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2005 pga championship | https://en.wikipedia.org/wiki/2005_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12512153-6.html.csv | superlative | in the 2005 pga championship , davis love iii ranks the highest . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'place'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; place }'}, 'player'], 'result': 'davis love iii', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; place } ; player }'}, 'davis love iii'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; place } ; player } ; davis love iii } = true', 'tointer': 'select the row whose place record of all rows is minimum . the player record of this row is davis love iii .'} | eq { hop { argmin { all_rows ; place } ; player } ; davis love iii } = true | select the row whose place record of all rows is minimum . the player record of this row is davis love iii . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'place_5': 5, 'player_6': 6, 'davis love iii_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'place_5': 'place', 'player_6': 'player', 'davis love iii_7': 'davis love iii'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'place_5': [0], 'player_6': [1], 'davis love iii_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'davis love iii', 'united states', '68 + 68 + 68 = 204', '- 6'], ['t1', 'phil mickelson', 'united states', '67 + 65 + 72 = 204', '- 6'], ['3', 'thomas bjørn', 'denmark', '71 + 71 + 63 = 205', '- 5'], ['t4', 'stuart appleby', 'australia', '67 + 70 + 69 = 206', '- 4'], ['t4', 'steve elkington', 'australia', '68 + 70 + 68 = 206', '- 4'], ['t4', 'pat perez', 'united states', '68 + 71 + 67 = 206', '- 4'], ['t4', 'vijay singh', 'fiji', '70 + 67 + 69 = 206', '- 4'], ['t8', 'jason bohn', 'united states', '71 + 68 + 68 = 207', '- 3'], ['t8', 'ben curtis', 'united states', '67 + 73 + 67 = 207', '- 3'], ['t8', 'retief goosen', 'south africa', '68 + 70 + 69 = 207', '- 3'], ['t8', 'greg owen', 'england', '68 + 69 + 70 = 207', '- 3'], ['t8', 'lee westwood', 'england', '68 + 68 + 71 = 207', '- 3']] |
kuwait at the 2008 summer paralympics | https://en.wikipedia.org/wiki/Kuwait_at_the_2008_Summer_Paralympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19398910-4.html.csv | majority | the majority of the atheles belong to the class cat a. | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'cat a', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'class', 'cat a'], 'result': True, 'ind': 0, 'tointer': 'for the class records of all rows , most of them fuzzily match to cat a .', 'tostr': 'most_eq { all_rows ; class ; cat a } = true'} | most_eq { all_rows ; class ; cat a } = true | for the class records of all rows , most of them fuzzily match to cat a . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'class_3': 3, 'cat a_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'class_3': 'class', 'cat a_4': 'cat a'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'class_3': [0], 'cat a_4': [0]} | ['athlete', 'class', 'event', 'bout 1', 'bout 2', 'bout 3', 'bout 4', 'bout 5', 'bout 6', 'rank', '1 / 8 finals', 'quarterfinals', 'semifinals'] | [['abdullah alhaddad', 'cat a', 'foil', 'pender ( pol ) l 3 - 5', 'maillard ( fra ) l 1 - 5', 'mato ( hun ) l 1 - 5', 'pellegrini ( ita ) l 4 - 5', 'andreev ( rus ) w 5 - 2', 'n / a', '5 q', 'pender ( pol ) l 6 - 15', 'did not advance', 'did not advance'], ['abdullah alhaddad', 'cat a', 'épée', 'pylarinos ( gre ) w 5 - 3', 'davydenko ( ukr ) l 1 - 5', 'serafini ( ita ) w 5 - 1', 'maillard ( fra ) l 4 - 5', 'saengsawang ( tha ) w 5 - 4', 'sanchez ( esp ) w 5 - 0', '3 q', 'saengsawang ( tha ) l 9 - 15', 'did not advance', 'did not advance'], ['tariq alqallaf', 'cat a', 'foil', 'saengsawang ( tha ) w 5 - 1', 'zhang ( chn ) l 0 - 5', 'betti ( ita ) l 0 - 5', 'horvath ( hun ) w 5 - 4', 'granell ( esp ) w 5 - 0', 'andree ( ger ) w 5 - 1', '3 q', 'bazhukov ( ukr ) w 15 - 9', 'ye ( chn ) l 6 - 15', 'did not advance'], ['tariq alqallaf', 'cat a', 'épée', 'horvath ( hun ) w 5 - 1', 'stanczuk ( pol ) w 5 - 3', 'wong ( hkg ) l 3 - 5', 'tian ( chn ) l 0 - 5', 'betti ( ita ) l 0 - 5', 'n / a', '5 q', 'maillard ( fra ) l 7 - 15', 'did not advance', 'did not advance'], ['abdulwahab alsaedi', 'cat b', 'foil', 'fawcett ( gbr ) w 5 - 2', 'francois ( fra ) l 3 - 5', 'rodgers ( usa ) l 4 - 5', 'datsko ( ukr ) l 4 - 5', 'czop ( pol ) l 2 - 5', 'n / a', '5 q', 'hui ( hkg ) l 3 - 15', 'did not advance', 'did not advance'], ['abdulwahab alsaedi', 'cat b', 'épée', 'williams ( usa ) l 4 - 5', 'bogdos ( gre ) l 4 - 5', 'poleshchuk ( rus ) l 1 - 5', 'latreche ( fra ) l 2 - 5', 'komar ( ukr ) l 2 - 5', 'n / a', '6', 'did not advance', 'did not advance', 'did not advance']] |
big 12 conference football | https://en.wikipedia.org/wiki/Big_12_Conference_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20190834-1.html.csv | superlative | in the big 12 conference football , baylor university has the largest enrollment among private schools . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,5', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'baylor university'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'baylor university'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; institution ; baylor university }', 'tointer': 'select the rows whose institution record fuzzily matches to baylor university .'}, 'enrollment'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; institution ; baylor university } ; enrollment }'}, 'affiliation'], 'result': 'private / baptist', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; institution ; baylor university } ; enrollment } ; affiliation }'}, 'private / baptist'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; institution ; baylor university } ; enrollment } ; affiliation } ; private / baptist } = true', 'tointer': 'select the rows whose institution record fuzzily matches to baylor university . select the row whose enrollment record of these rows is maximum . the affiliation record of this row is private / baptist .'} | eq { hop { argmax { filter_eq { all_rows ; institution ; baylor university } ; enrollment } ; affiliation } ; private / baptist } = true | select the rows whose institution record fuzzily matches to baylor university . select the row whose enrollment record of these rows is maximum . the affiliation record of this row is private / baptist . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'institution_6': 6, 'baylor university_7': 7, 'enrollment_8': 8, 'affiliation_9': 9, 'private / baptist_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'institution_6': 'institution', 'baylor university_7': 'baylor university', 'enrollment_8': 'enrollment', 'affiliation_9': 'affiliation', 'private / baptist_10': 'private / baptist'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'institution_6': [0], 'baylor university_7': [0], 'enrollment_8': [1], 'affiliation_9': [2], 'private / baptist_10': [3]} | ['institution', 'team name', 'location ( population )', 'team started', 'affiliation', 'enrollment', 'mascot', 'divisional titles', 'big 12 titles', 'national titles'] | [['iowa state university', 'cyclones', 'ames , iowa ( 51557 )', '1892', 'public', '31040', 'cy the cardinal', '1', '0', '0'], ['kansas state university', 'wildcats', 'manhattan , kansas ( 51707 )', '1896', 'public', '23520', 'willie the wildcat', '4', '2', '0'], ['university of kansas', 'jayhawks', 'lawrence , kansas ( 92048 )', '1890', 'public', '30102', 'big jay / baby jay', '1', '0', '0'], ['baylor university', 'bears', 'waco , texas ( 122222 )', '1896', 'private / baptist', '15195', 'judge and bruiser', '0', '0', '0'], ['oklahoma state university', 'cowboys', 'stillwater , oklahoma ( 46976 )', '1901', 'public', '23307', 'pistol pete / bullet', '1', '1', '0'], ['texas christian university', 'horned frogs', 'fort worth , texas ( 741206 )', '1896', 'private / disciples of christ', '9142', 'super frog', '0', '0', '2'], ['texas tech university', 'red raiders', 'lubbock , texas ( 212169 )', '1925', 'public', '30049', 'masked rider / raider red', '1', '0', '0'], ['university of oklahoma', 'sooners', 'norman , oklahoma ( 102827 )', '1895', 'public', '29721', 'sooner schooner / boomer and sooner', '8', '8', '7'], ['university of texas', 'longhorns', 'austin , texas ( 757688 )', '1893', 'public', '49696', "bevo / hook 'em", '7', '3', '4']] |
2008 - 09 lega pro prima divisione | https://en.wikipedia.org/wiki/2008%E2%80%9309_Lega_Pro_Prima_Divisione | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17605092-2.html.csv | ordinal | the stadium that can hold the second least amount of people is the stadio italia . | {'row': '15', 'col': '4', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'capacity', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; capacity ; 2 }'}, 'stadium'], 'result': 'stadio italia', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; capacity ; 2 } ; stadium }'}, 'stadio italia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; capacity ; 2 } ; stadium } ; stadio italia } = true', 'tointer': 'select the row whose capacity record of all rows is 2nd minimum . the stadium record of this row is stadio italia .'} | eq { hop { nth_argmin { all_rows ; capacity ; 2 } ; stadium } ; stadio italia } = true | select the row whose capacity record of all rows is 2nd minimum . the stadium record of this row is stadio italia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'capacity_5': 5, '2_6': 6, 'stadium_7': 7, 'stadio italia_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', 'capacity_5': 'capacity', '2_6': '2', 'stadium_7': 'stadium', 'stadio italia_8': 'stadio italia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'capacity_5': [0], '2_6': [0], 'stadium_7': [1], 'stadio italia_8': [2]} | ['club', 'city', 'stadium', 'capacity', '2007 - 08 season'] | [['ac arezzo', 'arezzo', 'stadio città di arezzo', '13128', '7th in serie c1 / b'], ['benevento calcio', 'benevento', 'stadio santa colomba', '18927', 'serie c2 / c champions'], ['ss cavese 1919', "cava de ' tirreni", 'stadio simonetta lamberti', '16000', '10th in serie c1 / a'], ['fc crotone', 'crotone', 'stadio ezio scida', '9631', '4th in serie c1 / b'], ['us foggia', 'foggia', 'stadio pino zaccheria', '25000', '5th in serie c1 / a'], ['foligno calcio', 'foligno', 'stadio enzo blasone', '5650', '4th in serie c1 / a'], ['gallipoli calcio', 'gallipoli', 'stadio antonio bianco', '5000', '9th in serie c1 / b'], ['ss juve stabia', 'castellammare di stabia', 'stadio romeo menti', '10400', '15th in serie c1 / b'], ['real marcianise calcio', 'marcianise', 'stadio progreditur', '3000', 'serie c2 / c play - off winners'], ['paganese calcio 1926', 'pagani', 'stadio marcello torre', '3700', '15th in serie c1 / a'], ['perugia calcio', 'perugia', 'stadio renato curi', '28000', '5th in serie c1 / b'], ['pescara calcio', 'pescara', 'stadio adriatico', '22260', '6th in serie c1 / b'], ['ac pistoiese', 'pistoia', 'stadio marcello melani', '13195', '14th in serie c1 / b'], ['potenza sc', 'potenza', 'stadio alfredo viviani', '6000', '11th in serie c1 / b'], ['sorrento calcio', 'sorrento', 'stadio italia', '3600', '10th in serie c1 / b'], ['taranto sport', 'taranto', 'stadio erasmo iacovone', '28000', '3rd in serie c1 / b'], ['ternana calcio', 'terni', 'stadio libero liberati', '20095', '13th in serie c1 / a'], ['ss virtus lanciano 1924', 'lanciano', 'stadio guido biondi', '7500', '16th in serie c1 / b']] |
