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2000 ansett australia cup | https://en.wikipedia.org/wiki/2000_Ansett_Australia_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16388398-3.html.csv | majority | most of the games of the 2000 ansett australia cup had an attendance higher than 10,000 . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 10000 .', 'tostr': 'most_greater { all_rows ; crowd ; 10000 } = true'} | most_greater { all_rows ; crowd ; 10000 } = true | for the crowd records of all rows , most of them are greater than 10000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '10000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '10000_4': '10000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '10000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date'] | [['adelaide', '17.5 ( 107 )', 'melbourne', '19.11 ( 125 )', 'football park', '12239', 'sunday , 30 january'], ['geelong', '10.14 ( 74 )', 'st kilda', '11.12 ( 78 )', 'waverley park', '7394', 'sunday , 30 january'], ['st kilda', '9.12 ( 66 )', 'melbourne', '13.14 ( 92 )', 'waverley park', '10533', 'saturday , 5 february'], ['adelaide', '19.10 ( 124 )', 'geelong', '15.12 ( 102 )', 'football park', '11326', 'sunday , 6 february'], ['adelaide', '14.11 ( 95 )', 'st kilda', '15.12 ( 102 )', 'football park', '13086', 'sunday , 13 february'], ['geelong', '17.12 ( 114 )', 'melbourne', '11.16 ( 82 )', 'waverley park', '4952', 'monday , 14 february']] |
john wayne filmography | https://en.wikipedia.org/wiki/John_Wayne_filmography | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12379832-9.html.csv | majority | rn bradbury directed most of the movies that john wayne was in . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rn bradbury', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'director', 'rn bradbury'], 'result': True, 'ind': 0, 'tointer': 'for the director records of all rows , most of them fuzzily match to rn bradbury .', 'tostr': 'most_eq { all_rows ; director ; rn bradbury } = true'} | most_eq { all_rows ; director ; rn bradbury } = true | for the director records of all rows , most of them fuzzily match to rn bradbury . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'director_3': 3, 'rn bradbury_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'director_3': 'director', 'rn bradbury_4': 'rn bradbury'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'director_3': [0], 'rn bradbury_4': [0]} | ['title', 'studio', 'role', 'leading lady', 'director'] | [['the lucky texan', 'mono', 'jerry mason', 'barbara sheldon', 'rn bradbury'], ['west of the divide', 'mono', 'ted hayden', 'virginia browne faire', 'rn bradbury'], ['blue steel', 'mono', 'john carruthers', 'eleanor hunt', 'rn bradbury'], ['the man from utah', 'mono', 'john westen', 'polly ann young', 'rn bradbury'], ['randy rides alone', 'mono', 'randy bowers', 'alberta vaughn', 'harry l fraser'], ['the star packer', 'mono', 'john travers', 'verna hillie', 'rn bradbury'], ['the trail beyond', 'mono', 'rod drew', 'verna hillie', 'rn bradbury'], ['the lawless frontier', 'mono', 'john tobin', 'sheila terry', 'rn bradbury'], ["' neath the arizona skies", 'mono', 'chris morrell', 'sheila terry', 'harry fraser']] |
north island main trunk | https://en.wikipedia.org/wiki/North_Island_Main_Trunk | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1799173-1.html.csv | count | six of the north island main truck lines are closed . | {'scope': 'all', 'criterion': 'not_equal', 'value': 'open', 'result': '6', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'date closed', 'open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date closed record does not match to open .', 'tostr': 'filter_not_eq { all_rows ; date closed ; open }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_not_eq { all_rows ; date closed ; open } }', 'tointer': 'select the rows whose date closed record does not match to open . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_not_eq { all_rows ; date closed ; open } } ; 6 } = true', 'tointer': 'select the rows whose date closed record does not match to open . the number of such rows is 6 .'} | eq { count { filter_not_eq { all_rows ; date closed ; open } } ; 6 } = true | select the rows whose date closed record does not match to open . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'date closed_5': 5, 'open_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'date closed_5': 'date closed', 'open_6': 'open', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'date closed_5': [0], 'open_6': [0], '6_7': [2]} | ['line name', 'date closed', 'nimt junction', 'terminus', 'length'] | [['auckland - newmarket line', 'open', 'quay park junction', 'newmarket junction', '2.5 km'], ['north auckland line', 'open', 'westfield junction', 'otiria junction', '280 km'], ['manukau branch', 'open', 'wiri junction', 'manukau', '2.5 km'], ['mission bush branch', 'open', 'paerata junction', 'mission bush', '17 km'], ['kimihia branch', 'open', 'huntly north', 'kimihia mine', '2.75 km'], ['rotowaro branch', 'open', 'huntly', 'rotowaro', '8.5 km'], ['waipa railway and coal co line', '19 - 5 - 1958', 'ngaruawahia', 'wilton collieries', '10.5 km'], ['east coast main trunk railway', 'open', 'frankton junction', 'kawerau', '180 km'], ['stratford - okahukura line', 'mothballed 2009', 'okahukura junction', 'stratford', '144 km'], ['raetihi branch', '1 - 1 - 1968', 'ohakune junction', 'raetihi', '13 km'], ['marton - new plymouth line', 'open', 'marton junction', 'breakwater ( new plymouth )', '212 km'], ['taonui branch', '14 - 8 - 1895', 'taonui', 'colyton', '3.5 km'], ['palmerston north - gisborne line', 'open', 'roslyn junction', 'gisborne', '391 km'], ['foxton branch', '18 - 7 - 1959', 'longburn junction', 'foxton', '31 km'], ['wairarapa line', 'open', 'distant junction ( wellington )', 'woodville', '170 km'], ['johnsonville branch', 'open', 'wellington junction', 'johnsonville', '10 km'], ['te aro branch', '23 - 4 - 1917', 'wellington ( lambton )', 'te aro', '1.77 km']] |
raul boesel | https://en.wikipedia.org/wiki/Raul_Boesel | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226543-6.html.csv | count | raul boesel was driving for team simon for five of the years listed in the table . | {'scope': 'all', 'criterion': 'equal', 'value': 'simon', 'result': '5', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'simon'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to simon .', 'tostr': 'filter_eq { all_rows ; team ; simon }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; simon } }', 'tointer': 'select the rows whose team record fuzzily matches to simon . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; simon } } ; 5 } = true', 'tointer': 'select the rows whose team record fuzzily matches to simon . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; team ; simon } } ; 5 } = true | select the rows whose team record fuzzily matches to simon . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'team_5': 5, 'simon_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'team_5': 'team', 'simon_6': 'simon', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'simon_6': [0], '5_7': [2]} | ['year', 'chassis', 'engine', 'start', 'finish', 'team'] | [['1985', 'march 85c', 'ford cosworth dfx', '23', '18', 'simon'], ['1986', 'lola t86 / 00', 'ford cosworth dfx', '22', '13', 'simon'], ['1988', 'lola t88 / 00', 'ford cosworth dfx', '20', '7', 'shierson'], ['1989', 'lola t89 / 00', 'judd', '9', '3', 'shierson'], ['1990', 'lola t89 / 00', 'judd', '17', '28', 'truesports'], ['1992', 'lola t92 / 00', 'chevrolet 265a', '27', '7', 'simon'], ['1993', 'lola t93 / 00', 'ford xb', '3', '4', 'simon'], ['1994', 'lola t94 / 00', 'ford xb', '2', '21', 'simon'], ['1995', 'lola t95 / 00', 'mercedes - benz ic108b', '22', '20', 'rahal / hogan'], ['1998', 'g - force', 'oldsmobile', '30', '19', 'mccormack'], ['1999', 'riley & scott', 'oldsmobile', '33', '12', 'brant'], ['2000', 'g - force', 'oldsmobile', '24', '16', 'treadway'], ['2001', 'g - force', 'oldsmobile', 'raced by f giaffone', 'raced by f giaffone', 'treadway'], ['2002', 'dallara', 'chevrolet', '3', '21', 'menard']] |
1984 - 85 philadelphia flyers season | https://en.wikipedia.org/wiki/1984%E2%80%9385_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14208855-10.html.csv | majority | in the majority of games against the new york islanders in the 1984 - 85 philadelphia flyers season one of the teams scored at least 5 goals . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'new york islanders', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'opponent', 'new york islanders'], 'result': True, 'ind': 0, 'tointer': 'for the opponent records of all rows , all of them fuzzily match to new york islanders .', 'tostr': 'all_eq { all_rows ; opponent ; new york islanders } = true'} | all_eq { all_rows ; opponent ; new york islanders } = true | for the opponent records of all rows , all of them fuzzily match to new york islanders . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'opponent_3': 3, 'new york islanders_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'opponent_3': 'opponent', 'new york islanders_4': 'new york islanders'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'opponent_3': [0], 'new york islanders_4': [0]} | ['game', 'date', 'opponent', 'score', 'series'] | [['1', 'april 18', 'new york islanders', '3 - 0', 'flyers lead 1 - 0'], ['2', 'april 21', 'new york islanders', '5 - 2', 'flyers lead 2 - 0'], ['3', 'april 23', 'new york islanders', '5 - 3', 'flyers lead 3 - 0'], ['4', 'april 25', 'new york islanders', '2 - 6', 'flyers lead 3 - 1'], ['5', 'april 28', 'new york islanders', '1 - 0', 'flyers win 3 - 0']] |
1988 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1988_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17231125-4.html.csv | majority | most of the players of the 1988 u.s. open ( golf ) tournament were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'bob gilder', 'united states', '68', '- 3'], ['t1', 'sandy lyle', 'scotland', '68', '- 3'], ['t1', 'mike nicolette', 'united states', '68', '- 3'], ['t4', 'paul azinger', 'united states', '69', '- 2'], ['t4', 'seve ballesteros', 'spain', '69', '- 2'], ['t4', 'dick mast', 'united states', '69', '- 2'], ['t4', 'larry mize', 'united states', '69', '- 2'], ['t4', 'scott simpson', 'united states', '69', '- 2'], ['t9', 'craig stadler', 'united states', '70', '- 1'], ['t9', 'curtis strange', 'united states', '70', '- 1'], ['t9', 'lanny wadkins', 'united states', '70', '- 1']] |
1980 open championship | https://en.wikipedia.org/wiki/1980_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18171018-5.html.csv | aggregation | all the players of the 1980 open championship had an average score of around 139 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '139', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '139', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '139'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 139 } = true', 'tointer': 'the average of the score record of all rows is 139 .'} | round_eq { avg { all_rows ; score } ; 139 } = true | the average of the score record of all rows is 139 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '139_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '139_5': '139'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '139_5': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'lee trevino', 'united states', '68 + 67 = 135', '- 7'], ['t2', 'ken brown', 'scotland', '70 + 68 = 138', '- 4'], ['t2', 'jerry pate', 'united states', '71 + 67 = 138', '- 4'], ['t2', 'tom watson', 'united states', '68 + 70 = 138', '- 4'], ['t5', 'seve ballesteros', 'spain', '72 + 68 = 140', '- 2'], ['t5', 'andy bean', 'united states', '71 + 69 = 140', '- 2'], ['t5', 'ben crenshaw', 'united states', '70 + 70 = 140', '- 2'], ['t5', 'gil morgan', 'united states', '70 + 70 = 140', '- 2'], ['t5', 'jack newton', 'australia', '69 + 71 = 140', '- 2'], ['t5', 'jack nicklaus', 'united states', '73 + 67 = 140', '- 2']] |
melanie south | https://en.wikipedia.org/wiki/Melanie_South | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12641767-2.html.csv | comparative | melanie south played a match in bath before she played in hull . | {'row_1': '3', 'row_2': '5', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'bath'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to bath .', 'tostr': 'filter_eq { all_rows ; tournament ; bath }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; bath } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to bath . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'hull'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to hull .', 'tostr': 'filter_eq { all_rows ; tournament ; hull }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; hull } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to hull . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; tournament ; bath } ; date } ; hop { filter_eq { all_rows ; tournament ; hull } ; date } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to bath . take the date record of this row . select the rows whose tournament record fuzzily matches to hull . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; tournament ; bath } ; date } ; hop { filter_eq { all_rows ; tournament ; hull } ; date } } = true | select the rows whose tournament record fuzzily matches to bath . take the date record of this row . select the rows whose tournament record fuzzily matches to hull . 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, 'tournament_7': 7, 'bath_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'hull_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', 'tournament_7': 'tournament', 'bath_8': 'bath', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'hull_12': 'hull', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'bath_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'hull_12': [1], 'date_13': [3]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', '3 march 2004', 'mumbai', 'hard', 'chen yanchong', '6 - 4 6 - 4'], ['runner - up', '1 may 2004', 'bournemouth', 'clay', 'elke clijsters', '6 - 3 1 - 6 2 - 6'], ['winner', '10 april 2005', 'bath', 'hard', 'anne keothavong', '6 - 4 4 - 6 6 - 4'], ['runner - up', '8 may 2005', 'edinburgh', 'clay', 'ekaterina kozhokina', '4 - 6 3 - 6'], ['winner', '29 january 2006', 'hull', 'hard', 'irena pavlovic', '6 - 4 6 - 1'], ['winner', '30 july 2006', 'chengdu', 'hard', 'lu jingjing', '7 - 5 7 - 6 ( 7 - 5 )'], ['winner', '23 march 2008', 'sorrento', 'hard', 'christina wheeler', '7 - 5 6 - 7 ( 6 - 8 ) 6 - 4'], ['runner - up', '12 october 2008', 'traralgon', 'hard', 'jarmila gajdošová', '3 - 6 6 - 3 1 - 6'], ['runner - up', '19 october 2008', 'mount gambier', 'hard', 'natalie grandin', '6 - 7 ( 2 - 7 ) 4 - 6'], ['winner', '26 october 2008', 'port pirie', 'hard', 'yurika sema', '6 - 3 6 - 4'], ['runner - up', '15 november 2008', 'pune', 'hard', 'lu jingjing', '3 - 6 2 - 6'], ['runner - up', '25 october 2009', 'glasgow', 'hard', 'johanna larsson', '1 - 6 6 - 1 3 - 6']] |
1934 masters tournament | https://en.wikipedia.org/wiki/1934_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12572213-3.html.csv | count | at the 1934 masters tournament , when the country is united states , there were two players who had a score of 143 . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '143', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'score', '143'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 143 .', 'tostr': 'filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 143 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 143 } }', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 143 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 143 } } ; 2 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 143 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; country ; united states } ; score ; 143 } } ; 2 } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record fuzzily matches to 143 . 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, 'country_6': 6, 'united states_7': 7, 'score_8': 8, '143_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', 'country_6': 'country', 'united states_7': 'united states', 'score_8': 'score', '143_9': '143', '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], 'country_6': [0], 'united states_7': [0], 'score_8': [1], '143_9': [1], '2_10': [3]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'horton smith', 'united states', '70 + 72 = 142', '- 2'], ['t3', 'ed dudley', 'united states', '74 + 69 = 143', '- 1'], ['t3', 'billy burke', 'united states', '72 + 71 = 143', '- 1'], ['t4', 'macdonald smith', 'scotland', '74 + 70 = 144', 'e'], ['t4', 'jimmy hines', 'united states', '70 + 74 = 144', 'e'], ['t6', 'al espinosa', 'united states', '75 + 70 = 145', '+ 1'], ['t6', 'leo diegel', 'united states', '73 + 72 = 145', '+ 1'], ['t6', 'craig wood', 'united states', '71 + 74 = 145', '+ 1'], ['t9', 'denny shute', 'united states', '73 + 73 = 146', '+ 2'], ['t9', 'johnny golden', 'united states', '71 + 75 = 146', '+ 2']] |
fa cup third - fourth place matches | https://en.wikipedia.org/wiki/FA_Cup_Third-fourth_place_matches | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18025901-1.html.csv | aggregation | in the fa cup third - fourth place matches , when the match was in august , the total attendance was 46879 . | {'scope': 'subset', 'col': '7', 'type': 'sum', 'result': '46879', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'august'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'august'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; august }', 'tointer': 'select the rows whose date record fuzzily matches to august .'}, 'attendance'], 'result': '46879', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; date ; august } ; attendance }'}, '46879'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; date ; august } ; attendance } ; 46879 } = true', 'tointer': 'select the rows whose date record fuzzily matches to august . the sum of the attendance record of these rows is 46879 .'} | round_eq { sum { filter_eq { all_rows ; date ; august } ; attendance } ; 46879 } = true | select the rows whose date record fuzzily matches to august . the sum of the attendance record of these rows is 46879 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'august_6': 6, 'attendance_7': 7, '46879_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'august_6': 'august', 'attendance_7': 'attendance', '46879_8': '46879'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'august_6': [0], 'attendance_7': [1], '46879_8': [2]} | ['season', 'date', 'winner', 'loser', 'score', 'venue', 'attendance'] | [['1969 - 70 fa cup', '10 april 1970', 'manchester united', 'watford', '2 - 0', 'highbury', '15105'], ['1970 - 71 fa cup', '7 may 1971', 'stoke city', 'everton', '3 - 2', 'selhurst park', '5031'], ['1971 - 72 fa cup', '5 august 1972', 'birmingham city', 'stoke city', '0 - 0 ( 4 - 3 pens )', "st andrew 's", '25841'], ['1972 - 73 fa cup', '18 august 1973', 'wolverhampton wanderers', 'arsenal', '3 - 1', 'highbury', '21038'], ['1973 - 74 fa cup', '9 may 1974', 'burnley', 'leicester city', '1 - 0', 'filbert street', '6458']] |
galatasaray s.k. ( superleague formula team ) | https://en.wikipedia.org/wiki/Galatasaray_S.K._%28Superleague_Formula_team%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23293785-3.html.csv | aggregation | for galatasaray s.k. , the average number of points for race 1 is 17.8 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '17.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'race 1 ( pts )'], 'result': '17.8', 'ind': 0, 'tostr': 'avg { all_rows ; race 1 ( pts ) }'}, '17.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; race 1 ( pts ) } ; 17.8 } = true', 'tointer': 'the average of the race 1 ( pts ) record of all rows is 17.8 .'} | round_eq { avg { all_rows ; race 1 ( pts ) } ; 17.8 } = true | the average of the race 1 ( pts ) record of all rows is 17.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'race 1 (pts)_4': 4, '17.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'race 1 (pts)_4': 'race 1 ( pts )', '17.8_5': '17.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'race 1 (pts)_4': [0], '17.8_5': [1]} | ['sf round', 'country', 'location', 'date', 'driver', 'race 1 ( pts )', 'race 2 ( pts )', 'race 3', 'race total ( pts )'] | [['1', 'france', 'circuit de nevers magny - cours', '28 june 2009', 'duncan tappy', '32', '16', 'dnq', '48'], ['2', 'belgium', 'zolder', '19 july 2009', 'duncan tappy', '20', '7', 'n / a', '75'], ['3', 'england', 'donington park', '2 august 2009', 'scott mansell', '12', '14', 'dnq', '101'], ['4', 'portugal', 'estoril circuit', '6 september 2009', 'ho pin tung', '17', '7', 'dnq', '133'], ['5', 'italy', 'autodromo nazionale monza', '4 october 2009', 'ho pin tung', '8', '7', 'n / a', '182']] |
list of carnivàle episodes | https://en.wikipedia.org/wiki/List_of_Carniv%C3%A0le_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12722302-2.html.csv | superlative | out of all episodes from the list of carnivàle episodes , the episode milfay had the greatest the number of us viewers . | {'scope': 'all', 'col_superlative': '7', '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', 'us viewers ( million )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( million ) }'}, 'title'], 'result': 'milfay', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( million ) } ; title }'}, 'milfay'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; milfay } = true', 'tointer': 'select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is milfay .'} | eq { hop { argmax { all_rows ; us viewers ( million ) } ; title } ; milfay } = true | select the row whose us viewers ( million ) record of all rows is maximum . the title record of this row is milfay . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (million)_5': 5, 'title_6': 6, 'milfay_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (million)_5': 'us viewers ( million )', 'title_6': 'title', 'milfay_7': 'milfay'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (million)_5': [0], 'title_6': [1], 'milfay_7': [2]} | ['no', 'title', 'directed by', 'written by', 'bens location', 'original air date', 'us viewers ( million )'] | [['1', 'milfay', 'rodrigo garcía', 'daniel knauf', 'milfay , oklahoma', 'september 14 , 2003', '5.3'], ['2', 'after the ball is over', 'jeremy podeswa', 'daniel knauf & ronald d moore', 'n / a', 'september 21 , 2003', '3.49'], ['4', 'black blizzard', 'peter medak', 'william schmidt', 'n / a', 'october 5 , 2003', '2.87'], ['5', 'babylon', 'tim hunter', 'dawn prestwich & nicole yorkin', 'babylon , texas', 'october 12 , 2003', '3.31'], ['6', 'pick a number', 'rodrigo garcía', 'ronald d moore', 'babylon , texas', 'october 19 , 2003', '3.40'], ['7', 'the river', 'alison maclean', 'toni graphia', 'texas', 'october 26 , 2003', '3.90'], ['8', 'lonnigan , texas', 'scott winant', 'daniel knauf', 'lonnigan , texas', 'november 2 , 2003', '2.96'], ['9', 'insomnia', 'jack bender', 'william schmidt', 'n / a', 'november 9 , 2003', '3.41'], ['10', 'hot and bothered', 'jeremy podeswa', 'dawn prestwich & nicole yorkin', 'loving , new mexico', 'november 16 , 2003', '3.19'], ['11', 'day of the dead', 'john patterson', 'toni graphia', 'loving , new mexico', 'november 23 , 2003', '2.56']] |
orlando magic all - time roster | https://en.wikipedia.org/wiki/Orlando_Magic_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15621965-11.html.csv | superlative | on the orlando magic all-time roster , of the players who are guards at least part of the time , the one who started playing for the magic the earliest was todd lichti . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1,3', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'guard'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'guard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; guard }', 'tointer': 'select the rows whose position record fuzzily matches to guard .'}, 'years in orlando'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; position ; guard } ; years in orlando }'}, 'player'], 'result': 'todd lichti', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; position ; guard } ; years in orlando } ; player }'}, 'todd lichti'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; position ; guard } ; years in orlando } ; player } ; todd lichti } = true', 'tointer': 'select the rows whose position record fuzzily matches to guard . select the row whose years in orlando record of these rows is minimum . the player record of this row is todd lichti .'} | eq { hop { argmin { filter_eq { all_rows ; position ; guard } ; years in orlando } ; player } ; todd lichti } = true | select the rows whose position record fuzzily matches to guard . select the row whose years in orlando record of these rows is minimum . the player record of this row is todd lichti . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'position_6': 6, 'guard_7': 7, 'years in orlando_8': 8, 'player_9': 9, 'todd lichti_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'position_6': 'position', 'guard_7': 'guard', 'years in orlando_8': 'years in orlando', 'player_9': 'player', 'todd lichti_10': 'todd lichti'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'position_6': [0], 'guard_7': [0], 'years in orlando_8': [1], 'player_9': [2], 'todd lichti_10': [3]} | ['player', 'nationality', 'position', 'years in orlando', 'school / club team'] | [['jason lawson', 'united states', 'center', '1997 - 1998', 'villanova'], ['courtney lee', 'united states', 'guard - forward', '2008 - 2009', 'western kentucky'], ['rashard lewis', 'united states', 'forward', '2007 - 2010', 'alief elsik hs'], ['todd lichti', 'united states', 'guard - forward', '1993 - 1994', 'stanford'], ['deandre liggins', 'united states', 'guard', '2011 - 2012', 'kentucky'], ['tyronn lue', 'united states', 'guard', '2003 - 2004', 'nebraska'], ['tyronn lue', 'united states', 'guard', '2009', 'nebraska']] |
anton putsila | https://en.wikipedia.org/wiki/Anton_Putsila | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16375026-1.html.csv | count | among the friendly competitions that anton putsilla played at , 2 of them were located in stadion villach lind , villach , austria . | {'scope': 'subset', 'criterion': 'equal', 'value': 'stadion villach lind , villach , austria', 'result': '2', 'col': '2', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'friendly'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; competition ; friendly }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly .'}, 'venue', 'stadion villach lind , villach , austria'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose competition record fuzzily matches to friendly . among these rows , select the rows whose venue record fuzzily matches to stadion villach lind , villach , austria .', 'tostr': 'filter_eq { filter_eq { all_rows ; competition ; friendly } ; venue ; stadion villach lind , villach , austria }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; competition ; friendly } ; venue ; stadion villach lind , villach , austria } }', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . among these rows , select the rows whose venue record fuzzily matches to stadion villach lind , villach , austria . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; competition ; friendly } ; venue ; stadion villach lind , villach , austria } } ; 2 } = true', 'tointer': 'select the rows whose competition record fuzzily matches to friendly . among these rows , select the rows whose venue record fuzzily matches to stadion villach lind , villach , austria . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; competition ; friendly } ; venue ; stadion villach lind , villach , austria } } ; 2 } = true | select the rows whose competition record fuzzily matches to friendly . among these rows , select the rows whose venue record fuzzily matches to stadion villach lind , villach , austria . 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, 'competition_6': 6, 'friendly_7': 7, 'venue_8': 8, 'stadion villach lind , villach , austria_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', 'competition_6': 'competition', 'friendly_7': 'friendly', 'venue_8': 'venue', 'stadion villach lind , villach , austria_9': 'stadion villach lind , villach , austria', '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], 'competition_6': [0], 'friendly_7': [0], 'venue_8': [1], 'stadion villach lind , villach , austria_9': [1], '2_10': [3]} | ['date', 'venue', 'score', 'result', 'competition'] | [['3 march 2010', 'antalya atatürk stadium , antalya , turkey', '1 - 0', '3 - 1', 'friendly'], ['27 may 2010', 'stadion villach lind , villach , austria', '1 - 1', '2 - 2', 'friendly'], ['27 may 2010', 'stadion villach lind , villach , austria', '2 - 1', '2 - 2', 'friendly'], ['7 june 2011', 'dynama stadium , minsk , belarus', '2 - 0', '2 - 0', 'uefa euro 2012 qualification'], ['11 september 2012', 'stade de france , paris , france', '1 - 2', '1 - 3', '2014 fifa world cup qualification'], ['3 june 2013', 'a le coq arena , tallinn , estonia', '1 - 0', '2 - 0', 'friendly']] |
atlantic city , new jersey | https://en.wikipedia.org/wiki/Atlantic_City%2C_New_Jersey | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-106211-1.html.csv | aggregation | the casinos in atlantic city , new jersey have a combined total of 18447 hotel rooms . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '18447', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'hotel rooms'], 'result': '18447', 'ind': 0, 'tostr': 'sum { all_rows ; hotel rooms }'}, '18447'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; hotel rooms } ; 18447 } = true', 'tointer': 'the sum of the hotel rooms record of all rows is 18447 .'} | round_eq { sum { all_rows ; hotel rooms } ; 18447 } = true | the sum of the hotel rooms record of all rows is 18447 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'hotel rooms_4': 4, '18447_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'hotel rooms_4': 'hotel rooms', '18447_5': '18447'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'hotel rooms_4': [0], '18447_5': [1]} | ['casino', 'opening date', 'theme', 'hotel rooms', 'section of atlantic city'] | [['atlantic club', 'december 12 , 1980', 'beach resort', '809', 'downbeach'], ["bally 's ᴮ", 'december 29 , 1979', 'modern', '1749', 'midtown'], ['borgata', 'july 2 , 2003', 'tuscany', '2767', 'marina'], ['caesars', 'june 26 , 1979', 'roman empire', '1141', 'midtown'], ['golden nugget', 'june 19 , 1985', 'gold rush era', '727', 'marina'], ["harrah 's", 'november 27 , 1980', 'marina waterfront', '2590', 'marina'], ['resorts', 'may 28 , 1978', 'roaring twenties', '942', 'uptown'], ['revel', 'april 2 , 2012', 'oceanfront', '1399', 'uptown'], ['showboat', 'april 2 , 1987', 'mardi gras', '1329', 'uptown'], ['tropicana', 'november 26 , 1981', 'old havana', '2078', 'downbeach'], ['trump plaza ᴬ', 'may 26 , 1984', 'luxury resort', '906', 'midtown'], ['taj mahal', 'april 2 , 1990', 'taj mahal', '2010', 'uptown']] |
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/1-17311759-6.html.csv | majority | all games of the 2008 - 09 atlanta hawks ' season were scheduled for the month of january . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'january', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'january'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to january .', 'tostr': 'all_eq { all_rows ; date ; january } = true'} | all_eq { all_rows ; date ; january } = true | for the date records of all rows , all of them fuzzily match to january . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'january_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'january_4': 'january'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'january_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['32', 'january 2', 'new jersey', 'l 91 - 93 ( ot )', 'mike bibby ( 22 )', 'joe johnson ( 9 )', 'joe johnson ( 9 )', 'izod center 16851', '21 - 11'], ['33', 'january 3', 'houston', 'w 103 - 100 ( ot )', 'josh smith ( 29 )', 'al horford ( 6 )', 'joe johnson ( 14 )', 'philips arena 16740', '22 - 11'], ['34', 'january 7', 'orlando', 'l 102 - 106 ( ot )', 'josh smith ( 21 )', 'al horford ( 13 )', 'mike bibby , joe johnson ( 9 )', 'philips arena 13748', '22 - 12'], ['35', 'january 9', 'orlando', 'l 87 - 121 ( ot )', 'acie law ( 16 )', 'solomon jones ( 8 )', 'joe johnson ( 4 )', 'amway arena 17461', '22 - 13'], ['36', 'january 11', 'philadelphia', 'l 94 - 109 ( ot )', 'joe johnson ( 25 )', 'zaza pachulia ( 6 )', 'joe johnson ( 9 )', 'philips arena 15079', '22 - 14'], ['37', 'january 13', 'phoenix', 'l 102 - 107 ( ot )', 'josh smith ( 24 )', 'marvin williams ( 12 )', 'joe johnson , mike bibby ( 3 )', 'us airways center 18422', '22 - 15'], ['38', 'january 14', 'la clippers', 'w 97 - 80 ( ot )', 'josh smith ( 26 )', 'josh smith ( 8 )', 'joe johnson ( 7 )', 'staples center 15901', '23 - 15'], ['39', 'january 16', 'golden state', 'l 114 - 119 ( ot )', 'joe johnson ( 25 )', 'zaza pachulia ( 8 )', 'mike bibby ( 7 )', 'oracle arena 18832', '23 - 16'], ['40', 'january 19', 'toronto', 'w 87 - 84 ( ot )', 'joe johnson ( 28 )', 'josh smith ( 14 )', 'mike bibby ( 5 )', 'philips arena 17199', '24 - 16'], ['41', 'january 20', 'chicago', 'w 105 - 102 ( ot )', 'mike bibby ( 31 )', 'josh smith ( 14 )', 'joe johnson ( 8 )', 'united center 20389', '25 - 16'], ['42', 'january 23', 'milwaukee', 'w 117 - 87 ( ot )', 'ronald murray ( 25 )', 'marvin williams ( 9 )', 'mike bibby ( 15 )', 'philips arena 18556', '26 - 16'], ['43', 'january 25', 'phoenix', 'l 99 - 104 ( ot )', 'josh smith ( 19 )', 'josh smith ( 12 )', 'joe johnson ( 13 )', 'philips arena 19153', '26 - 17'], ['44', 'january 26', 'miami', 'l 79 - 95 ( ot )', 'joe johnson ( 19 )', 'josh smith ( 10 )', 'joe johnson ( 4 )', 'american airlines arena 18103', '26 - 18'], ['45', 'january 28', 'new york', 'l 104 - 112 ( ot )', 'marvin williams ( 28 )', 'josh smith ( 12 )', 'joe johnson , mike bibby ( 7 )', 'madison square garden 18180', '26 - 19'], ['46', 'january 30', 'new jersey', 'w 105 - 88 ( ot )', 'joe johnson ( 29 )', 'marvin williams ( 11 )', 'josh smith ( 6 )', 'philips arena 17561', '27 - 19']] |
