topic
stringlengths 3
96
| wiki
stringlengths 33
127
| url
stringlengths 101
106
| action
stringclasses 7
values | sent
stringlengths 34
223
| annotation
stringlengths 74
227
| logic
stringlengths 207
5.45k
| logic_str
stringlengths 37
493
| interpret
stringlengths 43
471
| num_func
stringclasses 15
values | nid
stringclasses 13
values | g_ids
stringlengths 70
455
| g_ids_features
stringlengths 98
670
| g_adj
stringlengths 79
515
| table_header
stringlengths 40
458
| table_cont
large_stringlengths 135
4.41k
|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
leonardo de souza | https://en.wikipedia.org/wiki/Leonardo_de_Souza | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27582888-1.html.csv | majority | for the majority of his seasons racing , leonardo de souza 's was with team kemba racing . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'kemba racing', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'team name', 'kemba racing'], 'result': True, 'ind': 0, 'tointer': 'for the team name records of all rows , most of them fuzzily match to kemba racing .', 'tostr': 'most_eq { all_rows ; team name ; kemba racing } = true'} | most_eq { all_rows ; team name ; kemba racing } = true | for the team name records of all rows , most of them fuzzily match to kemba racing . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'team name_3': 3, 'kemba racing_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'team name_3': 'team name', 'kemba racing_4': 'kemba racing'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'team name_3': [0], 'kemba racing_4': [0]} | ['season', 'series', 'team name', 'races', 'poles', 'wins', 'podiums', 'f / laps', 'points', 'final placing'] | [['2005', 'formula renault brasil', 'kemba racing', '14', '0', '0', '0', '0', '18', '21st'], ['2006', 'formula renault brasil', 'eng makers', '10', '0', '0', '0', '0', '8', '18th'], ['2008', 'formula three sudamericana', 'kemba racing', '14', '0', '0', '0', '0', '24', '8th'], ['2009', 'formula three sudamericana', 'kemba racing', '14', '0', '1', '2', '0', '33', '9th'], ['2010', 'formula three sudamericana', 'kemba racing', '20', '0', '1', '4', '1', '171', '5th']] |
mattia pasini | https://en.wikipedia.org/wiki/Mattia_Pasini | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13985563-1.html.csv | unique | 2008 was the only year that mattia pasini reached exactly 4 podiums . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '4', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'podiums', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose podiums record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; podiums ; 4 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; podiums ; 4 } }', 'tointer': 'select the rows whose podiums record is equal to 4 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'podiums', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose podiums record is equal to 4 .', 'tostr': 'filter_eq { all_rows ; podiums ; 4 }'}, 'season'], 'result': '2008', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; podiums ; 4 } ; season }'}, '2008'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; podiums ; 4 } ; season } ; 2008 }', 'tointer': 'the season record of this unqiue row is 2008 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; podiums ; 4 } } ; eq { hop { filter_eq { all_rows ; podiums ; 4 } ; season } ; 2008 } } = true', 'tointer': 'select the rows whose podiums record is equal to 4 . there is only one such row in the table . the season record of this unqiue row is 2008 .'} | and { only { filter_eq { all_rows ; podiums ; 4 } } ; eq { hop { filter_eq { all_rows ; podiums ; 4 } ; season } ; 2008 } } = true | select the rows whose podiums record is equal to 4 . there is only one such row in the table . the season record of this unqiue row is 2008 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'podiums_7': 7, '4_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '2008_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'podiums_7': 'podiums', '4_8': '4', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '2008_10': '2008'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'podiums_7': [0], '4_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '2008_10': [3]} | ['season', 'races', 'podiums', 'pole', 'flap'] | [['2004', '16', '0', '0', '0'], ['2005', '15', '6', '0', '0'], ['2006', '16', '6', '2', '2'], ['2007', '17', '5', '9', '2'], ['2008', '16', '4', '0', '0'], ['2009', '16', '5', '0', '0'], ['2010', '8', '0', '0', '0'], ['2011', '17', '0', '0', '0'], ['2012', '14', '0', '0', '0'], ['2012', '1', '0', '0', '0'], ['2013', '16', '0', '0', '0'], ['total', '152', '26', '11', '4']] |
2009 - 10 english premiership ( rugby union ) | https://en.wikipedia.org/wiki/2009%E2%80%9310_English_Premiership_%28rugby_union%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23909238-2.html.csv | count | only two of the eleven clubs amassed more than 70 points in the 2009-2010 season . | {'scope': 'all', 'criterion': 'greater_than', 'value': '70', 'result': '2', 'col': '14', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '70'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is greater than 70 .', 'tostr': 'filter_greater { all_rows ; points ; 70 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; points ; 70 } }', 'tointer': 'select the rows whose points record is greater than 70 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; points ; 70 } } ; 2 } = true', 'tointer': 'select the rows whose points record is greater than 70 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; points ; 70 } } ; 2 } = true | select the rows whose points record is greater than 70 . 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, 'points_5': 5, '70_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'points_5': 'points', '70_6': '70', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'points_5': [0], '70_6': [0], '2_7': [2]} | ['', 'club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'points difference', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['1', 'leicester tigers ( c )', '22', '15', '1', '6', '541', '325', '216', '46', '18', '7', '4', '73'], ['2', 'northampton saints ( sf )', '22', '16', '0', '6', '472', '322', '150', '44', '26', '2', '5', '71'], ['3', 'saracens ( f )', '22', '15', '1', '6', '480', '367', '113', '39', '22', '2', '5', '69'], ['4', 'bath ( sf )', '22', '12', '2', '8', '450', '366', '84', '49', '33', '5', '4', '61'], ['5', 'london wasps', '22', '13', '0', '9', '394', '399', '5', '35', '31', '2', '3', '57'], ['6', 'london irish', '22', '10', '3', '9', '469', '384', '85', '42', '33', '3', '3', '52'], ['7', 'gloucester', '22', '10', '1', '11', '470', '457', '13', '46', '42', '2', '4', '48'], ['8', 'harlequins', '22', '9', '2', '11', '420', '484', '64', '42', '46', '3', '3', '46'], ['9', 'newcastle falcons', '22', '6', '4', '12', '319', '431', '112', '20', '41', '1', '4', '37'], ['10', 'leeds carnegie', '22', '7', '1', '14', '283', '493', '210', '17', '48', '0', '6', '36'], ['11', 'sale sharks', '22', '6', '1', '15', '333', '495', '162', '24', '51', '0', '6', '32']] |
1945 - 46 huddersfield town f.c. season | https://en.wikipedia.org/wiki/1945%E2%80%9346_Huddersfield_Town_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19730892-1.html.csv | superlative | billy price had the most total goals in the 1945 - 46 huddersfield town f.c. season . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '12', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total goals'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total goals }'}, 'name'], 'result': 'billy price', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total goals } ; name }'}, 'billy price'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total goals } ; name } ; billy price } = true', 'tointer': 'select the row whose total goals record of all rows is maximum . the name record of this row is billy price .'} | eq { hop { argmax { all_rows ; total goals } ; name } ; billy price } = true | select the row whose total goals record of all rows is maximum . the name record of this row is billy price . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total goals_5': 5, 'name_6': 6, 'billy price_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total goals_5': 'total goals', 'name_6': 'name', 'billy price_7': 'billy price'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total goals_5': [0], 'name_6': [1], 'billy price_7': [2]} | ['name', 'nation', 'position', 'fa cup apps', 'fa cup goals', 'total apps', 'total goals'] | [['graham bailey', 'england', 'df', '2', '0', '2', '0'], ['jeff barker', 'england', 'df', '2', '0', '2', '0'], ['albert bateman', 'england', 'mf', '2', '0', '2', '0'], ['eddie carr', 'england', 'mf', '1', '0', '1', '0'], ['don clegg', 'england', 'gk', '2', '0', '2', '0'], ['jimmy glazzard', 'england', 'fw', '2', '0', '2', '0'], ['george green', 'england', 'df', '2', '0', '2', '0'], ['george howe', 'england', 'df', '1', '0', '1', '0'], ['vic metcalfe', 'england', 'mf', '1', '0', '1', '0'], ['arthur morton', 'england', 'df', '2', '0', '2', '0'], ['joe poole', 'england', 'fw', '1', '0', '1', '0'], ['billy price', 'england', 'fw', '2', '1', '2', '1']] |
brian watts | https://en.wikipedia.org/wiki/Brian_Watts | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10167122-1.html.csv | majority | in the majority of tournaments brian makes at least 1 cut . | {'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None} | {'func': 'all_greater_eq', 'args': ['all_rows', 'cuts made', '1'], 'result': True, 'ind': 0, 'tointer': 'for the cuts made records of all rows , all of them are greater than or equal to 1 .', 'tostr': 'all_greater_eq { all_rows ; cuts made ; 1 } = true'} | all_greater_eq { all_rows ; cuts made ; 1 } = true | for the cuts made records of all rows , all of them are greater than or equal to 1 . | 1 | 1 | {'all_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'cuts made_3': 3, '1_4': 4} | {'all_greater_eq_0': 'all_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'cuts made_3': 'cuts made', '1_4': '1'} | {'all_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'cuts made_3': [0], '1_4': [0]} | ['tournament', 'wins', 'top - 5', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '0', '0', '2', '1'], ['us open', '0', '0', '1', '2', '1'], ['the open championship', '0', '1', '2', '7', '4'], ['pga championship', '0', '0', '0', '6', '4'], ['totals', '0', '1', '3', '17', '10']] |
1980 winter olympics | https://en.wikipedia.org/wiki/1980_Winter_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-113360-1.html.csv | unique | at the 1980 winter olympics , the only country to win 6 gold medals was the united states . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '6', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 6 .', 'tostr': 'filter_eq { all_rows ; gold ; 6 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 6 } }', 'tointer': 'select the rows whose gold record is equal to 6 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '6'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 6 .', 'tostr': 'filter_eq { all_rows ; gold ; 6 }'}, 'nation'], 'result': 'united states', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; gold ; 6 } ; nation }'}, 'united states'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; gold ; 6 } ; nation } ; united states }', 'tointer': 'the nation record of this unqiue row is united states .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; gold ; 6 } } ; eq { hop { filter_eq { all_rows ; gold ; 6 } ; nation } ; united states } } = true', 'tointer': 'select the rows whose gold record is equal to 6 . there is only one such row in the table . the nation record of this unqiue row is united states .'} | and { only { filter_eq { all_rows ; gold ; 6 } } ; eq { hop { filter_eq { all_rows ; gold ; 6 } ; nation } ; united states } } = true | select the rows whose gold record is equal to 6 . there is only one such row in the table . the nation record of this unqiue row is united states . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '6_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'united states_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '6_8': '6', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'united states_10': 'united states'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '6_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'united states_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '10', '6', '6', '22'], ['2', 'east germany ( gdr )', '9', '7', '7', '23'], ['3', 'united states', '6', '4', '2', '12'], ['4', 'austria', '3', '2', '2', '7'], ['5', 'sweden', '3', '0', '1', '4'], ['6', 'liechtenstein', '2', '2', '0', '4'], ['7', 'finland', '1', '5', '3', '9'], ['8', 'norway', '1', '3', '6', '10'], ['9', 'netherlands', '1', '2', '1', '4'], ['10', 'switzerland', '1', '1', '3', '5']] |
edmonton radial railway society | https://en.wikipedia.org/wiki/Edmonton_Radial_Railway_Society | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22481967-1.html.csv | count | a total of five edmonton radial railway society models were withdrawn in the year 1951 . | {'scope': 'all', 'criterion': 'equal', 'value': '1951', 'result': '5', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'withdrawn', '1951'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose withdrawn record is equal to 1951 .', 'tostr': 'filter_eq { all_rows ; withdrawn ; 1951 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; withdrawn ; 1951 } }', 'tointer': 'select the rows whose withdrawn record is equal to 1951 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; withdrawn ; 1951 } } ; 5 } = true', 'tointer': 'select the rows whose withdrawn record is equal to 1951 . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; withdrawn ; 1951 } } ; 5 } = true | select the rows whose withdrawn record is equal to 1951 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'withdrawn_5': 5, '1951_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'withdrawn_5': 'withdrawn', '1951_6': '1951', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'withdrawn_5': [0], '1951_6': [0], '5_7': [2]} | ['date', 'builder', 'type', 'operator', 'number', 'withdrawn', 'status'] | [['1907', 'occ', 'combination sweeper / overhead line car', 'saskatoon municipal railway', '200', '1951', 'stored'], ['1908', 'occ', 'streetcar', 'edmonton radial railway', '1', '1951', 'display only'], ['1912', 'stl', 'streetcar', 'edmonton radial railway', '33', '1951', 'stored'], ['1912', 'stl', 'streetcar', 'edmonton radial railway', '42', '1951', 'fort edmonton park line'], ['1914', 'preston', 'streetcar', 'toronto suburban railway', '24 , ( later cnr 15702 )', '1960s', 'fort edmonton park line'], ['1921', 'u / s', 'tram', 'nankai electric railway ( osaka , japan )', '247', '1990', 'high level bridge line'], ['ca 1920s', 'cc & f', 'streetcar', 'regina municipal railway', '42', '1950', 'closed to viewing'], ['1930', 'occ', 'streetcar', 'edmonton radial railway', '80', '1951', 'fort edmonton park line'], ['1947', 'ptc', 'w6 class tram', 'melbourne and metropolitan tramways board', '930', '1997', 'high level bridge line'], ['1951', 'cc & f', 'pcc streetcar', 'toronto transit commission', '4612', '1995', 'fort edmonton park line']] |
shane hall | https://en.wikipedia.org/wiki/Shane_Hall | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2649597-1.html.csv | count | shane hall drove with the stegell motorsports team for a total of four years . | {'scope': 'all', 'criterion': 'equal', 'value': 'stegell motorsports', 'result': '4', 'col': '12', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team ( s )', 'stegell motorsports'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team ( s ) record fuzzily matches to stegell motorsports .', 'tostr': 'filter_eq { all_rows ; team ( s ) ; stegell motorsports }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ( s ) ; stegell motorsports } }', 'tointer': 'select the rows whose team ( s ) record fuzzily matches to stegell motorsports . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ( s ) ; stegell motorsports } } ; 4 } = true', 'tointer': 'select the rows whose team ( s ) record fuzzily matches to stegell motorsports . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; team ( s ) ; stegell motorsports } } ; 4 } = true | select the rows whose team ( s ) record fuzzily matches to stegell motorsports . 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, 'team (s)_5': 5, 'stegell motorsports_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', 'team (s)_5': 'team ( s )', 'stegell motorsports_6': 'stegell motorsports', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team (s)_5': [0], 'stegell motorsports_6': [0], '4_7': [2]} | ['year', 'races', 'wins', 'poles', 'top 5', 'top 10', 'dnf', 'finish', 'start', 'winnings', 'season rank', 'team ( s )'] | [['1995', '2', '0', '0', '0', '0', '0', '24.0', '37.0', '5225', '75th', 'stegell motorsports'], ['1996', '14', '0', '0', '0', '0', '6', '26.4', '25.1', '63865', '42nd', 'stegell motorsports'], ['1997', '28', '0', '1', '0', '1', '10', '27.1', '21.6', '196656', '23rd', 'stegell motorsports'], ['1998', '31', '0', '1', '0', '3', '5', '24.9', '25.5', '335163', '19th', 'stegell motorsports'], ['1999', '25', '0', '0', '1', '1', '9', '25.8', '18.2', '243810', '24th', 'curb - agajanian performance group'], ['2000', '2', '0', '0', '0', '0', '1', '35.0', '28.5', '15900', '90th', 'alumni motorsports'], ['2001', '33', '0', '0', '0', '0', '6', '27.9', '32.7', '491977', '23rd', 'hensley racing'], ['2002', '24', '0', '0', '0', '1', '11', '27.0', '33.0', '288325', '29th', 'hensley racing'], ['2003', '5', '0', '0', '0', '0', '4', '35.8', '25.6', '68360', '85th', 'jay robinson racing'], ['2004', '9', '0', '0', '0', '0', '6', '31.4', '37.2', '139685', '54th', 'moy racing / jay robinson racing'], ['2005', '7', '0', '0', '0', '0', '7', '40.9', '32.6', '108921', '83rd', 'jay robinson racing'], ['2006', '9', '0', '0', '0', '0', '7', '38.9', '39.1', '151184', '70th', 'jay robinson racing'], ['2008', '1', '0', '0', '0', '0', '1', '43.0', '34.0', '15674', '149th', 'jay robinson racing']] |
list of number - one singles of 1999 ( canada ) | https://en.wikipedia.org/wiki/List_of_number-one_singles_of_1999_%28Canada%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17481317-1.html.csv | comparative | the song kiss me was the number one song in canada in 1999 for more weeks than the song smooth . | {'row_1': '11', 'row_2': '16', 'col': '3', 'col_other': '4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song', 'kiss me'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose song record fuzzily matches to kiss me .', 'tostr': 'filter_eq { all_rows ; song ; kiss me }'}, 'weeks on top'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; song ; kiss me } ; weeks on top }', 'tointer': 'select the rows whose song record fuzzily matches to kiss me . take the weeks on top record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'song', 'smooth'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose song record fuzzily matches to smooth .', 'tostr': 'filter_eq { all_rows ; song ; smooth }'}, 'weeks on top'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; song ; smooth } ; weeks on top }', 'tointer': 'select the rows whose song record fuzzily matches to smooth . take the weeks on top record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; song ; kiss me } ; weeks on top } ; hop { filter_eq { all_rows ; song ; smooth } ; weeks on top } } = true', 'tointer': 'select the rows whose song record fuzzily matches to kiss me . take the weeks on top record of this row . select the rows whose song record fuzzily matches to smooth . take the weeks on top record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; song ; kiss me } ; weeks on top } ; hop { filter_eq { all_rows ; song ; smooth } ; weeks on top } } = true | select the rows whose song record fuzzily matches to kiss me . take the weeks on top record of this row . select the rows whose song record fuzzily matches to smooth . take the weeks on top 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, 'song_7': 7, 'kiss me_8': 8, 'weeks on top_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'song_11': 11, 'smooth_12': 12, 'weeks on top_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', 'song_7': 'song', 'kiss me_8': 'kiss me', 'weeks on top_9': 'weeks on top', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'song_11': 'song', 'smooth_12': 'smooth', 'weeks on top_13': 'weeks on top'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'song_7': [0], 'kiss me_8': [0], 'weeks on top_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'song_11': [1], 'smooth_12': [1], 'weeks on top_13': [3]} | ['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist'] | [['68:10 - 12', '30 november - 4 january 1999 §', '6 §', 'thank u', 'alanis morissette'], ['68:13', '11 january - 18 january ≠', '2 ≠', "it 's all been done", 'barenaked ladies'], ['68:14', '25 january', '1', 'hands', 'jewel'], ['68:15', '1 february', '1', 'you get what you give', 'new radicals'], ['68:16', '8 february', '1', '… baby one more time', 'britney spears'], ['68:17 - 18', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks'], ['68:19', '1 march', '1', 'believe', 'cher'], ['68:20 - 24', '8 march - 5 april', '5', 'every morning', 'sugar ray'], ['68:25 - 26', '12 april - 19 april', '2', 'love song', 'sky'], ['69:1 - 2', '26 april - 3 may', '2', 'no scrubs', 'tlc'], ['69:3 - 5', '10 may - 24 may', '3', 'kiss me', 'sixpence none the richer'], ['69:6 - 13', '31 may - 19 july', '8', "livin ' la vida loca", 'ricky martin'], ['69:14 - 15', '26 july - 2 august', '2', 'beautiful stranger', 'madonna'], ['69:16 - 21', '9 august - 13 september', '6', 'if you had my love', 'jennifer lopez'], ['69:22 - 26 , 70:1 - 6', '20 september - 29 november', '11', 'mambo no 5', 'lou bega'], ['70:7', '6 december', '1', 'smooth', 'santana featuring rob thomas'], ['70:8 - 9', '13 december - 3 january 2000 ÷', '2 ÷', 'blue', 'eiffel 65']] |
statues of the liberators | https://en.wikipedia.org/wiki/Statues_of_the_Liberators | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13846706-1.html.csv | ordinal | the statue of benito juarez was the third statue of liberator to be erected on virginia avenue . | {'row': '5', 'col': '4', 'order': '3', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year erected', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year erected ; 3 }'}, 'statue'], 'result': 'benito juarez', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year erected ; 3 } ; statue }'}, 'benito juarez'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year erected ; 3 } ; statue } ; benito juarez } = true', 'tointer': 'select the row whose year erected record of all rows is 3rd minimum . the statue record of this row is benito juarez .'} | eq { hop { nth_argmin { all_rows ; year erected ; 3 } ; statue } ; benito juarez } = true | select the row whose year erected record of all rows is 3rd minimum . the statue record of this row is benito juarez . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year erected_5': 5, '3_6': 6, 'statue_7': 7, 'benito juarez_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'year erected_5': 'year erected', '3_6': '3', 'statue_7': 'statue', 'benito juarez_8': 'benito juarez'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year erected_5': [0], '3_6': [0], 'statue_7': [1], 'benito juarez_8': [2]} | ['statue', 'liberator', 'country', 'year erected', 'artist'] | [['general josé gervasio artigas', 'josé gervasio artigas', 'uruguay', '1950', 'juan manuel blanes ( 1830 - 1901 )'], ['equestrian of simón bolívar', 'simón bolívar', 'venezuela', '1958', 'felix de weldon ( 1907 - 2003 )'], ['general jose de san martin memorial', 'josé de san martín', 'argentina', '1970s', 'augustin - alexandre dumont ( 1801 - 1884 )'], ['bernardo de gálvez', 'bernardo de gálvez', 'spain', '1976', 'juan de ávalos ( 1911 - 2006 )'], ['benito juarez', 'benito juárez', 'mexico', '1969', 'enrique alciati']] |
locomotives of the glasgow and south western railway | https://en.wikipedia.org/wiki/Locomotives_of_the_Glasgow_and_South_Western_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15412381-5.html.csv | comparative | north british built a locomotive in an earlier year than g & swr kilmarnock . | {'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'north british'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose builder record fuzzily matches to north british .', 'tostr': 'filter_eq { all_rows ; builder ; north british }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; builder ; north british } ; date }', 'tointer': 'select the rows whose builder record fuzzily matches to north british . take the date record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'builder', 'g & swr kilmarnock'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose builder record fuzzily matches to g & swr kilmarnock .', 'tostr': 'filter_eq { all_rows ; builder ; g & swr kilmarnock }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; builder ; g & swr kilmarnock } ; date }', 'tointer': 'select the rows whose builder record fuzzily matches to g & swr kilmarnock . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; builder ; north british } ; date } ; hop { filter_eq { all_rows ; builder ; g & swr kilmarnock } ; date } } = true', 'tointer': 'select the rows whose builder record fuzzily matches to north british . take the date record of this row . select the rows whose builder record fuzzily matches to g & swr kilmarnock . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; builder ; north british } ; date } ; hop { filter_eq { all_rows ; builder ; g & swr kilmarnock } ; date } } = true | select the rows whose builder record fuzzily matches to north british . take the date record of this row . select the rows whose builder record fuzzily matches to g & swr kilmarnock . take the date 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, 'builder_7': 7, 'north british_8': 8, 'date_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'builder_11': 11, 'g&swr kilmarnock_12': 12, 'date_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', 'builder_7': 'builder', 'north british_8': 'north british', 'date_9': 'date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'builder_11': 'builder', 'g&swr kilmarnock_12': 'g & swr kilmarnock', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'builder_7': [0], 'north british_8': [0], 'date_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'builder_11': [1], 'g&swr kilmarnock_12': [1], 'date_13': [3]} | ['class', 'wheels', 'date', 'builder', 'no built', '1919 nos', 'lms class', 'lms nos'] | [['4 - 4 - 0', '131', '1913', 'north british', '6', '331 - 336', '3p', '14510 - 5'], ['4 - 4 - 0', '137', '1915', 'g & swr kilmarnock', '6', '325 - 330', '3p', '14516 - 21'], ['0 - 6 - 0t', '5', '1917', 'north british', '3', '322 - 324', '2f', '16377 - 9'], ['0 - 6 - 2t', '45', '1915 - 17', 'north british', '18', '11 - 28', '3f', '16410 - 27 ( later 16910 - 27 )'], ['0 - 6 - 0', '279', '1913', 'north british', '15', '71 - 85', '4f', '17750 - 64'], ['2 - 6 - 0', '403', '1915', 'north british', '11', '51 - 61', '4f', '17820 - 30']] |
2009 - 10 washington capitals season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Washington_Capitals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23308178-9.html.csv | count | six games were played at the verizon center . | {'scope': 'all', 'criterion': 'equal', 'value': 'verizon center', 'result': '7', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'verizon center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to verizon center .', 'tostr': 'filter_eq { all_rows ; location ; verizon center }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; verizon center } }', 'tointer': 'select the rows whose location record fuzzily matches to verizon center . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; verizon center } } ; 7 } = true', 'tointer': 'select the rows whose location record fuzzily matches to verizon center . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; location ; verizon center } } ; 7 } = true | select the rows whose location record fuzzily matches to verizon center . 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, 'location_5': 5, 'verizon center_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', 'location_5': 'location', 'verizon center_6': 'verizon center', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'verizon center_6': [0], '7_7': [2]} | ['game', 'date', 'opponent', 'score', 'location', 'attendance', 'record', 'points'] | [['63', 'march 3', 'buffalo sabres', '3 - 1', 'hsbc arena', '18690', '42 - 13 - 8', '92'], ['64', 'march 4', 'tampa bay lightning', '5 - 4', 'verizon center', '18277', '43 - 13 - 8', '94'], ['65', 'march 6', 'new york rangers', '2 - 0', 'verizon center', '18277', '44 - 13 - 8', '96'], ['66', 'march 8', 'dallas stars', '4 - 3 so', 'verizon center', '18277', '44 - 13 - 9', '97'], ['67', 'march 10', 'carolina hurricanes', '4 - 3 ot', 'verizon center', '18277', '45 - 13 - 9', '99'], ['68', 'march 12', 'tampa bay lightning', '2 - 3', 'verizon center', '18277', '45 - 14 - 9', '99'], ['69', 'march 14', 'chicago blackhawks', '4 - 3 ot', 'united center', '22289', '46 - 14 - 9', '101'], ['70', 'march 16', 'florida panthers', '7 - 3', 'bankatlantic center', '15123', '47 - 14 - 9', '103'], ['71', 'march 18', 'carolina hurricanes', '3 - 4 ot', 'rbc center', '18144', '47 - 14 - 10', '104'], ['72', 'march 20', 'tampa bay lightning', '3 - 1', 'st pete times forum', '19844', '48 - 14 - 10', '106'], ['73', 'march 24', 'pittsburgh penguins', '4 - 3 so', 'verizon center', '18277', '49 - 14 - 10', '108'], ['74', 'march 25', 'carolina hurricanes', '3 - 2 so', 'rbc center', '18046', '49 - 14 - 11', '109'], ['75', 'march 28', 'calgary flames', '5 - 3', 'verizon center', '18277', '49 - 15 - 11', '109']] |
1975 dallas cowboys season | https://en.wikipedia.org/wiki/1975_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16767061-2.html.csv | count | the dallas cowboys played against the st louis cardinals 2 times during the 1975 season . | {'scope': 'all', 'criterion': 'equal', 'value': 'st louis cardinals', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'st louis cardinals'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to st louis cardinals .', 'tostr': 'filter_eq { all_rows ; opponent ; st louis cardinals }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; opponent ; st louis cardinals } }', 'tointer': 'select the rows whose opponent record fuzzily matches to st louis cardinals . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; opponent ; st louis cardinals } } ; 2 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to st louis cardinals . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; opponent ; st louis cardinals } } ; 2 } = true | select the rows whose opponent record fuzzily matches to st louis cardinals . 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, 'opponent_5': 5, 'st louis cardinals_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', 'opponent_5': 'opponent', 'st louis cardinals_6': 'st louis cardinals', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'st louis cardinals_6': [0], '2_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 21 , 1975', 'los angeles rams', 'w 18 - 7', '49091'], ['2', 'september 28 , 1975', 'st louis cardinals', 'w 37 - 31', '52417'], ['3', 'october 6 , 1975', 'detroit lions', 'w 36 - 10', '79384'], ['4', 'october 12 , 1975', 'new york giants', 'w 13 - 7', '56511'], ['5', 'october 19 , 1975', 'green bay packers', 'l 19 - 17', '64189'], ['6', 'october 26 , 1975', 'philadelphia eagles', 'w 20 - 17', '64889'], ['7', 'november 2 , 1975', 'washington redskins', 'l 30 - 24', '55004'], ['8', 'november 10 , 1975', 'kansas city chiefs', 'l 34 - 31', '63539'], ['9', 'november 16 , 1975', 'new england patriots', 'w 34 - 31', '60905'], ['10', 'november 23 , 1975', 'philadelphia eagles', 'w 27 - 17', '57893'], ['11', 'november 30 , 1975', 'new york giants', 'w 14 - 3', '53329'], ['12', 'december 7 , 1975', 'st louis cardinals', 'l 31 - 17', '49701'], ['13', 'december 13 , 1975', 'washington redskins', 'w 31 - 10', '61091'], ['14', 'december 21 , 1975', 'new york jets', 'w 31 - 21', '37279']] |