steamboats of coos bay | https://en.wikipedia.org/wiki/Steamboats_of_Coos_Bay | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15289945-1.html.csv | superlative | the fay no. 4 steamboat from coos bay was the longest steamboat measuring 136 ' . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'length'], 'result': "136 '", 'ind': 0, 'tostr': 'max { all_rows ; length }', 'tointer': "the maximum length record of all rows is 136 ' ."}, "136 '"], 'result': True, 'ind': 1, 'tostr': "eq { max { all_rows ; length } ; 136 ' }", 'tointer': "the maximum length record of all rows is 136 ' ."}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'length'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; length }'}, 'name'], 'result': 'fay no 4', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; length } ; name }'}, 'fay no 4'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; length } ; name } ; fay no 4 }', 'tointer': 'the name record of the row with superlative length record is fay no 4 .'}], 'result': True, 'ind': 5, 'tostr': "and { eq { max { all_rows ; length } ; 136 ' } ; eq { hop { argmax { all_rows ; length } ; name } ; fay no 4 } } = true", 'tointer': "the maximum length record of all rows is 136 ' . the name record of the row with superlative length record is fay no 4 ."} | and { eq { max { all_rows ; length } ; 136 ' } ; eq { hop { argmax { all_rows ; length } ; name } ; fay no 4 } } = true | the maximum length record of all rows is 136 ' . the name record of the row with superlative length record is fay no 4 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'length_8': 8, "136'_9": 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'length_11': 11, 'name_12': 12, 'fay no 4_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'length_8': 'length', "136'_9": "136 '", 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'length_11': 'length', 'name_12': 'name', 'fay no 4_13': 'fay no 4'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'length_8': [0], "136'_9": [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'length_11': [2], 'name_12': [3], 'fay no 4_13': [4]} | ['name', 'type', 'year built', 'where built', 'length'] | [['messenger', 'sternwheeler', '1872', 'empire city', "91 '"], ['juno', 'propeller', '1906', 'marshfield', "60.8 '"], ['millicoma', 'sternwheeler', '1909', 'marshfield', "55 '"], ['pedler', 'sternwheeler', '1908', 'marshfield', "124 '"], ['fay no 4', 'sternwheeler ( gasoline )', '1912', 'north bend', "136 '"], ['life - line', 'propeller ( gasoline )', '1912', 'marshfield', "36 '"], ['rainbow', 'sternwheeler', '1912', 'marshfield', "64 '"]] |
tnq | https://en.wikipedia.org/wiki/TNQ | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12112313-1.html.csv | ordinal | for tnq , the 2nd earliest first air date was for the city of cairns . | {'row': '1', '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 air date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first air date ; 2 }'}, 'city'], 'result': 'cairns', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first air date ; 2 } ; city }'}, 'cairns'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first air date ; 2 } ; city } ; cairns } = true', 'tointer': 'select the row whose first air date record of all rows is 2nd minimum . the city record of this row is cairns .'} | eq { hop { nth_argmin { all_rows ; first air date ; 2 } ; city } ; cairns } = true | select the row whose first air date record of all rows is 2nd minimum . the city record of this row is cairns . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'first air date_5': 5, '2_6': 6, 'city_7': 7, 'cairns_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 air date_5': 'first air date', '2_6': '2', 'city_7': 'city', 'cairns_8': 'cairns'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first air date_5': [0], '2_6': [0], 'city_7': [1], 'cairns_8': [2]} | ['region served', 'city', 'channels ( analog / digital )', 'first air date', 'erp ( analog / digital )', 'haat ( analog / digital ) 1', 'transmitter location'] | [['cairns 2', 'cairns', '10 ( vhf ) 3 6 ( vhf )', '7 september 1966', '200 kw 50 kw', '1177 m 1190 m', 'mount bellenden ker'], ['darling downs', 'toowoomba', '41 ( uhf ) 3 40 ( uhf )', '31 december 1990', '1300 kw 500 kw', '515 m 520 m', 'mount mowbullan'], ['mackay', 'mackay', '33 ( uhf ) 3 32 ( uhf )', '31 december 1990', '1300 kw 360 kw', '612 m 630 m', 'mount blackwood'], ['rockhampton', 'rockhampton', '34 ( uhf ) 3 36 ( uhf )', '31 december 1990', '2000 kw 500 kw', '523 m 523 m', 'mount hopeful'], ['southern downs', 'warwick', '39 ( uhf ) 3 52 ( uhf )', '31 december 1990', '600 kw 500 kw', '301 m 301 m', 'passchendaele ridge'], ['townsville', 'townsville', '7 ( vhf ) 3 36 ( uhf )', '1 november 1962', '200 kw 200 kw', '612 m 655 m', 'mount stuart'], ['wide bay', 'maryborough', '33 ( uhf ) 3 9 ( vhf )', '31 december 1990', '1000 kw 60 kw', '646 m 646 m', 'mount goonaneman']] |
mañana es para siempre | https://en.wikipedia.org/wiki/Ma%C3%B1ana_es_para_siempre | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18498743-1.html.csv | majority | the majority of countries show the programme mañana es para siempre on monday to friday . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'monday to friday', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'monday to friday', 'monday to friday'], 'result': True, 'ind': 0, 'tointer': 'for the monday to friday records of all rows , most of them fuzzily match to monday to friday .', 'tostr': 'most_eq { all_rows ; monday to friday ; monday to friday } = true'} | most_eq { all_rows ; monday to friday ; monday to friday } = true | for the monday to friday records of all rows , most of them fuzzily match to monday to friday . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'monday to friday_3': 3, 'monday to friday_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'monday to friday_3': 'monday to friday', 'monday to friday_4': 'monday to friday'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'monday to friday_3': [0], 'monday to friday_4': [0]} | ['mexico', 'mañana es para siempre', 'el canal de las estrellas', 'october 20 , 2008', 'june 14 , 2009', 'monday to friday'] | [['argentina', 'mañana es para siempre', 'canal 9', 'november 10 , 2011', 'march 16 , 2012', 'monday to friday'], ['bulgaria', 'утре и завинаги', 'diema family', 'january 11 , 2010', 'april 30 , 2010', 'monday to friday'], ['bosnia and herzegovina', 'ljubav je večna', 'pink bh', 'december 3 , 2009', 'may 29 , 2010', 'monday to saturday'], ['croatia', 'odavde do vječnosti', 'nova tv', 'february 1 , 2010', 'june 10 , 2010', 'monday to friday'], ['croatia', 'odavde do vječnosti', 'doma tv', 'june 16 , 2011', 'october 30 , 2011', 'monday to friday'], ['estonia', 'igavene homne', 'tv3', 'march 30 , 2010', 'november 8 , 2010', 'monday to friday'], ['hungary', 'mindörökké szerelem', 'rtl klub', 'november 15 , 2010', 'july 8 , 2011', 'monday to friday'], ['macedonia', 'љубовта е вечна', 'sitel tv', '2009', '2009', 'monday to friday'], ['lithuania', 'amžinai tavo', 'lnk', 'march , 2009', 'october 30 , 2009', 'monday to friday'], ['montenegro', 'ljubav je večna', 'pink m', 'august 10 , 2009', 'february 23 , 2010', 'monday to friday'], ['romania', 'impreuna pentru totdeauna', 'acasă', 'march 29 , 2010', 'september 4 , 2010', 'monday to friday'], ['serbia', 'ljubav je večna', 'rtv pink', 'june 5 , 2009', 'january 29 , 2010', 'monday to friday'], ['slovakia', 'love never dies', 'joj plus', 'december 21 , 2009', 'april , 2010', 'monday to friday'], ['slovenia', 'jutri je za večno', 'pop tv', 'september 25 , 2009', 'may 10 , 2010', 'monday to friday'], ['usa', 'mañana es para siempre', 'univision', 'february 23 , 2009', 'october 5 , 2009', 'monday to friday'], ['iran', 'mañana es para siempre', 'pmc', '2010', '2011', 'saturday to wednesday']] |
