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1996 ncaa women 's division i basketball tournament | https://en.wikipedia.org/wiki/1996_NCAA_Women%27s_Division_I_Basketball_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16679797-4.html.csv | count | during the 1996 ncaa women 's division i basketball tournament , in the east region , two times the game was held in virginia . | {'scope': 'subset', 'criterion': 'equal', 'value': 'virginia', 'result': '2', 'col': '5', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'east'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'east'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; region ; east }', 'tointer': 'select the rows whose region record fuzzily matches to east .'}, 'state', 'virg... | eq { count { filter_eq { filter_eq { all_rows ; region ; east } ; state ; virginia } } ; 2 } = true | select the rows whose region record fuzzily matches to east . among these rows , select the rows whose state record fuzzily matches to virginia . 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, 'region_6': 6, 'east_7': 7, 'state_8': 8, 'virginia_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', 'region_6': 'region', 'east_7': 'east', 'state_8': 'state', 'virginia_9': 'virginia', '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], 'region_6': [0], 'east_7': [0], 'state_8': [1], 'virginia_9': [1], '2_10': [3]} | ['region', 'host', 'venue', 'city', 'state'] | [['east', 'old dominion university', 'old dominion university fieldhouse', 'norfolk', 'virginia'], ['east', 'university of virginia', 'university hall ( university of virginia )', 'charlottesville', 'virginia'], ['east', 'university of tennessee', 'thompson - boling arena', 'knoxville', 'tennessee'], ['east', 'universi... |
1992 - 93 toronto maple leafs season | https://en.wikipedia.org/wiki/1992%E2%80%9393_Toronto_Maple_Leafs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13913477-5.html.csv | count | in the 1992 - 93 toronto maple leafs season , among the games where toronto was a home team , 2 of them had total points of 28 . | {'scope': 'subset', 'criterion': 'equal', 'value': '28', 'result': '2', 'col': '7', 'subset': {'col': '3', 'criterion': 'not_equal', 'value': 'toronto'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'visitor', 'toronto'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; visitor ; toronto }', 'tointer': 'select the rows whose visitor record does not match to toronto .'},... | eq { count { filter_eq { filter_not_eq { all_rows ; visitor ; toronto } ; points ; 28 } } ; 2 } = true | select the rows whose visitor record does not match to toronto . among these rows , select the rows whose points record is equal to 28 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_5': 5, 'visitor_6': 6, 'toronto_7': 7, 'points_8': 8, '28_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_5': 'all_rows', 'visitor_6': 'visitor', 'toronto_7': 'toronto', 'points_8': 'points', '28_9': '28', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_5': [0], 'visitor_6': [0], 'toronto_7': [0], 'points_8': [1], '28_9': [1], '2_10': [3]} | ['game', 'date', 'visitor', 'score', 'home', 'record', 'points'] | [['24', 'december 1', 'toronto', '3 - 8', 'new jersey', '11 - 10 - 3', '25'], ['25', 'december 3', 'toronto', '3 - 4', 'chicago', '11 - 11 - 3', '25'], ['26', 'december 5', 'chicago', '2 - 2', 'toronto', '11 - 11 - 4', '26'], ['27', 'december 6', 'toronto', '0 - 6', 'ny rangers', '11 - 12 - 4', '26'], ['28', 'december ... |
1962 oakland raiders season | https://en.wikipedia.org/wiki/1962_Oakland_Raiders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12676700-1.html.csv | unique | the oakland raiders game the took place on september 9 , 1962 is the onlt game during the 1962 season that resulted in a score of 28 - 17 . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': '28 - 17', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', '28 - 17'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to 28 - 17 .', 'tostr': 'filter_eq { all_rows ; result ; 28 - 17 }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; result ; 28 - 17 } } ; eq { hop { filter_eq { all_rows ; result ; 28 - 17 } ; date } ; september 9 , 1962 } } = true | select the rows whose result record fuzzily matches to 28 - 17 . there is only one such row in the table . the date record of this unqiue row is september 9 , 1962 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, '28 - 17_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'september 9 , 1962_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', '28 - 17_8': '28 - 17', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'september 9 , 1962_10': 'september 9 , 1962'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], '28 - 17_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'september 9 , 1962_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 9 , 1962', 'new york titans', 'l 28 - 17', '12893'], ['2', 'september 23 , 1962', 'dallas texans', 'l 26 - 16', '12500'], ['3', 'september 30 , 1962', 'san diego chargers', 'l 42 - 33', '13000'], ['4', 'october 5 , 1962', 'denver broncos', 'l 44 - 7', '22452'], ['5', 'october 14 , 1962', 'denver bronc... |
badminton at the pan american games | https://en.wikipedia.org/wiki/Badminton_at_the_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10371133-1.html.csv | superlative | canada won more gold medals in badminton at the pan american games than any other nation . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'gold'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; gold }'}, 'nation'], 'result': 'canada ( can )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; gold } ; nation }'}, 'canada ( can )'], 'result': True, 'ind': ... | eq { hop { argmax { all_rows ; gold } ; nation } ; canada ( can ) } = true | select the row whose gold record of all rows is maximum . the nation record of this row is canada ( can ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'gold_5': 5, 'nation_6': 6, 'canada (can)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'gold_5': 'gold', 'nation_6': 'nation', 'canada (can)_7': 'canada ( can )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'gold_5': [0], 'nation_6': [1], 'canada (can)_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'canada ( can )', '16', '16', '11', '43'], ['2', 'united states ( usa )', '7', '6', '12', '25'], ['3', 'guatemala ( gua )', '1', '2', '3', '6'], ['4', 'jamaica ( jam )', '1', '0', '5', '6'], ['5', 'cuba ( cub )', '0', '1', '0', '1'], ['6', 'peru ( per )', '0', '0', '14', '14'], ['7', 'mexico ( mex )', '0', '0', ... |
lard | https://en.wikipedia.org/wiki/Lard | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18621997-1.html.csv | superlative | suet has the highest level of saturated fat , at 55 % . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '10', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'saturated fat'], 'result': '52 g ( 55 % )', 'ind': 0, 'tostr': 'max { all_rows ; saturated fat }', 'tointer': 'the maximum saturated fat record of all rows is 52 g ( 55 % ) .'}, '52 g ( 55 % )'], 'result': True, 'ind': 1, 'tostr': 'e... | and { eq { max { all_rows ; saturated fat } ; 52 g ( 55 % ) } ; eq { hop { argmax { all_rows ; saturated fat } ; } ; suet } } = true | the maximum saturated fat record of all rows is 52 g ( 55 % ) . the record of the row with superlative saturated fat record is suet . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'saturated fat_8': 8, '52 g (55%)_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'saturated fat_11': 11, '_12': 12, 'suet_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'saturated fat_8': 'saturated fat', '52 g (55%)_9': '52 g ( 55 % )', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'saturated fat_11': 'saturated fat', '_12': '', 'suet_13': 'sue... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'saturated fat_8': [0], '52 g (55%)_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'saturated fat_11': [2], '_12': [3], 'suet_13': [4]} | ['', 'total fat', 'saturated fat', 'monounsaturated fat', 'polyunsaturated fat', 'smoke point'] | [['sunflower oil', '100 g', '11 g', '20 g ( 84 g in high oleic variety )', '69 g ( 4 g in high oleic variety )', 'degree'], ['soybean oil', '100 g', '16 g', '23 g', '58 g', 'degree'], ['canola oil', '100 g', '7 g', '63 g', '28 g', 'degree'], ['olive oil', '100 g', '14 g', '73 g', '11 g', 'degree'], ['corn oil', '100 g'... |
galicia , spain | https://en.wikipedia.org/wiki/Galicia%2C_Spain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12837-1.html.csv | aggregation | the average number of days with frost in galicia , spain , is 15.67 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '15.67', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'days with frost'], 'result': '15.67', 'ind': 0, 'tostr': 'avg { all_rows ; days with frost }'}, '15.67'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; days with frost } ; 15.67 } = true', 'tointer': 'the average of the days with fros... | round_eq { avg { all_rows ; days with frost } ; 15.67 } = true | the average of the days with frost record of all rows is 15.67 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'days with frost_4': 4, '15.67_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'days with frost_4': 'days with frost', '15.67_5': '15.67'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'days with frost_4': [0], '15.67_5': [1]} | ['city / town', 'july av t', 'rain', 'days with rain ( year / summer )', 'days with frost', 'sunlight hours'] | [['santiago de compostela', 'degree', 'mm ( in )', '141 / 19', '15', '1998'], ['a coruña', 'degree', 'mm ( in )', '131 / 19', '0', '1966'], ['lugo', 'degree', 'mm ( in )', '131 / 18', '42', '1821'], ['vigo', 'degree', 'mm ( in )', '130 / 18', '5', '2212'], ['ourense', 'degree', 'mm ( in )', '97 / 12', '30', '2043'], ['... |
2000 u.s. open ( golf ) | https://en.wikipedia.org/wiki/2000_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17128242-7.html.csv | count | 11 players participated in the 2000 u.s. open ( golf ) tournament . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '11', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'place'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose place record is arbitrary .', 'tostr': 'filter_all { all_rows ; place }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; place } }',... | eq { count { filter_all { all_rows ; place } } ; 11 } = true | select the rows whose place record is arbitrary . the number of such rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'place_5': 5, '11_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'place_5': 'place', '11_6': '11'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'place_5': [0], '11_6': [2]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'tiger woods', 'united states', '65 + 69 + 71 + 67 = 272', '- 12', '800000'], ['t2', 'miguel ángel jiménez', 'spain', '66 + 74 + 76 + 71 = 287', '+ 3', '391150'], ['t2', 'ernie els', 'south africa', '74 + 73 + 68 + 72 = 287', '+ 3', '391150'], ['4', 'john huston', 'united states', '67 + 75 + 76 + 70 = 288', '+ 4... |
catch me if you can ( musical ) | https://en.wikipedia.org/wiki/Catch_Me_If_You_Can_%28musical%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14779860-1.html.csv | majority | most of the awards catch me if you can was nominated for were drama desk awards . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'drama desk award', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'award ceremony', 'drama desk award'], 'result': True, 'ind': 0, 'tointer': 'for the award ceremony records of all rows , most of them fuzzily match to drama desk award .', 'tostr': 'most_eq { all_rows ; award ceremony ; drama desk award } = true'} | most_eq { all_rows ; award ceremony ; drama desk award } = true | for the award ceremony records of all rows , most of them fuzzily match to drama desk award . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'award ceremony_3': 3, 'drama desk award_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'award ceremony_3': 'award ceremony', 'drama desk award_4': 'drama desk award'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'award ceremony_3': [0], 'drama desk award_4': [0]} | ['year', 'award ceremony', 'category', 'nominee', 'result'] | [['2011', 'tony award', 'best musical', 'best musical', 'nominated'], ['2011', 'tony award', 'best performance by a leading actor in a musical', 'norbert leo butz', 'won'], ['2011', 'tony award', 'best sound design', 'steve canyon kennedy', 'nominated'], ['2011', 'tony award', 'best orchestrations', 'marc shaiman and l... |
largest gold companies | https://en.wikipedia.org/wiki/Largest_gold_companies | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24307126-3.html.csv | count | the united states has two of the largest gold companies . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'united states', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'base', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose base record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; base ; united states }'}], 'result': '2', 'ind': 1, 't... | eq { count { filter_eq { all_rows ; base ; united states } } ; 2 } = true | select the rows whose base record fuzzily matches to united states . 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, 'base_5': 5, 'united states_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', 'base_5': 'base', 'united states_6': 'united states', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'base_5': [0], 'united states_6': [0], '2_7': [2]} | ['april 2013 cum rank', 'name', 'rank 2012', 'rank 2013', 'base', '2013 rev ( bil usd )', '2013 profit ( mil usd )', 'assets 2013 ( bil )', 'market cap march 15 ( mil )'] | [['1', 'freeport - mcmoran', '235', '273', 'united states', '18.0', '3000', '35.4', '23100'], ['2', 'newmont mining', '639', '448', 'united states', '9.9', '1800', '29.6', '19700'], ['3', 'goldcorp', '507', '559', 'canada', '5.4', '1700', '31.2', '26400'], ['4', 'barrick gold', '225', '659', 'canada', '14.5', '( 700 )'... |
1984 washington redskins season | https://en.wikipedia.org/wiki/1984_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15085579-1.html.csv | ordinal | the washington redskins game played on december 9 , 1984 had the second highest attendance . | {'row': '15', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'december 9 , 1984', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}, ... | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; december 9 , 1984 } = true | select the row whose attendance record of all rows is 2nd maximum . the date record of this row is december 9 , 1984 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'december 9 , 1984_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'december 9 , 1984_8': 'december 9 , 1984'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'december 9 , 1984_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 2 , 1984', 'miami dolphins', 'l , 17 - 35', '52683'], ['2', 'september 10 , 1984', 'san francisco 49ers', 'l , 31 - 37', '59707'], ['3', 'september 16 , 1984', 'new york giants', 'w , 30 - 14', '52997'], ['4', 'september 23 , 1984', 'new england patriots', 'w , 26 - 10', '60503'], ['5', 'september 30 ... |
rustavi 2 | https://en.wikipedia.org/wiki/Rustavi_2 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1544974-1.html.csv | majority | majority of rustavi 2 series that have present finale can be watched monday to friday . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'monday to friday', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'present'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series finale', 'present'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; series finale ; present }', 'tointer': 'select the rows whose series finale record fuzzily matches to present .'}, 'weekly schedule', 'monday to friday'... | most_eq { filter_eq { all_rows ; series finale ; present } ; weekly schedule ; monday to friday } = true | select the rows whose series finale record fuzzily matches to present . for the weekly schedule records of these rows , most of them fuzzily match to monday to friday . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'series finale_4': 4, 'present_5': 5, 'weekly schedule_6': 6, 'monday to friday_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'series finale_4': 'series finale', 'present_5': 'present', 'weekly schedule_6': 'weekly schedule', 'monday to friday_7': 'monday to friday'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'series finale_4': [0], 'present_5': [0], 'weekly schedule_6': [1], 'monday to friday_7': [1]} | ['country', 'telenovela', 'translation', 'series premiere', 'series finale', 'weekly schedule', 'timeslot'] | [['mexico', 'mentir para vivir', 'ოჰ ეს ცრემლები / პარალელური საიდუმლო', 'september 2 , 2013', 'present', 'monday to friday', '10:10'], ['mexico', 'corazon indomable', 'კატური სულის საიდუმლო', 'june 24 , 2013', 'present', 'monday to friday', '10:55'], ['mexico', 'cachito de cielo', 'მცირე ნაწილი', 'october 7 , 2013', '... |
eurovision song contest 1970 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1970 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184813-1.html.csv | count | two of the songs had lyrics written in the english language . | {'scope': 'all', 'criterion': 'equal', 'value': 'english', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'language', 'english'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose language record fuzzily matches to english .', 'tostr': 'filter_eq { all_rows ; language ; english }'}], 'result': '2', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; language ; english } } ; 2 } = true | select the rows whose language record fuzzily matches to english . 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, 'language_5': 5, 'english_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', 'language_5': 'language', 'english_6': 'english', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'language_5': [0], 'english_6': [0], '2_7': [2]} | ['language', 'artist', 'song', 'place', 'points'] | [['dutch', 'hearts of soul', 'waterman', '7', '7'], ['french', 'henri dès', 'retour', '4', '8'], ['italian', 'gianni morandi', 'occhi di ragazza', '8', '5'], ['slovene', 'eva sršen', 'pridi , dala ti bom cvet', '11', '4'], ['french', 'jean vallée', "viens l'oublier", '8', '5'], ['french', 'guy bonnet', 'marie - blanche... |
list of festivals at donington park | https://en.wikipedia.org/wiki/List_of_Festivals_at_Donington_Park | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10311801-2.html.csv | unique | there was only one metallica concert that was held at donlington park . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'metallica', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'metallica'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to metallica .', 'tostr': 'filter_eq { all_rows ; event ; metallica }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_ro... | only { filter_eq { all_rows ; event ; metallica } } = true | select the rows whose event record fuzzily matches to metallica . 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, 'event_4': 4, 'metallica_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'event_4': 'event', 'metallica_5': 'metallica'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'event_4': [0], 'metallica_5': [0]} | ['year', 'date', 'event', 'days', 'stages', 'acts'] | [['1990', '18 august', 'monsters of rock', '1 day', '1 stage', '5 bands'], ['1991', '17 august', 'monsters of rock', '1 day', '1 stage', '5 bands'], ['1992', '2526 july', 'one step beyond', '24 hours', '1 stage', "60 + dj 's"], ['1992', '22 august', 'monsters of rock', '1 day', '1 stage', '6 bands'], ['1994', '4 june',... |
