles', 'pat charles', 'november 5 , 2008', '1wab09'], ['11', 'capybara', 'stephen kay', 'kurt sutter & dave erickson', 'november 12 , 2008', '1wab10'], ['12', 'the sleep of babies', "terrence o'hara", 'kurt sutter', 'november 19 , 2008', '1wab11']] |
utah jazz all - time roster | https://en.wikipedia.org/wiki/Utah_Jazz_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11545282-1.html.csv | majority | the majority of players on the utah jazz all - time roster have united states nationality . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'nationality', 'position', 'years for jazz', 'school / club team'] | [['rick adelman', 'united states', 'guard', '1974 - 75', 'loyola ( ca )'], ['john amaechi', 'england', 'center / forward', '2001 - 03', 'penn state'], ['louis amundson', 'united states', 'forward', '2007', 'unlv'], ['j j anderson', 'united states', 'forward', '1982 - 85', 'bradley'], ['shandon anderson', 'united states', 'guard / forward', '1996 - 99', 'georgia'], ['rafael araãjo', 'brazil', 'center', '2006 - 2007', 'byu'], ['carlos arroyo', 'puerto rico', 'guard', '2002 - 05', 'florida international'], ['isaac austin', 'united states', 'center', '1991 - 93', 'arizona state'], ['anthony avent', 'united states', 'forward', '1998 - 99', 'seton hall']] |
european film award for best short film | https://en.wikipedia.org/wiki/European_Film_Award_for_Best_Short_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12152327-4.html.csv | count | prix uip valladolid was the nominating festival for two different films . | {'scope': 'all', 'criterion': 'equal', 'value': 'prix uip valladolid', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nominating festival', 'prix uip valladolid'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nominating festival record fuzzily matches to prix uip valladolid .', 'tostr': 'filter_eq { all_rows ; nominating festival ; prix uip valladolid }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nominating festival ; prix uip valladolid } }', 'tointer': 'select the rows whose nominating festival record fuzzily matches to prix uip valladolid . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nominating festival ; prix uip valladolid } } ; 2 } = true', 'tointer': 'select the rows whose nominating festival record fuzzily matches to prix uip valladolid . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; nominating festival ; prix uip valladolid } } ; 2 } = true | select the rows whose nominating festival record fuzzily matches to prix uip valladolid . 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, 'nominating festival_5': 5, 'prix uip valladolid_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', 'nominating festival_5': 'nominating festival', 'prix uip valladolid_6': 'prix uip valladolid', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nominating festival_5': [0], 'prix uip valladolid_6': [0], '2_7': [2]} | ['category', 'film', 'director ( s )', 'country', 'nominating festival'] | [['short film 2005 prix uip', 'undressing my mother', 'ken wardrop', 'ireland', 'prix uip tampere'], ['short film 2005 prix uip', 'little terrorist', 'ashvin kumar', 'united kingdom', 'prix uip ghent'], ['short film 2005 prix uip', 'rendevú', 'ferenc cakó', 'hungary', 'prix uip valladolid'], ['short film 2005 prix uip', 'rain is falling', 'holger ernst', 'germany', 'prix uip valladolid'], ['short film 2005 prix uip', 'flatlife', 'jonas geirnaert', 'belgium', 'prix uip angers'], ['short film 2005 prix uip', 'hoi maya', 'claudia lorenz', 'switzerland', 'prix uip berlin'], ['short film 2005 prix uip', 'toz ( dust )', 'halit fatih kizilgok', 'turkey', 'prix uip cracow'], ['short film 2005 prix uip', 'bawke', 'hisham zaman', 'norway', 'prix uip grimstad'], ['short film 2005 prix uip', 'a serpente', 'sandro aguilar', 'portugal', 'prix uip vila do conde'], ['short film 2005 prix uip', 'scen nr 6882 ur mitt liv', 'ruben östlund', 'sweden', 'prix uip edinburgh'], ['short film 2005 prix uip', 'prva plata', 'alen drljević', 'bosnia and herzegovina', 'prix uip sarajevo'], ['short film 2005 prix uip', 'butterflies', 'max jacoby', 'luxembourg', 'prix uip venezia'], ['short film 2005 prix uip', 'minotauromaquia , pablo en el laberinto', 'juan pablo etcheverry', 'spain', 'prix uip drama']] |