list of schools in the waikato region | https://en.wikipedia.org/wiki/List_of_schools_in_the_Waikato_Region | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12146269-10.html.csv | unique | st joseph 's catholic school is the only one that is state integrated . | {'scope': 'all', 'row': '12', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'state integrated', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'authority', 'state integrated'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose authority record fuzzily matches to state integrated .', 'tostr': 'filter_eq { all_rows ; authority ; state integrated }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; authority ; state integrated } }', 'tointer': 'select the rows whose authority record fuzzily matches to state integrated . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'authority', 'state integrated'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose authority record fuzzily matches to state integrated .', 'tostr': 'filter_eq { all_rows ; authority ; state integrated }'}, 'name'], 'result': "st joseph 's catholic school", 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; authority ; state integrated } ; name }'}, "st joseph 's catholic school"], 'result': True, 'ind': 3, 'tostr': "eq { hop { filter_eq { all_rows ; authority ; state integrated } ; name } ; st joseph 's catholic school }", 'tointer': "the name record of this unqiue row is st joseph 's catholic school ."}], 'result': True, 'ind': 4, 'tostr': "and { only { filter_eq { all_rows ; authority ; state integrated } } ; eq { hop { filter_eq { all_rows ; authority ; state integrated } ; name } ; st joseph 's catholic school } } = true", 'tointer': "select the rows whose authority record fuzzily matches to state integrated . there is only one such row in the table . the name record of this unqiue row is st joseph 's catholic school ."} | and { only { filter_eq { all_rows ; authority ; state integrated } } ; eq { hop { filter_eq { all_rows ; authority ; state integrated } ; name } ; st joseph 's catholic school } } = true | select the rows whose authority record fuzzily matches to state integrated . there is only one such row in the table . the name record of this unqiue row is st joseph 's catholic school . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'authority_7': 7, 'state integrated_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, "st joseph 's catholic school_10": 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'authority_7': 'authority', 'state integrated_8': 'state integrated', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', "st joseph 's catholic school_10": "st joseph 's catholic school"} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'authority_7': [0], 'state integrated_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], "st joseph 's catholic school_10": [3]} | ['name', 'years', 'gender', 'area', 'authority', 'decile', 'roll'] | [['aria school', '1 - 6', 'coed', 'aria', 'state', '5', '55'], ['benneydale school', '1 - 8', 'coed', 'benneydale', 'state', '1', '14'], ['centennial park school', '1 - 8', 'coed', 'te kuiti', 'state', '1', '113'], ['kinohaku school', '1 - 8', 'coed', 'te kuiti', 'state', '4', '32'], ['mapiu school', '1 - 8', 'coed', 'mapiu', 'state', '4', '9'], ['mokau school', '1 - 8', 'coed', 'mokau', 'state', '3', '24'], ['piopio college', '7 - 15', 'coed', 'piopio', 'state', '4', '202'], ['piopio primary school', '1 - 6', 'coed', 'piopio', 'state', '5', '129'], ['piri piri school', '1 - 8', 'coed', 'te kuiti', 'state', '4', '22'], ['pukenui school', '1 - 8', 'coed', 'te kuiti', 'state', '2', '186'], ['rangitoto school', '1 - 8', 'coed', 'rangitoto', 'state', '6', '40'], ["st joseph 's catholic school", '1 - 8', 'coed', 'te kuiti', 'state integrated', '4', '102'], ['te kuiti high school', '9 - 15', 'coed', 'te kuiti', 'state', '3', '321'], ['te kuiti primary school', '1 - 8', 'coed', 'te kuiti', 'state', '2', '356'], ['te kura o tahaaroa', '1 - 8', 'coed', 'te kuiti', 'state', '3', '38'], ['te wharekura o maniapoto', '1 - 15', 'coed', 'te kuiti', 'state', '2', '96'], ['waitomo caves school', '1 - 8', 'coed', 'waitomo caves', 'state', '5', '44'], ['whareorino school', '1 - 8', 'coed', 'mokau', 'state', '5', '10']] |
sidecarcross world championship | https://en.wikipedia.org/wiki/Sidecarcross_World_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16729457-16.html.csv | count | two teams in the sidecarcross world championship used ktm - vmc equipment . | {'scope': 'all', 'criterion': 'equal', 'value': 'ktm - vmc', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'equipment', 'ktm - vmc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose equipment record fuzzily matches to ktm - vmc .', 'tostr': 'filter_eq { all_rows ; equipment ; ktm - vmc }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; equipment ; ktm - vmc } }', 'tointer': 'select the rows whose equipment record fuzzily matches to ktm - vmc . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; equipment ; ktm - vmc } } ; 2 } = true', 'tointer': 'select the rows whose equipment record fuzzily matches to ktm - vmc . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; equipment ; ktm - vmc } } ; 2 } = true | select the rows whose equipment record fuzzily matches to ktm - vmc . 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, 'equipment_5': 5, 'ktm - vmc_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', 'equipment_5': 'equipment', 'ktm - vmc_6': 'ktm - vmc', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'equipment_5': [0], 'ktm - vmc_6': [0], '2_7': [2]} | ['position', 'driver / passenger', 'equipment', 'bike no', 'points'] | [['1', 'daniãl willemsen / sven verbrugge 1', 'zabel - wsp', '1', '487'], ['2', 'janis daiders / lauris daiders', 'zabel - vmc', '8', '478'], ['3', 'jan hendrickx / tim smeuninx', 'zabel - vmc', '3', '405'], ['4', 'maris rupeiks / kaspars stupelis 2', 'zabel - wsp', '5', '349'], ['5', 'etienne bax / ben van den bogaart', 'zabel - vmc', '4', '347'], ['6', 'ben adriaenssen / guennady auvray', 'ktm - vmc', '6', '346'], ['7', 'ewgeny scherbinin / haralds kurpnieks', 'zabel - wsp', '20', '321'], ['8', 'marko happich / meinrad schelbert', 'zabel - vmc', '15', '317'], ['9', 'joris hendrickx / kaspars liepins', 'ktm - vmc', '2', '315']] |
yen plus | https://en.wikipedia.org/wiki/Yen_Plus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18685750-1.html.csv | count | there are 5 titles in yen plus whose first issues were released in august 2008 . | {'scope': 'all', 'criterion': 'equal', 'value': 'august 2008', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first issue', 'august 2008'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first issue record fuzzily matches to august 2008 .', 'tostr': 'filter_eq { all_rows ; first issue ; august 2008 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first issue ; august 2008 } }', 'tointer': 'select the rows whose first issue record fuzzily matches to august 2008 . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first issue ; august 2008 } } ; 5 } = true', 'tointer': 'select the rows whose first issue record fuzzily matches to august 2008 . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; first issue ; august 2008 } } ; 5 } = true | select the rows whose first issue record fuzzily matches to august 2008 . 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, 'first issue_5': 5, 'august 2008_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', 'first issue_5': 'first issue', 'august 2008_6': 'august 2008', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'first issue_5': [0], 'august 2008_6': [0], '5_7': [2]} | ['title', 'author', 'first issue', 'last issue', 'completed'] | [['bamboo blade', 'masahiro totsuka ( author ) , aguri igarashi ( artist )', 'august 2008', 'may 2009', 'no'], ['black butler', 'yana toboso', 'august 2009', 'july 2010', 'no'], ['higurashi when they cry', 'ryukishi07 ( author ) , karin suzuragi ( artist )', 'august 2008', 'january 2009', 'no'], ['hero tales', 'huang jin zhou ( author ) , hiromu arakawa ( artist )', 'february 2009', 'on hiatus', 'no'], ['k - on !', 'kakifly', 'september 2010', 'ongoing', 'no'], ['nabari no ou', 'yuhki kamatani', 'august 2008', 'unknown', 'no'], ['pandora hearts', 'jun mochizuki', 'june 2009', 'unknown', 'no'], ['soul eater', 'atsushi okubo', 'august 2008', 'unknown', 'no'], ['sumomomo momomo', 'shinobu ohtaka', 'august 2008', 'october 2009', 'no'], ['yotsuba & !', 'kiyohiko azuma', 'september 2010', 'ongoing', 'no']] |
enlargement of the eurozone | https://en.wikipedia.org/wiki/Enlargement_of_the_eurozone | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12641034-2.html.csv | comparative | the lithuanian litas has an earlier erm ii entry date than the latvian lats . | {'row_1': '7', 'row_2': '6', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'currency', 'lithuanian litas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose currency record fuzzily matches to lithuanian litas .', 'tostr': 'filter_eq { all_rows ; currency ; lithuanian litas }'}, 'entry erm ii'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; currency ; lithuanian litas } ; entry erm ii }', 'tointer': 'select the rows whose currency record fuzzily matches to lithuanian litas . take the entry erm ii record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'currency', 'latvian lats'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose currency record fuzzily matches to latvian lats .', 'tostr': 'filter_eq { all_rows ; currency ; latvian lats }'}, 'entry erm ii'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; currency ; latvian lats } ; entry erm ii }', 'tointer': 'select the rows whose currency record fuzzily matches to latvian lats . take the entry erm ii record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; currency ; lithuanian litas } ; entry erm ii } ; hop { filter_eq { all_rows ; currency ; latvian lats } ; entry erm ii } } = true', 'tointer': 'select the rows whose currency record fuzzily matches to lithuanian litas . take the entry erm ii record of this row . select the rows whose currency record fuzzily matches to latvian lats . take the entry erm ii record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; currency ; lithuanian litas } ; entry erm ii } ; hop { filter_eq { all_rows ; currency ; latvian lats } ; entry erm ii } } = true | select the rows whose currency record fuzzily matches to lithuanian litas . take the entry erm ii record of this row . select the rows whose currency record fuzzily matches to latvian lats . take the entry erm ii 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, 'currency_7': 7, 'lithuanian litas_8': 8, 'entry erm ii_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'currency_11': 11, 'latvian lats_12': 12, 'entry erm ii_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', 'currency_7': 'currency', 'lithuanian litas_8': 'lithuanian litas', 'entry erm ii_9': 'entry erm ii', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'currency_11': 'currency', 'latvian lats_12': 'latvian lats', 'entry erm ii_13': 'entry erm ii'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'currency_7': [0], 'lithuanian litas_8': [0], 'entry erm ii_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'currency_11': [1], 'latvian lats_12': [1], 'entry erm ii_13': [3]} | ['currency', 'code', 'entry erm ii', 'central rate', 'official target date'] | [['bulgarian lev', 'bgn', '-', '1.95583', '-'], ['croatian kuna', 'hrk', '-', '-', '-'], ['czech koruna', 'czk', '-', '-', '-'], ['danish krone', 'dkk', '1 january 1999', '7.46038', 'formal opt - out'], ['hungarian forint', 'huf', '-', '-', '-'], ['latvian lats', 'lvl', '2 may 2005', '0.702804', '1 january 2014'], ['lithuanian litas', 'ltl', '28 june 2004', '3.45280', '1 january 2015'], ['polish złoty', 'pln', '-', '-', '-'], ['romanian leu', 'ron', '-', '-', '-'], ['swedish krona', 'sek', 'not considered', '-', 'de facto opt - out'], ['british pound sterling gibraltar pound', 'gbp gip', 'not considered', '-', 'formal opt - out']] |