2007 amsterdam admirals season | https://en.wikipedia.org/wiki/2007_Amsterdam_Admirals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10392906-2.html.csv | superlative | the amsterdam admirals received their highest score during the 2007 season against the hamburg devils with 41 points . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '4', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'final score'], 'result': 'w 41 - 31', 'ind': 0, 'tostr': 'max { all_rows ; final score }', 'tointer': 'the maximum final score record of all rows is w 41 - 31 .'}, 'w 41 - 31'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; final score } ; w 41 - 31 }', 'tointer': 'the maximum final score record of all rows is w 41 - 31 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'final score'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; final score }'}, 'opponent'], 'result': 'hamburg sea devils', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; final score } ; opponent }'}, 'hamburg sea devils'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; final score } ; opponent } ; hamburg sea devils }', 'tointer': 'the opponent record of the row with superlative final score record is hamburg sea devils .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; final score } ; w 41 - 31 } ; eq { hop { argmax { all_rows ; final score } ; opponent } ; hamburg sea devils } } = true', 'tointer': 'the maximum final score record of all rows is w 41 - 31 . the opponent record of the row with superlative final score record is hamburg sea devils .'} | and { eq { max { all_rows ; final score } ; w 41 - 31 } ; eq { hop { argmax { all_rows ; final score } ; opponent } ; hamburg sea devils } } = true | the maximum final score record of all rows is w 41 - 31 . the opponent record of the row with superlative final score record is hamburg sea devils . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'final score_8': 8, 'w 41 - 31_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'final score_11': 11, 'opponent_12': 12, 'hamburg sea devils_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'final score_8': 'final score', 'w 41 - 31_9': 'w 41 - 31', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'final score_11': 'final score', 'opponent_12': 'opponent', 'hamburg sea devils_13': 'hamburg sea devils'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'final score_8': [0], 'w 41 - 31_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'final score_11': [2], 'opponent_12': [3], 'hamburg sea devils_13': [4]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , april 14', '7:00 pm', 'frankfurt galaxy', 'l 14 - 30', '0 - 1', 'commerzbank - arena', '38125'], ['2', 'friday , april 20', '8:00 pm', 'rhein fire', 'l 10 - 16', '0 - 2', 'amsterdam arena', '14611'], ['3', 'saturday , april 28', '6:00 pm', 'berlin thunder', 'w 14 - 10', '1 - 2', 'olympic stadium', '11942'], ['4', 'sunday , may 6', '3:00 pm', 'frankfurt galaxy', 'w 19 - 17', '2 - 2', 'amsterdam arena', '10788'], ['5', 'saturday , may 12', '6:00 pm', 'hamburg sea devils', 'l 17 - 24', '2 - 3', 'aol arena', '15271'], ['6', 'friday , may 18', '8:00 pm', 'hamburg sea devils', 'w 41 - 31', '3 - 3', 'amsterdam arena', '9384'], ['7', 'friday , may 25', '8:00 pm', 'cologne centurions', 'l 7 - 30', '3 - 4', 'amsterdam arena', '11714'], ['8', 'sunday , june 3', '4:00 pm', 'rhein fire', 'l 38 - 41', '3 - 5', 'ltu arena', '20355'], ['9', 'saturday , june 9', '6:00 pm', 'cologne centurions', 'l 13 - 31', '3 - 6', 'rheinenergiestadion', '12878']] |
fabiano iha | https://en.wikipedia.org/wiki/Fabiano_Iha | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445451-2.html.csv | majority | the majority of fabiano iha 's fights ended in the 1st round of the fight . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'round', '1'], 'result': True, 'ind': 0, 'tointer': 'for the round records of all rows , most of them are equal to 1 .', 'tostr': 'most_eq { all_rows ; round ; 1 } = true'} | most_eq { all_rows ; round ; 1 } = true | for the round records of all rows , most of them are equal to 1 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'round_3': 3, '1_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'round_3': 'round', '1_4': '1'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'round_3': [0], '1_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time'] | [['win', '9 - 5', 'john cox', 'ko', 'lip 1 - lockdown in paradise 1', '1', '0:30'], ['win', '8 - 5', 'flavio troccoli', 'submission ( armbar )', 'hfp 2 - hitman fighting productions 2', '1', '0:53'], ['loss', '7 - 5', 'din thomas', 'decision ( unanimous )', 'ufc 33', '3', '5:00'], ['loss', '7 - 4', 'caol uno', 'ko ( punches )', 'ufc 32', '1', '1:48'], ['win', '7 - 3', 'phil johns', 'submission ( armbar )', 'ufc 30', '1', '2:05'], ['win', '6 - 3', 'daiju takase', 'tko ( strikes )', 'ufc 29', '1', '2:24'], ['win', '5 - 3', 'laverne clark', 'submission ( armbar )', 'ufc 27', '1', '1:10'], ['win', '4 - 3', 'danny bennett', 'submission ( armbar )', 'kotc 4 - gladiators', '1', '0:49'], ['loss', '3 - 3', 'dave menne', 'decision', 'ufc 24', '3', '5:00'], ['loss', '3 - 2', 'frank trigg', 'tko ( strikes )', 'pride 8', '1', '5:00'], ['loss', '3 - 1', 'laverne clark', 'tko ( cut )', 'ufc 20', '1', '1:31'], ['win', '3 - 0', 'cleber luciano', 'ko', 'ec 22 - extreme challenge 22', '1', '7:57'], ['win', '2 - 0', 'yves edwards', 'submission ( armbar )', 'ec 22 - extreme challenge 22', '1', '3:56'], ['win', '1 - 0', 'john borsos', 'submission ( armbar )', 'ng 5 - neutral grounds 5', '1', '0:25']] |
list of england national rugby union team results 1980 - 89 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-3.html.csv | majority | in regards to the england national rugby union team , the status of most of the matches was five nations . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'five nations', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'status', 'five nations'], 'result': True, 'ind': 0, 'tointer': 'for the status records of all rows , most of them fuzzily match to five nations .', 'tostr': 'most_eq { all_rows ; status ; five nations } = true'} | most_eq { all_rows ; status ; five nations } = true | for the status records of all rows , most of them fuzzily match to five nations . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'status_3': 3, 'five nations_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'status_3': 'status', 'five nations_4': 'five nations'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'status_3': [0], 'five nations_4': [0]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['australia', '11', '02 / 01 / 1982', 'twickenham , london', 'test match'], ['scotland', '9', '16 / 01 / 1982', 'murrayfield , edinburgh', 'five nations'], ['ireland', '16', '06 / 02 / 1982', 'twickenham , london', 'five nations'], ['france', '15', '20 / 02 / 1982', 'parc des princes , paris', 'five nations'], ['wales', '7', '06 / 03 / 1982', 'twickenham , london', 'five nations']] |
new zealand open ( badminton ) | https://en.wikipedia.org/wiki/New_Zealand_Open_%28badminton%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12275551-1.html.csv | comparative | nicholas hall participated in the men 's singles event before andrew smith did . | {'row_1': '1', 'row_2': '13', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', "men 's singles", 'nicholas hall'], 'result': None, 'ind': 0, 'tointer': "select the rows whose men 's singles record fuzzily matches to nicholas hall .", 'tostr': "filter_eq { all_rows ; men 's singles ; nicholas hall }"}, 'year'], 'result': None, 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; men 's singles ; nicholas hall } ; year }", 'tointer': "select the rows whose men 's singles record fuzzily matches to nicholas hall . take the year record of this row ."}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', "men 's singles", 'andrew smith'], 'result': None, 'ind': 1, 'tointer': "select the rows whose men 's singles record fuzzily matches to andrew smith .", 'tostr': "filter_eq { all_rows ; men 's singles ; andrew smith }"}, 'year'], 'result': None, 'ind': 3, 'tostr': "hop { filter_eq { all_rows ; men 's singles ; andrew smith } ; year }", 'tointer': "select the rows whose men 's singles record fuzzily matches to andrew smith . take the year record of this row ."}], 'result': True, 'ind': 4, 'tostr': "less { hop { filter_eq { all_rows ; men 's singles ; nicholas hall } ; year } ; hop { filter_eq { all_rows ; men 's singles ; andrew smith } ; year } } = true", 'tointer': "select the rows whose men 's singles record fuzzily matches to nicholas hall . take the year record of this row . select the rows whose men 's singles record fuzzily matches to andrew smith . take the year record of this row . the first record is less than the second record ."} | less { hop { filter_eq { all_rows ; men 's singles ; nicholas hall } ; year } ; hop { filter_eq { all_rows ; men 's singles ; andrew smith } ; year } } = true | select the rows whose men 's singles record fuzzily matches to nicholas hall . take the year record of this row . select the rows whose men 's singles record fuzzily matches to andrew smith . take the year record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, "men 's singles_7": 7, 'nicholas hall_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, "men 's singles_11": 11, 'andrew smith_12': 12, 'year_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', "men 's singles_7": "men 's singles", 'nicholas hall_8': 'nicholas hall', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', "men 's singles_11": "men 's singles", 'andrew smith_12': 'andrew smith', 'year_13': 'year'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], "men 's singles_7": [0], 'nicholas hall_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], "men 's singles_11": [1], 'andrew smith_12': [1], 'year_13': [3]} | ['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles'] | [['1990', 'nicholas hall', 'stephanie spicer', 'nicholas hall dean galt', 'rhona robertson lynne scutt', 'brent chapman tammy jenkins'], ['1991', 'wei yan', 'anna oi chan lao', 'peter blackburn darren mcdonald', 'rhonda cator anna oi chan lao', 'peter blackburn lisa campbell'], ['1992', 'dean galt', 'julie still', 'dean galt andrew compton', 'rhona robertson tammy jenkins', 'grant walker sheree jefferson'], ['1993', 'dean galt', 'rhona robertson', 'dean galt kerrin harrison', 'rhona robertson liao yue jin', 'dean galt liao yue jin'], ['1994', 'oliver pongratz', 'song yang', 'michael helber michael keck', 'lisa campbell amanda hardy', 'peter blackburn rhonda cator'], ['1995', 'tam kai chuen', 'song yang', 'he tim chan siu kwong', 'rhona robertson tammy jenkins', 'he tim chan oi ni'], ['1996', 'tam kai chuen', 'li feng', 'ma che kong chow kin man', 'rhona robertson tammy jenkins', 'tam kai chuen tung chau man'], ['1997', 'nicholas hall', 'li feng', 'ma che kong liu kwok wa', 'rhona robertson tammy jenkins', 'ma che kong tung chau man'], ['1998', 'geoffrey bellingham', 'li feng', 'daniel shirley dean galt', 'rhona robertson tammy jenkins', 'dean galt tammy jenkins'], ['2000', 'geoffrey bellingham', 'rhona robertson', 'daniel shirley john gordon', 'masami yamazaki keiko yoshitomi', 'peter blackburn rhonda cator'], ['2002', 'geoffrey bellingham', 'kim ji - hyun', 'daniel shirley john gordon', 'nicole gordon sara runesten - petersen', 'daniel shirley sara runesten - petersen'], ['2003', 'shōji satō', 'lenny permana', 'ashley brehaut travis denney', 'nicole gordon rebecca gordon', 'travis denney kate wilson - smith'], ['2004', 'andrew smith', 'huang chia chi', 'suichi nakao suichi sakamoto', 'rachel hindley rebecca gordon', 'craig cooper lianne shirley'], ['2005', 'sairul amar ayob', 'adriyanti firdasari', 'boyd cooper travis denney', 'rachel hindley rebecca bellingham', 'daniel shirley sara runesten - petersen'], ['2006', 'lee tsuen seng', 'huang chia - chi', 'eng hian rian sukmawan', 'jiang yanmei li yujia', 'hendri kurniawan saputra li yujia'], ['2007', 'andre kurniawan tedjono', 'zhou mi', 'chan chong ming hoon thien how', 'ikue tatani aya wakisaka', 'devin lahardi fitriawan lita nurlita'], ['2008', 'lee tsuen seng', 'zhou mi', 'chen hung - ling lin yu - lang', 'chien yu - chin chou chia - chi', 'chen hung - ling chou chia - chi'], ['2009', 'chan yan kit', 'sayaka sato', 'ruseph kumar sanave thomas', 'annisa wahyuni anneke feinya agustin', 'frans kurniawan pia zebadiah bernadet'], ['2013', 'riichi takeshita', 'deng xuan', 'angga pratama rian agung saputro', 'ou dongni tang yuanting', 'praveen jordan vita marissa']] |
radiopharmacology | https://en.wikipedia.org/wiki/Radiopharmacology | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1035507-12.html.csv | unique | in111 - s leukocyte is the only one with infection / inflammation imaging among those with iv route of administration . | {'scope': 'subset', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'infection / inflammation imaging', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'iv'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'route of administration', 'iv'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; route of administration ; iv }', 'tointer': 'select the rows whose route of administration record fuzzily matches to iv .'}, 'investigation', 'infection / inflammation imaging'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose route of administration record fuzzily matches to iv . among these rows , select the rows whose investigation record fuzzily matches to infection / inflammation imaging .', 'tostr': 'filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } }', 'tointer': 'select the rows whose route of administration record fuzzily matches to iv . among these rows , select the rows whose investigation record fuzzily matches to infection / inflammation imaging . 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', 'route of administration', 'iv'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; route of administration ; iv }', 'tointer': 'select the rows whose route of administration record fuzzily matches to iv .'}, 'investigation', 'infection / inflammation imaging'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose route of administration record fuzzily matches to iv . among these rows , select the rows whose investigation record fuzzily matches to infection / inflammation imaging .', 'tostr': 'filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging }'}, 'name'], 'result': 'in111 - s leukocyte', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } ; name }'}, 'in111 - s leukocyte'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } ; name } ; in111 - s leukocyte }', 'tointer': 'the name record of this unqiue row is in111 - s leukocyte .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } } ; eq { hop { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } ; name } ; in111 - s leukocyte } } = true', 'tointer': 'select the rows whose route of administration record fuzzily matches to iv . among these rows , select the rows whose investigation record fuzzily matches to infection / inflammation imaging . there is only one such row in the table . the name record of this unqiue row is in111 - s leukocyte .'} | and { only { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } } ; eq { hop { filter_eq { filter_eq { all_rows ; route of administration ; iv } ; investigation ; infection / inflammation imaging } ; name } ; in111 - s leukocyte } } = true | select the rows whose route of administration record fuzzily matches to iv . among these rows , select the rows whose investigation record fuzzily matches to infection / inflammation imaging . there is only one such row in the table . the name record of this unqiue row is in111 - s leukocyte . | 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, 'route of administration_8': 8, 'iv_9': 9, 'investigation_10': 10, 'infection / inflammation imaging_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'name_12': 12, 'in111 - s leukocyte_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', 'route of administration_8': 'route of administration', 'iv_9': 'iv', 'investigation_10': 'investigation', 'infection / inflammation imaging_11': 'infection / inflammation imaging', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'name_12': 'name', 'in111 - s leukocyte_13': 'in111 - s leukocyte'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'route of administration_8': [0], 'iv_9': [0], 'investigation_10': [1], 'infection / inflammation imaging_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'name_12': [3], 'in111 - s leukocyte_13': [4]} | ['name', 'investigation', 'route of administration', 'in - vitro / in - vivo', 'imaging / non - imaging'] | [['in111 - dtpa ( diethylenetriaminepenta - acetic acid )', 'ventriculo - peritoneal shunt ( laveen shunt )', 'intraperitoneal injection', 'in - vivo', 'imaging'], ['in111 - dtpa ( diethylenetriaminepenta - acetic acid )', 'cisternography', 'intra - cisternal', 'in - vivo', 'imaging'], ['in111 - s leukocyte', 'infection / inflammation imaging', 'iv', 'in - vivo', 'imaging'], ['in111 - s platelet', 'thrombus imaging', 'iv', 'in - vivo', 'imaging'], ['in111 - pentetreotide', 'somatostatin receptor imaging', 'iv', 'in - vivo', 'imaging'], ['in111 - octreotide', 'somatostatin receptor imaging ( octreoscan )', 'iv', 'in - vivo', 'imaging']] |
1981 all - ireland senior hurling championship | https://en.wikipedia.org/wiki/1981_All-Ireland_Senior_Hurling_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18937093-2.html.csv | aggregation | in the 1981 all-ireland senior hurling championship all 17 players combined achieved an average total of 9.29 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '9.29', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '9.29', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '9.29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 9.29 } = true', 'tointer': 'the average of the total record of all rows is 9.29 .'} | round_eq { avg { all_rows ; total } ; 9.29 } = true | the average of the total record of all rows is 9.29 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '9.29_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '9.29_5': '9.29'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '9.29_5': [1]} | ['rank', 'player', 'county', 'tally', 'total', 'opposition'] | [['1', 'joe connolly', 'galway', '2 - 7', '13', 'limerick'], ['2', 'joe mckenna', 'limerick', '3 - 3', '12', 'clare'], ['2', 'john grogan', 'tipperary', '2 - 6', '12', 'limerick'], ['4', 'bernie forde', 'galway', '2 - 5', '11', 'antrim'], ['5', 'joe mckenna', 'limerick', '3 - 1', '10', 'tipperary'], ['6', 'billy bohane', 'laois', '2 - 3', '9', 'offaly'], ['6', 'pádraig horan', 'offaly', '2 - 3', '9', 'wexford'], ['6', 'séamus bourke', 'tipperary', '2 - 3', '9', 'limerick'], ['6', 'noel lane', 'galway', '1 - 6', '9', 'antrim'], ['6', 'martin brophy', 'laois', '0 - 9', '9', 'westmeath'], ['11', 'pádraig horan', 'offaly', '2 - 2', '8', 'laois'], ['11', 'éamonn cregan', 'limerick', '1 - 5', '8', 'offaly'], ['11', 'mark corrigan', 'offaly', '1 - 5', '8', 'laois'], ['11', 'tony doran', 'wexford', '1 - 5', '8', 'dublin'], ['11', 'billy fitzpatrick', 'kilkenny', '0 - 8', '8', 'wexford'], ['11', 'joe connolly', 'galway', '0 - 8', '8', 'offaly'], ['17', 'dinny donnelly', 'antrim', '1 - 4', '7', 'galway']] |
2001 - 02 philadelphia flyers season | https://en.wikipedia.org/wiki/2001%E2%80%9302_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14347256-5.html.csv | superlative | the philadelphia flyers ' game against vancouver canucks recorded the most points in the 2001 - 02 season . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '15', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'opponent'], 'result': 'vancouver canucks', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; opponent }'}, 'vancouver canucks'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; opponent } ; vancouver canucks } = true', 'tointer': 'select the row whose points record of all rows is maximum . the opponent record of this row is vancouver canucks .'} | eq { hop { argmax { all_rows ; points } ; opponent } ; vancouver canucks } = true | select the row whose points record of all rows is maximum . the opponent record of this row is vancouver canucks . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'opponent_6': 6, 'vancouver canucks_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'opponent_6': 'opponent', 'vancouver canucks_7': 'vancouver canucks'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'opponent_6': [1], 'vancouver canucks_7': [2]} | ['game', 'december', 'opponent', 'score', 'record', 'points'] | [['24', '1', 'tampa bay lightning', '2 - 0', '11 - 7 - 5 - 1', '28'], ['25', '4', 'new york islanders', '3 - 2', '12 - 7 - 5 - 1', '30'], ['26', '6', 'new york islanders', '0 - 2', '12 - 8 - 5 - 1', '30'], ['27', '8', 'minnesota wild', '5 - 1', '13 - 8 - 5 - 1', '32'], ['28', '10', 'atlanta thrashers', '3 - 1', '14 - 8 - 5 - 1', '34'], ['29', '13', 'montreal canadiens', '2 - 3', '14 - 9 - 5 - 1', '34'], ['30', '15', 'boston bruins', '5 - 2', '15 - 9 - 5 - 1', '36'], ['31', '16', 'edmonton oilers', '2 - 3', '15 - 10 - 5 - 1', '36'], ['32', '18', 'st louis blues', '6 - 3', '16 - 10 - 5 - 1', '38'], ['33', '20', 'dallas stars', '2 - 1', '17 - 10 - 5 - 1', '40'], ['34', '22', 'carolina hurricanes', '4 - 3 ot', '18 - 10 - 5 - 1', '42'], ['35', '26', 'washington capitals', '4 - 1', '19 - 10 - 5 - 1', '44'], ['36', '28', 'phoenix coyotes', '2 - 4', '19 - 11 - 5 - 1', '44'], ['37', '29', 'colorado avalanche', '5 - 2', '20 - 11 - 5 - 1', '46'], ['38', '31', 'vancouver canucks', '2 - 1', '21 - 11 - 5 - 1', '48']] |
saulo roston | https://en.wikipedia.org/wiki/Saulo_Roston | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27614707-1.html.csv | count | there are three episodes of ídolos brazil where the theme of the songs were the judge 's choice . | {'scope': 'all', 'criterion': 'equal', 'value': "judge 's choice", 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'theme', "judge 's choice"], 'result': None, 'ind': 0, 'tointer': "select the rows whose theme record fuzzily matches to judge 's choice .", 'tostr': "filter_eq { all_rows ; theme ; judge 's choice }"}], 'result': '3', 'ind': 1, 'tostr': "count { filter_eq { all_rows ; theme ; judge 's choice } }", 'tointer': "select the rows whose theme record fuzzily matches to judge 's choice . the number of such rows is 3 ."}, '3'], 'result': True, 'ind': 2, 'tostr': "eq { count { filter_eq { all_rows ; theme ; judge 's choice } } ; 3 } = true", 'tointer': "select the rows whose theme record fuzzily matches to judge 's choice . the number of such rows is 3 ."} | eq { count { filter_eq { all_rows ; theme ; judge 's choice } } ; 3 } = true | select the rows whose theme record fuzzily matches to judge 's choice . 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, 'theme_5': 5, "judge's choice_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', 'theme_5': 'theme', "judge's choice_6": "judge 's choice", '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'theme_5': [0], "judge's choice_6": [0], '3_7': [2]} | ['week', 'theme', 'song choice', 'original artist', 'order', 'result'] | [['audition', "auditioner 's choice", 'bem que se quis', 'marisa monte', 'n / a', 'advanced'], ['theater', 'first solo', 'n / a', 'n / a', 'n / a', 'advanced'], ['top 24', 'top 12 men', 'como vai você', 'roberto carlos', '7', 'advanced'], ['top 12', 'sing your idol', 'beija eu', 'marisa monte', '4', 'safe'], ['top 11', '70s night', 'mania de você', 'rita lee', '10', 'safe'], ['top 10', 'the roguish', 'já tive mulheres', 'martinho da vila', '6', 'safe'], ['top 9', 'broken heart songs', 'tem que ser você', 'victor & léo', '4', 'bottom 3'], ['top 7', '80s night', 'você é linda', 'caetano veloso', '2', 'safe'], ['top 6', 'cult trash', 'aguenta coração', 'josé augusto', '1', 'safe'], ['top 5', 'kings of the pop', 'amor i love you', 'marisa monte', '4', 'safe'], ['top 5', 'kings of the pop', 'your song', 'elton john', '9', 'safe'], ['top 4', 'dedicate a song', 'monalisa', 'jorge vercilo', '1', 'safe'], ['top 4', 'my soundtrack', 'eu sei que vou te amar', 'tom jobim', '5', 'safe'], ['top 3', "judge 's choice", 'pro dia nascer feliz', 'cazuza', '1', 'safe'], ['top 3', "judge 's choice", 'fácil', 'jota quest', '4', 'safe'], ['top 3', "judge 's choice", 'o portão', 'roberto carlos', '7', 'safe'], ['top 2', "winner 's single 1", 'nova paixão', 'saulo roston', '1', 'winner'], ['top 2', 'best of the season', 'your song', 'elton john', '3', 'winner']] |
2008 tour de suisse | https://en.wikipedia.org/wiki/2008_Tour_de_Suisse | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17672470-19.html.csv | majority | rene weissinger had the majority of sprints classification in the 2008 tour de suisse . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rené weissinger', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'sprints classification', 'rené weissinger'], 'result': True, 'ind': 0, 'tointer': 'for the sprints classification records of all rows , most of them fuzzily match to rené weissinger .', 'tostr': 'most_eq { all_rows ; sprints classification ; rené weissinger } = true'} | most_eq { all_rows ; sprints classification ; rené weissinger } = true | for the sprints classification records of all rows , most of them fuzzily match to rené weissinger . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'sprints classification_3': 3, 'rené weissinger_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'sprints classification_3': 'sprints classification', 'rené weissinger_4': 'rené weissinger'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'sprints classification_3': [0], 'rené weissinger_4': [0]} | ['stage', 'winner', 'general classification', 'mountains classification', 'points classification', 'sprints classification', 'team classification'] | [['1', 'óscar freire', 'óscar freire', 'no award', 'óscar freire', 'no award', "caisse d'epargne"], ['2', 'igor antón', 'igor antón', 'david loosli', 'kim kirchen', 'david loosli', 'team csc'], ['3', 'robbie mcewen', 'igor antón', 'david loosli', 'óscar freire', 'rené weissinger', 'team csc'], ['4', 'robbie mcewen', 'igor antón', 'david loosli', 'óscar freire', 'rené weissinger', 'team csc'], ['5', 'markus fothen', 'igor antón', 'david loosli', 'óscar freire', 'rené weissinger', 'gerolsteiner'], ['6', 'kim kirchen', 'kim kirchen', 'david loosli', 'óscar freire', 'rené weissinger', 'astana'], ['7', 'fabian cancellara', 'kim kirchen', 'maxim iglinsky', 'óscar freire', 'rené weissinger', 'astana'], ['8', 'roman kreuziger', 'roman kreuziger', 'maxim iglinsky', 'óscar freire', 'rené weissinger', 'astana'], ['9', 'fabian cancellara', 'roman kreuziger', 'maxim iglinsky', 'fabian cancellara', 'rené weissinger', 'astana'], ['final', 'final', 'roman kreuziger', 'maxim iglinsky', 'fabian cancellara', 'rené weissinger', 'astana']] |
greg norman | https://en.wikipedia.org/wiki/Greg_Norman | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-157447-7.html.csv | aggregation | the professional golfer greg norman had an added total of 48 top 25 placements . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '48', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'top - 25'], 'result': '48', 'ind': 0, 'tostr': 'sum { all_rows ; top - 25 }'}, '48'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; top - 25 } ; 48 } = true', 'tointer': 'the sum of the top - 25 record of all rows is 48 .'} | round_eq { sum { all_rows ; top - 25 } ; 48 } = true | the sum of the top - 25 record of all rows is 48 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'top - 25_4': 4, '48_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'top - 25_4': 'top - 25', '48_5': '48'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'top - 25_4': [0], '48_5': [1]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '8', '9', '12', '23', '17'], ['us open', '0', '3', '5', '7', '19', '13'], ['the open championship', '2', '4', '10', '17', '27', '23'], ['pga championship', '0', '5', '6', '12', '22', '18'], ['totals', '2', '20', '30', '48', '91', '71']] |
1986 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1986_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17231232-7.html.csv | unique | bernhard langer was the only non-american who won a share of the prize money . | {'scope': 'all', 'row': '8', 'col': '3', 'col_other': '2', 'criterion': 'not_equal', 'value': 'united states', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record does not match to united states .', 'tostr': 'filter_not_eq { all_rows ; country ; united states }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record does not match to united states . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record does not match to united states .', 'tostr': 'filter_not_eq { all_rows ; country ; united states }'}, 'player'], 'result': 'bernhard langer', 'ind': 2, 'tostr': 'hop { filter_not_eq { all_rows ; country ; united states } ; player }'}, 'bernhard langer'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; bernhard langer }', 'tointer': 'the player record of this unqiue row is bernhard langer .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_not_eq { all_rows ; country ; united states } } ; eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; bernhard langer } } = true', 'tointer': 'select the rows whose country record does not match to united states . there is only one such row in the table . the player record of this unqiue row is bernhard langer .'} | and { only { filter_not_eq { all_rows ; country ; united states } } ; eq { hop { filter_not_eq { all_rows ; country ; united states } ; player } ; bernhard langer } } = true | select the rows whose country record does not match to united states . there is only one such row in the table . the player record of this unqiue row is bernhard langer . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'united states_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'bernhard langer_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', 'country_7': 'country', 'united states_8': 'united states', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'bernhard langer_10': 'bernhard langer'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'united states_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'bernhard langer_10': [3]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'raymond floyd', 'united states', '75 + 68 + 70 + 66 = 279', '1', '115000'], ['t2', 'chip beck', 'united states', '75 + 73 + 68 + 65 = 281', '+ 1', '47646'], ['t2', 'lanny wadkins', 'united states', '74 + 70 + 72 + 65 = 281', '+ 1', '47646'], ['t4', 'hal sutton', 'united states', '75 + 70 + 66 + 71 = 282', '+ 2', '26269'], ['t4', 'lee trevino', 'united states', '74 + 68 + 69 + 71 = 282', '+ 2', '26269'], ['t6', 'ben crenshaw', 'united states', '76 + 69 + 69 + 69 = 283', '+ 3', '19009'], ['t6', 'payne stewart', 'united states', '76 + 68 + 69 + 70 = 283', '+ 3', '19009'], ['t8', 'bernhard langer', 'west germany', '74 + 70 + 70 + 70 = 284', '+ 4', '14500'], ['t8', 'mark mccumber', 'united states', '74 + 71 + 68 + 71 = 284', '+ 4', '14500'], ['t8', 'jack nicklaus', 'united states', '77 + 72 + 67 + 68 = 284', '+ 4', '14500'], ['t8', 'bob tway', 'united states', '70 + 73 + 69 + 72 = 284', '+ 4', '14500']] |