1938 vfl season | https://en.wikipedia.org/wiki/1938_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806592-13.html.csv | majority | all games of the 1938 vfl season were played on the 23rd of july . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '23 july', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '23 july'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 23 july .', 'tostr': 'all_eq { all_rows ; date ; 23 july } = true'} | all_eq { all_rows ; date ; 23 july } = true | for the date records of all rows , all of them fuzzily match to 23 july . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '23 july_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '23 july_4': '23 july'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '23 july_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '10.9 ( 69 )', 'melbourne', '9.16 ( 70 )', 'glenferrie oval', '7000', '23 july 1938'], ['geelong', '14.20 ( 104 )', 'st kilda', '15.13 ( 103 )', 'corio oval', '7000', '23 july 1938'], ['fitzroy', '13.8 ( 86 )', 'footscray', '18.21 ( 129 )', 'brunswick street oval', '16000', '23 july 1938'], ['south melbourne', '14.11 ( 95 )', 'north melbourne', '13.18 ( 96 )', 'lake oval', '8000', '23 july 1938'], ['essendon', '17.17 ( 119 )', 'collingwood', '17.16 ( 118 )', 'windy hill', '13000', '23 july 1938'], ['richmond', '20.12 ( 132 )', 'carlton', '12.19 ( 91 )', 'punt road oval', '28000', '23 july 1938']] |
2010 - 11 tff first league | https://en.wikipedia.org/wiki/2010%E2%80%9311_TFF_First_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27091128-2.html.csv | ordinal | jürgen röber was the first manager to leave his team in the 2010 - 11 tff first league . | {'row': '1', 'col': '4', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date of vacancy', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date of vacancy ; 1 }'}, 'outgoing manager'], 'result': 'jürgen röber', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date of vacancy ; 1 } ; outgoing manager }'}, 'jürgen röber'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date of vacancy ; 1 } ; outgoing manager } ; jürgen röber } = true', 'tointer': 'select the row whose date of vacancy record of all rows is 1st minimum . the outgoing manager record of this row is jürgen röber .'} | eq { hop { nth_argmin { all_rows ; date of vacancy ; 1 } ; outgoing manager } ; jürgen röber } = true | select the row whose date of vacancy record of all rows is 1st minimum . the outgoing manager record of this row is jürgen röber . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date of vacancy_5': 5, '1_6': 6, 'outgoing manager_7': 7, 'jürgen röber_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date of vacancy_5': 'date of vacancy', '1_6': '1', 'outgoing manager_7': 'outgoing manager', 'jürgen röber_8': 'jürgen röber'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date of vacancy_5': [0], '1_6': [0], 'outgoing manager_7': [1], 'jürgen röber_8': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment'] | [['ankaraspor', 'jürgen röber', 'contract cancelled', '07.12.2009', 'önder özen', '09.07.2010'], ['boluspor', 'cüneyt karakuş', 'contract ended', '31.05.2010', 'levent eriş', '02.06.2010'], ['mersin idmanyurdu', 'ergün penbe', 'contract ended', '31.05.2010', 'yüksel yeşilova', '03.06.2010'], ['kartalspor', 'kadir özcan', 'contract ended', '31.05.2010', 'ergün penbe', '08.06.2010'], ['orduspor', 'ahmet akcan', 'contract ended', '31.05.2010', 'uğur tütüneker', '10.06.2010'], ['altay', 'güvenç kurtar', 'contract ended', '31.05.2010', 'ercan ertemçöz', '12.06.2010'], ['giresunspor', 'levent eriş', 'contract ended', '31.05.2010', 'hüsnü özkara', '18.06.2010'], ['diyarbakırspor', 'mehmet budakın', 'contract ended', '31.05.2010', 'suat kaya', '06.07.2010']] |
list of l.a. law episodes | https://en.wikipedia.org/wiki/List_of_L.A._Law_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25604014-5.html.csv | count | according to the list of l.a. law episodes , two of the episodes directed by win phelps were written by david e kelley and william m finkelstein . | {'scope': 'subset', 'criterion': 'equal', 'value': 'david e kelley and william m finkelstein', 'result': '2', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'win phelps'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'win phelps'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; directed by ; win phelps }', 'tointer': 'select the rows whose directed by record fuzzily matches to win phelps .'}, 'written by', 'david e kelley and william m finkelstein'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose directed by record fuzzily matches to win phelps . among these rows , select the rows whose written by record fuzzily matches to david e kelley and william m finkelstein .', 'tostr': 'filter_eq { filter_eq { all_rows ; directed by ; win phelps } ; written by ; david e kelley and william m finkelstein }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; directed by ; win phelps } ; written by ; david e kelley and william m finkelstein } }', 'tointer': 'select the rows whose directed by record fuzzily matches to win phelps . among these rows , select the rows whose written by record fuzzily matches to david e kelley and william m finkelstein . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; directed by ; win phelps } ; written by ; david e kelley and william m finkelstein } } ; 2 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to win phelps . among these rows , select the rows whose written by record fuzzily matches to david e kelley and william m finkelstein . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; directed by ; win phelps } ; written by ; david e kelley and william m finkelstein } } ; 2 } = true | select the rows whose directed by record fuzzily matches to win phelps . among these rows , select the rows whose written by record fuzzily matches to david e kelley and william m finkelstein . 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, 'directed by_6': 6, 'win phelps_7': 7, 'written by_8': 8, 'david e kelley and william m finkelstein_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', 'directed by_6': 'directed by', 'win phelps_7': 'win phelps', 'written by_8': 'written by', 'david e kelley and william m finkelstein_9': 'david e kelley and william m finkelstein', '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], 'directed by_6': [0], 'win phelps_7': [0], 'written by_8': [1], 'david e kelley and william m finkelstein_9': [1], '2_10': [3]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code'] | [['63', '1', 'the unsterile cuckoo', 'rob thompson', 'david e kelley', 'november 2 , 1989', '7d01'], ['64', '2', 'captain hurt', 'win phelps', 'william m finkelstein', 'november 9 , 1989', '7d02'], ['65', '3', 'when irish eyes are smiling', 'david carson', 'david e kelley and william m finkelstein', 'november 16 , 1989', '7d03'], ['66', '4', 'the mouse that soared', 'sandy smolan', 'david e kelley and william m finkelstein', 'november 23 , 1989', '7d04'], ['67', '5', 'one rat , one ranger', 'tom moore', 'douglas mcgrath', 'november 30 , 1989', '7d05'], ['68', '6', 'lie down and deliver', 'gabrielle beaumont', 'christopher keyser & harry lippman', 'december 7 , 1989', '7d06'], ['69', '7', 'placenta claus is coming to town', 'rob thompson', 'william m finkelstein and cynthia saunders', 'december 14 , 1989', '7d07'], ['70', '8', 'the good human bar', 'johanna demetrakas', 'david e kelley and cynthia saunders', 'january 4 , 1990', '7d08'], ['71', '9', "noah 's bark", 'win phelps', 'david e kelley and william m finkelstein', 'january 11 , 1990', '7d09'], ['74', '12', 'on your honor', 'steven robman', 'david e kelley and william m finkelstein', 'february 8 , 1990', '7d12'], ['76', '14', 'ex - wives and videotapes', 'miles watkins', 'david e kelley and william m finkelstein', 'february 22 , 1990', '7d14'], ['77', '15', 'blood , sweat and fears', 'edwin sherin', 'david e kelley', 'march 15 , 1990', '7d15'], ['78', '16', 'bounds for glory', 'win phelps', 'david e kelley and william m finkelstein', 'march 22 , 1990', '7d16'], ['79', '17', 'justice swerved', 'menachem binetski', 'david e kelley and bryce zabel', 'march 29 , 1990', '7d17'], ['80', '18', 'watts a matter', 'tom moore', 'david e kelley and bryce zabel', 'april 5 , 1990', '7d18'], ['81', '19', 'bang zoom zap', 'miles watkins', 'david e kelley and william m finkelstein', 'april 26 , 1990', '7d19'], ['83', '21', 'outward bound', 'edwin sherin', 'david e kelley and william m finkelstein', 'may 10 , 1990', '7d21']] |
shaun murphy ( snooker player ) | https://en.wikipedia.org/wiki/Shaun_Murphy_%28snooker_player%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1795208-10.html.csv | majority | the majority of shaun murphy 's snooker championship outcomes were winner . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'winner', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': True, 'ind': 0, 'tointer': 'for the outcome records of all rows , most of them fuzzily match to winner .', 'tostr': 'most_eq { all_rows ; outcome ; winner } = true'} | most_eq { all_rows ; outcome ; winner } = true | for the outcome records of all rows , most of them fuzzily match to winner . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'outcome_3': 3, 'winner_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'outcome_3': 'outcome', 'winner_4': 'winner'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'outcome_3': [0], 'winner_4': [0]} | ['outcome', 'year', 'championship', 'opponent in the final', 'score'] | [['runner - up', '2008', 'world series - berlin event', 'graeme dott', '1 - 6'], ['winner', '2008', 'paul hunter classic', 'mark selby', '4 - 0'], ['winner', '2009', 'world series - grand final', 'john higgins', '6 - 2'], ['winner', '2009', 'world series - champion of champions challenge', 'jimmy white', '5 - 1'], ['winner', '2009', 'paul hunter classic', 'jimmy white', '4 - 0']] |