list of northern ireland executives | https://en.wikipedia.org/wiki/List_of_Northern_Ireland_Executives | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12647910-1.html.csv | count | of northern ireland executives , when it is the second executive , there were two times that the first minister was ian paisley . | {'scope': 'subset', 'criterion': 'equal', 'value': 'ian paisley', 'result': '2', 'col': '3', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'second'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'executive', 'second'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; executive ; second }', 'tointer': 'select the rows whose executive record fuzzily matches to second .'}, 'first minister', 'ian paisley'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose executive record fuzzily matches to second . among these rows , select the rows whose first minister record fuzzily matches to ian paisley .', 'tostr': 'filter_eq { filter_eq { all_rows ; executive ; second } ; first minister ; ian paisley }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; executive ; second } ; first minister ; ian paisley } }', 'tointer': 'select the rows whose executive record fuzzily matches to second . among these rows , select the rows whose first minister record fuzzily matches to ian paisley . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; executive ; second } ; first minister ; ian paisley } } ; 2 } = true', 'tointer': 'select the rows whose executive record fuzzily matches to second . among these rows , select the rows whose first minister record fuzzily matches to ian paisley . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; executive ; second } ; first minister ; ian paisley } } ; 2 } = true | select the rows whose executive record fuzzily matches to second . among these rows , select the rows whose first minister record fuzzily matches to ian paisley . 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, 'executive_6': 6, 'second_7': 7, 'first minister_8': 8, 'ian paisley_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', 'executive_6': 'executive', 'second_7': 'second', 'first minister_8': 'first minister', 'ian paisley_9': 'ian paisley', '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], 'executive_6': [0], 'second_7': [0], 'first minister_8': [1], 'ian paisley_9': [1], '2_10': [3]} | ['term', 'executive', 'first minister', 'deputy', 'parties'] | [['term', 'executive', 'first minister', 'deputy', 'parties'], ['1998 - 2002', 'first', 'david trimble', 'seamus mallon', 'ulster unionist party ( 4 seats )'], ['1998 - 2002', 'first', 'david trimble', 'seamus mallon', 'social democratic and labour party ( 4 seats )'], ['1998 - 2002', 'first', 'david trimble', 'mark durkan', 'democratic unionist party ( 2 seats )'], ['1998 - 2002', 'first', 'david trimble', 'mark durkan', 'sinn féin ( 2 seats )'], ['2nd assembly ( mlas )', '2nd assembly ( mlas )', '2nd assembly ( mlas )', '2nd assembly ( mlas )', '2nd assembly ( mlas )'], ['2003 - 2007', 'suspended', 'vacant', 'vacant', 'none'], ['3rd assembly ( mlas )', '3rd assembly ( mlas )', '3rd assembly ( mlas )', '3rd assembly ( mlas )', '3rd assembly ( mlas )'], ['2007 - 2011', 'second', 'ian paisley', 'martin mcguinness', 'democratic unionist party ( 5 seats )'], ['2007 - 2011', 'second', 'ian paisley', 'martin mcguinness', 'sinn féin ( 4 seats )'], ['2007 - 2011', 'second', 'peter robinson', 'martin mcguinness', 'ulster unionist party ( 2 seats )'], ['2007 - 2011', 'second', 'peter robinson', 'martin mcguinness', 'social democratic and labour party ( 1 seat )'], ['2007 - 2011', 'second', 'peter robinson', 'martin mcguinness', 'alliance party of northern ireland ( 1 seat )'], ['4th assembly ( mlas )', '4th assembly ( mlas )', '4th assembly ( mlas )', '4th assembly ( mlas )', '4th assembly ( mlas )'], ['2011 -', 'third', 'peter robinson', 'martin mcguinness', 'democratic unionist party ( 5 seats )'], ['2011 -', 'third', 'peter robinson', 'martin mcguinness', 'sinn féin ( 4 seats )'], ['2011 -', 'third', 'peter robinson', 'martin mcguinness', 'ulster unionist party ( 1 seat )'], ['2011 -', 'third', 'peter robinson', 'martin mcguinness', 'social democratic and labour party ( 1 seat )'], ['2011 -', 'third', 'peter robinson', 'martin mcguinness', 'alliance party of northern ireland ( 2 seats )']] |
1977 baltimore colts season | https://en.wikipedia.org/wiki/1977_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14945608-1.html.csv | count | in the 1977 season , the baltimore colts played 6 games at memorial staduim . | {'scope': 'all', 'criterion': 'equal', 'value': 'memorial stadium', 'result': '6', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'memorial stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to memorial stadium .', 'tostr': 'filter_eq { all_rows ; game site ; memorial stadium }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; game site ; memorial stadium } }', 'tointer': 'select the rows whose game site record fuzzily matches to memorial stadium . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; game site ; memorial stadium } } ; 6 } = true', 'tointer': 'select the rows whose game site record fuzzily matches to memorial stadium . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; game site ; memorial stadium } } ; 6 } = true | select the rows whose game site record fuzzily matches to memorial stadium . 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, 'game site_5': 5, 'memorial stadium_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', 'game site_5': 'game site', 'memorial stadium_6': 'memorial stadium', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'memorial stadium_6': [0], '6_7': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 18 , 1977', 'seattle seahawks', 'w 29 - 14', '1 - 0', 'kingdome', '58991'], ['2', 'september 25 , 1977', 'new york jets', 'w 20 - 12', '2 - 0', 'shea stadium', '43439'], ['3', 'october 2 , 1977', 'buffalo bills', 'w 17 - 14', '3 - 0', 'memorial stadium', '49247'], ['4', 'october 9 , 1977', 'miami dolphins', 'w 45 - 28', '4 - 0', 'memorial stadium', '57829'], ['5', 'october 16 , 1977', 'kansas city chiefs', 'w 17 - 6', '5 - 0', 'arrowhead stadium', '63076'], ['6', 'october 23 , 1977', 'new england patriots', 'l 3 - 17', '5 - 1', 'schaeffer stadium', '60958'], ['7', 'october 30 , 1977', 'pittsburgh steelers', 'w 31 - 21', '6 - 1', 'memorial stadium', '60225'], ['8', 'november 7 , 1977', 'washington redskins', 'w 10 - 3', '7 - 1', 'memorial stadium', '57740'], ['9', 'november 13 , 1977', 'buffalo bills', 'w 31 - 13', '8 - 1', 'rich stadium', '39444'], ['10', 'november 20 , 1977', 'new york jets', 'w 33 - 12', '9 - 1', 'memorial stadium', '50957'], ['11', 'november 27 , 1977', 'denver broncos', 'l 13 - 27', '9 - 2', 'mile high stadium', '74939'], ['12', 'december 5 , 1977', 'miami dolphins', 'l 6 - 17', '9 - 3', 'miami orange bowl', '68977'], ['13', 'december 11 , 1977', 'detroit lions', 'l 10 - 13', '9 - 4', 'memorial stadium', '45124']] |
2007 - 08 dallas stars season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Dallas_Stars_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11801912-4.html.csv | ordinal | the dallas stars ' game against anaheim recorded their highest attendance of the 2007 - 08 season . | {'row': '9', 'col': '6', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'visitor'], 'result': 'anaheim', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; visitor }'}, 'anaheim'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; visitor } ; anaheim } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the visitor record of this row is anaheim .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; visitor } ; anaheim } = true | select the row whose attendance record of all rows is 1st maximum . the visitor record of this row is anaheim . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'visitor_7': 7, 'anaheim_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'visitor_7': 'visitor', 'anaheim_8': 'anaheim'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'visitor_7': [1], 'anaheim_8': [2]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 2', 'phoenix', '5 - 0', 'dallas', 'smith', '18203', '5 - 6 - 2'], ['november 5', 'dallas', '5 - 0', 'anaheim', 'turco', '17174', '6 - 6 - 2'], ['november 7', 'dallas', '3 - 1', 'san jose', 'turco', '17496', '7 - 6 - 2'], ['november 8', 'dallas', '2 - 5', 'phoenix', 'turco', '12027', '7 - 7 - 2'], ['november 10', 'dallas', '5 - 6', 'los angeles', 'turco', '18118', '7 - 7 - 3'], ['november 14', 'san jose', '4 - 3', 'dallas', 'turco', '17682', '7 - 7 - 4'], ['november 16', 'colorado', '1 - 6', 'dallas', 'smith', '18019', '8 - 7 - 4'], ['november 19', 'los angeles', '0 - 3', 'dallas', 'smith', '17208', '9 - 7 - 4'], ['november 21', 'anaheim', '1 - 2', 'dallas', 'smith', '18584', '10 - 7 - 4'], ['november 23', 'toronto', '1 - 3', 'dallas', 'turco', '18409', '11 - 7 - 4'], ['november 25', 'dallas', '3 - 2', 'ny rangers', 'smith', '18200', '12 - 7 - 4'], ['november 26', 'dallas', '3 - 2', 'ny islanders', 'turco', '8161', '13 - 7 - 4'], ['november 28', 'dallas', '2 - 4', 'new jersey', 'turco', '13665', '13 - 8 - 4'], ['november 30', 'dallas', '1 - 4', 'pittsburgh', 'smith', '17132', '13 - 9 - 4']] |