laser quest | https://en.wikipedia.org/wiki/Laser_Quest | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2011349-2.html.csv | count | paragon denver co was the first runner up for laser quest a total of three times . | {'scope': 'all', 'criterion': 'equal', 'value': 'paragon denver co', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first runner up', 'paragon denver co'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first runner up record fuzzily matches to paragon denver co .', 'tostr': 'filter_eq { all_rows ; first runner up ; paragon denver co }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first runner up ; paragon denver co } }', 'tointer': 'select the rows whose first runner up record fuzzily matches to paragon denver co . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first runner up ; paragon denver co } } ; 3 } = true', 'tointer': 'select the rows whose first runner up record fuzzily matches to paragon denver co . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; first runner up ; paragon denver co } } ; 3 } = true | select the rows whose first runner up record fuzzily matches to paragon denver co . 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 runner up_5': 5, 'paragon denver co_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 runner up_5': 'first runner up', 'paragon denver co_6': 'paragon denver co', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'first runner up_5': [0], 'paragon denver co_6': [0], '3_7': [2]} | ['year', 'winner', 'first runner up', 'third place', 'consolation winner / 4th', 'finals location'] | [['2012 details', 'tsa toronto on', 'nrh north richland hills tx', 'mesa mesa az', 'denver denver co', 'las vegas nv'], ['2011 details', 'nrh north richland hills tx', 'tsa toronto on', 'mesa mesa az', 'federal way seattle wa', 'las vegas nv'], ['2010 details', 'tsa toronto on', 'nrh north richland hills tx', 'mesa mesa az', 'federal way seattle wa', 'hoffman estates il'], ['2009 details', 'nrh north richland hills tx', 'tsa toronto on', 'federal way seattle wa', 'team off hoffman estates il', 'las vegas nv'], ['2008 details', 'nrh north richland hills tx', 'shadowz lincoln ne', 'tsa scarborough on', 'team off hoffman estates il', 'hoffman estates il'], ['2007 details', '9 deadly venoms houston tx', 'brampton brew crew brampton on', 'team off hoffman estates il', 'nrh north richland hills tx', 'gwinnett ga'], ['2006 details', 'shadowz lincoln ne', 'westland wolfpack westland mi', '42 appleton wi', 'brampton brew crew brampton on', 'las vegas nv'], ['2005 details', 'nrh north richland hills tx', '9 deadly venoms houston tx', 'westland wolfpack westland mi', 'brampton brew crew brampton on', 'mesquite tx'], ['2004 details', 'brampton brew crew brampton on', 'nrh north richland hills tx', '9 deadly venoms houston tx', 'phoenix pyros phoenix az', 'rochester ny'], ['2003 details', 'paragon denver co', 'westland wolfpack westland mi', 'shadowz lincoln ne', 'brampton brew crew brampton on', 'north richland hills tx'], ['2002 details', 'paragon denver co', 'phoenix pyros phoenix az', '9 deadly venoms houston tx', 'shadowz lincoln ne', 'norridge il'], ['2001 details', 'paragon denver co', 'westland wolfpack westland mi', 'san antonio san antonio tx', 'austin austin tx', 'colorado springs co'], ['2000 details', 'phoenix pyros phoenix az', 'paragon denver co', 'tulsa whoopdonkeys tulsa ok', 'westland wolfpack westland mi', 'scarborough on'], ['1999 details', 'phoenix pyros phoenix az', 'paragon denver co', 'austin austin tx', 'nrh north richland hills tx', 'north richland hills tx'], ['1998 details', '9 deadly venoms houston tx', 'phoenix pyros phoenix az', 'armageddon lincoln ne', 'mesa mesa az', 'knoxville tn'], ['1997 details', 'team mad madison heights mi', 'paragon denver co', 'oshawa oshawa on', 'phoenix pyros phoenix az', 'downers grove il'], ['1996 details', 'oshawa oshawa on', 'london london on', 'brampton brew crew brampton on', 'charlotte charlotte nc', 'london on']] |
cho jae - jin | https://en.wikipedia.org/wiki/Cho_Jae-Jin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1385081-3.html.csv | aggregation | from 2003 - 2007 , cho jae-jin scored a total of 10 goals in international games . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '10', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '10', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '10'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 10 } = true', 'tointer': 'the sum of the score record of all rows is 10 .'} | round_eq { sum { all_rows ; score } ; 10 } = true | the sum of the score record of all rows is 10 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '10_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '10_5': '10'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '10_5': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['25 september 2003', 'incheon', '1 goal', '5 - 0', '2004 afc asian cup qualification'], ['24 october 2003', 'muscat', '1 goal', '7 - 0', '2004 afc asian cup qualification'], ['19 december 2004', 'busan', '1 goal', '3 - 1', 'friendly match'], ['1 february 2006', 'hong kong', '1 goal', '1 - 3', '2006 carlsberg cup'], ['26 may 2006', 'seoul', '1 goal', '2 - 0', 'friendly match'], ['6 september 2006', 'suwon', '2 goals', '8 - 0', '2007 afc asian cup qualification'], ['11 october 2006', 'seoul', '1 goal', '2 - 1', '2007 afc asian cup qualification'], ['5 july 2007', 'seoul', '2 goals', '2 - 1', 'friendly match']] |
1996 senior pga tour | https://en.wikipedia.org/wiki/1996_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11621873-3.html.csv | count | three of the top-ranked players in the 1996 senior pga tour came from the united states . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; united states } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; united states } } ; 3 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; country ; united states } } ; 3 } = true | select the rows whose country record fuzzily matches to united states . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], '3_7': [2]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'jim colbert', 'united states', '1627890', '32', '5'], ['2', 'hale irwin', 'united states', '1615769', '23', '2'], ['3', 'john bland', 'south africa', '1357987', '35', '4'], ['4', 'isao aoki', 'japan', '1162581', '26', '2'], ['5', 'dave stockton', 'united states', '1117685', '29', '2']] |
list of prime ministers of albania | https://en.wikipedia.org/wiki/List_of_Prime_Ministers_of_Albania | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-167235-2.html.csv | majority | the majority of prime ministers in albania ere not members of a party . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'non - party', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'political party', 'non - party'], 'result': True, 'ind': 0, 'tointer': 'for the political party records of all rows , most of them fuzzily match to non - party .', 'tostr': 'most_eq { all_rows ; political party ; non - party } = true'} | most_eq { all_rows ; political party ; non - party } = true | for the political party records of all rows , most of them fuzzily match to non - party . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'political party_3': 3, 'non - party_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'political party_3': 'political party', 'non - party_4': 'non - party'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'political party_3': [0], 'non - party_4': [0]} | ['name', 'born - died', 'term start', 'term end', 'political party'] | [['prime ministers 1914 - 1925', 'prime ministers 1914 - 1925', 'prime ministers 1914 - 1925', 'prime ministers 1914 - 1925', 'prime ministers 1914 - 1925'], ['turhan pasha përmeti ( 1st time )', '1846 - 1927', '7 march 1914', '3 september 1914', 'non - party'], ['essad pasha toptani', '1863 - 1920', '5 october 1914', '24 february 1916', 'non - party'], ['vacant ( 24 february 1916 - 25 december 1918 )', 'vacant ( 24 february 1916 - 25 december 1918 )', 'vacant ( 24 february 1916 - 25 december 1918 )', 'vacant ( 24 february 1916 - 25 december 1918 )', 'vacant ( 24 february 1916 - 25 december 1918 )'], ['turhan pasha përmeti ( 2nd time )', '1846 - 1927', '25 december 1918', '29 january 1920', 'non - party'], ['sulejman bej delvina', '1884 - 1932', '30 january 1920', '14 november 1920', 'non - party'], ['iliaz bej vrioni ( 1st time )', '1882 - 1932', '19 november 1920', '16 october 1921', 'non - party'], ['pandeli evangjeli ( 1st time )', '1859 - 1939', '16 october 1921', '6 december 1921', 'non - party'], ['qazim koculi ( acting )', '1887 - 1943', '6 december 1921', '7 december 1921', 'non - party'], ['hasan bej prishtina', '1873 - 1933', '7 december 1921', '12 december 1921', 'non - party'], ['idhomene kosturi ( acting )', '1873 - 1943', '12 december 1921', '24 december 1921', 'non - party'], ['xhafer bej ypi', '1880 - 1940', '24 december 1921', '26 december 1922', 'albanian popular party'], ['ahmet zogu ( 1st time )', '1895 - 1961', '26 december 1922', '25 february 1924', 'non - party'], ['shefqet bej vërlaci ( 1st time )', '1877 - 1946', '30 march 1924', '27 may 1924', 'progressive party'], ['ilias bej vrioni ( 2nd time )', '1882 - 1932', '27 may 1924', '10 june 1924', 'non - party'], ['fan s noli', '1882 - 1965', '16 june 1924', '23 december 1924', 'democratic party'], ['ilias bej vrioni ( 3rd time )', '1882 - 1932', '24 december 1924', '5 january 1925', 'non - party'], ['ahmet zogu ( 2nd time )', '1895 - 1961', '6 january 1925', '31 january 1925', 'non - party']] |
list of earthquakes in iran | https://en.wikipedia.org/wiki/List_of_earthquakes_in_Iran | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10677198-1.html.csv | superlative | the biggest earthquake in iran during 2002-2013 happened in saravan . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'magnitude'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; magnitude }'}, 'epicenter'], 'result': 'saravan , iran', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; magnitude } ; epicenter }'}, 'saravan , iran'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; magnitude } ; epicenter } ; saravan , iran } = true', 'tointer': 'select the row whose magnitude record of all rows is maximum . the epicenter record of this row is saravan , iran .'} | eq { hop { argmax { all_rows ; magnitude } ; epicenter } ; saravan , iran } = true | select the row whose magnitude record of all rows is maximum . the epicenter record of this row is saravan , iran . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'magnitude_5': 5, 'epicenter_6': 6, 'saravan , iran_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'magnitude_5': 'magnitude', 'epicenter_6': 'epicenter', 'saravan , iran_7': 'saravan , iran'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'magnitude_5': [0], 'epicenter_6': [1], 'saravan , iran_7': [2]} | ['date', 'time', 'epicenter', 'magnitude', 'fatalities', 'name'] | [['apr 16 , 2013', '10:44:13', 'saravan , iran', '7.8', '1 ( non - residential area , due to landslide )', '2013 sistan and baluchestan earthquake'], ['apr 9 , 2013', '16:22:50', 'bushehr', '6.3', '30 ( early estimate )', '2013 bushehr earthquake'], ['aug 11 , 2012', '12:23:18', 'tabriz', '6.4 and 6.3', '306', '2012 tabriz earthquakes'], ['jun 15 , 2011', '01:05:30', 'kahnooj', '5.3', '2', '2011 kahnooj earthquake'], ['dec 20 , 2010', '22:12:01', 'hosseinabad', '6.5', '11', '2010 hosseinabad earthquake'], ['aug 27 , 2010', '23:56:34', 'damghan', '5.9', '19', '2010 damghan earthquake'], ['sep 10 , 2008', '11:00:34', 'qeshm', '6.1', '7', '2008 bandar abbas earthquake'], ['march 31 , 2006', '01:17:01', 'borujerd', '6.1', '70', '2006 borujerd earthquake'], ['november 27 , 2005', '10:22:19', 'qeshm', '6.0', '13', '2005 qeshm earthquake'], ['february 22 , 2005', '02:25:22', 'zarand', '6.4', 'least 602', '2005 zarand earthquake'], ['may 28 , 2004', '12:38:46', 'm훮zandar훮n', '6.3', 'least 35', '2004 m훮zandar훮n earthquake'], ['december 26 , 2003', '01:56:52', 'bam', '6.6', 'least 30000', '2003 bam earthquake'], ['june 22 , 2002', '02:58:21', 'qazvin', '6.5', '262', "2002 bou'in - zahra earthquake"]] |
lukoil | https://en.wikipedia.org/wiki/Lukoil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1027881-2.html.csv | majority | all lukoil that was launched in 1958 has a capacity , mln tpa of 12 ,0 or more . | {'scope': 'subset', 'col': '5', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '12,0', 'subset': {'col': '3', 'criterion': 'equal', 'value': '1958'}} | {'func': 'all_greater_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'launched', '1958'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; launched ; 1958 }', 'tointer': 'select the rows whose launched record is equal to 1958 .'}, 'capacity , mln tpa', '12,0'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose launched record is equal to 1958 . for the capacity , mln tpa records of these rows , all of them are greater than or equal to 12,0 .', 'tostr': 'all_greater_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12,0 } = true'} | all_greater_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12,0 } = true | select the rows whose launched record is equal to 1958 . for the capacity , mln tpa records of these rows , all of them are greater than or equal to 12,0 . | 2 | 2 | {'all_greater_eq_1': 1, 'result_2': 2, 'filter_eq_0': 0, 'all_rows_3': 3, 'launched_4': 4, '1958_5': 5, 'capacity , mln tpa_6': 6, '12,0_7': 7} | {'all_greater_eq_1': 'all_greater_eq', 'result_2': 'true', 'filter_eq_0': 'filter_eq', 'all_rows_3': 'all_rows', 'launched_4': 'launched', '1958_5': '1958', 'capacity , mln tpa_6': 'capacity , mln tpa', '12,0_7': '12,0'} | {'all_greater_eq_1': [2], 'result_2': [], 'filter_eq_0': [1], 'all_rows_3': [0], 'launched_4': [0], '1958_5': [0], 'capacity , mln tpa_6': [1], '12,0_7': [1]} | ['name', 'location', 'launched', 'acquired', 'capacity , mln tpa'] | [['lukoil - nizhegorodnefteorgsintez', 'kstovo', '1958', '2000', '15 , 0'], ['lukoil - permnefteorgsintez', 'perm', '1958', '1991', '12 , 0'], ['lukoil - volgogradneftepererabotka', 'volgograd', '1957', '1991', '9 , 9'], ['lukoil - ukhtaneftepererabotka', 'ukhta', '1934', '2000', '3 , 7'], ['lukoil - odessky neftepererabatyvayuschiy zavod', 'odessa', '1937', '1999', '3 , 6'], ['lukoil neftochim burgas', 'burgas', '1964', '1999', '7 , 5'], ['petrotel - lukoil', 'ploieåÿti', '1904', '1998', '2 , 4'], ['isab', 'priolo gargallo', '1975', '2008', '16 , 0'], ['trn', 'vlissingen', '1973', '2009', '7 , 9']] |
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/2-11545282-10.html.csv | unique | mark jackson is the only player on the utah jazz all - time roster from the st john 's school . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': "st john 's", 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', "st john 's"], 'result': None, 'ind': 0, 'tointer': "select the rows whose school / club team record fuzzily matches to st john 's .", 'tostr': "filter_eq { all_rows ; school / club team ; st john 's }"}], 'result': True, 'ind': 1, 'tostr': "only { filter_eq { all_rows ; school / club team ; st john 's } }", 'tointer': "select the rows whose school / club team record fuzzily matches to st john 's . there is only one such row in the table ."}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', "st john 's"], 'result': None, 'ind': 0, 'tointer': "select the rows whose school / club team record fuzzily matches to st john 's .", 'tostr': "filter_eq { all_rows ; school / club team ; st john 's }"}, 'player'], 'result': 'mark jackson', 'ind': 2, 'tostr': "hop { filter_eq { all_rows ; school / club team ; st john 's } ; player }"}, 'mark jackson'], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; school / club team ; st john 's } ; player } ; mark jackson }", 'tointer': 'the player record of this unqiue row is mark jackson .'}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; school / club team ; st john 's } } ; eq { hop { filter_eq { all_rows ; school / club team ; st john 's } ; player } ; mark jackson } } = true", 'tointer': "select the rows whose school / club team record fuzzily matches to st john 's . there is only one such row in the table . the player record of this unqiue row is mark jackson ."} | and { only { filter_eq { all_rows ; school / club team ; st john 's } } ; eq { hop { filter_eq { all_rows ; school / club team ; st john 's } ; player } ; mark jackson } } = true | select the rows whose school / club team record fuzzily matches to st john 's . there is only one such row in the table . the player record of this unqiue row is mark jackson . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'school / club team_7': 7, "st john 's_8": 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'mark jackson_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'school / club team_7': 'school / club team', "st john 's_8": "st john 's", 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'mark jackson_10': 'mark jackson'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'school / club team_7': [0], "st john 's_8": [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'mark jackson_10': [3]} | ['player', 'nationality', 'position', 'years for jazz', 'school / club team'] | [['mark jackson', 'united states', 'point guard', '2002 - 03', "st john 's"], ['dave jamerson', 'united states', 'guard - forward', '1993', 'ohio'], ['aaron james', 'united states', 'forward', '1974 - 79', 'grambling state'], ['henry james', 'united states', 'forward', '1993', "st mary 's ( tx )"], ['al jefferson', 'united states', 'forward - center', '2010 - present', 'prentiss high school'], ['eric johnson', 'united states', 'guard', '1989 - 90', 'nebraska'], ['ollie johnson', 'united states', 'forward', '1974 - 75', 'temple'], ['nate johnston', 'united states', 'forward', '1989 - 90', 'tampa'], ['jeff judkins', 'united states', 'guard', '1980 - 81', 'utah']] |
toronto , grey and bruce railway | https://en.wikipedia.org/wiki/Toronto%2C_Grey_and_Bruce_Railway | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15339223-1.html.csv | majority | most of the railways were built by avonside engine company . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'avonside engine company', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'builder', 'avonside engine company'], 'result': True, 'ind': 0, 'tointer': 'for the builder records of all rows , most of them fuzzily match to avonside engine company .', 'tostr': 'most_eq { all_rows ; builder ; avonside engine company } = true'} | most_eq { all_rows ; builder ; avonside engine company } = true | for the builder records of all rows , most of them fuzzily match to avonside engine company . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'builder_3': 3, 'avonside engine company_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'builder_3': 'builder', 'avonside engine company_4': 'avonside engine company'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'builder_3': [0], 'avonside engine company_4': [0]} | ['number', 'name', 'builder', 'type', 'date', 'works number'] | [['1', 'gordon', 'avonside engine company', '4 - 6 - 0', 'aug 1870', '799'], ['2', 'ar mcmaster', 'avonside engine company', '4 - 4 - 0', 'aug 1870', '800'], ['3', 'kincardine', 'avonside engine company', '4 - 4 - 0', 'september 1870', '809'], ['4', 'r walker & sons', 'avonside engine company', '4 - 4 - 0', 'may 1871', '838'], ['5', 'albion', 'avonside engine company', '4 - 4 - 0', 'july 1871', '839'], ['6', 'rice lewis & son', 'avonside engine company', '4 - 4 - 0', 'mid 1871', '840'], ['7', 'caledon', 'avonside engine company', '0 - 6 - 6 - 0 fairlie type', 'late 1872', '862 & 863'], ['8', 'mono', 'avonside engine company', '4 - 6 - 0', 'late 1871', '866'], ['9', 'toronto', 'baldwin locomotive works', '2 - 6 - 0', 'september 1871', '2534'], ['10', 'amaranth', 'baldwin locomotive works', '2 - 6 - 0', 'september 1871', '2538'], ['11', 'holland', 'avonside engine company', '4 - 6 - 0', 'early 1873', 'one of 935 - 939'], ['12', 'sydenham', 'avonside engine company', '4 - 6 - 0', 'early 1873', 'one of 935 - 939'], ['13', 'artemisia', 'avonside engine company', '4 - 6 - 0', 'early 1873', 'one of 935 - 939'], ['14', 'owen sound', 'avonside engine company', '4 - 6 - 0', 'early 1873', 'one of 931932933 , or 934'], ['15', 'mount forest', 'baldwin locomotive works', '2 - 8 - 0', 'february 1874', '3524'], ['16', 'orangeville', 'baldwin locomotive works', '2 - 8 - 0', 'february 1874', '3525'], ['17', 'sarawak', 'baldwin locomotive works', '2 - 8 - 0', 'april 1874', '3551'], ['18', 'melancthon', 'baldwin locomotive works', '2 - 8 - 0', 'april 1874', '3552'], ['19', 'howick', 'baldwin locomotive works', '2 - 8 - 0', 'september 1874', '3636'], ['20', 'culross', 'baldwin locomotive works', '2 - 8 - 0', 'september 1874', '3640']] |
nathan ablett | https://en.wikipedia.org/wiki/Nathan_Ablett | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1756688-1.html.csv | superlative | nathan ablett played in the most games in the year of 2007 . | {'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', 'games'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; games }'}, 'season'], 'result': '2007', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; games } ; season }'}, '2007'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; games } ; season } ; 2007 } = true', 'tointer': 'select the row whose games record of all rows is maximum . the season record of this row is 2007 .'} | eq { hop { argmax { all_rows ; games } ; season } ; 2007 } = true | select the row whose games record of all rows is maximum . the season record of this row is 2007 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'games_5': 5, 'season_6': 6, '2007_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'games_5': 'games', 'season_6': 'season', '2007_7': '2007'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'games_5': [0], 'season_6': [1], '2007_7': [2]} | ['season', 'team', 'games', 'disposals', 'kicks', 'handballs', 'marks', 'tackles', 'goals', 'behinds'] | [['2005', 'geelong', '4', '27 ( 6.8 )', '19 ( 4.8 )', '8 ( 2.0 )', '13 ( 3.2 )', '5 ( 1.2 )', '8 ( 2.0 )', '2 ( 0.5 )'], ['2006', 'geelong', '7', '56 ( 8.0 )', '33 ( 4.7 )', '23 ( 3.3 )', '27 ( 3.9 )', '5 ( 0.7 )', '4 ( 0.6 )', '3 ( 0.4 )'], ['2007', 'geelong', '21', '191 ( 9.1 )', '117 ( 5.6 )', '74 ( 3.5 )', '86 ( 4.1 )', '28 ( 1.3 )', '34 ( 1.6 )', '18 ( 0.9 )'], ['2008', 'geelong', '-', '-', '-', '-', '-', '-', '-', '-'], ['2011', 'gold coast', '2', '22 ( 11.0 )', '9 ( 4.5 )', '13 ( 6.5 )', '5 ( 2.5 )', '3 ( 1.5 )', '1 ( 0.5 )', '1 ( 0.5 )'], ['career totals', 'career totals', '34', '296 ( 8.7 )', '178 ( 5.2 )', '118 ( 3.5 )', '131 ( 3.9 )', '41 ( 1.2 )', '47 ( 1.4 )', '24 ( 0.7 )']] |
1973 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1973_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245540-2.html.csv | unique | only one player in the 1973 us open came from england . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'england', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'england'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to england .', 'tostr': 'filter_eq { all_rows ; country ; england }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; england } } = true', 'tointer': 'select the rows whose country record fuzzily matches to england . there is only one such row in the table .'} | only { filter_eq { all_rows ; country ; england } } = true | select the rows whose country record fuzzily matches to england . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'country_4': 4, 'england_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'england_5': 'england'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'england_5': [0]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['jack nicklaus', 'united states', '1962 , 1967 , 1972', '282', '- 2', 't4'], ['arnold palmer', 'united states', '1960', '282', '- 2', 't4'], ['lee trevino', 'united states', '1968 , 1971', '282', '- 2', 't4'], ['julius boros', 'united states', '1952 , 1963', '283', '- 1', 't7'], ['gary player', 'south africa', '1965', '287', '+ 3', '12'], ['gene littler', 'united states', '1961', '291', '+ 7', 't18'], ['tony jacklin', 'england', '1970', '300', '+ 16', 't52']] |
oldest football competitions | https://en.wikipedia.org/wiki/Oldest_football_competitions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18050568-2.html.csv | ordinal | the first football competition that took place in launceston , tasmania had victorian rules . | {'scope': 'subset', 'row': '4', 'col': '1', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'launceston , tasmania'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'launceston , tasmania'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; launceston , tasmania }', 'tointer': 'select the rows whose location record fuzzily matches to launceston , tasmania .'}, 'years', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmin { filter_eq { all_rows ; location ; launceston , tasmania } ; years ; 1 }'}, 'original code'], 'result': 'victorian rules', 'ind': 2, 'tostr': 'hop { nth_argmin { filter_eq { all_rows ; location ; launceston , tasmania } ; years ; 1 } ; original code }'}, 'victorian rules'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmin { filter_eq { all_rows ; location ; launceston , tasmania } ; years ; 1 } ; original code } ; victorian rules } = true', 'tointer': 'select the rows whose location record fuzzily matches to launceston , tasmania . select the row whose years record of these rows is 1st minimum . the original code record of this row is victorian rules .'} | eq { hop { nth_argmin { filter_eq { all_rows ; location ; launceston , tasmania } ; years ; 1 } ; original code } ; victorian rules } = true | select the rows whose location record fuzzily matches to launceston , tasmania . select the row whose years record of these rows is 1st minimum . the original code record of this row is victorian rules . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location_6': 6, 'launceston , tasmania_7': 7, 'years_8': 8, '1_9': 9, 'original code_10': 10, 'victorian rules_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmin_1': 'nth_argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location_6': 'location', 'launceston , tasmania_7': 'launceston , tasmania', 'years_8': 'years', '1_9': '1', 'original code_10': 'original code', 'victorian rules_11': 'victorian rules'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location_6': [0], 'launceston , tasmania_7': [0], 'years_8': [1], '1_9': [1], 'original code_10': [2], 'victorian rules_11': [3]} | ['years', 'type', 'original code', 'current code', 'location'] | [['1860 -', 'interclub fixture', 'sheffield rules', 'defunct', 'sheffield , england'], ['1867 only', 'club trophy', 'sheffield rules', 'defunct', 'sheffield , england'], ['1868 only', 'club trophy', 'sheffield rules', 'defunct', 'sheffield , england'], ['1882 - 1883', 'club league', 'victorian rules', 'defunct', 'launceston , tasmania'], ['1884 - 1984', 'international challenge', 'association football', 'defunct', 'home nations ( uk )']] |
family life radio | https://en.wikipedia.org/wiki/Family_Life_Radio | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17101015-10.html.csv | unique | the k297au call sign of family life radio is the only one with an fcc info . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'fcc', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fcc info', 'fcc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fcc info record fuzzily matches to fcc .', 'tostr': 'filter_eq { all_rows ; fcc info ; fcc }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; fcc info ; fcc } }', 'tointer': 'select the rows whose fcc info record fuzzily matches to fcc . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'fcc info', 'fcc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose fcc info record fuzzily matches to fcc .', 'tostr': 'filter_eq { all_rows ; fcc info ; fcc }'}, 'call sign'], 'result': 'k297au', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; fcc info ; fcc } ; call sign }'}, 'k297au'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; fcc info ; fcc } ; call sign } ; k297au }', 'tointer': 'the call sign record of this unqiue row is k297au .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; fcc info ; fcc } } ; eq { hop { filter_eq { all_rows ; fcc info ; fcc } ; call sign } ; k297au } } = true', 'tointer': 'select the rows whose fcc info record fuzzily matches to fcc . there is only one such row in the table . the call sign record of this unqiue row is k297au .'} | and { only { filter_eq { all_rows ; fcc info ; fcc } } ; eq { hop { filter_eq { all_rows ; fcc info ; fcc } ; call sign } ; k297au } } = true | select the rows whose fcc info record fuzzily matches to fcc . there is only one such row in the table . the call sign record of this unqiue row is k297au . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'fcc info_7': 7, 'fcc_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'call sign_9': 9, 'k297au_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'fcc info_7': 'fcc info', 'fcc_8': 'fcc', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'call sign_9': 'call sign', 'k297au_10': 'k297au'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'fcc info_7': [0], 'fcc_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'call sign_9': [2], 'k297au_10': [3]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'fcc info'] | [['kamy', '90.1', 'lubbock , texas', '63000', ''], ['kflb', '88.1', 'midland , texas', '100000', ''], ['kflb', '920', 'odessa , texas', '1000 day 500 night', ''], ['krgn', '102.9', 'amarillo , texas', '100000', ''], ['k297au', '107.3', 'big spring , texas', '62', 'fcc']] |
anaprof 2006 | https://en.wikipedia.org/wiki/ANAPROF_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11442591-4.html.csv | unique | the tauro fc is the only team with a single lost ( pp ) in the 2006 season of anaprof . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lost ( pp )', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lost ( pp ) record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; lost ( pp ) ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; lost ( pp ) ; 1 } }', 'tointer': 'select the rows whose lost ( pp ) record is equal to 1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'lost ( pp )', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose lost ( pp ) record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; lost ( pp ) ; 1 }'}, 'team ( equipo )'], 'result': 'tauro fc', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; lost ( pp ) ; 1 } ; team ( equipo ) }'}, 'tauro fc'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; lost ( pp ) ; 1 } ; team ( equipo ) } ; tauro fc }', 'tointer': 'the team ( equipo ) record of this unqiue row is tauro fc .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; lost ( pp ) ; 1 } } ; eq { hop { filter_eq { all_rows ; lost ( pp ) ; 1 } ; team ( equipo ) } ; tauro fc } } = true', 'tointer': 'select the rows whose lost ( pp ) record is equal to 1 . there is only one such row in the table . the team ( equipo ) record of this unqiue row is tauro fc .'} | and { only { filter_eq { all_rows ; lost ( pp ) ; 1 } } ; eq { hop { filter_eq { all_rows ; lost ( pp ) ; 1 } ; team ( equipo ) } ; tauro fc } } = true | select the rows whose lost ( pp ) record is equal to 1 . there is only one such row in the table . the team ( equipo ) record of this unqiue row is tauro fc . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'lost (pp)_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team (equipo)_9': 9, 'tauro fc_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'lost (pp)_7': 'lost ( pp )', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team (equipo)_9': 'team ( equipo )', 'tauro fc_10': 'tauro fc'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'lost (pp)_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team (equipo)_9': [2], 'tauro fc_10': [3]} | ['place ( posición )', 'team ( equipo )', 'played ( pj )', 'won ( pg )', 'draw ( pe )', 'lost ( pp )', 'goals scored ( gf )', 'goals conceded ( gc )', '+ / - ( dif )', 'points ( pts )'] | [['1', 'tauro fc', '18', '10', '7', '1', '31', '17', '+ 14', '37'], ['2', 'san francisco fc', '18', '11', '2', '5', '40', '25', '+ 15', '35'], ['3', 'arabe unido', '18', '10', '3', '5', '30', '20', '+ 10', '33'], ['4', 'atlético veragüense', '18', '9', '6', '3', '22', '16', '+ 6', '33'], ['5', 'plaza amador', '18', '9', '4', '5', '25', '17', '+ 8', '31'], ['6', 'alianza fc', '18', '8', '2', '8', '29', '31', '- 2', '26'], ['7', 'municipal chorrillo', '18', '6', '6', '6', '24', '23', '+ 1', '24'], ['8', "sporting ' 89", '18', '4', '1', '13', '17', '31', '- 14', '13'], ['9', 'atlético chiriquí', '18', '2', '4', '12', '14', '30', '- 16', '10'], ['10', 'policia nacional', '18', '3', '1', '14', '17', '39', '- 22', '10']] |