list of government bonds | https://en.wikipedia.org/wiki/List_of_government_bonds | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2764267-2.html.csv | ordinal | us dollars have the second highest negotiable debt at mid value in government bonds . | {'row': '2', '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', 'negotiable debt at mid - 2005 ( us dollar bn equivalent )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; negotiable debt at mid - 2005 ( us dollar bn equivalent ) ; 2 }'}, 'currency'], 'result': 'us dollar', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; negotiable debt at mid - 2005 ( us dollar bn equivalent ) ; 2 } ; currency }'}, 'us dollar'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; negotiable debt at mid - 2005 ( us dollar bn equivalent ) ; 2 } ; currency } ; us dollar } = true', 'tointer': 'select the row whose negotiable debt at mid - 2005 ( us dollar bn equivalent ) record of all rows is 2nd maximum . the currency record of this row is us dollar .'} | eq { hop { nth_argmax { all_rows ; negotiable debt at mid - 2005 ( us dollar bn equivalent ) ; 2 } ; currency } ; us dollar } = true | select the row whose negotiable debt at mid - 2005 ( us dollar bn equivalent ) record of all rows is 2nd maximum . the currency record of this row is us dollar . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'negotiable debt at mid - 2005 ( us dollar bn equivalent)_5': 5, '2_6': 6, 'currency_7': 7, 'us dollar_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', 'negotiable debt at mid - 2005 ( us dollar bn equivalent)_5': 'negotiable debt at mid - 2005 ( us dollar bn equivalent )', '2_6': '2', 'currency_7': 'currency', 'us dollar_8': 'us dollar'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'negotiable debt at mid - 2005 ( us dollar bn equivalent)_5': [0], '2_6': [0], 'currency_7': [1], 'us dollar_8': [2]} | ['currency', 'country', 'generic name or nickname', 'rating ( s & p / moodys )', 'negotiable debt at mid - 2005 ( us dollar bn equivalent )', 'government financial liabilities as % of gdp ( end 2003 )', 'issuer', 'internet site'] | [['yen', 'japan', 's jgb', 'aa - / a2', '6666', '157.5 %', 'ministry of finance ( mof )', 'site'], ['us dollar', 'united states', 'us treasuries', 'aa + / aaa', '4000', '62.5 %', 'bureau of the public debt', 'site'], ['euro', 'italy', 's btp', 'bbb + / baa2', '1530', '120.9 %', 'dipartimento del tesoro', 'site'], ['euro', 'france', 's oat', 'aa + / aaa', '1300', '71.2 %', 'agence france trãsor', 'site'], ['euro', 'germany', 'bunds', 'aaa / aaa', '1020', '65.1 %', 'finanzagentur gmbh', 'site']] |
2010 - 11 scottish premier league | https://en.wikipedia.org/wiki/2010%E2%80%9311_Scottish_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26980923-2.html.csv | superlative | celtic park was the only stadium that had , on average , more than 45000 fans present per game . | {'scope': 'all', 'col_superlative': '7', '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', 'average'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; average }'}, 'team'], 'result': 'celtic', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; average } ; team }'}, 'celtic'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; average } ; team } ; celtic } = true', 'tointer': 'select the row whose average record of all rows is maximum . the team record of this row is celtic .'} | eq { hop { argmax { all_rows ; average } ; team } ; celtic } = true | select the row whose average record of all rows is maximum . the team record of this row is celtic . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'average_5': 5, 'team_6': 6, 'celtic_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'average_5': 'average', 'team_6': 'team', 'celtic_7': 'celtic'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'average_5': [0], 'team_6': [1], 'celtic_7': [2]} | ['team', 'stadium', 'capacity', 'total', 'highest', 'lowest', 'average'] | [['aberdeen', 'pittodrie stadium', '22199', '173460', '15307', '5955', '9129'], ['celtic', 'celtic park', '60832', '930395', '58874', '40750', '48968'], ['dundee united', 'tannadice park', '14209', '140391', '11790', '4918', '7389'], ['hamilton academical', 'new douglas park', '6096', '55056', '5356', '2011', '2898'], ['heart of midlothian', 'tynecastle stadium', '17420', '269506', '17420', '12009', '14185'], ['inverness ct', 'caledonian stadium', '7500', '85998', '7547', '3241', '4526'], ['kilmarnock', 'rugby park', '18128', '122106', '16173', '4214', '6427'], ['motherwell', 'fir park', '13742', '99838', '9716', '3324', '5255'], ['rangers', 'ibrox stadium', '51082', '860793', '50248', '41514', '45305'], ['st johnstone', 'mcdiarmid park', '10673', '72982', '6866', '2253', '3841']] |