1966 major league baseball draft | https://en.wikipedia.org/wiki/1966_Major_League_Baseball_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15667202-1.html.csv | comparative | bob jones was drafted by the minnesota twins and larry hutton was drafted by the los angeles dodgers in the 1966 major league baseball draft . | {'row_1': '20', 'row_2': '19', 'col': '3', 'col_other': '2', 'relation': 'not_equal', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'not_str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'bob jones'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to bob jones .', 'tostr': 'filter_eq { all_rows ; player ; bob jones }'}, 'team'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; bob jones } ; team }', 'tointer': 'select the rows whose player record fuzzily matches to bob jones . take the team record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'larry hutton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to larry hutton .', 'tostr': 'filter_eq { all_rows ; player ; larry hutton }'}, 'team'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; larry hutton } ; team }', 'tointer': 'select the rows whose player record fuzzily matches to larry hutton . take the team record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'not_eq { hop { filter_eq { all_rows ; player ; bob jones } ; team } ; hop { filter_eq { all_rows ; player ; larry hutton } ; team } }', 'tointer': 'select the rows whose player record fuzzily matches to bob jones . take the team record of this row . select the rows whose player record fuzzily matches to larry hutton . take the team record of this row . the first record does not match to the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'bob jones'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to bob jones .', 'tostr': 'filter_eq { all_rows ; player ; bob jones }'}, 'team'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; bob jones } ; team }', 'tointer': 'select the rows whose player record fuzzily matches to bob jones . take the team record of this row .'}, 'minnesota twins'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; bob jones } ; team } ; minnesota twins }', 'tointer': 'the team record of the first row is minnesota twins .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'larry hutton'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to larry hutton .', 'tostr': 'filter_eq { all_rows ; player ; larry hutton }'}, 'team'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; larry hutton } ; team }', 'tointer': 'select the rows whose player record fuzzily matches to larry hutton . take the team record of this row .'}, 'los angeles dodgers'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; larry hutton } ; team } ; los angeles dodgers }', 'tointer': 'the team record of the second row is los angeles dodgers .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; player ; bob jones } ; team } ; minnesota twins } ; eq { hop { filter_eq { all_rows ; player ; larry hutton } ; team } ; los angeles dodgers } }', 'tointer': 'the team record of the first row is minnesota twins . the team record of the second row is los angeles dodgers .'}], 'result': True, 'ind': 8, 'tostr': 'and { not_eq { hop { filter_eq { all_rows ; player ; bob jones } ; team } ; hop { filter_eq { all_rows ; player ; larry hutton } ; team } } ; and { eq { hop { filter_eq { all_rows ; player ; bob jones } ; team } ; minnesota twins } ; eq { hop { filter_eq { all_rows ; player ; larry hutton } ; team } ; los angeles dodgers } } } = true', 'tointer': 'select the rows whose player record fuzzily matches to bob jones . take the team record of this row . select the rows whose player record fuzzily matches to larry hutton . take the team record of this row . the first record does not match to the second record . the team record of the first row is minnesota twins . the team record of the second row is los angeles dodgers .'} | and { not_eq { hop { filter_eq { all_rows ; player ; bob jones } ; team } ; hop { filter_eq { all_rows ; player ; larry hutton } ; team } } ; and { eq { hop { filter_eq { all_rows ; player ; bob jones } ; team } ; minnesota twins } ; eq { hop { filter_eq { all_rows ; player ; larry hutton } ; team } ; los angeles dodgers } } } = true | select the rows whose player record fuzzily matches to bob jones . take the team record of this row . select the rows whose player record fuzzily matches to larry hutton . take the team record of this row . the first record does not match to the second record . the team record of the first row is minnesota twins . the team record of the second row is los angeles dodgers . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'not_str_eq_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'player_11': 11, 'bob jones_12': 12, 'team_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'player_15': 15, 'larry hutton_16': 16, 'team_17': 17, 'and_7': 7, 'str_eq_5': 5, 'minnesota twins_18': 18, 'str_eq_6': 6, 'los angeles dodgers_19': 19} | {'and_8': 'and', 'result_9': 'true', 'not_str_eq_4': 'not_str_eq', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'bob jones_12': 'bob jones', 'team_13': 'team', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'player_15': 'player', 'larry hutton_16': 'larry hutton', 'team_17': 'team', 'and_7': 'and', 'str_eq_5': 'str_eq', 'minnesota twins_18': 'minnesota twins', 'str_eq_6': 'str_eq', 'los angeles dodgers_19': 'los angeles dodgers'} | {'and_8': [9], 'result_9': [], 'not_str_eq_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'player_11': [0], 'bob jones_12': [0], 'team_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'player_15': [1], 'larry hutton_16': [1], 'team_17': [3], 'and_7': [8], 'str_eq_5': [7], 'minnesota twins_18': [5], 'str_eq_6': [7], 'los angeles dodgers_19': [6]} | ['pick', 'player', 'team', 'position', 'hometown / school'] | [['1', 'steve chilcott', 'new york mets', 'c', 'lancaster , ca'], ['2', 'reggie jackson', 'kansas city athletics', 'of', 'arizona state'], ['3', 'wayne twitchell', 'houston astros', 'rhp', 'portland , or'], ['4', 'ken brett', 'boston red sox', 'lhp', 'el segundo , ca'], ['5', 'dean burk', 'chicago cubs', 'rhp', 'highland , il'], ['6', 'tom grieve', 'washington senators', 'of', 'pittsfield , ma'], ['7', 'leron lee', 'st louis cardinals', 'of', 'sacramento , ca'], ['8', 'jim deneff', 'california angels', 'ss', 'indiana university'], ['9', 'mike biko', 'philadelphia phillies', 'rhp', 'dallas , tx'], ['10', 'jim lyttle', 'new york yankees', 'of', 'florida state'], ['11', 'al santorini', 'milwaukee braves', 'rhp', 'union , nj'], ['12', 'john curtis', 'cleveland indians', 'lhp', 'smithtown , ny'], ['13', 'gary nolan', 'cincinnati reds', 'rhp', 'oroville , ca'], ['14', 'rick konik', 'detroit tigers', '1b', 'detroit , mi'], ['15', 'richie hebner', 'pittsburgh pirates', 'ss', 'norwood , ma'], ['16', 'ted parks', 'baltimore orioles', 'ss', 'university of california'], ['17', 'bob reynolds', 'san francisco giants', 'rhp', 'seattle , wa'], ['18', 'carlos may', 'chicago white sox', 'of', 'birmingham , al'], ['19', 'larry hutton', 'los angeles dodgers', 'rhp', 'greenfield , in'], ['20', 'bob jones', 'minnesota twins', '3b', 'dawson , ga']] |
dessine - moi un mouton | https://en.wikipedia.org/wiki/Dessine-moi_un_mouton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14857820-1.html.csv | count | two of the versions of dessine - moi un mouton were remixed by laurent boutonnat . | {'scope': 'all', 'criterion': 'equal', 'value': 'laurent boutonnat', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'remixed by', 'laurent boutonnat'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose remixed by record fuzzily matches to laurent boutonnat .', 'tostr': 'filter_eq { all_rows ; remixed by ; laurent boutonnat }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; remixed by ; laurent boutonnat } }', 'tointer': 'select the rows whose remixed by record fuzzily matches to laurent boutonnat . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; remixed by ; laurent boutonnat } } ; 2 } = true', 'tointer': 'select the rows whose remixed by record fuzzily matches to laurent boutonnat . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; remixed by ; laurent boutonnat } } ; 2 } = true | select the rows whose remixed by record fuzzily matches to laurent boutonnat . 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, 'remixed by_5': 5, 'laurent boutonnat_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', 'remixed by_5': 'remixed by', 'laurent boutonnat_6': 'laurent boutonnat', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'remixed by_5': [0], 'laurent boutonnat_6': [0], '2_7': [2]} | ['version', 'length', 'album', 'remixed by', 'year'] | [['album version', '4:34', 'innamoramento', '-', '1999'], ['live version ( recorded in 2000 )', '4:50 ( cd ) 6:40 ( dvd / vhs ) 4:16 ( cassette )', 'mylenium tour', '-', '2000'], ['single live version', '4:34', '-', 'laurent boutonnat', '2000'], ['live radio edit', '4:05', '-', 'laurent boutonnat', '2000'], ['world is mine remix', '4:53', '-', 'quentin and visa', '2000'], ['snakebite beat mix', '4:42', '-', 'osman and visa', '2000'], ['draw me a sheep remix', '3:53', '-', 'hot sly and visa', '2000'], ['music video', '4:56', '-', '-', '2000']] |
2009 - 10 cleveland cavaliers season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22654073-7.html.csv | unique | delonte west only scored the highest number of assists in one game . | {'scope': 'all', 'row': '12', 'col': '7', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'delonte west', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'delonte west'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to delonte west .', 'tostr': 'filter_eq { all_rows ; high assists ; delonte west }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; high assists ; delonte west } } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to delonte west . there is only one such row in the table .'} | only { filter_eq { all_rows ; high assists ; delonte west } } = true | select the rows whose high assists record fuzzily matches to delonte west . 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, 'high assists_4': 4, 'delonte west_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'high assists_4': 'high assists', 'delonte west_5': 'delonte west'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'high assists_4': [0], 'delonte west_5': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['18', 'december 2', 'phoenix suns', 'w 107 - 90 ( ot )', 'zydrunas ilgauskas ( 14 )', "shaquille o'neal ( 9 )", 'lebron james ( 10 )', 'quicken loans arena 20562', '13 - 5'], ['19', 'december 4', 'chicago bulls', 'w 101 - 87 ( ot )', 'lebron james ( 23 )', "zydrunas ilgauskas , shaquille o'neal ( 7 )", 'lebron james ( 11 )', 'quicken loans arena 20562', '14 - 5'], ['20', 'december 6', 'milwaukee bucks', 'w 101 - 86 ( ot )', 'delonte west ( 21 )', 'anderson varejão ( 12 )', 'lebron james ( 10 )', 'bradley center 16625', '15 - 5'], ['21', 'december 8', 'memphis grizzlies', 'l 109 - 111 ( ot )', 'lebron james ( 43 )', 'lebron james ( 13 )', 'mo williams ( 8 )', 'fedex forum 16325', '15 - 6'], ['22', 'december 9', 'houston rockets', 'l 85 - 95 ( ot )', 'lebron james ( 27 )', "shaquille o'neal , j j hickson ( 10 )", 'lebron james ( 7 )', 'toyota center 18200', '15 - 7'], ['23', 'december 11', 'portland trail blazers', 'w 104 - 99 ( ot )', 'lebron james ( 33 )', "shaquille o'neal ( 11 )", 'mo williams ( 10 )', 'quicken loans arena 20562', '16 - 7'], ['24', 'december 13', 'oklahoma city thunder', 'w 102 - 89 ( ot )', 'lebron james ( 44 )', 'anderson varejão ( 10 )', 'lebron james ( 6 )', 'ford center 18203', '17 - 7'], ['25', 'december 15', 'new jersey nets', 'w 99 - 89 ( ot )', 'lebron james ( 23 )', 'mo williams , jamario moon ( 8 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '18 - 7'], ['26', 'december 16', 'philadelphia 76ers', 'w 108 - 101 ( ot )', 'lebron james ( 36 )', "shaquille o'neal ( 9 )", 'lebron james ( 7 )', 'wachovia center 19517', '19 - 7'], ['27', 'december 18', 'milwaukee bucks', 'w 85 - 82 ( ot )', 'lebron james ( 26 )', 'lebron james ( 10 )', 'lebron james ( 8 )', 'quicken loans arena 20562', '20 - 7'], ['28', 'december 20', 'dallas mavericks', 'l 95 - 102 ( ot )', 'lebron james ( 25 )', "anderson varejão , shaquille o'neal ( 8 )", 'lebron james ( 6 )', 'american airlines center 20346', '20 - 8'], ['29', 'december 21', 'phoenix suns', 'w 109 - 91 ( ot )', 'lebron james ( 29 )', 'mo williams , lebron james , jj hickson ( 6 )', 'delonte west ( 6 )', 'us airways center 18221', '21 - 8'], ['30', 'december 23', 'sacramento kings', 'w 117 - 104 ( ot )', 'lebron james ( 34 )', 'lebron james ( 16 )', 'lebron james ( 10 )', 'arco arena 16407', '22 - 8'], ['31', 'december 25', 'la lakers', 'w 102 - 87 ( ot )', 'mo williams ( 28 )', 'anderson varejão , zydrunas ilgauskas ( 9 )', 'lebron james ( 9 )', 'staples center 18997', '23 - 8'], ['32', 'december 27', 'houston rockets', 'w 108 - 83 ( ot )', 'lebron james ( 29 )', "shaquille o'neal ( 11 )", 'lebron james ( 6 )', 'quicken loans arena 20562', '24 - 8']] |
fundraising for the 2008 united states presidential election | https://en.wikipedia.org/wiki/Fundraising_for_the_2008_United_States_presidential_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12030247-2.html.csv | unique | dennis kucinich was the only candidate with a fundraising contribution of less than 5000000 for the 2008 united states presidential election . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '1', 'criterion': 'less_than', 'value': '5000000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'contributions', '5000000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose contributions record is less than 5000000 .', 'tostr': 'filter_less { all_rows ; contributions ; 5000000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; contributions ; 5000000 } }', 'tointer': 'select the rows whose contributions record is less than 5000000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'contributions', '5000000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose contributions record is less than 5000000 .', 'tostr': 'filter_less { all_rows ; contributions ; 5000000 }'}, 'candidate'], 'result': 'dennis kucinich', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; contributions ; 5000000 } ; candidate }'}, 'dennis kucinich'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; contributions ; 5000000 } ; candidate } ; dennis kucinich }', 'tointer': 'the candidate record of this unqiue row is dennis kucinich .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; contributions ; 5000000 } } ; eq { hop { filter_less { all_rows ; contributions ; 5000000 } ; candidate } ; dennis kucinich } } = true', 'tointer': 'select the rows whose contributions record is less than 5000000 . there is only one such row in the table . the candidate record of this unqiue row is dennis kucinich .'} | and { only { filter_less { all_rows ; contributions ; 5000000 } } ; eq { hop { filter_less { all_rows ; contributions ; 5000000 } ; candidate } ; dennis kucinich } } = true | select the rows whose contributions record is less than 5000000 . there is only one such row in the table . the candidate record of this unqiue row is dennis kucinich . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'contributions_7': 7, '5000000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'candidate_9': 9, 'dennis kucinich_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'contributions_7': 'contributions', '5000000_8': '5000000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'candidate_9': 'candidate', 'dennis kucinich_10': 'dennis kucinich'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'contributions_7': [0], '5000000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'candidate_9': [2], 'dennis kucinich_10': [3]} | ['candidate', 'contributions', 'loans received', 'all receipts', 'operating expenditures', 'all disbursements'] | [['hillary clinton', '107056586', '0', '118301659', '77804197', '106000000'], ['barack obama', '102092819', '0', '103802537', '84497445', '85176289'], ['john edwards', '34986088', '8974714', '44259386', '33513005', '36468929'], ['bill richardson', '22421742', '1000000', '23671031', '21401414', '21857565'], ['chris dodd', '10414392', '1302811', '16547015', '14040555', '14057455'], ['joe biden', '8245241', '1132114', '11405771', '9518537', '9538687'], ['dennis kucinich', '3869613', '0', '3870840', '3638219', '3641234'], ['combined total', '289086481', '12409639', '321858239', '244413372', '251093944']] |
salyut 6 | https://en.wikipedia.org/wiki/Salyut_6 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-245800-2.html.csv | superlative | the longest duration of a salyut 6 in orbit was salyut 6 - eo - 4 with 184 . 84 days . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '7', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'duration ( days )'], 'result': '184.84', 'ind': 0, 'tostr': 'max { all_rows ; duration ( days ) }', 'tointer': 'the maximum duration ( days ) record of all rows is 184.84 .'}, '184.84'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; duration ( days ) } ; 184.84 }', 'tointer': 'the maximum duration ( days ) record of all rows is 184.84 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'duration ( days )'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; duration ( days ) }'}, 'expedition'], 'result': 'salyut 6 - eo - 4', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; duration ( days ) } ; expedition }'}, 'salyut 6 - eo - 4'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; duration ( days ) } ; expedition } ; salyut 6 - eo - 4 }', 'tointer': 'the expedition record of the row with superlative duration ( days ) record is salyut 6 - eo - 4 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; duration ( days ) } ; 184.84 } ; eq { hop { argmax { all_rows ; duration ( days ) } ; expedition } ; salyut 6 - eo - 4 } } = true', 'tointer': 'the maximum duration ( days ) record of all rows is 184.84 . the expedition record of the row with superlative duration ( days ) record is salyut 6 - eo - 4 .'} | and { eq { max { all_rows ; duration ( days ) } ; 184.84 } ; eq { hop { argmax { all_rows ; duration ( days ) } ; expedition } ; salyut 6 - eo - 4 } } = true | the maximum duration ( days ) record of all rows is 184.84 . the expedition record of the row with superlative duration ( days ) record is salyut 6 - eo - 4 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'duration (days)_8': 8, '184.84_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'duration (days)_11': 11, 'expedition_12': 12, 'salyut 6 - eo - 4_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'duration (days)_8': 'duration ( days )', '184.84_9': '184.84', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'duration (days)_11': 'duration ( days )', 'expedition_12': 'expedition', 'salyut 6 - eo - 4_13': 'salyut 6 - eo - 4'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'duration (days)_8': [0], '184.84_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'duration (days)_11': [2], 'expedition_12': [3], 'salyut 6 - eo - 4_13': [4]} | ['expedition', 'crew', 'launch date', 'flight up', 'landing date', 'flight down', 'duration ( days )'] | [['salyut 6 - eo - 1', 'yuri romanenko , georgi grechko', '10 december 1977 01:18:40', 'soyuz 26', '16 march 1978 11:18:47', 'soyuz 27', '96.42'], ['salyut 6 - ep - 1', 'vladimir dzhanibekov , oleg makarov', '10 january 1978 12:26:00', 'soyuz 27', '16 january 1978 11:24:58', 'soyuz 26', '5.96'], ['salyut 6 - ep - 2', 'aleksei gubarev , vladimír remek - czechoslovakia', '2 march 1978 15:28:00', 'soyuz 28', '10 march 1978 13:44:00', 'soyuz 28', '7.93'], ['salyut 6 - eo - 2', 'vladimir kovalyonok , aleksandr ivanchenkov', '15 june 1978 20:16:45', 'soyuz 29', '2 november 1978 11:04:17', 'soyuz 31', '139.62'], ['salyut 6 - ep - 3', 'pyotr klimuk , miroslaw hermaszewski - poland', '27 june 1978 15:27:21', 'soyuz 30', '5 july 1978 13:30:20', 'soyuz 30', '7.92'], ['salyut 6 - eo - 3', 'vladimir lyakhov , valery ryumin', '25 february 1979 11:53:49', 'soyuz 32', '19 august 1979 12:29:26', 'soyuz 34', '175.02'], ['salyut 6 - eo - 4', 'leonid popov , valery ryumin', '9 april 1980 13:38:22', 'soyuz 35', '11 october 1980 09:49:57', 'soyuz 37', '184.84'], ['salyut 6 - ep - 5', 'valery kubasov , bertalan farkas - hungary', '26 may 1980 18:20:39', 'soyuz 36', '3 june 1980 15:06:23', 'soyuz 35', '7.87'], ['salyut 6 - ep - 6', 'yuri malyshev , vladimir aksyonov', '5 june 1980 14:19:30', 'soyuz t - 2', '9 june 1980 12:39:00', 'soyuz t - 2', '3.93'], ['salyut 6 - ep - 7', 'viktor gorbatko , pham tuan - vietnam', '23 july 1980 18:33:03', 'soyuz 37', '31 july 1980 15:15:02', 'soyuz 36', '7.86'], ['salyut 6 - ep - 8', 'yuri romanenko , arnaldo tamayo méndez - cuba', '18 september 1980 19:11:03', 'soyuz 38', '26 september 1980 15:54:27', 'soyuz 38', '7.86'], ['salyut 6 - eo - 5', 'leonid kizim , oleg makarov gennady strekalov', '27 november 1980 14:18:28', 'soyuz t - 3', '10 december 1980 09:26:10', 'soyuz t - 3', '12.80'], ['salyut 6 - eo - 6', 'vladimir kovalyonok , viktor savinykh', '12 march 1981 19:00:11', 'soyuz t - 4', '26 may 1981 12:37:34', 'soyuz t - 4', '74.73']] |
2006 masters tournament | https://en.wikipedia.org/wiki/2006_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12626983-7.html.csv | unique | vijay singh was the only player in the 2006 masters tournament from the country of fiji . | {'scope': 'all', 'row': '9', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'fiji', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'fiji'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to fiji .', 'tostr': 'filter_eq { all_rows ; country ; fiji }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; fiji } }', 'tointer': 'select the rows whose country record fuzzily matches to fiji . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'fiji'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to fiji .', 'tostr': 'filter_eq { all_rows ; country ; fiji }'}, 'player'], 'result': 'vijay singh', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; fiji } ; player }'}, 'vijay singh'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; fiji } ; player } ; vijay singh }', 'tointer': 'the player record of this unqiue row is vijay singh .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; fiji } } ; eq { hop { filter_eq { all_rows ; country ; fiji } ; player } ; vijay singh } } = true', 'tointer': 'select the rows whose country record fuzzily matches to fiji . there is only one such row in the table . the player record of this unqiue row is vijay singh .'} | and { only { filter_eq { all_rows ; country ; fiji } } ; eq { hop { filter_eq { all_rows ; country ; fiji } ; player } ; vijay singh } } = true | select the rows whose country record fuzzily matches to fiji . there is only one such row in the table . the player record of this unqiue row is vijay singh . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'fiji_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'vijay singh_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', 'fiji_8': 'fiji', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'vijay singh_10': 'vijay singh'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'fiji_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'vijay singh_10': [3]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'phil mickelson', 'united states', '70 + 72 + 70 + 69 = 281', '- 7', '1260000'], ['2', 'tim clark', 'south africa', '70 + 72 + 72 + 69 = 283', '- 5', '756000'], ['t3', 'chad campbell', 'united states', '71 + 67 + 75 + 71 = 284', '- 4', '315700'], ['t3', 'fred couples', 'united states', '71 + 70 + 72 + 71 = 284', '- 4', '315700'], ['t3', 'retief goosen', 'south africa', '70 + 73 + 72 + 69 = 284', '- 4', '315700'], ['t3', 'josé maría olazábal', 'spain', '76 + 71 + 71 + 66 = 284', '- 4', '315700'], ['t3', 'tiger woods', 'united states', '72 + 71 + 71 + 70 = 284', '- 4', '315700'], ['t8', 'ángel cabrera', 'argentina', '73 + 74 + 70 + 68 = 285', '- 3', '210000'], ['t8', 'vijay singh', 'fiji', '67 + 74 + 73 + 71 = 285', '- 3', '210000'], ['10', 'stewart cink', 'united states', '72 + 73 + 71 + 70 = 286', '- 2', '189000']] |
forces of satan records | https://en.wikipedia.org/wiki/Forces_of_Satan_Records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14728538-1.html.csv | unique | the title bergen 1996 is the only title that has gorgoroth as the artist . | {'scope': 'all', 'row': '1', 'col': '1', 'col_other': '2', 'criterion': 'equal', 'value': 'gorgoroth', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'gorgoroth'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose artist record fuzzily matches to gorgoroth .', 'tostr': 'filter_eq { all_rows ; artist ; gorgoroth }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; artist ; gorgoroth } }', 'tointer': 'select the rows whose artist record fuzzily matches to gorgoroth . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'gorgoroth'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose artist record fuzzily matches to gorgoroth .', 'tostr': 'filter_eq { all_rows ; artist ; gorgoroth }'}, 'title'], 'result': 'bergen 1996', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; artist ; gorgoroth } ; title }'}, 'bergen 1996'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; artist ; gorgoroth } ; title } ; bergen 1996 }', 'tointer': 'the title record of this unqiue row is bergen 1996 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; artist ; gorgoroth } } ; eq { hop { filter_eq { all_rows ; artist ; gorgoroth } ; title } ; bergen 1996 } } = true', 'tointer': 'select the rows whose artist record fuzzily matches to gorgoroth . there is only one such row in the table . the title record of this unqiue row is bergen 1996 .'} | and { only { filter_eq { all_rows ; artist ; gorgoroth } } ; eq { hop { filter_eq { all_rows ; artist ; gorgoroth } ; title } ; bergen 1996 } } = true | select the rows whose artist record fuzzily matches to gorgoroth . there is only one such row in the table . the title record of this unqiue row is bergen 1996 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'artist_7': 7, 'gorgoroth_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'bergen 1996_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'artist_7': 'artist', 'gorgoroth_8': 'gorgoroth', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'bergen 1996_10': 'bergen 1996'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'artist_7': [0], 'gorgoroth_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'bergen 1996_10': [3]} | ['artist', 'title', 'release date', 'format', 'cat'] | [['gorgoroth', 'bergen 1996', 'november 2007', 'mcd / 7 pic disc', 'fsr001'], ['ophiolatry', 'transmutation', 'january 21 , 2008', 'full - length', 'fsr002'], ['ophiolatry', 'antievangelistical process ( re - release )', '2009', 'full - length', 'fsr003'], ['black flame', 'imperivm', 'june 23 , 2008', 'full - length', 'fsr004'], ['tangorodrim', 'unholy metal way ( re - release )', '2009', 'full - length', 'fsr005'], ['tangorodrim', 'those who unleashed ( re - release )', '2009', 'full - length', 'fsr006'], ['triumfall', 'antithesis of all flesh', 'june 15 , 2009', 'full - length', 'fsr007']] |
philipp petzschner | https://en.wikipedia.org/wiki/Philipp_Petzschner | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13014020-6.html.csv | majority | philipp petzschner partnered with jürgen melzer for the majority of his tennis doubles tournaments . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'jürgen melzer', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'partner', 'jürgen melzer'], 'result': True, 'ind': 0, 'tointer': 'for the partner records of all rows , most of them fuzzily match to jürgen melzer .', 'tostr': 'most_eq { all_rows ; partner ; jürgen melzer } = true'} | most_eq { all_rows ; partner ; jürgen melzer } = true | for the partner records of all rows , most of them fuzzily match to jürgen melzer . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'partner_3': 3, 'jürgen melzer_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'partner_3': 'partner', 'jürgen melzer_4': 'jürgen melzer'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'partner_3': [0], 'jürgen melzer_4': [0]} | ['outcome', 'date', 'surface', 'partner', 'opponents', 'score'] | [['runner - up', 'october 12 , 2008', 'hard ( i )', 'alexander peya', 'max mirnyi andy ram', '1 - 6 , 5 - 7'], ['winner', 'february 7 , 2010', 'hard ( i )', 'jürgen melzer', 'arnaud clément olivier rochus', '3 - 6 , 6 - 3 ,'], ['winner', 'july 3 , 2010', 'grass', 'jürgen melzer', 'robert lindstedt horia tecău', '6 - 1 , 7 - 5 , 7 - 5'], ['runner - up', 'july 18 , 2010', 'clay', 'christopher kas', 'carlos berlocq eduardo schwank', '6 - 7 ( 5 - 7 ) , 6 - 7 ( 6 - 8 )'], ['winner', 'february 13 , 2011', 'hard ( i )', 'jürgen melzer', 'michaël llodra nenad zimonjić', '6 - 4 , 3 - 6 ,'], ['winner', 'july 16 , 2011', 'clay', 'jürgen melzer', 'marcel granollers marc lópez', '6 - 3 , 6 - 4'], ['winner', 'september 10 , 2011', 'hard', 'jürgen melzer', 'mariusz fyrstenberg marcin matkowski', '6 - 2 , 6 - 2'], ['runner - up', 'january 7 , 2012', 'hard', 'jürgen melzer', 'max mirnyi daniel nestor', '1 - 6 , 2 - 6']] |
jason leffler | https://en.wikipedia.org/wiki/Jason_Leffler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1637041-2.html.csv | majority | jason leffler ranked lower than 50th place in most of his matches after 2004 . | {'scope': 'subset', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '50', 'subset': {'col': '1', 'criterion': 'greater_than', 'value': '2004'}} | {'func': 'most_greater', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'year', '2004'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; year ; 2004 }', 'tointer': 'select the rows whose year record is greater than 2004 .'}, 'position', '50'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose year record is greater than 2004 . for the position records of these rows , most of them are greater than 50 .', 'tostr': 'most_greater { filter_greater { all_rows ; year ; 2004 } ; position ; 50 } = true'} | most_greater { filter_greater { all_rows ; year ; 2004 } ; position ; 50 } = true | select the rows whose year record is greater than 2004 . for the position records of these rows , most of them are greater than 50 . | 2 | 2 | {'most_greater_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'year_4': 4, '2004_5': 5, 'position_6': 6, '50_7': 7} | {'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'year_4': 'year', '2004_5': '2004', 'position_6': 'position', '50_7': '50'} | {'most_greater_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'year_4': [0], '2004_5': [0], 'position_6': [1], '50_7': [1]} | ['year', 'starts', 'wins', 'top 10', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['2001', '30', '0', '1', '28.7', '27.7', '1724692', '37th', '01 chip ganassi racing'], ['2002', '2', '0', '0', '32.5', '33.0', '78500', '63rd', '7 ultra motorsports'], ['2003', '10', '0', '0', '28.0', '29.2', '594500', '47th', '0 haas cnc racing'], ['2004', '1', '0', '0', '25.0', '43.0', '116359', '88th', '60 haas cnc racing'], ['2005', '19', '0', '0', '25.7', '27.5', '1663868', '38th', '11 joe gibbs racing'], ['2008', '3', '0', '0', '30.0', '33.0', '286450', '59th', '70 haas cnc racing'], ['2010', '2', '0', '0', '34.0', '43.0', '135984', '70th', '32 braun racing 66 prism motorsports']] |
1953 argentine grand prix | https://en.wikipedia.org/wiki/1953_Argentine_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122075-2.html.csv | unique | nino farina was the only driver to retire because of an accident at the 1953 argentine grand prix . | {'scope': 'all', 'row': '13', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'accident', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time / retired ; accident }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; time / retired ; accident } }', 'tointer': 'select the rows whose time / retired record fuzzily matches to accident . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'time / retired', 'accident'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose time / retired record fuzzily matches to accident .', 'tostr': 'filter_eq { all_rows ; time / retired ; accident }'}, 'driver'], 'result': 'nino farina', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; time / retired ; accident } ; driver }'}, 'nino farina'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; time / retired ; accident } ; driver } ; nino farina }', 'tointer': 'the driver record of this unqiue row is nino farina .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; time / retired ; accident } } ; eq { hop { filter_eq { all_rows ; time / retired ; accident } ; driver } ; nino farina } } = true', 'tointer': 'select the rows whose time / retired record fuzzily matches to accident . there is only one such row in the table . the driver record of this unqiue row is nino farina .'} | and { only { filter_eq { all_rows ; time / retired ; accident } } ; eq { hop { filter_eq { all_rows ; time / retired ; accident } ; driver } ; nino farina } } = true | select the rows whose time / retired record fuzzily matches to accident . there is only one such row in the table . the driver record of this unqiue row is nino farina . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time / retired_7': 7, 'accident_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'nino farina_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time / retired_7': 'time / retired', 'accident_8': 'accident', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'nino farina_10': 'nino farina'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time / retired_7': [0], 'accident_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'nino farina_10': [3]} | ['driver', 'constructor', 'laps', 'time / retired', 'grid'] | [['alberto ascari', 'ferrari', '97', '3:01:04.6', '1'], ['luigi villoresi', 'ferrari', '96', '+ 1 lap', '3'], ['josé froilán gonzález', 'maserati', '96', '+ 1 lap', '5'], ['mike hawthorn', 'ferrari', '96', '+ 1 lap', '6'], ['oscar alfredo gálvez', 'maserati', '96', '+ 1 lap', '9'], ['jean behra', 'gordini', '94', '+ 3 laps', '11'], ['maurice trintignant harry schell', 'gordini', '91', '+ 6 laps', '7'], ['john barber', 'cooper - bristol', '90', '+ 7 laps', '16'], ['alan brown', 'cooper - bristol', '87', '+ 10 laps', '12'], ['robert manzon', 'gordini', '67', 'wheel', '8'], ['juan manuel fangio', 'maserati', '36', 'transmission', '2'], ['felice bonetto', 'maserati', '32', 'transmission', '15'], ['nino farina', 'ferrari', '31', 'accident', '4'], ['carlos menditeguy', 'gordini', '24', 'gearbox', '10'], ['pablo birger', 'simca - gordini - gordini', '21', 'differential', '14'], ['adolfo schwelm cruz', 'cooper - bristol', '20', 'wheel', '13']] |