2008 north west 200 races | https://en.wikipedia.org/wiki/2008_North_West_200_Races | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17477518-2.html.csv | aggregation | the average speed among competitors in the 2008 north west 200 races was around 121.208 mph . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '121.208', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'speed'], 'result': '121.208', 'ind': 0, 'tostr': 'avg { all_rows ; speed }'}, '121.208'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; speed } ; 121.208 } = true', 'tointer': 'the average of the speed record of all rows is 121.208 .'... | round_eq { avg { all_rows ; speed } ; 121.208 } = true | the average of the speed record of all rows is 121.208 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'speed_4': 4, '121.208_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'speed_4': 'speed', '121.208_5': '121.208'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'speed_4': [0], '121.208_5': [1]} | ['rank', 'rider', 'team', 'time', 'speed'] | [['1', 'michael rutter', 'ducati', "21 ' 52.169", '122.609 mph'], ['2', 'guy martin', 'honda', '+ 0.810', '122.534 mph'], ['3', 'john mcguinness', 'honda', '+ 0.956', '122.510 mph'], ['4', 'steve plater', 'yamaha yzf - r', '+ 1.192', '121.658 mph'], ['5', 'gary johnson', 'honda', '+ 10.257', '120.979 mph'], ['6', 'bruc... |
football records in spain | https://en.wikipedia.org/wiki/Football_records_in_Spain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17937080-2.html.csv | superlative | the team that had the most goals in a season was real madrid . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'goals'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; goals }'}, 'club'], 'result': 'real madrid', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; goals } ; club }'}, 'real madrid'], 'result': True, 'ind': 2, 'tos... | eq { hop { argmax { all_rows ; goals } ; club } ; real madrid } = true | select the row whose goals record of all rows is maximum . the club record of this row is real madrid . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'goals_5': 5, 'club_6': 6, 'real madrid_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'goals_5': 'goals', 'club_6': 'club', 'real madrid_7': 'real madrid'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'goals_5': [0], 'club_6': [1], 'real madrid_7': [2]} | ['rank', 'club', 'season', 'goals', 'apps'] | [['1', 'real madrid', '2011 / 12', '121', '38'], ['2', 'barcelona', '2012 / 13', '115', '38'], ['3', 'barcelona', '2011 / 12', '114', '38'], ['4', 'real madrid', '1989 / 90', '107', '38'], ['5', 'barcelona', '2008 / 09', '105', '38'], ['6', 'real madrid', '2012 / 13', '103', '38'], ['7', 'real madrid', '2009 / 10', '10... |
mighty ships | https://en.wikipedia.org/wiki/Mighty_Ships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26168687-3.html.csv | aggregation | the average original air date for mighty ships is 2009 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '2009', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'original air date'], 'result': '2009', 'ind': 0, 'tostr': 'avg { all_rows ; original air date }'}, '2009'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; original air date } ; 2009 } = true', 'tointer': 'the average of the original ai... | round_eq { avg { all_rows ; original air date } ; 2009 } = true | the average of the original air date record of all rows is 2009 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'original air date_4': 4, '2009_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'original air date_4': 'original air date', '2009_5': '2009'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'original air date_4': [0], '2009_5': [1]} | ['no in series', 'no in season', 'title', 'vessel type', 'vessel operator', 'narrated by', 'original air date'] | [['5', '1', 'mv resolution', 'turbine installation vessel', 'mpi offshore ltd', 'barbara budd', '2009'], ['6', '2', 'mv peace in africa', 'dredger', 'de beers', 'barbara budd', '2009'], ['7', '3', 'akamalik', 'fishing trawler', 'royal greenland', 'barbara budd', '2009'], ['8', '4', 'ccgs henry larsen', 'icebreaker', 'c... |
2009 open championship | https://en.wikipedia.org/wiki/2009_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18811509-5.html.csv | unique | in the 2009 open championship , the only player from australia was mathew goggin . | {'scope': 'all', 'row': '11', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'australia', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'australia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to australia .', 'tostr': 'filter_eq { all_rows ; country ; australia }'}], 'result': True, 'ind': 1, 'tos... | and { only { filter_eq { all_rows ; country ; australia } } ; eq { hop { filter_eq { all_rows ; country ; australia } ; player } ; mathew goggin } } = true | select the rows whose country record fuzzily matches to australia . there is only one such row in the table . the player record of this unqiue row is mathew goggin . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'australia_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'mathew goggin_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'australia_8': 'australia', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'mathew goggin_10': 'mathew goggin'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'australia_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'mathew goggin_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'steve marino', 'united states', '67 + 68 = 135', '5'], ['t1', 'tom watson', 'united states', '65 + 70 = 135', '5'], ['3', 'mark calcavecchia', 'united states', '67 + 69 = 136', '4'], ['t4', 'ross fisher', 'england', '69 + 68 = 137', '3'], ['t4', 'retief goosen', 'south africa', '67 + 70 = 137', '3'], ['t4', 'm... |
1948 ashes series | https://en.wikipedia.org/wiki/1948_Ashes_series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16570286-4.html.csv | comparative | ray lindwall and bill johnston both got the same number of wickets in the 1948 ashes series . | {'row_1': '1', 'row_2': '4', 'col': '4', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'ray lindwall'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to ray lindwall .', 'tostr': 'filter_eq { all_rows ; player ; ray lindwall }'}, 'wickets'], 'result': N... | eq { hop { filter_eq { all_rows ; player ; ray lindwall } ; wickets } ; hop { filter_eq { all_rows ; player ; bill johnston } ; wickets } } = true | select the rows whose player record fuzzily matches to ray lindwall . take the wickets record of this row . select the rows whose player record fuzzily matches to bill johnston . take the wickets record of this row . the first record is equal to the second record . | 5 | 5 | {'eq_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'ray lindwall_8': 8, 'wickets_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'bill johnston_12': 12, 'wickets_13': 13} | {'eq_4': 'eq', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'ray lindwall_8': 'ray lindwall', 'wickets_9': 'wickets', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'bill joh... | {'eq_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'ray lindwall_8': [0], 'wickets_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'bill johnston_12': [1], 'wickets_13': [3]} | ['player', 'team', 'matches', 'wickets', 'average', 'best bowling'] | [['ray lindwall', 'australia', '5', '27', '19.62', '6 / 20'], ['norman yardley', 'england', '5', '9', '22.66', '2 / 32'], ['keith miller', 'australia', '5', '13', '23.15', '4 / 125'], ['bill johnston', 'australia', '5', '27', '23.33', '5 / 36'], ['ernie toshack', 'australia', '4', '11', '33.09', '5 / 40'], ['alec bedse... |
mystery of mamo | https://en.wikipedia.org/wiki/Mystery_of_Mamo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2160215-1.html.csv | count | for the mystery of mamo , when the english ( streamline ) is unknown , there were two instances where the english ( pioneer / geneon ) is richard cansino . | {'scope': 'subset', 'criterion': 'equal', 'value': 'richard cansino', 'result': '2', 'col': '5', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'unknown'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'english ( streamline )', 'unknown'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; english ( streamline ) ; unknown }', 'tointer': 'select the rows whose english ( streamlin... | eq { count { filter_eq { filter_eq { all_rows ; english ( streamline ) ; unknown } ; english ( pioneer / geneon ) ; richard cansino } } ; 2 } = true | select the rows whose english ( streamline ) record fuzzily matches to unknown . among these rows , select the rows whose english ( pioneer / geneon ) record fuzzily matches to richard cansino . 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, 'english ( streamline )_6': 6, 'unknown_7': 7, 'english ( pioneer / geneon )_8': 8, 'richard cansino_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', 'english ( streamline )_6': 'english ( streamline )', 'unknown_7': 'unknown', 'english ( pioneer / geneon )_8': 'english ( pioneer / geneon )', 'richard cansino_9': 'r... | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'english ( streamline )_6': [0], 'unknown_7': [0], 'english ( pioneer / geneon )_8': [1], 'richard cansino_9': [1], '2_10': [3]} | ['character', 'original japanese', 'english ( streamline )', 'english ( manga uk )', 'english ( pioneer / geneon )'] | [['arsène lupin iii / wolf iii', 'yasuo yamada', 'bob bergen', 'bill dufris', 'tony oliver'], ['fujiko mine / margot', 'eiko masuyama', 'edie mirman', 'toni barry', 'michelle ruff'], ['howard lockewood / foward fughes ( mamo / mameaux )', 'kō nishimura', 'robert axelrod', 'allan wenger', 'george c cole'], ['daisuke jig... |
skal vi danse ? ( season 6 ) | https://en.wikipedia.org/wiki/Skal_vi_danse%3F_%28season_6%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28677723-9.html.csv | aggregation | in the sixth season of the show " skal vi danse ? " the scores from tango dances totaled 54 . | {'scope': 'subset', 'col': '8', 'type': 'sum', 'result': '54', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'tango'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'style', 'tango'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; style ; tango }', 'tointer': 'select the rows whose style record fuzzily matches to tango .'}, 'total'], 'result': '54', 'ind': 1, 'tostr': ... | round_eq { sum { filter_eq { all_rows ; style ; tango } ; total } ; 54 } = true | select the rows whose style record fuzzily matches to tango . the sum of the total record of these rows is 54 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'style_5': 5, 'tango_6': 6, 'total_7': 7, '54_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'style_5': 'style', 'tango_6': 'tango', 'total_7': 'total', '54_8': '54'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'style_5': [0], 'tango_6': [0], 'total_7': [1], '54_8': [2]} | ['couple', 'style', 'music', 'trine dehli cleve', 'tor fløysvik', 'karianne gulliksen', 'christer tornell', 'total'] | [['åsleik & nadia', 'cha - cha - cha', 'ymca - village people', '8', '8', '8', '8', '32'], ['stig & alexandra', 'pasodoble', 'eye of the tiger - survivor', '6', '5', '6', '7', '24'], ['stine & tom - erik', 'rumba', 'la isla bonita - madonna', '6', '6', '7', '6', '25'], ['cecilie & tobias', 'tango', 'twist in my sobriet... |
list of how it 's made episodes | https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15187735-13.html.csv | count | there are 13 episodes in series titled ' how it 's made ' . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '13', 'result': '13', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series ep', '13'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series ep record fuzzily matches to 13 .', 'tostr': 'filter_eq { all_rows ; series ep ; 13 }'}], 'result': '13', 'ind': 1, 'tostr': 'count { f... | eq { count { filter_eq { all_rows ; series ep ; 13 } } ; 13 } = true | select the rows whose series ep record fuzzily matches to 13 . the number of such rows is 13 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'series ep_5': 5, '13_6': 6, '13_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'series ep_5': 'series ep', '13_6': '13', '13_7': '13'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'series ep_5': [0], '13_6': [0], '13_7': [2]} | ['series ep', 'episode', 'segment a', 'segment b', 'segment c', 'segment d'] | [['13 - 01', '157', 'hammers', 'swiss cheese', 'roller skates', 'coloured pencils'], ['13 - 02', '158', 'carbon fiber bicycles', 'blood products', 'forged chandeliers', 'ballpoint pens'], ['13 - 03', '159', 'swiss army knives', 'player piano rolls', 'oil tankers', 'racing wheels'], ['13 - 04', '160', 'bowling balls', '... |
2nd amateurliga bayern | https://en.wikipedia.org/wiki/2nd_Amateurliga_Bayern | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23224961-1.html.csv | count | fc passau won the niederbayern region a total of four times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'fc passau', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'niederbayern', 'fc passau'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose niederbayern record fuzzily matches to fc passau .', 'tostr': 'filter_eq { all_rows ; niederbayern ; fc passau }'}], 'result': '4', ... | eq { count { filter_eq { all_rows ; niederbayern ; fc passau } } ; 4 } = true | select the rows whose niederbayern record fuzzily matches to fc passau . 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, 'niederbayern_5': 5, 'fc passau_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', 'niederbayern_5': 'niederbayern', 'fc passau_6': 'fc passau', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'niederbayern_5': [0], 'fc passau_6': [0], '4_7': [2]} | ['season', 'oberbayern a', 'oberbayern b', 'niederbayern', 'schwaben', 'oberpfalz'] | [['1951 - 52', 'sc münchen - süd', 'spvgg helios münchen', 'spvgg plattling', 'fc kempten', 'sv mitterteich'], ['1952 - 53', 'mtv ingolstadt', 'fc penzberg', 'spvgg deggendorf', 'tsv kottern', 'sv mitterteich'], ['1953 - 54', 'bsc sendling', 'tsv raubling', 'sv saal', 'spvgg kaufbeuren', 'tv sulzbach - rosenberg'], ['1... |
vesna dolonc | https://en.wikipedia.org/wiki/Vesna_Dolonc | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15639710-7.html.csv | majority | vesna dolonc had a runner-up outcome in the majority of tournaments that she played . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'runner-up', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'outcome', 'runner-up'], 'result': True, 'ind': 0, 'tointer': 'for the outcome records of all rows , most of them fuzzily match to runner-up .', 'tostr': 'most_eq { all_rows ; outcome ; runner-up } = true'} | most_eq { all_rows ; outcome ; runner-up } = true | for the outcome records of all rows , most of them fuzzily match to runner-up . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'outcome_3': 3, 'runner-up_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'outcome_3': 'outcome', 'runner-up_4': 'runner-up'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'outcome_3': [0], 'runner-up_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score'] | [['runner - up', '2 october 2005', 'podgorica , serbia & montenegro', 'clay', 'neda kozić', 'ani mijačika dijana stojics', '6 - 1 3 - 6 4 - 6'], ['runner - up', '11 may 2007', 'monzón , spain', 'hard', 'iryna kuryanovich', 'estrella cabeza - candela maría emilia salerni', '2 - 6 1 - 6'], ['winner', '25 august 2007', 'm... |
1965 vfl season | https://en.wikipedia.org/wiki/1965_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10788451-11.html.csv | count | there were 6 game venues used during the 1965 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', ... | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '9.13 ( 67 )', 'melbourne', '19.11 ( 125 )', 'glenferrie oval', '14900', '3 july 1965'], ['footscray', '7.10 ( 52 )', 'north melbourne', '5.10 ( 40 )', 'western oval', '14150', '3 july 1965'], ['st kilda', '12.8 ( 80 )', 'carlton', '10.14 ( 74 )', 'moorabbin oval', '35794', '3 july 1965'], ['richmond', '2... |
1981 vfl season | https://en.wikipedia.org/wiki/1981_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10823950-20.html.csv | ordinal | mcg 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': 'mcg', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'mcg'], 'result': True, 'in... | eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; mcg } = true | select the row whose crowd record of all rows is 1st maximum . the venue record of this row is mcg . | 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, 'mcg_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', 'mcg_8': 'mcg'} | {'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], 'mcg_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['carlton', '15.8 ( 98 )', 'essendon', '14.15 ( 99 )', 'princes park', '36736', '15 august 1981'], ['north melbourne', '21.19 ( 145 )', 'melbourne', '13.9 ( 87 )', 'arden street oval', '7749', '15 august 1981'], ['south melbourne', '12.14 ( 86 )', 'geelong', '21.13 ( 139 )', 'lake oval', '11489', '15 august 1981'], ['... |
yen plus | https://en.wikipedia.org/wiki/Yen_Plus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18685750-1.html.csv | comparative | in yen plus , the title bamboo blade had its last issue released earlier than the title black butler . | {'row_1': '1', 'row_2': '2', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'bamboo blade'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to bamboo blade .', 'tostr': 'filter_eq { all_rows ; title ; bamboo blade }'}, 'last issue'], 'result':... | less { hop { filter_eq { all_rows ; title ; bamboo blade } ; last issue } ; hop { filter_eq { all_rows ; title ; black butler } ; last issue } } = true | select the rows whose title record fuzzily matches to bamboo blade . take the last issue record of this row . select the rows whose title record fuzzily matches to black butler . take the last issue 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, 'title_7': 7, 'bamboo blade_8': 8, 'last issue_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'black butler_12': 12, 'last issue_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', 'title_7': 'title', 'bamboo blade_8': 'bamboo blade', 'last issue_9': 'last issue', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'bl... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'bamboo blade_8': [0], 'last issue_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'black butler_12': [1], 'last issue_13': [3]} | ['title', 'author', 'first issue', 'last issue', 'completed'] | [['bamboo blade', 'masahiro totsuka ( author ) , aguri igarashi ( artist )', 'august 2008', 'may 2009', 'no'], ['black butler', 'yana toboso', 'august 2009', 'july 2010', 'no'], ['higurashi when they cry', 'ryukishi07 ( author ) , karin suzuragi ( artist )', 'august 2008', 'january 2009', 'no'], ['hero tales', 'huang j... |