2009 tour de pologne | https://en.wikipedia.org/wiki/2009_Tour_de_Pologne | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22917458-15.html.csv | superlative | the earliest stage that edvald boasson hagen won in the 2009 tour de pologne was the fourth stage . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '4', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'edvald boasson hagen'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winner', 'edvald boasson hagen'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; winner ; edvald boasson hagen }', 'tointer': 'select the rows whose winner record fuzzily matches to edvald boasson hagen .'}, 'stage'], 'result': '4', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; winner ; edvald boasson hagen } ; stage }', 'tointer': 'select the rows whose winner record fuzzily matches to edvald boasson hagen . the minimum stage record of these rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; winner ; edvald boasson hagen } ; stage } ; 4 } = true', 'tointer': 'select the rows whose winner record fuzzily matches to edvald boasson hagen . the minimum stage record of these rows is 4 .'} | eq { min { filter_eq { all_rows ; winner ; edvald boasson hagen } ; stage } ; 4 } = true | select the rows whose winner record fuzzily matches to edvald boasson hagen . the minimum stage record of these rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'winner_5': 5, 'edvald boasson hagen_6': 6, 'stage_7': 7, '4_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'winner_5': 'winner', 'edvald boasson hagen_6': 'edvald boasson hagen', 'stage_7': 'stage', '4_8': '4'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winner_5': [0], 'edvald boasson hagen_6': [0], 'stage_7': [1], '4_8': [2]} | ['stage', 'winner', 'general classification żółta koszulka', 'mountains classification klasyfikacja górska', 'intermediate sprints classification klasyfikacja najaktywniejszych', 'points classification klasyfikacja punktowa'] | [['1', 'borut božič', 'borut božič', 'błażej janiaczyk', 'david loosli', 'borut božič'], ['2', 'angelo furlan', 'borut božič', 'błażej janiaczyk', 'david loosli', 'jurgen roelandts'], ['3', 'jacopo guarnieri', 'andré greipel', 'błażej janiaczyk', 'david loosli', 'andré greipel'], ['4', 'edvald boasson hagen', 'jurgen roelandts', 'błażej janiaczyk', 'david loosli', 'jurgen roelandts'], ['5', 'alessandro ballan', 'alessandro ballan', 'pavel brutt', 'david loosli', 'jurgen roelandts'], ['6', 'edvald boasson hagen', 'alessandro ballan', 'marek rutkiewicz', 'david loosli', 'jurgen roelandts'], ['7', 'andré greipel', 'alessandro ballan', 'marek rutkiewicz', 'david loosli', 'jurgen roelandts']] |
amstel gold race | https://en.wikipedia.org/wiki/Amstel_Gold_Race | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1749567-2.html.csv | superlative | in the amstel gold race , keutenberg has the highest number of kilometers . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '15', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'kilometer'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; kilometer }'}, 'number'], 'result': '31', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; kilometer } ; number }'}, '31'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; kilometer } ; number } ; 31 } = true', 'tointer': 'select the row whose kilometer record of all rows is maximum . the number record of this row is 31 .'} | eq { hop { argmax { all_rows ; kilometer } ; number } ; 31 } = true | select the row whose kilometer record of all rows is maximum . the number record of this row is 31 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'kilometer_5': 5, 'number_6': 6, '31_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'kilometer_5': 'kilometer', 'number_6': 'number', '31_7': '31'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'kilometer_5': [0], 'number_6': [1], '31_7': [2]} | ['number', 'name', 'kilometer', 'location', 'length ( in m )', 'average climb ( % )'] | [['17', 'plettenbergweg', '159', 'eys', '1000', '42'], ['18', 'eyserweg', '160', 'eys', '2200', '43'], ['19', 'hulsberg', '165', 'simpelveld', '1000', '77'], ['20', 'vrakelberg', '171', 'voerendaal', '700', '79'], ['21', 'sibbergrubbe', '179', 'valkenburg', '2100', '41'], ['22', 'cauberg', '184', 'valkenburg', '1200', '58'], ['23', 'geulhemmerweg', '188', 'valkenburg', '1000', '62'], ['24', 'bemelerberg', '201', 'margraten', '900', '50'], ['25', 'wolfsberg', '218', 'noorbeek', '800', '44'], ['26', 'loorberg', '224', 'slenaken', '1500', '55'], ['27', 'gulperberg', '232', 'gulpen', '700', '81'], ['28', 'kruisberg', '238', 'eys', '800', '75'], ['29', 'eyserbosweg', '240', 'eys', '1100', '81'], ['30', 'fromberg', '244', 'voerendaal', '1600', '40'], ['31', 'keutenberg', '248', 'valkenburg', '700', '94']] |
1992 - 93 belarusian premier league | https://en.wikipedia.org/wiki/1992%E2%80%9393_Belarusian_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14744744-1.html.csv | superlative | in the 1992 - 93 belarusian premier league , dinamo minsk had the highest position . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', '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', 'position in 1992'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; position in 1992 }'}, 'team'], 'result': 'dinamo minsk', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; position in 1992 } ; team }'}, 'dinamo minsk'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; position in 1992 } ; team } ; dinamo minsk } = true', 'tointer': 'select the row whose position in 1992 record of all rows is minimum . the team record of this row is dinamo minsk .'} | eq { hop { argmin { all_rows ; position in 1992 } ; team } ; dinamo minsk } = true | select the row whose position in 1992 record of all rows is minimum . the team record of this row is dinamo minsk . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'position in 1992_5': 5, 'team_6': 6, 'dinamo minsk_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'position in 1992_5': 'position in 1992', 'team_6': 'team', 'dinamo minsk_7': 'dinamo minsk'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'position in 1992_5': [0], 'team_6': [1], 'dinamo minsk_7': [2]} | ['team', 'location', 'venue', 'capacity', 'position in 1992'] | [['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '1'], ['dnepr', 'mogilev', 'spartak', '11200', '2'], ['dinamo brest', 'brest', 'dinamo , brest', '10080', '3'], ['fandok', 'bobruisk', 'spartak , bobruisk', '3550', '4'], ['neman', 'grodno', 'neman', '6300', '5'], ['kim', 'vitebsk', 'central , vitebsk', '8300', '6'], ['torpedo mogilev', 'mogilev', 'torpedo , mogilev', '3500', '7'], ['vedrich', 'rechytsa', 'central , rechytsa', '3550', '8'], ['molodechno', 'molodechno', 'city stadium , molodechno', '5500', '9'], ['torpedo minsk', 'minsk', 'torpedo , minsk', '5200', '10'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '11'], ['obuvshchik', 'lida', 'city stadium , lida', '4000', '12'], ['torpedo zhodino', 'zhodino', 'torpedo , zhodino', '3020', '13'], ['stroitel', 'starye dorogi', 'stroitel', '2000', '14'], ['lokomotiv', 'vitebsk', 'central , vitebsk', '8300', '15'], ['gomselmash', 'gomel', 'central , gomel', '11800', '16'], ['belarus', 'minsk', 'dinamo , minsk', '41040', 'first league , 1']] |
powerade tigers all - time roster | https://en.wikipedia.org/wiki/Powerade_Tigers_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15463188-4.html.csv | majority | on the powerade tigers all - time roster , for those in the guard position , most of them have numbers under 20 . | {'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '20', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'guard'}} | {'func': 'most_less', '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 .'}, 'number', '20'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose position record fuzzily matches to guard . for the number records of these rows , most of them are less than 20 .', 'tostr': 'most_less { filter_eq { all_rows ; position ; guard } ; number ; 20 } = true'} | most_less { filter_eq { all_rows ; position ; guard } ; number ; 20 } = true | select the rows whose position record fuzzily matches to guard . for the number records of these rows , most of them are less than 20 . | 2 | 2 | {'most_less_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'position_4': 4, 'guard_5': 5, 'number_6': 6, '20_7': 7} | {'most_less_1': 'most_less', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'position_4': 'position', 'guard_5': 'guard', 'number_6': 'number', '20_7': '20'} | {'most_less_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'position_4': [0], 'guard_5': [0], 'number_6': [1], '20_7': [1]} | ['name', 'position', 'number', 'season', 'acquisition via'] | [['carlos daniel', 'forward', '21', '2002', 'import'], ['gary david', 'guard', '20', '2004 - 05 , 2010 - 2012', 'rookie draft , trade'], ['brandon dean', 'guard', '1', '2008', 'import'], ['aries dimaunahan', 'guard', '8', '2007 - 2009', 'trade'], ['jason dixon', 'center', '42', '2008', 'import'], ['kenneth duremdes', 'guard', '19', '2007 - 2008', 'trade']] |
lukoil | https://en.wikipedia.org/wiki/Lukoil | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1027881-2.html.csv | superlative | tm is a lukoil refinery with the smallest capacity among refineries that have been acquired after 2001 . | {'scope': 'subset', 'col_superlative': '5', 'row_superlative': '9', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': {'col': '4', 'criterion': 'greater_than', 'value': '2001'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'acquired', '2001'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; acquired ; 2001 }', 'tointer': 'select the rows whose acquired record is greater than 2001 .'}, 'capacity , mln tpa'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_greater { all_rows ; acquired ; 2001 } ; capacity , mln tpa }'}, 'name'], 'result': 'trn', 'ind': 2, 'tostr': 'hop { argmin { filter_greater { all_rows ; acquired ; 2001 } ; capacity , mln tpa } ; name }'}, 'trn'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_greater { all_rows ; acquired ; 2001 } ; capacity , mln tpa } ; name } ; trn } = true', 'tointer': 'select the rows whose acquired record is greater than 2001 . select the row whose capacity , mln tpa record of these rows is minimum . the name record of this row is trn .'} | eq { hop { argmin { filter_greater { all_rows ; acquired ; 2001 } ; capacity , mln tpa } ; name } ; trn } = true | select the rows whose acquired record is greater than 2001 . select the row whose capacity , mln tpa record of these rows is minimum . the name record of this row is trn . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'acquired_6': 6, '2001_7': 7, 'capacity , mln tpa_8': 8, 'name_9': 9, 'trn_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'acquired_6': 'acquired', '2001_7': '2001', 'capacity , mln tpa_8': 'capacity , mln tpa', 'name_9': 'name', 'trn_10': 'trn'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'acquired_6': [0], '2001_7': [0], 'capacity , mln tpa_8': [1], 'name_9': [2], 'trn_10': [3]} | ['name', 'location', 'launched', 'acquired', 'capacity , mln tpa'] | [['lukoil - nizhegorodnefteorgsintez', 'kstovo', '1958', '2000', '15 , 0'], ['lukoil - permnefteorgsintez', 'perm', '1958', '1991', '12 , 0'], ['lukoil - volgogradneftepererabotka', 'volgograd', '1957', '1991', '9 , 9'], ['lukoil - ukhtaneftepererabotka', 'ukhta', '1934', '2000', '3 , 7'], ['lukoil - odessky neftepererabatyvayuschiy zavod', 'odessa', '1937', '1999', '3 , 6'], ['lukoil neftochim burgas', 'burgas', '1964', '1999', '7 , 5'], ['petrotel - lukoil', 'ploieåÿti', '1904', '1998', '2 , 4'], ['isab', 'priolo gargallo', '1975', '2008', '16 , 0'], ['trn', 'vlissingen', '1973', '2009', '7 , 9']] |