2009 - 10 cleveland cavaliers season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22654073-7.html.csv | majority | most of the games had lebron james as the highest assists . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'lebron james', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'lebron james'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to lebron james .', 'tostr': 'most_eq { all_rows ; high points ; lebron james } = true'} | most_eq { all_rows ; high points ; lebron james } = true | for the high points records of all rows , most of them fuzzily match to lebron james . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'lebron james_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'lebron james_4': 'lebron james'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'lebron james_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['18', 'december 2', 'phoenix suns', 'w 107 - 90 ( ot )', 'zydrunas ilgauskas ( 14 )', "shaquille o'neal ( 9 )", 'lebron james ( 10 )', 'quicken loans arena 20562', '13 - 5'], ['19', 'december 4', 'chicago bulls', 'w 101 - 87 ( ot )', 'lebron james ( 23 )', "zydrunas ilgauskas , shaquille o'neal ( 7 )", 'lebron james ( 11 )', 'quicken loans arena 20562', '14 - 5'], ['20', 'december 6', 'milwaukee bucks', 'w 101 - 86 ( ot )', 'delonte west ( 21 )', 'anderson varejão ( 12 )', 'lebron james ( 10 )', 'bradley center 16625', '15 - 5'], ['21', 'december 8', 'memphis grizzlies', 'l 109 - 111 ( ot )', 'lebron james ( 43 )', 'lebron james ( 13 )', 'mo williams ( 8 )', 'fedex forum 16325', '15 - 6'], ['22', 'december 9', 'houston rockets', 'l 85 - 95 ( ot )', 'lebron james ( 27 )', "shaquille o'neal , j j hickson ( 10 )", 'lebron james ( 7 )', 'toyota center 18200', '15 - 7'], ['23', 'december 11', 'portland trail blazers', 'w 104 - 99 ( ot )', 'lebron james ( 33 )', "shaquille o'neal ( 11 )", 'mo williams ( 10 )', 'quicken loans arena 20562', '16 - 7'], ['24', 'december 13', 'oklahoma city thunder', 'w 102 - 89 ( ot )', 'lebron james ( 44 )', 'anderson varejão ( 10 )', 'lebron james ( 6 )', 'ford center 18203', '17 - 7'], ['25', 'december 15', 'new jersey nets', 'w 99 - 89 ( ot )', 'lebron james ( 23 )', 'mo williams , jamario moon ( 8 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '18 - 7'], ['26', 'december 16', 'philadelphia 76ers', 'w 108 - 101 ( ot )', 'lebron james ( 36 )', "shaquille o'neal ( 9 )", 'lebron james ( 7 )', 'wachovia center 19517', '19 - 7'], ['27', 'december 18', 'milwaukee bucks', 'w 85 - 82 ( ot )', 'lebron james ( 26 )', 'lebron james ( 10 )', 'lebron james ( 8 )', 'quicken loans arena 20562', '20 - 7'], ['28', 'december 20', 'dallas mavericks', 'l 95 - 102 ( ot )', 'lebron james ( 25 )', "anderson varejão , shaquille o'neal ( 8 )", 'lebron james ( 6 )', 'american airlines center 20346', '20 - 8'], ['29', 'december 21', 'phoenix suns', 'w 109 - 91 ( ot )', 'lebron james ( 29 )', 'mo williams , lebron james , jj hickson ( 6 )', 'delonte west ( 6 )', 'us airways center 18221', '21 - 8'], ['30', 'december 23', 'sacramento kings', 'w 117 - 104 ( ot )', 'lebron james ( 34 )', 'lebron james ( 16 )', 'lebron james ( 10 )', 'arco arena 16407', '22 - 8'], ['31', 'december 25', 'la lakers', 'w 102 - 87 ( ot )', 'mo williams ( 28 )', 'anderson varejão , zydrunas ilgauskas ( 9 )', 'lebron james ( 9 )', 'staples center 18997', '23 - 8'], ['32', 'december 27', 'houston rockets', 'w 108 - 83 ( ot )', 'lebron james ( 29 )', "shaquille o'neal ( 11 )", 'lebron james ( 6 )', 'quicken loans arena 20562', '24 - 8']] |
forbes global 2000 | https://en.wikipedia.org/wiki/Forbes_Global_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1682026-9.html.csv | comparative | the profits for bp in 2000 were higher than the profits for hsbc . | {'row_1': '8', 'row_2': '5', 'col': '6', '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', 'company', 'bp'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose company record fuzzily matches to bp .', 'tostr': 'filter_eq { all_rows ; company ; bp }'}, 'profits ( billion )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; company ; bp } ; profits ( billion ) }', 'tointer': 'select the rows whose company record fuzzily matches to bp . take the profits ( billion ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'company', 'hsbc'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose company record fuzzily matches to hsbc .', 'tostr': 'filter_eq { all_rows ; company ; hsbc }'}, 'profits ( billion )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; company ; hsbc } ; profits ( billion ) }', 'tointer': 'select the rows whose company record fuzzily matches to hsbc . take the profits ( billion ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; company ; bp } ; profits ( billion ) } ; hop { filter_eq { all_rows ; company ; hsbc } ; profits ( billion ) } } = true', 'tointer': 'select the rows whose company record fuzzily matches to bp . take the profits ( billion ) record of this row . select the rows whose company record fuzzily matches to hsbc . take the profits ( billion ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; company ; bp } ; profits ( billion ) } ; hop { filter_eq { all_rows ; company ; hsbc } ; profits ( billion ) } } = true | select the rows whose company record fuzzily matches to bp . take the profits ( billion ) record of this row . select the rows whose company record fuzzily matches to hsbc . take the profits ( billion ) 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, 'company_7': 7, 'bp_8': 8, 'profits (billion )_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'company_11': 11, 'hsbc_12': 12, 'profits (billion )_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', 'company_7': 'company', 'bp_8': 'bp', 'profits (billion )_9': 'profits ( billion )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'company_11': 'company', 'hsbc_12': 'hsbc', 'profits (billion )_13': 'profits ( billion )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'company_7': [0], 'bp_8': [0], 'profits (billion )_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'company_11': [1], 'hsbc_12': [1], 'profits (billion )_13': [3]} | ['rank', 'company', 'country', 'industry', 'sales ( billion )', 'profits ( billion )', 'assets ( billion )', 'market value ( billion )'] | [['1', 'citigroup', 'usa', 'banking', '108.28', '17.05', '1 , 4.10', '247.66'], ['2', 'general electric', 'usa', 'conglomerates', '152.36', '16.59', '750.33', '372.14'], ['3', 'american international group', 'usa', 'insurance', '95.04', '10.91', '776.42', '173.99'], ['4', 'bank of america', 'usa', 'banking', '65.45', '14.14', '1110.46', '188.77'], ['5', 'hsbc', 'uk', 'banking', '62.97', '9.52', '1031.29', '186.74'], ['6', 'exxonmobil', 'usa', 'oil & gas', '263.99', '25.33', '195.26', '405.25'], ['7', 'royal dutch shell', 'netherlands', 'oil & gas', '265.19', '18.54', '193.83', '221.49'], ['8', 'bp', 'uk', 'oil & gas', '285.06', '15.73', '191.11', '231.88'], ['9', 'ing group', 'netherlands', 'diversified financials', '92.01', '8.10', '1175.16', '68.04']] |
1929 in brazilian football | https://en.wikipedia.org/wiki/1929_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15372465-2.html.csv | comparative | during the 1929 brazilian football games , hespanha scored more than ca paulista . | {'row_1': '5', 'row_2': '12', 'col': '3', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'hespanha'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to hespanha .', 'tostr': 'filter_eq { all_rows ; team ; hespanha }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; hespanha } ; points }', 'tointer': 'select the rows whose team record fuzzily matches to hespanha . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'ca paulista'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to ca paulista .', 'tostr': 'filter_eq { all_rows ; team ; ca paulista }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; ca paulista } ; points }', 'tointer': 'select the rows whose team record fuzzily matches to ca paulista . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; hespanha } ; points } ; hop { filter_eq { all_rows ; team ; ca paulista } ; points } } = true', 'tointer': 'select the rows whose team record fuzzily matches to hespanha . take the points record of this row . select the rows whose team record fuzzily matches to ca paulista . take the points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; team ; hespanha } ; points } ; hop { filter_eq { all_rows ; team ; ca paulista } ; points } } = true | select the rows whose team record fuzzily matches to hespanha . take the points record of this row . select the rows whose team record fuzzily matches to ca paulista . take the points record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'hespanha_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'ca paulista_12': 12, 'points_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'hespanha_8': 'hespanha', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'ca paulista_12': 'ca paulista', 'points_13': 'points'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'hespanha_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'ca paulista_12': [1], 'points_13': [3]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'paulistano', '30', '19', '2', '3', '15', '38'], ['2', 'ponte preta', '26', '20', '2', '6', '36', '19'], ['3', 'sc internacional de são paulo', '23', '18', '5', '4', '23', '11'], ['4', 'independência', '23', '20', '5', '7', '37', '5'], ['5', 'hespanha', '22', '20', '6', '6', '35', '11'], ['6', 'atlético santista', '19', '19', '5', '7', '28', '6'], ['7', 'germnia', '18', '18', '2', '8', '45', '- 7'], ['8', 'portuguesa santista', '18', '21', '4', '10', '40', '- 3'], ['9', 'antártica', '17', '21', '7', '9', '47', '- 17'], ['10', 'aa são bento', '16', '19', '6', '8', '32', '- 12'], ['11', 'aa das palmeiras', '11', '17', '1', '11', '50', '- 22'], ['12', 'ca paulista', '11', '20', '1', '14', '58', '- 29']] |
bombay jayashri | https://en.wikipedia.org/wiki/Bombay_Jayashri | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11203591-2.html.csv | count | 6 of bombay jayashri 's songs were sung solo without a co-performer . | {'scope': 'all', 'criterion': 'equal', 'value': 'solo', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'co - singers', 'solo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose co - singers record fuzzily matches to solo .', 'tostr': 'filter_eq { all_rows ; co - singers ; solo }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; co - singers ; solo } }', 'tointer': 'select the rows whose co - singers record fuzzily matches to solo . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; co - singers ; solo } } ; 6 } = true', 'tointer': 'select the rows whose co - singers record fuzzily matches to solo . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; co - singers ; solo } } ; 6 } = true | select the rows whose co - singers record fuzzily matches to solo . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'co - singers_5': 5, 'solo_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'co - singers_5': 'co - singers', 'solo_6': 'solo', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'co - singers_5': [0], 'solo_6': [0], '6_7': [2]} | ['year', 'song title', 'movie', 'music director', 'co - singers'] | [['1997', 'sasivadane', 'iddaru', 'a r rahman', 'unni krishnan'], ['2001', 'manohara', 'cheli', 'harris jayaraj', 'solo'], ['2002', 'tiya tiyani kalalanu', 'sreeram', 'r p patnaik', 'solo'], ['2005', 'hrudayam ekkadunnadi', 'ghajini', 'harris jayaraj', 'harish raghavendra'], ['2005', 'aamani koyilanai', 'premikulu', 'sajan madhav', 'solo'], ['2006', 'vere maina anani', 'amma cheppindi', 'm m keeravani', 'solo'], ['2006', 'yentho dooram', 'amma cheppindi', 'm m keeravani', 'solo'], ['2006', 'ulike o chilake', 'jalakanta', 'harris jayaraj', 'karthik'], ['2007', 'banam', 'raghavan', 'harris jayaraj', 'harish raghavendra'], ['2008', 'anti pettukundhuna', '16 days', 'dharan', 'haricharan'], ['2008', 'enduko madi', 'nenu meeku telusa', 'achu', 'hemachandra'], ['2008', 'muddula muddula', 'salute', 'harris jayaraj', 'balram , sunitha sarathy'], ['2009', 'eenaadu ee samaram', 'eeenadu', 'shruthi hassan', 'kamal haasan'], ['2011', 'ee manchullo', 'rangam', 'harris jayaraj', 'sriram parthasarathy'], ['2012', 'vennelave', 'thuppakki', 'harris jayaraj', 'hariharan'], ['2013', 'kamalaasana', 'intinta annamaya', 'm m keeravani', 'solo']] |
united states house of representatives elections , 1942 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1942 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342256-40.html.csv | ordinal | of the incumbents in the 1942 election for united states house of representatives , the 2nd earliest first election date was for james p richards . | {'row': '5', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'first elected', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 2 }'}, 'incumbent'], 'result': 'james p richards', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent }'}, 'james p richards'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; james p richards } = true', 'tointer': 'select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is james p richards .'} | eq { hop { nth_argmin { all_rows ; first elected ; 2 } ; incumbent } ; james p richards } = true | select the row whose first elected record of all rows is 2nd minimum . the incumbent record of this row is james p richards . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '2_6': 6, 'incumbent_7': 7, 'james p richards_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', 'first elected_5': 'first elected', '2_6': '2', 'incumbent_7': 'incumbent', 'james p richards_8': 'james p richards'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '2_6': [0], 'incumbent_7': [1], 'james p richards_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['south carolina 1', 'l mendel rivers', 'democratic', '1940', 're - elected', 'l mendel rivers ( d ) unopposed'], ['south carolina 2', 'hampton p fulmer', 'democratic', '1920', 're - elected', 'hampton p fulmer ( d ) unopposed'], ['south carolina 3', 'butler b hare', 'democratic', '1938', 're - elected', 'butler b hare ( d ) unopposed'], ['south carolina 4', 'joseph r bryson', 'democratic', '1938', 're - elected', 'joseph r bryson ( d ) unopposed'], ['south carolina 5', 'james p richards', 'democratic', '1932', 're - elected', 'james p richards ( d ) unopposed']] |
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/1-15187735-4.html.csv | unique | episode 4-04 is the only one with a two-part segment with buttons . | {'scope': 'all', 'row': '4', 'col': '7', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'part 2', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment d', 'part 2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment d record fuzzily matches to part 2 .', 'tostr': 'filter_eq { all_rows ; segment d ; part 2 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; segment d ; part 2 } }', 'tointer': 'select the rows whose segment d record fuzzily matches to part 2 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment d', 'part 2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment d record fuzzily matches to part 2 .', 'tostr': 'filter_eq { all_rows ; segment d ; part 2 }'}, 'series ep'], 'result': '4 - 04', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; segment d ; part 2 } ; series ep }'}, '4 - 04'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; segment d ; part 2 } ; series ep } ; 4 - 04 }', 'tointer': 'the series ep record of this unqiue row is 4 - 04 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; segment d ; part 2 } } ; eq { hop { filter_eq { all_rows ; segment d ; part 2 } ; series ep } ; 4 - 04 } } = true', 'tointer': 'select the rows whose segment d record fuzzily matches to part 2 . there is only one such row in the table . the series ep record of this unqiue row is 4 - 04 .'} | and { only { filter_eq { all_rows ; segment d ; part 2 } } ; eq { hop { filter_eq { all_rows ; segment d ; part 2 } ; series ep } ; 4 - 04 } } = true | select the rows whose segment d record fuzzily matches to part 2 . there is only one such row in the table . the series ep record of this unqiue row is 4 - 04 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'segment d_7': 7, 'part 2_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'series ep_9': 9, '4 - 04_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'segment d_7': 'segment d', 'part 2_8': 'part 2', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'series ep_9': 'series ep', '4 - 04_10': '4 - 04'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'segment d_7': [0], 'part 2_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'series ep_9': [2], '4 - 04_10': [3]} | ['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d'] | [['4 - 01', '40', 's02e14', 'plastic bottles & s jar', 'mail', 's egg', 'ed handcraft en wood s pen'], ['4 - 02', '41', 's02e15', 'plastic injection moulds', 'automotive oil filters', 'filing cabinets', 'blown glass'], ['4 - 03', '42', 's02e16', 'high - precision cutting tools', 'stained glass', 's semi - trailer', 's recorder'], ['4 - 04', '43', 's02e17', 'conga drums', 'metal plating', 's button ( part 1 )', 's button ( part 2 )'], ['4 - 05', '44', 's02e18', 'grinding wheels', 'compost', 'window blinds', 'milk'], ['4 - 06', '45', 's02e19', 'es brush and push brooms', 's blackboard', 'smoked salmon', 's zipper'], ['4 - 07', '46', 's02e20', '3d commercial signs', 'hardwood floors', 'corrugated polyethylene pipe', 'es mattress'], ['4 - 08', '47', 's02e21', 'ceramic tiles', 'nuts', 'steel forgings', 's skateboard'], ['4 - 09', '48', 's02e22', 'car engines', 'flour', 's recliner', 's envelope'], ['4 - 10', '49', 's02e23', 'plastic cups and cutlery', 'special effects makeup', 'gold', 's harp'], ['4 - 11', '50', 's02e24', 'laminate', 's frozen treat', "children 's building blocks", 's detergent'], ['4 - 12', '51', 's02e25', 's decorative moulding', 'commercial pulleys', 'industrial rubber hose', 'sheet vinyl flooring']] |
members of the 14th seanad | https://en.wikipedia.org/wiki/Members_of_the_14th_Seanad | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15547255-1.html.csv | unique | the independent party was the only one with 0 members in the agricultural panel . | {'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'agricultural panel', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose agricultural panel record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; agricultural panel ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; agricultural panel ; 0 } }', 'tointer': 'select the rows whose agricultural panel record is equal to 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'agricultural panel', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose agricultural panel record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; agricultural panel ; 0 }'}, 'party'], 'result': 'independent', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; agricultural panel ; 0 } ; party }'}, 'independent'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; agricultural panel ; 0 } ; party } ; independent }', 'tointer': 'the party record of this unqiue row is independent .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; agricultural panel ; 0 } } ; eq { hop { filter_eq { all_rows ; agricultural panel ; 0 } ; party } ; independent } } = true', 'tointer': 'select the rows whose agricultural panel record is equal to 0 . there is only one such row in the table . the party record of this unqiue row is independent .'} | and { only { filter_eq { all_rows ; agricultural panel ; 0 } } ; eq { hop { filter_eq { all_rows ; agricultural panel ; 0 } ; party } ; independent } } = true | select the rows whose agricultural panel record is equal to 0 . there is only one such row in the table . the party record of this unqiue row is independent . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'agricultural panel_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'party_9': 9, 'independent_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'agricultural panel_7': 'agricultural panel', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'party_9': 'party', 'independent_10': 'independent'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'agricultural panel_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'party_9': [2], 'independent_10': [3]} | ['party', 'administrative panel', 'agricultural panel', 'cultural and educational panel', 'industrial and commercial panel', 'labour panel', 'national university of ireland', 'university of dublin', 'nominated by the taoiseach', 'total'] | [['fianna fáil', '4', '5', '2', '4', '5', '0', '0', '9', '29'], ['fine gael', '3', '5', '2', '4', '4', '0', '0', '0', '18'], ['labour party', '0', '1', '1', '1', '2', '0', '1', '0', '6'], ['independent', '0', '0', '0', '0', '0', '3', '2', '2', '7'], ['total', '7', '11', '5', '9', '11', '3', '3', '11', '60']] |
list of top association football goal scorers by country | https://en.wikipedia.org/wiki/List_of_top_association_football_goal_scorers_by_country | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1590321-74.html.csv | unique | for the top association football goal scorers , for those that had over 200 matches , the only one with 134 goals was jeff cunningham . | {'scope': 'subset', 'row': '1', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': '134', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '200'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'matches', '200'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; matches ; 200 }', 'tointer': 'select the rows whose matches record is greater than 200 .'}, 'goals', '134'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose matches record is greater than 200 . among these rows , select the rows whose goals record is equal to 134 .', 'tostr': 'filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 } }', 'tointer': 'select the rows whose matches record is greater than 200 . among these rows , select the rows whose goals record is equal to 134 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'matches', '200'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; matches ; 200 }', 'tointer': 'select the rows whose matches record is greater than 200 .'}, 'goals', '134'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose matches record is greater than 200 . among these rows , select the rows whose goals record is equal to 134 .', 'tostr': 'filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 }'}, 'name'], 'result': 'jeff cunningham', 'ind': 3, 'tostr': 'hop { filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 } ; name }'}, 'jeff cunningham'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 } ; name } ; jeff cunningham }', 'tointer': 'the name record of this unqiue row is jeff cunningham .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 } } ; eq { hop { filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 } ; name } ; jeff cunningham } } = true', 'tointer': 'select the rows whose matches record is greater than 200 . among these rows , select the rows whose goals record is equal to 134 . there is only one such row in the table . the name record of this unqiue row is jeff cunningham .'} | and { only { filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 } } ; eq { hop { filter_eq { filter_greater { all_rows ; matches ; 200 } ; goals ; 134 } ; name } ; jeff cunningham } } = true | select the rows whose matches record is greater than 200 . among these rows , select the rows whose goals record is equal to 134 . there is only one such row in the table . the name record of this unqiue row is jeff cunningham . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_eq_1': 1, 'filter_greater_0': 0, 'all_rows_7': 7, 'matches_8': 8, '200_9': 9, 'goals_10': 10, '134_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'name_12': 12, 'jeff cunningham_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_eq_1': 'filter_eq', 'filter_greater_0': 'filter_greater', 'all_rows_7': 'all_rows', 'matches_8': 'matches', '200_9': '200', 'goals_10': 'goals', '134_11': '134', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'name_12': 'name', 'jeff cunningham_13': 'jeff cunningham'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_eq_1': [2, 3], 'filter_greater_0': [1], 'all_rows_7': [0], 'matches_8': [0], '200_9': [0], 'goals_10': [1], '134_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'name_12': [3], 'jeff cunningham_13': [4]} | ['rank', 'name', 'years', 'matches', 'goals'] | [['1', 'jeff cunningham', '1998 - 2011', '365', '134'], ['2', 'jaime moreno', '1996 - 2010', '340', '133'], ['3', 'landon donovan', '2001 - present', '281', '124'], ['4', 'ante razov', '1996 - 2009', '262', '114'], ['5', 'jason kreis', '1996 - 2007', '305', '108'], ['6', 'taylor twellman', '2002 - 2010', '174', '101'], ['7', 'dwayne de rosario', '2001 - current', '300', '100'], ['8', 'edson buddle', '2001 - 2010', '231', '90'], ['9', 'carlos ruiz', '2002 - 2008 , 2011', '169', '88'], ['10', 'roy lassiter', '1996 - 2002', '179', '88']] |
1972 - 73 new york rangers season | https://en.wikipedia.org/wiki/1972%E2%80%9373_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17324893-6.html.csv | aggregation | the average score per game for the rangers during the 72-73 season was 5 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '5', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 5 } = true', 'tointer': 'the average of the score record of all rows is 5 .'} | round_eq { avg { all_rows ; score } ; 5 } = true | the average of the score record of all rows is 5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '5_5': '5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '5_5': [1]} | ['game', 'february', 'opponent', 'score', 'record'] | [['52', '3', 'boston bruins', '7 - 3', '35 - 13 - 4'], ['53', '4', 'atlanta flames', '6 - 0', '36 - 13 - 4'], ['54', '7', 'new york islanders', '6 - 0', '37 - 13 - 4'], ['55', '10', 'new york islanders', '6 - 0', '38 - 13 - 4'], ['56', '11', 'montreal canadiens', '2 - 2', '38 - 13 - 5'], ['57', '14', 'montreal canadiens', '6 - 3', '38 - 14 - 5'], ['58', '15', 'buffalo sabres', '4 - 1', '38 - 15 - 5'], ['59', '18', 'new york islanders', '3 - 2', '39 - 15 - 5'], ['60', '21', 'los angeles kings', '4 - 3', '40 - 15 - 5'], ['61', '23', 'california golden seals', '5 - 3', '40 - 16 - 5'], ['62', '25', 'minnesota north stars', '6 - 5', '41 - 16 - 5'], ['63', '28', 'chicago black hawks', '3 - 3', '41 - 16 - 6']] |
1979 new york jets season | https://en.wikipedia.org/wiki/1979_New_York_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13834389-1.html.csv | count | eight of the games were held at the shea stadium . | {'scope': 'all', 'criterion': 'equal', 'value': 'shea stadium', 'result': '8', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'shea stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to shea stadium .', 'tostr': 'filter_eq { all_rows ; game site ; shea stadium }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; game site ; shea stadium } }', 'tointer': 'select the rows whose game site record fuzzily matches to shea stadium . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; game site ; shea stadium } } ; 8 } = true', 'tointer': 'select the rows whose game site record fuzzily matches to shea stadium . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; game site ; shea stadium } } ; 8 } = true | select the rows whose game site record fuzzily matches to shea stadium . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'shea stadium_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'shea stadium_6': 'shea stadium', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'shea stadium_6': [0], '8_7': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', '1979 - 09 - 02', 'cleveland browns', 'l 25 - 22 ( ot )', 'shea stadium', '48472'], ['2', '1979 - 09 - 09', 'new england patriots', 'l 56 - 3', 'schafer stadium', '53113'], ['3', '1979 - 09 - 16', 'detroit lions', 'w 31 - 10', 'shea stadium', '49612'], ['4', '1979 - 09 - 23', 'buffalo bills', 'l 46 - 31', 'rich stadium', '68731'], ['5', '1979 - 09 - 30', 'miami dolphins', 'w 33 - 27', 'shea stadium', '51496'], ['6', '1979 - 10 - 07', 'baltimore colts', 'l 10 - 8', 'memorial stadium', '32142'], ['7', '1979 - 10 - 15', 'minnesota vikings', 'w 14 - 7', 'shea stadium', '54479'], ['8', '1979 - 10 - 21', 'oakland raiders', 'w 28 - 19', 'shea stadium', '55802'], ['9', '1979 - 10 - 28', 'houston oilers', 'l 27 - 24 ( ot )', 'the astrodome', '45825'], ['10', '1979 - 11 - 04', 'green bay packers', 'w 27 - 22', 'lambeau field', '54201'], ['11', '1979 - 11 - 11', 'buffalo bills', 'l 14 - 12', 'shea stadium', '50647'], ['12', '1979 - 11 - 18', 'chicago bears', 'l 23 - 13', 'soldier field', '52635'], ['13', '1979 - 11 - 26', 'seattle seahawks', 'l 30 - 7', 'kingdome', '59977'], ['14', '1979 - 12 - 02', 'baltimore colts', 'w 30 - 17', 'shea stadium', '47744'], ['15', '1979 - 12 - 09', 'new england patriots', 'w 27 - 26', 'shea stadium', '45131'], ['16', '1979 - 12 - 15', 'miami dolphins', 'w 27 - 24', 'miami orange bowl', '49915']] |
alicia molik | https://en.wikipedia.org/wiki/Alicia_Molik | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1398079-6.html.csv | majority | alicia molik did not attend the majority of tennis grand slams in the year 2011 . | {'scope': 'all', 'col': '15', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'a', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', '2011', 'a'], 'result': True, 'ind': 0, 'tointer': 'for the 2011 records of all rows , most of them fuzzily match to a .', 'tostr': 'most_eq { all_rows ; 2011 ; a } = true'} | most_eq { all_rows ; 2011 ; a } = true | for the 2011 records of all rows , most of them fuzzily match to a . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, '2011_3': 3, 'a_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', '2011_3': '2011', 'a_4': 'a'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], '2011_3': [0], 'a_4': [0]} | ['tournament', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', 'career w / l'] | [['grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams', 'grand slams'], ['australian open', '1r', '1r', '2r', '2r', '3r', 'a', 'a', 'w', 'a', '1r', '3r', 'a', '1r', '2r', '13 - 9'], ['french open', 'a', '2r', '1r', '1r', '3r', 'qf', '1r', 'a', '1r', 'w', '1r', 'a', '1r', 'a', '12 - 9'], ['wimbledon', 'a', '3r', '3r', '1r', '1r', '2r', '2r', '1r', 'a', 'sf', '1r', 'a', '1r', 'a', '10 - 10'], ['us open', 'a', '2r', '1r', '3r', '1r', '1r', '1r', 'qf', 'a', '3r', 'a', '1r', '1r', 'a', '8 - 10'], ['grand slam win - loss', '0 - 1', '4 - 4', '3 - 4', '3 - 4', '4 - 4', '4 - 3', '1 - 3', '9 - 2', '0 - 1', '13 - 3', '2 - 2', '0 - 1', '0 - 4', '1 - 1', '43 - 38']] |
2008 masters tournament | https://en.wikipedia.org/wiki/2008_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12531523-5.html.csv | unique | in the 2008 masters tournament , only one player from united states scored less than 208 . | {'scope': 'subset', 'row': '2', 'col': '4', 'col_other': 'n/a', 'criterion': 'less_than', 'value': '208', '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 .'}, 'score', '208'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record is less than 208 .', 'tostr': 'filter_less { filter_eq { all_rows ; country ; united states } ; score ; 208 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_eq { all_rows ; country ; united states } ; score ; 208 } } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record is less than 208 . there is only one such row in the table .'} | only { filter_less { filter_eq { all_rows ; country ; united states } ; score ; 208 } } = true | select the rows whose country record fuzzily matches to united states . among these rows , select the rows whose score record is less than 208 . 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, 'score_7': 7, '208_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', 'score_7': 'score', '208_8': '208'} | {'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], 'score_7': [1], '208_8': [1]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'trevor immelman', 'south africa', '68 + 68 + 69 = 205', '- 11'], ['2', 'brandt snedeker', 'united states', '69 + 68 + 70 = 207', '- 9'], ['3', 'steve flesch', 'united states', '72 + 67 + 69 = 208', '- 8'], ['4', 'paul casey', 'england', '71 + 69 + 69 = 209', '- 7'], ['5', 'tiger woods', 'united states', '72 + 71 + 68 = 211', '- 5'], ['6', 'stewart cink', 'united states', '72 + 69 + 71 = 212', '- 4'], ['t7', 'retief goosen', 'south africa', '71 + 71 + 72 = 214', '- 2'], ['t7', 'pádraig harrington', 'ireland', '74 + 71 + 69 = 214', '- 2'], ['t7', 'zach johnson', 'united states', '70 + 76 + 68 = 214', '- 2'], ['t7', 'robert karlsson', 'sweden', '70 + 73 + 71 = 214', '- 2'], ['t7', 'phil mickelson', 'united states', '71 + 68 + 75 = 214', '- 2'], ['t7', "sean o'hair", 'united states', '72 + 71 + 71 = 214', '- 2'], ['t7', 'ian poulter', 'england', '70 + 69 + 75 = 214', '- 2'], ['t7', 'andrés romero', 'argentina', '72 + 72 + 70 = 214', '- 2'], ['t7', 'boo weekley', 'united states', '72 + 74 + 68 = 214', '- 2']] |