new year 's revolution ( 2006 ) | https://en.wikipedia.org/wiki/New_Year%27s_Revolution_%282006%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14656943-2.html.csv | ordinal | chris masters had the second highest elimination time in the ring at the 2006 new year 's revolution . | {'row': '4', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'time', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; time ; 2 }'}, 'wrestler'], 'result': 'chris masters', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; time ; 2 } ; wrestler }'}, 'chris masters... | eq { hop { nth_argmax { all_rows ; time ; 2 } ; wrestler } ; chris masters } = true | select the row whose time record of all rows is 2nd maximum . the wrestler record of this row is chris masters . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'time_5': 5, '2_6': 6, 'wrestler_7': 7, 'chris masters_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', 'time_5': 'time', '2_6': '2', 'wrestler_7': 'wrestler', 'chris masters_8': 'chris masters'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'time_5': [0], '2_6': [0], 'wrestler_7': [1], 'chris masters_8': [2]} | ['elimination no', 'wrestler', 'entered', 'eliminated by', 'time'] | [['1', 'kurt angle', '4', 'michaels', '13:58'], ['2', 'kane', '6', 'carlito and masters', '19:24'], ['3', 'shawn michaels', '1', 'carlito', '23:35'], ['4', 'chris masters', '5', 'carlito', '28:15'], ['5', 'carlito', '3', 'cena', '28:22'], ['winner', 'john cena', '2', 'n / a', 'n / a']] |
list of songs in rock band | https://en.wikipedia.org/wiki/List_of_songs_in_Rock_Band | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14160327-3.html.csv | majority | most of the songs are considered to be family friendly . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'yes', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'family friendly', 'yes'], 'result': True, 'ind': 0, 'tointer': 'for the family friendly records of all rows , most of them fuzzily match to yes .', 'tostr': 'most_eq { all_rows ; family friendly ; yes } = true'} | most_eq { all_rows ; family friendly ; yes } = true | for the family friendly records of all rows , most of them fuzzily match to yes . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'family friendly_3': 3, 'yes_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'family friendly_3': 'family friendly', 'yes_4': 'yes'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'family friendly_3': [0], 'yes_4': [0]} | ['song title', 'artist', 'decade', 'genre', 'family friendly'] | [['dirty little secret', 'all american rejects the all american rejects', '2000s', 'emo', 'yes'], ["do n't look back in anger", 'oasis', '1990s', 'rock', 'yes'], ['roam', "b - 52 's the b - 52 's", '1980s', 'pop / rock', 'yes'], ['rockaway beach', 'ramones', '1970s', 'punk', 'yes'], ['roxanne', 'police the police', '19... |
1971 - 72 cleveland cavaliers season | https://en.wikipedia.org/wiki/1971%E2%80%9372_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16946097-3.html.csv | comparative | the caveliers scored more points on october 31 than they did on the 29th . | {'row_1': '10', 'row_2': '9', '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', 'october 31'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to october 31 .', 'tostr': 'filter_eq { all_rows ; date ; october 31 }'}, 'score'], 'result': None, 'ind... | greater { hop { filter_eq { all_rows ; date ; october 31 } ; score } ; hop { filter_eq { all_rows ; date ; october 29 } ; score } } = true | select the rows whose date record fuzzily matches to october 31 . take the score record of this row . select the rows whose date record fuzzily matches to october 29 . take the score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'october 31_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'october 29_12': 12, 'score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'october 31_8': 'october 31', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'october 29_12'... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'october 31_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'october 29_12': [1], 'score_13': [3]} | ['date', 'h / a / n', 'opponent', 'score', 'record'] | [['october 15', 'h', 'buffalo braves', '109 - 111 ( ot )', '0 - 1'], ['october 16', 'a', 'buffalo braves', '93 - 89', '1 - 1'], ['october 17', 'h', 'new york knicks', '120 - 121 ( ot )', '1 - 2'], ['october 19', 'a', 'milwaukee bucks', '82 - 116', '1 - 3'], ['october 20', 'h', 'san francisco warriors', '98 - 115', '1 -... |
boroughs of sherbrooke | https://en.wikipedia.org/wiki/Boroughs_of_Sherbrooke | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14927794-1.html.csv | aggregation | the average number of borough councilors is about 3.8 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '3.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'number of borough councilors'], 'result': '3.8', 'ind': 0, 'tostr': 'avg { all_rows ; number of borough councilors }'}, '3.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; number of borough councilors } ; 3.8 } = true', 'tointer': '... | round_eq { avg { all_rows ; number of borough councilors } ; 3.8 } = true | the average of the number of borough councilors record of all rows is 3.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'number of borough councilors_4': 4, '3.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'number of borough councilors_4': 'number of borough councilors', '3.8_5': '3.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'number of borough councilors_4': [0], '3.8_5': [1]} | ['borough', 'components', 'population', 'number of borough councilors', 'number of municipal councilors'] | [['brompton', 'bromptonville', '5771', '3', '1'], ['fleurimont', 'eastern sherbrooke , fleurimont', '41289', '5', '5'], ['lennoxville', 'lennoxville', '4947', '3', '1'], ['mont - bellevue', 'western sherbrooke , ascot', '31373', '4', '4'], ['rock forest - saint - élie - deauville', "rock forest , saint - élie - d'orfor... |
list of ship launches in 1878 | https://en.wikipedia.org/wiki/List_of_ship_launches_in_1878 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18548768-1.html.csv | unique | john roach and son built the only passenger ship that launched in 1878 . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'passenger ship', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class / type', 'passenger ship'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class / type record fuzzily matches to passenger ship .', 'tostr': 'filter_eq { all_rows ; class / type ; passenger ship }'}], ... | and { only { filter_eq { all_rows ; class / type ; passenger ship } } ; eq { hop { filter_eq { all_rows ; class / type ; passenger ship } ; builder } ; john roach and son } } = true | select the rows whose class / type record fuzzily matches to passenger ship . there is only one such row in the table . the builder record of this unqiue row is john roach and son . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'class / type_7': 7, 'passenger ship_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'builder_9': 9, 'john roach and son_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'class / type_7': 'class / type', 'passenger ship_8': 'passenger ship', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'builder_9': 'builder', 'john roach and son_10': 'john roach and son'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'class / type_7': [0], 'passenger ship_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'builder_9': [2], 'john roach and son_10': [3]} | ['country', 'builder', 'location', 'ship', 'class / type'] | [['united states', 'john roach and son', 'chester , pennsylvania', 'city of rio de janeiro', 'passenger ship'], ['germany', 'kaiserliche werft wilhelmshaven', 'wilhelmshaven', 'bayern', 'sachsen - class ironclad'], ['united kingdom', 'royal dockyard', 'devonport , devon', 'pegasus', 'doterel - class sloop'], ['united k... |
mont \ xc3 \ xa9r \ xc3 \ xa9gie | https://en.wikipedia.org/wiki/Mont%C3%A9r%C3%A9gie | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1011906-1.html.csv | count | there are 6 regional county municipalities ( rcm ) in the montérégie region . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'regional county municipality ( rcm )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose regional county municipality ( rcm ) record is arbitrary .', 'tostr': 'filter_all { all_rows ; regional county municipality ... | eq { count { filter_all { all_rows ; regional county municipality ( rcm ) } } ; 6 } = true | select the rows whose regional county municipality ( rcm ) record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'regional county municipality (rcm)_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'regional county municipality (rcm)_5': 'regional county municipality ( rcm )', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'regional county municipality (rcm)_5': [0], '6_6': [2]} | ['regional county municipality ( rcm )', 'population canada 2011 census', 'land area', 'density ( pop per km2 )', 'seat of rcm'] | [['acton', '15381', 'km2 ( sqmi )', '26.5', 'acton vale'], ['brome - missisquoi', '55621', 'km2 ( sqmi )', '33.7', 'cowansville'], ['la haute - yamaska', '85042', 'km2 ( sqmi )', '133.6', 'granby'], ['la vallãe - du - richelieu', '116773', 'km2 ( sqmi )', '198.3', 'mcmasterville'], ['le haut - richelieu', '114344', 'km... |
1990 - 91 atlanta hawks season | https://en.wikipedia.org/wiki/1990%E2%80%9391_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27882867-6.html.csv | ordinal | in the 1990-91 atlanta hawks season , the game with the 2nd highest attendance was on january 12th . | {'row': '6', 'col': '8', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'location attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 2 }'}, 'date'], 'result': 'january 12', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendanc... | eq { hop { nth_argmax { all_rows ; location attendance ; 2 } ; date } ; january 12 } = true | select the row whose location attendance record of all rows is 2nd maximum . the date record of this row is january 12 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '2_6': 6, 'date_7': 7, 'january 12_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', '2_6': '2', 'date_7': 'date', 'january 12_8': 'january 12'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '2_6': [0], 'date_7': [1], 'january 12_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['29', 'january 2', 'la clippers', 'w 120 - 107', 'd wilkins ( 35 )', 'd wilkins ( 16 )', 'g rivers ( 11 )', 'omni coliseum 8733', '16 - 13'], ['30', 'january 4', 'indiana', 'w 111 - 96', 'd wilkins ( 36 )', 'm malone ( 11 )', 'g rivers , r robinson ( 5 )', 'omni coliseum 10124', '17 - 13'], ['31', 'january 5', 'minne... |
united states house of representatives elections , 1946 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1946 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342233-3.html.csv | count | two of the incumbents in the election of 1946 for united states house of representatives , were first elected in 1944 . | {'scope': 'all', 'criterion': 'equal', 'value': '1944', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'first elected', '1944'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first elected record is equal to 1944 .', 'tostr': 'filter_eq { all_rows ; first elected ; 1944 }'}], 'result': '2', 'ind': 1, 'tostr': 'cou... | eq { count { filter_eq { all_rows ; first elected ; 1944 } } ; 2 } = true | select the rows whose first elected record is equal to 1944 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '1944_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', '1944_6': '1944', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1944_6': [0], '2_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['alabama 1', 'frank w boykin', 'democratic', '1935', 're - elected', 'frank w boykin ( d ) unopposed'], ['alabama 2', 'george m grant', 'democratic', '1938', 're - elected', 'george m grant ( d ) unopposed'], ['alabama 3', 'george w andrews', 'democratic', '1944', 're - elected', 'george w andrews ( d ) unopposed'], ... |
alona bondarenko | https://en.wikipedia.org/wiki/Alona_Bondarenko | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1498593-3.html.csv | unique | hard ( i ) is the only surface used once by alona bondarenko . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'hard ( i )', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard ( i )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard ( i ) .', 'tostr': 'filter_eq { all_rows ; surface ; hard ( i ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq... | only { filter_eq { all_rows ; surface ; hard ( i ) } } = true | select the rows whose surface record fuzzily matches to hard ( i ) . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'surface_4': 4, 'hard (i)_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'surface_4': 'surface', 'hard (i)_5': 'hard ( i )'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'surface_4': [0], 'hard (i)_5': [0]} | ['outcome', 'date', 'championship', 'surface', 'partner', 'opponent in the final', 'score in the final'] | [['winner', '27 may 2006', 'istanbul , turkey', 'clay', 'anastasiya yakimova', 'sania mirza alicia molik', '6 - 2 , 6 - 4'], ['winner', '26 january 2008', 'melbourne , australia', 'hard', 'kateryna bondarenko', "victoria azarenka shahar pe'er", '2 - 6 , 6 - 1 , 6 - 4'], ['winner', '10 february 2008', 'paris , france', ... |
ugly betty ( season 4 ) | https://en.wikipedia.org/wiki/Ugly_Betty_%28season_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22570439-1.html.csv | unique | in ugly betty season 4 , for the episodes that originally aired in march , the only one directed by andy wolk was the episode titled all the world 's a stage . | {'scope': 'subset', 'row': '16', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'andy wolk', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'march'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'march'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; original air date ; march }', 'tointer': 'select the rows whose original air date record fuzzily ... | and { only { filter_eq { filter_eq { all_rows ; original air date ; march } ; directed by ; andy wolk } } ; eq { hop { filter_eq { filter_eq { all_rows ; original air date ; march } ; directed by ; andy wolk } ; episode title } ; all the world 's a stage } } = true | select the rows whose original air date record fuzzily matches to march . among these rows , select the rows whose directed by record fuzzily matches to andy wolk . there is only one such row in the table . the episode title record of this unqiue row is all the world 's a stage . | 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, 'original air date_8': 8, 'march_9': 9, 'directed by_10': 10, 'andy wolk_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'episode title_12': 12, "all the world 's a stage_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', 'original air date_8': 'original air date', 'march_9': 'march', 'directed by_10': 'directed by', 'andy wolk_11': 'andy wolk', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_h... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'original air date_8': [0], 'march_9': [0], 'directed by_10': [1], 'andy wolk_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'episode title_12': [3], "all the world 's a stage_13": [4]} | ['series', 'season', 'episode title', 'written by', 'directed by', 'us viewers ( millions )', 'original air date'] | [['66', '1', 'the butterfly effect ( part 1 )', 'sheila lawrence & henry alonso myers', 'john terlesky', '5.01', 'october 16 , 2009'], ['67', '2', 'the butterfly effect ( part 2 )', 'sheila lawrence & henry alonso myers', 'victor nelli , jr', '5.18', 'october 16 , 2009'], ['68', '3', 'blue on blue', 'abraham higginboth... |
1935 masters tournament | https://en.wikipedia.org/wiki/1935_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12586224-1.html.csv | aggregation | the average scores of the top 10 finishes in the 1935 masters tournament was 70 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '70', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '70', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '70'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 70 } = true', 'tointer': 'the average of the score record of all rows is 70 .'} | round_eq { avg { all_rows ; score } ; 70 } = true | the average of the score record of all rows is 70 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '70_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '70_5': '70'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '70_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'henry picard', 'united states', '67', '- 5'], ['t2', 'gene sarazen', 'united states', '68', '- 4'], ['t2', 'ray mangrum', 'united states', '68', '- 4'], ['t2', 'willie goggin', 'united states', '68', '- 4'], ['5', 'craig wood', 'united states', '69', '- 3'], ['t6', 'olin dutra', 'united states', '70', '- 2'], [... |
list of greek episodes | https://en.wikipedia.org/wiki/List_of_Greek_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12419515-4.html.csv | superlative | our fathers episode in the greek series has the most total viewers ( in millions ) . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '2', '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', 'total viewers ( in millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total viewers ( in millions ) }'}, 'title'], 'result': 'our fathers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total viewers ( i... | eq { hop { argmax { all_rows ; total viewers ( in millions ) } ; title } ; our fathers } = true | select the row whose total viewers ( in millions ) record of all rows is maximum . the title record of this row is our fathers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total viewers (in millions)_5': 5, 'title_6': 6, 'our fathers_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total viewers (in millions)_5': 'total viewers ( in millions )', 'title_6': 'title', 'our fathers_7': 'our fathers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total viewers (in millions)_5': [0], 'title_6': [1], 'our fathers_7': [2]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'total viewers ( in millions )'] | [['45', '1', 'the day after', 'michael lange', 'patrick sean smith', 'august 31 , 2009', '1.211'], ['46', '2', 'our fathers', 'patrick norris', 'jessica otoole & amy rardin', 'september 7 , 2009', '1.313'], ['47', '3', 'the half - naked gun', 'michael lange', 'roger grant', 'september 14 , 2009', 'n / a'], ['48', '4', ... |