canadian interuniversity sport men 's soccer | https://en.wikipedia.org/wiki/Canadian_Interuniversity_Sport_men%27s_soccer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27369069-4.html.csv | majority | for canadian interuniversity sport men 's soccer , most of the founding dates are before 1900 . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1900', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'founded', '1900'], 'result': True, 'ind': 0, 'tointer': 'for the founded records of all rows , most of them are less than 1900 .', 'tostr': 'most_less { all_rows ; founded ; 1900 } = true'} | most_less { all_rows ; founded ; 1900 } = true | for the founded records of all rows , most of them are less than 1900 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'founded_3': 3, '1900_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'founded_3': 'founded', '1900_4': '1900'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'founded_3': [0], '1900_4': [0]} | ['university', 'varsity name', 'city', 'province', 'founded', 'soccer stadium', 'stadium capacity'] | [['concordia university', 'stingers', 'montreal', 'qc', '1896', 'concordia stadium', '4000'], ['université laval', 'rouge et or', 'quebec city', 'qc', '1663', 'peps stadium', '12257'], ['mcgill university', 'redmen', 'montreal', 'qc', '1821', 'percival molson memorial stadium', '25012'], ['université de montréal', 'carabins', 'montreal', 'qc', '1821', 'cepsum stadium', '5100'], ['université de sherbrooke', 'vert et or', 'sherbrooke', 'qc', '1843', "stade de l'université de sherbrooke", '3359'], ['université du québec à montréal', 'citadins', 'montreal', 'qc', '1969', 'terrain 2 of complexe sportif claude - robillard', '1000']] |
1979 vfl season | https://en.wikipedia.org/wiki/1979_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823719-7.html.csv | comparative | essendon 's game had a bigger crowd than footscray 's game did . | {'row_1': '3', 'row_2': '1', 'col': '6', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'essendon'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to essendon .', 'tostr': 'filter_eq { all_rows ; home team ; essendon }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; home team ; essendon } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to essendon . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'footscray'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team record fuzzily matches to footscray .', 'tostr': 'filter_eq { all_rows ; home team ; footscray }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; home team ; footscray } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to footscray . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; home team ; essendon } ; crowd } ; hop { filter_eq { all_rows ; home team ; footscray } ; crowd } } = true', 'tointer': 'select the rows whose home team record fuzzily matches to essendon . take the crowd record of this row . select the rows whose home team record fuzzily matches to footscray . take the crowd record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; home team ; essendon } ; crowd } ; hop { filter_eq { all_rows ; home team ; footscray } ; crowd } } = true | select the rows whose home team record fuzzily matches to essendon . take the crowd record of this row . select the rows whose home team record fuzzily matches to footscray . take the crowd 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, 'home team_7': 7, 'essendon_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'footscray_12': 12, 'crowd_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', 'home team_7': 'home team', 'essendon_8': 'essendon', 'crowd_9': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'home team_11': 'home team', 'footscray_12': 'footscray', 'crowd_13': 'crowd'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'essendon_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'footscray_12': [1], 'crowd_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '22.17 ( 149 )', 'south melbourne', '14.17 ( 101 )', 'western oval', '15045', '19 may 1979'], ['fitzroy', '14.18 ( 102 )', 'hawthorn', '11.24 ( 90 )', 'junction oval', '15870', '19 may 1979'], ['essendon', '23.18 ( 156 )', 'melbourne', '9.20 ( 74 )', 'windy hill', '21592', '19 may 1979'], ['carlton', '15.14 ( 104 )', 'north melbourne', '16.12 ( 108 )', 'princes park', '39411', '19 may 1979'], ['st kilda', '16.15 ( 111 )', 'richmond', '14.15 ( 99 )', 'moorabbin oval', '18087', '19 may 1979'], ['collingwood', '13.14 ( 92 )', 'geelong', '6.15 ( 51 )', 'vfl park', '37260', '19 may 1979']] |