united states house of representatives elections , 2010 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2010 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19753079-12.html.csv | count | for the united states house of representatives election in 2010 , when the result was re-elected , two of the incumbents were from the democratic party . | {'scope': 'subset', 'criterion': 'equal', 'value': 'democratic', 'result': '2', 'col': '3', 'subset': {'col': '5', 'criterion': 'equal', 'value': 're - elected'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're - elected'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; re - elected }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected .'}, 'party', 'democratic'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { filter_eq { all_rows ; result ; re - elected } ; party ; democratic }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; party ; democratic } }', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose party record fuzzily matches to democratic . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; party ; democratic } } ; 2 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose party record fuzzily matches to democratic . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; result ; re - elected } ; party ; democratic } } ; 2 } = true | select the rows whose result record fuzzily matches to re - elected . among these rows , select the rows whose party record fuzzily matches to democratic . 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, 'result_6': 6, 're - elected_7': 7, 'party_8': 8, 'democratic_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', 'result_6': 'result', 're - elected_7': 're - elected', 'party_8': 'party', 'democratic_9': 'democratic', '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], 'result_6': [0], 're - elected_7': [0], 'party_8': [1], 'democratic_9': [1], '2_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['florida 4', 'ander crenshaw', 'republican', '2000', 're - elected', 'ander crenshaw ( r ) 77.2 % troy stanley ( i ) 22.8 %'], ['florida 5', 'ginny brown - waite', 'republican', '2002', 'retired republican hold', 'rich nugent ( r ) 67.4 % jim piccillo ( d ) 32.6 %'], ['florida 6', 'cliff stearns', 'republican', '1988', 're - elected', 'cliff stearns ( r ) 71.5 % steve schonberg ( i ) 28.5 %'], ['florida 7', 'john mica', 'republican', '1992', 're - elected', 'john mica ( r ) 69.0 % heather beaven ( d ) 31.0 %'], ['florida 9', 'gus bilirakis', 'republican', '2006', 're - elected', 'gus bilirakis ( r ) 71.4 % anita de palma ( d ) 28.6 %'], ['florida 10', 'bill young', 'republican', '1970', 're - elected', 'bill young ( r ) 65.9 % charlie justice ( d ) 34.1 %'], ['florida 11', 'kathy castor', 'democratic', '2006', 're - elected', 'kathy castor ( d ) 59.6 % mike prendergast ( r ) 40.4 %'], ['florida 13', 'vern buchanan', 'republican', '2006', 're - elected', 'vern buchanan ( r ) 68.9 % james golden ( d ) 31.1 %'], ['florida 15', 'bill posey', 'republican', '2008', 're - elected', 'bill posey ( r ) 64.7 % shannon roberts ( d ) 35.3 %'], ['florida 16', 'tom rooney', 'republican', '2008', 're - elected', 'tom rooney ( r ) 66.9 % jim horn ( d ) 33.1 %'], ['florida 19', 'ted deutch', 'democratic', '2010', 're - elected', 'ted deutch ( d ) 62.6 % joe budd ( r ) 37.3 %'], ['florida 21', 'lincoln diaz - balart', 'republican', '1992', 'retired republican hold', 'mario diaz - balart ( r ) unopposed'], ['florida 21', 'mario diaz - balart ( moved from 25th district )', 'republican', '2002', 're - elected', 'mario diaz - balart ( r ) unopposed'], ['florida 22', 'ron klein', 'democratic', '2006', 'lost re - election republican gain', 'allen west ( r ) 54.4 % ron klein ( d ) 45.6 %']] |
chan kin seng | https://en.wikipedia.org/wiki/Chan_Kin_Seng | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16752369-1.html.csv | ordinal | the 2012 philippine peace cup is the latest competition that chan kin seng participated in . | {'row': '17', 'col': '1', 'order': '17', 'col_other': '5', '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', '17'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 17 }'}, 'competition'], 'result': '2012 philippine peace cup', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 17 } ; competition }'}, '2012 philippine peace cup'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 17 } ; competition } ; 2012 philippine peace cup } = true', 'tointer': 'select the row whose date record of all rows is 17th minimum . the competition record of this row is 2012 philippine peace cup .'} | eq { hop { nth_argmin { all_rows ; date ; 17 } ; competition } ; 2012 philippine peace cup } = true | select the row whose date record of all rows is 17th minimum . the competition record of this row is 2012 philippine peace cup . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '17_6': 6, 'competition_7': 7, '2012 philippine peace cup_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', '17_6': '17', 'competition_7': 'competition', '2012 philippine peace cup_8': '2012 philippine peace cup'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '17_6': [0], 'competition_7': [1], '2012 philippine peace cup_8': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['6 april 2006', 'bangabandhu national stadium , dhaka', '1 - 1', '2 - 2', '2006 afc challenge cup'], ['6 april 2006', 'bangabandhu national stadium , dhaka', '2 - 2', '2 - 2', '2006 afc challenge cup'], ['10 june 2007', 'so kon po recreation groun , hong kong', '1 - 1', '1 - 2', '2007 hong kong - macau interport'], ['21 june 2007', 'macau stadium , tapai', '1 - 5', '1 - 7', '2008 east asian championship qualifier'], ['8 october 2007', 'suphachalasai stadium , bangkok', '1 - 2', '1 - 6', '2010 fifa world cup qualifier'], ['15 october 2007', 'macau stadium , taipa', '1 - 7', '1 - 7', '2010 fifa world cup qualifier'], ['24 may 2008', 'olympic stadium , phnom penh', '2 - 2', '2 - 3', '2008 afc challenge cup qualifier'], ['11 march 2009', 'leo palace resort soccer field , yona', '1 - 1', '6 - 1', '2008 east asian football championship qualifier'], ['11 march 2009', 'leo palace resort soccer field , yona', '2 - 1', '6 - 1', '2010 east asian football championship qualifier'], ['15 march 2009', 'leo palace resort soccer field , yona', '1 - 0', '2 - 2', '2010 east asian football championship qualifier'], ['15 march 2009', 'leo palace resort soccer field , yona', '2 - 1', '2 - 2', '2010 east asian football championship qualifier'], ['7 april 2009', 'macau stadium , taipa', '1 - 0', '2 - 0', '2010 afc challenge cup qualifier'], ['14 april 2009', 'mff football centre , ulan bator', '1 - 0', '1 - 3', '2010 afc challenge cup qualifier'], ['20 july 2012', 'leo palace resort soccer field , yona', '1 - 0', '5 - 1', '2012 eaff east asian cup qualifier'], ['20 july 2012', 'leo palace resort soccer field , yona', '4 - 1', '5 - 1', '2013 eaff east asian cup qualifier'], ['20 july 2012', 'leo palace resort soccer field , yona', '5 - 1', '5 - 1', '2013 eaff east asian cup qualifier'], ['25 september 2012', 'rizal memorial stadium , manila', '2 - 1', '2 - 2', '2012 philippine peace cup']] |
l'amour n'est rien | https://en.wikipedia.org/wiki/L%27amour_n%27est_rien... | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14773149-2.html.csv | superlative | the obsessed club mix is the longest audio version of the song l'amour n'est rien . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'length'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; length }'}, 'version'], 'result': 'obsessed club mix', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; length } ; version }'}, 'obsessed club mix'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; length } ; version } ; obsessed club mix } = true', 'tointer': 'select the row whose length record of all rows is maximum . the version record of this row is obsessed club mix .'} | eq { hop { argmax { all_rows ; length } ; version } ; obsessed club mix } = true | select the row whose length record of all rows is maximum . the version record of this row is obsessed club mix . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, 'version_6': 6, 'obsessed club mix_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'length_5': 'length', 'version_6': 'version', 'obsessed club mix_7': 'obsessed club mix'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], 'version_6': [1], 'obsessed club mix_7': [2]} | ['version', 'length', 'album', 'remixed by', 'year'] | [['single / album version', '5:03', "avant que l'ombre", '-', '2005'], ['radio edit', '3:40', '-', 'laurent boutonnat', '2006'], ['instrumental', '5:03', '-', 'laurent boutonnat', '2006'], ['the sexually no remix', '3:30', '-', 'the bionix', '2006'], ['obsessed club mix', '5:47', '-', 'fat phaze', '2006'], ['music video', '3:40', 'music videos iv', '-', '2006'], ['patrice strike & teo moss remix', '5:04', '-', 'patrice strike and teo moss', '2006'], ['live version ( recorded in 2006 )', '4:59 ( video ) 5:05 ( audio )', "avant que l'ombre à bercy", '-', '2006']] |
list of tvb series ( 2007 ) | https://en.wikipedia.org/wiki/List_of_TVB_series_%282007%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11173827-1.html.csv | superlative | the tvb series " heart of greed " had the largest peak rating at 48 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '3', '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', 'peak'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; peak }'}, 'english title'], 'result': 'heart of greed', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; peak } ; english title }'}, 'heart of greed'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; peak } ; english title } ; heart of greed } = true', 'tointer': 'select the row whose peak record of all rows is maximum . the english title record of this row is heart of greed .'} | eq { hop { argmax { all_rows ; peak } ; english title } ; heart of greed } = true | select the row whose peak record of all rows is maximum . the english title record of this row is heart of greed . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'peak_5': 5, 'english title_6': 6, 'heart of greed_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'peak_5': 'peak', 'english title_6': 'english title', 'heart of greed_7': 'heart of greed'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'peak_5': [0], 'english title_6': [1], 'heart of greed_7': [2]} | ['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers'] | [['1', 'the family link', '師奶兵團', '33', '42', '31', '33', '2.12 million'], ['2', 'fathers and sons', '爸爸閉翳', '32', '40', '31', '37', '2.11 million'], ['3', 'heart of greed', '溏心風暴', '32', '48', '29', '40', '2.08 million'], ['4', 'ten brothers', '十兄弟', '32', '39', '29', '36', '2.05 million'], ['5', 'on the first beat', '學警出更', '31', '38', '30', '35', '2.03 million'], ['6', 'the green grass of home', '緣來自有機', '31', '36', '29', '33', '2.01 million'], ['7', 'dicey business', '賭場風雲', '31', '37', '30', '34', '1.99 million'], ['8', 'steps', '舞動全城', '31', '36', '31', '32', '1.98 million'], ['9', 'the drive of life', '歲月風雲', '30', '39', '31', '33', '1.97 million']] |
tedd williams | https://en.wikipedia.org/wiki/Tedd_Williams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445700-2.html.csv | comparative | tedd williams won the fight against opponent bull shaw with a time of 20:00 , but he won the fight against opponent robert burnell in only 1:23 . | {'row_1': '4', 'row_2': '8', 'col': '7', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'bull shaw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to bull shaw .', 'tostr': 'filter_eq { all_rows ; opponent ; bull shaw }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; bull shaw } ; time }', 'tointer': 'select the rows whose opponent record fuzzily matches to bull shaw . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'robert burnell'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to robert burnell .', 'tostr': 'filter_eq { all_rows ; opponent ; robert burnell }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; robert burnell } ; time }', 'tointer': 'select the rows whose opponent record fuzzily matches to robert burnell . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; bull shaw } ; time } ; hop { filter_eq { all_rows ; opponent ; robert burnell } ; time } }', 'tointer': 'select the rows whose opponent record fuzzily matches to bull shaw . take the time record of this row . select the rows whose opponent record fuzzily matches to robert burnell . take the time record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'bull shaw'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to bull shaw .', 'tostr': 'filter_eq { all_rows ; opponent ; bull shaw }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; bull shaw } ; time }', 'tointer': 'select the rows whose opponent record fuzzily matches to bull shaw . take the time record of this row .'}, '20:00'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; bull shaw } ; time } ; 20:00 }', 'tointer': 'the time record of the first row is 20:00 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'robert burnell'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to robert burnell .', 'tostr': 'filter_eq { all_rows ; opponent ; robert burnell }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; robert burnell } ; time }', 'tointer': 'select the rows whose opponent record fuzzily matches to robert burnell . take the time record of this row .'}, '1:23'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; opponent ; robert burnell } ; time } ; 1:23 }', 'tointer': 'the time record of the second row is 1:23 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; opponent ; bull shaw } ; time } ; 20:00 } ; eq { hop { filter_eq { all_rows ; opponent ; robert burnell } ; time } ; 1:23 } }', 'tointer': 'the time record of the first row is 20:00 . the time record of the second row is 1:23 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; opponent ; bull shaw } ; time } ; hop { filter_eq { all_rows ; opponent ; robert burnell } ; time } } ; and { eq { hop { filter_eq { all_rows ; opponent ; bull shaw } ; time } ; 20:00 } ; eq { hop { filter_eq { all_rows ; opponent ; robert burnell } ; time } ; 1:23 } } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to bull shaw . take the time record of this row . select the rows whose opponent record fuzzily matches to robert burnell . take the time record of this row . the first record is greater than the second record . the time record of the first row is 20:00 . the time record of the second row is 1:23 .'} | and { greater { hop { filter_eq { all_rows ; opponent ; bull shaw } ; time } ; hop { filter_eq { all_rows ; opponent ; robert burnell } ; time } } ; and { eq { hop { filter_eq { all_rows ; opponent ; bull shaw } ; time } ; 20:00 } ; eq { hop { filter_eq { all_rows ; opponent ; robert burnell } ; time } ; 1:23 } } } = true | select the rows whose opponent record fuzzily matches to bull shaw . take the time record of this row . select the rows whose opponent record fuzzily matches to robert burnell . take the time record of this row . the first record is greater than the second record . the time record of the first row is 20:00 . the time record of the second row is 1:23 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'opponent_11': 11, 'bull shaw_12': 12, 'time_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'opponent_15': 15, 'robert burnell_16': 16, 'time_17': 17, 'and_7': 7, 'str_eq_5': 5, '20:00_18': 18, 'str_eq_6': 6, '1:23_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'bull shaw_12': 'bull shaw', 'time_13': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'opponent_15': 'opponent', 'robert burnell_16': 'robert burnell', 'time_17': 'time', 'and_7': 'and', 'str_eq_5': 'str_eq', '20:00_18': '20:00', 'str_eq_6': 'str_eq', '1:23_19': '1:23'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'opponent_11': [0], 'bull shaw_12': [0], 'time_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'opponent_15': [1], 'robert burnell_16': [1], 'time_17': [3], 'and_7': [8], 'str_eq_5': [7], '20:00_18': [5], 'str_eq_6': [7], '1:23_19': [6]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time'] | [['loss', '7 - 1', 'ian freeman', 'decision', 'ufc 27', '3', '5:00'], ['win', '7 - 0', 'bill parker', 'submission ( armlock )', 'kotc 4 - gladiators', '1', '0:32'], ['win', '6 - 0', 'steve judson', 'ko', 'ufc 24', '1', '3:23'], ['win', '5 - 0', 'bull shaw', 'decision', 'hfp - holiday fight party', '1', '20:00'], ['win', '4 - 0', 'joe campanella', 'submission ( keylock )', 'wef 7 - stomp in the swamp', '1', '1:48'], ['win', '3 - 0', 'travis fulton', 'decision ( unanimous )', 'li - lionheart invitational', '1', '20:00'], ['win', '2 - 0', 'joseph marquez', 'submission ( palm strikes )', 'bri 3 - bas rutten invitational 3', '1', '1:50'], ['win', '1 - 0', 'robert burnell', 'submission', 'esf - empire one', '1', '1:23']] |
2009 - 10 new york knicks season | https://en.wikipedia.org/wiki/2009%E2%80%9310_New_York_Knicks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23248869-6.html.csv | count | al harrington had four high points performances for the new york knicks . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'al harrington', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high points', 'al harrington'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high points record fuzzily matches to al harrington .', 'tostr': 'filter_eq { all_rows ; high points ; al harrington }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; high points ; al harrington } }', 'tointer': 'select the rows whose high points record fuzzily matches to al harrington . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; high points ; al harrington } } ; 4 } = true', 'tointer': 'select the rows whose high points record fuzzily matches to al harrington . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; high points ; al harrington } } ; 4 } = true | select the rows whose high points record fuzzily matches to al harrington . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high points_5': 5, 'al harrington_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high points_5': 'high points', 'al harrington_6': 'al harrington', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high points_5': [0], 'al harrington_6': [0], '4_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['18', 'december 1', 'phoenix', 'w 126 - 99 ( ot )', 'danilo gallinari ( 27 )', 'danilo gallinari ( 10 )', 'larry hughes ( 12 )', 'madison square garden 19763', '4 - 14'], ['19', 'december 2', 'orlando', 'l 104 - 118 ( ot )', 'wilson chandler ( 24 )', 'danilo gallinari ( 7 )', 'danilo gallinari , larry hughes ( 3 )', 'amway arena 17461', '4 - 15'], ['20', 'december 4', 'atlanta', 'w 114 - 107 ( ot )', 'al harrington ( 27 )', 'david lee ( 17 )', 'chris duhon ( 10 )', 'philips arena 17165', '5 - 15'], ['21', 'december 6', 'new jersey', 'w 106 - 97 ( ot )', 'al harrington ( 26 )', 'al harrington ( 14 )', 'al harrington , chris duhon ( 5 )', 'madison square garden 19602', '6 - 15'], ['22', 'december 7', 'portland', 'w 93 - 84 ( ot )', 'larry hughes ( 21 )', 'david lee ( 10 )', 'chris duhon ( 9 )', 'madison square garden 19763', '7 - 15'], ['23', 'december 11', 'new orleans', 'w 113 - 96 ( ot )', 'al harrington ( 28 )', 'david lee ( 14 )', 'chris duhon ( 9 )', 'new orleans arena 15569', '8 - 15'], ['24', 'december 15', 'charlotte', 'l 87 - 94 ( ot )', 'chris duhon ( 18 )', 'david lee ( 8 )', 'chris duhon ( 6 )', 'time warner cable arena 13606', '8 - 16'], ['26', 'december 18', 'la clippers', 'w 95 - 91 ( ot )', 'david lee ( 25 )', 'david lee ( 11 )', 'chris duhon ( 10 )', 'madison square garden 19763', '9 - 17'], ['27', 'december 20', 'charlotte', 'w 98 - 94 ( ot )', 'wilson chandler ( 26 )', 'david lee ( 15 )', 'david lee ( 7 )', 'madison square garden 18767', '10 - 17'], ['28', 'december 22', 'chicago', 'w 88 - 81 ( ot )', 'al harrington ( 20 )', 'david lee ( 21 )', 'david lee ( 5 )', 'madison square garden 19763', '11 - 17'], ['29', 'december 25', 'miami', 'l 87 - 93 ( ot )', 'danilo gallinari ( 26 )', 'david lee ( 16 )', 'danilo gallinari , chris duhon ( 3 )', 'madison square garden 19763', '11 - 18'], ['30', 'december 27', 'san antonio', 'l 88 - 95 ( ot )', 'david lee ( 28 )', 'david lee ( 10 )', 'chris duhon ( 13 )', 'madison square garden 19763', '11 - 19'], ['31', 'december 29', 'detroit', 'w 104 - 87 ( ot )', 'david lee ( 30 )', 'david lee ( 12 )', 'chris duhon ( 7 )', 'the palace of auburn hills 22076', '12 - 19']] |
northern province , sri lanka | https://en.wikipedia.org/wiki/Northern_Province%2C_Sri_Lanka | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23777640-1.html.csv | comparative | in northern province , sri lanka , the administrative district of mullaitivu has a greater land area than the district of mannar . | {'row_1': '4', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'administrative district', 'mullaitivu'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose administrative district record fuzzily matches to mullaitivu .', 'tostr': 'filter_eq { all_rows ; administrative district ; mullaitivu }'}, 'land area ( km 2 )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; administrative district ; mullaitivu } ; land area ( km 2 ) }', 'tointer': 'select the rows whose administrative district record fuzzily matches to mullaitivu . take the land area ( km 2 ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'administrative district', 'mannar'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose administrative district record fuzzily matches to mannar .', 'tostr': 'filter_eq { all_rows ; administrative district ; mannar }'}, 'land area ( km 2 )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; administrative district ; mannar } ; land area ( km 2 ) }', 'tointer': 'select the rows whose administrative district record fuzzily matches to mannar . take the land area ( km 2 ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; administrative district ; mullaitivu } ; land area ( km 2 ) } ; hop { filter_eq { all_rows ; administrative district ; mannar } ; land area ( km 2 ) } } = true', 'tointer': 'select the rows whose administrative district record fuzzily matches to mullaitivu . take the land area ( km 2 ) record of this row . select the rows whose administrative district record fuzzily matches to mannar . take the land area ( km 2 ) record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; administrative district ; mullaitivu } ; land area ( km 2 ) } ; hop { filter_eq { all_rows ; administrative district ; mannar } ; land area ( km 2 ) } } = true | select the rows whose administrative district record fuzzily matches to mullaitivu . take the land area ( km 2 ) record of this row . select the rows whose administrative district record fuzzily matches to mannar . take the land area ( km 2 ) 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, 'administrative district_7': 7, 'mullaitivu_8': 8, 'land area (km 2 )_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'administrative district_11': 11, 'mannar_12': 12, 'land area (km 2 )_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', 'administrative district_7': 'administrative district', 'mullaitivu_8': 'mullaitivu', 'land area (km 2 )_9': 'land area ( km 2 )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'administrative district_11': 'administrative district', 'mannar_12': 'mannar', 'land area (km 2 )_13': 'land area ( km 2 )'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'administrative district_7': [0], 'mullaitivu_8': [0], 'land area (km 2 )_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'administrative district_11': [1], 'mannar_12': [1], 'land area (km 2 )_13': [3]} | ['administrative district', 'ds divisions', 'gn divisions', 'total area ( km 2 )', 'land area ( km 2 )', 'sri lankan tamil', 'sri lankan moors', 'sinhalese', 'indian tamil', 'other', 'total', 'population density ( / km 2 )'] | [['jaffna', '15', '435', '1025', '929', '577246', '2139', '3366', '499', '128', '583378', '569'], ['kilinochchi', '4', '95', '1279', '1205', '109528', '678', '962', '1682', '25', '112875', '88'], ['mannar', '5', '153', '1996', '1880', '80568', '16087', '1961', '394', '41', '99051', '50'], ['mullaitivu', '5', '127', '2617', '2415', '79081', '1760', '8851', '2182', '73', '91947', '35'], ['vavuniya', '4', '102', '1967', '1861', '141269', '11700', '17191', '1292', '59', '171511', '87']] |
grey 's anatomy ( season 4 ) | https://en.wikipedia.org/wiki/Grey%27s_Anatomy_%28season_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11058032-1.html.csv | superlative | the first episode in the season four series of grey 's anatomy had the highest number of viewers for that season . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( millions ) }'}, 'no in season'], 'result': '1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( millions ) } ; no in season }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( millions ) } ; no in season } ; 1 } = true', 'tointer': 'select the row whose us viewers ( millions ) record of all rows is maximum . the no in season record of this row is 1 .'} | eq { hop { argmax { all_rows ; us viewers ( millions ) } ; no in season } ; 1 } = true | select the row whose us viewers ( millions ) record of all rows is maximum . the no in season record of this row is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, 'no in season_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (millions)_5': 'us viewers ( millions )', 'no in season_6': 'no in season', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], 'no in season_6': [1], '1_7': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['62', '1', 'a change is gon na come', 'rob corn', 'shonda rhimes', 'september 27 , 2007', '20.93'], ['63', '2', 'love / addiction', 'james frawley', 'debora cahn', 'october 4 , 2007', '18.51'], ['64', '3', 'let the truth sting', 'dan minahan', 'mark wilding', 'october 11 , 2007', '19.04'], ['65', '4', 'the heart of the matter', 'randy zisk', 'allan heinberg', 'october 18 , 2007', '18.04'], ['66', '5', 'haunt you every day', 'bethany rooney', 'krista vernoff', 'october 25 , 2007', '18.17'], ['67', '6', 'kung fu fighting', 'tom verica', 'stacy mckee', 'november 1 , 2007', '19.31'], ['68', '7', 'physical attraction , chemical reaction', 'jeff melman', 'tony phelan & joan rater', 'november 8 , 2007', '19.50'], ['69', '8', 'forever young', 'rob corn', 'mark wilding', 'november 15 , 2007', '19.61'], ['70', '9', 'crash into me ( part 1 )', 'michael grossman', 'shonda rhimes & krista vernoff', 'november 22 , 2007', '14.11'], ['71', '10', 'crash into me ( part 2 )', 'jessica yu', 'shonda rhimes & krista vernoff', 'december 6 , 2007', '17.78'], ['72', '11', 'lay your hands on me', 'john terlesky', 'allan heinberg', 'january 10 , 2008', '17.68'], ['73', '12', 'where the wild things are', 'rob corn', 'zoanne clack', 'april 24 , 2008', '16.37'], ['74', '13', 'piece of my heart', 'mark tinker', 'stacy mckee', 'may 1 , 2008', '15.31'], ['75', '14', 'the becoming', 'julie anne robinson', 'tony phelan & joan rater', 'may 8 , 2008', '16.03'], ['76', '15', 'losing my mind', 'james frawley', 'debora cahn', 'may 15 , 2008', '15.55'], ['77', '16', 'freedom ( part 1 )', 'rob corn', 'shonda rhimes', 'may 22 , 2008', '18.09']] |
list of major league baseball home run records | https://en.wikipedia.org/wiki/List_of_Major_League_Baseball_home_run_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13669614-14.html.csv | ordinal | the arizona diamondbacks major league baseball home run record was in the second earliest inning . | {'row': '7', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'inn', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; inn ; 2 }'}, 'team'], 'result': 'arizona diamondbacks', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; inn ; 2 } ; team }'}, 'arizona diamondbacks'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; inn ; 2 } ; team } ; arizona diamondbacks } = true', 'tointer': 'select the row whose inn record of all rows is 2nd minimum . the team record of this row is arizona diamondbacks .'} | eq { hop { nth_argmin { all_rows ; inn ; 2 } ; team } ; arizona diamondbacks } = true | select the row whose inn record of all rows is 2nd minimum . the team record of this row is arizona diamondbacks . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'inn_5': 5, '2_6': 6, 'team_7': 7, 'arizona diamondbacks_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', 'inn_5': 'inn', '2_6': '2', 'team_7': 'team', 'arizona diamondbacks_8': 'arizona diamondbacks'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'inn_5': [0], '2_6': [0], 'team_7': [1], 'arizona diamondbacks_8': [2]} | ['team', 'date', 'opponent', 'pitcher', 'inn', 'venue'] | [['milwaukee braves', 'june 8 , 1961', 'cincinnati reds', 'jim maloney ( 2 ) marshall bridges', '7th', 'crosley field'], ['cleveland indians', 'july 31 , 1963', 'los angeles angels', 'paul foytack', '6th', 'cleveland stadium'], ['minnesota twins', 'may 2 , 1964', 'kansas city athletics', 'dan pfister ( 3 ) vern handrahan', '11th', 'municipal stadium'], ['los angeles dodgers', 'september 18 , 2006', 'san diego padres', 'jon adkins ( 2 ) trevor hoffman', '9th', 'dodger stadium'], ['boston red sox', 'april 22 , 2007', 'new york yankees', 'chase wright', '3rd', 'fenway park'], ['chicago white sox', 'august 14 , 2008', 'kansas city royals', 'joel peralta ( 3 ) robinson tejeda', '6th', 'us cellular field'], ['arizona diamondbacks', 'august 11 , 2010', 'milwaukee brewers', 'dave bush', '4th', 'miller park']] |
real salt lake | https://en.wikipedia.org/wiki/Real_Salt_Lake | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1053453-8.html.csv | ordinal | kyle beckerman is the real salt lake player with the third most caps . | {'row': '3', 'col': '4', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'caps', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; caps ; 3 }'}, 'player'], 'result': 'kyle beckerman', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; caps ; 3 } ; player }'}, 'kyle beckerman'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; caps ; 3 } ; player } ; kyle beckerman } = true', 'tointer': 'select the row whose caps record of all rows is 3rd maximum . the player record of this row is kyle beckerman .'} | eq { hop { nth_argmax { all_rows ; caps ; 3 } ; player } ; kyle beckerman } = true | select the row whose caps record of all rows is 3rd maximum . the player record of this row is kyle beckerman . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'caps_5': 5, '3_6': 6, 'player_7': 7, 'kyle beckerman_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', 'caps_5': 'caps', '3_6': '3', 'player_7': 'player', 'kyle beckerman_8': 'kyle beckerman'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'caps_5': [0], '3_6': [0], 'player_7': [1], 'kyle beckerman_8': [2]} | ['rank', 'player', 'nation', 'caps', 'goals', 'years'] | [['1', 'nick rimando', 'usa', '201', '0', '2007 - present'], ['2', 'andy williams', 'jam', '189', '14', '2005 - 2011'], ['3', 'kyle beckerman', 'usa', '177', '21', '2007 - present'], ['4', 'chris wingert', 'usa', '174', '1', '2007 - present'], ['5', 'nat borchers', 'usa', '173', '9', '2008 - present'], ['6', 'javier morales', 'arg', '155', '28', '2007 - present'], ['7', 'tony beltran', 'usa', '135', '0', '2008 - present'], ['8', 'ned grabavoy', 'usa', '126', '8', '2009 - present'], ['9', 'fabián espíndola', 'arg', '125', '35', '2007 - 2012'], ['10', 'robbie findley', 'usa', '121', '35', '2007 - 2010 , 2013 - present']] |
1951 vfl season | https://en.wikipedia.org/wiki/1951_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10701914-8.html.csv | count | all 6 games took place on the same date . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '16 june 1951', 'result': '6', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '16 june 1951'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 16 june 1951 .', 'tostr': 'filter_eq { all_rows ; date ; 16 june 1951 }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; 16 june 1951 } }', 'tointer': 'select the rows whose date record fuzzily matches to 16 june 1951 . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; 16 june 1951 } } ; 6 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 16 june 1951 . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; date ; 16 june 1951 } } ; 6 } = true | select the rows whose date record fuzzily matches to 16 june 1951 . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '16 june 1951_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '16 june 1951_6': '16 june 1951', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '16 june 1951_6': [0], '6_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '9.5 ( 59 )', 'geelong', '11.11 ( 77 )', 'western oval', '19500', '16 june 1951'], ['essendon', '15.13 ( 103 )', 'st kilda', '12.7 ( 79 )', 'windy hill', '15000', '16 june 1951'], ['carlton', '7.11 ( 53 )', 'collingwood', '9.13 ( 67 )', 'princes park', '31000', '16 june 1951'], ['north melbourne', '14.9 ( 93 )', 'melbourne', '6.12 ( 48 )', 'arden street oval', '13000', '16 june 1951'], ['south melbourne', '12.14 ( 86 )', 'hawthorn', '7.11 ( 53 )', 'lake oval', '8500', '16 june 1951'], ['richmond', '9.12 ( 66 )', 'fitzroy', '12.16 ( 88 )', 'punt road oval', '26000', '16 june 1951']] |
1937 vfl season | https://en.wikipedia.org/wiki/1937_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806194-10.html.csv | aggregation | in the 1937 vfl season , for games where the away team has melbourne in their name , the total crowd was 25000 . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '25000', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'melbourne'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'melbourne'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; away team ; melbourne }', 'tointer': 'select the rows whose away team record fuzzily matches to melbourne .'}, 'crowd'], 'result': '25000', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; away team ; melbourne } ; crowd }'}, '25000'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; away team ; melbourne } ; crowd } ; 25000 } = true', 'tointer': 'select the rows whose away team record fuzzily matches to melbourne . the sum of the crowd record of these rows is 25000 .'} | round_eq { sum { filter_eq { all_rows ; away team ; melbourne } ; crowd } ; 25000 } = true | select the rows whose away team record fuzzily matches to melbourne . the sum of the crowd record of these rows is 25000 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'away team_5': 5, 'melbourne_6': 6, 'crowd_7': 7, '25000_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'away team_5': 'away team', 'melbourne_6': 'melbourne', 'crowd_7': 'crowd', '25000_8': '25000'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'away team_5': [0], 'melbourne_6': [0], 'crowd_7': [1], '25000_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '18.16 ( 124 )', 'north melbourne', '4.14 ( 38 )', 'corio oval', '9000', '26 june 1937'], ['fitzroy', '7.8 ( 50 )', 'melbourne', '11.23 ( 89 )', 'brunswick street oval', '16000', '26 june 1937'], ['south melbourne', '14.18 ( 102 )', 'st kilda', '8.12 ( 60 )', 'lake oval', '22000', '26 june 1937'], ['hawthorn', '15.16 ( 106 )', 'footscray', '14.15 ( 99 )', 'glenferrie oval', '7500', '26 june 1937'], ['richmond', '12.8 ( 80 )', 'collingwood', '14.9 ( 93 )', 'punt road oval', '22000', '26 june 1937'], ['essendon', '13.18 ( 96 )', 'carlton', '15.18 ( 108 )', 'windy hill', '14000', '26 june 1937']] |