swatch fivb world tour 2006 | https://en.wikipedia.org/wiki/Swatch_FIVB_World_Tour_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18395409-3.html.csv | aggregation | the total number of medals won by all the nations in the 2006 swatch fivb world tour was 87 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '87', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total'], 'result': '87', 'ind': 0, 'tostr': 'sum { all_rows ; total }'}, '87'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total } ; 87 } = true', 'tointer': 'the sum of the total record of all rows is 87 .'} | round_eq { sum { all_rows ; total } ; 87 } = true | the sum of the total record of all rows is 87 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total_4': 4, '87_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total_4': 'total', '87_5': '87'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total_4': [0], '87_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'brazil', '17', '18', '15', '50'], ['2', 'united states', '5', '5', '4', '14'], ['3', 'china', '4', '5', '5', '14'], ['4', 'germany', '2', '1', '3', '6'], ['5', 'switzerland', '1', '0', '0', '1'], ['6', 'netherlands', '0', '0', '1', '1'], ['6', 'norway', '0', '0', '1', '1']] |
nature of america | https://en.wikipedia.org/wiki/Nature_of_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15635768-1.html.csv | ordinal | the alpine tundra ecosystem series of nature of america stamps has the fourth highest face value . | {'row': '9', 'col': '5', 'order': '4', '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', 'face value', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; face value ; 4 }'}, 'ecosystem'], 'result': 'alpine tundra', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; face value ; 4 } ; ecosystem... | eq { hop { nth_argmax { all_rows ; face value ; 4 } ; ecosystem } ; alpine tundra } = true | select the row whose face value record of all rows is 4th maximum . the ecosystem record of this row is alpine tundra . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'face value_5': 5, '4_6': 6, 'ecosystem_7': 7, 'alpine tundra_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', 'face value_5': 'face value', '4_6': '4', 'ecosystem_7': 'ecosystem', 'alpine tundra_8': 'alpine tundra'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'face value_5': [0], '4_6': [0], 'ecosystem_7': [1], 'alpine tundra_8': [2]} | ['ecosystem', 'date of issue', 'place of issue', 'no stamps in sheet', 'face value', 'printer'] | [['sonoran desert', 'april 6 , 1999', 'tucson , arizona', '10', '33', 'banknote corporation of america'], ['pacific coast rain forest', 'march 28 , 2000', 'seattle , washington', '10', '33', 'banknote corporation of america'], ['great plains prairie', 'march 29 , 2001', 'lincoln , nebraska', '10', '34', 'ashton - potte... |
24th united states congress | https://en.wikipedia.org/wiki/24th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-225200-4.html.csv | comparative | hopkins holsey was seated as a successor earlier than john young in the 24th united states congress . | {'row_1': '3', 'row_2': '12', 'col': '5', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'hopkins holsey ( j )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to hopkins holsey ( j ) .', 'tostr': 'filter_eq { all_rows ; successor ; hopkins holsey... | less { hop { filter_eq { all_rows ; successor ; hopkins holsey ( j ) } ; date successor seated } ; hop { filter_eq { all_rows ; successor ; john young ( aj ) } ; date successor seated } } = true | select the rows whose successor record fuzzily matches to hopkins holsey ( j ) . take the date successor seated record of this row . select the rows whose successor record fuzzily matches to john young ( aj ) . take the date successor seated 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, 'successor_7': 7, 'hopkins holsey ( j )_8': 8, 'date successor seated_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'successor_11': 11, 'john young ( aj )_12': 12, 'date successor seated_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', 'successor_7': 'successor', 'hopkins holsey ( j )_8': 'hopkins holsey ( j )', 'date successor seated_9': 'date successor seated', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'successor_7': [0], 'hopkins holsey ( j )_8': [0], 'date successor seated_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'successor_11': [1], 'john young ( aj )_12': [1], 'date successor seated_13': [3]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['south carolina 6th', 'vacant', 'rep warren r davis died during previous congress', 'waddy thompson , jr ( aj )', 'seated september 10 , 1835'], ['georgia at - large', 'vacant', 'rep james m wayne resigned in previous congress', 'jabez y jackson ( j )', 'seated october 5 , 1835'], ['georgia at - large', 'james c terr... |
japanese house of councillors election , 2001 | https://en.wikipedia.org/wiki/Japanese_House_of_Councillors_election%2C_2001 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10124546-1.html.csv | ordinal | the democratic party won the second most seats in 2001 . | {'row': '2', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total elected 2001', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total elected 2001 ; 2 }'}, 'party'], 'result': 'democratic party', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total elected... | eq { hop { nth_argmax { all_rows ; total elected 2001 ; 2 } ; party } ; democratic party } = true | select the row whose total elected 2001 record of all rows is 2nd maximum . the party record of this row is democratic party . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total elected 2001_5': 5, '2_6': 6, 'party_7': 7, 'democratic party_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', 'total elected 2001_5': 'total elected 2001', '2_6': '2', 'party_7': 'party', 'democratic party_8': 'democratic party'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total elected 2001_5': [0], '2_6': [0], 'party_7': [1], 'democratic party_8': [2]} | ['party', 'pr seats', 'district seats', 'total elected 2001', 'total seats'] | [['liberal democratic party', '20', '45', '65', '111'], ['democratic party', '8', '18', '26', '59'], ['new komeito party', '8', '5', '13', '23'], ['liberal party', '4', '2', '6', '8'], ['communist party', '4', '1', '5', '20'], ['social democratic party', '3', '0', '3', '8'], ['new conservative party', '1', '0', '1', '5... |
1965 belgian grand prix | https://en.wikipedia.org/wiki/1965_Belgian_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122334-1.html.csv | count | of the teams in the 1965 belgian grand prix that completed fewer than 25 laps , two had ignition problems . | {'scope': 'subset', 'criterion': 'equal', 'value': 'ignition', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'less_than', 'value': '25'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'laps', '25'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; laps ; 25 }', 'tointer': 'select the rows whose laps record is less than 25 .'}, 'time / retired', 'ignition'], '... | eq { count { filter_eq { filter_less { all_rows ; laps ; 25 } ; time / retired ; ignition } } ; 2 } = true | select the rows whose laps record is less than 25 . among these rows , select the rows whose time / retired record fuzzily matches to ignition . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'laps_6': 6, '25_7': 7, 'time / retired_8': 8, 'ignition_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'laps_6': 'laps', '25_7': '25', 'time / retired_8': 'time / retired', 'ignition_9': 'ignition', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'laps_6': [0], '25_7': [0], 'time / retired_8': [1], 'ignition_9': [1], '2_10': [3]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['jim clark', 'lotus - climax', '32', '2:23:34.8', '2'], ['jackie stewart', 'brm', '32', '+ 44.8 secs', '3'], ['bruce mclaren', 'cooper - climax', '31', '+ 1 lap', '9'], ['jack brabham', 'brabham - climax', '31', '+ 1 lap', '10'], ['graham hill', 'brm', '31', '+ 1 lap', '1'], ['richie ginther', 'honda', '31', '+ 1 lap... |
1996 - 97 philadelphia flyers season | https://en.wikipedia.org/wiki/1996%E2%80%9397_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208850-4.html.csv | count | the philadelphia flyers played against the hartford whalers twice . | {'scope': 'all', 'criterion': 'equal', 'value': 'hartford whalers', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'hartford whalers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to hartford whalers .', 'tostr': 'filter_eq { all_rows ; opponent ; hartford whalers }'}], 'resul... | eq { count { filter_eq { all_rows ; opponent ; hartford whalers } } ; 2 } = true | select the rows whose opponent record fuzzily matches to hartford whalers . 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, 'hartford whalers_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', 'hartford whalers_6': 'hartford whalers', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'opponent_5': [0], 'hartford whalers_6': [0], '2_7': [2]} | ['game', 'december', 'opponent', 'score', 'record', 'points'] | [['27', '1', 'vancouver canucks', '4 - 3', '14 - 12 - 1', '29'], ['28', '4', 'new york rangers', '1 - 1 ot', '14 - 12 - 2', '30'], ['29', '6', 'dallas stars', '6 - 3', '15 - 12 - 2', '32'], ['30', '10', 'florida panthers', '5 - 4', '16 - 12 - 2', '34'], ['31', '12', 'hartford whalers', '3 - 2', '17 - 12 - 2', '36'], ['... |
list of cities , towns and villages in vojvodina | https://en.wikipedia.org/wiki/List_of_cities%2C_towns_and_villages_in_Vojvodina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2562572-19.html.csv | comparative | in the list of cities , towns and villages in vojvodina , gardinovci has a larger population than lok . | {'row_1': '2', 'row_2': '3', 'col': '4', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'settlement', 'gardinovci'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose settlement record fuzzily matches to gardinovci .', 'tostr': 'filter_eq { all_rows ; settlement ; gardinovci }'}, 'population ... | greater { hop { filter_eq { all_rows ; settlement ; gardinovci } ; population ( 2011 ) } ; hop { filter_eq { all_rows ; settlement ; lok } ; population ( 2011 ) } } = true | select the rows whose settlement record fuzzily matches to gardinovci . take the population ( 2011 ) record of this row . select the rows whose settlement record fuzzily matches to lok . take the population ( 2011 ) 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, 'settlement_7': 7, 'gardinovci_8': 8, 'population (2011)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'settlement_11': 11, 'lok_12': 12, 'population (2011)_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', 'settlement_7': 'settlement', 'gardinovci_8': 'gardinovci', 'population (2011)_9': 'population ( 2011 )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_row... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'settlement_7': [0], 'gardinovci_8': [0], 'population (2011)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'settlement_11': [1], 'lok_12': [1], 'population (2011)_13': [3]} | ['settlement', 'cyrillic name', 'type', 'population ( 2011 )', 'largest ethnic group ( 2002 )', 'dominant religion ( 2002 )'] | [['titel', 'тител', 'town', '5294', 'serbs', 'orthodox christianity'], ['gardinovci', 'гардиновци', 'village', '1297', 'serbs', 'orthodox christianity'], ['lok', 'лок', 'village', '1114', 'serbs', 'orthodox christianity'], ['mošorin', 'мошорин', 'village', '2569', 'serbs', 'orthodox christianity'], ['šajkaš', 'шајкаш',... |
united states house of representatives elections , 1962 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1962 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341884-12.html.csv | majority | most of the incumbents in the 1962 united states elections of the house of representatives for georgia ran unopposed . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'unopposed', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': True, 'ind': 0, 'tointer': 'for the candidates records of all rows , most of them fuzzily match to unopposed .', 'tostr': 'most_eq { all_rows ; candidates ; unopposed } = true'} | most_eq { all_rows ; candidates ; unopposed } = true | for the candidates records of all rows , most of them fuzzily match to unopposed . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'candidates_3': 3, 'unopposed_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'candidates_3': 'candidates', 'unopposed_4': 'unopposed'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'candidates_3': [0], 'unopposed_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['georgia 1', 'george elliott hagan', 'democratic', '1960', 're - elected', 'george elliott hagan ( d ) unopposed'], ['georgia 2', 'j l pilcher', 'democratic', '1953', 're - elected', 'j l pilcher ( d ) unopposed'], ['georgia 3', 'tic forrester', 'democratic', '1950', 're - elected', 'tic forrester ( d ) unopposed'], ... |
automobiles gonfaronnaises sportives | https://en.wikipedia.org/wiki/Automobiles_Gonfaronnaises_Sportives | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226665-1.html.csv | majority | the majority of the chasis in automobiles gonfaronnaises sportives between 1986 and 1991 uses g tyres . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'g', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'tyres', 'g'], 'result': True, 'ind': 0, 'tointer': 'for the tyres records of all rows , most of them fuzzily match to g .', 'tostr': 'most_eq { all_rows ; tyres ; g } = true'} | most_eq { all_rows ; tyres ; g } = true | for the tyres records of all rows , most of them fuzzily match to g . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tyres_3': 3, 'g_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tyres_3': 'tyres', 'g_4': 'g'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tyres_3': [0], 'g_4': [0]} | ['year', 'chassis', 'engine', 'tyres', 'points'] | [['1986', 'ags jh21c', 'motori moderni 615 - 90 v6 ( t / c )', 'p', '0'], ['1987', 'ags jh22', 'ford dfz v8', 'g', '1'], ['1988', 'ags jh23', 'ford dfz v8', 'g', '0'], ['1989', 'ags jh23b ags jh24', 'ford dfr v8', 'g', '1'], ['1990', 'ags jh24 ags jh25', 'ford dfr v8', 'g', '0'], ['1991', 'ags jh25b ags jh27', 'ford df... |
b " rqw women 's championship " | https://en.wikipedia.org/wiki/RQW_Women%27s_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18963089-2.html.csv | count | four of the rqw women 's championship events were held in norfolk . | {'scope': 'all', 'criterion': 'equal', 'value': 'norfolk', 'result': '4', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'norfolk'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to norfolk .', 'tostr': 'filter_eq { all_rows ; location ; norfolk }'}], 'result': '4', 'ind': 1, 'tostr':... | eq { count { filter_eq { all_rows ; location ; norfolk } } ; 4 } = true | select the rows whose location record fuzzily matches to norfolk . 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, 'location_5': 5, 'norfolk_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', 'location_5': 'location', 'norfolk_6': 'norfolk', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'norfolk_6': [0], '4_7': [2]} | ['wrestlers', 'reign', 'days held', 'location', 'event'] | [['erin angel', '1', '111', 'eastleigh , hampshire', 'a night of champions'], ['vacated', '-', '-', '-', '-'], ['eden black', '1', '302', 'horndean , portsmouth', 'summer brawl 2006'], ['wesna', '1', '392', 'live event', 'a night of champions'], ['sweet saraya', '1', '225', 'vienna , austria', 'wrestling weltmeistersch... |
1980 tampa bay buccaneers season | https://en.wikipedia.org/wiki/1980_Tampa_Bay_Buccaneers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11406866-2.html.csv | ordinal | the attendance at the third game the tampa bay buccaneers won was 51925 . | {'scope': 'subset', 'row': '9', 'col': '2', 'order': '3', 'col_other': '7', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'w'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; w }', 'tointer': 'select the rows whose result record fuzzily matches to w .'}, 'date', '3'], 'resul... | eq { hop { nth_argmin { filter_eq { all_rows ; result ; w } ; date ; 3 } ; attendance } ; 51925 } = true | select the rows whose result record fuzzily matches to w . select the row whose date record of these rows is 3rd minimum . the attendance record of this row is 51925 . | 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, 'result_6': 6, 'w_7': 7, 'date_8': 8, '3_9': 9, 'attendance_10': 10, '51925_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', 'result_6': 'result', 'w_7': 'w', 'date_8': 'date', '3_9': '3', 'attendance_10': 'attendance', '51925_11': '51925'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'result_6': [0], 'w_7': [0], 'date_8': [1], '3_9': [1], 'attendance_10': [2], '51925_11': [3]} | ['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'] | [['week', 'date', 'opponent', 'result', 'kickoff', 'game site', 'attendance', 'record'], ['1', 'september 7 , 1980', 'cincinnati bengals', 'w 17 - 12', '1:00', 'riverfront stadium', '35551', '1 - 0'], ['2', 'september 11 , 1980', 'los angeles rams', 'w 10 - 9', '9:00', 'tampa stadium', '66576', '2 - 0'], ['3', 'septemb... |
2010 red bull motogp rookies cup season | https://en.wikipedia.org/wiki/2010_Red_Bull_MotoGP_Rookies_Cup_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28925058-1.html.csv | unique | the italian grand prix is the only one to have only one round on one day . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'italian grand prix', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'grand prix', 'italian grand prix'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose grand prix record fuzzily matches to italian grand prix .', 'tostr': 'filter_eq { all_rows ; grand prix ; italian grand prix }'}], 'result': True, 'in... | only { filter_eq { all_rows ; grand prix ; italian grand prix } } = true | select the rows whose grand prix record fuzzily matches to italian grand prix . 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, 'grand prix_4': 4, 'italian grand prix_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'grand prix_4': 'grand prix', 'italian grand prix_5': 'italian grand prix'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'grand prix_4': [0], 'italian grand prix_5': [0]} | ['round', 'date', 'grand prix', 'circuit', 'pole position', 'fastest lap', 'race winner'] | [['1', 'may 1', 'spanish grand prix', 'jerez', 'daijiro hiura', 'daniel ruiz', 'danny kent'], ['1', 'may 2', 'spanish grand prix', 'jerez', 'daijiro hiura', 'daniel ruiz', 'daniel ruiz'], ['2', 'june 5', 'italian grand prix', 'mugello circuit', 'daniel ruiz', 'kevin calia', 'daijiro hiura'], ['3', 'june 25', 'dutch tt'... |
blue ridge hockey conference | https://en.wikipedia.org/wiki/Blue_Ridge_Hockey_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16404837-3.html.csv | majority | most of the schools in the blue ridge hockey conference were founded prior to 1900 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '1900', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'founded', '1900'], 'result': True, 'ind': 0, 'tointer': 'for the founded records of all rows , most of them are less than 1900 .', 'tostr': 'most_less { all_rows ; founded ; 1900 } = true'} | most_less { all_rows ; founded ; 1900 } = true | for the founded records of all rows , most of them are less than 1900 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'founded_3': 3, '1900_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'founded_3': 'founded', '1900_4': '1900'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'founded_3': [0], '1900_4': [0]} | ['school', 'location', 'founded', 'affiliation', 'nickname'] | [['american university', 'washington dc', '1893', 'private / methodist', 'eagles'], ['catholic university', 'washington dc', '1887', 'private / roman catholic', 'cardinals'], ['george mason university', 'fairfax , va', '1957', 'public', 'patriots'], ['university of maryland', 'college park , md', '1856', 'public flagsh... |