wvtf | https://en.wikipedia.org/wiki/WVTF | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12155786-3.html.csv | ordinal | the 2nd highest frequency for wvtf was when the license was for the city of pound . | {'row': '5', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'frequency mhz', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; frequency mhz ; 2 }'}, 'city of license'], 'result': 'pound , virginia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; city of license }'}, 'pound , virginia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; city of license } ; pound , virginia } = true', 'tointer': 'select the row whose frequency mhz record of all rows is 2nd maximum . the city of license record of this row is pound , virginia .'} | eq { hop { nth_argmax { all_rows ; frequency mhz ; 2 } ; city of license } ; pound , virginia } = true | select the row whose frequency mhz record of all rows is 2nd maximum . the city of license record of this row is pound , virginia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, '2_6': 6, 'city of license_7': 7, 'pound , virginia_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', 'frequency mhz_5': 'frequency mhz', '2_6': '2', 'city of license_7': 'city of license', 'pound , virginia_8': 'pound , virginia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], '2_6': [0], 'city of license_7': [1], 'pound , virginia_8': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'fcc info'] | [['w211bf', '90.1', 'big stone gap , virginia', '8', 'fcc'], ['w212bp', '90.3', 'clintwood , virginia', '1', 'fcc'], ['w211be', '90.1', 'lebanon , virginia', '8.5', 'fcc'], ['w219cj', '91.7', 'norton , virginia', '50', 'fcc'], ['w217bf', '91.3', 'pound , virginia', '1', 'fcc'], ['w215bj', '90.9', 'saint paul , virginia', '1', 'fcc']] |
2009 open championship | https://en.wikipedia.org/wiki/2009_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811509-7.html.csv | comparative | in the 2009 open championship , mathew goggin earned 66600 more than justin leonard . | {'row_1': '6', 'row_2': '12', 'col': '6', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '66600', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'mathew goggin'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to mathew goggin .', 'tostr': 'filter_eq { all_rows ; player ; mathew goggin }'}, 'money'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; mathew goggin } ; money }', 'tointer': 'select the rows whose player record fuzzily matches to mathew goggin . take the money record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'justin leonard'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to justin leonard .', 'tostr': 'filter_eq { all_rows ; player ; justin leonard }'}, 'money'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; justin leonard } ; money }', 'tointer': 'select the rows whose player record fuzzily matches to justin leonard . take the money record of this row .'}], 'result': '66600', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; player ; mathew goggin } ; money } ; hop { filter_eq { all_rows ; player ; justin leonard } ; money } }'}, '66600'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; player ; mathew goggin } ; money } ; hop { filter_eq { all_rows ; player ; justin leonard } ; money } } ; 66600 } = true', 'tointer': 'select the rows whose player record fuzzily matches to mathew goggin . take the money record of this row . select the rows whose player record fuzzily matches to justin leonard . take the money record of this row . the first record is 66600 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; player ; mathew goggin } ; money } ; hop { filter_eq { all_rows ; player ; justin leonard } ; money } } ; 66600 } = true | select the rows whose player record fuzzily matches to mathew goggin . take the money record of this row . select the rows whose player record fuzzily matches to justin leonard . take the money record of this row . the first record is 66600 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'mathew goggin_9': 9, 'money_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'justin leonard_13': 13, 'money_14': 14, '66600_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', 'player_8': 'player', 'mathew goggin_9': 'mathew goggin', 'money_10': 'money', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player', 'justin leonard_13': 'justin leonard', 'money_14': 'money', '66600_15': '66600'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'mathew goggin_9': [0], 'money_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'justin leonard_13': [1], 'money_14': [3], '66600_15': [5]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'stewart cink', 'united states', '66 + 72 + 71 + 69 = 278', '2', 'playoff'], ['t1', 'tom watson', 'united states', '65 + 70 + 71 + 72 = 278', '2', 'playoff'], ['t3', 'lee westwood', 'england', '68 + 70 + 70 + 71 = 279', '1', '255000'], ['t3', 'chris wood', 'england', '70 + 70 + 72 + 67 = 279', '1', '255000'], ['t5', 'luke donald', 'england', '71 + 72 + 70 + 67 = 280', 'e', '157000'], ['t5', 'mathew goggin', 'australia', '66 + 72 + 69 + 73 = 280', 'e', '157000'], ['t5', 'retief goosen', 'south africa', '67 + 70 + 71 + 72 = 280', 'e', '157000'], ['t8', 'thomas aiken', 'south africa', '71 + 72 + 69 + 69 = 281', '+ 1', '90400'], ['t8', 'ernie els', 'south africa', '69 + 72 + 72 + 68 = 281', '+ 1', '90400'], ['t8', 'søren hansen', 'denmark', '68 + 72 + 74 + 67 = 281', '+ 1', '90400'], ['t8', 'richard s johnson', 'sweden', '70 + 72 + 69 + 70 = 281', '+ 1', '90400'], ['t8', 'justin leonard', 'united states', '70 + 70 + 73 + 68 = 281', '+ 1', '90400']] |
dominik meffert | https://en.wikipedia.org/wiki/Dominik_Meffert | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13141391-4.html.csv | majority | in most of the tournaments that dominik meffert participated in , the clay surface was used . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['tournament', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['freudenstadt', 'clay', 'tomas behrend', 'alexandre sidorenko mischa zverev', '7 - 5 , 7 - 6 5'], ['durban', 'hard', 'rik de voest', 'stéphane bohli noam okun', '6 - 4 , 6 - 2'], ['tanger', 'clay', 'steve darcis', 'uladzimir ignatik martin kližan', '5 - 7 , 7 - 5 ,'], ['pereira', 'clay', 'philipp oswald', 'gero kretschmer alex satschko', '6 - 7 4 , 7 - 6 6 ,'], ['curitiba', 'clay', 'leonardo tavares', 'ramón delgado andré sá', '3 - 6 , 6 - 2 ,'], ['nouméa', 'hard', 'frederik nielsen', 'flavio cipolla simone vagnozzi', '7 - 6 4 , 5 - 7 ,'], ['kyoto', 'carpet ( i )', 'simon stadler', 'andre begemann james lemke', '7 - 5 , 2 - 6 ,'], ['dortmund', 'clay', 'björn phau', 'teymuraz gabashvili andrey kuznetsov', '6 - 4 , 6 - 3'], ['tunis', 'clay', 'philipp oswald', 'jamie delgado andreas siljeström', '3 - 6 , 7 - 6 ( 7 - 0 ) ,']] |
1979 buffalo bills season | https://en.wikipedia.org/wiki/1979_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17386076-3.html.csv | superlative | on october 7th against the chicaco bears , the bills had their highest attended game of the season . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,3', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': 'october 7 , 1979', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, 'october 7 , 1979'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; october 7 , 1979 }', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is october 7 , 1979 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'chicago bears', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'chicago bears'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; opponent } ; chicago bears }', 'tointer': 'the opponent record of this row is chicago bears .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; attendance } ; date } ; october 7 , 1979 } ; eq { hop { argmax { all_rows ; attendance } ; opponent } ; chicago bears } } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is october 7 , 1979 . the opponent record of this row is chicago bears .'} | and { eq { hop { argmax { all_rows ; attendance } ; date } ; october 7 , 1979 } ; eq { hop { argmax { all_rows ; attendance } ; opponent } ; chicago bears } } = true | select the row whose attendance record of all rows is maximum . the date record of this row is october 7 , 1979 . the opponent record of this row is chicago bears . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'attendance_8': 8, 'date_9': 9, 'october 7 , 1979_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'opponent_11': 11, 'chicago bears_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'attendance_8': 'attendance', 'date_9': 'date', 'october 7 , 1979_10': 'october 7 , 1979', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'opponent_11': 'opponent', 'chicago bears_12': 'chicago bears'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'attendance_8': [0], 'date_9': [1], 'october 7 , 1979_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'opponent_11': [3], 'chicago bears_12': [4]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 2 , 1979', 'miami dolphins', 'l 9 - 7', '69441'], ['2', 'september 9 , 1979', 'cincinnati bengals', 'w 51 - 24', '43504'], ['3', 'september 16 , 1979', 'san diego chargers', 'l 27 - 19', '50709'], ['4', 'september 23 , 1979', 'new york jets', 'w 46 - 31', '68731'], ['5', 'september 30 , 1979', 'baltimore colts', 'w 31 - 13', '31904'], ['6', 'october 7 , 1979', 'chicago bears', 'l 7 - 0', '73383'], ['7', 'october 14 , 1979', 'miami dolphins', 'l 17 - 7', '45597'], ['8', 'october 21 , 1979', 'baltimore colts', 'l 14 - 13', '50581'], ['9', 'october 28 , 1979', 'detroit lions', 'w 20 - 17', '61911'], ['10', 'november 4 , 1979', 'new england patriots', 'l 26 - 6', '67935'], ['11', 'november 11 , 1979', 'new york jets', 'w 14 - 12', '50647'], ['12', 'november 18 , 1979', 'green bay packers', 'w 19 - 12', '39679'], ['13', 'november 25 , 1979', 'new england patriots', 'w 16 - 13', '60991'], ['14', 'december 2 , 1979', 'denver broncos', 'l 19 - 16', '37886'], ['15', 'december 9 , 1979', 'minnesota vikings', 'l 10 - 3', '42239'], ['16', 'december 16 , 1979', 'pittsburgh steelers', 'l 28 - 0', '48002']] |
1977 washington redskins season | https://en.wikipedia.org/wiki/1977_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15085862-2.html.csv | superlative | the buffalo bills were the opponent of the game of the '77 season of the washington redskins with the lowest attendance count . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '12', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; attendance }'}, 'opponent'], 'result': 'buffalo bills', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; attendance } ; opponent }'}, 'buffalo bills'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; attendance } ; opponent } ; buffalo bills } = true', 'tointer': 'select the row whose attendance record of all rows is minimum . the opponent record of this row is buffalo bills .'} | eq { hop { argmin { all_rows ; attendance } ; opponent } ; buffalo bills } = true | select the row whose attendance record of all rows is minimum . the opponent record of this row is buffalo bills . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'buffalo bills_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'buffalo bills_7': 'buffalo bills'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'buffalo bills_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 18 , 1977', 'new york giants', 'l 20 - 17', '76086'], ['2', 'september 25 , 1977', 'atlanta falcons', 'w 10 - 6', '55031'], ['3', 'october 2 , 1977', 'st louis cardinals', 'w 24 - 14', '55031'], ['4', 'october 9 , 1977', 'tampa bay buccaneers', 'w 10 - 0', '58571'], ['5', 'october 16 , 1977', 'dallas cowboys', 'l 34 - 16', '62115'], ['6', 'october 23 , 1977', 'new york giants', 'l 17 - 6', '53903'], ['7', 'october 30 , 1977', 'philadelphia eagles', 'w 23 - 17', '55031'], ['8', 'november 7 , 1977', 'baltimore colts', 'l 10 - 3', '57740'], ['9', 'november 13 , 1977', 'philadelphia eagles', 'w 17 - 14', '60702'], ['10', 'november 21 , 1977', 'green bay packers', 'w 10 - 9', '51498'], ['11', 'november 27 , 1977', 'dallas cowboys', 'l 14 - 7', '55031'], ['12', 'december 4 , 1977', 'buffalo bills', 'w 10 - 0', '22975'], ['13', 'december 10 , 1977', 'st louis cardinals', 'w 26 - 20', '36067'], ['14', 'december 17 , 1977', 'los angeles rams', 'w 17 - 14', '54208']] |
vc zenit - kazan | https://en.wikipedia.org/wiki/VC_Zenit-Kazan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14363116-1.html.csv | unique | matthew anderson is the only player on the vc zenit - kazan team from the united states . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': '3', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; nationality ; united states }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; united states } }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; nationality ; united states }'}, 'player'], 'result': 'matthew anderson', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; united states } ; player }'}, 'matthew anderson'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; united states } ; player } ; matthew anderson }', 'tointer': 'the player record of this unqiue row is matthew anderson .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; united states } } ; eq { hop { filter_eq { all_rows ; nationality ; united states } ; player } ; matthew anderson } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . there is only one such row in the table . the player record of this unqiue row is matthew anderson .'} | and { only { filter_eq { all_rows ; nationality ; united states } } ; eq { hop { filter_eq { all_rows ; nationality ; united states } ; player } ; matthew anderson } } = true | select the rows whose nationality record fuzzily matches to united states . there is only one such row in the table . the player record of this unqiue row is matthew anderson . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'united states_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'matthew anderson_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'united states_8': 'united states', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'matthew anderson_10': 'matthew anderson'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'united states_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'matthew anderson_10': [3]} | ['shirt no', 'nationality', 'player', 'birth date', 'height', 'position'] | [['1', 'united states', 'matthew anderson', 'april 18 , 1987 ( age26 )', '204', 'outside hitter'], ['3', 'russia', 'nikolay apalikov', 'august 26 , 1982 ( age31 )', '203', 'middle blocker'], ['4', 'russia', 'ivan demakov', 'june 1 , 1993 ( age20 )', '209', 'middle blocker'], ['5', 'italy', 'valerio vermiglio', 'march 1 , 1976 ( age37 )', '189', 'setter'], ['6', 'russia', 'eugeniy sivozhelez', 'june 8 , 1986 ( age27 )', '196', 'outside hitter'], ['7', 'russia', 'aleksandr volkov', 'february 14 , 1985 ( age28 )', '210', 'middle blocker'], ['8', 'russia', 'igor kolodinsky', 'july 7 , 1983 ( age30 )', '197', 'setter'], ['9', 'russia', 'alexey cheremisin', 'september 23 , 1980 ( age33 )', '204', 'opposite hitter'], ['10', 'russia', 'yury berezhko', 'january 27 , 1981 ( age33 )', '198', 'outside hitter'], ['13', 'russia', 'vitaliy matychenko', 'august 4 , 1983 ( age30 )', '194', 'setter'], ['14', 'russia', 'alexander abrosimov', 'august 25 , 1983 ( age30 )', '207', 'middle blocker'], ['15', 'russia', 'alexey obmochaev', 'may 22 , 1989 ( age24 )', '188', 'libero'], ['17', 'russia', 'vladislav babichev', 'february 18 , 1981 ( age32 )', '185', 'libero']] |
1994 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1994_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17162228-2.html.csv | count | 7 players participated in the 1994 u.s. open ( golf ) . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '7', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 7 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 7 .'} | eq { count { filter_all { all_rows ; player } } ; 7 } = true | select the rows whose player record is arbitrary . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '7_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '7_6': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '7_6': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish'] | [['curtis strange', 'united states', '1988 , 1989', '280', '- 4', '4'], ['tom watson', 'united states', '1982', '283', '- 1', 't6'], ['hale irwin', 'united states', '1974 , 1979 , 1990', '287', '+ 3', 't18'], ['jack nicklaus', 'united states', '1962 , 1967 , 1972 , 1980', '292', '+ 8', 't28'], ['tom kite', 'united states', '1992', '293', '+ 9', 't33'], ['scott simpson', 'united states', '1987', '298', '+ 14', 't55'], ['fuzzy zoeller', 'united states', '1984', '299', '+ 15', 't58']] |
kim hyun - joong | https://en.wikipedia.org/wiki/Kim_Hyun-joong | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18629727-2.html.csv | count | kim hyun-joong has appeared in only 2 sitcoms . | {'scope': 'all', 'criterion': 'equal', 'value': 'sitcom', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'genre', 'sitcom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose genre record fuzzily matches to sitcom .', 'tostr': 'filter_eq { all_rows ; genre ; sitcom }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; genre ; sitcom } }', 'tointer': 'select the rows whose genre record fuzzily matches to sitcom . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; genre ; sitcom } } ; 2 } = true', 'tointer': 'select the rows whose genre record fuzzily matches to sitcom . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; genre ; sitcom } } ; 2 } = true | select the rows whose genre record fuzzily matches to sitcom . 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, 'genre_5': 5, 'sitcom_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', 'genre_5': 'genre', 'sitcom_6': 'sitcom', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'genre_5': [0], 'sitcom_6': [0], '2_7': [2]} | ['year', 'title', 'hangul / japanese', 'role', 'network', 'genre'] | [['2005', 'nonstop 5', '논스톱 5', 'guest ep208', 'mbc', 'sitcom'], ['2005', 'can love be refilled', '사랑도 리필이 되나요', 'william', 'kbs2', 'sitcom'], ['2007', 'hotelier', 'ホテリアー', 'cameo ep7 ( with ss501 )', 'tv asahi', 'drama'], ['2008', 'spotlight', '스포트라이트', 'cameo ( with ss501 )', 'mbc', 'drama'], ['2009', 'boys over flowers', '꽃보다 남자', 'yoon ji - hoo', 'kbs2', 'drama'], ['2010', 'playful kiss', '장난스런 키스', 'baek seung - jo', 'mbc', 'drama'], ['2011', 'dream high', '드림하이', 'cameo ep1', 'kbs2', 'drama'], ['2014', 'age of feeling', '감격시대', 'shin jung - tae', 'kbs2', 'drama']] |
1930 british empire games | https://en.wikipedia.org/wiki/1930_British_Empire_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-177520-1.html.csv | majority | all of the ranks at the 1930 british empire games had at east one silver medal . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '1', 'subset': None} | {'func': 'all_greater_eq', 'args': ['all_rows', 'silver', '1'], 'result': True, 'ind': 0, 'tointer': 'for the silver records of all rows , all of them are greater than or equal to 1 .', 'tostr': 'all_greater_eq { all_rows ; silver ; 1 } = true'} | all_greater_eq { all_rows ; silver ; 1 } = true | for the silver records of all rows , all of them are greater than or equal to 1 . | 1 | 1 | {'all_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'silver_3': 3, '1_4': 4} | {'all_greater_eq_0': 'all_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'silver_3': 'silver', '1_4': '1'} | {'all_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'silver_3': [0], '1_4': [0]} | ['rank', 'gold', 'silver', 'bronze', 'total'] | [['1', '25', '22', '13', '60'], ['2', '20', '16', '18', '54'], ['3', '6', '4', '8', '18'], ['4', '3', '4', '2', '9'], ['5', '3', '4', '1', '8'], ['6', '2', '3', '5', '10'], ['7', '0', '2', '1', '3'], ['8', '0', '1', '1', '2'], ['9', '0', '1', '0', '1'], ['total', '59', '57', '49', '165']] |
jimmy davies | https://en.wikipedia.org/wiki/Jimmy_Davies | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236195-3.html.csv | majority | jimmy davies drove a majority of years with the offenhauser l4 engine . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'offenhauser l4', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'engine', 'offenhauser l4'], 'result': True, 'ind': 0, 'tointer': 'for the engine records of all rows , most of them fuzzily match to offenhauser l4 .', 'tostr': 'most_eq { all_rows ; engine ; offenhauser l4 } = true'} | most_eq { all_rows ; engine ; offenhauser l4 } = true | for the engine records of all rows , most of them fuzzily match to offenhauser l4 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'engine_3': 3, 'offenhauser l4_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'engine_3': 'engine', 'offenhauser l4_4': 'offenhauser l4'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'engine_3': [0], 'offenhauser l4_4': [0]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1950', 'pat clancy', 'ewing', 'offenhauser l4', '0'], ['1951', 'parks offenhauser / le parks', 'pawl', 'offenhauser l4', '0'], ['1953', 'pat clancy', 'kurtis kraft 500b', 'offenhauser l4', '0'], ['1954', 'bardahl / ed walsh', 'kurtis kraft 4000', 'offenhauser l4', '0'], ['1955', 'bardahl / pat clancy', 'kurtis kraft 500b', 'offenhauser l4', '4'], ['1956', 'novi racing', 'kurtis kraft 500f', 'novi v8', '0'], ['1957', 'trio brdeact wind allass', 'kurtis kraft 500d', 'offenhauser l4', '0'], ['1959', 'sumar / chapman root', 'kurtis kraft 500 g', 'offenhauser l4', '0']] |
lexington legends | https://en.wikipedia.org/wiki/Lexington_Legends | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1031852-2.html.csv | unique | the 2013 season was the only year where kansas city was the mlb affiliate for the lexington legends . | {'scope': 'all', 'row': '13', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': 'kansas city', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mlb affiliate', 'kansas city'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mlb affiliate record fuzzily matches to kansas city .', 'tostr': 'filter_eq { all_rows ; mlb affiliate ; kansas city }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; mlb affiliate ; kansas city } }', 'tointer': 'select the rows whose mlb affiliate record fuzzily matches to kansas city . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'mlb affiliate', 'kansas city'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose mlb affiliate record fuzzily matches to kansas city .', 'tostr': 'filter_eq { all_rows ; mlb affiliate ; kansas city }'}, 'season'], 'result': '2013', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; mlb affiliate ; kansas city } ; season }'}, '2013'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; mlb affiliate ; kansas city } ; season } ; 2013 }', 'tointer': 'the season record of this unqiue row is 2013 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; mlb affiliate ; kansas city } } ; eq { hop { filter_eq { all_rows ; mlb affiliate ; kansas city } ; season } ; 2013 } } = true', 'tointer': 'select the rows whose mlb affiliate record fuzzily matches to kansas city . there is only one such row in the table . the season record of this unqiue row is 2013 .'} | and { only { filter_eq { all_rows ; mlb affiliate ; kansas city } } ; eq { hop { filter_eq { all_rows ; mlb affiliate ; kansas city } ; season } ; 2013 } } = true | select the rows whose mlb affiliate record fuzzily matches to kansas city . there is only one such row in the table . the season record of this unqiue row is 2013 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'mlb affiliate_7': 7, 'kansas city_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '2013_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'mlb affiliate_7': 'mlb affiliate', 'kansas city_8': 'kansas city', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '2013_10': '2013'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'mlb affiliate_7': [0], 'kansas city_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '2013_10': [3]} | ['season', 'manager', 'record', 'win %', 'post - season record', 'post - season win %', 'mlb affiliate'] | [['2001', 'joe cannon', '92 - 48', '657', '4 - 0', '1.000', 'houston'], ['2002', 'joe cannon', '81 - 59', '579', '-', '-', 'houston'], ['2003 ♦', 'russ nixon', '75 - 63', '543', '0 - 2', '000', 'houston'], ['2004', 'iván dejesús', '68 - 72', '486', '-', '-', 'houston'], ['2005', 'tim bogar', '81 - 58', '583', '-', '-', 'houston'], ['2006 ♦', 'jack lind', '75 - 63', '543', '0 - 2', '000', 'houston'], ['2007', 'gregg langbehn', '59 - 81', '421', '-', '-', 'houston'], ['2008', 'gregg langbehn', '45 - 93', '326', '-', '-', 'houston'], ['2009', 'tom lawless', '68 - 72', '486', '-', '-', 'houston'], ['2010', 'rodney linares', '71 - 68', '511', '-', '-', 'houston'], ['2011', 'rodney linares', '59 - 79', '428', '-', '-', 'houston'], ['2012', 'iván dejesús', '69 - 69', '500', '-', '-', 'houston'], ['2013', 'brian buchanan', '44 - 42', '512', '-', '-', 'kansas city']] |
clear lake ( oregon ) | https://en.wikipedia.org/wiki/Clear_Lake_%28Oregon%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12484336-1.html.csv | majority | the majority of clear lake bodies of water in oregon are of the lake type . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'lake', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'type', 'lake'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , most of them fuzzily match to lake .', 'tostr': 'most_eq { all_rows ; type ; lake } = true'} | most_eq { all_rows ; type ; lake } = true | for the type records of all rows , most of them fuzzily match to lake . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'lake_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'lake_4': 'lake'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'lake_4': [0]} | ['name', 'type', 'elevation', 'usgs map', 'gnis id'] | [['clear lake ( douglas county , oregon )', 'lake', 'feet ( m )', 'winchester bay', '1139800'], ['clear lake ( wasco county , oregon )', 'reservoir', 'feet ( m )', 'wapinitia pass', '1139803'], ['clear lake ( amazon creek , oregon )', 'lake', 'feet ( m )', 'eugene west', '1119000'], ['clear lake ( marion county , oregon )', 'lake', 'feet ( m )', 'mission bottom', '1119001'], ['clear lake ( tillamook county , oregon )', 'lake', 'feet ( m )', 'garibaldi', '1119002'], ['clear lake ( clatsop county , oregon )', 'lake', 'feet ( m )', 'warrenton', '1119003'], ['clear lake , oregon', 'populated place', 'feet ( m )', 'mission bottom', '1119004'], ['clear lake ( florence , lane county , oregon )', 'lake', 'feet ( m )', 'mercer lake', '1139801'], ['clear lake ( clackamas county , oregon )', 'lake', 'feet ( m )', 'elwood', '1139802'], ['clear lake ( wallowa county , oregon )', 'lake', 'feet ( m )', 'clear lake ridge', '1139804'], ['clear lake ( linn county , oregon )', 'lake', 'feet ( m )', 'clear lake', '1139805'], ['clear lake ( coos county , oregon )', 'lake', 'feet ( m )', 'lakeside', '1154640'], ['malabon , oregon', 'historic locale', 'feet ( m )', 'eugene west', '1166549']] |
list of tallest buildings in kansas city , missouri | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Kansas_City%2C_Missouri | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12815540-4.html.csv | comparative | the historic federal reserve bank has less floors than the kansas city power and light building . | {'row_1': '3', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'historic federal reserve bank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to historic federal reserve bank .', 'tostr': 'filter_eq { all_rows ; name ; historic federal reserve bank }'}, 'floors'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors }', 'tointer': 'select the rows whose name record fuzzily matches to historic federal reserve bank . take the floors record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'kansas city power and light building'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to kansas city power and light building .', 'tostr': 'filter_eq { all_rows ; name ; kansas city power and light building }'}, 'floors'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors }', 'tointer': 'select the rows whose name record fuzzily matches to kansas city power and light building . take the floors record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors } }', 'tointer': 'select the rows whose name record fuzzily matches to historic federal reserve bank . take the floors record of this row . select the rows whose name record fuzzily matches to kansas city power and light building . take the floors record of this row . the first record is less than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'historic federal reserve bank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to historic federal reserve bank .', 'tostr': 'filter_eq { all_rows ; name ; historic federal reserve bank }'}, 'floors'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors }', 'tointer': 'select the rows whose name record fuzzily matches to historic federal reserve bank . take the floors record of this row .'}, '16'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; 16 }', 'tointer': 'the floors record of the first row is 16 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'kansas city power and light building'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to kansas city power and light building .', 'tostr': 'filter_eq { all_rows ; name ; kansas city power and light building }'}, 'floors'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors }', 'tointer': 'select the rows whose name record fuzzily matches to kansas city power and light building . take the floors record of this row .'}, '34'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors } ; 34 }', 'tointer': 'the floors record of the second row is 34 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; 16 } ; eq { hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors } ; 34 } }', 'tointer': 'the floors record of the first row is 16 . the floors record of the second row is 34 .'}], 'result': True, 'ind': 8, 'tostr': 'and { less { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors } } ; and { eq { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; 16 } ; eq { hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors } ; 34 } } } = true', 'tointer': 'select the rows whose name record fuzzily matches to historic federal reserve bank . take the floors record of this row . select the rows whose name record fuzzily matches to kansas city power and light building . take the floors record of this row . the first record is less than the second record . the floors record of the first row is 16 . the floors record of the second row is 34 .'} | and { less { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors } } ; and { eq { hop { filter_eq { all_rows ; name ; historic federal reserve bank } ; floors } ; 16 } ; eq { hop { filter_eq { all_rows ; name ; kansas city power and light building } ; floors } ; 34 } } } = true | select the rows whose name record fuzzily matches to historic federal reserve bank . take the floors record of this row . select the rows whose name record fuzzily matches to kansas city power and light building . take the floors record of this row . the first record is less than the second record . the floors record of the first row is 16 . the floors record of the second row is 34 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'less_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'name_11': 11, 'historic federal reserve bank_12': 12, 'floors_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'name_15': 15, 'kansas city power and light building_16': 16, 'floors_17': 17, 'and_7': 7, 'eq_5': 5, '16_18': 18, 'eq_6': 6, '34_19': 19} | {'and_8': 'and', 'result_9': 'true', 'less_4': 'less', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'historic federal reserve bank_12': 'historic federal reserve bank', 'floors_13': 'floors', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'name_15': 'name', 'kansas city power and light building_16': 'kansas city power and light building', 'floors_17': 'floors', 'and_7': 'and', 'eq_5': 'eq', '16_18': '16', 'eq_6': 'eq', '34_19': '34'} | {'and_8': [9], 'result_9': [], 'less_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'name_11': [0], 'historic federal reserve bank_12': [0], 'floors_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'name_15': [1], 'kansas city power and light building_16': [1], 'floors_17': [3], 'and_7': [8], 'eq_5': [7], '16_18': [5], 'eq_6': [7], '34_19': [6]} | ['name', 'street address', 'years as tallest', 'height feet / m', 'floors'] | [['new york life insurance building', '20 w ninth street', '1890 - 1906', '180 / 55', '12'], ['commerce trust building', '922 walnut street', '1906 - 1921', '258 / 79', '17'], ['historic federal reserve bank', '925 grand avenue', '1921 - 1929', '298 / 91', '16'], ['oak tower', '324 e 11th street', '1929 - 1931', '379 / 116', '28'], ['kansas city power and light building', '1330 baltimore street', '1931 - 1977', '476 / 145', '34'], ['2345 grand ( formerly ibm plaza )', '2345 grand avenue', '1977 - 1980', '477 / 145', '28'], ['sheraton kansas city hotel at crown center', '2345 mcgee street', '1980 - 1986', '504 / 154', '40'], ['town pavilion', '1111 main street', '1986 - 1988', '591 / 180', '38'], ['one kansas city place', '1200 main street', '1988 - present', '624 / 198', '42']] |