ethan juan | https://en.wikipedia.org/wiki/Ethan_Juan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10314814-1.html.csv | count | ethan juan had a 2nd male lead role in two different television series . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2nd male lead', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'role', '2nd male lead'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose role record fuzzily matches to 2nd male lead .', 'tostr': 'filter_eq { all_rows ; role ; 2nd male lead }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; role ; 2nd male lead } }', 'tointer': 'select the rows whose role record fuzzily matches to 2nd male lead . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; role ; 2nd male lead } } ; 2 } = true', 'tointer': 'select the rows whose role record fuzzily matches to 2nd male lead . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; role ; 2nd male lead } } ; 2 } = true | select the rows whose role record fuzzily matches to 2nd male lead . 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, 'role_5': 5, '2nd male lead_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', 'role_5': 'role', '2nd male lead_6': '2nd male lead', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'role_5': [0], '2nd male lead_6': [0], '2_7': [2]} | ['year', 'chinese title', 'english title', 'role', 'character'] | [['2004', '米迦勒之舞', "michael the archangel 's dance", 'supporting', 'ghost'], ['2005', '綠光森林', 'green forest , my home', '2nd male lead', 'owen ( 靳歐文 )'], ['2006', '花樣少年少女', 'hanazakarino kimitachihe', 'supporting', 'shen le ( 申樂 )'], ['2007', '熱情仲夏', 'summer x summer', 'supporting', 'qiao shan ( 周喬杉 )'], ['2007', '我在墾丁天氣晴', 'wayward kenting', '2nd male lead', 'shao nan ( 郭紹南 )'], ['2008', '命中注定我愛你', 'fated to love you', 'male lead', 'ji cun xi ( 紀存希 )'], ['2008', '無敵珊寶妹', 'invincible shan bao mei', 'cameo', 'ji cun xi ( 紀存希 )'], ['2009', '敗犬女王', 'my queen', 'male lead', 'lucas ( 盧卡斯 )']] |
2007 - 08 atlanta hawks season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11961582-10.html.csv | count | five of the games took place in the month of april . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'april', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'april'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to april .', 'tostr': 'filter_eq { all_rows ; date ; april }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; april } }', 'tointer': 'select the rows whose date record fuzzily matches to april . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; april } } ; 5 } = true', 'tointer': 'select the rows whose date record fuzzily matches to april . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; date ; april } } ; 5 } = true | select the rows whose date record fuzzily matches to april . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'april_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'april_6': 'april', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'april_6': [0], '5_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 20', 'boston', '81 - 104', 'a horford ( 20 )', 'a horford ( 10 )', 'j johnson ( 7 )', 'td banknorth garden 18624', '0 - 1'], ['2', 'april 23', 'boston', '77 - 96', 'two - way tie ( 13 )', 'a horford ( 9 )', 'two - way tie ( 3 )', 'td banknorth garden 18624', '0 - 2'], ['3', 'april 26', 'boston', '102 - 93', 'j smith ( 27 )', 'a horford ( 10 )', 'm bibby ( 8 )', 'philips arena 19725', '1 - 2'], ['4', 'april 28', 'boston', '97 - 92', 'j johnson ( 35 )', 'a horford ( 13 )', 'j johnson ( 6 )', 'philips arena 20016', '2 - 2'], ['5', 'april 30', 'boston', '85 - 110', 'j johnson ( 21 )', 'a horford ( 10 )', 'a horford ( 5 )', 'td banknorth garden 18624', '2 - 3'], ['6', 'may 2', 'boston', '103 - 100', 'm williams ( 18 )', 'four - way tie ( 6 )', 'm bibby ( 7 )', 'philips arena 20425', '3 - 3'], ['7', 'may 4', 'boston', '99 - 65', 'j johnson ( 16 )', 'a horford ( 12 )', 'a horford ( 3 )', 'td banknorth garden 18624', '3 - 4']] |
alto de l'angliru | https://en.wikipedia.org/wiki/Alto_de_L%27Angliru | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1756060-2.html.csv | unique | the only person who has ever ascended alto de l'angliru at a speed faster than 18 km/hour was roberto heras . | {'scope': 'all', 'row': '1', 'col': '4', 'col_other': '5', 'criterion': 'greater_than', 'value': '18.00 km/h', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'speed', '18.00 km/h'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose speed record is greater than 18.00 km/h .', 'tostr': 'filter_greater { all_rows ; speed ; 18.00 km/h }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; speed ; 18.00 km/h } }', 'tointer': 'select the rows whose speed record is greater than 18.00 km/h . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'speed', '18.00 km/h'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose speed record is greater than 18.00 km/h .', 'tostr': 'filter_greater { all_rows ; speed ; 18.00 km/h }'}, 'rider'], 'result': 'roberto heras ( esp )', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; speed ; 18.00 km/h } ; rider }'}, 'roberto heras ( esp )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; speed ; 18.00 km/h } ; rider } ; roberto heras ( esp ) }', 'tointer': 'the rider record of this unqiue row is roberto heras ( esp ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; speed ; 18.00 km/h } } ; eq { hop { filter_greater { all_rows ; speed ; 18.00 km/h } ; rider } ; roberto heras ( esp ) } } = true', 'tointer': 'select the rows whose speed record is greater than 18.00 km/h . there is only one such row in the table . the rider record of this unqiue row is roberto heras ( esp ) .'} | and { only { filter_greater { all_rows ; speed ; 18.00 km/h } } ; eq { hop { filter_greater { all_rows ; speed ; 18.00 km/h } ; rider } ; roberto heras ( esp ) } } = true | select the rows whose speed record is greater than 18.00 km/h . there is only one such row in the table . the rider record of this unqiue row is roberto heras ( esp ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'speed_7': 7, '18.00 km/h_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'rider_9': 9, 'roberto heras ( esp )_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'speed_7': 'speed', '18.00 km/h_8': '18.00 km/h', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'rider_9': 'rider', 'roberto heras ( esp )_10': 'roberto heras ( esp )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'speed_7': [0], '18.00 km/h_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'rider_9': [2], 'roberto heras ( esp )_10': [3]} | ['rank', 'year', 'ascent time', 'speed', 'rider'] | [['1', '2000', '41:55', '18.32 km / h', 'roberto heras ( esp )'], ['2', '2013', '43:07', '17.81 km / h', 'chris horner ( usa )'], ['3', '2008', '43:12', '17.78 km / h', 'alberto contador ( esp )'], ['4', '2000', '43:24', '17.70 km / h', 'pavel tonkov ( rus )'], ['5', '2000', '43:24', '17.70 km / h', 'roberto laiseka ( esp )'], ['6', '2013', '43:35', '17.62 km / h', 'alejandro valverde ( esp )'], ['7', '2013', '43:35', '17.62 km / h', 'vincenzo nibali ( ita )'], ['8', '2008', '43:54', '17.49 km / h', 'alejandro valverde ( esp )'], ['9', '2002', '43:55', '17.49 km / h', 'roberto heras ( esp )'], ['10', '2011', '43:57', '17.47 km / h', 'juan jose cobo ( esp )'], ['11', '2008', '44:10', '17.39 km / h', 'joaquim rodriguez ( esp )'], ['12', '2000', '44:13', '17.37 km / h', 'raimondas rumå ¡ as ( lit )'], ['13', '2008', '44:17', '17.34 km / h', 'levi leipheimer ( usa )']] |
rousimar palhares | https://en.wikipedia.org/wiki/Rousimar_Palhares | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17440284-2.html.csv | unique | the match against helio dipp was the only one won by a rear naked choke . | {'scope': 'all', 'row': '16', 'col': '4', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': 'rear naked choke', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'rear naked choke'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to rear naked choke .', 'tostr': 'filter_eq { all_rows ; method ; rear naked choke }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; method ; rear naked choke } }', 'tointer': 'select the rows whose method record fuzzily matches to rear naked choke . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'rear naked choke'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to rear naked choke .', 'tostr': 'filter_eq { all_rows ; method ; rear naked choke }'}, 'opponent'], 'result': 'helio dipp', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; method ; rear naked choke } ; opponent }'}, 'helio dipp'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; method ; rear naked choke } ; opponent } ; helio dipp }', 'tointer': 'the opponent record of this unqiue row is helio dipp .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; method ; rear naked choke } } ; eq { hop { filter_eq { all_rows ; method ; rear naked choke } ; opponent } ; helio dipp } } = true', 'tointer': 'select the rows whose method record fuzzily matches to rear naked choke . there is only one such row in the table . the opponent record of this unqiue row is helio dipp .'} | and { only { filter_eq { all_rows ; method ; rear naked choke } } ; eq { hop { filter_eq { all_rows ; method ; rear naked choke } ; opponent } ; helio dipp } } = true | select the rows whose method record fuzzily matches to rear naked choke . there is only one such row in the table . the opponent record of this unqiue row is helio dipp . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'method_7': 7, 'rear naked choke_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opponent_9': 9, 'helio dipp_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'method_7': 'method', 'rear naked choke_8': 'rear naked choke', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opponent_9': 'opponent', 'helio dipp_10': 'helio dipp'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'method_7': [0], 'rear naked choke_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opponent_9': [2], 'helio dipp_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['win', '15 - 5', 'mike pierce', 'submission ( heel hook )', 'ufc fight night : maia vs shields', '1', '0:31', 'barueri , são paulo , brazil'], ['loss', '14 - 5', 'hector lombard', 'ko ( punches )', 'ufc on fx : sotiropoulos vs pearson', '1', '3:38', 'gold coast , queensland , australia'], ['loss', '14 - 4', 'alan belcher', 'tko ( punches & elbows )', 'ufc on fox : diaz vs miller', '1', '4:18', 'east rutherford , new jersey , united states'], ['win', '14 - 3', 'mike massenzio', 'submission ( heel hook )', 'ufc 142', '1', '1:03', 'rio de janeiro , rio de janeiro , brazil'], ['win', '13 - 3', 'dan miller', 'decision ( unanimous )', 'ufc 134', '3', '5:00', 'rio de janeiro , rio de janeiro , brazil'], ['win', '12 - 3', 'david branch', 'submission ( kneebar )', 'ufc live : sanchez vs kampmann', '2', '1:44', 'louisville , kentucky , united states'], ['loss', '11 - 3', 'nate marquardt', 'tko ( punches )', 'ufc fight night : marquardt vs palhares', '1', '3:28', 'austin , texas , united states'], ['win', '11 - 2', 'tomasz drwal', 'submission ( heel hook )', 'ufc 111', '1', '0:45', 'newark , new jersey , united states'], ['win', '10 - 2', 'lucio linhares', 'submission ( heel hook )', 'ufc 107', '2', '3:21', 'memphis , tennessee , united states'], ['win', '9 - 2', 'jeremy horn', 'decision ( unanimous )', 'ufc 93', '3', '5:00', 'dublin , ireland'], ['loss', '8 - 2', 'dan henderson', 'decision ( unanimous )', 'ufc 88', '3', '5:00', 'atlanta , georgia , united states'], ['win', '8 - 1', 'ivan salaverry', 'submission ( armbar )', 'ufc 84', '1', '2:36', 'las vegas , nevada , united states'], ['win', '7 - 1', 'daniel acacio', 'submission ( heel hook )', 'fury fc 5 : final conflict', '1', '1:22', 'são paulo , brazil'], ['win', '6 - 1', 'fabio nascimento', 'submission ( heel hook )', 'fury fc 5 : final conflict', '1', '2:45', 'são paulo , brazil'], ['win', '5 - 1', 'flavio luiz moura', 'submission ( heel hook )', 'fury fc 4 : high voltage', '1', '1:21', 'teresopolis , brazil'], ['win', '4 - 1', 'helio dipp', 'submission ( rear naked choke )', 'floripa fight 3', '1', '1:40', 'florianópolis , brazil'], ['win', '3 - 1', 'claudio mattos', 'tko ( injury )', 'storm samurai 12', '1', '4:58', 'curitiba , brazil'], ['loss', '2 - 1', 'arthur cesar jacintho', 'decision ( split )', 'rio mma challenger 2', '3', '5:00', 'rio de janeiro , brazil'], ['win', '2 - 0', 'renan moraes', 'submission ( armbar )', 'gold fighters championship 1', '1', 'n / a', 'rio de janeiro , brazil'], ['win', '1 - 0', 'bruno bastos', 'decision ( split )', 'floripa fight 2', '3', '5:00', 'florianópolis , brazil']] |
eddie sachs | https://en.wikipedia.org/wiki/Eddie_Sachs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252072-1.html.csv | unique | 1964 was the only year when eddie sachs finished only a single lap and finished 30th . | {'scope': 'all', 'row': '8', 'col': '6', 'col_other': '1,5', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; laps ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; laps ; 1 } }', 'tointer': 'select the rows whose laps record is equal to 1 . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; laps ; 1 }'}, 'year'], 'result': '1964', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; laps ; 1 } ; year }'}, '1964'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; laps ; 1 } ; year } ; 1964 }', 'tointer': 'the year record of this unqiue row is 1964 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; laps ; 1 }'}, 'finish'], 'result': '30', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; laps ; 1 } ; finish }'}, '30'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; laps ; 1 } ; finish } ; 30 }', 'tointer': 'the finish record of this unqiue row is 30 .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; laps ; 1 } ; year } ; 1964 } ; eq { hop { filter_eq { all_rows ; laps ; 1 } ; finish } ; 30 } }', 'tointer': 'the year record of this unqiue row is 1964 . the finish record of this unqiue row is 30 .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; laps ; 1 } } ; and { eq { hop { filter_eq { all_rows ; laps ; 1 } ; year } ; 1964 } ; eq { hop { filter_eq { all_rows ; laps ; 1 } ; finish } ; 30 } } } = true', 'tointer': 'select the rows whose laps record is equal to 1 . there is only one such row in the table . the year record of this unqiue row is 1964 . the finish record of this unqiue row is 30 .'} | and { only { filter_eq { all_rows ; laps ; 1 } } ; and { eq { hop { filter_eq { all_rows ; laps ; 1 } ; year } ; 1964 } ; eq { hop { filter_eq { all_rows ; laps ; 1 } ; finish } ; 30 } } } = true | select the rows whose laps record is equal to 1 . there is only one such row in the table . the year record of this unqiue row is 1964 . the finish record of this unqiue row is 30 . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_9': 9, 'laps_10': 10, '1_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'year_12': 12, '1964_13': 13, 'eq_5': 5, 'num_hop_4': 4, 'finish_14': 14, '30_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_9': 'all_rows', 'laps_10': 'laps', '1_11': '1', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_12': 'year', '1964_13': '1964', 'eq_5': 'eq', 'num_hop_4': 'num_hop', 'finish_14': 'finish', '30_15': '30'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_eq_0': [1, 2, 4], 'all_rows_9': [0], 'laps_10': [0], '1_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'year_12': [2], '1964_13': [3], 'eq_5': [6], 'num_hop_4': [5], 'finish_14': [4], '30_15': [5]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1957', '2', '143.872', '3', '23', '105'], ['1958', '18', '144.660', '7', '22', '68'], ['1959', '2', '145.425', '2', '17', '182'], ['1960', '1', '146.592', '2', '21', '132'], ['1961', '1', '147.481', '1', '2', '200'], ['1962', '27', '146.431', '27', '3', '200'], ['1963', '10', '149.570', '10', '17', '181'], ['1964', '17', '151.439', '22', '30', '1']] |
athletics at the 2008 summer olympics - women 's 200 metres | https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_200_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18569021-5.html.csv | comparative | in the 200 metres at the 2008 summer olympics , emily freeman was ranked one position better than aleksandra fedoriva . | {'row_1': '7', 'row_2': '8', 'col': '1', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'yes', 'diff_result': {'diff_value': '1', 'bigger': 'row2'}} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'emily freeman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record fuzzily matches to emily freeman .', 'tostr': 'filter_eq { all_rows ; athlete ; emily freeman }'}, 'rank'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank }', 'tointer': 'select the rows whose athlete record fuzzily matches to emily freeman . take the rank record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'aleksandra fedoriva'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose athlete record fuzzily matches to aleksandra fedoriva .', 'tostr': 'filter_eq { all_rows ; athlete ; aleksandra fedoriva }'}, 'rank'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank }', 'tointer': 'select the rows whose athlete record fuzzily matches to aleksandra fedoriva . take the rank record of this row .'}], 'result': '-1', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank } ; hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank } }'}, '-1'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank } ; hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank } } ; -1 }', 'tointer': 'select the rows whose athlete record fuzzily matches to emily freeman . take the rank record of this row . select the rows whose athlete record fuzzily matches to aleksandra fedoriva . take the rank record of this row . the second record is 1 larger than the first record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'emily freeman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record fuzzily matches to emily freeman .', 'tostr': 'filter_eq { all_rows ; athlete ; emily freeman }'}, 'rank'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank }', 'tointer': 'select the rows whose athlete record fuzzily matches to emily freeman . take the rank record of this row .'}, '7'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank } ; 7 }', 'tointer': 'the rank record of the first row is 7 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'aleksandra fedoriva'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose athlete record fuzzily matches to aleksandra fedoriva .', 'tostr': 'filter_eq { all_rows ; athlete ; aleksandra fedoriva }'}, 'rank'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank }', 'tointer': 'select the rows whose athlete record fuzzily matches to aleksandra fedoriva . take the rank record of this row .'}, '8'], 'result': True, 'ind': 7, 'tostr': 'eq { hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank } ; 8 }', 'tointer': 'the rank record of the second row is 8 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank } ; 7 } ; eq { hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank } ; 8 } }', 'tointer': 'the rank record of the first row is 7 . the rank record of the second row is 8 .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { diff { hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank } ; hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank } } ; -1 } ; and { eq { hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank } ; 7 } ; eq { hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank } ; 8 } } } = true', 'tointer': 'select the rows whose athlete record fuzzily matches to emily freeman . take the rank record of this row . select the rows whose athlete record fuzzily matches to aleksandra fedoriva . take the rank record of this row . the second record is 1 larger than the first record . the rank record of the first row is 7 . the rank record of the second row is 8 .'} | and { eq { diff { hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank } ; hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank } } ; -1 } ; and { eq { hop { filter_eq { all_rows ; athlete ; emily freeman } ; rank } ; 7 } ; eq { hop { filter_eq { all_rows ; athlete ; aleksandra fedoriva } ; rank } ; 8 } } } = true | select the rows whose athlete record fuzzily matches to emily freeman . take the rank record of this row . select the rows whose athlete record fuzzily matches to aleksandra fedoriva . take the rank record of this row . the second record is 1 larger than the first record . the rank record of the first row is 7 . the rank record of the second row is 8 . | 14 | 10 | {'and_9': 9, 'result_10': 10, 'eq_5': 5, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_11': 11, 'athlete_12': 12, 'emily freeman_13': 13, 'rank_14': 14, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_15': 15, 'athlete_16': 16, 'aleksandra fedoriva_17': 17, 'rank_18': 18, '-1_19': 19, 'and_8': 8, 'eq_6': 6, '7_20': 20, 'eq_7': 7, '8_21': 21} | {'and_9': 'and', 'result_10': 'true', 'eq_5': 'eq', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_11': 'all_rows', 'athlete_12': 'athlete', 'emily freeman_13': 'emily freeman', 'rank_14': 'rank', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_15': 'all_rows', 'athlete_16': 'athlete', 'aleksandra fedoriva_17': 'aleksandra fedoriva', 'rank_18': 'rank', '-1_19': '-1', 'and_8': 'and', 'eq_6': 'eq', '7_20': '7', 'eq_7': 'eq', '8_21': '8'} | {'and_9': [10], 'result_10': [], 'eq_5': [9], 'diff_4': [5], 'num_hop_2': [4, 6], 'filter_str_eq_0': [2], 'all_rows_11': [0], 'athlete_12': [0], 'emily freeman_13': [0], 'rank_14': [2], 'num_hop_3': [4, 7], 'filter_str_eq_1': [3], 'all_rows_15': [1], 'athlete_16': [1], 'aleksandra fedoriva_17': [1], 'rank_18': [3], '-1_19': [5], 'and_8': [9], 'eq_6': [8], '7_20': [6], 'eq_7': [8], '8_21': [7]} | ['rank', 'lane', 'athlete', 'country', 'time', 'react'] | [['1', '7', 'allyson felix', 'united states', '22.33', '0.181'], ['2', '9', 'marshevet hooker', 'united states', '22.50', '0.196'], ['3', '5', 'sherone simpson', 'jamaica', '22.50', '0.175'], ['4', '3', 'cydonie mothersille', 'cayman islands', '22.61', '0.212'], ['5', '4', 'muriel hurtis - houairi', 'france', '22.71', '0.188'], ['6', '6', 'roqaya al - gassra', 'bahrain', '22.72', '0.259'], ['7', '8', 'emily freeman', 'great britain', '22.83', '0.201'], ['8', '2', 'aleksandra fedoriva', 'russia', '23.22', '0.202']] |
1954 vfl season | https://en.wikipedia.org/wiki/1954_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-17.html.csv | aggregation | crowds totaled 129,800 for the games of the 1954 vfl season . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '129,800', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '129,800', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '129,800'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 129,800 } = true', 'tointer': 'the sum of the crowd record of all rows is 129,800 .'} | round_eq { sum { all_rows ; crowd } ; 129,800 } = true | the sum of the crowd record of all rows is 129,800 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '129,800_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '129,800_5': '129,800'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '129,800_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '14.13 ( 97 )', 'st kilda', '5.10 ( 40 )', 'mcg', '16700', '21 august 1954'], ['hawthorn', '10.10 ( 70 )', 'richmond', '6.11 ( 47 )', 'glenferrie oval', '14000', '21 august 1954'], ['essendon', '7.17 ( 59 )', 'footscray', '11.12 ( 78 )', 'windy hill', '36000', '21 august 1954'], ['collingwood', '6.14 ( 50 )', 'geelong', '10.12 ( 72 )', 'victoria park', '36000', '21 august 1954'], ['carlton', '22.11 ( 143 )', 'fitzroy', '14.7 ( 91 )', 'princes park', '12100', '21 august 1954'], ['south melbourne', '11.14 ( 80 )', 'north melbourne', '14.11 ( 95 )', 'lake oval', '15000', '21 august 1954']] |
primera división de fútbol profesional apertura 2002 | https://en.wikipedia.org/wiki/Primera_Divisi%C3%B3n_de_F%C3%BAtbol_Profesional_Apertura_2002 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13013383-1.html.csv | majority | all the teams in the primera división de fútbol profesional apertura 2002 played a total of 18 matches . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '18', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '18'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 18 .', 'tostr': 'all_eq { all_rows ; played ; 18 } = true'} | all_eq { all_rows ; played ; 18 } = true | for the played records of all rows , all of them are equal to 18 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '18_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '18_4': '18'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '18_4': [0]} | ['place', 'team', 'played', 'draw', 'lost', 'goals scored', 'goals conceded', 'points'] | [['1', 'cd fas', '18', '5', '3', '24', '20', '35'], ['2', 'municipal limeño', '18', '4', '5', '33', '19', '31'], ['3', 'san salvador fc', '18', '7', '4', '28', '21', '28'], ['4', 'cd águila', '18', '9', '3', '26', '20', '27'], ['5', 'cd luis ángel firpo', '18', '6', '5', '23', '24', '27'], ['6', 'ad isidro metapán', '18', '6', '7', '22', '24', '21'], ['7', 'cd arcense', '18', '6', '7', '15', '17', '21'], ['8', 'cd atlético balboa', '18', '5', '9', '21', '31', '17'], ['9', 'alianza fc', '18', '7', '8', '17', '22', '16'], ['10', 'cd dragón', '18', '7', '8', '20', '31', '16']] |
economy of greece | https://en.wikipedia.org/wiki/Economy_of_Greece | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12113-7.html.csv | aggregation | the average per capita of the five top ranking regions in greece 's economy is 19,880 . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '19,880', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '5'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'rank', '5'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; rank ; 5 }', 'tointer': 'select the rows whose rank record is less than or equal to 5 .'}, 'per capita'], 'result': '19,880', 'ind': 1, 'tostr': 'avg { filter_less_eq { all_rows ; rank ; 5 } ; per capita }'}, '19,880'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less_eq { all_rows ; rank ; 5 } ; per capita } ; 19,880 } = true', 'tointer': 'select the rows whose rank record is less than or equal to 5 . the average of the per capita record of these rows is 19,880 .'} | round_eq { avg { filter_less_eq { all_rows ; rank ; 5 } ; per capita } ; 19,880 } = true | select the rows whose rank record is less than or equal to 5 . the average of the per capita record of these rows is 19,880 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'rank_5': 5, '5_6': 6, 'per capita_7': 7, '19,880_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '5_6': '5', 'per capita_7': 'per capita', '19,880_8': '19,880'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '5_6': [0], 'per capita_7': [1], '19,880_8': [2]} | ['rank', 'region', 'total gdp ( bn )', '% growth', 'per capita'] | [['1', 'attica', '110.546', '0.8', '29100'], ['2', 'central macedonia', '32.285', '1.3', '17900'], ['3', 'thessaly', '11.608', '1.3', '17000'], ['4', 'crete', '11.243', '1.6', '19900'], ['5', 'west greece', '10.659', '3.6', '15500'], ['6', 'central greece', '10.537', '1.7', '20500'], ['7', 'peloponnese', '9.809', '0.7', '17900'], ['8', 'east macedonia and thrace', '9.265', '0.9', '16500'], ['9', 'south aegean', '7.646', '2.8', '26800'], ['10', 'epirus', '5.079', '0.2', '15300'], ['11', 'west macedonia', '5.506', '1.9', '20300'], ['12', 'ionian islands', '4.130', '7.4', '19100'], ['13', 'north aegean', '3.330', '3.3', '17900'], ['14', 'mount athos', 'n / a', 'n / a', 'n / a'], ['-', 'greece', '231.643', '0.5', '20500'], ['-', 'eu', '11745.353', '5.8', '23500']] |
samantha miss | https://en.wikipedia.org/wiki/Samantha_Miss | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20626467-1.html.csv | comparative | of the races that samantha miss participated in , flight stakes was 21 days before cox plate . | {'row_1': '9', 'row_2': '10', 'col': '2', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '21', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'race', 'flight stakes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race record fuzzily matches to flight stakes .', 'tostr': 'filter_eq { all_rows ; race ; flight stakes }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; race ; flight stakes } ; date }', 'tointer': 'select the rows whose race record fuzzily matches to flight stakes . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'race', 'cox plate'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose race record fuzzily matches to cox plate .', 'tostr': 'filter_eq { all_rows ; race ; cox plate }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; race ; cox plate } ; date }', 'tointer': 'select the rows whose race record fuzzily matches to cox plate . take the date record of this row .'}], 'result': '-21', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; race ; flight stakes } ; date } ; hop { filter_eq { all_rows ; race ; cox plate } ; date } }'}, '-21'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; race ; flight stakes } ; date } ; hop { filter_eq { all_rows ; race ; cox plate } ; date } } ; -21 } = true', 'tointer': 'select the rows whose race record fuzzily matches to flight stakes . take the date record of this row . select the rows whose race record fuzzily matches to cox plate . take the date record of this row . the second record is 21 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; race ; flight stakes } ; date } ; hop { filter_eq { all_rows ; race ; cox plate } ; date } } ; -21 } = true | select the rows whose race record fuzzily matches to flight stakes . take the date record of this row . select the rows whose race record fuzzily matches to cox plate . take the date record of this row . the second record is 21 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'race_8': 8, 'flight stakes_9': 9, 'date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'race_12': 12, 'cox plate_13': 13, 'date_14': 14, '-21_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'race_8': 'race', 'flight stakes_9': 'flight stakes', 'date_10': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'race_12': 'race', 'cox plate_13': 'cox plate', 'date_14': 'date', '-21_15': '-21'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'race_8': [0], 'flight stakes_9': [0], 'date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'race_12': [1], 'cox plate_13': [1], 'date_14': [3], '-21_15': [5]} | ['result', 'date', 'race', 'venue', 'distance', 'class', 'weight ( kg )', 'time', 'jockey', 'odds', 'winner / 2nd'] | [['1st', '12 / 03 / 08', 'wattle grove handicap', 'kensington', '1150 m', 'handicap', '54.5 kg', '1 - 07.95', 'hugh bowman', '1.75 f', '2nd - packing supreme'], ['3rd', '29 / 03 / 08', 'sweet embrace stakes', 'randwick', '1200 m', 'group 3', '55.5 kg', '1 - 11.03', 'hugh bowman', '3.00 f', '1st - stripper'], ['4th', '12 / 04 / 08', 'magic night stakes', 'rosehill', '1200 m', 'group 2', '55.5 kg', '1 - 11.91', 'hugh bowman', '4.40', '1st - portillo'], ['2nd', '26 / 04 / 08', 'ajc sires produce stakes', 'randwick', '1400 m', 'group 1', '54.5 kg', '1 - 25.99', 'hugh bowman', '12.00', '1st - sebring'], ['1st', '03 / 05 / 08', 'champagne stakes', 'randwick', '1600 m', 'group 1', '54.4 kg', '1 - 38.28', 'hugh bowman', '6.00', '2nd - sebring'], ['1st', '23 / 08 / 08', 'silver shadow stakes', 'wawrick farm', '1200 m', 'group 3', '58 kg', '1 - 12.44', 'hugh bowman', '6.00', '2nd - glowlamp'], ['1st', '09 / 09 / 08', 'furious stakes', 'randwick', '1400 m', 'group 2', '56 kg', '1 - 26.21', 'hugh bow man', '2.20 f', '2nd - love and kisses'], ['1st', '20 / 09 / 08', 'tea rose stakes', 'rosehill', '1500 m', 'group 2', '56 kg', '1 - 30.61', 'hugh bowman', '1.95 f', '2nd - kimillsy'], ['1st', '04 / 10 / 08', 'flight stakes', 'randwick', '1600 m', 'group 1', '56 kg', '1 - 38.49', 'hugh bowman', '1.55 f', '2nd - portillo'], ['3rd', '25 / 10 / 08', 'cox plate', 'moonee valley', '2040 m', 'group 1', '47.5 kg', '2 - 06.92', 'glen boss', '4.60 f', '1st - maldivian'], ['1st', '08 / 11 / 08', 'vrc oaks', 'flemington', '2500 m', 'group 1', '55.5 kg', '2 - 37.57', 'hugh bowman', '1.85 f', '2nd - miss scarlatti']] |
2001 new york jets season | https://en.wikipedia.org/wiki/2001_New_York_Jets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10768951-1.html.csv | count | eight of the games were held at the meadowlands . | {'scope': 'all', 'criterion': 'equal', 'value': 'the meadowlands', 'result': '8', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'the meadowlands'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to the meadowlands .', 'tostr': 'filter_eq { all_rows ; game site ; the meadowlands }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; game site ; the meadowlands } }', 'tointer': 'select the rows whose game site record fuzzily matches to the meadowlands . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; game site ; the meadowlands } } ; 8 } = true', 'tointer': 'select the rows whose game site record fuzzily matches to the meadowlands . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; game site ; the meadowlands } } ; 8 } = true | select the rows whose game site record fuzzily matches to the meadowlands . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'the meadowlands_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'the meadowlands_6': 'the meadowlands', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'the meadowlands_6': [0], '8_7': [2]} | ['week', 'date', 'opponent', 'result', 'game site', 'attendance'] | [['1', '2001 - 09 - 09', 'indianapolis colts', 'l 45 - 24', 'the meadowlands', '78606'], ['2', '2001 - 09 - 23', 'new england patriots', 'w 10 - 3', 'foxboro stadium', '60292'], ['3', '2001 - 10 - 01', 'san francisco 49ers', 'l 19 - 17', 'the meadowlands', '78722'], ['4', '2001 - 10 - 07', 'buffalo bills', 'w 42 - 36', 'ralph wilson stadium', '72654'], ['5', '2001 - 10 - 14', 'miami dolphins', 'w 21 - 17', 'the meadowlands', '78823'], ['6', '2001 - 10 - 21', 'st louis rams', 'l 34 - 14', 'the meadowlands', '78766'], ['7', '2001 - 10 - 28', 'carolina panthers', 'w 13 - 12', 'bank of america stadium', '72642'], ['8', '2001 - 11 - 04', 'new orleans saints', 'w 16 - 9', 'louisiana superdome', '70020'], ['9', '2001 - 11 - 11', 'kansas city chiefs', 'w 27 - 7', 'the meadowlands', '78234'], ['10', '2001 - 11 - 18', 'miami dolphins', 'w 24 - 0', 'pro player stadium', '74259'], ['11', '-', '-', '-', '-', ''], ['12', '2001 - 12 - 02', 'new england patriots', 'l 17 - 16', 'the meadowlands', '78712'], ['13', '2001 - 12 - 09', 'pittsburgh steelers', 'l 18 - 7', 'heinz field', '62884'], ['14', '2001 - 12 - 16', 'cincinnati bengals', 'w 15 - 14', 'the meadowlands', '77745'], ['15', '2001 - 12 - 23', 'indianapolis colts', 'w 29 - 28', 'rca dome', '56302'], ['16', '2001 - 12 - 30', 'buffalo bills', 'l 14 - 9', 'the meadowlands', '78200'], ['17', '2002 - 01 - 06', 'oakland raiders', 'w 24 - 22', 'network associates coliseum', '62011']] |