ryan briscoe | https://en.wikipedia.org/wiki/Ryan_Briscoe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1390721-8.html.csv | majority | ryan briscoe drove the majority of his races using a dallara type chassis . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'dallara', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'chassis', 'dallara'], 'result': True, 'ind': 0, 'tointer': 'for the chassis records of all rows , most of them fuzzily match to dallara .', 'tostr': 'most_eq { all_rows ; chassis ; dallara } = true'} | most_eq { all_rows ; chassis ; dallara } = true | for the chassis records of all rows , most of them fuzzily match to dallara . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'chassis_3': 3, 'dallara_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'chassis_3': 'chassis', 'dallara_4': 'dallara'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'chassis_3': [0], 'dallara_4': [0]} | ['year', 'chassis', 'engine', 'start', 'finish', 'team'] | [['2005', 'panoz', 'toyota', '24', '10', 'chip ganassi racing'], ['2007', 'dallara', 'honda', '7', '5', 'luczo - dragon racing'], ['2008', 'dallara', 'honda', '3', '23', 'team penske'], ['2009', 'dallara', 'honda', '2', '15', 'team penske'], ['2010', 'dallara', 'honda', '4', '24', 'team penske'], ['2011', 'dallara', 'honda', '26', '27', 'team penske'], ['2012', 'dallara', 'chevrolet', '1', '5', 'team penske'], ['2013', 'dallara', 'honda', '23', '12', 'chip ganassi racing']] |
wvtf | https://en.wikipedia.org/wiki/WVTF | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12155786-3.html.csv | comparative | of the frequencies for wvtf , the frequency for norton , va is .4 higher than the frequency for pound , va . | {'row_1': '4', 'row_2': '5', 'col': '2', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '0.4', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city of license', 'norton , virginia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city of license record fuzzily matches to norton , virginia .', 'tostr': 'filter_eq { all_rows ; city of license ; norton , virginia }'}, 'frequency mhz'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; city of license ; norton , virginia } ; frequency mhz }', 'tointer': 'select the rows whose city of license record fuzzily matches to norton , virginia . take the frequency mhz record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city of license', 'pound , virginia'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose city of license record fuzzily matches to pound , virginia .', 'tostr': 'filter_eq { all_rows ; city of license ; pound , virginia }'}, 'frequency mhz'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; city of license ; pound , virginia } ; frequency mhz }', 'tointer': 'select the rows whose city of license record fuzzily matches to pound , virginia . take the frequency mhz record of this row .'}], 'result': '0.4', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; city of license ; norton , virginia } ; frequency mhz } ; hop { filter_eq { all_rows ; city of license ; pound , virginia } ; frequency mhz } }'}, '0.4'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; city of license ; norton , virginia } ; frequency mhz } ; hop { filter_eq { all_rows ; city of license ; pound , virginia } ; frequency mhz } } ; 0.4 } = true', 'tointer': 'select the rows whose city of license record fuzzily matches to norton , virginia . take the frequency mhz record of this row . select the rows whose city of license record fuzzily matches to pound , virginia . take the frequency mhz record of this row . the first record is 0.4 larger than the second record .'} | eq { diff { hop { filter_eq { all_rows ; city of license ; norton , virginia } ; frequency mhz } ; hop { filter_eq { all_rows ; city of license ; pound , virginia } ; frequency mhz } } ; 0.4 } = true | select the rows whose city of license record fuzzily matches to norton , virginia . take the frequency mhz record of this row . select the rows whose city of license record fuzzily matches to pound , virginia . take the frequency mhz record of this row . the first record is 0.4 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, 'city of license_8': 8, 'norton , virginia_9': 9, 'frequency mhz_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'city of license_12': 12, 'pound , virginia_13': 13, 'frequency mhz_14': 14, '0.4_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', 'city of license_8': 'city of license', 'norton , virginia_9': 'norton , virginia', 'frequency mhz_10': 'frequency mhz', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'city of license_12': 'city of license', 'pound , virginia_13': 'pound , virginia', 'frequency mhz_14': 'frequency mhz', '0.4_15': '0.4'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'city of license_8': [0], 'norton , virginia_9': [0], 'frequency mhz_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'city of license_12': [1], 'pound , virginia_13': [1], 'frequency mhz_14': [3], '0.4_15': [5]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'fcc info'] | [['w211bf', '90.1', 'big stone gap , virginia', '8', 'fcc'], ['w212bp', '90.3', 'clintwood , virginia', '1', 'fcc'], ['w211be', '90.1', 'lebanon , virginia', '8.5', 'fcc'], ['w219cj', '91.7', 'norton , virginia', '50', 'fcc'], ['w217bf', '91.3', 'pound , virginia', '1', 'fcc'], ['w215bj', '90.9', 'saint paul , virginia', '1', 'fcc']] |
2007 - 08 uci america tour | https://en.wikipedia.org/wiki/2007%E2%80%9308_UCI_America_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15519312-1.html.csv | majority | all of the races have a uci rating of 2.2 . | {'scope': 'all', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': '2.2', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'uci rating', '2.2'], 'result': True, 'ind': 0, 'tointer': 'for the uci rating records of all rows , all of them are equal to 2.2 .', 'tostr': 'all_eq { all_rows ; uci rating ; 2.2 } = true'} | all_eq { all_rows ; uci rating ; 2.2 } = true | for the uci rating records of all rows , all of them are equal to 2.2 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'uci rating_3': 3, '2.2_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'uci rating_3': 'uci rating', '2.2_4': '2.2'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'uci rating_3': [0], '2.2_4': [0]} | ['date', 'race name', 'location', 'uci rating', 'winner', 'team'] | [['7 - 14 october', 'clasico ciclistico banfoandes', 'venezuela', '2.2', 'sergio luis henao ( col )', 'colombia és pasión coldeportes'], ['7 - 14 october', 'vuelta chihuahua internacional', 'mexico', '2.2', 'francisco mancebo ( esp )', 'relax - gam'], ['20 october - 1 november', 'vuelta a guatemala', 'guatemala', '2.2', 'carlos lópez ( mex )', "canel 's - turbo - mayordomo"], ['6 - 11 november', 'doble copacabana gp fides', 'bolivia', '2.2', 'óscar soliz ( bol )', 'coordinadora ebsa'], ['15 - 25 november', 'tour de santa catarina', 'brazil', '2.2', 'alex diniz ( bra )', 'scott - marcondes cesar - são josé dos campos'], ['17 - 25 november', 'vuelta a ecuador', 'ecuador', '2.2', 'alex atapuma ( col )', 'indernariño'], ['14 - 28 december', 'vuelta ciclista a costa rica', 'costa rica', '2.2', 'henry raabe ( crc )', 'bcr - pizza hut']] |
volleyball at the summer olympics | https://en.wikipedia.org/wiki/Volleyball_at_the_Summer_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1613392-1.html.csv | aggregation | for volleyball at the summer olympics the total combined number of gold medals was 26 . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '26', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'gold'], 'result': '26', 'ind': 0, 'tostr': 'sum { all_rows ; gold }'}, '26'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; gold } ; 26 } = true', 'tointer': 'the sum of the gold record of all rows is 26 .'} | round_eq { sum { all_rows ; gold } ; 26 } = true | the sum of the gold record of all rows is 26 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'gold_4': 4, '26_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '26_5': '26'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'gold_4': [0], '26_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'soviet union', '7', '4', '1', '12'], ['2', 'brazil', '4', '3', '2', '9'], ['3', 'japan', '3', '3', '3', '9'], ['4', 'united states', '3', '3', '2', '8'], ['5', 'cuba', '3', '0', '2', '5'], ['6', 'china', '2', '1', '2', '5'], ['7', 'russia', '1', '3', '2', '6'], ['8', 'netherlands', '1', '1', '0', '2'], ['9', 'poland', '1', '0', '2', '3'], ['10', 'yugoslavia', '1', '0', '1', '2'], ['11', 'italy', '0', '2', '3', '5'], ['12', 'east germany', '0', '2', '0', '2'], ['13', 'bulgaria', '0', '1', '1', '2'], ['13', 'czechoslovakia', '0', '1', '1', '2'], ['15', 'peru', '0', '1', '0', '1'], ['15', 'unified team', '0', '1', '0', '1'], ['17', 'argentina', '0', '0', '1', '1'], ['17', 'north korea', '0', '0', '1', '1'], ['17', 'south korea', '0', '0', '1', '1'], ['17', 'romania', '0', '0', '1', '1']] |