new york film critics circle award for best foreign language film | https://en.wikipedia.org/wiki/New_York_Film_Critics_Circle_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12788276-5.html.csv | comparative | bad education won an award after city of god did . | {'row_1': '5', 'row_2': '4', 'col': '1', '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', 'english title', 'bad education'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose english title record fuzzily matches to bad education .', 'tostr': 'filter_eq { all_rows ; english title ; bad education }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; english title ; bad education } ; year }', 'tointer': 'select the rows whose english title record fuzzily matches to bad education . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'english title', 'city of god'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose english title record fuzzily matches to city of god .', 'tostr': 'filter_eq { all_rows ; english title ; city of god }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; english title ; city of god } ; year }', 'tointer': 'select the rows whose english title record fuzzily matches to city of god . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; english title ; bad education } ; year } ; hop { filter_eq { all_rows ; english title ; city of god } ; year } } = true', 'tointer': 'select the rows whose english title record fuzzily matches to bad education . take the year record of this row . select the rows whose english title record fuzzily matches to city of god . take the year record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; english title ; bad education } ; year } ; hop { filter_eq { all_rows ; english title ; city of god } ; year } } = true | select the rows whose english title record fuzzily matches to bad education . take the year record of this row . select the rows whose english title record fuzzily matches to city of god . take the year 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, 'english title_7': 7, 'bad education_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'english title_11': 11, 'city of god_12': 12, 'year_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', 'english title_7': 'english title', 'bad education_8': 'bad education', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'english title_11': 'english title', 'city of god_12': 'city of god', 'year_13': 'year'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'english title_7': [0], 'bad education_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'english title_11': [1], 'city of god_12': [1], 'year_13': [3]} | ['year', 'english title', 'original title', 'country', 'director ( s )'] | [['2000', 'yi yi : a one and a two', 'yi yi', 'japan / taiwan', 'edward yang'], ['2001', 'in the mood for love', 'fa yeung nin wa', 'france / hong kong', 'wong kar - wai'], ['2002', 'and your mother too', 'y tu mamá también', 'mexico', 'alfonso cuarón'], ['2003', 'city of god', 'cidade de deus', 'brazil', 'fernando meirelles'], ['2004', 'bad education', 'la mala educación', 'spain', 'pedro almodóvar'], ['2005', '2046', '2046', 'china / hong kong', 'wong kar - wai'], ['2006', 'army of shadows', "l'armée des ombres", 'france / italy', 'jean - pierre melville'], ['2007', 'the lives of others', 'das leben der anderen', 'germany', 'florian henckel von donnersmarck'], ['2008', '4 months , 3 weeks and 2 days', '4 luni , 3 săptămni şi 2 zile', 'romania', 'cristian mungiu'], ['2009', 'summer hours', "l'heure de été", 'france', 'olivier assayas']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-37.html.csv | unique | ernest istook was the only representative who retired that year . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'retired', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'results', 'retired'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose results record fuzzily matches to retired .', 'tostr': 'filter_eq { all_rows ; results ; retired }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; results ; retired } }', 'tointer': 'select the rows whose results record fuzzily matches to retired . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'results', 'retired'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose results record fuzzily matches to retired .', 'tostr': 'filter_eq { all_rows ; results ; retired }'}, 'incumbent'], 'result': 'ernest istook', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; results ; retired } ; incumbent }'}, 'ernest istook'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; results ; retired } ; incumbent } ; ernest istook }', 'tointer': 'the incumbent record of this unqiue row is ernest istook .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; results ; retired } } ; eq { hop { filter_eq { all_rows ; results ; retired } ; incumbent } ; ernest istook } } = true', 'tointer': 'select the rows whose results record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is ernest istook .'} | and { only { filter_eq { all_rows ; results ; retired } } ; eq { hop { filter_eq { all_rows ; results ; retired } ; incumbent } ; ernest istook } } = true | select the rows whose results record fuzzily matches to retired . there is only one such row in the table . the incumbent record of this unqiue row is ernest istook . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'results_7': 7, 'retired_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'ernest istook_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'results_7': 'results', 'retired_8': 'retired', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'ernest istook_10': 'ernest istook'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'results_7': [0], 'retired_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'ernest istook_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['oklahoma 1', 'john sullivan', 'republican', '2002', 're - elected'], ['oklahoma 2', 'dan boren', 'democratic', '2004', 're - elected'], ['oklahoma 3', 'frank lucas', 'republican', '1994', 're - elected'], ['oklahoma 4', 'tom cole', 'republican', '2002', 're - elected'], ['oklahoma 5', 'ernest istook', 'republican', '1992', 'retired to run for governor republican hold']] |
sparc enterprise | https://en.wikipedia.org/wiki/SPARC_Enterprise | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10818465-1.html.csv | count | in sparc enterprise , 2 of the ones with max memory 128 gb its max processors is 1 ultrasparc t2 . | {'scope': 'subset', 'criterion': 'equal', 'value': '1 ultrasparc t2', 'result': '2', 'col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': '128 gb'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'max memory', '128 gb'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; max memory ; 128 gb }', 'tointer': 'select the rows whose max memory record fuzzily matches to 128 gb .'}, 'max processors', '1 ultrasparc t2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose max memory record fuzzily matches to 128 gb . among these rows , select the rows whose max processors record fuzzily matches to 1 ultrasparc t2 .', 'tostr': 'filter_eq { filter_eq { all_rows ; max memory ; 128 gb } ; max processors ; 1 ultrasparc t2 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; max memory ; 128 gb } ; max processors ; 1 ultrasparc t2 } }', 'tointer': 'select the rows whose max memory record fuzzily matches to 128 gb . among these rows , select the rows whose max processors record fuzzily matches to 1 ultrasparc t2 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; max memory ; 128 gb } ; max processors ; 1 ultrasparc t2 } } ; 2 } = true', 'tointer': 'select the rows whose max memory record fuzzily matches to 128 gb . among these rows , select the rows whose max processors record fuzzily matches to 1 ultrasparc t2 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; max memory ; 128 gb } ; max processors ; 1 ultrasparc t2 } } ; 2 } = true | select the rows whose max memory record fuzzily matches to 128 gb . among these rows , select the rows whose max processors record fuzzily matches to 1 ultrasparc t2 . 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, 'max memory_6': 6, '128 gb_7': 7, 'max processors_8': 8, '1 ultrasparc t2_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', 'max memory_6': 'max memory', '128 gb_7': '128 gb', 'max processors_8': 'max processors', '1 ultrasparc t2_9': '1 ultrasparc t2', '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], 'max memory_6': [0], '128 gb_7': [0], 'max processors_8': [1], '1 ultrasparc t2_9': [1], '2_10': [3]} | ['model', 'ru', 'max processors', 'processor frequency', 'max memory', 'max disk capacity', 'ga date'] | [['m3000', '2', '1 sparc64 vii or vii +', '2.52 , 2.75 ghz ( vii ) or 2.86 ghz ( vii + )', '64 gb', '4 2.5 sas', 'october 2008 ( vii ) , april 2011 ( vii + )'], ['t1000', '1', '1 ultrasparc t1', '1.0 ghz', '32 gb', 'one 3.5 sata or two 2.5 sas', 'march 2006'], ['t2000', '2', '1 ultrasparc t1', '1.0 , 1.2 , 1.4 ghz', '64 gb', 'up to four 2.5 sas', 'december 2005'], ['t5120', '1', '1 ultrasparc t2', '1.2 , 1.4 ghz', '128 gb', 'up to eight 2.5 sas', 'november 2007'], ['t5140', '1', '2 ultrasparc t2 +', '1.2 , 1.4 ghz', '128 gb', 'up to eight 2.5 sas', 'april 2008'], ['t5220', '2', '1 ultrasparc t2', '1.2 , 1.4 ghz', '128 gb', 'up to sixteen 2.5 sas', 'november 2007'], ['t5240', '2', '2 ultrasparc t2 +', '1.2 , 1.4 ghz', '256 gb', 'up to sixteen 2.5 sas', 'april 2008']] |
2007 kansas lottery indy 300 | https://en.wikipedia.org/wiki/2007_Kansas_Lottery_Indy_300 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17693171-1.html.csv | ordinal | driver dan wheldon had the highest number of points in the 2007 kansas lottery indy 300 . | {'row': '1', 'col': '9', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 1 }'}, 'driver'], 'result': 'dan wheldon', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 1 } ; driver }'}, 'dan wheldon'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points ; 1 } ; driver } ; dan wheldon } = true', 'tointer': 'select the row whose points record of all rows is 1st maximum . the driver record of this row is dan wheldon .'} | eq { hop { nth_argmax { all_rows ; points ; 1 } ; driver } ; dan wheldon } = true | select the row whose points record of all rows is 1st maximum . the driver record of this row is dan wheldon . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '1_6': 6, 'driver_7': 7, 'dan wheldon_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', '1_6': '1', 'driver_7': 'driver', 'dan wheldon_8': 'dan wheldon'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '1_6': [0], 'driver_7': [1], 'dan wheldon_8': [2]} | ['fin pos', 'car no', 'driver', 'team', 'laps', 'time / retired', 'grid', 'laps led', 'points'] | [['1', '10', 'dan wheldon', 'target chip ganassi', '200', '1:36:56.0586', '4', '177', '50 + 3'], ['2', '27', 'dario franchitti', 'andretti green', '200', '+ 18.4830', '6', '0', '40'], ['3', '3', 'hãlio castroneves', 'team penske', '200', '+ 33.2280', '3', '0', '35'], ['4', '9', 'scott dixon', 'target chip ganassi', '200', '+ 34.4208', '5', '16', '32'], ['5', '2', 'tomas scheckter', 'vision racing', '199', '+ 1 lap', '7', '0', '30'], ['6', '6', 'sam hornish , jr', 'team penske', '199', '+ 1 lap', '2', '0', '28'], ['7', '7', 'danica patrick', 'andretti green', '198', '+ 2 laps', '10', '0', '26'], ['8', '4', 'vitor meira', 'panther racing', '198', '+ 2 laps', '8', '0', '24'], ['9', '22', 'a j foyt iv', 'vision racing', '198', '+ 2 laps', '15', '0', '22'], ['10', '17', 'jeff simmons', 'rahal letterman', '198', '+ 2 laps', '16', '0', '20'], ['11', '14', 'darren manning', 'aj foyt racing', '198', '+ 2 laps', '11', '0', '19'], ['12', '5', 'sarah fisher', 'dreyer & reinbold racing', '196', '+ 4 laps', '17', '0', '18'], ['13', '8', 'scott sharp', 'rahal letterman', '195', 'accident', '14', '0', '17'], ['14', '23', 'milka duno', 'samax motorsport', '194', '+ 6 laps', '21', '0', '16'], ['15', '11', 'tony kanaan', 'andretti green racing', '192', '+ 8 laps', '1', '7', '15'], ['16', '98', 'alex barron', 'curb / agajanian / beck', '191', '+ 9 laps', '20', '0', '14'], ['17', '20', 'ed carpenter', 'vision racing', '99', 'accident', '13', '0', '13'], ['18', '55', 'kosuke matsuura', 'super aguri panther racing', '57', 'mechanical', '12', '0', '12'], ['19', '26', 'marco andretti', 'andretti green racing', '43', 'mechanical', '9', '0', '12'], ['20', '15', 'buddy rice', 'dreyer & reinbold racing', '37', 'mechanical', '18', '0', '12']] |
2000 san diego chargers season | https://en.wikipedia.org/wiki/2000_San_Diego_Chargers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15331726-1.html.csv | aggregation | in the 2000 san diego chargers season the total attendance at the two games with the oakland raiders was 123,032 . | {'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '123032', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'oakland raiders'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'oakland raiders'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; oakland raiders }', 'tointer': 'select the rows whose opponent record fuzzily matches to oakland raiders .'}, 'attendance'], 'result': '123032', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; opponent ; oakland raiders } ; attendance }'}, '123032'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; opponent ; oakland raiders } ; attendance } ; 123032 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to oakland raiders . the sum of the attendance record of these rows is 123032 .'} | round_eq { sum { filter_eq { all_rows ; opponent ; oakland raiders } ; attendance } ; 123032 } = true | select the rows whose opponent record fuzzily matches to oakland raiders . the sum of the attendance record of these rows is 123032 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'opponent_5': 5, 'oakland raiders_6': 6, 'attendance_7': 7, '123032_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'opponent_5': 'opponent', 'oakland raiders_6': 'oakland raiders', 'attendance_7': 'attendance', '123032_8': '123032'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'oakland raiders_6': [0], 'attendance_7': [1], '123032_8': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 3 , 2000', 'oakland raiders', 'l 6 - 9', 'network associates coliseum', '0 - 1', '56373'], ['2', 'september 10 , 2000', 'new orleans saints', 'l 27 - 28', 'qualcomm stadium', '0 - 2', '51300'], ['3', 'september 17 , 2000', 'kansas city chiefs', 'l 10 - 42', 'arrowhead stadium', '0 - 3', '77604'], ['4', 'september 24 , 2000', 'seattle seahawks', 'l 12 - 20', 'qualcomm stadium', '0 - 4', '47233'], ['5', 'october 1 , 2000', 'st louis rams', 'l 31 - 57', 'trans world dome', '0 - 5', '66010'], ['6', 'october 8 , 2000', 'denver broncos', 'l 7 - 21', 'qualcomm stadium', '0 - 6', '56079'], ['7', 'october 15 , 2000', 'buffalo bills', 'l 24 - 27', 'ralph wilson stadium', '0 - 7', '72351'], ['8', 'october 22 , 2000', '-', '-', '-', '-', ''], ['9', 'october 29 , 2000', 'oakland raiders', 'l 13 - 15', 'qualcomm stadium', '0 - 8', '66659'], ['10', 'november 5 , 2000', 'seattle seahawks', 'l 15 - 17', 'husky stadium', '0 - 9', '59884'], ['11', 'november 12 , 2000', 'miami dolphins', 'l 7 - 17', 'qualcomm stadium', '0 - 10', '56896'], ['12', 'november 19 , 2000', 'denver broncos', 'l 37 - 38', 'mile high stadium', '0 - 11', '75218'], ['13', 'november 26 , 2000', 'kansas city chiefs', 'w 17 - 16', 'qualcomm stadium', '1 - 11', '47228'], ['14', 'december 3 , 2000', 'san francisco 49ers', 'l 17 - 45', 'qualcomm stadium', '1 - 12', '57255'], ['15', 'december 10 , 2000', 'baltimore ravens', 'l 3 - 24', 'psinet stadium', '1 - 13', '68805'], ['16', 'december 17 , 2000', 'carolina panthers', 'l 22 - 30', 'ericsson stadium', '1 - 14', '72159'], ['17', 'december 24 , 2000', 'pittsburgh steelers', 'l 21 - 34', 'qualcomm stadium', '1 - 15', '50809']] |
records of members of parliament of the united kingdom | https://en.wikipedia.org/wiki/Records_of_members_of_parliament_of_the_United_Kingdom | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11921877-1.html.csv | majority | the majority of members of parliament of the united kingdom belong to the labour party . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'labour party', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'political party', 'labour party'], 'result': True, 'ind': 0, 'tointer': 'for the political party records of all rows , most of them fuzzily match to labour party .', 'tostr': 'most_eq { all_rows ; political party ; labour party } = true'} | most_eq { all_rows ; political party ; labour party } = true | for the political party records of all rows , most of them fuzzily match to labour party . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'political party_3': 3, 'labour party_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'political party_3': 'political party', 'labour party_4': 'labour party'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'political party_3': [0], 'labour party_4': [0]} | ['born', 'became oldest mp', 'left house', 'age on leaving', 'died', 'political party'] | [['6 may 1866', '1945', '1950', '83 2', '24 april 1957', 'liberal party'], ['22 november 1871', '1950', 'feb 1964', '92 1', '25 february 1964', 'labour party'], ['30 november 1874', 'feb 1964', 'sep 1964', '89 2', '24 january 1965', 'conservative'], ['18 october 1884', 'sep 1964', '1970', '85 2', '8 may 1986', 'labour party'], ['probably 9 november 1879', '1970', '1972', '92 1', '25 february 1972', 'labour party'], ['1 february 1890', '1972', '1973', '83 1', '8 october 1973', 'labour party'], ['23 february 1895', '1973', 'feb 1974', '79 2', '26 april 1980', 'conservative'], ['18 june 1898', 'feb 1974', '1979', '80 2', '6 may 1987', 'labour party'], ['16 january 1905', '1979', '1987', '82 2', '4 june 1990', 'labour party'], ['23 july 1913', '1987', '1992', '78 2', '3 march 2010', 'labour party'], ['9 july 1916', '1992', '2001', '84 2', '17 july 2005', 'conservative'], ['20 november 1921', '2001', '2007', '85 1', '21 june 2007', 'labour party'], ['6 april 1926', '2007', '2010', '84 2', 'living', 'democratic unionist party'], ['1 february 1930', '2010', 'n / a', 'n / a', 'living', 'conservative']] |
joão barbosa | https://en.wikipedia.org/wiki/Jo%C3%A3o_Barbosa | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18864385-1.html.csv | unique | 2004 was the only year that that joão barbosa had a dnf position . | {'scope': 'all', 'row': '1', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': 'dnf', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', 'dnf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record fuzzily matches to dnf .', 'tostr': 'filter_eq { all_rows ; pos ; dnf }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; pos ; dnf } }', 'tointer': 'select the rows whose pos record fuzzily matches to dnf . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', 'dnf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record fuzzily matches to dnf .', 'tostr': 'filter_eq { all_rows ; pos ; dnf }'}, 'year'], 'result': '2004', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; pos ; dnf } ; year }'}, '2004'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; pos ; dnf } ; year } ; 2004 }', 'tointer': 'the year record of this unqiue row is 2004 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; pos ; dnf } } ; eq { hop { filter_eq { all_rows ; pos ; dnf } ; year } ; 2004 } } = true', 'tointer': 'select the rows whose pos record fuzzily matches to dnf . there is only one such row in the table . the year record of this unqiue row is 2004 .'} | and { only { filter_eq { all_rows ; pos ; dnf } } ; eq { hop { filter_eq { all_rows ; pos ; dnf } ; year } ; 2004 } } = true | select the rows whose pos record fuzzily matches to dnf . there is only one such row in the table . the year record of this unqiue row is 2004 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'pos_7': 7, 'dnf_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2004_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'pos_7': 'pos', 'dnf_8': 'dnf', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2004_10': '2004'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'pos_7': [0], 'dnf_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2004_10': [3]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2004', 'rollcentre racing', 'martin short rob barff', 'lmp1', '230', 'dnf', 'dnf'], ['2005', 'rollcentre racing', 'martin short vanina ickx', 'lmp1', '318', '16th', '8th'], ['2006', 'rollcentre racing', 'martin short stuart moseley', 'lmp2', '294', '20th', '5th'], ['2007', 'rollcentre racing', 'stuart hall martin short', 'lmp1', '347', '4th', '4th'], ['2008', 'rollcentre racing', 'stéphan grégoire vanina ickx', 'lmp1', '352', '11th', '10th'], ['2009', 'pescarolo sport', 'christophe tinseau bruce jouanny', 'lmp1', '368', '8th', '8th'], ['2011', 'level 5 motorsports', 'scott tucker christophe bouchut', 'lmp2', '319', '10th', '3rd']] |
1973 ohio state buckeyes football team | https://en.wikipedia.org/wiki/1973_Ohio_State_Buckeyes_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17824926-1.html.csv | ordinal | the ohio state buckeyes ' game against usc recorded their highest attendance of the 1973 football season . | {'row': '11', 'col': '6', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'opponent'], 'result': '7 usc', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent }'}, '7 usc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent } ; 7 usc } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the opponent record of this row is 7 usc .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; opponent } ; 7 usc } = true | select the row whose attendance record of all rows is 1st maximum . the opponent record of this row is 7 usc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'opponent_7': 7, '7 usc_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'opponent_7': 'opponent', '7 usc_8': '7 usc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'opponent_7': [1], '7 usc_8': [2]} | ['date', 'opponent', 'rank', 'site', 'result', 'attendance'] | [['september 15', 'minnesota', '3', 'ohio stadium columbus , oh', 'w56 - 7', '86005'], ['september 29', 'tcu', '3', 'ohio stadium columbus , oh', 'w37 - 3', '87439'], ['october 6', 'washington state', '1', 'ohio stadium columbus , oh', 'w27 - 3', '87425'], ['october 13', 'wisconsin', '1', 'camp randall stadium madison , wi', 'w24 - 0', '77413'], ['october 20', 'indiana', '1', 'memorial stadium bloomington , in', 'w37 - 7', '53183'], ['october 27', 'northwestern', '1', 'ohio stadium columbus , oh', 'w60 - 0', '87453'], ['november 3', 'illinois', '1', 'memorial stadium champaign , il', 'w30 - 0', '60707'], ['november 10', 'michigan state', '1', 'ohio stadium columbus , oh', 'w35 - 0', '87600'], ['november 17', 'iowa', '1', 'ohio stadium columbus , oh', 'w55 - 13', '87447'], ['november 24', '4 michigan', '1', 'michigan stadium ann arbor , mi', 't 10 - 10', '105223'], ['january 1', '7 usc', '4', 'rose bowl pasadena , ca ( rose bowl )', 'w42 - 21', '105267']] |
list of number - one singles of 1999 ( canada ) | https://en.wikipedia.org/wiki/List_of_number-one_singles_of_1999_%28Canada%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17481317-1.html.csv | ordinal | livin ' la vida loca spent the 2nd highest number of weeks on top among all number one singles of 1999 in canada . | {'row': '12', 'col': '3', 'order': '2', 'col_other': '4', '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', 'weeks on top', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; weeks on top ; 2 }'}, 'song'], 'result': "livin ' la vida loca", 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; weeks on top ; 2 } ; song }'}, "livin ' la vida loca"], 'result': True, 'ind': 2, 'tostr': "eq { hop { nth_argmax { all_rows ; weeks on top ; 2 } ; song } ; livin ' la vida loca } = true", 'tointer': "select the row whose weeks on top record of all rows is 2nd maximum . the song record of this row is livin ' la vida loca ."} | eq { hop { nth_argmax { all_rows ; weeks on top ; 2 } ; song } ; livin ' la vida loca } = true | select the row whose weeks on top record of all rows is 2nd maximum . the song record of this row is livin ' la vida loca . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'weeks on top_5': 5, '2_6': 6, 'song_7': 7, "livin' la vida loca_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', 'weeks on top_5': 'weeks on top', '2_6': '2', 'song_7': 'song', "livin' la vida loca_8": "livin ' la vida loca"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'weeks on top_5': [0], '2_6': [0], 'song_7': [1], "livin' la vida loca_8": [2]} | ['volume : issue', 'issue date ( s )', 'weeks on top', 'song', 'artist'] | [['68:10 - 12', '30 november - 4 january 1999 §', '6 §', 'thank u', 'alanis morissette'], ['68:13', '11 january - 18 january ≠', '2 ≠', "it 's all been done", 'barenaked ladies'], ['68:14', '25 january', '1', 'hands', 'jewel'], ['68:15', '1 february', '1', 'you get what you give', 'new radicals'], ['68:16', '8 february', '1', '… baby one more time', 'britney spears'], ['68:17 - 18', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks', 'information still to be obtained for these weeks'], ['68:19', '1 march', '1', 'believe', 'cher'], ['68:20 - 24', '8 march - 5 april', '5', 'every morning', 'sugar ray'], ['68:25 - 26', '12 april - 19 april', '2', 'love song', 'sky'], ['69:1 - 2', '26 april - 3 may', '2', 'no scrubs', 'tlc'], ['69:3 - 5', '10 may - 24 may', '3', 'kiss me', 'sixpence none the richer'], ['69:6 - 13', '31 may - 19 july', '8', "livin ' la vida loca", 'ricky martin'], ['69:14 - 15', '26 july - 2 august', '2', 'beautiful stranger', 'madonna'], ['69:16 - 21', '9 august - 13 september', '6', 'if you had my love', 'jennifer lopez'], ['69:22 - 26 , 70:1 - 6', '20 september - 29 november', '11', 'mambo no 5', 'lou bega'], ['70:7', '6 december', '1', 'smooth', 'santana featuring rob thomas'], ['70:8 - 9', '13 december - 3 january 2000 ÷', '2 ÷', 'blue', 'eiffel 65']] |
fabiano iha | https://en.wikipedia.org/wiki/Fabiano_Iha | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445451-2.html.csv | comparative | fabiano iha 's fight against clever luciano lasted a longer time than his fight against john borsos . | {'row_1': '12', 'row_2': '14', 'col': '7', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'cleber luciano'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to cleber luciano .', 'tostr': 'filter_eq { all_rows ; opponent ; cleber luciano }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; cleber luciano } ; time }', 'tointer': 'select the rows whose opponent record fuzzily matches to cleber luciano . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'john borsos'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to john borsos .', 'tostr': 'filter_eq { all_rows ; opponent ; john borsos }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; john borsos } ; time }', 'tointer': 'select the rows whose opponent record fuzzily matches to john borsos . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; cleber luciano } ; time } ; hop { filter_eq { all_rows ; opponent ; john borsos } ; time } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to cleber luciano . take the time record of this row . select the rows whose opponent record fuzzily matches to john borsos . take the time record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; cleber luciano } ; time } ; hop { filter_eq { all_rows ; opponent ; john borsos } ; time } } = true | select the rows whose opponent record fuzzily matches to cleber luciano . take the time record of this row . select the rows whose opponent record fuzzily matches to john borsos . take the time record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'cleber luciano_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'john borsos_12': 12, 'time_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'cleber luciano_8': 'cleber luciano', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'john borsos_12': 'john borsos', 'time_13': 'time'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'cleber luciano_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'john borsos_12': [1], 'time_13': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time'] | [['win', '9 - 5', 'john cox', 'ko', 'lip 1 - lockdown in paradise 1', '1', '0:30'], ['win', '8 - 5', 'flavio troccoli', 'submission ( armbar )', 'hfp 2 - hitman fighting productions 2', '1', '0:53'], ['loss', '7 - 5', 'din thomas', 'decision ( unanimous )', 'ufc 33', '3', '5:00'], ['loss', '7 - 4', 'caol uno', 'ko ( punches )', 'ufc 32', '1', '1:48'], ['win', '7 - 3', 'phil johns', 'submission ( armbar )', 'ufc 30', '1', '2:05'], ['win', '6 - 3', 'daiju takase', 'tko ( strikes )', 'ufc 29', '1', '2:24'], ['win', '5 - 3', 'laverne clark', 'submission ( armbar )', 'ufc 27', '1', '1:10'], ['win', '4 - 3', 'danny bennett', 'submission ( armbar )', 'kotc 4 - gladiators', '1', '0:49'], ['loss', '3 - 3', 'dave menne', 'decision', 'ufc 24', '3', '5:00'], ['loss', '3 - 2', 'frank trigg', 'tko ( strikes )', 'pride 8', '1', '5:00'], ['loss', '3 - 1', 'laverne clark', 'tko ( cut )', 'ufc 20', '1', '1:31'], ['win', '3 - 0', 'cleber luciano', 'ko', 'ec 22 - extreme challenge 22', '1', '7:57'], ['win', '2 - 0', 'yves edwards', 'submission ( armbar )', 'ec 22 - extreme challenge 22', '1', '3:56'], ['win', '1 - 0', 'john borsos', 'submission ( armbar )', 'ng 5 - neutral grounds 5', '1', '0:25']] |
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 | superlative | chema was the goalkeeper who played the most matches in the 2008 - 09 segunda división . | {'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': 'chema', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; matches } ; goalkeeper }'}, 'chema'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; matches } ; goalkeeper } ; chema } = true', 'tointer': 'select the row whose matches record of all rows is maximum . the goalkeeper record of this row is chema .'} | eq { hop { argmax { all_rows ; matches } ; goalkeeper } ; chema } = true | select the row whose matches record of all rows is maximum . the goalkeeper record of this row is chema . | 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, 'chema_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', 'chema_7': 'chema'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'matches_5': [0], 'goalkeeper_6': [1], 'chema_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']] |
1993 minnesota vikings season | https://en.wikipedia.org/wiki/1993_Minnesota_Vikings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10362162-2.html.csv | superlative | the minnesota vikings ' game against the denver broncos had the most attendance in the 1993 season . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'denver broncos', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'denver broncos'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; opponent } ; denver broncos } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the opponent record of this row is denver broncos .'} | eq { hop { argmax { all_rows ; attendance } ; opponent } ; denver broncos } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is denver broncos . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'denver broncos_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'denver broncos_7': 'denver broncos'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'denver broncos_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 5 , 1993', 'los angeles raiders', 'l 24 - 7', '44120'], ['2', 'september 12 , 1993', 'chicago bears', 'w 10 - 7', '57921'], ['4', 'september 26 , 1993', 'green bay packers', 'w 15 - 13', '61746'], ['5', 'october 3 , 1993', 'san francisco 49ers', 'l 38 - 19', '63071'], ['6', 'october 10 , 1993', 'tampa bay buccaneers', 'w 15 - 0', '54215'], ['8', 'october 25 , 1993', 'chicago bears', 'w 19 - 12', '64677'], ['9', 'october 31 , 1993', 'detroit lions', 'l 30 - 27', '53428'], ['10', 'november 7 , 1993', 'san diego chargers', 'l 30 - 17', '55527'], ['11', 'november 14 , 1993', 'denver broncos', 'w 26 - 23', '67329'], ['12', 'november 21 , 1993', 'tampa bay buccaneers', 'l 23 - 10', '40848'], ['13', 'november 28 , 1993', 'new orleans saints', 'l 17 - 14', '53030'], ['14', 'december 5 , 1993', 'detroit lions', 'w 13 - 0', '63216'], ['15', 'december 12 , 1993', 'dallas cowboys', 'l 37 - 20', '63321'], ['16', 'december 19 , 1993', 'green bay packers ( milw )', 'w 21 - 17', '54773'], ['17', 'december 26 , 1993', 'kansas city chiefs', 'w 30 - 10', '59236'], ['18', 'december 31 , 1993', 'washington redskins', 'w 14 - 9', '42836']] |