list of communities in saskatchewan | https://en.wikipedia.org/wiki/List_of_communities_in_Saskatchewan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-189598-7.html.csv | count | according to the list of communities in saskatchewan , among the communities with land area below 10.00 km square , 2 of them have a population density over 150.00 per km square . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '150.0', 'result': '2', 'col': '6', 'subset': {'col': '5', 'criterion': 'less_than', 'value': '10.0'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'land area ( km square )', '10.0'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; land area ( km square ) ; 10.0 }', 'tointer': 'select the rows whose land area ( km square ) record is less than 10.0 .'}, 'population density ( per km square )', '150.0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose land area ( km square ) record is less than 10.0 . among these rows , select the rows whose population density ( per km square ) record is greater than 150.0 .', 'tostr': 'filter_greater { filter_less { all_rows ; land area ( km square ) ; 10.0 } ; population density ( per km square ) ; 150.0 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_greater { filter_less { all_rows ; land area ( km square ) ; 10.0 } ; population density ( per km square ) ; 150.0 } }', 'tointer': 'select the rows whose land area ( km square ) record is less than 10.0 . among these rows , select the rows whose population density ( per km square ) record is greater than 150.0 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_less { all_rows ; land area ( km square ) ; 10.0 } ; population density ( per km square ) ; 150.0 } } ; 2 } = true', 'tointer': 'select the rows whose land area ( km square ) record is less than 10.0 . among these rows , select the rows whose population density ( per km square ) record is greater than 150.0 . the number of such rows is 2 .'} | eq { count { filter_greater { filter_less { all_rows ; land area ( km square ) ; 10.0 } ; population density ( per km square ) ; 150.0 } } ; 2 } = true | select the rows whose land area ( km square ) record is less than 10.0 . among these rows , select the rows whose population density ( per km square ) record is greater than 150.0 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'land area (km square)_6': 6, '10.0_7': 7, 'population density (per km square)_8': 8, '150.0_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'land area (km square)_6': 'land area ( km square )', '10.0_7': '10.0', 'population density (per km square)_8': 'population density ( per km square )', '150.0_9': '150.0', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'land area (km square)_6': [0], '10.0_7': [0], 'population density (per km square)_8': [1], '150.0_9': [1], '2_10': [3]} | ['name', 'population ( 2011 )', 'population ( 2006 )', 'change ( % )', 'land area ( km square )', 'population density ( per km square )'] | [['air ronge', '1043', '1032', '1.1', '6.00', '173.8'], ['beauval', '756', '806', '- 6.2', '6.71', '112.6'], ['buffalo narrows', '1153', '1081', '6.7', '68.63', '16.8'], ['cumberland house', '772', '810', '- 4.7', '15.69', '49.2'], ['denare beach', '820', '785', '4.5', '5.84', '140.4'], ['green lake', '418', '361', '15.8', '121.92', '3.4'], ['île - à - la - crosse', '1365', '1341', '1.8', '23.84', '57.3'], ['la loche', '2611', '2348', '11.2', '15.59', '167.5'], ['pelican narrows', '790', '599', '31.9', '3.70', '213.3'], ['pinehouse', '978', '1076', '- 9.1', '6.84', '142.9'], ['sandy bay', '1233', '1175', '4.9', '14.85', '83.0']] |
history of test cricket from 1901 to 1914 | https://en.wikipedia.org/wiki/History_of_Test_cricket_from_1901_to_1914 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1598207-1.html.csv | superlative | the earliest match in the history of test cricket took place on december 13 , 1901 . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'min', 'args': ['all_rows', 'date'], 'result': '13 , 14 , 16 dec 1901', 'ind': 0, 'tostr': 'min { all_rows ; date }', 'tointer': 'the minimum date record of all rows is 13 , 14 , 16 dec 1901 .'}, '13 , 14 , 16 dec 1901'], 'result': True, 'ind': 1, 'tostr': 'eq { min { all_rows ; date } ; 13 , 14 , 16 dec 1901 } = true', 'tointer': 'the minimum date record of all rows is 13 , 14 , 16 dec 1901 .'} | eq { min { all_rows ; date } ; 13 , 14 , 16 dec 1901 } = true | the minimum date record of all rows is 13 , 14 , 16 dec 1901 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'min_0': 0, 'all_rows_3': 3, 'date_4': 4, '13 , 14 , 16 dec 1901_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'min_0': 'min', 'all_rows_3': 'all_rows', 'date_4': 'date', '13 , 14 , 16 dec 1901_5': '13 , 14 , 16 dec 1901'} | {'eq_1': [2], 'result_2': [], 'min_0': [1], 'all_rows_3': [0], 'date_4': [0], '13 , 14 , 16 dec 1901_5': [1]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['13 , 14 , 16 dec 1901', 'joe darling', 'archie maclaren', 'sydney cricket ground', 'eng by inns & 124 runs'], ['1 , 2 , 3 , 4 jan 1902', 'joe darling', 'archie maclaren', 'melbourne cricket ground', 'aus by 229 runs'], ['17 , 18 , 20 , 21 , 22 , 23 jan 1902', 'joe darling', 'archie maclaren', 'adelaide oval', 'aus by 4 wkts'], ['14 , 15 , 17 , 18 feb 1902', 'hugh trumble', 'archie maclaren', 'sydney cricket ground', 'aus by 7 wkts'], ['28 feb , 1 , 3 , 4 mar 1902', 'hugh trumble', 'archie maclaren', 'melbourne cricket ground', 'aus by 32 runs']] |
mid - american collegiate hockey association | https://en.wikipedia.org/wiki/Mid-American_Collegiate_Hockey_Association | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16406736-4.html.csv | count | in the mid - american collegiate hockey association , when the affiliation is public , there are 4 institutions where the enrollment is over 20000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '20000', 'result': '4', 'col': '5', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'public'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'affiliation', 'public'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; affiliation ; public }', 'tointer': 'select the rows whose affiliation record fuzzily matches to public .'}, 'enrollment', '20000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose affiliation record fuzzily matches to public . among these rows , select the rows whose enrollment record is greater than 20000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; affiliation ; public } ; enrollment ; 20000 }'}], 'result': '4', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; affiliation ; public } ; enrollment ; 20000 } }', 'tointer': 'select the rows whose affiliation record fuzzily matches to public . among these rows , select the rows whose enrollment record is greater than 20000 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; affiliation ; public } ; enrollment ; 20000 } } ; 4 } = true', 'tointer': 'select the rows whose affiliation record fuzzily matches to public . among these rows , select the rows whose enrollment record is greater than 20000 . the number of such rows is 4 .'} | eq { count { filter_greater { filter_eq { all_rows ; affiliation ; public } ; enrollment ; 20000 } } ; 4 } = true | select the rows whose affiliation record fuzzily matches to public . among these rows , select the rows whose enrollment record is greater than 20000 . the number of such rows is 4 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'affiliation_6': 6, 'public_7': 7, 'enrollment_8': 8, '20000_9': 9, '4_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'affiliation_6': 'affiliation', 'public_7': 'public', 'enrollment_8': 'enrollment', '20000_9': '20000', '4_10': '4'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'affiliation_6': [0], 'public_7': [0], 'enrollment_8': [1], '20000_9': [1], '4_10': [3]} | ['institution', 'location', 'founded', 'affiliation', 'enrollment', 'nickname'] | [['dordt college', 'sioux center , ia', '1955', 'private / christian reformed church', '1300', 'blades'], ['university of iowa', 'iowa city , ia', '1847', 'public', '30000', 'hawkeyes'], ['iowa state university', 'ames , ia', '1858', 'public', '29000', 'cyclones'], ['missouri state university', 'springfield , mo', '1905', 'public', '21059', 'ice bears'], ['university of nebraska', 'lincoln , ne', '1869', 'public', '24593', 'huskers'], ['university of wisconsin - platteville', 'platteville , wi', '1866', 'public', '7928', 'pioneers']] |
list of intel core i7 microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Core_i7_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18823880-2.html.csv | count | 6 of the intel core i7 i/o bus are dml . | {'scope': 'all', 'criterion': 'equal', 'value': 'dmi', 'result': '6', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'i / o bus', 'dmi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose i / o bus record fuzzily matches to dmi .', 'tostr': 'filter_eq { all_rows ; i / o bus ; dmi }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; i / o bus ; dmi } }', 'tointer': 'select the rows whose i / o bus record fuzzily matches to dmi . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; i / o bus ; dmi } } ; 6 } = true', 'tointer': 'select the rows whose i / o bus record fuzzily matches to dmi . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; i / o bus ; dmi } } ; 6 } = true | select the rows whose i / o bus record fuzzily matches to dmi . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'i / o bus_5': 5, 'dmi_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'i / o bus_5': 'i / o bus', 'dmi_6': 'dmi', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'i / o bus_5': [0], 'dmi_6': [0], '6_7': [2]} | ['model number', 'sspec number', 'frequency', 'turbo', 'cores', 'l2 cache', 'l3 cache', 'i / o bus', 'mult', 'memory', 'voltage', 'socket', 'release date', 'part number ( s )', 'release price ( usd )'] | [['standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power'], ['core i7 - 860', 'slbjj ( b1 )', '2.8 ghz', '1 / 1 / 4 / 5', '4', '4 256 kb', '8 mb', 'dmi', '21', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'september 2009', 'bv80605001908akbx80605i7860', '284'], ['core i7 - 870', 'slbjg ( b1 )', '2.93 ghz', '2 / 2 / 4 / 5', '4', '4 256 kb', '8 mb', 'dmi', '22', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'september 2009', 'bv80605001905aibx80605i7870', '562'], ['core i7 - 875k', 'slbs2 ( b1 )', '2.93 ghz', '2 / 2 / 4 / 5', '4', '4 256 kb', '8 mb', 'dmi', '22', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'may 2010', 'bv80605001905 ambx80605i7875k', '342'], ['core i7 - 880', 'slbps ( b1 )', '3.07 ghz', '2 / 2 / 4 / 5', '4', '4 256 kb', '8 mb', 'dmi', '23', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'may 2010', 'bv80605002505ag', '583'], ['low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power'], ['core i7 - 860s', 'slblg ( b1 )', '2.53 ghz', '0 / 0 / 6 / 7', '4', '4 256 kb', '8 mb', 'dmi', '19', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'january 2010', 'bv80605003210adbx80605i7860s', '337'], ['core i7 - 870s', 'slbq7 ( b1 )', '2.67 ghz', '0 / 0 / 6 / 7', '4', '4 256 kb', '8 mb', 'dmi', '20', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'july 2010', 'bx80605i7870sbv80605004494ab', '351']] |
united states house of representatives elections , 1826 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1826 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668254-25.html.csv | comparative | robert taylor was first elected after mark alexander was first elected . | {'row_1': '9', 'row_2': '3', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'robert taylor'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to robert taylor .', 'tostr': 'filter_eq { all_rows ; incumbent ; robert taylor }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; robert taylor } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to robert taylor . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'mark alexander'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to mark alexander .', 'tostr': 'filter_eq { all_rows ; incumbent ; mark alexander }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; mark alexander } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to mark alexander . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; incumbent ; robert taylor } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; mark alexander } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to robert taylor . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to mark alexander . take the first elected record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; incumbent ; robert taylor } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; mark alexander } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to robert taylor . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to mark alexander . take the first elected 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, 'incumbent_7': 7, 'robert taylor_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'mark alexander_12': 12, 'first elected_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', 'incumbent_7': 'incumbent', 'robert taylor_8': 'robert taylor', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'mark alexander_12': 'mark alexander', 'first elected_13': 'first elected'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'robert taylor_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'mark alexander_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['virginia 2', 'james trezvant', 'jacksonian', '1825', 're - elected', 'james trezvant ( j ) 100 %'], ['virginia 3', 'william s archer', 'jacksonian', '1820 ( special )', 're - elected', 'william s archer ( j ) 100 %'], ['virginia 4', 'mark alexander', 'jacksonian', '1819', 're - elected', 'mark alexander ( j ) 100 %'], ['virginia 5', 'george w crump', 'jacksonian', '1826 ( special )', 'retired jacksonian hold', 'john randolph ( j ) 100 %'], ['virginia 6', 'thomas davenport', 'jacksonian', '1825', 're - elected', 'thomas davenport ( j ) 100 %'], ['virginia 8', 'burwell bassett', 'jacksonian', '1805 1821', 're - elected', 'burwell bassett ( j ) 100 %'], ['virginia 9', 'andrew stevenson', 'jacksonian', '1821', 're - elected', 'andrew stevenson ( j ) 100 %'], ['virginia 10', 'william c rives', 'jacksonian', '1823', 're - elected', 'william c rives ( j ) 100 %'], ['virginia 11', 'robert taylor', 'adams', '1825', 'retired jacksonian gain', 'philip p barbour ( j ) 100 %'], ['virginia 12', 'robert s garnett', 'jacksonian', '1817', 'retired jacksonian hold', 'john roane ( j ) 100 %'], ['virginia 14', 'charles f mercer', 'adams', '1817', 're - elected', 'charles f mercer ( a ) 63.0 % robert thompson 37.0 %'], ['virginia 15', 'john s barbour', 'jacksonian', '1823', 're - elected', 'john s barbour ( j ) 65.0 % william e hunton 35.0 %'], ['virginia 16', 'william armstrong', 'adams', '1825', 're - elected', 'william armstrong ( a ) 78.0 % john peters 22.0 %'], ['virginia 19', 'william mccoy', 'jacksonian', '1811', 're - elected', 'william mccoy ( j )'], ['virginia 20', 'john floyd', 'jacksonian', '1817', 're - elected', 'john floyd ( j ) 87.2 % edward watts 12.8 %']] |
radio iq | https://en.wikipedia.org/wiki/Radio_IQ | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12265526-1.html.csv | majority | the majority of radio channels under the radio iq brand are class a radio channels . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'a', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'class', 'a'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , most of them fuzzily match to a .', 'tostr': 'most_eq { all_rows ; class ; a } = true'} | most_eq { all_rows ; class ; a } = true | for the class records of all rows , most of them fuzzily match to a . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, 'a_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', 'a_4': 'a'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], 'a_4': [0]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['wvtw', '88.5', 'charlottesville , virginia', '1000', 'b1', 'fcc'], ['wffc', '89.9', 'ferrum , virginia', '1100', 'a', 'fcc'], ['wqiq', '88.3', 'spotsylvania , virginia', '3500', 'a', 'fcc'], ['wriq', '88.7', 'lexington , virginia', '3900', 'a', 'fcc'], ['wwvt', '1260', 'christiansburg , virginia', '5000 day 25 night', 'd', 'fcc']] |
1989 indianapolis colts season | https://en.wikipedia.org/wiki/1989_Indianapolis_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14875671-1.html.csv | comparative | in the 1989 colts season , the attendance for the game on december 17 , 1989 was 6656 people higher than the game on december 24 , 1989 . | {'row_1': '15', 'row_2': '16', 'col': '7', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '6656', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december 17 , 1989'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to december 17 , 1989 .', 'tostr': 'filter_eq { all_rows ; date ; december 17 , 1989 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; december 17 , 1989 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 17 , 1989 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december 24 , 1989'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december 24 , 1989 .', 'tostr': 'filter_eq { all_rows ; date ; december 24 , 1989 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; december 24 , 1989 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 24 , 1989 . take the attendance record of this row .'}], 'result': '6656', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; date ; december 17 , 1989 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 24 , 1989 } ; attendance } }'}, '6656'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; date ; december 17 , 1989 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 24 , 1989 } ; attendance } } ; 6656 } = true', 'tointer': 'select the rows whose date record fuzzily matches to december 17 , 1989 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 24 , 1989 . take the attendance record of this row . the first record is 6656 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; date ; december 17 , 1989 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 24 , 1989 } ; attendance } } ; 6656 } = true | select the rows whose date record fuzzily matches to december 17 , 1989 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 24 , 1989 . take the attendance record of this row . the first record is 6656 larger than the second record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'date_8': 8, 'december 17 , 1989_9': 9, 'attendance_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'date_12': 12, 'december 24 , 1989_13': 13, 'attendance_14': 14, '6656_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'date_8': 'date', 'december 17 , 1989_9': 'december 17 , 1989', 'attendance_10': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'date_12': 'date', 'december 24 , 1989_13': 'december 24 , 1989', 'attendance_14': 'attendance', '6656_15': '6656'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'date_8': [0], 'december 17 , 1989_9': [0], 'attendance_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'date_12': [1], 'december 24 , 1989_13': [1], 'attendance_14': [3], '6656_15': [5]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 10 , 1989', 'san francisco 49ers', 'l 24 - 30', '0 - 1', 'hoosier dome', '60111'], ['2', 'september 17 , 1989', 'los angeles rams', 'l 17 - 31', '0 - 2', 'anaheim stadium', '63995'], ['3', 'september 24 , 1989', 'atlanta falcons', 'w 13 - 9', '1 - 2', 'hoosier dome', '57816'], ['4', 'october 1 , 1989', 'new york jets', 'w 17 - 10', '2 - 2', 'the meadowlands', '65542'], ['5', 'october 8 , 1989', 'buffalo bills', 'w 37 - 14', '3 - 2', 'hoosier dome', '58890'], ['6', 'october 15 , 1989', 'denver broncos', 'l 3 - 14', '3 - 3', 'mile high stadium', '74680'], ['7', 'october 22 , 1989', 'cincinnati bengals', 'w 23 - 12', '4 - 3', 'riverfront stadium', '57642'], ['8', 'october 29 , 1989', 'new england patriots', 'l 20 - 23', '4 - 4', 'hoosier dome', '59356'], ['9', 'november 5 , 1989', 'miami dolphins', 'l 13 - 19', '4 - 5', 'joe robbie stadium', '52680'], ['10', 'november 12 , 1989', 'buffalo bills', 'l 7 - 30', '4 - 6', 'rich stadium', '79256'], ['11', 'november 19 , 1989', 'new york jets', 'w 27 - 10', '5 - 6', 'hoosier dome', '58236'], ['12', 'november 26 , 1989', 'san diego chargers', 'w 10 - 6', '6 - 6', 'hoosier dome', '58822'], ['13', 'december 3 , 1989', 'new england patriots', 'l 16 - 22', '6 - 7', 'sullivan stadium', '32234'], ['14', 'december 10 , 1989', 'cleveland browns', 'w 23 - 17', '7 - 7', 'hoosier dome', '58550'], ['15', 'december 17 , 1989', 'miami dolphins', 'w 42 - 13', '8 - 7', 'hoosier dome', '55665'], ['16', 'december 24 , 1989', 'new orleans saints', 'l 6 - 41', '8 - 8', 'louisiana superdome', '49009']] |
1946 in brazilian football | https://en.wikipedia.org/wiki/1946_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15319684-1.html.csv | superlative | corinthians won the most games in the campeonato paulista in 1946 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'won'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; won }'}, 'team'], 'result': 'corinthians', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; won } ; team }'}, 'corinthians'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; won } ; team } ; corinthians } = true', 'tointer': 'select the row whose won record of all rows is maximum . the team record of this row is corinthians .'} | eq { hop { argmax { all_rows ; won } ; team } ; corinthians } = true | select the row whose won record of all rows is maximum . the team record of this row is corinthians . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'won_5': 5, 'team_6': 6, 'corinthians_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'won_5': 'won', 'team_6': 'team', 'corinthians_7': 'corinthians'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'won_5': [0], 'team_6': [1], 'corinthians_7': [2]} | ['position', 'team', 'points', 'played', 'won', 'drawn', 'lost', 'for', 'against', 'difference'] | [['1', 'são paulo', '37', '20', '17', '3', '0', '62', '20', '42'], ['2', 'corinthians', '36', '20', '18', '0', '2', '62', '29', '33'], ['3', 'portuguesa', '28', '20', '13', '2', '5', '46', '20', '26'], ['4', 'santos', '22', '20', '9', '4', '7', '37', '32', '5'], ['5', 'palmeiras', '20', '20', '8', '4', '8', '37', '31', '6'], ['6', 'portuguesa santista', '17', '20', '7', '3', '10', '41', '51', '- 10'], ['7', 'ypiranga - sp', '14', '20', '6', '2', '12', '35', '48', '- 13'], ['8', 'comercial - sp', '14', '20', '4', '6', '10', '38', '55', '- 17'], ['9', 'são paulo railway', '12', '20', '5', '2', '13', '27', '46', '- 19'], ['10', 'juventus', '11', '20', '4', '3', '13', '32', '60', '- 28']] |
frank loughran | https://en.wikipedia.org/wiki/Frank_Loughran | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15278411-1.html.csv | unique | the only one of frank loughran 's football events held in melbourne where he scored a goal was held on 11-27-1956 . | {'scope': 'subset', 'row': '4', 'col': '4', 'col_other': '1,2', 'criterion': 'greater_than', 'value': '0', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'melbourne'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'melbourne'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; melbourne }', 'tointer': 'select the rows whose venue record fuzzily matches to melbourne .'}, 'goals', '0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to melbourne . among these rows , select the rows whose goals record is greater than 0 .', 'tostr': 'filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 } }', 'tointer': 'select the rows whose venue record fuzzily matches to melbourne . among these rows , select the rows whose goals record is greater than 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'melbourne'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; melbourne }', 'tointer': 'select the rows whose venue record fuzzily matches to melbourne .'}, 'goals', '0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to melbourne . among these rows , select the rows whose goals record is greater than 0 .', 'tostr': 'filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 }'}, 'date'], 'result': '1956 - 11 - 27', 'ind': 3, 'tostr': 'hop { filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 } ; date }'}, '1956 - 11 - 27'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 } ; date } ; 1956 - 11 - 27 }', 'tointer': 'the date record of this unqiue row is 1956 - 11 - 27 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 } } ; eq { hop { filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 } ; date } ; 1956 - 11 - 27 } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to melbourne . among these rows , select the rows whose goals record is greater than 0 . there is only one such row in the table . the date record of this unqiue row is 1956 - 11 - 27 .'} | and { only { filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 } } ; eq { hop { filter_greater { filter_eq { all_rows ; venue ; melbourne } ; goals ; 0 } ; date } ; 1956 - 11 - 27 } } = true | select the rows whose venue record fuzzily matches to melbourne . among these rows , select the rows whose goals record is greater than 0 . there is only one such row in the table . the date record of this unqiue row is 1956 - 11 - 27 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'venue_8': 8, 'melbourne_9': 9, 'goals_10': 10, '0_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'date_12': 12, '1956 - 11 - 27_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'venue_8': 'venue', 'melbourne_9': 'melbourne', 'goals_10': 'goals', '0_11': '0', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'date_12': 'date', '1956 - 11 - 27_13': '1956 - 11 - 27'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_greater_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'venue_8': [0], 'melbourne_9': [0], 'goals_10': [1], '0_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'date_12': [3], '1956 - 11 - 27_13': [4]} | ['date', 'venue', 'result', 'goals', 'competition'] | [['1955 - 09 - 03', 'brisbane', '0 - 3', '0', 'friendly match'], ['1955 - 09 - 10', 'melbourne', '0 - 2', '0', 'friendly match'], ['1955 - 09 - 17', 'adelaide', '0 - 8', '0', 'friendly match'], ['1956 - 11 - 27', 'melbourne', '2 - 0', '1', 'olympic games'], ['1956 - 12 - 01', 'melbourne', '2 - 4', '0', 'olympic games'], ['1956 - 12 - 12', 'sydney', '1 - 7', '0', 'friendly match'], ['1958 - 08 - 16', 'wellington', '3 - 2', '1', 'friendly match'], ['1958 - 08 - 23', 'auckland', '2 - 2', '0', 'friendly match']] |
canadian interuniversity sport football | https://en.wikipedia.org/wiki/Canadian_Interuniversity_Sport_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12896884-2.html.csv | aggregation | for canadian universities , the average football stadium capacity in schools with enrollment below 25000 is 5590 . | {'scope': 'subset', 'col': '9', 'type': 'average', 'result': '5590', 'subset': {'col': '7', 'criterion': 'less_than', 'value': '25000'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'enrollment', '25000'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; enrollment ; 25000 }', 'tointer': 'select the rows whose enrollment record is less than 25000 .'}, 'capacity'], 'result': '5590', 'ind': 1, 'tostr': 'avg { filter_less { all_rows ; enrollment ; 25000 } ; capacity }'}, '5590'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_less { all_rows ; enrollment ; 25000 } ; capacity } ; 5590 } = true', 'tointer': 'select the rows whose enrollment record is less than 25000 . the average of the capacity record of these rows is 5590 .'} | round_eq { avg { filter_less { all_rows ; enrollment ; 25000 } ; capacity } ; 5590 } = true | select the rows whose enrollment record is less than 25000 . the average of the capacity record of these rows is 5590 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '25000_6': 6, 'capacity_7': 7, '5590_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', '25000_6': '25000', 'capacity_7': 'capacity', '5590_8': '5590'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '25000_6': [0], 'capacity_7': [1], '5590_8': [2]} | ['institution', 'team', 'city', 'province', 'first season', 'head coach', 'enrollment', 'football stadium', 'capacity'] | [['university of windsor', 'lancers', 'windsor', 'on', '1968', "joe d'amore", '13496', 'south campus stadium', '2000'], ['university of western ontario', 'mustangs', 'london', 'on', '1929', 'greg marshall', '30000', 'td waterhouse stadium', '10000'], ['university of waterloo', 'warriors', 'waterloo', 'on', '1957', 'joe paopao', '27978', 'warrior field', '5200'], ['wilfrid laurier university', 'golden hawks', 'waterloo', 'on', '1961', 'michael faulds', '12394', 'university stadium', '6000'], ['university of guelph', 'gryphons', 'guelph', 'on', '1950', 'stu lang', '19408', 'alumni stadium', '4100'], ['mcmaster university', 'marauders', 'hamilton', 'on', '1901', 'stefan ptaszek', '25688', 'ron joyce stadium', '6000'], ['university of toronto', 'varsity blues', 'toronto', 'on', '1877', 'greg gary', '73185', 'varsity stadium', '5000'], ['york university', 'lions', 'toronto', 'on', '1969', 'warren craney', '42400', 'york stadium', '2500'], ["queen 's university", 'golden gaels', 'kingston', 'on', '1882', 'pat sheahan', '20566', 'richardson stadium', '10258'], ['university of ottawa', 'gee - gees', 'ottawa', 'on', '1894', 'jamie barresi', '35548', 'gee - gees field', '4152'], ['carleton university', 'ravens', 'ottawa', 'on', '1945', 'steve sumarah', '25890', 'keith harris stadium', '3000']] |
1995 pga tour | https://en.wikipedia.org/wiki/1995_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14611590-3.html.csv | aggregation | the average earnings of players in the 1995 pga tour was 1434310 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1434310', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'earnings'], 'result': '1434310', 'ind': 0, 'tostr': 'avg { all_rows ; earnings }'}, '1434310'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; earnings } ; 1434310 } = true', 'tointer': 'the average of the earnings record of all rows is 1434310 .'} | round_eq { avg { all_rows ; earnings } ; 1434310 } = true | the average of the earnings record of all rows is 1434310 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'earnings_4': 4, '1434310_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'earnings_4': 'earnings', '1434310_5': '1434310'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'earnings_4': [0], '1434310_5': [1]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'greg norman', 'australia', '1654959', '16', '3'], ['2', 'billy mayfair', 'united states', '1543192', '28', '2'], ['3', 'lee janzen', 'united states', '1378966', '28', '3'], ['4', 'corey pavin', 'united states', '1340079', '22', '2'], ['5', 'steve elkington', 'australia', '1254352', '21', '2']] |
operation priboi | https://en.wikipedia.org/wiki/Operation_Priboi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16048129-5.html.csv | aggregation | for operation priboi the total combined number of families was 30630 . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '30630', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'number of families'], 'result': '30630', 'ind': 0, 'tostr': 'sum { all_rows ; number of families }'}, '30630'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; number of families } ; 30630 } = true', 'tointer': 'the sum of the number of families record of all rows is 30630 .'} | round_eq { sum { all_rows ; number of families } ; 30630 } = true | the sum of the number of families record of all rows is 30630 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'number of families_4': 4, '30630_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'number of families_4': 'number of families', '30630_5': '30630'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'number of families_4': [0], '30630_5': [1]} | ['region of ussr', 'number of families', 'number of people', 'average family size', '% of total deportees'] | [['amur oblast', '2028', '5451', '2.7', '5.8'], ['irkutsk oblast', '8475', '25834', '3.0', '27.3'], ['krasnoyarsk krai', '3671', '13823', '3.8', '14.6'], ['novosibirsk oblast', '3152', '10064', '3.2', '10.6'], ['omsk oblast', '7944', '22542', '2.8', '23.8'], ['tomsk oblast', '5360', '16065', '3.0', '16.9']] |
television in italy | https://en.wikipedia.org/wiki/Television_in_Italy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15887683-19.html.csv | count | five of the television services in italy provide general television content . | {'scope': 'all', 'criterion': 'equal', 'value': 'general television', 'result': '5', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'content', 'general television'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose content record fuzzily matches to general television .', 'tostr': 'filter_eq { all_rows ; content ; general television }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; content ; general television } }', 'tointer': 'select the rows whose content record fuzzily matches to general television . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; content ; general television } } ; 5 } = true', 'tointer': 'select the rows whose content record fuzzily matches to general television . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; content ; general television } } ; 5 } = true | select the rows whose content record fuzzily matches to general television . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'content_5': 5, 'general television_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'content_5': 'content', 'general television_6': 'general television', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'content_5': [0], 'general television_6': [0], '5_7': [2]} | ['television service', 'country', 'language', 'content', 'hdtv', 'package / option'] | [['contotv 1', 'italy', 'italian', 'general television', 'no', 'qualsiasi'], ['contotv 2', 'italy', 'italian', 'general television', 'no', 'qualsiasi'], ['contotv 3', 'italy', 'italian', 'general television', 'no', 'qualsiasi'], ['contotv 4', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['contotv 5', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['teleitalia', 'italy', 'italian', 'general television', 'no', 'qualsiasi ( fta )'], ['teleitalia spot', 'italy', 'italian', 'general television', 'no', 'qualsiasi ( fta )'], ['d - xtv', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['r - light', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['sct', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['boy & boy', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['privã', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['themex', 'italy', 'italian', 'programmi per adulti 24h / 24', 'no', 'qualsiasi'], ['satisfaction hd', 'italy', 'italian', 'programmi per adulti 24h / 24', 'yes', 'qualsiasi']] |