pirveli liga | https://en.wikipedia.org/wiki/Pirveli_Liga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18009885-2.html.csv | comparative | the mikheil meskhi stadium has a higher seating capacity than the sasha kvaratskhelia stadium . | {'row_1': '15', 'row_2': '13', 'col': '5', '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', 'stadium', 'mikheil meskhi stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose stadium record fuzzily matches to mikheil meskhi stadium .', 'tostr': 'filter_eq { all_rows ; stadium ; mikheil meskh... | greater { hop { filter_eq { all_rows ; stadium ; mikheil meskhi stadium } ; capacity } ; hop { filter_eq { all_rows ; stadium ; sasha kvaratskhelia stadium } ; capacity } } = true | select the rows whose stadium record fuzzily matches to mikheil meskhi stadium . take the capacity record of this row . select the rows whose stadium record fuzzily matches to sasha kvaratskhelia stadium . take the capacity record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'stadium_7': 7, 'mikheil meskhi stadium_8': 8, 'capacity_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'stadium_11': 11, 'sasha kvaratskhelia stadium_12': 12, 'capacity_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'stadium_7': 'stadium', 'mikheil meskhi stadium_8': 'mikheil meskhi stadium', 'capacity_9': 'capacity', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows'... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'stadium_7': [0], 'mikheil meskhi stadium_8': [0], 'capacity_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'stadium_11': [1], 'sasha kvaratskhelia stadium_12': [1], 'capacity_13': [3]} | ['clubs', 'position 2010 - 11', 'region', 'stadium', 'capacity'] | [['samtredia', 'umaglesi liga', 'imereti', 'erosi manjgaladze stadium', '15000'], ['chikhura sachkhere', '4', 'imereti', 'tsentral stadium ( sachkhere )', '2000'], ['dinamo batumi', '5', 'adjara', 'batumi stadium', '30000'], ['guria lanchkhuti', '6', 'guria', 'evgrapi shevardnadze stadium', '22000'], ['kolkheti khobi',... |
coppa italia | https://en.wikipedia.org/wiki/Coppa_Italia | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1281200-1.html.csv | count | a total of four rounds had no new entries in the round . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'none', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'new entries this round', 'none'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose new entries this round record fuzzily matches to none .', 'tostr': 'filter_eq { all_rows ; new entries this round ; none }'}], ... | eq { count { filter_eq { all_rows ; new entries this round ; none } } ; 4 } = true | select the rows whose new entries this round record fuzzily matches to none . 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, 'new entries this round_5': 5, 'none_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', 'new entries this round_5': 'new entries this round', 'none_6': 'none', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'new entries this round_5': [0], 'none_6': [0], '4_7': [2]} | ['phase', 'round', 'clubs remaining', 'clubs involved', 'winners from previous round', 'new entries this round', 'leagues entering at this round'] | [['first phase', 'first round', '78', '36', 'none', '36', 'teams from lega pro and serie d'], ['first phase', 'second round', '60', '40', '18', '22', 'serie b'], ['first phase', 'third round', '40', '32', '20', '12', 'lowest - ranked serie a teams'], ['first phase', 'fourth round', '24', '16', '16', 'none', 'none'], ['... |
1992 - 93 toronto maple leafs season | https://en.wikipedia.org/wiki/1992%E2%80%9393_Toronto_Maple_Leafs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13913477-9.html.csv | ordinal | the toronto maple leafs game against new jersey was the earliest in the 1992 - 93 season . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'visitor'], 'result': 'new jersey', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; visitor }'}, 'new jersey'], 'res... | eq { hop { nth_argmin { all_rows ; date ; 1 } ; visitor } ; new jersey } = true | select the row whose date record of all rows is 1st minimum . the visitor record of this row is new jersey . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'visitor_7': 7, 'new jersey_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '1_6': '1', 'visitor_7': 'visitor', 'new jersey_8': 'new jersey'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'visitor_7': [1], 'new jersey_8': [2]} | ['game', 'date', 'visitor', 'score', 'home', 'record', 'points'] | [['78', 'april 3', 'new jersey', '1 - 0', 'toronto', '42 - 25 - 11', '95'], ['79', 'april 4', 'toronto', '0 - 4', 'philadelphia', '42 - 26 - 11', '95'], ['80', 'april 8', 'toronto', '3 - 5', 'winnipeg', '42 - 27 - 11', '95'], ['81', 'april 10', 'philadelphia', '0 - 4', 'toronto', '42 - 28 - 11', '95'], ['82', 'april 11... |
wru division four south east | https://en.wikipedia.org/wiki/WRU_Division_Four_South_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13940275-4.html.csv | unique | cefn coed rfc is the only club with a single try bonus in the wru division four south east . | {'scope': 'all', 'row': '13', 'col': '9', 'col_other': '1', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'try bonus', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose try bonus record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; try bonus ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_... | and { only { filter_eq { all_rows ; try bonus ; 1 } } ; eq { hop { filter_eq { all_rows ; try bonus ; 1 } ; club } ; cefn coed rfc } } = true | select the rows whose try bonus record is equal to 1 . there is only one such row in the table . the club record of this unqiue row is cefn coed rfc . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'try bonus_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'cefn coed rfc_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'try bonus_7': 'try bonus', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'cefn coed rfc_10': 'cefn coed rfc'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'try bonus_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'cefn coed rfc_10': [3]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['pentyrch rfc', '22', '0', '3', '542', '210', '78', '25', '11', '1', '88'], ['heol y cyw rfc', '22', '2', '3', '513', '219', '70', '24', '9', '3', '84'], ['porth harlequins rfc', '... |
ray sefo | https://en.wikipedia.org/wiki/Ray_Sefo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1533651-2.html.csv | count | ray sefo had 4 fights that only went 1 round . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '1', 'result': '4', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'round', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose round record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; round ; 1 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_r... | eq { count { filter_eq { all_rows ; round ; 1 } } ; 4 } = true | select the rows whose round record fuzzily matches to 1 . 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, 'round_5': 5, '1_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', 'round_5': 'round', '1_6': '1', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'round_5': [0], '1_6': [0], '4_7': [2]} | ['date', 'result', 'opponent', 'location', 'method', 'round', 'record'] | [['2001 - 09 - 02', 'loss', 'chester hughes', 'elgin , illinois , usa', 'ko', '1', '5 - 1 - 0'], ['2001 - 06 - 03', 'win', 'joe lenhart', 'elgin , illinois , usa', 'tko', '1', '5 - 0 - 0'], ['2001 - 02 - 11', 'win', 'steve griffin', 'elgin , illinois , usa', 'tko', '1', '4 - 0 - 0'], ['1996 - 10 - 05', 'win', 'nicky fa... |
regions of iceland | https://en.wikipedia.org/wiki/Regions_of_Iceland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2252745-1.html.csv | count | four of the regions of iceland have an area smaller than 10000 square kilometers . | {'scope': 'all', 'criterion': 'less_than', 'value': '10000', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'area ( km square )', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose area ( km square ) record is less than 10000 .', 'tostr': 'filter_less { all_rows ; area ( km square ) ; 10000 }'}], 'result': '4', ... | eq { count { filter_less { all_rows ; area ( km square ) ; 10000 } } ; 4 } = true | select the rows whose area ( km square ) record is less than 10000 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'area (km square)_5': 5, '10000_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'area (km square)_5': 'area ( km square )', '10000_6': '10000', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'area (km square)_5': [0], '10000_6': [0], '4_7': [2]} | ['', 'name', 'name ( english )', 'population 2008 - 07 - 01', 'area ( km square )', 'pop / km square', 'iso 3166 - 2', 'administrative centre'] | [['1', 'höfuðborgarsvæði', 'capital region', '200969', '1062', '167.61', 'is - 1', 'reykjavík'], ['2', 'suðurnes', 'southern peninsula', '21431', '829', '20.18', 'is - 2', 'keflavík'], ['3', 'vesturland', 'western region', '15601', '9554', '1.51', 'is - 3', 'akranes'], ['4', 'vestfirðir', 'westfjords', '7279', '9409', ... |
2008 - 09 süper lig | https://en.wikipedia.org/wiki/2008%E2%80%9309_S%C3%BCper_Lig | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17356873-2.html.csv | comparative | raşit cetiner left his position eight days before engin ipekoğlu left his position . | {'row_1': '1', 'row_2': '2', 'col': '4', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '8 days', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outgoing manager', 'raşit çetiner'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose outgoing manager record fuzzily matches to raşit çetiner .', 'tostr': 'filter_eq { all_rows ; ou... | eq { diff { hop { filter_eq { all_rows ; outgoing manager ; raşit çetiner } ; date of vacancy } ; hop { filter_eq { all_rows ; outgoing manager ; engin ipekoğlu } ; date of vacancy } } ; -8 days } = true | select the rows whose outgoing manager record fuzzily matches to raşit çetiner . take the date of vacancy record of this row . select the rows whose outgoing manager record fuzzily matches to engin ipekoğlu . take the date of vacancy record of this row . the second record is 8 days larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'outgoing manager_8': 8, 'raşit çetiner_9': 9, 'date of vacancy_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'outgoing manager_12': 12, 'engin ipekoğlu_13': 13, 'date of vacancy_14': 14, '-8 days_15':... | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'outgoing manager_8': 'outgoing manager', 'raşit çetiner_9': 'raşit çetiner', 'date of vacancy_10': 'date of vacancy', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str... | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'outgoing manager_8': [0], 'raşit çetiner_9': [0], 'date of vacancy_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'outgoing manager_12': [1], 'engin ipekoğlu_13': [1], 'date of vacancy... | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment'] | [['konyaspor', 'raşit çetiner', 'sacked', '17 september 2008', 'giray bulak', '24 september 2008'], ['kocaelispor', 'engin ipekoğlu', 'sacked', '25 september 2008', 'yılmaz vural', '28 september 2008'], ['beşiktaş', 'ertuğrul sağlam', 'resigned', '7 october 2008', 'mustafa denizli', '9 october 2008'], ['ankaragücü', 'h... |
1995 - 96 colorado avalanche season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Colorado_Avalanche_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11945691-4.html.csv | aggregation | the average number of points scored by the colorado avalanche in each game was 4.21 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '4.21', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '4.21', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '4.21'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 4.21 } = true', 'tointer': 'the average of the score record of all rows is 4.21 .'} | round_eq { avg { all_rows ; score } ; 4.21 } = true | the average of the score record of all rows is 4.21 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '4.21_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '4.21_5': '4.21'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '4.21_5': [1]} | ['date', 'visitor', 'score', 'home', 'record'] | [['december 1', 'colorado', '3 - 5', 'ny rangers', '15 - 6 - 4'], ['december 3', 'dallas', '7 - 6', 'colorado', '15 - 7 - 4'], ['december 5', 'san jose', '2 - 12', 'colorado', '16 - 7 - 4'], ['december 7', 'edmonton', '5 - 3', 'colorado', '16 - 8 - 4'], ['december 9', 'colorado', '7 - 3', 'ottawa', '17 - 8 - 4'], ['dec... |
danny sullivan | https://en.wikipedia.org/wiki/Danny_Sullivan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226454-1.html.csv | unique | the only time that danny sullivan finished in fourteenth place was 1982 . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '14', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'finish', '14'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose finish record is equal to 14 .', 'tostr': 'filter_eq { all_rows ; finish ; 14 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ;... | and { only { filter_eq { all_rows ; finish ; 14 } } ; eq { hop { filter_eq { all_rows ; finish ; 14 } ; year } ; 1982 } } = true | select the rows whose finish record is equal to 14 . there is only one such row in the table . the year record of this unqiue row is 1982 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'finish_7': 7, '14_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1982_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'finish_7': 'finish', '14_8': '14', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1982_10': '1982'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'finish_7': [0], '14_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1982_10': [3]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1982', '13', '196.292', '17', '14', '148'], ['1984', '28', '203.567', '17', '29', '57'], ['1985', '8', '210.298', '8', '1', '200'], ['1986', '2', '215.382', '2', '9', '197'], ['1987', '16', '210.271', '6', '13', '160'], ['1988', '2', '216.214', '2', '23', '101'], ['1989', '26', '216.027', '15', '28', '41'], ['1990',... |
1995 - 96 colorado avalanche season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Colorado_Avalanche_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11945691-4.html.csv | majority | all of the games took place in the month of december . | {'scope': 'all', 'col': '1', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'december', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'december'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to december .', 'tostr': 'all_eq { all_rows ; date ; december } = true'} | all_eq { all_rows ; date ; december } = true | for the date records of all rows , all of them fuzzily match to december . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'december_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'december_4': 'december'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'december_4': [0]} | ['date', 'visitor', 'score', 'home', 'record'] | [['december 1', 'colorado', '3 - 5', 'ny rangers', '15 - 6 - 4'], ['december 3', 'dallas', '7 - 6', 'colorado', '15 - 7 - 4'], ['december 5', 'san jose', '2 - 12', 'colorado', '16 - 7 - 4'], ['december 7', 'edmonton', '5 - 3', 'colorado', '16 - 8 - 4'], ['december 9', 'colorado', '7 - 3', 'ottawa', '17 - 8 - 4'], ['dec... |
list of memorial cup champions | https://en.wikipedia.org/wiki/List_of_Memorial_Cup_champions | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17751942-2.html.csv | superlative | of all the memorial cup champions , the toronto marlboros scored the most goals in a single championship game . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'champion'], 'result': 'toronto marlboros ( oha )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; champion }'}, 'toronto marlboros ( oha... | eq { hop { argmax { all_rows ; score } ; champion } ; toronto marlboros ( oha ) } = true | select the row whose score record of all rows is maximum . the champion record of this row is toronto marlboros ( oha ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'champion_6': 6, 'toronto marlboros (oha)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'champion_6': 'champion', 'toronto marlboros (oha)_7': 'toronto marlboros ( oha )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'champion_6': [1], 'toronto marlboros (oha)_7': [2]} | ['champion', 'score', 'runner - up', 'additional participants', 'host location ( s )'] | [['cornwall royals ( qmjhl )', '2 - 1', 'peterborough petes ( oha )', 'edmonton oil kings ( wchl )', 'ottawa'], ['toronto marlboros ( oha )', '9 - 1', 'quebec remparts ( qmjhl )', 'medicine hat tigers ( wchl )', 'montreal'], ['regina pats ( wchl )', '7 - 4', 'quebec remparts ( qmjhl )', 'st catharines black hawks ( oha... |
1977 baltimore colts season | https://en.wikipedia.org/wiki/1977_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14945608-1.html.csv | comparative | in the 1977 baltimore colts season , the game on october 16 had a higher attendance than the game on november 13 . | {'row_1': '5', 'row_2': '9', 'col': '7', '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', 'date', 'october 16 , 1977'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to october 16 , 1977 .', 'tostr': 'filter_eq { all_rows ; date ; october 16 , 1977 }'}, 'attendan... | greater { hop { filter_eq { all_rows ; date ; october 16 , 1977 } ; attendance } ; hop { filter_eq { all_rows ; date ; november 13 , 1977 } ; attendance } } = true | select the rows whose date record fuzzily matches to october 16 , 1977 . take the attendance record of this row . select the rows whose date record fuzzily matches to november 13 , 1977 . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'october 16 , 1977_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'november 13 , 1977_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'october 16 , 1977_8': 'october 16 , 1977', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11':... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'october 16 , 1977_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'november 13 , 1977_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 18 , 1977', 'seattle seahawks', 'w 29 - 14', '1 - 0', 'kingdome', '58991'], ['2', 'september 25 , 1977', 'new york jets', 'w 20 - 12', '2 - 0', 'shea stadium', '43439'], ['3', 'october 2 , 1977', 'buffalo bills', 'w 17 - 14', '3 - 0', 'memorial stadium', '49247'], ['4', 'october 9 , 1977', 'miami dolp... |