html5 video | https://en.wikipedia.org/wiki/HTML5_video | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26099252-1.html.csv | majority | the majority of the latest stable releases were in 2013 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '2013', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'latest stable release', '2013'], 'result': True, 'ind': 0, 'tointer': 'for the latest stable release records of all rows , most of them fuzzily match to 2013 .', 'tostr': 'most_eq { all_rows ; latest stable release ; 2013 } = true'} | most_eq { all_rows ; latest stable release ; 2013 } = true | for the latest stable release records of all rows , most of them fuzzily match to 2013 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'latest stable release_3': 3, '2013_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'latest stable release_3': 'latest stable release', '2013_4': '2013'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'latest stable release_3': [0], '2013_4': [0]} | ['browser', 'operating system', 'latest stable release', 'theora', 'h264', 'vp8 ( webm )', 'vp9 ( webm )'] | [['android browser', 'android', '4.2.1 jelly bean ( november 27 , 2012 )', '2.3', '3.0', '2.3', 'no'], ['chromium', 'all supported', 'n / a', 'r18297', 'manual install', 'r47759', 'r172738'], ['google chrome', '30.0.1599.101 ( october 15 , 2013 )', '30.0.1599.101 ( october 15 , 2013 )', '3.0', '3.0', '6.0', '29.0'], ['internet explorer', 'windows', 'v11 .0.9600.16384 ( 17 october 2013 )', 'manual install', '9.0', 'manual install', 'no'], ['internet explorer', 'windows phone', '10.0 ( november 21 , 2012 )', 'no', '9.0', 'no', 'no'], ['internet explorer', 'windows rt', '10.0', 'no', '10.0', 'no', 'no'], ['konqueror', 'all supported', '4.11.2 ( 1 october 2013 )', '4.4', '4.4', '4.4', 'no'], ['safari', 'ios', '7.0 ( october 24 , 2013 )', 'no', '3.1', 'no', 'no'], ['safari', 'macos x', '7.0 ( october 24 , 2013 )', 'manual install', '3.1', 'manual install', 'no']] |
flavio cipolla | https://en.wikipedia.org/wiki/Flavio_Cipolla | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16474033-12.html.csv | majority | a majority of events during flavio cipolla took place on clay court . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'clay', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to clay .', 'tostr': 'most_eq { all_rows ; surface ; clay } = true'} | most_eq { all_rows ; surface ; clay } = true | for the surface records of all rows , most of them fuzzily match to clay . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'clay_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'clay_4': 'clay'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'clay_4': [0]} | ['date', 'tournament', 'surface', 'partnering', 'opponents', 'score'] | [['29 june 2004', 'mantua , italy', 'clay', 'alessandro motti', 'daniele bracciali giorgio galimberti', '6 - 0 , 6 - 4'], ['25 july 2005', 'togliatti , russia', 'hard', 'massimo ocera', 'scott lipsky mark nielsen', '6 - 2 , 6 - 3'], ['12 september 2005', 'seville , spain', 'clay', 'alessandro motti', 'marcos daniel fernando vicente', '6 - 2 , 6 - 7 ( 1 - 7 ) , 7 - 5'], ['3 october 2005', 'rome , italy', 'clay', 'alessandro motti', 'konstantinos economidis vasilis mazarakis', '6 - 4 , 7 - 6 ( 7 - 4 )'], ['20 march 2006', 'barletta , italy', 'clay', 'alessandro motti', 'santiago ventura fernando vicente', '7 - 6 ( 7 - 2 ) , 4 - 6 ,'], ['15 may 2006', 'san remo , italy', 'clay', 'francesco piccari', 'julien benneteau nicolas mahut', '6 - 4 , 7 - 6 ( 8 - 6 )'], ['30 may 2006', 'turin , italy', 'clay', 'leonardo azzaro', 'marcel granollers marc lópez', '6 - 4 , 6 - 3'], ['11 june 2007', 'košice , slovak republic', 'clay', 'leonardo azzaro', 'filip polášek lukáš rosol', '6 - 1 , 7 - 6 ( 7 - 5 )'], ['23 july 2007', 'poznań , poland', 'clay', 'ivo klec', 'marc lópez santiago ventura', '6 - 2 , 5 - 7 ,'], ['27 august 2007', 'como , italy', 'clay', 'maro pedrini', 'máximo gonzález simone vagnozzi', '7 - 6 ( 7 - 5 ) , 6 - 4'], ['4 september 2007', 'genoa , italy', 'clay', 'simone bolelli', 'daniele giorgini simone vagnozzi', '6 - 3 , 6 - 1'], ['11 october 2009', 'tarragona , spain', 'clay', 'alessandro motti', 'tomasz bednarek mateusz kowalczyk', '6 - 1 , 6 - 1'], ['10 january 2010', 'nouméa , new caledonia', 'hard', 'simone vagnozzi', 'nicolas devilder édouard roger - vasselin', '5 - 7 , 6 - 2 ,'], ['9 january 2011', 'nouméa , new caledonia', 'hard', 'simone vagnozzi', 'dominik meffert frederik nielsen', '7 - 6 ( 7 - 4 ) , 5 - 7 ,'], ['24 september 2011', 'izmir , turkey', 'hard', 'thomas fabbiano', 'travis rettenmaier simon stadler', '6 - 0 , 6 - 2']] |
list of england national rugby union team results 1980 - 89 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-8.html.csv | count | of the games listed england played three games at the concord oval in sydney . | {'scope': 'all', 'criterion': 'equal', 'value': 'concord oval , sydney', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'concord oval , sydney'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to concord oval , sydney .', 'tostr': 'filter_eq { all_rows ; venue ; concord oval , sydney }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; concord oval , sydney } }', 'tointer': 'select the rows whose venue record fuzzily matches to concord oval , sydney . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; concord oval , sydney } } ; 3 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to concord oval , sydney . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; venue ; concord oval , sydney } } ; 3 } = true | select the rows whose venue record fuzzily matches to concord oval , sydney . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'concord oval, sydney_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'concord oval, sydney_6': 'concord oval , sydney', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'concord oval, sydney_6': [0], '3_7': [2]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['ireland', '17', '07 / 02 / 1987', 'lansdowne road , dublin', 'five nations'], ['france', '19', '21 / 02 / 1987', 'twickenham , london', 'five nations'], ['wales', '19', '07 / 03 / 1987', 'cardiff arms park , cardiff', 'five nations'], ['scotland', '12', '04 / 04 / 1987', 'twickenham , london', 'five nations'], ['australia', '19', '23 / 05 / 1987', 'concord oval , sydney', '1987 rugby world cup'], ['japan', '7', '30 / 05 / 1987', 'concord oval , sydney', '1987 rugby world cup'], ['usa', '6', '03 / 06 / 1987', 'concord oval , sydney', '1987 rugby world cup'], ['wales', '16', '08 / 06 / 1987', 'ballymore stadium , brisbane', '1987 rugby world cup']] |
economy of europe | https://en.wikipedia.org/wiki/Economy_of_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1069072-1.html.csv | ordinal | london has the second greatest population of the cities of europe . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'population m ( luz )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population m ( luz ) ; 2 }'}, 'city'], 'result': 'london', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population m ( luz ) ; 2 } ; city }'}, 'london'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; population m ( luz ) ; 2 } ; city } ; london } = true', 'tointer': 'select the row whose population m ( luz ) record of all rows is 2nd maximum . the city record of this row is london .'} | eq { hop { nth_argmax { all_rows ; population m ( luz ) ; 2 } ; city } ; london } = true | select the row whose population m ( luz ) record of all rows is 2nd maximum . the city record of this row is london . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population m (luz)_5': 5, '2_6': 6, 'city_7': 7, 'london_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'population m (luz)_5': 'population m ( luz )', '2_6': '2', 'city_7': 'city', 'london_8': 'london'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population m (luz)_5': [0], '2_6': [0], 'city_7': [1], 'london_8': [2]} | ['rank', 'city', 'state', 'gdp in id b', 'population m ( luz )', 'gdp per capita id k', 'eurozone'] | [['1', 'paris', 'france', '731', '11.5', '62.4', 'y'], ['2', 'london', 'united kingdom', '565', '11.9', '49.4', 'n'], ['3', 'moscow', 'russia', '321', '10.5', '30.6', 'n'], ['4', 'madrid', 'spain', '230', '5.80', '39.7', 'y'], ['5', 'istanbul', 'turkey', '187', '13.2', '14.2', 'n'], ['6', 'barcelona', 'spain', '177', '4.97', '35.6', 'y'], ['7', 'rome', 'italy', '144', '3.46', '41.6', 'y'], ['8', 'milan', 'italy', '136', '3.08', '44.2', 'y'], ['9', 'vienna', 'austria', '122', '2.18', '56.0', 'y'], ['10', 'lisbon', 'portugal', '98', '2.44', '40.2', 'y'], ['11', 'athens', 'greece', '96', '4.01', '23.9', 'y'], ['12', 'berlin', 'germany', '95', '4.97', '19.1', 'y']] |
2008 kentucky wildcats football team | https://en.wikipedia.org/wiki/2008_Kentucky_Wildcats_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14624447-26.html.csv | superlative | of the starters for the middle tennessee game in the 2008 kentucky wildcats season , justin jeffries weighed the most . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '11', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'weight'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; weight }'}, 'name'], 'result': 'justin jeffries', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; weight } ; name }'}, 'justin jeffries'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; weight } ; name } ; justin jeffries } = true', 'tointer': 'select the row whose weight record of all rows is maximum . the name record of this row is justin jeffries .'} | eq { hop { argmax { all_rows ; weight } ; name } ; justin jeffries } = true | select the row whose weight record of all rows is maximum . the name record of this row is justin jeffries . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'weight_5': 5, 'name_6': 6, 'justin jeffries_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'weight_5': 'weight', 'name_6': 'name', 'justin jeffries_7': 'justin jeffries'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'weight_5': [0], 'name_6': [1], 'justin jeffries_7': [2]} | ['position', 'number', 'name', 'height', 'weight', 'class', 'hometown', 'games ↑'] | [['qb', '5', 'mike hartline', "6 ' 6", '205', 'rs - so', 'canton , ohio', '3'], ['tb', '28', 'tony dixon', "5 ' 9", '203', 'sr', 'parrish , alabama', '3'], ['fb', '38', 'john conner', "5 ' 11", '230', 'jr', 'west chester , ohio', '3'], ['wr', '12', 'dicky lyons', "5 ' 11", '190', 'sr', 'new orleans , louisiana', '3'], ['wr', '81', 'kyrus lanxter', "6 ' 3", '193', 'so', 'alcoa , tennessee', '1'], ['te', '80', 'tc drake', "6 ' 6", '242', 'jr', 'bardstown , kentucky', '1'], ['lt', '52', 'billy joe murphy', "6 ' 6", '292', 'rs - fr', 'gamaliel , kentucky', '2'], ['lg', '72', 'zipp duncan', "6 ' 5", '295', 'jr', 'magnolia , kentucky', '3'], ['c', '61', 'jorge gonzález', "6 ' 3", '303', 'jr', 'tampa bay , florida', '3'], ['rg', '73', 'jess beets', "6 ' 2", '293', 'sr', 'dove canyon , california', '3'], ['rt', '76', 'justin jeffries', "6 ' 6", '310', 'jr', 'louisville , kentucky', '3']] |