list of boston celtics broadcasters | https://en.wikipedia.org/wiki/List_of_Boston_Celtics_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14902507-9.html.csv | count | craig mustard was studio host for boston celtics for a period of 5 years . | {'scope': 'all', 'criterion': 'equal', 'value': 'craig mustard', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'studio host', 'craig mustard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose studio host record fuzzily matches to craig mustard .', 'tostr': 'filter_eq { all_rows ; studio host ; craig mustard }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; studio host ; craig mustard } }', 'tointer': 'select the rows whose studio host record fuzzily matches to craig mustard . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; studio host ; craig mustard } } ; 5 } = true', 'tointer': 'select the rows whose studio host record fuzzily matches to craig mustard . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; studio host ; craig mustard } } ; 5 } = true | select the rows whose studio host record fuzzily matches to craig mustard . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'studio host_5': 5, 'craig mustard_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'studio host_5': 'studio host', 'craig mustard_6': 'craig mustard', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'studio host_5': [0], 'craig mustard_6': [0], '5_7': [2]} | ['year', 'flagship station', 'play - by - play', 'color commentator ( s )', 'studio host'] | [['1999 - 2000', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1998 - 99', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1997 - 98', 'weei', 'howard david', 'cedric maxwell', 'ted sarandis'], ['1996 - 97', 'weei', 'spencer ross', 'cedric maxwell', 'ted sarandis'], ['1995 - 96', 'wrko', 'spencer ross', 'cedric maxwell', 'ted sarandis'], ['1994 - 95', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1993 - 94', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1992 - 93', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1991 - 92', 'weei', 'glenn ordway', 'jerry sichting', 'craig mustard'], ['1990 - 91', 'weei', 'glenn ordway', 'doug brown', 'craig mustard']] |
1976 - 77 san antonio spurs season | https://en.wikipedia.org/wiki/1976%E2%80%9377_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16386910-2.html.csv | majority | the san antonio spurs were the visiting team for the majority of games . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'san antonio spurs', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'visitor', 'san antonio spurs'], 'result': True, 'ind': 0, 'tointer': 'for the visitor records of all rows , most of them fuzzily match to san antonio spurs .', 'tostr': 'most_eq { all_rows ; visitor ; san antonio spurs } = true'} | most_eq { all_rows ; visitor ; san antonio spurs } = true | for the visitor records of all rows , most of them fuzzily match to san antonio spurs . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'visitor_3': 3, 'san antonio spurs_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'visitor_3': 'visitor', 'san antonio spurs_4': 'san antonio spurs'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'visitor_3': [0], 'san antonio spurs_4': [0]} | ['date', 'visitor', 'score', 'home', 'record'] | [['october 22 , 1976', 'san antonio spurs', '121 - 118', 'philadelphia 76ers', '1 - 0'], ['october 23 , 1976', 'san antonio spurs', '98 - 117', 'new york knicks', '1 - 1'], ['october 26 , 1976', 'san antonio spurs', '114 - 122', 'atlanta hawks', '1 - 2'], ['october 27 , 1976', 'phoenix suns', '106 - 115', 'san antonio spurs', '2 - 2'], ['october 29 , 1976', 'san antonio spurs', '102 - 130', 'kansas city kings', '2 - 3'], ['october 30 , 1976', 'boston celtics', '126 - 117', 'san antonio spurs', '2 - 4']] |
albert county , new brunswick | https://en.wikipedia.org/wiki/Albert_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-170958-2.html.csv | comparative | among the parishes in albert county , hillsborough has a higher population compared to the parish of hopewell . | {'row_1': '2', 'row_2': '4', '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', 'official name', 'hillsborough'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose official name record fuzzily matches to hillsborough .', 'tostr': 'filter_eq { all_rows ; official name ; hillsborough }'}, 'population'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; official name ; hillsborough } ; population }', 'tointer': 'select the rows whose official name record fuzzily matches to hillsborough . take the population record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'official name', 'hopewell'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose official name record fuzzily matches to hopewell .', 'tostr': 'filter_eq { all_rows ; official name ; hopewell }'}, 'population'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; official name ; hopewell } ; population }', 'tointer': 'select the rows whose official name record fuzzily matches to hopewell . take the population record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; official name ; hillsborough } ; population } ; hop { filter_eq { all_rows ; official name ; hopewell } ; population } } = true', 'tointer': 'select the rows whose official name record fuzzily matches to hillsborough . take the population record of this row . select the rows whose official name record fuzzily matches to hopewell . take the population record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; official name ; hillsborough } ; population } ; hop { filter_eq { all_rows ; official name ; hopewell } ; population } } = true | select the rows whose official name record fuzzily matches to hillsborough . take the population record of this row . select the rows whose official name record fuzzily matches to hopewell . take the population 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, 'official name_7': 7, 'hillsborough_8': 8, 'population_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'official name_11': 11, 'hopewell_12': 12, 'population_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', 'official name_7': 'official name', 'hillsborough_8': 'hillsborough', 'population_9': 'population', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'official name_11': 'official name', 'hopewell_12': 'hopewell', 'population_13': 'population'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'official name_7': [0], 'hillsborough_8': [0], 'population_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'official name_11': [1], 'hopewell_12': [1], 'population_13': [3]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['coverdale', 'parish', '236.15', '4401', '769 of 5008'], ['hillsborough', 'parish', '303.73', '1395', '1684 of 5008'], ['elgin', 'parish', '519.38', '968', '2124 of 5008'], ['hopewell', 'parish', '149.32', '643', '2689 of 5008'], ['harvey', 'parish', '276.84', '376', '3372 of 5008']] |
1934 vfl season | https://en.wikipedia.org/wiki/1934_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790510-6.html.csv | count | in the 1934 vfl season , when the away team 's score was under 20 , there were 3 times when the crowd was under 20000 . | {'scope': 'subset', 'criterion': 'less_than', 'value': '20000', 'result': '3', 'col': '6', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '20'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'away team score', '20'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; away team score ; 20 }', 'tointer': 'select the rows whose away team score record is less than 20 .'}, 'crowd', '20000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose away team score record is less than 20 . among these rows , select the rows whose crowd record is less than 20000 .', 'tostr': 'filter_less { filter_less { all_rows ; away team score ; 20 } ; crowd ; 20000 }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_less { filter_less { all_rows ; away team score ; 20 } ; crowd ; 20000 } }', 'tointer': 'select the rows whose away team score record is less than 20 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_less { filter_less { all_rows ; away team score ; 20 } ; crowd ; 20000 } } ; 3 } = true', 'tointer': 'select the rows whose away team score record is less than 20 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 3 .'} | eq { count { filter_less { filter_less { all_rows ; away team score ; 20 } ; crowd ; 20000 } } ; 3 } = true | select the rows whose away team score record is less than 20 . among these rows , select the rows whose crowd record is less than 20000 . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_less_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'away team score_6': 6, '20_7': 7, 'crowd_8': 8, '20000_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_less_1': 'filter_less', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'away team score_6': 'away team score', '20_7': '20', 'crowd_8': 'crowd', '20000_9': '20000', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_less_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'away team score_6': [0], '20_7': [0], 'crowd_8': [1], '20000_9': [1], '3_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '14.17 ( 101 )', 'st kilda', '20.14 ( 134 )', 'mcg', '18102', '9 june 1934'], ['essendon', '14.11 ( 95 )', 'geelong', '11.16 ( 82 )', 'windy hill', '15000', '9 june 1934'], ['collingwood', '16.15 ( 111 )', 'fitzroy', '13.18 ( 96 )', 'victoria park', '22000', '9 june 1934'], ['carlton', '20.25 ( 145 )', 'north melbourne', '12.11 ( 83 )', 'princes park', '15000', '9 june 1934'], ['south melbourne', '9.10 ( 64 )', 'richmond', '16.12 ( 108 )', 'lake oval', '32000', '9 june 1934'], ['hawthorn', '11.11 ( 77 )', 'footscray', '10.11 ( 71 )', 'glenferrie oval', '8000', '9 june 1934']] |
catholic church by country | https://en.wikipedia.org/wiki/Catholic_Church_by_country | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1364343-4.html.csv | ordinal | south asia region has the 2nd highest percentage of global catholic population . | {'row': '3', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', '% of global catholic pop', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; % of global catholic pop ; 2 }'}, 'region'], 'result': 'south asia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; % of global catholic pop ; 2 } ; region }'}, 'south asia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; % of global catholic pop ; 2 } ; region } ; south asia } = true', 'tointer': 'select the row whose % of global catholic pop record of all rows is 2nd maximum . the region record of this row is south asia .'} | eq { hop { nth_argmax { all_rows ; % of global catholic pop ; 2 } ; region } ; south asia } = true | select the row whose % of global catholic pop record of all rows is 2nd maximum . the region record of this row is south asia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, '% of global catholic pop_5': 5, '2_6': 6, 'region_7': 7, 'south asia_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', '% of global catholic pop_5': '% of global catholic pop', '2_6': '2', 'region_7': 'region', 'south asia_8': 'south asia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], '% of global catholic pop_5': [0], '2_6': [0], 'region_7': [1], 'south asia_8': [2]} | ['region', 'total population', 'catholic', '% catholic', '% of global catholic pop'] | [['central asia', '92019166', '199086', '1.23 %', '0.01 %'], ['east asia', '1528384440', '13853142', '0.90 %', '1.28 %'], ['south asia', '1437326682', '20107050', '1.39 %', '1.87 %'], ['southeast asia', '571337070', '86701421', '15.17 %', '8.06 %'], ['total', '3629067358', '120860699', '3.33 %', '11.24 %']] |
list of rizzoli & isles episodes | https://en.wikipedia.org/wiki/List_of_Rizzoli_%26_Isles_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27969432-4.html.csv | unique | the episode of rizzoli & isles that was titled class action satisfaction , was the only episode that had an original air date in november . | {'scope': 'all', 'row': '9', 'col': '6', 'col_other': '3', 'criterion': 'equal', 'value': 'november', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'november'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to november .', 'tostr': 'filter_eq { all_rows ; original air date ; november }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; original air date ; november } }', 'tointer': 'select the rows whose original air date record fuzzily matches to november . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'november'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to november .', 'tostr': 'filter_eq { all_rows ; original air date ; november }'}, 'title'], 'result': 'class action satisfaction', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; original air date ; november } ; title }'}, 'class action satisfaction'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; original air date ; november } ; title } ; class action satisfaction }', 'tointer': 'the title record of this unqiue row is class action satisfaction .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; original air date ; november } } ; eq { hop { filter_eq { all_rows ; original air date ; november } ; title } ; class action satisfaction } } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to november . there is only one such row in the table . the title record of this unqiue row is class action satisfaction .'} | and { only { filter_eq { all_rows ; original air date ; november } } ; eq { hop { filter_eq { all_rows ; original air date ; november } ; title } ; class action satisfaction } } = true | select the rows whose original air date record fuzzily matches to november . there is only one such row in the table . the title record of this unqiue row is class action satisfaction . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'original air date_7': 7, 'november_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'class action satisfaction_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'original air date_7': 'original air date', 'november_8': 'november', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'class action satisfaction_10': 'class action satisfaction'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'original air date_7': [0], 'november_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'class action satisfaction_10': [3]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production', 'us viewers ( in millions )'] | [['26', '1', "what does n't kill you", 'michael katleman', 'janet tamaro', 'june 5 , 2012', '2 m5901', '5.62'], ['27', '2', 'dirty little secret', 'aaron lipstadt', 'steve lichtman & kiersten van home', 'june 12 , 2012', '2 m5902', '5.13'], ['28', '3', 'this is how a heart breaks', 'steve robin', 'david gould & sal calleros', 'june 19 , 2012', '2 m5903', '5.36'], ['29', '4', 'welcome to the dollhouse', 'mark haber', 'russell j grant & janet tamaro', 'june 26 , 2012', '2 m5904', '5.43'], ['30', '5', 'throwing down the gauntlet', 'jamie babbit', 'antoinette stella & janet tamaro', 'july 3 , 2012', '2 m5905', '5.32'], ['32', '7', 'crazy for you', 'frederick e o toye', 'antoinette stella & lindsay sturman', 'july 17 , 2012', '2 m5907', '5.84'], ['33', '8', 'cuts like a knife', 'randy zisk', 'david gould & sal calleros', 'july 24 , 2012', '2 m5908', '5.59'], ['34', '9', 'home town glory', 'milan cheylov', 'janet tamaro', 'july 31 , 2012', '2 m5909', '4.44'], ['36', '11', 'class action satisfaction', 'norman buckley', 'antoinette stella & lindsay sturman', 'november 27 , 2012', '2 m5911', '3.44'], ['37', '12', 'love the way you lie', 'mark harber', 'steve lichtman & david gould', 'december 4 , 2012', '2 m5912', '4.75']] |
1977 - 78 new york rangers season | https://en.wikipedia.org/wiki/1977%E2%80%9378_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17310913-3.html.csv | aggregation | in november 1977 , the new york rangers scored an average of 4.5 points per game . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '4.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '4.5', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '4.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 4.5 } = true', 'tointer': 'the average of the score record of all rows is 4.5 .'} | round_eq { avg { all_rows ; score } ; 4.5 } = true | the average of the score record of all rows is 4.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '4.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '4.5_5': '4.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '4.5_5': [1]} | ['game', 'november', 'opponent', 'score', 'record'] | [['11', '2', 'colorado rockies', '6 - 2', '4 - 6 - 1'], ['12', '4', 'vancouver canucks', '5 - 1', '5 - 6 - 1'], ['13', '5', 'los angeles kings', '3 - 1', '5 - 7 - 1'], ['14', '9', 'buffalo sabres', '8 - 4', '6 - 7 - 1'], ['15', '12', 'detroit red wings', '3 - 1', '6 - 8 - 1'], ['16', '13', 'atlanta flames', '5 - 2', '6 - 9 - 1'], ['17', '16', 'chicago black hawks', '5 - 2', '7 - 9 - 1'], ['18', '19', 'pittsburgh penguins', '5 - 5', '7 - 9 - 2'], ['19', '20', 'vancouver canucks', '3 - 0', '7 - 10 - 2'], ['20', '23', 'colorado rockies', '6 - 3', '8 - 10 - 2'], ['21', '26', 'boston bruins', '3 - 2', '8 - 11 - 2'], ['22', '27', 'buffalo sabres', '3 - 2', '8 - 12 - 2'], ['23', '30', 'st louis blues', '4 - 0', '9 - 12 - 2']] |
list of iron chef episodes | https://en.wikipedia.org/wiki/List_of_Iron_Chef_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23982399-12.html.csv | comparative | kobe beef was featured as the food item before rock crab was . | {'row_1': '2', 'row_2': '3', 'col': '2', 'col_other': '6', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'theme ingredient', 'kobe beef'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose theme ingredient record fuzzily matches to kobe beef .', 'tostr': 'filter_eq { all_rows ; theme ingredient ; kobe beef }'}, 'original airdate'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; theme ingredient ; kobe beef } ; original airdate }', 'tointer': 'select the rows whose theme ingredient record fuzzily matches to kobe beef . take the original airdate record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'theme ingredient', 'rock crab'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose theme ingredient record fuzzily matches to rock crab .', 'tostr': 'filter_eq { all_rows ; theme ingredient ; rock crab }'}, 'original airdate'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; theme ingredient ; rock crab } ; original airdate }', 'tointer': 'select the rows whose theme ingredient record fuzzily matches to rock crab . take the original airdate record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; theme ingredient ; kobe beef } ; original airdate } ; hop { filter_eq { all_rows ; theme ingredient ; rock crab } ; original airdate } } = true', 'tointer': 'select the rows whose theme ingredient record fuzzily matches to kobe beef . take the original airdate record of this row . select the rows whose theme ingredient record fuzzily matches to rock crab . take the original airdate record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; theme ingredient ; kobe beef } ; original airdate } ; hop { filter_eq { all_rows ; theme ingredient ; rock crab } ; original airdate } } = true | select the rows whose theme ingredient record fuzzily matches to kobe beef . take the original airdate record of this row . select the rows whose theme ingredient record fuzzily matches to rock crab . take the original airdate 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, 'theme ingredient_7': 7, 'kobe beef_8': 8, 'original airdate_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'theme ingredient_11': 11, 'rock crab_12': 12, 'original airdate_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', 'theme ingredient_7': 'theme ingredient', 'kobe beef_8': 'kobe beef', 'original airdate_9': 'original airdate', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'theme ingredient_11': 'theme ingredient', 'rock crab_12': 'rock crab', 'original airdate_13': 'original airdate'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'theme ingredient_7': [0], 'kobe beef_8': [0], 'original airdate_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'theme ingredient_11': [1], 'rock crab_12': [1], 'original airdate_13': [3]} | ['special', 'original airdate', 'iron chef', 'challenger', 'challenger specialty', 'theme ingredient', 'winner'] | [['millennium cup', 'january 5 , 2000', 'chen kenichi', 'zhao renliang ( 趙仁良 chō jinryō )', 'chinese ( beijing )', 'abalone', 'chen kenichi'], ['millennium cup', 'january 5 , 2000', 'rokusaburo michiba', 'dominique bouchet', 'french', 'kobe beef', 'rokusaburo michiba'], ['new york special', 'march 28 , 2000', 'masaharu morimoto', 'bobby flay', 'southwestern', 'rock crab', 'masaharu morimoto'], ['21st century battles', 'january 2 , 2001', 'hiroyuki sakai', 'toshirō kandagawa', 'japanese', 'red snapper', 'toshirō kandagawa'], ['21st century battles', 'january 2 , 2001', 'masaharu morimoto', 'bobby flay', 'southwestern', 'spiny lobster', 'bobby flay'], ['japan cup', 'january 2 , 2002', 'chen kenichi', 'yūichirō ebisu ( 胡 雄一郎 )', 'italian', 'king crab', 'chen kenichi'], ['japan cup', 'january 2 , 2002', 'kimio nonaga ( 野永喜三夫 )', 'takeshi tanabe ( 田辺 猛 )', 'japanese ( nonaga ) , french ( tanabe )', 'pacific bluefin tuna', 'kimio nonaga']] |
ik start | https://en.wikipedia.org/wiki/IK_Start | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1214850-1.html.csv | aggregation | over the season , ik start scored an aggregate total of 20-39 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '20-39', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'aggregate'], 'result': '20-39', 'ind': 0, 'tostr': 'sum { all_rows ; aggregate }'}, '20-39'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; aggregate } ; 20-39 } = true', 'tointer': 'the sum of the aggregate record of all rows is 20-39 .'} | round_eq { sum { all_rows ; aggregate } ; 20-39 } = true | the sum of the aggregate record of all rows is 20-39 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'aggregate_4': 4, '20-39_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'aggregate_4': 'aggregate', '20-39_5': '20-39'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'aggregate_4': [0], '20-39_5': [1]} | ['round', 'club', 'home', 'away', 'aggregate'] | [['1 . round', 'djurgården', '1 - 2', '0 - 5', '1 - 7'], ['1 . round', 'wacker innsbruck', '0 - 5', '1 - 2', '1 - 7'], ['1 . round', 'fram', '6 - 0', '2 - 0', '8 - 0'], ['2 . round', 'eintracht braunschweig', '1 - 0', '0 - 4', '1 - 4'], ['1 . round', 'esbjerg', '0 - 0', '0 - 1', '0 - 1'], ['1 . round', 'strasbourg', '1 - 2', '0 - 4', '1 - 6'], ['1 . round', 'az', '1 - 3', '0 - 1', '1 - 4'], ['1 . qualifying round', 'skála', '3 - 0', '1 - 0', '4 - 0'], ['2 . qualifying round', 'drogheda united', '1 - 0', '0 - 1', '1 - 1 ( 11 - 10 p )'], ['1 . round', 'ajax', '2 - 5', '0 - 4', '2 - 9']] |
2008 - 09 serie a | https://en.wikipedia.org/wiki/2008%E2%80%9309_Serie_A | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17043360-4.html.csv | majority | the majority of managers who were appointed were replacements for managers who had been sacked . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sacked', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'manner of departure', 'sacked'], 'result': True, 'ind': 0, 'tointer': 'for the manner of departure records of all rows , most of them fuzzily match to sacked .', 'tostr': 'most_eq { all_rows ; manner of departure ; sacked } = true'} | most_eq { all_rows ; manner of departure ; sacked } = true | for the manner of departure records of all rows , most of them fuzzily match to sacked . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'manner of departure_3': 3, 'sacked_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'manner of departure_3': 'manner of departure', 'sacked_4': 'sacked'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'manner of departure_3': [0], 'sacked_4': [0]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment'] | [['siena', 'mario beretta', 'contract expired', '27 may 2008', 'marco giampaolo', '27 may 2008'], ['cagliari', 'davide ballardini', 'contract expired', '27 may 2008', 'massimiliano allegri', '29 may 2008'], ['internazionale', 'roberto mancini', 'sacked', '29 may 2008', 'josé mourinho', '2 june 2008'], ['lecce', 'giuseppe papadopulo', 'contract expired', '23 june 2008', 'mario beretta', '23 june 2008'], ['palermo', 'stefano colantuono', 'sacked', '4 september 2008', 'davide ballardini', '4 september 2008'], ['bologna', 'daniele arrigoni', 'sacked', '3 november 2008', 'siniša mihajlović', '3 november 2008'], ['chievo verona', 'giuseppe iachini', 'sacked', '4 november 2008', 'domenico di carlo', '4 november 2008'], ['torino', 'gianni de biasi', 'sacked', '8 december 2008', 'walter novellino', '8 december 2008'], ['reggina', 'nevio orlandi', 'sacked', '16 december 2008', 'giuseppe pillon', '16 december 2008'], ['reggina', 'giuseppe pillon', 'sacked', '25 january 2009', 'nevio orlandi', '25 january 2009'], ['lecce', 'mario beretta', 'sacked', '9 march 2009', 'luigi de canio', '9 march 2009'], ['napoli', 'edoardo reja', 'sacked', '10 march 2009', 'roberto donadoni', '10 march 2009'], ['torino', 'walter novellino', 'sacked', '24 march 2009', 'giancarlo camolese', '24 march 2009'], ['bologna', 'siniša mihajlović', 'sacked', '14 april 2009', 'giuseppe papadopulo', '14 april 2009'], ['juventus', 'claudio ranieri', 'sacked', '18 may 2009', 'ciro ferrara', '18 may 2009']] |
lince ( tank ) | https://en.wikipedia.org/wiki/Lince_%28tank%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17733227-1.html.csv | unique | the m60a3 patton is the only tank to use a 105 mm m68 rifled tank - gun . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': '105 mm m68 rifled tank - gun', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'm60a3 patton', '105 mm m68 rifled tank - gun'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose m60a3 patton record fuzzily matches to 105 mm m68 rifled tank - gun .', 'tostr': 'filter_eq { all_rows ; m60a3 patton ; 105 mm m68 rifled tank - gun }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; m60a3 patton ; 105 mm m68 rifled tank - gun } } = true', 'tointer': 'select the rows whose m60a3 patton record fuzzily matches to 105 mm m68 rifled tank - gun . there is only one such row in the table .'} | only { filter_eq { all_rows ; m60a3 patton ; 105 mm m68 rifled tank - gun } } = true | select the rows whose m60a3 patton record fuzzily matches to 105 mm m68 rifled tank - gun . 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, 'm60a3 patton_4': 4, '105 mm m68 rifled tank - gun_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'm60a3 patton_4': 'm60a3 patton', '105 mm m68 rifled tank - gun_5': '105 mm m68 rifled tank - gun'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'm60a3 patton_4': [0], '105 mm m68 rifled tank - gun_5': [0]} | ['lince', 'leopard 2a4', 'leclerc', 'm1a1 abrams', 'm60a3 patton'] | [['t ( short tons )', 't ( short tons )', 't ( short tons )', 't ( short tons )', 't ( short tons )'], ['120 mm l / 44 smoothbore', '120 mm l / 44 smoothbore', '120 mmm l / 52 smoothbore', '120 mm l / 44 smoothbore', '105 mm m68 rifled tank - gun'], ['40 rounds', '42 rounds', '40 rounds', '40 rounds', '63 rounds'], ['km ( mi )', '-', 'km ( mi )', '-', 'km ( mi )']] |
1956 - 57 segunda división | https://en.wikipedia.org/wiki/1956%E2%80%9357_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17619574-2.html.csv | ordinal | in the 1956 - 57 segunda división , baracaldo ah had the 2nd highest goals against . | {'row': '18', 'col': '9', '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', 'goals against', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; goals against ; 2 }'}, 'club'], 'result': 'baracaldo ah', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; goals against ; 2 } ; club }'}, 'baracaldo ah'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; goals against ; 2 } ; club } ; baracaldo ah } = true', 'tointer': 'select the row whose goals against record of all rows is 2nd maximum . the club record of this row is baracaldo ah .'} | eq { hop { nth_argmax { all_rows ; goals against ; 2 } ; club } ; baracaldo ah } = true | select the row whose goals against record of all rows is 2nd maximum . the club record of this row is baracaldo ah . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'goals against_5': 5, '2_6': 6, 'club_7': 7, 'baracaldo ah_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'goals against_5': 'goals against', '2_6': '2', 'club_7': 'club', 'baracaldo ah_8': 'baracaldo ah'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'goals against_5': [0], '2_6': [0], 'club_7': [1], 'baracaldo ah_8': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'real gijón cf', '38', '62', '28', '6', '4', '107', '26', '+ 81'], ['2', 'cd sabadell cf', '38', '54', '24', '6', '8', '92', '39', '+ 53'], ['3', 'sd indauchu', '38', '48', '21', '6', '11', '72', '45', '+ 27'], ['4', 'real oviedo', '38', '46', '20', '6', '12', '77', '60', '+ 17'], ['5', 'deportivo alavés', '38', '43', '17', '9', '12', '61', '52', '+ 9'], ['6', 'cultural leonesa', '38', '41', '18', '5', '15', '63', '61', '+ 2'], ['7', 'real avilés cf', '38', '39', '17', '5', '16', '75', '60', '+ 15'], ['8', 'real santander', '38', '37', '15', '7', '16', '60', '62', '- 2'], ['9', 'gerona cf', '38', '37', '15', '7', '16', '54', '53', '+ 1'], ['10', 'sd eibar', '38', '36', '14', '8', '16', '63', '79', '- 16'], ['11', 'caudal deportivo', '38', '35', '16', '3', '19', '66', '72', '- 6'], ['12', 'ad rayo vallecano', '38', '35', '15', '5', '18', '45', '45', '0'], ['13', 'cd tarrasa', '38', '34', '13', '8', '17', '57', '60', '- 3'], ['14', 'club sestao', '38', '34', '13', '8', '17', '60', '67', '- 7'], ['15', 'cp la felguera', '38', '34', '15', '4', '19', '46', '62', '- 16'], ['16', 'club ferrol', '38', '33', '14', '5', '19', '51', '72', '- 21'], ['17', 'cd logroñés', '38', '32', '12', '8', '18', '44', '70', '- 26'], ['18', 'baracaldo ah', '38', '31', '12', '7', '19', '50', '83', '- 33'], ['19', 'burgos cf', '38', '30', '11', '8', '19', '46', '65', '- 19'], ['20', 'ud lérida', '38', '19', '8', '3', '27', '37', '93', '- 56']] |
list of radio stations in tamaulipas | https://en.wikipedia.org/wiki/List_of_radio_stations_in_Tamaulipas | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17982829-9.html.csv | majority | the majority of radio stations in tamaulipas are licensed in the city of nuevo laredo . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nuevo laredo', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'city of license', 'nuevo laredo'], 'result': True, 'ind': 0, 'tointer': 'for the city of license records of all rows , most of them fuzzily match to nuevo laredo .', 'tostr': 'most_eq { all_rows ; city of license ; nuevo laredo } = true'} | most_eq { all_rows ; city of license ; nuevo laredo } = true | for the city of license records of all rows , most of them fuzzily match to nuevo laredo . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'city of license_3': 3, 'nuevo laredo_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'city of license_3': 'city of license', 'nuevo laredo_4': 'nuevo laredo'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'city of license_3': [0], 'nuevo laredo_4': [0]} | ['frequency', 'power d / n', 'callsign', 'brand', 'city of license'] | [['790', '1 kw / 500w', 'xefe', 'la pura ley', 'nuevo laredo'], ['890', '10 / 1 kw', 'kvoz', 'la radio cristiana ( kczo )', 'laredo'], ['960', '5 / 1 kw', 'xek', 'la estación grande', 'nuevo laredo'], ['1000', '1 kw / 250w', 'xenlt', 'radio formula', 'nuevo laredo'], ['1090', '1 kw / 250w', 'xewl', 'w radio ( xew )', 'nuevo laredo'], ['1300', '1 kw / 500w', 'klar', 'radio poder', 'laredo'], ['1340', '1 / 1 kw', 'xebk', 'el norteñazo', 'nuevo laredo'], ['1370', '1 kw / 250w', 'xegnk', 'mariachi estéreo', 'nuevo laredo'], ['1410', '1 kw / 250w', 'xeas', 'ke buena xhpo', 'nuevo laredo'], ['1490', '1 / 1 kw', 'klnt', 'espn radio', 'laredo'], ['1550', '5 kw / 250w', 'xenu', 'la rancherita', 'nuevo laredo']] |
1991 national league championship series | https://en.wikipedia.org/wiki/1991_National_League_Championship_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1742998-1.html.csv | majority | most of the games in the 1991 national league championship series were played at three rivers stadium . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'three rivers stadium', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'three rivers stadium'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to three rivers stadium .', 'tostr': 'most_eq { all_rows ; location ; three rivers stadium } = true'} | most_eq { all_rows ; location ; three rivers stadium } = true | for the location records of all rows , most of them fuzzily match to three rivers stadium . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'three rivers stadium_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'three rivers stadium_4': 'three rivers stadium'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'three rivers stadium_4': [0]} | ['game', 'date', 'location', 'time', 'attendance'] | [['1', 'october 9', 'three rivers stadium', '2:51', '57347'], ['2', 'october 10', 'three rivers stadium', '2:46', '57533'], ['3', 'october 12', 'atlanta - fulton county stadium', '3:21', '50905'], ['4', 'october 13', 'atlanta - fulton county stadium', '3:43', '51109'], ['5', 'october 14', 'atlanta - fulton county stadium', '2:51', '51109'], ['6', 'october 16', 'three rivers stadium', '3:09', '54508'], ['7', 'october 17', 'three rivers stadium', '3:04', '46932']] |