athletics at the 1956 summer olympics - men 's long jump | https://en.wikipedia.org/wiki/Athletics_at_the_1956_Summer_Olympics_%E2%80%93_Men%27s_long_jump | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10676139-2.html.csv | superlative | gregory bell had the highest jump 3 score in the 1956 summer olympics - men 's long jump . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'jump 3'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; jump 3 }'}, 'athlete name'], 'result': 'gregory bell ( usa )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; jump 3 } ; athlete name }'}, 'gregory bell ( usa )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; jump 3 } ; athlete name } ; gregory bell ( usa ) } = true', 'tointer': 'select the row whose jump 3 record of all rows is maximum . the athlete name record of this row is gregory bell ( usa ) .'} | eq { hop { argmax { all_rows ; jump 3 } ; athlete name } ; gregory bell ( usa ) } = true | select the row whose jump 3 record of all rows is maximum . the athlete name record of this row is gregory bell ( usa ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'jump 3_5': 5, 'athlete name_6': 6, 'gregory bell ( usa )_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'jump 3_5': 'jump 3', 'athlete name_6': 'athlete name', 'gregory bell ( usa )_7': 'gregory bell ( usa )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'jump 3_5': [0], 'athlete name_6': [1], 'gregory bell ( usa )_7': [2]} | ['athlete name', 'jump 1', 'jump 2', 'jump 3', 'best jump'] | [['gregory bell ( usa )', '6.98', '7.83', '7.77', '7.83 m'], ['john bennett ( usa )', '7.68', '7.61', 'x', '7.68 m'], ['jorma valkama ( fin )', '7.11', 'x', '7.48', '7.48 m'], ['dmitriy bondarenko ( urs )', '7.44', 'x', '7.13', '7.44 m'], ['karim olowu ( ngr )', '7.28', '6.77', '7.36', '7.36 m'], ['kazimierz kropidlowski ( pol )', '7.27', '6.92', '7.30', '7.30 m'], ['neville price ( rsa )', 'x', '7.28', 'x', '7.28 m'], ['oleg fyodoseyev ( urs )', 'x', '7.25', '7.27', '7.27 m'], ['arthur gruttenden ( gbr )', '7.15', 'x', '6.96', '7.15 m'], ['henryk grabowski ( pol )', 'x', 'x', '7.15', '7.15 m'], ['ken wilmshurst ( gbr )', '7.14', '7.06', '7.05', '7.14 m'], ['fermã\xadn donazar ( uru )', 'x', 'x', '6.57', '6.57 m'], ['igor ter - ovanesian ( urs )', 'x', 'x', 'x', 'no mark']] |
gilmour racing | https://en.wikipedia.org/wiki/Gilmour_Racing | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16351380-1.html.csv | aggregation | gilmour racing averaged 160.5 points in the australian formula 3 championship - national class . | {'scope': 'subset', 'col': '3', 'type': 'average', 'result': '160.5', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'australian formula 3 championship - national class'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series', 'australian formula 3 championship - national class'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; series ; australian formula 3 championship - national class }', 'tointer': 'select the rows whose series record fuzzily matches to australian formula 3 championship - national class .'}, 'points'], 'result': '160.5', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; series ; australian formula 3 championship - national class } ; points }'}, '160.5'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; series ; australian formula 3 championship - national class } ; points } ; 160.5 } = true', 'tointer': 'select the rows whose series record fuzzily matches to australian formula 3 championship - national class . the average of the points record of these rows is 160.5 .'} | round_eq { avg { filter_eq { all_rows ; series ; australian formula 3 championship - national class } ; points } ; 160.5 } = true | select the rows whose series record fuzzily matches to australian formula 3 championship - national class . the average of the points record of these rows is 160.5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'series_5': 5, 'australian formula 3 championship - national class_6': 6, 'points_7': 7, '160.5_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'series_5': 'series', 'australian formula 3 championship - national class_6': 'australian formula 3 championship - national class', 'points_7': 'points', '160.5_8': '160.5'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'series_5': [0], 'australian formula 3 championship - national class_6': [0], 'points_7': [1], '160.5_8': [2]} | ['season', 'series', 'points', 'position', 'driver'] | [['2001', 'queensland formula ford championship', '216', '2nd', 'chris gilmour'], ['2002', 'queensland formula ford championship', '234', '2nd', 'chris gilmour'], ['2003', 'queensland formula ford championship', '222', '1st', 'chris gilmour'], ['2004', 'australian formula 3 championship', '235', '2nd', 'chris gilmour'], ['2005', 'australian formula 3 championship', '142', '4th', 'chris gilmour'], ['2006', 'australian formula 3 championship', '150', '4th', 'chris gilmour'], ['2007', 'australian formula 3 championship', '52', '8th', 'chris gilmour'], ['2008', 'australian formula 3 championship - national class', '228', '1st', 'chris gilmour'], ['2009', 'australian formula 3 championship - national class', '93', '4th', 'chris gilmour'], ['2010', 'australian formula 3 championship', '90', '5th', 'chris gilmour'], ['2011', 'australian formula 3 championship', '210', '1st', 'chris gilmour']] |
2008 in british television | https://en.wikipedia.org/wiki/2008_in_British_television | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13549921-18.html.csv | majority | most of the programmes had itv as the original channel . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'itv', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'original channel', 'itv'], 'result': True, 'ind': 0, 'tointer': 'for the original channel records of all rows , most of them fuzzily match to itv .', 'tostr': 'most_eq { all_rows ; original channel ; itv } = true'} | most_eq { all_rows ; original channel ; itv } = true | for the original channel records of all rows , most of them fuzzily match to itv . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'original channel_3': 3, 'itv_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'original channel_3': 'original channel', 'itv_4': 'itv'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'original channel_3': [0], 'itv_4': [0]} | ['programme', 'date ( s ) of original removal', 'original channel', 'date ( s ) of return', 'new channel ( s )'] | [['mr and mrs as all star mr & mrs', '1999', 'itv', '12 april 2008', 'n / a ( same channel as original )'], ['itv news at ten', '5 march 1999 30 january 2004', 'itv', '22 january 2001 14 january 2008', 'n / a ( same channel as original )'], ['gladiators', '1 january 2000', 'itv', '11 may 2008', 'sky1'], ['superstars', '2005', 'bbc one', 'july 2008', 'five'], ["it 'll be alright on the night", '18 march 2006', 'itv', '20 september 2008', 'n / a ( same channel as original )']] |
2008 - 09 croatian cup | https://en.wikipedia.org/wiki/2008%E2%80%9309_Croatian_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18828647-1.html.csv | majority | most of the rounds did n't have any new entries in the round . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'none', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'new entries this round', 'none'], 'result': True, 'ind': 0, 'tointer': 'for the new entries this round records of all rows , most of them fuzzily match to none .', 'tostr': 'most_eq { all_rows ; new entries this round ; none } = true'} | most_eq { all_rows ; new entries this round ; none } = true | for the new entries this round records of all rows , most of them fuzzily match to none . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'new entries this round_3': 3, 'none_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'new entries this round_3': 'new entries this round', 'none_4': 'none'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'new entries this round_3': [0], 'none_4': [0]} | ['round', 'main date', 'number of fixtures', 'clubs', 'new entries this round'] | [['preliminary round', '27 august 2008', '16', '48 → 32', 'none'], ['first round', '23 and 24 september 2008', '16', '32 → 16', '16'], ['second round', '29 october 2008', '8', '16 → 8', 'none'], ['quarter - finals', '12 and 26 november 2008', '8', '8 → 4', 'none'], ['semi - finals', '4 and 18 march 2009', '4', '4 → 2', 'none'], ['final', '13 and 28 may 2009', '2', '2 → 1', 'none']] |
1983 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1983_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11440693-2.html.csv | superlative | the largest attendance of the 1983 tampa bay buccaneers season was at the last game of the season . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '17', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'week'], 'result': '16', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; week }'}, '16'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; week } ; 16 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the week record of this row is 16 .'} | eq { hop { argmax { all_rows ; attendance } ; week } ; 16 } = true | select the row whose attendance record of all rows is maximum . the week record of this row is 16 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'week_6': 6, '16_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'week_6': 'week', '16_7': '16'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'week_6': [1], '16_7': [2]} | ['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'] | [['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'], ['1', 'september 4 , 1983', 'detroit lions', 'l 11 - 0', '1:00', 'tampa stadium', '62154', '0 - 1'], ['2', 'september 11 , 1983', 'chicago bears', 'l 17 - 10', '1:00', 'soldier field', '58156', '0 - 2'], ['3', 'september 18 , 1983', 'minnesota vikings', 'l 19 - 16 ot', '4:00', 'tampa stadium', '57567', '0 - 3'], ['4', 'september 25 , 1983', 'cincinnati bengals', 'l 23 - 17', '1:00', 'tampa stadium', '56023', '0 - 4'], ['5', 'october 2 , 1983', 'green bay packers', 'l 55 - 14', '1:00', 'lambeau field', '54272', '0 - 5'], ['6', 'october 9 , 1983', 'dallas cowboys', 'l 27 - 24 ot', '4:00', 'texas stadium', '63308', '0 - 6'], ['7', 'october 16 , 1983', 'st louis cardinals', 'l 34 - 27', '1:00', 'tampa stadium', '48224', '0 - 7'], ['8', 'october 23 , 1983', 'new orleans saints', 'l 24 - 21', '4:00', 'tampa stadium', '48242', '0 - 8'], ['9', 'october 30 , 1983', 'pittsburgh steelers', 'l 17 - 12', '1:00', 'three rivers stadium', '57648', '0 - 9'], ['10', 'november 6 , 1983', 'minnesota vikings', 'w 17 - 12', '1:00', 'hubert h humphrey metrodome', '59239', '1 - 9'], ['11', 'november 13 , 1983', 'cleveland browns', 'l 20 - 0', '1:00', 'cleveland stadium', '56091', '1 - 10'], ['12', 'november 20 , 1983', 'chicago bears', 'l 27 - 0', '1:00', 'tampa stadium', '36816', '1 - 11'], ['13', 'november 27 , 1983', 'houston oilers', 'w 33 - 24', '1:00', 'tampa stadium', '38625', '2 - 11'], ['14', 'december 4 , 1983', 'san francisco 49ers', 'l 35 - 21', '4:00', 'candlestick park', '49773', '2 - 12'], ['15', 'december 12 , 1983', 'green bay packers', 'l 12 - 9 ot', '9:00', 'tampa stadium', '50763', '2 - 13'], ['16', 'december 18 , 1983', 'detroit lions', 'l 23 - 20', '4:00', 'pontiac silverdome', '78392', '2 - 14']] |
2007 - 08 four hills tournament | https://en.wikipedia.org/wiki/2007%E2%80%9308_Four_Hills_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14948647-3.html.csv | count | in the 2007 - 08 four hills tournament , among the players not from germany ( ger ) , 2 of them earned more than 257.0 points . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '257.0', 'result': '2', 'col': '6', 'subset': {'col': '3', 'criterion': 'not_equal', 'value': 'ger'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'nationality', 'ger'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; nationality ; ger }', 'tointer': 'select the rows whose nationality record does not match to ger .'}, 'points', '257.0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nationality record does not match to ger . among these rows , select the rows whose points record is greater than 257.0 .', 'tostr': 'filter_greater { filter_not_eq { all_rows ; nationality ; ger } ; points ; 257.0 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_not_eq { all_rows ; nationality ; ger } ; points ; 257.0 } }', 'tointer': 'select the rows whose nationality record does not match to ger . among these rows , select the rows whose points record is greater than 257.0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_not_eq { all_rows ; nationality ; ger } ; points ; 257.0 } } ; 2 } = true', 'tointer': 'select the rows whose nationality record does not match to ger . among these rows , select the rows whose points record is greater than 257.0 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_not_eq { all_rows ; nationality ; ger } ; points ; 257.0 } } ; 2 } = true | select the rows whose nationality record does not match to ger . among these rows , select the rows whose points record is greater than 257.0 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_5': 5, 'nationality_6': 6, 'ger_7': 7, 'points_8': 8, '257.0_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_5': 'all_rows', 'nationality_6': 'nationality', 'ger_7': 'ger', 'points_8': 'points', '257.0_9': '257.0', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_5': [0], 'nationality_6': [0], 'ger_7': [0], 'points_8': [1], '257.0_9': [1], '2_10': [3]} | ['rank', 'name', 'nationality', '1st ( m )', '2nd ( m )', 'points', 'overall fht points', 'overall wc points ( rank )'] | [['1', 'gregor schlierenzauer', 'aut', '132.0', '141.0', '274.4', '555.1 ( 1 )', '609 ( 2 )'], ['2', 'janne ahonen', 'fin', '139.0', '135.0', '272.7', '551.7 ( 3 )', '415 ( 3 )'], ['3', 'michael neumayer', 'ger', '131.5', '135.5', '258.6', '518.1 ( 5 )', '240 ( 10 )'], ['4', 'roman koudelka', 'cze', '132.0', '132.0', '256.7', '504.2 ( 9 )', '220 ( 13 )'], ['5', 'adam maå ‚ ysz', 'pol', '133.0', '131.5', '256.6', '503.5 ( 10 )', '243 ( 9 )']] |
harlem rocker | https://en.wikipedia.org/wiki/Harlem_Rocker | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17644295-1.html.csv | superlative | hallandale beach was the first site location on which harlem rocker participated in a race . | {'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', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'location'], 'result': 'hallandale beach , florida', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; location }'}, 'hallandale beach , florida'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; location } ; hallandale beach , florida } = true', 'tointer': 'select the row whose date record of all rows is minimum . the location record of this row is hallandale beach , florida .'} | eq { hop { argmin { all_rows ; date } ; location } ; hallandale beach , florida } = true | select the row whose date record of all rows is minimum . the location record of this row is hallandale beach , florida . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'location_6': 6, 'hallandale beach , florida_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'location_6': 'location', 'hallandale beach , florida_7': 'hallandale beach , florida'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'location_6': [1], 'hallandale beach , florida_7': [2]} | ['date', 'race', 'track', 'location', 'distance', 'surface', 'purse', 'finish'] | [['february 14 , 2008', 'maiden special weight', 'gulfstream park', 'hallandale beach , florida', '7 fur', 'dirt', '40000', '1st'], ['march 30 , 2008', 'allowance', 'gulfstream park', 'hallandale beach , florida', '1 mi', 'dirt', '42500', '1st'], ['april 26 , 2008', 'withers stakes', 'aqueduct racetrack', 'new york city , new york', '1 mi', 'dirt', '142500', '1st'], ['june 1 , 2008', 'plate trial stakes', 'woodbine racetrack', 'toronto , ontario', '1 ⅛ mi', 'polytrack', '151781', '4th'], ['july 13 , 2008', 'prince of wales stakes', 'fort erie racetrack', 'fort erie , ontario', '1 1 / 16 mi', 'dirt', '495400', '1st'], ['august 23 , 2008', 'travers stakes', 'saratoga race course', 'saratoga springs , new york', '1 ¼ mi', 'dirt', '1000000', '4th'], ['october 5 , 2008', 'jerome handicap', 'belmont park', 'elmont , new york', '1 mi', 'dirt', '150000', '3rd'], ['november 29 , 2008', 'cigar mile handicap', 'aqueduct racetrack', 'new york city , new york', '1 mi', 'dirt', '300000', '2nd'], ['november 14 , 2009', 'allowance optional claiming', 'churchill downs', 'louisville , kentucky', '7 fur', 'dirt', '56000', '2nd'], ['january 3 , 2010', "hal 's hope handicap", 'gulfstream park', 'hallandale beach , florida', '1 mi', 'dirt', '100000', '4th']] |
list of mountains in norway by prominence | https://en.wikipedia.org/wiki/List_of_mountains_in_Norway_by_prominence | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12280396-1.html.csv | count | two of the mountains in norway are located in oppland county . | {'scope': 'all', 'criterion': 'equal', 'value': 'oppland', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'oppland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to oppland .', 'tostr': 'filter_eq { all_rows ; county ; oppland }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; county ; oppland } }', 'tointer': 'select the rows whose county record fuzzily matches to oppland . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; county ; oppland } } ; 2 } = true', 'tointer': 'select the rows whose county record fuzzily matches to oppland . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; county ; oppland } } ; 2 } = true | select the rows whose county record fuzzily matches to oppland . 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, 'county_5': 5, 'oppland_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', 'county_5': 'county', 'oppland_6': 'oppland', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'county_5': [0], 'oppland_6': [0], '2_7': [2]} | ['peak', 'elevation ( m )', 'prominence ( m )', 'isolation ( km )', 'municipality', 'county'] | [['galdhøpiggen', '2469', '2372', '1570', 'lom', 'oppland'], ['jiehkkevárri', '1833', '1741', '140', 'lyngen , tromsø', 'troms'], ['snøhetta', '2286', '1675', '83', 'dovre', 'oppland'], ['store lenangstind', '1625', '1576', '47', 'lyngen', 'troms'], ['gjegnen / blånibba', '1670', '1460', '47', 'bremanger', 'sogn og fjordane'], ['hamperokken', '1404', '1396', '18', 'tromsø', 'troms'], ['skårasalen', '1542', '1385', '7', 'ørsta', 'møre og romsdal'], ['oksskolten', '1916', '1384', '185', 'hemnes', 'nordland'], ['botnafjellet', '1572', '1339', '15', 'gloppen', 'sogn og fjordane'], ['kvitegga', '1717', '1324', '23', 'stranda , ørsta', 'møre og romsdal'], ['fresvikbreen', '1660', '1310', '17', 'vik', 'sogn og fjordane'], ['smørskredtindane', '1630', '1306', '12', 'stranda , ørsta', 'møre og romsdal'], ['njunis', '1717', '1305', '53', 'målselv', 'troms'], ['store trolla', '1850', '1292', '11', 'sunndal', 'møre og romsdal'], ['langlitinden', '1276', '1276', '26', 'ibestad', 'troms'], ['indre russetind', '1527', '1268', '9', 'balsfjord', 'troms'], ['møysalen', '1262', '1262', '60', 'hinnøya', 'nordland'], ['stortind', '1320', '1242', '14', 'tromsø', 'troms'], ['folgefonna', '1660', '1233', '29', 'kvinnherad , odda', 'hordaland'], ['daurmål', '1446', '1230', '4', 'gloppen , jølster', 'sogn og fjordane']] |
1960 philadelphia eagles season | https://en.wikipedia.org/wiki/1960_Philadelphia_Eagles_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16678519-2.html.csv | aggregation | the 1960 philadelphia eagles scored an average of 24.69 points a game . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '24.69', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'result'], 'result': '24.69', 'ind': 0, 'tostr': 'avg { all_rows ; result }'}, '24.69'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; result } ; 24.69 } = true', 'tointer': 'the average of the result record of all rows is 24.69 .'} | round_eq { avg { all_rows ; result } ; 24.69 } = true | the average of the result record of all rows is 24.69 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'result_4': 4, '24.69_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'result_4': 'result', '24.69_5': '24.69'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'result_4': [0], '24.69_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 25 , 1960', 'cleveland browns', 'l 24 - 41', '56303'], ['2', 'september 30 , 1960', 'dallas cowboys', 'w 27 - 25', '18500'], ['3', 'october 9 , 1960', 'st louis cardinals', 'w 31 - 27', '33701'], ['4', 'october 16 , 1960', 'detroit lions', 'w 28 - 10', '38065'], ['5', 'october 23 , 1960', 'cleveland browns', 'w 31 - 29', '64850'], ['7', 'november 6 , 1960', 'pittsburgh steelers', 'w 34 - 7', '58324'], ['8', 'november 13 , 1960', 'washington redskins', 'w 19 - 13', '39361'], ['9', 'november 20 , 1960', 'new york giants', 'w 17 - 10', '63571'], ['10', 'november 27 , 1960', 'new york giants', 'w 31 - 23', '60547'], ['11', 'december 4 , 1960', 'st louis cardinals', 'w 20 - 6', '21358'], ['12', 'december 11 , 1960', 'pittsburgh steelers', 'l 21 - 27', '22101'], ['13', 'december 18 , 1960', 'washington redskins', 'w 38 - 28', '20558']] |
media in sherbrooke | https://en.wikipedia.org/wiki/Media_in_Sherbrooke | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409243-1.html.csv | unique | of the media in sherbrooke , only the station with the format campus radio is cfak - fm . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'campus radio', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'campus radio'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose format record fuzzily matches to campus radio .', 'tostr': 'filter_eq { all_rows ; format ; campus radio }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; format ; campus radio } }', 'tointer': 'select the rows whose format record fuzzily matches to campus radio . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'campus radio'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose format record fuzzily matches to campus radio .', 'tostr': 'filter_eq { all_rows ; format ; campus radio }'}, 'call sign'], 'result': 'cfak - fm', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; format ; campus radio } ; call sign }'}, 'cfak - fm'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; format ; campus radio } ; call sign } ; cfak - fm }', 'tointer': 'the call sign record of this unqiue row is cfak - fm .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; format ; campus radio } } ; eq { hop { filter_eq { all_rows ; format ; campus radio } ; call sign } ; cfak - fm } } = true', 'tointer': 'select the rows whose format record fuzzily matches to campus radio . there is only one such row in the table . the call sign record of this unqiue row is cfak - fm .'} | and { only { filter_eq { all_rows ; format ; campus radio } } ; eq { hop { filter_eq { all_rows ; format ; campus radio } ; call sign } ; cfak - fm } } = true | select the rows whose format record fuzzily matches to campus radio . there is only one such row in the table . the call sign record of this unqiue row is cfak - fm . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'format_7': 7, 'campus radio_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'call sign_9': 9, 'cfak - fm_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'format_7': 'format', 'campus radio_8': 'campus radio', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'call sign_9': 'call sign', 'cfak - fm_10': 'cfak - fm'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'format_7': [0], 'campus radio_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'call sign_9': [2], 'cfak - fm_10': [3]} | ['frequency', 'call sign', 'format', 'owner', 'notes'] | [['fm 88.1', 'cfpp - fm', 'christian radio', 'fabrique notre - dame du perpétuel - secours', 'french'], ['fm 88.3', 'cfak - fm', 'campus radio', 'université de sherbrooke', 'french'], ['fm 88.9', 'cjmq - fm', 'community radio', "bishop 's university", 'english'], ['fm 89.7', 'cbm - fm - 1', 'public music', 'canadian broadcasting corporation', 'english'], ['fm 90.7', 'cbfx - fm - 2', 'public music', 'société radio - canada', 'french'], ['fm 91.7', 'cbmb - fm', 'public news / talk', 'canadian broadcasting corporation', 'english'], ['fm 93.7', 'cfge - fm', 'adult contemporary', 'cogeco', 'french'], ['fm 95.5', 'cflx - fm', 'community radio', "radio communautaire de l'estrie", 'french'], ['fm 100.3', 'cira - fm - 1', 'christian radio', 'radio ville - marie', 'french'], ['fm 101.1', 'cbf - fm - 10', 'public news / talk', 'société radio - canada', 'french'], ['fm 102.7', 'cite - fm - 1', 'soft adult contemporary', 'bell media radio', 'french'], ['fm 106.1', 'cimo - fm', 'contemporary hit radio', 'bell media radio', 'french'], ['fm 107.7', 'ckoy - fm', 'talk radio', 'cogeco', 'french']] |
1938 vfl season | https://en.wikipedia.org/wiki/1938_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806592-9.html.csv | majority | a majority of the time the crowd was over 10,000 people . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10,000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'crowd', '10,000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 10,000 .', 'tostr': 'most_greater { all_rows ; crowd ; 10,000 } = true'} | most_greater { all_rows ; crowd ; 10,000 } = true | for the crowd records of all rows , most of them are greater than 10,000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '10,000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '10,000_4': '10,000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '10,000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '11.23 ( 89 )', 'hawthorn', '6.13 ( 49 )', 'corio oval', '7000', '18 june 1938'], ['fitzroy', '16.12 ( 108 )', 'south melbourne', '8.8 ( 56 )', 'brunswick street oval', '12000', '18 june 1938'], ['st kilda', '14.12 ( 96 )', 'melbourne', '16.16 ( 112 )', 'junction oval', '14000', '18 june 1938'], ['richmond', '15.14 ( 104 )', 'essendon', '15.9 ( 99 )', 'punt road oval', '20000', '18 june 1938'], ['footscray', '13.9 ( 87 )', 'collingwood', '10.5 ( 65 )', 'western oval', '18000', '18 june 1938'], ['north melbourne', '11.5 ( 71 )', 'carlton', '16.25 ( 121 )', 'arden street oval', '13000', '18 june 1938']] |
1973 - 74 football league cup | https://en.wikipedia.org/wiki/1973%E2%80%9374_Football_League_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24887326-8.html.csv | majority | most of the 1973-74 football league cup matches that had over 10000 people were played on 21-11-1973 . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '21 - 11 - 1973', 'subset': {'col': '5', 'criterion': 'greater_than', 'value': '10000'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'attendance', '10000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; attendance ; 10000 }', 'tointer': 'select the rows whose attendance record is greater than 10000 .'}, 'date', '21 - 11 - 1973'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose attendance record is greater than 10000 . for the date records of these rows , most of them fuzzily match to 21 - 11 - 1973 .', 'tostr': 'most_eq { filter_greater { all_rows ; attendance ; 10000 } ; date ; 21 - 11 - 1973 } = true'} | most_eq { filter_greater { all_rows ; attendance ; 10000 } ; date ; 21 - 11 - 1973 } = true | select the rows whose attendance record is greater than 10000 . for the date records of these rows , most of them fuzzily match to 21 - 11 - 1973 . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '10000_5': 5, 'date_6': 6, '21 - 11 - 1973_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '10000_5': '10000', 'date_6': 'date', '21 - 11 - 1973_7': '21 - 11 - 1973'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '10000_5': [0], 'date_6': [1], '21 - 11 - 1973_7': [1]} | ['tie no', 'home team', 'score 1', 'away team', 'attendance', 'date'] | [['1', 'york city', '0 - 0', 'manchester city', '15360', '21 - 11 - 1973'], ['2', 'queens park rangers', '0 - 3', 'plymouth argyle', '19072', '20 - 11 - 1973'], ['3', 'southampton', '0 - 2', 'norwich city', '14415', '21 - 11 - 1973'], ['4', 'ipswich town', '1 - 3', 'birmingham city', '12241', '21 - 11 - 1973'], ['5', 'wolverhampton wanderers', '5 - 1', 'exeter city', '7623', '20 - 11 - 1973'], ['6', 'millwall', '3 - 1', 'luton town', '8777', '21 - 11 - 1973'], ['7', 'coventry city', '2 - 1', 'stoke city', '17485', '20 - 11 - 1973']] |
will & grace ( season 5 ) | https://en.wikipedia.org/wiki/Will_%26_Grace_%28season_5%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27833469-1.html.csv | majority | the majority of episodes had over 15 million viewers . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '15', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'us viewers ( millions )', '15'], 'result': True, 'ind': 0, 'tointer': 'for the us viewers ( millions ) records of all rows , most of them are greater than or equal to 15 .', 'tostr': 'most_greater_eq { all_rows ; us viewers ( millions ) ; 15 } = true'} | most_greater_eq { all_rows ; us viewers ( millions ) ; 15 } = true | for the us viewers ( millions ) records of all rows , most of them are greater than or equal to 15 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'us viewers (millions)_3': 3, '15_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'us viewers (millions)_3': 'us viewers ( millions )', '15_4': '15'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'us viewers (millions)_3': [0], '15_4': [0]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['93', '1', 'and the horse he rode in on', 'james burrows', 'adam barr', 'september 26 , 2002', '21.5'], ['94', '2', 'bacon and eggs', 'james burrows', 'alex herschlag', 'october 3 , 2002', '20.6'], ['95', '3', 'the kid stays out of the picture', 'james burrows', 'jhoni marchinko', 'october 10 , 2002', '20.2'], ['96', '4', 'humongous growth', 'james burrows', 'kari lizer', 'october 17 , 2002', '19.5'], ['97', '5', "it 's the gay pumpkin , charlie brown", 'james burrows', 'gary janetti', 'october 31 , 2002', '17.2'], ['98', '6', 'boardroom and a parked place', 'james burrows', 'gail lerner', 'november 7 , 2002', '21.1'], ['99', '7', "the needle and the omelet 's done", 'james burrows', 'tracy poust & jon kinnally', 'november 14 , 2002', '19.1'], ['100', '8 - 9', 'marry me a little , marry me a little more', 'james burrows', 'jeff greenstein & bill wrubel', 'november 21 , 2002', '24.3'], ['101', '10', "the honeymoon 's over", 'james burrows', 'sally bradford', 'december 5 , 2002', '19.3'], ['102', '11', 'all about christmas eve', 'james burrows', 'adam barr', 'december 12 , 2002', '16.2'], ['103', '12', 'field of queens', 'james burrows', 'katie palmer', 'january 9 , 2003', '16.2'], ['104', '13', 'fagmalion part i : gay it forward', 'james burrows', 'tracy poust & jon kinnally', 'january 16 , 2003', '16.0'], ['105', '14', 'fagmalion part ii : attack of the clones', 'james burrows', 'gary janetti', 'january 30 , 2003', '15.8'], ['106', '15', 'homojo', 'james burrows', 'bill wrubel', 'february 6 , 2003', '16.5'], ['107', '16', 'women and children first', 'james burrows', 'laura kightlinger', 'february 13 , 2003', '18.7'], ['108', '17', 'fagmalion part iii : bye , bye , beardy', 'james burrows', 'alex herschlag', 'february 20 , 2003', '16.4'], ['109', '18', 'fagmalion part iv : the guy who loved me', 'james burrows', 'gail lerner', 'march 13 , 2003', '15.0'], ['110', '19', 'sex , losers , and videotape', 'james burrows', 'steve gabriel', 'april 3 , 2003', '15.0'], ['111', '20', 'leo unwrapped', 'james burrows', 'sonja warfield', 'april 17 , 2003', '14.7'], ['112', '21', 'dolls and dolls', 'james burrows', 'kari lizer', 'april 24 , 2003', '17.7']] |