1983 senior pga tour | https://en.wikipedia.org/wiki/1983_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622862-3.html.csv | count | two of the players had exactly one win . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '1', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'wins', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wins record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; wins ; 1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; wins ; 1 } }', 'tointer': 'select the rows whose wins record fuzzily matches to 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; wins ; 1 } } ; 2 } = true', 'tointer': 'select the rows whose wins record fuzzily matches to 1 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; wins ; 1 } } ; 2 } = true | select the rows whose wins record fuzzily matches to 1 . 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, 'wins_5': 5, '1_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', 'wins_5': 'wins', '1_6': '1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'wins_5': [0], '1_6': [0], '2_7': [2]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'don january', 'united states', '237571', '13', '6'], ['2', 'miller barber', 'united states', '231008', '16', '4'], ['3', 'billy casper', 'united states', '136749', '13', '1'], ['4', 'gene littler', 'united states', '130002', '13', '2'], ['5', 'rod funseth', 'united states', '120367', '14', '1']] |
1971 - 72 st. louis blues season | https://en.wikipedia.org/wiki/1971%E2%80%9372_St._Louis_Blues_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22402438-7.html.csv | count | two of the players picked by the blues had played for the calgary centennials . | {'scope': 'all', 'criterion': 'equal', 'value': 'calgary centennials', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college / junior / club team', 'calgary centennials'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college / junior / club team record fuzzily matches to calgary centennials .', 'tostr': 'filter_eq { all_rows ; college / junior / club team ; calgary centennials }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; college / junior / club team ; calgary centennials } }', 'tointer': 'select the rows whose college / junior / club team record fuzzily matches to calgary centennials . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; college / junior / club team ; calgary centennials } } ; 2 } = true', 'tointer': 'select the rows whose college / junior / club team record fuzzily matches to calgary centennials . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; college / junior / club team ; calgary centennials } } ; 2 } = true | select the rows whose college / junior / club team record fuzzily matches to calgary centennials . 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, 'college / junior / club team_5': 5, 'calgary centennials_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', 'college / junior / club team_5': 'college / junior / club team', 'calgary centennials_6': 'calgary centennials', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college / junior / club team_5': [0], 'calgary centennials_6': [0], '2_7': [2]} | ['pick', 'player', 'position', 'nationality', 'nhl team', 'college / junior / club team'] | [['4', 'gene carr', 'centre', 'canada', 'st louis blues', 'flin flon bombers ( wchl )'], ['38', 'john garrett', 'goaltender', 'canada', 'st louis blues', 'peterborough petes ( oha )'], ['52', 'derek harker', 'defence', 'canada', 'st louis blues', 'edmonton oil kings ( wchl )'], ['66', 'wayne gibbs', 'defence', 'canada', 'st louis blues', 'calgary centennials ( wchl )'], ['80', 'bernie doan', 'defence', 'canada', 'st louis blues', 'calgary centennials ( wchl )'], ['94', 'dave smith', 'defence', 'canada', 'st louis blues', 'regina pats ( wchl )']] |
galatasaray s.k. ( men 's volleyball ) | https://en.wikipedia.org/wiki/Galatasaray_S.K._%28men%27s_volleyball%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18729570-2.html.csv | ordinal | caner pekşen is the third tallest player on the galatasaray s.k. men 's volleyball team . | {'row': '3', 'col': '5', 'order': '3', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'height', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; height ; 3 }'}, 'player'], 'result': 'caner pekşen', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; height ; 3 } ; player }'}, 'caner pekşen'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; height ; 3 } ; player } ; caner pekşen } = true', 'tointer': 'select the row whose height record of all rows is 3rd maximum . the player record of this row is caner pekşen .'