afl records | https://en.wikipedia.org/wiki/List_of_VFL/AFL_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12161422-9.html.csv | ordinal | the 2nd highest margin for afl records was for the geelong club . | {'row': '2', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'margin', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; margin ; 2 }'}, 'club'], 'result': 'geelong', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; margin ; 2 } ; club }'}, 'geelong'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; margin ; 2 } ; club } ; geelong } = true', 'tointer': 'select the row whose margin record of all rows is 2nd maximum . the club record of this row is geelong .'} | eq { hop { nth_argmax { all_rows ; margin ; 2 } ; club } ; geelong } = true | select the row whose margin record of all rows is 2nd maximum . the club record of this row is geelong . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'margin_5': 5, '2_6': 6, 'club_7': 7, 'geelong_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', 'margin_5': 'margin', '2_6': '2', 'club_7': 'club', 'geelong_8': 'geelong'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'margin_5': [0], '2_6': [0], 'club_7': [1], 'geelong_8': [2]} | ['rank', 'margin', 'club', 'opponent', 'year', 'round', 'venue'] | [['1', '190', 'fitzroy', 'melbourne', '1979', '17', 'vfl park'], ['2', '186', 'geelong', 'melbourne', '2011', '19', 'kardinia park'], ['3', '178', 'collingwood', 'st kilda', '1979', '4', 'victoria park'], ['4', '171', 'south melbourne', 'st kilda', '1919', '12', 'lake oval'], ['5', '168', 'richmond', 'north melbourne', '1931', '2', 'punt road oval']] |
pedro rodríguez ( racing driver ) | https://en.wikipedia.org/wiki/Pedro_Rodr%C3%ADguez_%28racing_driver%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1156744-1.html.csv | comparative | pedro rodriguez scored more race points in 1967 than he did in 1965 . | {'row_1': '7', 'row_2': '3', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1967'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 1967 .', 'tostr': 'filter_eq { all_rows ; year ; 1967 }'}, 'pts'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 1967 } ; pts }', 'tointer': 'select the rows whose year record fuzzily matches to 1967 . take the pts record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '1965'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 1965 .', 'tostr': 'filter_eq { all_rows ; year ; 1965 }'}, 'pts'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 1965 } ; pts }', 'tointer': 'select the rows whose year record fuzzily matches to 1965 . take the pts record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 1967 } ; pts } ; hop { filter_eq { all_rows ; year ; 1965 } ; pts } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 1967 . take the pts record of this row . select the rows whose year record fuzzily matches to 1965 . take the pts record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; year ; 1967 } ; pts } ; hop { filter_eq { all_rows ; year ; 1965 } ; pts } } = true | select the rows whose year record fuzzily matches to 1967 . take the pts record of this row . select the rows whose year record fuzzily matches to 1965 . take the pts record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '1967_8': 8, 'pts_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '1965_12': 12, 'pts_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '1967_8': '1967', 'pts_9': 'pts', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '1965_12': '1965', 'pts_13': 'pts'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '1967_8': [0], 'pts_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '1965_12': [1], 'pts_13': [3]} | ['year', 'entrant', 'chassis', 'engine', 'pts'] | [['1963', 'team lotus', 'lotus 25', 'climax v8', '0'], ['1964', 'north american racing team', 'ferrari 156 aero', 'ferrari v6', '1'], ['1965', 'north american racing team', 'ferrari 1512', 'ferrari v12', '2'], ['1966', 'team lotus', 'lotus 33', 'climax v8', '0'], ['1966', 'team lotus', 'lotus f2 44', 'cosworth straight - 4', '0'], ['1966', 'team lotus', 'lotus 33', 'brm v8', '0'], ['1967', 'cooper car company', 'cooper t81', 'maserati v12', '15'], ['1968', 'owen racing organisation', 'brm p126', 'brm v12', '18'], ['1968', 'owen racing organisation', 'brm p133', 'brm v12', '18'], ['1968', 'owen racing organisation', 'brm p138', 'brm v12', '18'], ['1969', 'reg parnell racing', 'brm p126', 'brm v12', '3'], ['1969', 'scuderia ferrari', 'ferrari 312', 'ferrari v12', '3'], ['1969', 'north american racing team', 'ferrari 312', 'ferrari v12', '3'], ['1970', 'yardley team brm', 'brm p153', 'brm v12', '23'], ['1971', 'yardley team brm', 'brm p160', 'brm v12', '9']] |
2002 - 03 european challenge cup | https://en.wikipedia.org/wiki/2002%E2%80%9303_European_Challenge_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27986200-3.html.csv | unique | the match between montauban and borders was the only match with a points margin below 10 . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1,5', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points margin', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points margin record is less than 10 .', 'tostr': 'filter_less { all_rows ; points margin ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; points margin ; 10 } }', 'tointer': 'select the rows whose points margin record is less than 10 . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points margin', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points margin record is less than 10 .', 'tostr': 'filter_less { all_rows ; points margin ; 10 }'}, 'proceed to quarter - final'], 'result': 'montauban', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; points margin ; 10 } ; proceed to quarter - final }'}, 'montauban'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; points margin ; 10 } ; proceed to quarter - final } ; montauban }', 'tointer': 'the proceed to quarter - final record of this unqiue row is montauban .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points margin', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points margin record is less than 10 .', 'tostr': 'filter_less { all_rows ; points margin ; 10 }'}, 'eliminated from competition'], 'result': 'borders', 'ind': 4, 'tostr': 'hop { filter_less { all_rows ; points margin ; 10 } ; eliminated from competition }'}, 'borders'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_less { all_rows ; points margin ; 10 } ; eliminated from competition } ; borders }', 'tointer': 'the eliminated from competition record of this unqiue row is borders .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_less { all_rows ; points margin ; 10 } ; proceed to quarter - final } ; montauban } ; eq { hop { filter_less { all_rows ; points margin ; 10 } ; eliminated from competition } ; borders } }', 'tointer': 'the proceed to quarter - final record of this unqiue row is montauban . the eliminated from competition record of this unqiue row is borders .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_less { all_rows ; points margin ; 10 } } ; and { eq { hop { filter_less { all_rows ; points margin ; 10 } ; proceed to quarter - final } ; montauban } ; eq { hop { filter_less { all_rows ; points margin ; 10 } ; eliminated from competition } ; borders } } } = true', 'tointer': 'select the rows whose points margin record is less than 10 . there is only one such row in the table . the proceed to quarter - final record of this unqiue row is montauban . the eliminated from competition record of this unqiue row is borders .'} | and { only { filter_less { all_rows ; points margin ; 10 } } ; and { eq { hop { filter_less { all_rows ; points margin ; 10 } ; proceed to quarter - final } ; montauban } ; eq { hop { filter_less { all_rows ; points margin ; 10 } ; eliminated from competition } ; borders } } } = true | select the rows whose points margin record is less than 10 . there is only one such row in the table . the proceed to quarter - final record of this unqiue row is montauban . the eliminated from competition record of this unqiue row is borders . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_less_0': 0, 'all_rows_9': 9, 'points margin_10': 10, '10_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'proceed to quarter - final_12': 12, 'montauban_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'eliminated from competition_14': 14, 'borders_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_9': 'all_rows', 'points margin_10': 'points margin', '10_11': '10', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'proceed to quarter - final_12': 'proceed to quarter - final', 'montauban_13': 'montauban', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'eliminated from competition_14': 'eliminated from competition', 'borders_15': 'borders'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_less_0': [1, 2, 4], 'all_rows_9': [0], 'points margin_10': [0], '10_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'proceed to quarter - final_12': [2], 'montauban_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'eliminated from competition_14': [4], 'borders_15': [5]} | ['proceed to quarter - final', 'match points', 'aggregate score', 'points margin', 'eliminated from competition'] | [['london wasps', '4 - 0', '72 - 29', '43', 'nec harlequins'], ['stade français', '4 - 0', '55 - 12', '43', 'bordeaux - bègles'], ['saracens', '4 - 0', '46 - 25', '21', 'colomiers'], ['montauban', '4 - 0', '31 - 22', '9', 'borders'], ['pontypridd', '3 - 1', '56 - 42', '14', 'leeds tykes'], ['bath', '2 - 2', '64 - 38', '26', 'bridgend'], ['newcastle falcons', '2 - 2', '43 - 32', '11', 'benetton treviso']] |
kansas jayhawk community college conference | https://en.wikipedia.org/wiki/Kansas_Jayhawk_Community_College_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12434380-2.html.csv | superlative | garden city community college was the earliest to be established among the others . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'founded'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; founded }'}, 'institution'], 'result': 'garden city community college', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; founded } ; institution }'}, 'garden city community college'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; founded } ; institution } ; garden city community college } = true', 'tointer': 'select the row whose founded record of all rows is minimum . the institution record of this row is garden city community college .'} | eq { hop { argmin { all_rows ; founded } ; institution } ; garden city community college } = true | select the row whose founded record of all rows is minimum . the institution record of this row is garden city community college . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'founded_5': 5, 'institution_6': 6, 'garden city community college_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'founded_5': 'founded', 'institution_6': 'institution', 'garden city community college_7': 'garden city community college'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'founded_5': [0], 'institution_6': [1], 'garden city community college_7': [2]} | ['institution', 'main campus location', 'founded', 'mascot', 'school colors'] | [['barton community college', 'great bend', '1969', 'cougars', 'blue & gold'], ['butler community college', 'el dorado', '1927', 'grizzlies', 'purple & vegas gold'], ['cloud county community college', 'concordia', '1965', 'thunderbirds', 'black & gold'], ['colby community college', 'colby', '1964', 'trojans', 'blue & white'], ['dodge city community college', 'dodge city', '1935', 'conquistadors', 'purple & gold'], ['garden city community college', 'garden city', '1919', 'broncbusters', 'brown , gold & white'], ['hutchinson community college', 'hutchinson', '1928', 'blue dragons', 'blue & red'], ['pratt community college', 'pratt', '1938', 'beavers', 'royal blue & white'], ['seward county community college', 'liberal', '1969', 'saints', 'green & white']] |
mauro baldi | https://en.wikipedia.org/wiki/Mauro_Baldi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1226503-1.html.csv | aggregation | from 1982 to 1985 , mauro baldi scored an average of 1.4 points during his formula one races in that period . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '1.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '1.4', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '1.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 1.4 } = true', 'tointer': 'the average of the points record of all rows is 1.4 .'} | round_eq { avg { all_rows ; points } ; 1.4 } = true | the average of the points record of all rows is 1.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '1.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '1.4_5': '1.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '1.4_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1982', 'arrows racing team', 'arrows a4', 'cosworth v8', '2'], ['1982', 'arrows racing team', 'arrows a5', 'cosworth v8', '2'], ['1983', 'marlboro team alfa romeo', 'alfa romeo 183t', 'alfa romeo v8', '3'], ['1984', 'spirit racing', 'spirit 101', 'hart straight - 4', '0'], ['1985', 'spirit enterprises ltd', 'spirit 101d', 'hart straight - 4', '0']] |
chris van der drift | https://en.wikipedia.org/wiki/Chris_van_der_Drift | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16864452-1.html.csv | count | chris van der drift did twenty races in two different years . | {'scope': 'all', 'criterion': 'equal', 'value': '20', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'races', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose races record is equal to 20 .', 'tostr': 'filter_eq { all_rows ; races ; 20 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; races ; 20 } }', 'tointer': 'select the rows whose races record is equal to 20 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; races ; 20 } } ; 2 } = true', 'tointer': 'select the rows whose races record is equal to 20 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; races ; 20 } } ; 2 } = true | select the rows whose races record is equal to 20 . 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, 'races_5': 5, '20_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'races_5': 'races', '20_6': '20', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'races_5': [0], '20_6': [0], '2_7': [2]} | ['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position'] | [['2004', 'formula bmw adac', 'team rosberg', '20', '0', '0', '0', '8', '168', '4th'], ['2005', 'formula bmw adac', 'team rosberg', '20', '1', '0', '1', '5', '149', '4th'], ['2006', 'formula renault 2.0 eurocup', 'jd motorsport', '14', '2', '2', '1', '6', '91', '2nd'], ['2006', 'formula renault 2.0 nec', 'jd motorsport', '14', '4', '7', '4', '7', '267', '2nd'], ['2007', 'international formula master', 'jd motorsport', '16', '2', '1', '2', '7', '65', '2nd'], ['2008', 'international formula master', 'jd motorsport', '16', '6', '6', '8', '10', '101', '1st'], ['2008 - 09', 'gp2 asia series', 'trident racing', '3', '0', '0', '0', '0', '5', '18th'], ['2008 - 09', 'a1 grand prix', 'new zealand', '4', '0', '0', '0', '0', '36', '7th'], ['2009', 'formula renault 3.5 series', 'epsilon euskadi', '17', '0', '0', '0', '1', '41', '11th'], ['2010', 'superleague formula', 'olympiacos cfp', '18', '4', '2', '3', '10', '653', '4th'], ['2010', 'superleague formula', 'galatasaray', '3', '0', '0', '0', '0', '358', '13th'], ['2011', 'superleague formula', 'new zealand', '3', '0', '0', '0', '0', '116', '7th'], ['2011', 'formula renault 3.5 series', 'mofaz racing', '7', '0', '0', '0', '1', '43', '12th'], ['2012', 'auto gp world series', 'manor mp motorsport', '12', '1', '0', '0', '4', '127', '4th']] |
thai clubs in the afc cup | https://en.wikipedia.org/wiki/Thai_clubs_in_the_AFC_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16707879-4.html.csv | unique | muangthon united vs. persiwa wamena was the only game in the thai clubs in the afc club to have a score of 4:1 . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2,4', 'criterion': 'equal', 'value': '4:1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '4:1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 4:1 .', 'tostr': 'filter_eq { all_rows ; score ; 4:1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; 4:1 } }', 'tointer': 'select the rows whose score record fuzzily matches to 4:1 . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '4:1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 4:1 .', 'tostr': 'filter_eq { all_rows ; score ; 4:1 }'}, 'team 1'], 'result': 'muangthong united', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; 4:1 } ; team 1 }'}, 'muangthong united'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; 4:1 } ; team 1 } ; muangthong united }', 'tointer': 'the team 1 record of this unqiue row is muangthong united .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '4:1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 4:1 .', 'tostr': 'filter_eq { all_rows ; score ; 4:1 }'}, 'team 2'], 'result': 'persiwa wamena', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; score ; 4:1 } ; team 2 }'}, 'persiwa wamena'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; 4:1 } ; team 2 } ; persiwa wamena }', 'tointer': 'the team 2 record of this unqiue row is persiwa wamena .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; score ; 4:1 } ; team 1 } ; muangthong united } ; eq { hop { filter_eq { all_rows ; score ; 4:1 } ; team 2 } ; persiwa wamena } }', 'tointer': 'the team 1 record of this unqiue row is muangthong united . the team 2 record of this unqiue row is persiwa wamena .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; score ; 4:1 } } ; and { eq { hop { filter_eq { all_rows ; score ; 4:1 } ; team 1 } ; muangthong united } ; eq { hop { filter_eq { all_rows ; score ; 4:1 } ; team 2 } ; persiwa wamena } } } = true', 'tointer': 'select the rows whose score record fuzzily matches to 4:1 . there is only one such row in the table . the team 1 record of this unqiue row is muangthong united . the team 2 record of this unqiue row is persiwa wamena .'} | and { only { filter_eq { all_rows ; score ; 4:1 } } ; and { eq { hop { filter_eq { all_rows ; score ; 4:1 } ; team 1 } ; muangthong united } ; eq { hop { filter_eq { all_rows ; score ; 4:1 } ; team 2 } ; persiwa wamena } } } = true | select the rows whose score record fuzzily matches to 4:1 . there is only one such row in the table . the team 1 record of this unqiue row is muangthong united . the team 2 record of this unqiue row is persiwa wamena . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'score_10': 10, '4:1_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'team 1_12': 12, 'muangthong united_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'team 2_14': 14, 'persiwa wamena_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'score_10': 'score', '4:1_11': '4:1', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'team 1_12': 'team 1', 'muangthong united_13': 'muangthong united', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'team 2_14': 'team 2', 'persiwa wamena_15': 'persiwa wamena'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'score_10': [0], '4:1_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'team 1_12': [2], 'muangthong united_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'team 2_14': [4], 'persiwa wamena_15': [5]} | ['season', 'team 1', 'score', 'team 2', 'venue'] | [['2010', 'south china', '0:0', 'muangthong united', 'hong kong stadium , hong kong'], ['2010', 'muangthong united', '3:1', 'vb sports club', 'yamaha stadium ( thailand )'], ['2010', 'muangthong united', '4:1', 'persiwa wamena', 'yamaha stadium ( thailand )'], ['2010', 'vb sports club', '2:3', 'muangthong united', 'national stadium , maldives'], ['2010', 'muangthong united', '0:1', 'south china', 'surakul stadium , thailand'], ['2010', 'persiwa wamena', '2:2', 'muangthong united', 'gajayana stadium , indonesia'], ['2010', 'al - rayyan', '1:1 ( aet ) ( 2:4 p )', 'muangthong united', 'umm - affai stadium , qatar'], ['2010', 'al - karamah', '1:0', 'muangthong united', 'khaled bin walid stadium , syria'], ['2010', 'muangthong united', '2:0', 'al - karamah', 'yamaha stadium ( thailand )'], ['2010', 'muangthong united', '1:0', 'al - ittihad', 'yamaha stadium ( thailand )'], ['2010', 'al - ittihad', '2:0', 'muangthong united', 'aleppo international stadium , syria'], ['2011', 'muangthong united', '4:0', 't & t hanoi', 'scg stadium , thailand'], ['2011', 'tampines rovers', '1:1', 'muangthong united', 'jalan besar stadium , singapore'], ['2011', 'muangthong united', '1:0', 'victory sc', 'scg stadium , thailand'], ['2011', 'victory sc', '0:4', 'muangthong united', 'national stadium , maldives'], ['2011', 't & t hanoi', '0:0', 'muangthong united', 'hang day stadium , vietnam'], ['2011', 'muangthong united', '4:0', 'tampines rovers', 'scg stadium , thailand'], ['2011', 'muangthong united', '4:0', 'al ahed', 'scg stadium , thailand'], ['2011', 'kuwait sc', '1:0', 'muangthong united', 'al kuwait sports club stadium , kuwait'], ['2011', 'muangthong united', '0:0', 'kuwait sc', 'scg stadium , thailand']] |
2008 - 09 boston celtics season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17140608-6.html.csv | count | in december of the 2008 - 09 season , the boston celtics played against portland 2 times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'portland', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'portland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to portland .', 'tostr': 'filter_eq { all_rows ; team ; portland }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; team ; portland } }', 'tointer': 'select the rows whose team record fuzzily matches to portland . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; team ; portland } } ; 2 } = true', 'tointer': 'select the rows whose team record fuzzily matches to portland . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; team ; portland } } ; 2 } = true | select the rows whose team record fuzzily matches to portland . 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, 'team_5': 5, 'portland_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', 'team_5': 'team', 'portland_6': 'portland', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'team_5': [0], 'portland_6': [0], '2_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['19', 'december 1', 'orlando', 'w 107 - 88 ( ot )', 'paul pierce ( 24 )', 'kendrick perkins ( 13 )', 'rajon rondo ( 12 )', 'td banknorth garden 18624', '17 - 2'], ['20', 'december 3', 'indiana', 'w 114 - 96 ( ot )', 'ray allen ( 31 )', 'kevin garnett ( 14 )', 'rajon rondo ( 17 )', 'td banknorth garden 18624', '18 - 2'], ['21', 'december 5', 'portland', 'w 93 - 78 ( ot )', 'ray allen ( 19 )', 'kendrick perkins ( 12 )', 'rajon rondo ( 7 )', 'td banknorth garden 18624', '19 - 2'], ['22', 'december 7', 'indiana', 'w 122 - 117 ( ot )', 'ray allen ( 35 )', 'kevin garnett ( 20 )', 'paul pierce ( 8 )', 'conseco fieldhouse 16102', '20 - 2'], ['23', 'december 11', 'washington', 'w 122 - 88 ( ot )', 'ray allen , paul pierce ( 22 )', 'kevin garnett ( 12 )', 'paul pierce ( 8 )', 'verizon center 20173', '21 - 2'], ['24', 'december 12', 'new orleans', 'w 94 - 82 ( ot )', 'paul pierce ( 28 )', 'kendrick perkins ( 13 )', 'paul pierce ( 6 )', 'td banknorth garden 18624', '22 - 2'], ['25', 'december 15', 'utah', 'w 100 - 91 ( ot )', 'rajon rondo ( 25 )', 'kendrick perkins ( 14 )', 'rajon rondo ( 8 )', 'td banknorth garden 18624', '23 - 2'], ['26', 'december 17', 'atlanta', 'w 88 - 85 ( ot )', 'kevin garnett , paul pierce ( 18 )', 'kendrick perkins ( 10 )', 'rajon rondo ( 7 )', 'philips arena 18729', '24 - 2'], ['27', 'december 19', 'chicago', 'w 126 - 108 ( ot )', 'ray allen ( 27 )', 'kendrick perkins ( 8 )', 'rajon rondo ( 15 )', 'td banknorth garden 18624', '25 - 2'], ['28', 'december 21', 'new york', 'w 124 - 105 ( ot )', 'rajon rondo ( 26 )', 'kendrick perkins ( 12 )', 'kevin garnett ( 8 )', 'td banknorth garden 18624', '26 - 2'], ['29', 'december 23', 'philadelphia', 'w 110 - 91 ( ot )', 'kevin garnett , rajon rondo ( 18 )', 'kendrick perkins ( 11 )', 'paul pierce ( 7 )', 'td banknorth garden 18624', '27 - 2'], ['30', 'december 25', 'la lakers', 'l 83 - 92 ( ot )', 'kevin garnett ( 22 )', 'paul pierce ( 10 )', 'rajon rondo ( 12 )', 'staples center 18997', '27 - 3'], ['31', 'december 26', 'golden state', 'l 89 - 99 ( ot )', 'paul pierce ( 21 )', 'rajon rondo ( 10 )', 'rajon rondo ( 9 )', 'oracle arena 19596', '27 - 4'], ['32', 'december 28', 'sacramento', 'w 108 - 63 ( ot )', 'kevin garnett ( 21 )', 'kendrick perkins ( 12 )', 'rajon rondo ( 6 )', 'arco arena 16029', '28 - 4'], ['33', 'december 30', 'portland', 'l 86 - 91 ( ot )', 'paul pierce ( 28 )', 'kevin garnett ( 8 )', 'rajon rondo ( 7 )', 'rose garden 20651', '28 - 5']] |
art competitions at the 1928 summer olympics | https://en.wikipedia.org/wiki/Art_competitions_at_the_1928_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16574447-6.html.csv | count | in art competitions at the 1928 summer olympics , three countries won 1 bronze medal . | {'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'bronze', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose bronze record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; bronze ; 1 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; bronze ; 1 } }', 'tointer': 'select the rows whose bronze record is equal to 1 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; bronze ; 1 } } ; 3 } = true', 'tointer': 'select the rows whose bronze record is equal to 1 . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; bronze ; 1 } } ; 3 } = true | select the rows whose bronze record is equal to 1 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'bronze_5': 5, '1_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'bronze_5': 'bronze', '1_6': '1', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'bronze_5': [0], '1_6': [0], '3_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'netherlands ( ned )', '2', '1', '1', '4'], ['2', 'germany ( ger )', '1', '2', '5', '8'], ['3', 'france ( fra )', '1', '2', '1', '4'], ['4', 'great britain ( gbr )', '1', '1', '0', '2'], ['5', 'poland ( pol )', '1', '0', '1', '2'], ['6', 'austria ( aut )', '1', '0', '0', '1'], ['6', 'hungary ( hun )', '1', '0', '0', '1'], ['6', 'luxembourg ( lux )', '1', '0', '0', '1'], ['9', 'switzerland ( sui )', '0', '2', '0', '2'], ['10', 'denmark ( den )', '0', '1', '2', '3'], ['11', 'italy ( ita )', '0', '1', '0', '1']] |
2009 - 10 alabama crimson tide men 's basketball team | https://en.wikipedia.org/wiki/2009%E2%80%9310_Alabama_Crimson_Tide_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25360865-1.html.csv | superlative | anthony brock was the shortest member of the 2009-2010 alabama crimson tide men 's basketball team . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'height'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; height }'}, 'name'], 'result': 'anthony brock', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; height } ; name }'}, 'anthony brock'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; height } ; name } ; anthony brock } = true', 'tointer': 'select the row whose height record of all rows is minimum . the name record of this row is anthony brock .'} | eq { hop { argmin { all_rows ; height } ; name } ; anthony brock } = true | select the row whose height record of all rows is minimum . the name record of this row is anthony brock . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'height_5': 5, 'name_6': 6, 'anthony brock_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'height_5': 'height', 'name_6': 'name', 'anthony brock_7': 'anthony brock'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'height_5': [0], 'name_6': [1], 'anthony brock_7': [2]} | ['', 'name', 'position', 'height', 'weight', 'year', 'home town', 'last school'] | [['1', 'anthony brock', 'guard', '5 - 9', '165', 'senior', 'little rock , ark', 'itawamba cc'], ['2', 'mikhail torrance', 'guard', '6 - 5', '210', 'senior', 'eight mile , ala', 'mary montgomery hs'], ['5', 'tony mitchell', 'forward', '6 - 6', '185', 'freshman', 'swainsboro , ga', 'central park christian hs'], ['10', 'ben eblen', 'guard', '6 - 1', '180', 'freshman', 'isle of palms , sc', 'florida air academy'], ['20', 'greg cage', 'guard', '6 - 4', '212', 'senior', 'indianapolis , ind', 'bishop chatard hs'], ['21', 'senario hillman', 'guard', '6 - 1', '192', 'junior', 'irwinton , ga', 'wilkinson county hs'], ['23', 'demetrius jemison', 'forward', '6 - 8', '240', 'senior', 'birmingham , ala', 'huffman hs'], ['24', 'charvez davis', 'guard', '6 - 3', '190', 'junior', 'montgomery , ala', 'northwest florida state college'], ['25', 'andrew steele', 'guard', '6 - 3', '215', 'sophomore', 'birmingham , ala', 'john carroll hs'], ['32', 'jamychal green', 'forward', '6 - 9', '220', 'sophomore', 'montgomery , ala', 'st jude hs'], ['40', 'justin knox', 'forward', '6 - 9', '240', 'junior', 'tuscaloosa , ala', 'central hs']] |
1959 - 60 segunda división | https://en.wikipedia.org/wiki/1959%E2%80%9360_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17710217-2.html.csv | comparative | the club cd sabadell cf had more wins than the club deportivo alavés . | {'row_1': '7', 'row_2': '13', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'cd sabadell cf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to cd sabadell cf .', 'tostr': 'filter_eq { all_rows ; club ; cd sabadell cf }'}, 'wins'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; cd sabadell cf } ; wins }', 'tointer': 'select the rows whose club record fuzzily matches to cd sabadell cf . take the wins record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'deportivo alavés'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to deportivo alavés .', 'tostr': 'filter_eq { all_rows ; club ; deportivo alavés }'}, 'wins'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; deportivo alavés } ; wins }', 'tointer': 'select the rows whose club record fuzzily matches to deportivo alavés . take the wins record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; club ; cd sabadell cf } ; wins } ; hop { filter_eq { all_rows ; club ; deportivo alavés } ; wins } } = true', 'tointer': 'select the rows whose club record fuzzily matches to cd sabadell cf . take the wins record of this row . select the rows whose club record fuzzily matches to deportivo alavés . take the wins record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; club ; cd sabadell cf } ; wins } ; hop { filter_eq { all_rows ; club ; deportivo alavés } ; wins } } = true | select the rows whose club record fuzzily matches to cd sabadell cf . take the wins record of this row . select the rows whose club record fuzzily matches to deportivo alavés . take the wins 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, 'club_7': 7, 'cd sabadell cf_8': 8, 'wins_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'club_11': 11, 'deportivo alavés_12': 12, 'wins_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', 'club_7': 'club', 'cd sabadell cf_8': 'cd sabadell cf', 'wins_9': 'wins', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'club_11': 'club', 'deportivo alavés_12': 'deportivo alavés', 'wins_13': 'wins'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'club_7': [0], 'cd sabadell cf_8': [0], 'wins_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'club_11': [1], 'deportivo alavés_12': [1], 'wins_13': [3]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'real santander', '30', '42', '17', '8', '5', '63', '28', '+ 35'], ['2', 'rc celta de vigo', '30', '40', '18', '4', '8', '63', '37', '+ 26'], ['3', 'cd orense', '30', '37', '15', '7', '8', '56', '41', '+ 15'], ['4', 'deportivo la coruña', '30', '35', '16', '3', '11', '56', '47', '+ 9'], ['5', 'real gijón', '30', '32', '14', '4', '12', '56', '44', '+ 12'], ['6', 'cd tarrasa', '30', '31', '12', '7', '11', '47', '44', '+ 3'], ['7', 'cd sabadell cf', '30', '31', '13', '5', '12', '52', '41', '+ 11'], ['8', 'sd indautxu', '30', '29', '13', '3', '14', '56', '54', '+ 2'], ['9', 'baracaldo ah', '30', '29', '11', '7', '12', '53', '51', '+ 2'], ['10', 'cd condal', '30', '29', '11', '7', '12', '46', '45', '+ 1'], ['11', 'cd basconia', '30', '27', '11', '5', '14', '41', '57', '- 16'], ['12', 'cultural leonesa', '30', '27', '10', '7', '13', '47', '61', '- 14'], ['13', 'deportivo alavés', '30', '24', '8', '8', '14', '44', '70', '- 26'], ['14', 'club sestao', '30', '24', '9', '6', '15', '30', '47', '- 17'], ['15', 'real avilés cf', '30', '22', '6', '10', '14', '38', '52', '- 14'], ['16', 'club ferrol', '30', '21', '9', '3', '18', '50', '79', '- 29']] |
2008 - 09 kansas jayhawks men 's basketball team | https://en.wikipedia.org/wiki/2008%E2%80%9309_Kansas_Jayhawks_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17728794-2.html.csv | majority | on the 2008-09 kansas jayhawks men 's basketball team , most players were 200 or more pounds . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '200', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'weight', '200'], 'result': True, 'ind': 0, 'tointer': 'for the weight records of all rows , most of them are greater than or equal to 200 .', 'tostr': 'most_greater_eq { all_rows ; weight ; 200 } = true'} | most_greater_eq { all_rows ; weight ; 200 } = true | for the weight records of all rows , most of them are greater than or equal to 200 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'weight_3': 3, '200_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'weight_3': 'weight', '200_4': '200'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'weight_3': [0], '200_4': [0]} | ['name', 'position', 'height', 'weight', 'year', 'home town'] | [['cole aldrich', 'center', '6 - 11', '245', 'sophomore', 'bloomington , mn'], ['tyrone appleton', 'guard', '6 - 3', '190', 'junior', 'midland , texas'], ['brennan bechard', 'guard', '6 - 0', '183', 'senior', 'lawrence , ks'], ['chase buford', 'guard', '6 - 3', '200', 'sophomore', 'san antonio , texas'], ['sherron collins', 'guard', '5 - 11', '200', 'junior', 'chicago , il'], ['jordan juenemann', 'guard', '6 - 4', '195', 'freshman', 'hays , ks'], ['matt kleinmann', 'center', '6 - 10', '247', 'senior', 'overland park , ks'], ['mario little', 'forward', '6 - 5', '210', 'junior', 'marianna , fl'], ['brady morningstar', 'guard', '6 - 3', '185', 'sophomore', 'lawrence , ks'], ['marcus morris', 'forward', '6 - 8', '230', 'freshman', 'pennsauken , nj'], ['markieff morris', 'forward', '6 - 9', '220', 'freshman', 'pennsauken , nj'], ['tyrel reed', 'guard', '6 - 3', '180', 'sophomore', 'burlington , ks'], ['travis releford', 'guard', '6 - 5', '190', 'freshman', 'shawnee mission , ks'], ['tyshawn taylor', 'guard', '6 - 3', '160', 'freshman', 'jersey city , nj'], ['conner teahan', 'guard', '6 - 5', '200', 'sophomore', 'leawood , ks'], ['quintrell thomas', 'forward', '6 - 8', '225', 'freshman', 'elizabeth , nj']] |
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