1981 vfl season | https://en.wikipedia.org/wiki/1981_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-14.html.csv | ordinal | vfl park venue recorded the highest crowd participation during the 1981 vfl season . | {'row': '5', 'col': '6', 'order': '1', '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', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'vfl park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'vfl park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; vfl park } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is vfl park .'} | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; vfl park } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is vfl 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, '1_6': 6, 'venue_7': 7, 'vfl 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', '1_6': '1', 'venue_7': 'venue', 'vfl park_8': 'vfl park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'vfl park_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['carlton', '15.25 ( 115 )', 'footscray', '5.4 ( 34 )', 'princes park', '17419', '27 june 1981'], ['richmond', '21.23 ( 149 )', 'north melbourne', '15.16 ( 106 )', 'mcg', '31212', '27 june 1981'], ['st kilda', '18.19 ( 127 )', 'melbourne', '8.7 ( 55 )', 'moorabbin oval', '14058', '27 june 1981'], ['south melbourne', '9.16 ( 70 )', 'fitzroy', '14.9 ( 93 )', 'lake oval', '11756', '27 june 1981'], ['collingwood', '13.8 ( 86 )', 'geelong', '9.14 ( 68 )', 'vfl park', '50441', '27 june 1981'], ['hawthorn', '20.13 ( 133 )', 'essendon', '22.19 ( 151 )', 'the gabba', '20351', '28 june 1981']] |
minnesota golden gophers football under bernie bierman | https://en.wikipedia.org/wiki/Minnesota_Golden_Gophers_football_under_Bernie_Bierman | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16518708-2.html.csv | comparative | more points were scored in the golden gopher 's game on september 30 , 1993 than the game on november 4 . | {'row_1': '1', 'row_2': '6', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '09 / 30 / 1933'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 09 / 30 / 1933 .', 'tostr': 'filter_eq { all_rows ; date ; 09 / 30 / 1933 }'}, 'result'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 09 / 30 / 1933 } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to 09 / 30 / 1933 . take the result record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '11 / 04 / 1933'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 11 / 04 / 1933 .', 'tostr': 'filter_eq { all_rows ; date ; 11 / 04 / 1933 }'}, 'result'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 11 / 04 / 1933 } ; result }', 'tointer': 'select the rows whose date record fuzzily matches to 11 / 04 / 1933 . take the result record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; 09 / 30 / 1933 } ; result } ; hop { filter_eq { all_rows ; date ; 11 / 04 / 1933 } ; result } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 09 / 30 / 1933 . take the result record of this row . select the rows whose date record fuzzily matches to 11 / 04 / 1933 . take the result record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; 09 / 30 / 1933 } ; result } ; hop { filter_eq { all_rows ; date ; 11 / 04 / 1933 } ; result } } = true | select the rows whose date record fuzzily matches to 09 / 30 / 1933 . take the result record of this row . select the rows whose date record fuzzily matches to 11 / 04 / 1933 . take the result record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '09 / 30 / 1933_8': 8, 'result_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '11 / 04 / 1933_12': 12, 'result_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '09 / 30 / 1933_8': '09 / 30 / 1933', 'result_9': 'result', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '11 / 04 / 1933_12': '11 / 04 / 1933', 'result_13': 'result'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '09 / 30 / 1933_8': [0], 'result_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '11 / 04 / 1933_12': [1], 'result_13': [3]} | ['date', 'opponent', 'site', 'result', 'attendance'] | [['09 / 30 / 1933', 'south dakota state', 'memorial stadium minneapolis , mn', 'w19 - 6', '25000'], ['10 / 07 / 1933', 'indiana', 'memorial stadium minneapolis , mn', 't6 - 6', '20000'], ['10 / 14 / 1933', 'purdue', 'memorial stadium minneapolis , mn', 't7 - 7', '26497'], ['10 / 21 / 1933', 'pittsburgh', 'memorial stadium minneapolis , mn', 'w7 - 3', '26000'], ['10 / 28 / 1933', 'iowa', 'memorial stadium minneapolis , mn', 'w19 - 7', '45000'], ['11 / 04 / 1933', 'northwestern', 'dyche stadium evanston , il', 't0 - 0', '35000'], ['11 / 18 / 1933', 'michigan', 'michigan stadium ann arbor , mi', 't0 - 0', '52137'], ['11 / 25 / 1933', 'wisconsin', 'memorial stadium minneapolis , mn', 'w6 - 3', '25000']] |
1991 san diego chargers season | https://en.wikipedia.org/wiki/1991_San_Diego_Chargers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15345678-1.html.csv | count | in the 1991 san diego chargers season , two of the players went to school at tennessee . | {'scope': 'all', 'criterion': 'equal', 'value': 'tennessee', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school / club team', 'tennessee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school / club team record fuzzily matches to tennessee .', 'tostr': 'filter_eq { all_rows ; school / club team ; tennessee }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; school / club team ; tennessee } }', 'tointer': 'select the rows whose school / club team record fuzzily matches to tennessee . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; school / club team ; tennessee } } ; 2 } = true', 'tointer': 'select the rows whose school / club team record fuzzily matches to tennessee . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; school / club team ; tennessee } } ; 2 } = true | select the rows whose school / club team record fuzzily matches to tennessee . 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, 'school / club team_5': 5, 'tennessee_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', 'school / club team_5': 'school / club team', 'tennessee_6': 'tennessee', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'school / club team_5': [0], 'tennessee_6': [0], '2_7': [2]} | ['round', 'pick', 'player', 'position', 'school / club team'] | [['1', '9', 'stanley richard', 'defensive back', 'texas'], ['2', '36', 'george thornton', 'defensive tackle', 'alabama'], ['2', '39', 'eric bieniemy', 'running back', 'colorado'], ['2', '47', 'eric moten', 'guard', 'michigan state'], ['4', '90', 'yancey thigpen', 'wide receiver', 'winston - salem state'], ['5', '123', 'duane young', 'tight end', 'michigan state'], ['5', '127', 'floyd fields', 'defensive back', 'arizona state'], ['6', '150', 'jimmy laister', 'offensive tackle', 'oregon tech'], ['7', '177', 'david jones', 'tight end', 'delaware state'], ['7', '192', 'terry beauford', 'guard', 'florida a & m'], ['9', '230', 'andy katoa', 'linebacker', 'southern oregon'], ['10', '254', 'ronald poles', 'running back', 'tennessee'], ['10', '257', 'mike heldt', 'center', 'tennessee'], ['11', '290', 'joachim weinberg', 'wide receiver', 'johnson c smith u'], ['12', '317', 'chris samuels', 'running back', 'texas']] |
list of dams and reservoirs in asturias | https://en.wikipedia.org/wiki/List_of_dams_and_reservoirs_in_Asturias | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28702208-1.html.csv | unique | in the list of dams and reservoirs in asturias , the only one of gravity type that has drainage basin 0.0 km square its location is morcín . | {'scope': 'subset', 'row': '9', 'col': '7', 'col_other': '3', 'criterion': 'equal', 'value': '0.0', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'gravity'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'gravity'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; gravity }', 'tointer': 'select the rows whose type record fuzzily matches to gravity .'}, 'drainage basin ( km square )', '0.0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose type record fuzzily matches to gravity . among these rows , select the rows whose drainage basin ( km square ) record is equal to 0.0 .', 'tostr': 'filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } }', 'tointer': 'select the rows whose type record fuzzily matches to gravity . among these rows , select the rows whose drainage basin ( km square ) record is equal to 0.0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'type', 'gravity'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; type ; gravity }', 'tointer': 'select the rows whose type record fuzzily matches to gravity .'}, 'drainage basin ( km square )', '0.0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose type record fuzzily matches to gravity . among these rows , select the rows whose drainage basin ( km square ) record is equal to 0.0 .', 'tostr': 'filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 }'}, 'location'], 'result': 'morcín', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } ; location }'}, 'morcín'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } ; location } ; morcín }', 'tointer': 'the location record of this unqiue row is morcín .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } ; location } ; morcín } } = true', 'tointer': 'select the rows whose type record fuzzily matches to gravity . among these rows , select the rows whose drainage basin ( km square ) record is equal to 0.0 . there is only one such row in the table . the location record of this unqiue row is morcín .'} | and { only { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; type ; gravity } ; drainage basin ( km square ) ; 0.0 } ; location } ; morcín } } = true | select the rows whose type record fuzzily matches to gravity . among these rows , select the rows whose drainage basin ( km square ) record is equal to 0.0 . there is only one such row in the table . the location record of this unqiue row is morcín . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'type_8': 8, 'gravity_9': 9, 'drainage basin (km square)_10': 10, '0.0_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'location_12': 12, 'morcín_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'type_8': 'type', 'gravity_9': 'gravity', 'drainage basin (km square)_10': 'drainage basin ( km square )', '0.0_11': '0.0', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'location_12': 'location', 'morcín_13': 'morcín'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'type_8': [0], 'gravity_9': [0], 'drainage basin (km square)_10': [1], '0.0_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'location_12': [3], 'morcín_13': [4]} | ['reservoir', 'basin', 'location', 'type', 'height ( m )', 'length along the top ( m )', 'drainage basin ( km square )', 'reservoir surface ( ha )', 'volume ( hm cubic )'] | [['alfilorios', 'barrea', 'ribera de arriba', 'embankment', '67.0', '171.7', '4.09', '52.0', '9.140'], ['arbón', 'navia', 'coaña , villayón', 'embankment', '35.0', '180.0', '2443.0', '270.0', '38.20'], ['barca , la', 'narcea', 'belmonte , tineo', 'arch', '73.5', '178.0', '1216.0', '194.0', '31.10'], ['doiras', 'navia', 'boal', 'arch - gravity', '90.0', '165.0', '2288.0', '347.0', '114.60'], ['florida , la', 'narcea', 'tineo', 'gravity', '19.0', '70.0', '1005.0', '18.40', '0.75'], ['furacón , el', 'nalón', 'trubia ( oviedo )', 'gravity', '14.0', '70.0', '2180.0', '19.0', '0.522'], ['granda , la', 'granda', 'gozón', 'embankment', '23.7', '270.0', '1.25', '32.50', '3.208'], ['jocica , la', 'dobra', 'amieva', 'arch', '87.0', '66.0', '39.0', '6.14', '0.4'], ['mortera , la', 'mortera', 'morcín', 'gravity', '8.0', '91.0', '0.0', '0.0', '0.017'], ['priañes', 'nora', 'oviedo , las regueras', 'gravity', '27.0', '50.0', '340.0', '35.17', '1.9'], ['saliencia', 'saliencia', 'somiedo', 'gravity', '20.0', '33.0', '48.0', '0.30', '0.02'], ['salime', 'navia', 'grandas de salime', 'gravity', '125.67', '250.0', '1806.0', '685.0', '266.30'], ['san andrés tacones', 'aboño', 'sa tacones ( gijón )', 'embankment', '22.0', '434.0', '37.5', '4.0', '71.0'], ['somiedo', 'somiedo', 'somiedo', 'gravity', '24.0', '18.0', '82.0', '0.29', '0.018'], ['tanes', 'nalón', 'caso , sobrescobio', 'gravity', '95.0', '195.0', '271.0', '159.0', '33.27'], ['trasona', 'alvares', 'trasona ( corvera )', 'gravity', '16.0', '332.0', '37.0', '61.0', '4.1'], ['valdemurio', 'trubia', 'quirós', 'gravity', '40.15', '119.0', '196.0', '1.43', '1.43'], ['valduno ii', 'nalón', 'las regueras', 'gravity', '9.9', '105.0', '2500.0', '34.36', '0.3'], ['valle', 'valle', 'somiedo', 'gravity', '12.5', '52.8', '39.0', '23.7', '3.7']] |
amy alcott | https://en.wikipedia.org/wiki/Amy_Alcott | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1629086-4.html.csv | majority | amy alcott won the nabisco dinah shore major championship more often than any other major competition she was in . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nabisco dinah shore', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'championship', 'nabisco dinah shore'], 'result': True, 'ind': 0, 'tointer': 'for the championship records of all rows , most of them fuzzily match to nabisco dinah shore .', 'tostr': 'most_eq { all_rows ; championship ; nabisco dinah shore } = true'} | most_eq { all_rows ; championship ; nabisco dinah shore } = true | for the championship records of all rows , most of them fuzzily match to nabisco dinah shore . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'championship_3': 3, 'nabisco dinah shore_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'championship_3': 'championship', 'nabisco dinah shore_4': 'nabisco dinah shore'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'championship_3': [0], 'nabisco dinah shore_4': [0]} | ['year', 'championship', 'winning score', 'margin', 'runner ( s ) - up'] | [['1979', 'peter jackson classic', '7 ( 75 + 70 + 70 + 70 = 285 )', '3 strokes', 'nancy lopez'], ['1980', "us women 's open", '4 ( 70 + 70 + 68 + 72 = 280 )', '9 strokes', 'hollis stacy'], ['1983', 'nabisco dinah shore', '6 ( 70 + 70 + 70 + 72 = 282 )', '2 strokes', 'beth daniel , kathy whitworth'], ['1988', 'nabisco dinah shore', '14 ( 71 + 66 + 66 + 71 = 274 )', '2 strokes', 'colleen walker'], ['1991', 'nabisco dinah shore', '15 ( 67 + 70 + 68 + 68 = 273 )', '8 strokes', 'dottie mochrie']] |
katie taylor | https://en.wikipedia.org/wiki/Katie_Taylor | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12426364-1.html.csv | ordinal | the second tournament that katie taylor played in was in warsaw , poland . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 2 }'}, 'venue'], 'result': 'warsaw , poland', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 2 } ; venue }'}, 'warsaw , poland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 2 } ; venue } ; warsaw , poland } = true', 'tointer': 'select the row whose year record of all rows is 2nd minimum . the venue record of this row is warsaw , poland .'} | eq { hop { nth_argmin { all_rows ; year ; 2 } ; venue } ; warsaw , poland } = true | select the row whose year record of all rows is 2nd minimum . the venue record of this row is warsaw , poland . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'venue_7': 7, 'warsaw , poland_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'year_5': 'year', '2_6': '2', 'venue_7': 'venue', 'warsaw , poland_8': 'warsaw , poland'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'venue_7': [1], 'warsaw , poland_8': [2]} | ['year', 'tournament', 'venue', 'result', 'event'] | [['2005', 'european amateur championships', 'tãnsberg , norway', '1st', '60 kg'], ['2006', 'european amateur championships', 'warsaw , poland', '1st', '60 kg'], ['2006', 'world amateur championship', 'new delhi , india', '1st', '60 kg'], ['2007', 'european amateur championships', 'vejle , denmark', '1st', '60 kg'], ['2008', 'european union amateur championships', 'liverpool , england', '1st', '60 kg'], ['2008', 'world amateur championship', "ningbo , people 's republic of china", '1st', '60 kg'], ['2009', 'european union amateur championships', 'pazardzhik , bulgaria', '1st', '60 kg'], ['2009', 'russian multi - nations event', 'st petersburg , russia', '1st', '60 kg'], ['2009', 'european amateur championships', 'mykolaiv , ukraine', '1st', '60 kg'], ['2010', 'european union amateur championships', 'keszthely , hungary', '1st', '60 kg'], ['2010', 'world amateur championship', 'barbados', '1st', '60 kg'], ['2011', 'european union amateur championships', 'katowice , poland', '1st', '60 kg'], ['2011', 'european amateur championships', 'rotterdam , netherlands', '1st', '60 kg'], ['2012', 'world amateur championship', 'qinhuangdao , china', '1st', '60 kg'], ['2012', 'olympic games', 'london , united kingdom', '1st', '60 kg'], ['2013', 'european union amateur championships', 'keszthely , hungary', '1st', '60 kg']] |
fred astaire chronology of performances | https://en.wikipedia.org/wiki/Fred_Astaire_chronology_of_performances | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15186990-4.html.csv | count | in three of fred astaire 's performances , he played the role of guy holden . | {'scope': 'all', 'criterion': 'equal', 'value': 'guy holden', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'role', 'guy holden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose role record fuzzily matches to guy holden .', 'tostr': 'filter_eq { all_rows ; role ; guy holden }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; role ; guy holden } }', 'tointer': 'select the rows whose role record fuzzily matches to guy holden . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; role ; guy holden } } ; 3 } = true', 'tointer': 'select the rows whose role record fuzzily matches to guy holden . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; role ; guy holden } } ; 3 } = true | select the rows whose role record fuzzily matches to guy holden . 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, 'role_5': 5, 'guy holden_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', 'role_5': 'role', 'guy holden_6': 'guy holden', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'role_5': [0], 'guy holden_6': [0], '3_7': [2]} | ['date', 'theatre , studio , or network', 'role', 'dance partner', 'director'] | [['june 3 , 1931', 'new amsterdam', 'himself', 'adele astaire tilly losch', 'hassard short'], ['nov 29 1932', 'ethel barrymore', 'guy holden', 'claire luce', 'howard lindsay'], ['nov 2 1933', 'palace', 'guy holden', 'claire luce', 'felix edwardes'], ['dec 2 , 1933', 'mgm', 'himself', 'joan crawford', 'robert z leonard'], ['dec 20 , 1933', 'rko', 'fred ayres', 'dolores del río ginger rogers', 'thornton freeland'], ['oct 3 , 1934', 'rko', 'guy holden', 'ginger rogers', 'mark sandrich'], ['feb 12 , 1935', 'rko', 'huckleberry haines', 'ginger rogers', 'william a seiter'], ['aug 12 1935', 'nbc', 'himself', '-', '-'], ['aug 16 , 1935', 'rko', 'jerry travers', 'ginger rogers', 'mark sandrich'], ['feb 19 , 1936', 'rko', 'bake baker', 'ginger rogers', 'mark sandrich'], ['aug 26 , 1936', 'rko', 'lucky garnett', 'ginger rogers', 'george stevens'], ['sept 15 1936', 'nbc', 'himself ( host )', '-', '-'], ['apr 30 , 1937', 'rko', 'peter p peters', 'ginger rogers', 'mark sandrich'], ['nov 20 , 1937', 'rko', 'jerry halliday', 'george burns & gracie allen joan fontaine', 'george stevens'], ['aug 30 , 1938', 'rko', 'tony flagg', 'ginger rogers', 'mark sandrich'], ['jan 15 1939', 'nbc', '-', '-', '-'], ['mar 31 , 1939', 'rko', 'vernon castle', 'ginger rogers', 'hc potter'], ['feb 14 , 1940', 'mgm', 'johnny brett', 'eleanor powell george murphy', 'norman taurog'], ['dec 3 , 1940', 'paramount', "danny o'neill", 'paulette goddard', 'hc potter']] |
three rivers conference ( indiana ) | https://en.wikipedia.org/wiki/Three_Rivers_Conference_%28Indiana%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15176211-1.html.csv | majority | the majority of schools in the three rivers conference have an aa ihsaa class . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'aa', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'ihsaa class', 'aa'], 'result': True, 'ind': 0, 'tointer': 'for the ihsaa class records of all rows , most of them fuzzily match to aa .', 'tostr': 'most_eq { all_rows ; ihsaa class ; aa } = true'} | most_eq { all_rows ; ihsaa class ; aa } = true | for the ihsaa class records of all rows , most of them fuzzily match to aa . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'ihsaa class_3': 3, 'aa_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'ihsaa class_3': 'ihsaa class', 'aa_4': 'aa'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'ihsaa class_3': [0], 'aa_4': [0]} | ['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county', 'year joined', 'previous conference'] | [['manchester', 'north manchester', 'squires', '434', 'aa', '85 wabash', '1976', 'northern lakes'], ['northfield', 'wabash', 'norsemen', '380', 'aa', '85 wabash', '1971', 'none ( new school )'], ['north miami', 'denver', 'warriors', '348', 'a', '52 miami', '1971', 'mid - indiana'], ['rochester community', 'rochester', 'zebras', '615', 'aaa', '25 fulton', '1987', 'northern lakes'], ['southwood', 'wabash', 'knights', '427', 'aa', '85 wabash', '1976', 'mid - indiana'], ['tippecanoe valley', 'akron', 'vikings', '600', 'aaa', '43 kosciusko', '1976', 'independents'], ['wabash', 'wabash', 'apaches', '455', 'aa', '85 wabash', '2006', 'central indiana'], ['whitko', 'south whitley', 'wildcats', '613', 'aa', '92 whitley', '1976', 'independents']] |
mikael pernfors | https://en.wikipedia.org/wiki/Mikael_Pernfors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1828774-4.html.csv | majority | in almost all of the matches mikael perfors played on a had surface , he was the winner of the match . | {'scope': 'subset', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'winner', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'hard'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; hard }', 'tointer': 'select the rows whose surface record fuzzily matches to hard .'}, 'outcome', 'winner'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to hard . for the outcome records of these rows , most of them fuzzily match to winner .', 'tostr': 'most_eq { filter_eq { all_rows ; surface ; hard } ; outcome ; winner } = true'} | most_eq { filter_eq { all_rows ; surface ; hard } ; outcome ; winner } = true | select the rows whose surface record fuzzily matches to hard . for the outcome records of these rows , most of them fuzzily match to winner . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'surface_4': 4, 'hard_5': 5, 'outcome_6': 6, 'winner_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'surface_4': 'surface', 'hard_5': 'hard', 'outcome_6': 'outcome', 'winner_7': 'winner'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'surface_4': [0], 'hard_5': [0], 'outcome_6': [1], 'winner_7': [1]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '26 may 1986', 'french open , paris , france', 'clay', 'ivan lendl', '3 - 6 , 2 - 6 , 4 - 6'], ['runner - up', '15 february 1988', 'memphis , usa', 'hard ( i )', 'andre agassi', '4 - 6 , 4 - 6 , 5 - 7'], ['winner', '19 september 1988', 'los angeles , usa', 'hard', 'andre agassi', '6 - 2 , 7 - 5'], ['winner', '3 october 1988', 'scottsdale , usa', 'hard', 'glenn layendecker', '6 - 2 , 6 - 4'], ['winner', '28 february 1993', 'montreal , canada', 'hard', 'todd martin', '2 - 6 , 6 - 2 , 7 - 5']] |
1983 formula one season | https://en.wikipedia.org/wiki/1983_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1140074-2.html.csv | comparative | in the 1983 formula one season , the italian grand prix took place 14 days before the european grand prix . | {'row_1': '13', 'row_2': '14', 'col': '3', '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', 'race', 'italian grand prix'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race record fuzzily matches to italian grand prix .', 'tostr': 'filter_eq { all_rows ; race ; italian grand prix }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; race ; italian grand prix } ; date }', 'tointer': 'select the rows whose race record fuzzily matches to italian grand prix . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'race', 'european grand prix'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose race record fuzzily matches to european grand prix .', 'tostr': 'filter_eq { all_rows ; race ; european grand prix }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; race ; european grand prix } ; date }', 'tointer': 'select the rows whose race record fuzzily matches to european grand prix . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; race ; italian grand prix } ; date } ; hop { filter_eq { all_rows ; race ; european grand prix } ; date } } = true', 'tointer': 'select the rows whose race record fuzzily matches to italian grand prix . take the date record of this row . select the rows whose race record fuzzily matches to european grand prix . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; race ; italian grand prix } ; date } ; hop { filter_eq { all_rows ; race ; european grand prix } ; date } } = true | select the rows whose race record fuzzily matches to italian grand prix . take the date record of this row . select the rows whose race record fuzzily matches to european grand prix . 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, 'race_7': 7, 'italian grand prix_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'race_11': 11, 'european grand prix_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', 'race_7': 'race', 'italian grand prix_8': 'italian grand prix', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'race_11': 'race', 'european grand prix_12': 'european grand prix', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'race_7': [0], 'italian grand prix_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'race_11': [1], 'european grand prix_12': [1], 'date_13': [3]} | ['rnd', 'race', 'date', 'location', 'pole position', 'fastest lap', 'race winner', 'constructor', 'report'] | [['1', 'brazilian grand prix', '13 march', 'jacarepaguá', 'keke rosberg', 'nelson piquet', 'nelson piquet', 'brabham - bmw', 'report'], ['2', 'united states grand prix west', '27 march', 'long beach', 'patrick tambay', 'niki lauda', 'john watson', 'mclaren - ford', 'report'], ['3', 'french grand prix', '17 april', 'paul ricard', 'alain prost', 'alain prost', 'alain prost', 'renault', 'report'], ['4', 'san marino grand prix', '1 may', 'imola', 'rené arnoux', 'riccardo patrese', 'patrick tambay', 'ferrari', 'report'], ['5', 'monaco grand prix', '15 may', 'monaco', 'alain prost', 'nelson piquet', 'keke rosberg', 'williams - ford', 'report'], ['6', 'belgian grand prix', '22 may', 'spa - francorchamps', 'alain prost', 'andrea de cesaris', 'alain prost', 'renault', 'report'], ['7', 'detroit grand prix', '5 june', 'detroit', 'rené arnoux', 'john watson', 'michele alboreto', 'tyrrell - ford', 'report'], ['8', 'canadian grand prix', '12 june', 'circuit gilles villeneuve', 'rené arnoux', 'patrick tambay', 'rené arnoux', 'ferrari', 'report'], ['9', 'british grand prix', '16 july', 'silverstone', 'rené arnoux', 'alain prost', 'alain prost', 'renault', 'report'], ['10', 'german grand prix', '7 august', 'hockenheimring', 'patrick tambay', 'rené arnoux', 'rené arnoux', 'ferrari', 'report'], ['11', 'austrian grand prix', '14 august', 'österreichring', 'patrick tambay', 'alain prost', 'alain prost', 'renault', 'report'], ['12', 'dutch grand prix', '28 august', 'zandvoort', 'nelson piquet', 'rené arnoux', 'rené arnoux', 'ferrari', 'report'], ['13', 'italian grand prix', '11 september', 'monza', 'riccardo patrese', 'nelson piquet', 'nelson piquet', 'brabham - bmw', 'report'], ['14', 'european grand prix', '25 september', 'brands hatch', 'elio de angelis', 'nigel mansell', 'nelson piquet', 'brabham - bmw', 'report']] |
budjak | https://en.wikipedia.org/wiki/Budjak | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1138646-1.html.csv | ordinal | in budjak , more people live in the city of izmayil ( 85100 ) than any other district or city . | {'row': '10', 'col': '2', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'total', '1'], 'result': '85100', 'ind': 0, 'tostr': 'nth_max { all_rows ; total ; 1 }', 'tointer': 'the 1st maximum total record of all rows is 85100 .'}, '85100'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; total ; 1 } ; 85100 }', 'tointer': 'the 1st maximum total record of all rows is 85100 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; total ; 1 }'}, 'raion ( district ) or city'], 'result': 'city of izmayil', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; total ; 1 } ; raion ( district ) or city }'}, 'city of izmayil'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 1 } ; raion ( district ) or city } ; city of izmayil }', 'tointer': 'the raion ( district ) or city record of the row with 1st maximum total record is city of izmayil .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; total ; 1 } ; 85100 } ; eq { hop { nth_argmax { all_rows ; total ; 1 } ; raion ( district ) or city } ; city of izmayil } } = true', 'tointer': 'the 1st maximum total record of all rows is 85100 . the raion ( district ) or city record of the row with 1st maximum total record is city of izmayil .'} | and { eq { nth_max { all_rows ; total ; 1 } ; 85100 } ; eq { hop { nth_argmax { all_rows ; total ; 1 } ; raion ( district ) or city } ; city of izmayil } } = true | the 1st maximum total record of all rows is 85100 . the raion ( district ) or city record of the row with 1st maximum total record is city of izmayil . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'total_8': 8, '1_9': 9, '85100_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'total_12': 12, '1_13': 13, 'raion (district) or city_14': 14, 'city of izmayil_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'total_8': 'total', '1_9': '1', '85100_10': '85100', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'total_12': 'total', '1_13': '1', 'raion (district) or city_14': 'raion ( district ) or city', 'city of izmayil_15': 'city of izmayil'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'total_8': [0], '1_9': [0], '85100_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'total_12': [2], '1_13': [2], 'raion (district) or city_14': [3], 'city of izmayil_15': [4]} | ['raion ( district ) or city', 'total', 'ukrainians', 'moldovans', 'bessarabian bulgarians', 'russians', 'gagauzians', 'other ethnic groups square'] | [['artsyzskyi raion', '51700', '14200', '3300', '20200', '11500', '900', '1600'], ['bilhorod - dnistrovskyi raion', '62300', '51000', '3900', '800', '5500', '200', '900'], ['bolhradskyi raion', '75000', '5700', '1200', '45600', '6000', '14000', '2500'], ['izmayilskyi raion', '54700', '15800', '15100', '14100', '8900', '200', '600'], ['kiliyskyi raion', '59800', '26700', '9400', '2600', '18000', '2300', '800'], ['reniyskyi raion', '40700', '7200', '19900', '3400', '6100', '3200', '900'], ['saratskyi raion', '49900', '21900', '9400', '10000', '7900', '200', '500'], ['tarutynskyi raion', '45 200', '11100', '7500', '17000', '6300', '2700', '600'], ['tatarbunarskyi raion', '41700', '29700', '3900', '4800', '2700', '-', '600'], ['city of izmayil', '85100', '32500', '3700', '8600', '37200', '800', '2300'], ['city of bilhorod - dnistrovskyi', '51100', '32200', '1000', '1900', '14400', '200', '1400'], ['total', '617200 1', '248000 1', '78300 1 square', '129000 1', '124500 1', '24700 1', '12700 1']] |