1920 summer olympics | https://en.wikipedia.org/wiki/1920_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-113485-1.html.csv | ordinal | sweden received the 2nd highest amount of bronze medals in the 1920 summer olympics . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'bronze', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; bronze ; 2 }'}, 'nation'], 'result': 'sweden', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; bronze ; 2 } ; nation }'}, 'sweden'], 'result'... | eq { hop { nth_argmax { all_rows ; bronze ; 2 } ; nation } ; sweden } = true | select the row whose bronze record of all rows is 2nd maximum . the nation record of this row is sweden . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '2_6': 6, 'nation_7': 7, 'sweden_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', 'bronze_5': 'bronze', '2_6': '2', 'nation_7': 'nation', 'sweden_8': 'sweden'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '2_6': [0], 'nation_7': [1], 'sweden_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '41', '27', '27', '95'], ['2', 'sweden', '19', '20', '25', '64'], ['3', 'great britain', '15', '15', '13', '43'], ['4', 'finland', '15', '10', '9', '34'], ['5', 'belgium ( host nation )', '14', '11', '11', '36'], ['6', 'norway', '13', '9', '9', '31'], ['7', 'italy', '13', '5', '5', '23'], ['8', ... |
1981 new york yankees season | https://en.wikipedia.org/wiki/1981_New_York_Yankees_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11487949-8.html.csv | count | in the 1981 nyy season games listed , 3 games were played at yankee stadium . | {'scope': 'all', 'criterion': 'equal', 'value': 'yankee stadium', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'yankee stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to yankee stadium .', 'tostr': 'filter_eq { all_rows ; location ; yankee stadium }'}], 'result': '3... | eq { count { filter_eq { all_rows ; location ; yankee stadium } } ; 3 } = true | select the rows whose location record fuzzily matches to yankee stadium . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location_5': 5, 'yankee stadium_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location_5': 'location', 'yankee stadium_6': 'yankee stadium', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'yankee stadium_6': [0], '3_7': [2]} | ['game', 'score', 'date', 'location', 'attendance', 'time of game'] | [['1', 'dodgers - 3 , yankees - 5', 'october 20', 'yankee stadium ( new york )', '56470', '2:32'], ['2', 'dodgers - 0 , yankees - 3', 'october 21', 'yankee stadium ( new york )', '56505', '2:29'], ['3', 'yankees - 4 , dodgers - 5', 'october 23', 'dodger stadium ( los angeles )', '56236', '3:04'], ['4', 'yankees - 7 , d... |
2005 buffalo bills season | https://en.wikipedia.org/wiki/2005_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18695319-1.html.csv | count | a total of two players from miami ( fla ) college were picked in the 2005 buffalo bills season . | {'scope': 'all', 'criterion': 'equal', 'value': 'miami ( fla )', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'miami ( fla )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to miami ( fla ) .', 'tostr': 'filter_eq { all_rows ; college ; miami ( fla ) }'}], 'result': '2', 'in... | eq { count { filter_eq { all_rows ; college ; miami ( fla ) } } ; 2 } = true | select the rows whose college record fuzzily matches to miami ( fla ) . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'college_5': 5, 'miami (fla)_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'college_5': 'college', 'miami (fla)_6': 'miami ( fla )', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'college_5': [0], 'miami (fla)_6': [0], '2_7': [2]} | ['round', 'pick', 'player', 'position', 'college'] | [['2', '5', 'roscoe parrish', 'wide receiver', 'miami ( fla )'], ['3', '86', 'kevin everett', 'tight end', 'miami ( fla )'], ['4', '122', 'duke preston', 'center', 'illinois'], ['5', '156', 'eric king', 'cornerback', 'wake forest'], ['6', '197', 'justin geisinger', 'offensive guard', 'vanterbilt'], ['7', '236', 'lionel... |
2007 calgary stampeders season | https://en.wikipedia.org/wiki/2007_Calgary_Stampeders_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12297537-1.html.csv | ordinal | jabari arthur was the third highest picked player for the calgary stampeders in the 2007 draft . | {'row': '3', 'col': '2', 'order': '3', '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', 'pick', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; pick ; 3 }'}, 'player'], 'result': 'jabari arthur', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; pick ; 3 } ; player }'}, 'jabari arthur'], ... | eq { hop { nth_argmin { all_rows ; pick ; 3 } ; player } ; jabari arthur } = true | select the row whose pick record of all rows is 3rd minimum . the player record of this row is jabari arthur . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'pick_5': 5, '3_6': 6, 'player_7': 7, 'jabari arthur_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', 'pick_5': 'pick', '3_6': '3', 'player_7': 'player', 'jabari arthur_8': 'jabari arthur'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'pick_5': [0], '3_6': [0], 'player_7': [1], 'jabari arthur_8': [2]} | ['round', 'pick', 'player', 'position', 'school / club team'] | [['1', '3', 'mike gyetvai', 'ol', 'michigan state'], ['1', '5', 'justin phillips', 'lb', 'wilfrid laurier'], ['1', '6', 'jabari arthur', 'wr', 'akron'], ['2', '14', 'kevin challenger', 'wr', 'boston college'], ['3', '21', 'patrick macdonald', 'dl', 'alberta'], ['5', '35', 'henry bekkering', 'k', 'eastern washington'], ... |
the rob brydon show | https://en.wikipedia.org/wiki/The_Rob_Brydon_Show | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29135051-2.html.csv | comparative | more people tuned into the rob brydon show when the musical guest was the script than when it was hurts . | {'row_1': '1', 'row_2': '6', 'col': '6', 'col_other': '4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'singer ( s )', 'the script'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose singer ( s ) record fuzzily matches to the script .', 'tostr': 'filter_eq { all_rows ; singer ( s ) ; the script }'}, 'ratin... | greater { hop { filter_eq { all_rows ; singer ( s ) ; the script } ; ratings } ; hop { filter_eq { all_rows ; singer ( s ) ; hurts } ; ratings } } = true | select the rows whose singer ( s ) record fuzzily matches to the script . take the ratings record of this row . select the rows whose singer ( s ) record fuzzily matches to hurts . take the ratings 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, 'singer (s)_7': 7, 'the script_8': 8, 'ratings_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'singer (s)_11': 11, 'hurts_12': 12, 'ratings_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', 'singer (s)_7': 'singer ( s )', 'the script_8': 'the script', 'ratings_9': 'ratings', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'singer (s)_11':... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'singer (s)_7': [0], 'the script_8': [0], 'ratings_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'singer (s)_11': [1], 'hurts_12': [1], 'ratings_13': [3]} | ['episode', 'broadcast date', 'guest ( s )', 'singer ( s )', 'comedian', 'ratings'] | [['1', '22 july 2011', 'matt lucas', 'the script', 'nina conti', '2.08 m'], ['2', '29 july 2011', 'bill bailey', 'beverley knight', 'celia pacquola', '1.45 m'], ['3', '5 august 2011', 'bruce forsyth', 'sophie ellis - bextor', 'elis james', 'under 1.41 m'], ['4', '12 august 2011', "chris o'dowd", 'the faces', 'josh widd... |
2000 masters tournament | https://en.wikipedia.org/wiki/2000_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514630-7.html.csv | unique | in the 2000 masters tournament , only one player from united states won less than 140,000 prize money . | {'scope': 'subset', 'row': '10', 'col': '6', 'col_other': '3', 'criterion': 'less_than', 'value': '140000', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'money', '1... | only { filter_less { filter_eq { all_rows ; country ; united states } ; money ; 140000 } } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose money record is less than 140000 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, 'money_7': 7, '140000_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', 'money_7': 'money', '140000_8': '140000'} | {'only_2': [3], 'result_3': [], 'filter_less_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], 'money_7': [1], '140000_8': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'vijay singh', 'fiji', '72 + 67 + 70 + 69 = 278', '- 10', '828000'], ['2', 'ernie els', 'south africa', '72 + 67 + 74 + 68 = 281', '- 7', '496800'], ['t3', 'david duval', 'united states', '73 + 65 + 74 + 70 = 282', '- 6', '266800'], ['t3', 'loren roberts', 'united states', '73 + 69 + 71 + 69 = 282', '- 6', '2668... |
concrete canoe | https://en.wikipedia.org/wiki/Concrete_canoe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2331549-1.html.csv | comparative | for concrete canoe , the host city was buffalo , new york one year before the host city was orlando , florida . | {'row_1': '3', 'row_2': '4', 'col': '1', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'host city', 'buffalo , new york'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose host city record fuzzily matches to buffalo , new york .', 'tostr': 'filter_eq { all_rows ; host c... | eq { diff { hop { filter_eq { all_rows ; host city ; buffalo , new york } ; year } ; hop { filter_eq { all_rows ; host city ; orlando , florida } ; year } } ; -1 } = true | select the rows whose host city record fuzzily matches to buffalo , new york . take the year record of this row . select the rows whose host city record fuzzily matches to orlando , florida . take the year record of this row . the second record is 1 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'host city_8': 8, 'buffalo , new york_9': 9, 'year_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'host city_12': 12, 'orlando , florida_13': 13, 'year_14': 14, '-1_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'host city_8': 'host city', 'buffalo , new york_9': 'buffalo , new york', 'year_10': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', '... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'host city_8': [0], 'buffalo , new york_9': [0], 'year_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'host city_12': [1], 'orlando , florida_13': [1], 'year_14': [3], '-1_15': [5]} | ['year', 'host city', 'host school', 'champion', 'second place', 'third place'] | [['1988', 'east lansing , michigan', 'michigan state university', 'university of california , berkeley', 'university of new hampshire', 'university of akron'], ['1989', 'lubbock , texas', 'texas tech university', 'university of california , berkeley', 'michigan state university', 'university of new hampshire'], ['1990'... |
1951 - 52 illinois fighting illini men 's basketball team | https://en.wikipedia.org/wiki/1951%E2%80%9352_Illinois_Fighting_Illini_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22824312-1.html.csv | aggregation | the average weight of players on the 1951 - 52 illinois fighting illini men 's basketball team is 188 lb . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '188', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weight'], 'result': '188', 'ind': 0, 'tostr': 'avg { all_rows ; weight }'}, '188'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weight } ; 188 } = true', 'tointer': 'the average of the weight record of all rows is 188 .'} | round_eq { avg { all_rows ; weight } ; 188 } = true | the average of the weight record of all rows is 188 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weight_4': 4, '188_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weight_4': 'weight', '188_5': '188'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weight_4': [0], '188_5': [1]} | ['no', 'player', 'position', 'height', 'weight', 'class', 'hometown'] | [['9', 'elmer plew', 'guard', '6 - 0', '170', 'freshman', 'paris , illinois'], ['11', 'jim dutcher', 'forward', '6 - 3', '185', 'freshman', 'downers grove , illinois'], ['16', 'jim wright', 'guard', '6 - 0', '160', 'sophomore', 'lawrenceville , illinois'], ['19', 'james bredar', 'guard', '5 - 11', '167', 'junior', 'sal... |
casey martin | https://en.wikipedia.org/wiki/Casey_Martin | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1697190-2.html.csv | superlative | casey martin 's best finish in a tournament on the pga tour was in 2000 when he finished tied 17th . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'best finish'], 'result': 't - 17', 'ind': 0, 'tostr': 'max { all_rows ; best finish }', 'tointer': 'the maximum best finish record of all rows is t - 17 .'}, 't - 17'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; best f... | and { eq { max { all_rows ; best finish } ; t - 17 } ; eq { hop { argmax { all_rows ; best finish } ; year } ; 2000 } } = true | the maximum best finish record of all rows is t - 17 . the year record of the row with superlative best finish record is 2000 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'best finish_8': 8, 't - 17_9': 9, 'eq_4': 4, 'num_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'best finish_11': 11, 'year_12': 12, '2000_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'best finish_8': 'best finish', 't - 17_9': 't - 17', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'best finish_11': 'best finish', 'year_12': 'year', '2000_13': '2000'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'best finish_8': [0], 't - 17_9': [1], 'eq_4': [5], 'num_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'best finish_11': [2], 'year_12': [3], '2000_13': [4]} | ['year', 'tournaments played', 'cuts made', 'wins', 'best finish', 'earnings', 'money list rank'] | [['1998', '3', '2', '0', 't - 23', '37221', '221'], ['2000', '29', '14', '0', 't - 17', '143248', '179'], ['2001', '2', '0', '0', 'cut', '0', 'n / a'], ['2002', '3', '0', '0', 'cut', '0', 'n / a'], ['2003', '1', '0', '0', 'cut', '0', 'n / a'], ['2004', '2', '2', '0', 't - 69', '15858', 'n / a'], ['2005', '1', '1', '0',... |
list of the busiest airports in the united states | https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18047346-5.html.csv | superlative | the memphis international airport is the most busy airport in the country . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'tonnes'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; tonnes }'}, 'airport name'], 'result': 'memphis international airport', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; tonnes } ; airport name }'}, 'memphis ... | eq { hop { argmax { all_rows ; tonnes } ; airport name } ; memphis international airport } = true | select the row whose tonnes record of all rows is maximum . the airport name record of this row is memphis international airport . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'tonnes_5': 5, 'airport name_6': 6, 'memphis international airport_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'tonnes_5': 'tonnes', 'airport name_6': 'airport name', 'memphis international airport_7': 'memphis international airport'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'tonnes_5': [0], 'airport name_6': [1], 'memphis international airport_7': [2]} | ['rank', 'airport name', 'location', 'iata code', 'tonnes', '% chg 2010 / 11'] | [['1', 'memphis international airport', 'memphis , tennessee', 'mem', '3916410', '0 0.0 %'], ['2', 'ted stevens anchorage international airport', 'anchorage , alaska', 'anc', '2543105', '0 3.9 %'], ['3', 'louisville international airport', 'louisville , kentucky', 'sdf', '2188422', '0 1.0 %'], ['4', 'miami internationa... |
2004 amsterdam admirals season | https://en.wikipedia.org/wiki/2004_Amsterdam_Admirals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24951872-2.html.csv | ordinal | the amsterdam admirals ' game against rhein fire recorded their 2nd highest attendance of the 2004 season . | {'row': '6', 'col': '8', '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', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'opponent'], 'result': 'rhein fire', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; opponent }'},... | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; opponent } ; rhein fire } = true | select the row whose attendance record of all rows is 2nd maximum . the opponent record of this row is rhein fire . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'opponent_7': 7, 'rhein fire_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'opponent_7': 'opponent', 'rhein fire_8': 'rhein fire'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'opponent_7': [1], 'rhein fire_8': [2]} | ['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance'] | [['1', 'saturday , april 3', '7:00 pm', 'frankfurt galaxy', 'l 11 - 34', '0 - 1', 'waldstadion', '21269'], ['2', 'saturday , april 10', '7:00 pm', 'berlin thunder', 'l 17 - 28', '0 - 2', 'amsterdam arena', '10763'], ['3', 'sunday , april 18', '2:00 pm', 'scottish claymores', 'w 3 - 0', '1 - 2', 'hampden park', '10971']... |
idaho vandals football | https://en.wikipedia.org/wiki/Idaho_Vandals_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15164733-4.html.csv | comparative | wayne walker was a higher overall pick than john yarno was . | {'row_1': '4', 'row_2': '9', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'wayne walker'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to wayne walker .', 'tostr': 'filter_eq { all_rows ; player ; wayne walker }'}, 'overall pick'], 'res... | less { hop { filter_eq { all_rows ; player ; wayne walker } ; overall pick } ; hop { filter_eq { all_rows ; player ; john yarno } ; overall pick } } = true | select the rows whose player record fuzzily matches to wayne walker . take the overall pick record of this row . select the rows whose player record fuzzily matches to john yarno . take the overall pick record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'wayne walker_8': 8, 'overall pick_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'john yarno_12': 12, 'overall pick_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'wayne walker_8': 'wayne walker', 'overall pick_9': 'overall pick', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'play... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'wayne walker_8': [0], 'overall pick_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'john yarno_12': [1], 'overall pick_13': [3]} | ['player', 'position', 'overall pick', 'round', 'nfl draft', 'franchise'] | [['ray mcdonald', 'rb', '13', '1st', '1967', 'washington redskins'], ['mike iupati', 'g', '17', '1st', '2010', 'san francisco 49ers'], ['jerry kramer', 'g / pk', '39', '4th', '1958', 'green bay packers'], ['wayne walker', 'lb / pk', '44', '4th', '1958', 'detroit lions'], ['carl kiilsgaard', 't', '61', '5th', '1950', 'c... |
glimt | https://en.wikipedia.org/wiki/FK_Bod%C3%B8/Glimt | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-159867-1.html.csv | unique | the 1978 - 79 season was the only season that glimt played against a team from luxembourg . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'luxembourg', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'luxembourg'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to luxembourg .', 'tostr': 'filter_eq { all_rows ; country ; luxembourg }'}], 'result': True, 'ind': 1, '... | and { only { filter_eq { all_rows ; country ; luxembourg } } ; eq { hop { filter_eq { all_rows ; country ; luxembourg } ; season } ; 1978 - 79 } } = true | select the rows whose country record fuzzily matches to luxembourg . there is only one such row in the table . the season record of this unqiue row is 1978 - 79 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'Luxembourg_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '1978 - 79_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'Luxembourg_8': 'luxembourg', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '1978 - 79_10': '1978 - 79'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'Luxembourg_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '1978 - 79_10': [3]} | ['season', 'round', 'country', 'opponent', 'result'] | [['1976 - 77', 'first round', 'italy', 'napoli', '0 - 2 , 0 - 1'], ['1978 - 79', 'first round', 'luxembourg', 'union luxembourg', '4 - 1 , 0 - 1'], ['1978 - 79', 'second round', 'italy', 'internazionale', '0 - 5 , 1 - 2'], ['1994 - 95', 'qualifying round', 'latvia', 'olimpija rīga', '6 - 0 , 0 - 0'], ['1994 - 95', 'fir... |