} | eq { hop { nth_argmax { all_rows ; height ; 3 } ; player } ; caner pekşen } = true | select the row whose height record of all rows is 3rd maximum . the player record of this row is caner pekşen . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'height_5': 5, '3_6': 6, 'player_7': 7, 'caner pekşen_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', 'height_5': 'height', '3_6': '3', 'player_7': 'player', 'caner pekşen_8': 'caner pekşen'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'height_5': [0], '3_6': [0], 'player_7': [1], 'caner pekşen_8': [2]} | ['shirt no', 'nationality', 'player', 'birth date', 'height', 'position'] | [['6', 'cuba', 'henry bell cisnero', 'july 27 , 1982 ( age31 )', '188', 'spiker'], ['7', 'turkey', 'tolgahan camgöz', 'january 27 , 1990 ( age24 )', '182', 'libero'], ['11', 'turkey', 'caner pekşen', 'june 9 , 1987 ( age26 )', '190', 'setter'], ['15', 'turkey', 'oğuzhan tarakçı', 'april 23 , 1993 ( age20 )', '195', 'outside hitter'], ['16', 'turkey', 'ferhat akdeniz', 'january 14 , 1986 ( age28 )', '203', 'middle blocker']] |
washington redskins draft history | https://en.wikipedia.org/wiki/Washington_Redskins_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-20.html.csv | count | the washington redskins drafted three players from the fb position . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'fb', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'fb'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to fb .', 'tostr': 'filter_eq { all_rows ; position ; fb }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; fb } }', 'tointer': 'select the rows whose position record fuzzily matches to fb . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; fb } } ; 3 } = true', 'tointer': 'select the rows whose position record fuzzily matches to fb . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; position ; fb } } ; 3 } = true | select the rows whose position record fuzzily matches to fb . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'fb_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'fb_6': 'fb', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'fb_6': [0], '3_7': [2]} | ['round', 'pick', 'name', 'position', 'college', 'aafc team'] | [['1', '5', 'jim spavital', 'fb', 'oklahoma a & m', 'los angeles dons'], ['2', '18', 'chuck drazenovich', 'fb', 'penn state', 'los angeles dons'], ['3', '31', 'roland dale', 'ot', 'mississippi', 'brooklyn dodgers'], ['4', '48', 'lloyd eisenberg', 'ot', 'duke', 'los angeles dons'], ['5', '61', 'hardy brown', 'fb', 'tulsa', 'chicago hornets'], ['6', '76', 'ed hirsch', 'lb', 'northwestern', 'buffalo bills'], ['7', '89', 'ed smith', 'hb', 'texas mines', 'new york yanks'], ['9', '117', 'murray alexander', 'e', 'mississippi state', 'brooklyn dodgers'], ['10', '132', 'dewey nelson', 'hb', 'utah', 'new york bulldogs']] |
2007 colorado crush season | https://en.wikipedia.org/wiki/2007_Colorado_Crush_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11785718-5.html.csv | count | in the 2007 colorado crush season 4 players had more than 50 receptions . | {'scope': 'all', 'criterion': 'greater_than', 'value': '50', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'rec', '50'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rec record is greater than 50 .', 'tostr': 'filter_greater { all_rows ; rec ; 50 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; rec ; 50 } }', 'tointer': 'select the rows whose rec record is greater than 50 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; rec ; 50 } } ; 4 } = true', 'tointer': 'select the rows whose rec record is greater than 50 . the number of such rows is 4 .'} | eq { count { filter_greater { all_rows ; rec ; 50 } } ; 4 } = true | select the rows whose rec record is greater than 50 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'rec_5': 5, '50_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'rec_5': 'rec', '50_6': '50', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'rec_5': [0], '50_6': [0], '4_7': [2]} | ['player', 'rec', 'yards', 'avg', "td 's", 'long'] | [['damian harrell', '132', '1537', '11.7', '47', '45'], ['brad pyatt', '95', '1169', '12.3', '19', '46'], ['willie quinnie', '72', '844', '11.7', '14', '42'], ['robert redd', '62', '547', '8.8', '5', '34'], ['alonzo nix', '50', '509', '10.2', '3', '34'], ['robert thomas', '2', '18', '9', '0', '19'], ['john peaua', '2', '11', '5.5', '1', '9'], ['anthony dunn', '1', '7', '7', '0', '7'], ['chris watton', '1', '1', '1', '0', '1'], ['brandon kirsch', '1', '0', '0', '0', '0']] |
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