fantasy black channel | https://en.wikipedia.org/wiki/Fantasy_Black_Channel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17637041-2.html.csv | superlative | the last time that fantasy black channel was released in 2008 was on september 4 , 2008 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': '2008'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '2008'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 2008 }', 'tointer': 'select the rows whose date record fuzzily matches to 2008 .'}, 'date'], 'result': '4 september 2008', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; date ; 2008 } ; date }', 'tointer': 'select the rows whose date record fuzzily matches to 2008 . the maximum date record of these rows is 4 september 2008 .'}, '4 september 2008'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; date ; 2008 } ; date } ; 4 september 2008 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 2008 . the maximum date record of these rows is 4 september 2008 .'} | eq { max { filter_eq { all_rows ; date ; 2008 } ; date } ; 4 september 2008 } = true | select the rows whose date record fuzzily matches to 2008 . the maximum date record of these rows is 4 september 2008 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '2008_6': 6, 'date_7': 7, '4 september 2008_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '2008_6': '2008', 'date_7': 'date', '4 september 2008_8': '4 september 2008'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '2008_6': [0], 'date_7': [1], '4 september 2008_8': [2]} | ['region', 'date', 'label', 'format ( s )', 'catalog'] | [['japan', '30 july 2008', 'toshiba emi', 'cd', 'tocp - 66797'], ['united kingdom and ireland', '4 august 2008', 'parlophone', 'lp', '228 0331'], ['united kingdom and ireland', '11 august 2008', 'parlophone', 'cd , digital download', '228 0342'], ['france', '4 september 2008', 'because music', 'cd', 'bec 5772361'], ['united states', '13 january 2009', 'astralwerks', 'lp', 'asw 28033'], ['united states', '13 january 2009', 'astralwerks', 'cd , digital download', 'asw 37034']] |
kslt | https://en.wikipedia.org/wiki/KSLT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10044708-2.html.csv | majority | all of the kslt radio channels belong to the d broadcast station class . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'd', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'class', 'd'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , all of them fuzzily match to d .', 'tostr': 'all_eq { all_rows ; class ; d } = true'} | all_eq { all_rows ; class ; d } = true | for the class records of all rows , all of them fuzzily match to d . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, 'd_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', 'd_4': 'd'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], 'd_4': [0]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['k276dl', '103.1', 'hemingford , nebraska', '80', 'd', 'fcc'], ['k276dm', '103.1', 'chadron , nebraska', '5', 'd', 'fcc'], ['k292ec', '106.3', 'hot springs , south dakota', '68', 'd', 'fcc'], ['k292dn', '106.3', 'newcastle , wyoming', '31', 'd', 'fcc'], ['k292dz', '106.3', 'sheridan , wyoming', '135', 'd', 'fcc'], ['k296ds', '107.1', 'alliance , nebraska', '74', 'd', 'fcc']] |
the midlands , england | https://en.wikipedia.org/wiki/The_Midlands%2C_England | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184077-2.html.csv | majority | most of the clubs in the midlands , england play in the aviva premiership league . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'aviva premiership', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'league', 'aviva premiership'], 'result': True, 'ind': 0, 'tointer': 'for the league records of all rows , most of them fuzzily match to aviva premiership .', 'tostr': 'most_eq { all_rows ; league ; aviva premiership } = true'} | most_eq { all_rows ; league ; aviva premiership } = true | for the league records of all rows , most of them fuzzily match to aviva premiership . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'league_3': 3, 'aviva premiership_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'league_3': 'league', 'aviva premiership_4': 'aviva premiership'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'league_3': [0], 'aviva premiership_4': [0]} | ['club', 'league', 'city / town', 'stadium', 'capacity'] | [['leicester tigers', 'aviva premiership', 'leicester', 'welford road', '24000'], ['northampton saints', 'aviva premiership', 'northampton', "franklin 's gardens", '13600'], ['worcester warriors', 'aviva premiership', 'worcester', 'sixways stadium', '12068'], ['moseley', 'rfu championship', 'birmingham', 'billesley common', '3000'], ['nottingham', 'rfu championship', 'nottingham', 'meadow lane', '19588']] |
anna thompson ( athlete ) | https://en.wikipedia.org/wiki/Anna_Thompson_%28athlete%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17218317-1.html.csv | aggregation | anna thompson averaged at 10.15 th place across all the given tournaments . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '10.15 th', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'result'], 'result': '10.15 th', 'ind': 0, 'tostr': 'avg { all_rows ; result }'}, '10.15 th'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; result } ; 10.15 th } = true', 'tointer': 'the average of the result record of all rows is 10.15 th .'} | round_eq { avg { all_rows ; result } ; 10.15 th } = true | the average of the result record of all rows is 10.15 th . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'result_4': 4, '10.15th_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'result_4': 'result', '10.15th_5': '10.15 th'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'result_4': [0], '10.15th_5': [1]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['2002', 'commonwealth games', 'manchester , england', '9th', '5000 m'], ['2002', 'world cross country championships', 'dublin , ireland', '15th', 'short race'], ['2002', 'world cross country championships', 'dublin , ireland', '5th', 'team competition'], ['2005', 'world cross country championships', 'st etienne , france', '19th', 'short race'], ['2005', 'world cross country championships', 'st etienne , france', '7th', 'team competition'], ['2005', 'world cross country championships', 'st etienne , france', '16th', 'long race'], ['2005', 'world cross country championships', 'st etienne , france', '8th', 'team competition'], ['2006', 'commonwealth games', 'melbourne , australia', '5th', '10000 m'], ['2006', 'world cross country championships', 'fukuoka , japan', '3rd', 'team competition'], ['2006', 'world road running championships', 'debrecen , hungary', '18th', '20 km run'], ['2007', 'world cross country championships', 'mombasa , kenya', '18th', 'senior race'], ['2007', 'world cross country championships', 'mombasa , kenya', '6th', 'team competition'], ['2008', 'world cross country championships', 'edinburgh , scotland', '3rd', 'team competition']] |
1939 vfl season | https://en.wikipedia.org/wiki/1939_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806852-6.html.csv | superlative | the game played between carlton and richmond in round 6 of the 1939 vfl season had the highest attendance of all the games played in that round . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,3', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'home team'], 'result': 'carlton', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; home team }'}, 'carlton'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; home team } ; carlton }', 'tointer': 'select the row whose crowd record of all rows is maximum . the home team record of this row is carlton .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'away team'], 'result': 'richmond', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; crowd } ; away team }'}, 'richmond'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; away team } ; richmond }', 'tointer': 'the away team record of this row is richmond .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { hop { argmax { all_rows ; crowd } ; home team } ; carlton } ; eq { hop { argmax { all_rows ; crowd } ; away team } ; richmond } } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the home team record of this row is carlton . the away team record of this row is richmond .'} | and { eq { hop { argmax { all_rows ; crowd } ; home team } ; carlton } ; eq { hop { argmax { all_rows ; crowd } ; away team } ; richmond } } = true | select the row whose crowd record of all rows is maximum . the home team record of this row is carlton . the away team record of this row is richmond . | 7 | 6 | {'and_5': 5, 'result_6': 6, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_7': 7, 'crowd_8': 8, 'home team_9': 9, 'carlton_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'away team_11': 11, 'richmond_12': 12} | {'and_5': 'and', 'result_6': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_7': 'all_rows', 'crowd_8': 'crowd', 'home team_9': 'home team', 'carlton_10': 'carlton', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'away team_11': 'away team', 'richmond_12': 'richmond'} | {'and_5': [6], 'result_6': [], 'str_eq_2': [5], 'str_hop_1': [2], 'argmax_0': [1, 3], 'all_rows_7': [0], 'crowd_8': [0], 'home team_9': [1], 'carlton_10': [2], 'str_eq_4': [5], 'str_hop_3': [4], 'away team_11': [3], 'richmond_12': [4]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '19.23 ( 137 )', 'south melbourne', '3.12 ( 30 )', 'mcg', '16523', '27 may 1939'], ['collingwood', '14.14 ( 98 )', 'hawthorn', '12.7 ( 79 )', 'victoria park', '15000', '27 may 1939'], ['carlton', '8.13 ( 61 )', 'richmond', '9.14 ( 68 )', 'princes park', '34000', '27 may 1939'], ['st kilda', '16.18 ( 114 )', 'geelong', '10.16 ( 76 )', 'junction oval', '17000', '27 may 1939'], ['footscray', '11.13 ( 79 )', 'fitzroy', '15.10 ( 100 )', 'western oval', '13000', '27 may 1939'], ['north melbourne', '15.11 ( 101 )', 'essendon', '13.10 ( 88 )', 'arden street oval', '14500', '27 may 1939']] |
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 | superlative | of the ten top-ranked countries in world tourism , uruguay saw the highest percentage growth of tourist arrivals from 2010 to 2011 . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '10', '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', 'change ( 2010 to 2011 )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; change ( 2010 to 2011 ) }'}, 'country'], 'result': 'uruguay', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; change ( 2010 to 2011 ) } ; country }'}, 'uruguay'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; change ( 2010 to 2011 ) } ; country } ; uruguay } = true', 'tointer': 'select the row whose change ( 2010 to 2011 ) record of all rows is maximum . the country record of this row is uruguay .'} | eq { hop { argmax { all_rows ; change ( 2010 to 2011 ) } ; country } ; uruguay } = true | select the row whose change ( 2010 to 2011 ) record of all rows is maximum . the country record of this row is uruguay . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'change (2010 to 2011)_5': 5, 'country_6': 6, 'uruguay_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'change (2010 to 2011)_5': 'change ( 2010 to 2011 )', 'country_6': 'country', 'uruguay_7': 'uruguay'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'change (2010 to 2011)_5': [0], 'country_6': [1], 'uruguay_7': [2]} | ['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 %']] |
ken schrader | https://en.wikipedia.org/wiki/Ken_Schrader | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1671401-2.html.csv | superlative | the highest amount of earnings for ken schrader came in the year 2006 . | {'scope': 'all', 'col_superlative': '9', 'row_superlative': '15', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'winnings'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; winnings }'}, 'year'], 'result': '2006', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; winnings } ; year }'}, '2006'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; winnings } ; year } ; 2006 } = true', 'tointer': 'select the row whose winnings record of all rows is maximum . the year record of this row is 2006 .'} | eq { hop { argmax { all_rows ; winnings } ; year } ; 2006 } = true | select the row whose winnings record of all rows is maximum . the year record of this row is 2006 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'winnings_5': 5, 'year_6': 6, '2006_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'winnings_5': 'winnings', 'year_6': 'year', '2006_7': '2006'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'winnings_5': [0], 'year_6': [1], '2006_7': [2]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1987', '1', '0', '1', '1', '0', '21.0', '5.0', '1825', '83rd', 'ken schrader racing'], ['1988', '10', '0', '2', '3', '0', '16.3', '20.1', '45175', '33rd', 'ken schrader racing'], ['1989', '11', '1', '1', '6', '1', '14.3', '17.6', '27577', '32nd', 'ken schrader racing hendrick motorsports'], ['1990', '11', '0', '1', '2', '0', '20.2', '24.1', '22860', '37th', 'ken schrader racing'], ['1991', '10', '0', '4', '5', '0', '14.0', '16.3', '57345', '35th', 'ken schrader racing darrell waltrip motorsports'], ['1992', '10', '0', '2', '6', '0', '18.8', '11.9', '48352', '29th', 'ken schrader racing ernie irvan racing'], ['1993', '9', '0', '2', '3', '1', '9.0', '15.8', '65628', '35th', 'ken schrader racing'], ['1994', '10', '1', '3', '3', '0', '20.5', '18.2', '68700', '38th', 'ken schrader racing'], ['1995', '9', '0', '2', '4', '0', '25.8', '18.8', '66605', '40th', 'ken schrader racing'], ['1998', '10', '0', '0', '3', '0', '20.7', '22.0', '68920', '46th', 'andy petree racing'], ['1999', '12', '0', '0', '3', '3', '12.1', '19.8', '148480', '42nd', 'andy petree racing'], ['2000', '1', '0', '0', '0', '0', '38.0', '43.0', '15000', '117th', 'team amick motorsports'], ['2001', '1', '0', '0', '0', '0', '11.0', '39.0', '13320', '139th', 'ken schrader racing'], ['2002', '2', '0', '0', '0', '0', '27.5', '38.0', '31000', '98th', 'ken schrader racing'], ['2006', '8', '0', '0', '0', '0', '21.5', '26.8', '197127', '59th', 'brewco motorsports']] |
northern indiana athletic conference | https://en.wikipedia.org/wiki/Northern_Indiana_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12264570-1.html.csv | ordinal | the third to last team to join the northern indiana athletic conference was south bend clay . | {'row': '6', 'col': '6', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'joined', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; joined ; 3 }'}, 'school'], 'result': 'south bend clay', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; joined ; 3 } ; school }'}, 'south bend clay'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; joined ; 3 } ; school } ; south bend clay } = true', 'tointer': 'select the row whose joined record of all rows is 3rd maximum . the school record of this row is south bend clay .'} | eq { hop { nth_argmax { all_rows ; joined ; 3 } ; school } ; south bend clay } = true | select the row whose joined record of all rows is 3rd maximum . the school record of this row is south bend clay . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'joined_5': 5, '3_6': 6, 'school_7': 7, 'south bend clay_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', 'joined_5': 'joined', '3_6': '3', 'school_7': 'school', 'south bend clay_8': 'south bend clay'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'joined_5': [0], '3_6': [0], 'school_7': [1], 'south bend clay_8': [2]} | ['school', 'location', 'mascot', 'county', 'enrollment ihsaa class', 'joined', 'previous conference'] | [['elkhart central', 'elkhart', 'blue blazers', '20 elkhart', '1747 aaaa', '1927', 'independents'], ['mishawaka', 'mishawaka', 'cavemen', '71 st joseph', '1761 aaaa', '1927', 'independents'], ['mishawaka marian', 'mishawaka', 'knights', '71 st joseph', '768 aaa', '2005', 'independents'], ['penn', 'mishawaka', 'kingsmen', '71 st joseph', '3222 aaaa', '1977', 'independents'], ['south bend adams', 'south bend', 'eagles', '71 st joseph', '1773 aaaa', '1941', 'none ( new school )'], ['south bend clay', 'south bend', 'colonials', '71 st joseph', '1466 aaaa', '1979', 'independents'], ['south bend riley', 'south bend', 'wildcats', '71 st joseph', '1511 aaaa', '1931', 'none ( new school )'], ["south bend st joseph 's", 'south bend', 'indians', '71 st joseph', '793 aaa', '2005', 'independents'], ['south bend washington', 'south bend', 'panthers', '71 st joseph', '1428 aaaa', '1938', 'none ( new school )']] |
international rankings of iran | https://en.wikipedia.org/wiki/International_rankings_of_Iran | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15733308-7.html.csv | comparative | the happy planet index ranked three points higher than the environmental performance index in the international rankings of iran . | {'row_1': '4', 'row_2': '5', 'col': '2', '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', 'name', 'happy planet index'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to happy planet index .', 'tostr': 'filter_eq { all_rows ; name ; happy planet index }'}, 'rank'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; happy planet index } ; rank }', 'tointer': 'select the rows whose name record fuzzily matches to happy planet index . take the rank record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'environmental performance index'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to environmental performance index .', 'tostr': 'filter_eq { all_rows ; name ; environmental performance index }'}, 'rank'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; environmental performance index } ; rank }', 'tointer': 'select the rows whose name record fuzzily matches to environmental performance index . take the rank record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; happy planet index } ; rank } ; hop { filter_eq { all_rows ; name ; environmental performance index } ; rank } } = true', 'tointer': 'select the rows whose name record fuzzily matches to happy planet index . take the rank record of this row . select the rows whose name record fuzzily matches to environmental performance index . take the rank record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; happy planet index } ; rank } ; hop { filter_eq { all_rows ; name ; environmental performance index } ; rank } } = true | select the rows whose name record fuzzily matches to happy planet index . take the rank record of this row . select the rows whose name record fuzzily matches to environmental performance index . take the rank 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, 'happy planet index_8': 8, 'rank_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'environmental performance index_12': 12, 'rank_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', 'happy planet index_8': 'happy planet index', 'rank_9': 'rank', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'environmental performance index_12': 'environmental performance index', 'rank_13': 'rank'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'happy planet index_8': [0], 'rank_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'environmental performance index_12': [1], 'rank_13': [3]} | ['name', 'rank', 'out of', 'source', 'year'] | [['environmental sustainability index', '132', '146', 'yale university', '2005'], ['greenhouse emissions per capita', '74', 'world', 'world resources institute', '2000'], ['number of species under threat of extinction', '37', '158', 'united nations', '1999'], ['happy planet index', '81', '178', 'new economics foundation', '2009'], ['environmental performance index', '78', '153', 'yale university / columbia university', '2010'], ['total renewable water resources', '58', '151', 'cia world factbook', '2008'], ['water availability per capita', '116', '141', 'united nations', '2001'], ['biodiversity richness', '13', '53', 'world conservation monitoring centre', '1994'], ['carbon efficiency', '28', '141', 'carbon dioxide information analysis center', '2005'], ['coral reefs area', '19', '28', 'united nations', '2005'], ['endangered species protection', '71', '141', 'cites', '2000'], ['land use statistics by country', '16', '176', 'cia world factbook', '2005'], ['carbon dioxide emissions per capita', '70', '210', 'united nations', '2003'], ['total carbon dioxide emissions', '11', '210', 'united nations', '2006'], ['total forest area', '47', '220', 'united nations', '2007'], ['fresh water withdrawal', '11', '168', 'cia world factbook', '2000'], ['industrial water pollution', '14', '129', 'world bank', '2003']] |
national technical university of athens | https://en.wikipedia.org/wiki/National_Technical_University_of_Athens | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1064216-1.html.csv | ordinal | the school that has 18 lecturers has the 2nd highest number of total professors . | {'row': '5', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'lecturers'], 'result': '18', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; lecturers }'}, '18'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 2 } ; lecturers } ; 18 } = true', 'tointer': 'select the row whose total record of all rows is 2nd maximum . the lecturers record of this row is 18 .'} | eq { hop { nth_argmax { all_rows ; total ; 2 } ; lecturers } ; 18 } = true | select the row whose total record of all rows is 2nd maximum . the lecturers record of this row is 18 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, 'lecturers_7': 7, '18_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '2_6': '2', 'lecturers_7': 'lecturers', '18_8': '18'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'lecturers_7': [1], '18_8': [2]} | ['lecturers', 'associate professors', 'assistant professors', 'professors', 'total'] | [['5', '35', '27', '40', '120'], ['9', '10', '8', '58', '96'], ['12', '16', '17', '23', '81'], ['5', '12', '8', '20', '55'], ['18', '20', '9', '34', '119'], ['6', '13', '10', '48', '78'], ['7', '14', '5', '15', '49'], ['4', '10', '9', '14', '51'], ['2', '4', '8', '14', '28']] |
fiat albea | https://en.wikipedia.org/wiki/Fiat_Albea | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1415652-1.html.csv | majority | all fiat albea with 16 v engine has a power of at4000 rpm at least . | {'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': 'at4000 rpm', 'subset': {'col': '1', 'criterion': 'equal', 'value': '16 v'}} | {'func': 'all_greater_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', '16 v'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; engine ; 16 v }', 'tointer': 'select the rows whose engine record fuzzily matches to 16 v .'}, 'power', 'at4000 rpm'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose engine record fuzzily matches to 16 v . for the power records of these rows , all of them are greater than or equal to at4000 rpm .', 'tostr': 'all_greater_eq { filter_eq { all_rows ; engine ; 16 v } ; power ; at4000 rpm } = true'} | all_greater_eq { filter_eq { all_rows ; engine ; 16 v } ; power ; at4000 rpm } = true | select the rows whose engine record fuzzily matches to 16 v . for the power records of these rows , all of them are greater than or equal to at4000 rpm . | 2 | 2 | {'all_greater_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'engine_4': 4, '16 v_5': 5, 'power_6': 6, 'at4000 rpm_7': 7} | {'all_greater_eq_1': 'all_greater_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'engine_4': 'engine', '16 v_5': '16 v', 'power_6': 'power', 'at4000 rpm_7': 'at4000 rpm'} | {'all_greater_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'engine_4': [0], '16 v_5': [0], 'power_6': [1], 'at4000 rpm_7': [1]} | ['engine', 'type', 'displacement', 'power', 'torque'] | [['1.2 8v sohc', 'i4', '1242 cc', 'at5000 rpm', 'at2500 rpm'], ['1.2 16v dohc', 'i4', '1242 cc', 'at5000 rpm', 'at4000 rpm'], ['1.4 8v sohc', 'i4', '1368 cc', 'at6000 rpm', 'at3000 rpm'], ['1.6 16v dohc', 'i4', '1596 cc', 'at5750 rpm', 'at4000 rpm'], ['1.3 16v multijet', 'i4', '1248 cc', 'at4000 rpm', 'at1500 rpm']] |
harry hinton | https://en.wikipedia.org/wiki/Harry_Hinton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16877441-3.html.csv | aggregation | the average number of points for harry hinton was two . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '2', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '2', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '2'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 2 } = true', 'tointer': 'the average of the points record of all rows is 2 .'} | round_eq { avg { all_rows ; points } ; 2 } = true | the average of the points record of all rows is 2 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '2_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '2_5': '2'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '2_5': [1]} | ['year', 'class', 'team', 'points', 'wins'] | [['1949', '350cc', 'norton', '0', '0'], ['1949', '500cc', 'norton', '0', '0'], ['1950', '350cc', 'norton', '9', '0'], ['1950', '500cc', 'norton', '5', '0'], ['1951', '350cc', 'norton', '0', '0'], ['1958', '350cc', 'velocette', '0', '0'], ['1958', '500cc', 'norton', '0', '0']] |
henri leconte | https://en.wikipedia.org/wiki/Henri_Leconte | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1171445-5.html.csv | unique | the only time henri leconte played in the us was in memphis . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'memphis , us', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'championship', 'memphis , us'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose championship record fuzzily matches to memphis , us .', 'tostr': 'filter_eq { all_rows ; championship ; memphis , us }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; championship ; memphis , us } } = true', 'tointer': 'select the rows whose championship record fuzzily matches to memphis , us . there is only one such row in the table .'} | only { filter_eq { all_rows ; championship ; memphis , us } } = true | select the rows whose championship record fuzzily matches to memphis , us . 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, 'championship_4': 4, 'memphis, us_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'championship_4': 'championship', 'memphis, us_5': 'memphis , us'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'championship_4': [0], 'memphis, us_5': [0]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['winner', '1982', 'stockholm , sweden', 'hard ( i )', 'mats wilander', '7 - 6 ( 4 ) , 6 - 3'], ['runner - up', '1983', 'kitzbühel , austria', 'clay', 'guillermo vilas', '6 - 7 , 6 - 4 , 4 - 6'], ['runner - up', '1983', 'sydney indoor , australia', 'hard ( i )', 'john mcenroe', '1 - 6 , 4 - 6 , 5 - 7'], ['runner - up', '1984', 'memphis , us', 'carpet', 'jimmy connors', '3 - 6 , 6 - 4 , 5 - 7'], ['winner', '1984', 'stuttgart outdoor , germany', 'clay', 'gene mayer', '7 - 6 ( 9 ) , 6 - 0 , 1 - 6 , 6 - 1'], ['winner', '1985', 'nice , france', 'clay', 'víctor pecci', '6 - 4 , 6 - 4'], ['runner - up', '1985', 'sydney indoor , australia', 'hard ( i )', 'ivan lendl', '4 - 6 , 4 - 6 , 6 - 7 ( 6 )'], ['winner', '1985', 'sydney outdoor , australia', 'grass', 'kelly evernden', '6 - 7 ( 6 ) , 6 - 2 , 6 - 3'], ['runner - up', '1986', 'bristol , united kingdom', 'grass', 'vijay amritraj', '6 - 7 ( 6 ) , 6 - 1 , 6 - 8'], ['winner', '1986', 'geneva , switzerland', 'clay', 'thierry tulasne', '7 - 5 , 6 - 3'], ['winner', '1986', 'hamburg , germany', 'clay', 'miloslav mečíř', '6 - 2 , 5 - 7 , 6 - 4 , 6 - 2'], ['winner', '1988', 'nice , france', 'clay', 'jérôme potier', '6 - 2 , 6 - 2'], ['runner - up', '1988', 'hamburg , germany', 'clay', 'kent carlsson', '2 - 6 , 1 - 6 , 4 - 6'], ['runner - up', '1988', 'french open , paris', 'clay', 'mats wilander', '5 - 7 , 2 - 6 , 1 - 6'], ['winner', '1988', 'brussels , belgium', 'carpet', 'jakob hlasek', '7 - 6 ( 3 ) , 7 - 6 ( 6 ) , 6 - 4'], ['winner', '1993', 'halle , germany', 'grass', 'andriy medvedev', '6 - 2 , 6 - 3']] |
2008 - 09 oklahoma city thunder season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Oklahoma_City_Thunder_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17355628-5.html.csv | unique | game number 10 was the only game where the location was the wachovia center . | {'scope': 'all', 'row': '9', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': 'wachovia center', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'wachovia center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to wachovia center .', 'tostr': 'filter_eq { all_rows ; location attendance ; wachovia center }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location attendance ; wachovia center } }', 'tointer': 'select the rows whose location attendance record fuzzily matches to wachovia center . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'wachovia center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to wachovia center .', 'tostr': 'filter_eq { all_rows ; location attendance ; wachovia center }'}, 'game'], 'result': '10', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location attendance ; wachovia center } ; game }'}, '10'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location attendance ; wachovia center } ; game } ; 10 }', 'tointer': 'the game record of this unqiue row is 10 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location attendance ; wachovia center } } ; eq { hop { filter_eq { all_rows ; location attendance ; wachovia center } ; game } ; 10 } } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to wachovia center . there is only one such row in the table . the game record of this unqiue row is 10 .'} | and { only { filter_eq { all_rows ; location attendance ; wachovia center } } ; eq { hop { filter_eq { all_rows ; location attendance ; wachovia center } ; game } ; 10 } } = true | select the rows whose location attendance record fuzzily matches to wachovia center . there is only one such row in the table . the game record of this unqiue row is 10 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location attendance_7': 7, 'wachovia center_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'game_9': 9, '10_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location attendance_7': 'location attendance', 'wachovia center_8': 'wachovia center', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'game_9': 'game', '10_10': '10'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location attendance_7': [0], 'wachovia center_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'game_9': [2], '10_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['2', 'november 1', 'houston', 'l 77 - 89 ( ot )', 'kevin durant ( 26 )', 'earl watson ( 8 )', 'toyota center 16996', '0 - 2'], ['3', 'november 2', 'minnesota', 'w 88 - 85 ( ot )', 'kevin durant ( 18 )', 'earl watson ( 4 )', 'ford center 18163', '1 - 2'], ['4', 'november 5', 'boston', 'l 83 - 96 ( ot )', 'kevin durant ( 17 )', 'earl watson ( 5 )', 'ford center 19136', '1 - 3'], ['5', 'november 7', 'utah', 'l 97 - 104 ( ot )', 'kevin durant ( 24 )', 'kevin durant , earl watson ( 3 )', 'energysolutions arena 19911', '1 - 4'], ['6', 'november 9', 'atlanta', 'l 85 - 89 ( ot )', 'kevin durant ( 20 )', 'earl watson ( 6 )', 'ford center 18231', '1 - 5'], ['7', 'november 10', 'indiana', 'l 99 - 107 ( ot )', 'kevin durant ( 37 )', 'earl watson ( 9 )', 'conseco fieldhouse 10165', '1 - 6'], ['8', 'november 12', 'orlando', 'l 92 - 109 ( ot )', 'jeff green ( 25 )', 'earl watson ( 8 )', 'ford center 18185', '1 - 7'], ['9', 'november 14', 'new york', 'l 106 - 116 ( ot )', 'kevin durant ( 23 )', 'earl watson ( 8 )', 'madison square garden 18008', '1 - 8'], ['10', 'november 15', 'philadelphia', 'l 85 - 110 ( ot )', 'jeff green ( 21 )', 'jeff green , russell westbrook ( 4 )', 'wachovia center 13385', '1 - 9'], ['11', 'november 17', 'houston', 'l 89 - 100 ( ot )', 'kevin durant ( 29 )', 'kevin durant , earl watson ( 4 )', 'ford center 18145', '1 - 10'], ['12', 'november 19', 'la clippers', 'l 88 - 108 ( ot )', 'kevin durant ( 18 )', 'earl watson ( 5 )', 'ford center 18312', '1 - 11'], ['13', 'november 21', 'new orleans', 'l 80 - 105 ( ot )', 'kevin durant ( 17 )', 'earl watson ( 4 )', 'ford center 19136', '1 - 12'], ['14', 'november 22', 'new orleans', 'l 97 - 109 ( ot )', 'kevin durant ( 30 )', 'russell westbrook ( 11 )', 'new orleans arena 16023', '1 - 13'], ['15', 'november 25', 'phoenix', 'l 98 - 99 ( ot )', 'kevin durant ( 29 )', 'earl watson ( 13 )', 'ford center 19136', '1 - 14'], ['16', 'november 26', 'cleveland', 'l 82 - 117 ( ot )', 'chris wilcox ( 14 )', 'russell westbrook , kyle weaver ( 5 )', 'quicken loans arena 19753', '1 - 15'], ['17', 'november 28', 'minnesota', 'l 103 - 105 ( ot )', 'kevin durant , jeff green ( 22 )', 'russell westbrook ( 8 )', 'ford center 18229', '1 - 16'], ['18', 'november 29', 'memphis', 'w 111 - 103 ( ot )', 'kevin durant ( 30 )', 'earl watson ( 7 )', 'fedexforum 11977', '2 - 16']] |