nemzeti bajnokság i ( men 's handball ) | https://en.wikipedia.org/wiki/Nemzeti_Bajnoks%C3%A1g_I_%28men%27s_handball%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12777591-5.html.csv | superlative | the most titles in men 's handball were won by the budapest team . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'titles'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; titles }'}, 'city'], 'result': 'budapest', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; titles } ; city }'}, 'budapest'], 'result': True, 'ind': 2, 'tostr'... | eq { hop { argmax { all_rows ; titles } ; city } ; budapest } = true | select the row whose titles record of all rows is maximum . the city record of this row is budapest . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'titles_5': 5, 'city_6': 6, 'budapest_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'titles_5': 'titles', 'city_6': 'city', 'budapest_7': 'budapest'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'titles_5': [0], 'city_6': [1], 'budapest_7': [2]} | ['rank', 'city', 'titles', 'winning clubs', 'last victory'] | [['1', 'budapest', '26', 'honvéd spartacus elektromos se vörös meteor újpest', '1991'], ['2', 'veszprém', '20', 'veszprém ( 20 )', '2012'], ['3', 'tatabánya', '4', 'tatabánya ( 4 )', '1984'], ['4', 'győr', '3', 'győr ( 3 )', '1990'], ['5', 'szeged', '2', 'szeged ( 2 )', '2007'], ['6', 'dunaújváros', '1', 'dunaferr se (... |
95th united states congress | https://en.wikipedia.org/wiki/95th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1013168-3.html.csv | majority | the majority of vacant seats were not filled during the term of the 95th united states congress . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'not filled this term', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'vacant'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'vacant'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; successor ; vacant }', 'tointer': 'select the rows whose successor record fuzzily matches to vacant .'}, 'date successor seated', 'not filled this term'], 'r... | most_eq { filter_eq { all_rows ; successor ; vacant } ; date successor seated ; not filled this term } = true | select the rows whose successor record fuzzily matches to vacant . for the date successor seated records of these rows , most of them fuzzily match to not filled this term . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'successor_4': 4, 'vacant_5': 5, 'date successor seated_6': 6, 'not filled this term_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'successor_4': 'successor', 'vacant_5': 'vacant', 'date successor seated_6': 'date successor seated', 'not filled this term_7': 'not filled this term'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'successor_4': [0], 'vacant_5': [0], 'date successor seated_6': [1], 'not filled this term_7': [1]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['louisiana 1st', 'richard a tonry ( d )', 'forced to resign may 4 , 1977', 'bob livingston ( r )', 'august 27 , 1977'], ['new york 21st', 'robert garcía ( r - l )', 'changed parties february 21 , 1978', 'robert garcía ( d )', 'february 21 , 1978'], ['tennessee 5th', 'clifford allen ( d )', 'died june 18 , 1978', 'vac... |
1999 - 2000 philadelphia flyers season | https://en.wikipedia.org/wiki/1999%E2%80%932000_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14173105-18.html.csv | unique | in the 1999-2000 philadelphia flyers season , the only player from sweden is david nystrom . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'sweden', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'sweden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to sweden .', 'tostr': 'filter_eq { all_rows ; nationality ; sweden }'}], 'result': True, 'ind': 1, '... | and { only { filter_eq { all_rows ; nationality ; sweden } } ; eq { hop { filter_eq { all_rows ; nationality ; sweden } ; player } ; david nystrom } } = true | select the rows whose nationality record fuzzily matches to sweden . there is only one such row in the table . the player record of this unqiue row is david nystrom . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'sweden_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'david nystrom_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', 'sweden_8': 'sweden', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'david nystrom_10': 'david nystrom'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'sweden_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'david nystrom_10': [3]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'maxime ouellet', 'goaltender', 'canada', 'quebec remparts ( qmjhl )'], ['4', 'jeff feniak', 'defense', 'canada', 'calgary hitmen ( whl )'], ['6', 'konstantin rudenko', 'forward', 'russia', 'severstal cherepovets ( rus )'], ['7', 'pavel kasparik', 'center', 'czech republic', 'ihc pisek ( cze )'], ['7', 'vaclav p... |
swimming at the 2000 summer olympics - women 's 200 metre individual medley | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Women%27s_200_metre_individual_medley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446647-4.html.csv | ordinal | marianne limpert had the third fastest swimming time at the 2000 summer olympics - women 's 200 metre individual medley . | {'row': '3', 'col': '5', 'order': '3', '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', 'time', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; time ; 3 }'}, 'name'], 'result': 'marianne limpert', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; time ; 3 } ; name }'}, 'marianne limpert']... | eq { hop { nth_argmin { all_rows ; time ; 3 } ; name } ; marianne limpert } = true | select the row whose time record of all rows is 3rd minimum . the name record of this row is marianne limpert . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, '3_6': 6, 'name_7': 7, 'marianne limpert_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', '3_6': '3', 'name_7': 'name', 'marianne limpert_8': 'marianne limpert'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], '3_6': [0], 'name_7': [1], 'marianne limpert_8': [2]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'beatrice cäƒslaru', 'romania', '2:13.31'], ['2', '5', 'joanne malar', 'canada', '2:13.59'], ['3', '3', 'marianne limpert', 'canada', '2:13.90'], ['4', '6', 'gabrielle rose', 'united states', '2:14.40'], ['5', '2', 'federica biscia', 'italy', '2:15.71'], ['6', '1', 'elli overton', 'australia', '2:15.74'], [... |
los angeles lakers all - time roster | https://en.wikipedia.org/wiki/Los_Angeles_Lakers_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10560886-17.html.csv | majority | all players in the los angeles lakers all - time roster are from the united states . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , all of them fuzzily match to united states .', 'tostr': 'all_eq { all_rows ; nationality ; united states } = true'} | all_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , all of them fuzzily match to united states . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'nationality', 'position', 'from', 'school / country'] | [['jannero pargo', 'united states', 'guard', '2002', 'arkansas'], ['parker , smush smush parker', 'united states', 'guard', '2005', 'fordham'], ['myles patrick', 'united states', 'forward', '1980', 'auburn'], ['ruben patterson', 'united states', 'guard / forward', '1998', 'cincinnati'], ['jim paxson', 'united states', ... |
1997 european judo championships | https://en.wikipedia.org/wiki/1997_European_Judo_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11755180-3.html.csv | majority | most of the competing nations won zero gold medals . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'gold', '0'], 'result': True, 'ind': 0, 'tointer': 'for the gold records of all rows , most of them are equal to 0 .', 'tostr': 'most_eq { all_rows ; gold ; 0 } = true'} | most_eq { all_rows ; gold ; 0 } = true | for the gold records of all rows , most of them are equal to 0 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'gold_3': 3, '0_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'gold_3': 'gold', '0_4': '0'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'gold_3': [0], '0_4': [0]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'belgium', '6', '0', '3', '9'], ['2 =', 'germany', '2', '2', '2', '7'], ['2 =', 'netherlands', '2', '2', '2', '6'], ['4', 'turkey', '2', '0', '1', '3'], ['5', 'france', '1', '3', '6', '10'], ['6', 'belarus', '1', '2', '1', '4'], ['7', 'georgia', '1', '1', '0', '2'], ['8', 'poland', '1', '0', '4', '5'], ['9', 'gr... |
australian technology network | https://en.wikipedia.org/wiki/Australian_Technology_Network | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1187124-1.html.csv | unique | queensland university of technology is the only austrialian technology network university ranked in the top 300 in the world university rankings . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'less_than', 'value': '300', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'the world university rankings 2012 - 13', '300'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose the world university rankings 2012 - 13 record is less than 300 .', 'tostr': 'filter_less { all_rows ; the world ... | and { only { filter_less { all_rows ; the world university rankings 2012 - 13 ; 300 } } ; eq { hop { filter_less { all_rows ; the world university rankings 2012 - 13 ; 300 } ; university } ; queensland university of technology } } = true | select the rows whose the world university rankings 2012 - 13 record is less than 300 . there is only one such row in the table . the university record of this unqiue row is queensland university of technology . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'the world university rankings 2012 - 13_7': 7, '300_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'university_9': 9, 'queensland university of technology_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'the world university rankings 2012 - 13_7': 'the world university rankings 2012 - 13', '300_8': '300', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'university_9': 'university', 'queensland university of t... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'the world university rankings 2012 - 13_7': [0], '300_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'university_9': [2], 'queensland university of technology_10': [3]} | ['university', 'location', 'year of foundation', 'university status', 'the world university rankings 2012 - 13', 'academic ranking of world universities 2012', 'qs world university rankings 2012'] | [['curtin university', 'perth , wa', '1902', '1986', 'not ranked', '401 - 500', '258'], ['queensland university of technology', 'brisbane , qld', '1908', '1989', '251 - 275', 'not ranked', '281'], ['royal melbourne institute of technology', 'melbourne , vic', '1887', '1992', 'not ranked', 'not ranked', '246'], ['univer... |
1997 - 98 toronto raptors season | https://en.wikipedia.org/wiki/1997%E2%80%9398_Toronto_Raptors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13619053-9.html.csv | unique | during april of the 1997 - 98 toronto raptors season , the team only won once , against new jersey . | {'scope': 'all', 'row': '8', 'col': '4', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; score ; w }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_r... | and { only { filter_eq { all_rows ; score ; w } } ; eq { hop { filter_eq { all_rows ; score ; w } ; team } ; new jersey } } = true | select the rows whose score record fuzzily matches to w . there is only one such row in the table . the team record of this unqiue row is new jersey . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, 'w_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'team_9': 9, 'new jersey_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', 'w_8': 'w', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team_9': 'team', 'new jersey_10': 'new jersey'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], 'w_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'team_9': [2], 'new jersey_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['72', 'april 1', 'atlanta', 'l 91 - 105 ( ot )', 'doug christie , gary trent ( 14 )', 'marcus camby , tracy mcgrady ( 9 )', 'doug christie ( 3 )', 'georgia dome 10441', '15 - 57'], ['73', 'april 3', 'washington', 'l 112 - 120 ( ot )', 'dee brown ( 30 )', 'gary trent ( 10 )', 'dee brown ( 6 )', 'mci center 18324', '15... |
2008 - 09 san antonio spurs season | https://en.wikipedia.org/wiki/2008%E2%80%9309_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17288845-11.html.csv | count | during this period of the 2008-09 san antonio spurs season , the san antonio spurs played two games at the american airlines center . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'american airlines center', 'result': '2', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'american airlines center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to american airlines center .', 'tostr': 'filter_eq { all_rows ; lo... | eq { count { filter_eq { all_rows ; location attendance ; american airlines center } } ; 2 } = true | select the rows whose location attendance record fuzzily matches to american airlines center . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'american airlines center_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'american airlines center_6': 'american airlines center', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'american airlines center_6': [0], '2_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 18', 'dallas', 'l 97 - 105 ( ot )', 'tim duncan ( 27 )', 'tim duncan ( 9 )', 'tony parker ( 8 )', 'at & t center 18797', '0 - 1'], ['2', 'april 20', 'dallas', 'w 105 - 84 ( ot )', 'tony parker ( 38 )', 'tim duncan ( 11 )', 'tony parker ( 8 )', 'at & t center 18797', '1 - 1'], ['3', 'april 23', 'dallas', '... |
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 | comparative | the game against the cleveland browns drew a bigger crowd than the game against the dallas cowboys . | {'row_1': '1', 'row_2': '2', 'col': '5', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'cleveland browns'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to cleveland browns .', 'tostr': 'filter_eq { all_rows ; opponent ; cleveland browns }'}, ... | greater { hop { filter_eq { all_rows ; opponent ; cleveland browns } ; attendance } ; hop { filter_eq { all_rows ; opponent ; dallas cowboys } ; attendance } } = true | select the rows whose opponent record fuzzily matches to cleveland browns . take the attendance record of this row . select the rows whose opponent record fuzzily matches to dallas cowboys . take the attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'cleveland browns_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'dallas cowboys_12': 12, 'attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'cleveland browns_8': 'cleveland browns', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opp... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'cleveland browns_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'dallas cowboys_12': [1], 'attendance_13': [3]} | ['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 b... |
2010 - 11 boston celtics season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27722408-10.html.csv | count | in the 2010 - 11 boston celtics season , when the celtics won , there were three times that ray allen had at least a share of the high points . | {'scope': 'subset', 'criterion': 'equal', 'value': 'ray allen', 'result': '3', 'col': '5', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'w'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; w }', 'tointer': 'select the rows whose score record fuzzily matches to w .'}, 'high points', 'ray allen'... | eq { count { filter_eq { filter_eq { all_rows ; score ; w } ; high points ; ray allen } } ; 3 } = true | select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high points record fuzzily matches to ray allen . the number of such rows is 3 . | 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, 'score_6': 6, 'w_7': 7, 'high points_8': 8, 'ray allen_9': 9, '3_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', 'score_6': 'score', 'w_7': 'w', 'high points_8': 'high points', 'ray allen_9': 'ray allen', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'score_6': [0], 'w_7': [0], 'high points_8': [1], 'ray allen_9': [1], '3_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 2', 'phoenix', 'w 115 - 103 ( ot )', 'kevin garnett ( 28 )', 'paul pierce ( 13 )', 'rajon rondo ( 15 )', 'td garden 18624', '44 - 15'], ['60', 'march 4', 'golden state', 'w 107 - 103 ( ot )', 'ray allen , paul pierce ( 27 )', 'paul pierce ( 7 )', 'rajon rondo ( 16 )', 'td garden 18624', '45 - 15'], ['61'... |
2008 brazilian grand prix | https://en.wikipedia.org/wiki/2008_Brazilian_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14270784-2.html.csv | count | 2 drivers in the 2008 brazilian grand prix had cars constructed by honda . | {'scope': 'all', 'criterion': 'equal', 'value': 'honda', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'constructor', 'honda'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose constructor record fuzzily matches to honda .', 'tostr': 'filter_eq { all_rows ; constructor ; honda }'}], 'result': '2', 'ind': 1, 'tost... | eq { count { filter_eq { all_rows ; constructor ; honda } } ; 2 } = true | select the rows whose constructor record fuzzily matches to honda . 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, 'constructor_5': 5, 'honda_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', 'constructor_5': 'constructor', 'honda_6': 'honda', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'constructor_5': [0], 'honda_6': [0], '2_7': [2]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['felipe massa', 'ferrari', '71', '1:34:11.435', '1'], ['fernando alonso', 'renault', '71', '+ 13.298', '6'], ['kimi räikkönen', 'ferrari', '71', '+ 16.235', '3'], ['sebastian vettel', 'toro rosso - ferrari', '71', '+ 38.011', '7'], ['lewis hamilton', 'mclaren - mercedes', '71', '+ 38.907', '4'], ['timo glock', 'toyot... |
flavio cipolla | https://en.wikipedia.org/wiki/Flavio_Cipolla | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16474033-6.html.csv | comparative | flavio cipolla partnered with simon stadler before he partnered with paolo lorenzi . | {'row_1': '2', 'row_2': '17', 'col': '1', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'partnering', 'simon stadler'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose partnering record fuzzily matches to simon stadler .', 'tostr': 'filter_eq { all_rows ; partnering ; simon stadler }'}, 'date'... | less { hop { filter_eq { all_rows ; partnering ; simon stadler } ; date } ; hop { filter_eq { all_rows ; partnering ; paolo lorenzi } ; date } } = true | select the rows whose partnering record fuzzily matches to simon stadler . take the date record of this row . select the rows whose partnering record fuzzily matches to paolo lorenzi . 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, 'partnering_7': 7, 'simon stadler_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'partnering_11': 11, 'paolo lorenzi_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', 'partnering_7': 'partnering', 'simon stadler_8': 'simon stadler', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'partnering_11': 'partne... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'partnering_7': [0], 'simon stadler_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'partnering_11': [1], 'paolo lorenzi_12': [1], 'date_13': [3]} | ['date', 'tournament', 'surface', 'partnering', 'opponents', 'score'] | [['4 july 2005', 'mantova , italy', 'clay', 'alessandro motti', 'salvador navarro óscar serrano', '5 - 7 , 6 - 3 , 6 - 3'], ['2 august 2005', 'saransk , russia', 'clay', 'simon stadler', 'konstantin kravchuk alexander kudryavtsev', '7 - 6 ( 7 - 2 ) , 4 - 6 , 7 - 6 ( 7 - 3 )'], ['19 september 2005', 'banja luka , bosnia... |
variobahn | https://en.wikipedia.org/wiki/Variobahn | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14316789-1.html.csv | majority | all variobahn whose owner is mvv verkehr has 80 seats at least . | {'scope': 'subset', 'col': '8', 'most_or_all': 'all', 'criterion': 'greater_than_eq', 'value': '80', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'mvv verkehr'}} | {'func': 'all_greater_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'owner', 'mvv verkehr'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; owner ; mvv verkehr }', 'tointer': 'select the rows whose owner record fuzzily matches to mvv verkehr .'}, 'seats', '80'], 'result': True, 'ind': 1, 'toi... | all_greater_eq { filter_eq { all_rows ; owner ; mvv verkehr } ; seats ; 80 } = true | select the rows whose owner record fuzzily matches to mvv verkehr . for the seats records of these rows , all of them are greater than or equal to 80 . | 2 | 2 | {'all_greater_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'owner_4': 4, 'mvv verkehr_5': 5, 'seats_6': 6, '80_7': 7} | {'all_greater_eq_1': 'all_greater_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'owner_4': 'owner', 'mvv verkehr_5': 'mvv verkehr', 'seats_6': 'seats', '80_7': '80'} | {'all_greater_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'owner_4': [0], 'mvv verkehr_5': [0], 'seats_6': [1], '80_7': [1]} | ['system', 'owner', 'quantity', 'delivery', 'length', 'gauge', 'operation', 'seats', 'standing'] | [['chemnitz stadtbahn', 'chemnitzer verkehrs - aktiengesellschaft', '14', '1993 - 2000', '-', 'standard', 'uni', '89', '123'], ['chemnitz stadtbahn', 'chemnitzer verkehrs - aktiengesellschaft', '10', '2000', '-', 'standard', 'bi', '74', '124'], ['city - bahn chemnitz', 'city - bahn chemnitz', '6', '2001', '-', 'standar... |
media in bismarck - mandan | https://en.wikipedia.org/wiki/Media_in_Bismarck-Mandan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14623167-1.html.csv | aggregation | the average physical channel number for tv stations in bismarck , nd is around 22 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '22', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'physical'], 'result': '22', 'ind': 0, 'tostr': 'avg { all_rows ; physical }'}, '22'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; physical } ; 22 } = true', 'tointer': 'the average of the physical record of all rows is 22 .'} | round_eq { avg { all_rows ; physical } ; 22 } = true | the average of the physical record of all rows is 22 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'physical_4': 4, '22_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'physical_4': 'physical', '22_5': '22'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'physical_4': [0], '22_5': [1]} | ['virtual', 'physical', 'call sign', 'branding', 'network', 'owner'] | [['3', '22', 'kbme - tv', 'prairie public', 'pbs', 'prairie public broadcasting'], ['5', '31', 'kfyr - tv', 'kfyr - tv nbc north dakota', 'nbc', 'hoak media corporation'], ['12', '12', 'kxmb - tv', 'kxmb cbs 12 kx television', 'cbs', 'reiten broadcasting'], ['17', '17', 'kbmy', 'kbmy 17', 'abc', 'forum communications']... |
2008 - 09 atlanta hawks season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17311759-9.html.csv | majority | all games of the atlanta hawks ' in the 2008 - 09 season were played in the month of april . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'april', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'april'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to april .', 'tostr': 'all_eq { all_rows ; date ; april } = true'} | all_eq { all_rows ; date ; april } = true | for the date records of all rows , all of them fuzzily match to april . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'april_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'april_4': 'april'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'april_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 3', 'boston', 'l 92 - 104 ( ot )', 'ronald murray ( 21 )', 'josh smith ( 10 )', 'mike bibby ( 6 )', 'td banknorth garden 18624', '43 - 33'], ['77', 'april 4', 'orlando', 'l 82 - 88 ( ot )', 'joe johnson ( 21 )', 'al horford ( 13 )', 'mike bibby ( 5 )', 'philips arena 19608', '43 - 34'], ['78', 'april 7',... |
1961 san francisco 49ers season | https://en.wikipedia.org/wiki/1961_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16715979-2.html.csv | count | there were three games during this season where there were less than 40000 fans at the 49ers game . | {'scope': 'all', 'criterion': 'less_than', 'value': '40000', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '40000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 40000 .', 'tostr': 'filter_less { all_rows ; attendance ; 40000 }'}], 'result': '3', 'ind': 1, 'tostr': 'coun... | eq { count { filter_less { all_rows ; attendance ; 40000 } } ; 3 } = true | select the rows whose attendance record is less than 40000 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '40000_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '40000_6': '40000', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '40000_6': [0], '3_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 17 , 1961', 'washington redskins', 'w 35 - 3', '43412'], ['2', 'september 24 , 1961', 'green bay packers', 'l 30 - 10', '38624'], ['3', 'october 1 , 1961', 'detroit lions', 'w 49 - 0', '53155'], ['4', 'october 8 , 1961', 'los angeles rams', 'w 35 - 0', '59004'], ['5', 'october 15 , 1961', 'minnesota v... |
swimming at the 2000 summer olympics - men 's 200 metre butterfly | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Men%27s_200_metre_butterfly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446425-5.html.csv | count | the united states had two swimmers at the 2000 summer olympics - men 's 200 metre butterfly . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', '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 }'}], 'resul... | eq { count { filter_eq { all_rows ; nationality ; united states } } ; 2 } = true | select the rows whose nationality record fuzzily matches to united states . 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, 'nationality_5': 5, 'united states_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', 'nationality_5': 'nationality', 'united states_6': 'united states', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'united states_6': [0], '2_7': [2]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'tom malchow', 'united states', '1:56.02'], ['2', '3', 'anatoly polyakov', 'russia', '1:56.78'], ['3', '5', 'michael phelps', 'united states', '1:57.00'], ['4', '6', 'franck esposito', 'france', '1:57.04'], ['5', '2', 'denis pankratov', 'russia', '1:57.24'], ['6', '8', 'andrew livingston', 'puerto rico', '1... |
2008 detroit shock season | https://en.wikipedia.org/wiki/2008_Detroit_Shock_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17103729-10.html.csv | ordinal | the detroit shock 's game against new york recorded their highest attendance of the 2008 season . | {'row': '5', 'col': '8', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'location / attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location / attendance ; 1 }'}, 'opponent'], 'result': 'new york', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location / a... | eq { hop { nth_argmax { all_rows ; location / attendance ; 1 } ; opponent } ; new york } = true | select the row whose location / attendance record of all rows is 1st maximum . the opponent record of this row is new york . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location / attendance_5': 5, '1_6': 6, 'opponent_7': 7, 'new york_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'location / attendance_5': 'location / attendance', '1_6': '1', 'opponent_7': 'opponent', 'new york_8': 'new york'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location / attendance_5': [0], '1_6': [0], 'opponent_7': [1], 'new york_8': [2]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['30', 'september 5', 'indiana', '90 - 68', 'pierson ( 20 )', 'pierson ( 6 )', 'mcwilliams - franklin , pierson ( 4 )', 'palace of auburn hills 9287', '18 - 12'], ['31', 'september 6', 'washington', '84 - 69', 'mcwilliams - franklin ( 21 )', 'nolan ( 10 )', 'smith ( 8 )', 'verizon center 9976', '19 - 12'], ['32', 'sep... |
1962 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1962_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277219-5.html.csv | aggregation | the total score of all players in the 1962 us open was 1419 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '1419', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'score'], 'result': '1419', 'ind': 0, 'tostr': 'sum { all_rows ; score }'}, '1419'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; score } ; 1419 } = true', 'tointer': 'the sum of the score record of all rows is 1419 .'} | round_eq { sum { all_rows ; score } ; 1419 } = true | the sum of the score record of all rows is 1419 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'score_4': 4, '1419_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'score_4': 'score', '1419_5': '1419'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'score_4': [0], '1419_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'arnold palmer', 'united states', '71 + 68 = 139', '- 3'], ['t1', 'bob rosburg', 'united states', '70 + 69 = 139', '- 3'], ['3', 'billy maxwell', 'united states', '71 + 70 = 141', '- 1'], ['t4', 'bobby nichols', 'united states', '70 + 72 = 142', 'e'], ['t4', 'jack nicklaus', 'united states', '72 + 70 = 142', 'e... |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-10.html.csv | unique | the only candidate to have died in office under the democratic party was john james flynt . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '6', 'criterion': 'fuzzily_match', 'value': 'died in office', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'died in office'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to died in office .', 'tostr': 'filter_eq { all_rows ; result ; died in office }'}], 'result': True, 'i... | and { only { filter_eq { all_rows ; result ; died in office } } ; eq { hop { filter_eq { all_rows ; result ; died in office } ; candidates } ; john james flynt , jr ( d ) unopposed } } = true | select the rows whose result record fuzzily matches to died in office . there is only one such row in the table . the candidates record of this unqiue row is john james flynt , jr ( d ) unopposed . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'result_7': 7, 'died in office_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'candidates_9': 9, 'john james flynt , jr (d) unopposed_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'result_7': 'result', 'died in office_8': 'died in office', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'candidates_9': 'candidates', 'john james flynt , jr (d) unopposed_10': 'john james flynt , jr ( ... | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], 'died in office_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'candidates_9': [2], 'john james flynt , jr (d) unopposed_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['georgia 1', 'prince hulon preston , jr', 'democratic', '1946', 're - elected', 'prince hulon preston , jr ( d ) 83.7 % others 16.3 %'], ['georgia 2', 'j l pilcher', 'democratic', '1953', 're - elected', 'j l pilcher ( d ) unopposed'], ['georgia 3', 'tic forrester', 'democratic', '1950', 're - elected', 'tic forreste... |
34th united states congress | https://en.wikipedia.org/wiki/34th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2417308-3.html.csv | comparative | john parker hale was installed before william bigler was installed . | {'row_1': '1', 'row_2': '3', 'col': '5', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'john parker hale ( r )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to john parker hale ( r ) .', 'tostr': 'filter_eq { all_rows ; successor ; john parke... | less { hop { filter_eq { all_rows ; successor ; john parker hale ( r ) } ; date of successors formal installation } ; hop { filter_eq { all_rows ; successor ; william bigler ( d ) } ; date of successors formal installation } } = true | select the rows whose successor record fuzzily matches to john parker hale ( r ) . take the date of successors formal installation record of this row . select the rows whose successor record fuzzily matches to william bigler ( d ) . take the date of successors formal installation record of this row . the first record i... | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'successor_7': 7, 'john parker hale (r)_8': 8, 'date of successors formal installation_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'successor_11': 11, 'william bigler (d)_12': 12, 'date of successors formal installat... | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'successor_7': 'successor', 'john parker hale (r)_8': 'john parker hale ( r )', 'date of successors formal installation_9': 'date of successors formal installation', 'str_hop_3': 'str_hop', 'filt... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'successor_7': [0], 'john parker hale (r)_8': [0], 'date of successors formal installation_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'successor_11': [1], 'william bigler (d)_12': [1], 'date of succe... | ['state ( class )', 'vacator', 'reason for change', 'successor', 'date of successors formal installation'] | [['new hampshire ( 2 )', 'vacant', 'legislature failed to elect on time', 'john parker hale ( r )', 'july 30 , 1855'], ['alabama ( 3 )', 'vacant', 'legislature failed to elect on time', 'benjamin fitzpatrick ( d )', 'november 26 , 1855'], ['pennsylvania ( 3 )', 'vacant', 'legislature failed to elect on time', 'william ... |
bharatiya janata party | https://en.wikipedia.org/wiki/Bharatiya_Janata_Party | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-149330-1.html.csv | unique | the 9th lok sabha is the only general election where 85 seats were won by the bharatiya janata party . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '85', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'seats won', '85'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose seats won record is equal to 85 .', 'tostr': 'filter_eq { all_rows ; seats won ; 85 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { a... | and { only { filter_eq { all_rows ; seats won ; 85 } } ; eq { hop { filter_eq { all_rows ; seats won ; 85 } ; general election } ; 9th lok sabha } } = true | select the rows whose seats won record is equal to 85 . there is only one such row in the table . the general election record of this unqiue row is 9th lok sabha . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'seats won_7': 7, '85_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'general election_9': 9, '9th lok sabha_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'seats won_7': 'seats won', '85_8': '85', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'general election_9': 'general election', '9th lok sabha_10': '9th lok sabha'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'seats won_7': [0], '85_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'general election_9': [2], '9th lok sabha_10': [3]} | ['year', 'general election', 'seats won', 'change in seat', '% of votes', 'votes swing'] | [['indian general election , 1980', '7th lok sabha', '12', '12', '8.75 %', '8.75'], ['indian general election , 1984', '8th lok sabha', '2', '10', '7.74 %', '1.01'], ['indian general election , 1989', '9th lok sabha', '85', '83', '11.36', '3.62'], ['indian general election , 1991', '10th lok sabha', '120', '37', '20.11... |
list of benedictine colleges and universities | https://en.wikipedia.org/wiki/List_of_Benedictine_colleges_and_universities | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14014822-1.html.csv | unique | benedictine university is the only benedictine university in illinois to be founded in 1887 . | {'scope': 'subset', 'row': '3', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '1887', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'illinois'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'state', 'illinois'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; state ; illinois }', 'tointer': 'select the rows whose state record fuzzily matches to illinois .'}, 'founded'... | and { only { filter_eq { filter_eq { all_rows ; state ; illinois } ; founded ; 1887 } } ; eq { hop { filter_eq { filter_eq { all_rows ; state ; illinois } ; founded ; 1887 } ; school } ; benedictine university } } = true | select the rows whose state record fuzzily matches to illinois . among these rows , select the rows whose founded record is equal to 1887 . there is only one such row in the table . the school record of this unqiue row is benedictine university . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'state_8': 8, 'illinois_9': 9, 'founded_10': 10, '1887_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'school_12': 12, 'benedictine university_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', 'state_8': 'state', 'illinois_9': 'illinois', 'founded_10': 'founded', '1887_11': '1887', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'school_12': 'school', 'benedictine uni... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'state_8': [0], 'illinois_9': [0], 'founded_10': [1], '1887_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'school_12': [3], 'benedictine university_13': [4]} | ['school', 'city', 'state', 'enrollment', 'founded'] | [['belmont abbey college', 'belmont', 'north carolina', '1320', '1876'], ['benedictine college', 'atchison', 'kansas', '1855', '1858'], ['benedictine university', 'lisle', 'illinois', '6857', '1887'], ['benedictine university at springfield', 'springfield', 'illinois', '981', '1929'], ['college of saint benedict', 'st ... |
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