colin morgan | https://en.wikipedia.org/wiki/Colin_Morgan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17973650-5.html.csv | unique | 2008 was the only year colin morgan won a newcomer award . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1,5', 'criterion': 'fuzzily_match', 'value': 'newcomer', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'newcomer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to newcomer .', 'tostr': 'filter_eq { all_rows ; category ; newcomer }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; category ; newcomer } }', 'tointer': 'select the rows whose category record fuzzily matches to newcomer . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'newcomer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to newcomer .', 'tostr': 'filter_eq { all_rows ; category ; newcomer }'}, 'year'], 'result': '2008', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; category ; newcomer } ; year }'}, '2008'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; category ; newcomer } ; year } ; 2008 }', 'tointer': 'the year record of this unqiue row is 2008 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'newcomer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to newcomer .', 'tostr': 'filter_eq { all_rows ; category ; newcomer }'}, 'result'], 'result': 'won', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; category ; newcomer } ; result }'}, 'won'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; category ; newcomer } ; result } ; won }', 'tointer': 'the result record of this unqiue row is won .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; category ; newcomer } ; year } ; 2008 } ; eq { hop { filter_eq { all_rows ; category ; newcomer } ; result } ; won } }', 'tointer': 'the year record of this unqiue row is 2008 . the result record of this unqiue row is won .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; category ; newcomer } } ; and { eq { hop { filter_eq { all_rows ; category ; newcomer } ; year } ; 2008 } ; eq { hop { filter_eq { all_rows ; category ; newcomer } ; result } ; won } } } = true', 'tointer': 'select the rows whose category record fuzzily matches to newcomer . there is only one such row in the table . the year record of this unqiue row is 2008 . the result record of this unqiue row is won .'} | and { only { filter_eq { all_rows ; category ; newcomer } } ; and { eq { hop { filter_eq { all_rows ; category ; newcomer } ; year } ; 2008 } ; eq { hop { filter_eq { all_rows ; category ; newcomer } ; result } ; won } } } = true | select the rows whose category record fuzzily matches to newcomer . there is only one such row in the table . the year record of this unqiue row is 2008 . the result record of this unqiue row is won . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'category_10': 10, 'newcomer_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'year_12': 12, '2008_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'result_14': 14, 'won_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'category_10': 'category', 'newcomer_11': 'newcomer', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_12': 'year', '2008_13': '2008', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'result_14': 'result', 'won_15': 'won'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'category_10': [0], 'newcomer_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'year_12': [2], '2008_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'result_14': [4], 'won_15': [5]} | ['year', 'award', 'category', 'role', 'result'] | [['2008', 'variety club showbiz awards', 'outstanding newcomer', 'merlin in merlin', 'won'], ['2009', 'monte carlo tv festival awards', 'outstanding actor ( drama )', 'merlin in merlin', 'nominated'], ['2010', 'monte carlo tv festival awards', 'outstanding actor ( drama )', 'merlin in merlin', 'nominated'], ['2011', 'monte carlo tv festival awards', 'outstanding actor ( drama )', 'merlin in merlin', 'nominated'], ['2012', 'virgin media tv awards', 'best actor', 'merlin in merlin', 'won'], ['2013', 'national television award', 'drama performance : male', 'merlin in merlin', 'won']] |
antonella capriotti | https://en.wikipedia.org/wiki/Antonella_Capriotti | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12273246-1.html.csv | majority | for antonella capriotti , for competitions in the 1990s , most of her performances were for triple jump . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'triple jump', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': '199'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '199'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; year ; 199 }', 'tointer': 'select the rows whose year record fuzzily matches to 199 .'}, 'performance', 'triple jump'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 199 . for the performance records of these rows , most of them fuzzily match to triple jump .', 'tostr': 'most_eq { filter_eq { all_rows ; year ; 199 } ; performance ; triple jump } = true'} | most_eq { filter_eq { all_rows ; year ; 199 } ; performance ; triple jump } = true | select the rows whose year record fuzzily matches to 199 . for the performance records of these rows , most of them fuzzily match to triple jump . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'year_4': 4, '199_5': 5, 'performance_6': 6, 'triple jump_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'year_4': 'year', '199_5': '199', 'performance_6': 'performance', 'triple jump_7': 'triple jump'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'year_4': [0], '199_5': [0], 'performance_6': [1], 'triple jump_7': [1]} | ['year', 'competition', 'venue', 'position', 'performance'] | [['1983', 'mediterranean games', 'casablanca , morocco', '3rd', 'long jump'], ['1987', 'world indoor championships', 'indianapolis , united states', '8th', 'long jump'], ['1987', 'european indoor championships', 'liãvin , france', '6th', 'long jump'], ['1987', 'mediterranean games', 'latakia , syria', '1st', 'long jump'], ['1988', 'european indoor championships', 'budapest , hungary', '4th', 'long jump'], ['1989', 'world indoor championships', 'budapest , hungary', '5th', 'long jump'], ['1989', 'european indoor championships', 'the hague , netherlands', '4th', 'long jump'], ['1992', 'european indoor championships', 'genoa , italy', '7th', 'long jump'], ['1992', 'european indoor championships', 'genoa , italy', '9th', 'triple jump'], ['1993', 'world indoor championships', 'toronto , canada', '10th', 'long jump'], ['1993', 'world indoor championships', 'toronto , canada', '4th', 'triple jump'], ['1993', 'world championships', 'stuttgart , germany', '6th', 'triple jump'], ['1997', 'mediterranean games', 'bari , italy', '3rd', 'triple jump']] |
loongson | https://en.wikipedia.org/wiki/Loongson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1764207-1.html.csv | comparative | the stls2f model loongson processor operates with a higher frequency than the stls2e model processor . | {'row_1': '7', 'row_2': '6', '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', 'model', 'stls2f'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose model record fuzzily matches to stls2f .', 'tostr': 'filter_eq { all_rows ; model ; stls2f }'}, 'frequency'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; model ; stls2f } ; frequency }', 'tointer': 'select the rows whose model record fuzzily matches to stls2f . take the frequency record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'model', 'stls2e'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose model record fuzzily matches to stls2e .', 'tostr': 'filter_eq { all_rows ; model ; stls2e }'}, 'frequency'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; model ; stls2e } ; frequency }', 'tointer': 'select the rows whose model record fuzzily matches to stls2e . take the frequency record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; model ; stls2f } ; frequency } ; hop { filter_eq { all_rows ; model ; stls2e } ; frequency } } = true', 'tointer': 'select the rows whose model record fuzzily matches to stls2f . take the frequency record of this row . select the rows whose model record fuzzily matches to stls2e . take the frequency record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; model ; stls2f } ; frequency } ; hop { filter_eq { all_rows ; model ; stls2e } ; frequency } } = true | select the rows whose model record fuzzily matches to stls2f . take the frequency record of this row . select the rows whose model record fuzzily matches to stls2e . take the frequency 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, 'model_7': 7, 'stls2f_8': 8, 'frequency_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'model_11': 11, 'stls2e_12': 12, 'frequency_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', 'model_7': 'model', 'stls2f_8': 'stls2f', 'frequency_9': 'frequency', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'model_11': 'model', 'stls2e_12': 'stls2e', 'frequency_13': 'frequency'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'model_7': [0], 'stls2f_8': [0], 'frequency_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'model_11': [1], 'stls2e_12': [1], 'frequency_13': [3]} | ['name / generation', 'model', 'frequency', 'architecture version', 'cores', 'process'] | [['godson - 1 ( embedded cpu )', '1', '266', 'mips32', '1', '180'], ['godson - 1 ( embedded cpu )', '1a', '300', 'mips32', '1', '130'], ['godson - 1 ( embedded cpu )', '1b', '200', 'mips32', '1', '130'], ['godson - 2 ( singlecore )', '2b', '250', 'mips - iii 64 - bit', '1', '180'], ['godson - 2 ( singlecore )', '2c', '450', 'mips - iii 64 - bit', '1', '180'], ['godson - 2 ( singlecore )', 'stls2e', '1000', 'mips - iii 64 - bit', '1', '90'], ['godson - 2 ( singlecore )', 'stls2f', '1200', 'mips - iii 64 - bit', '1', '90'], ['godson - 2 ( singlecore )', 'l2 g', '9001000', 'mips64', '1', '65'], ['godson - 2 ( singlecore )', 'l2h', '1000', 'mips64', '1', '65'], ['godson - 3 ( multicore )', 'l3a / l2 gq', '1000', 'mips64', '4', '65'], ['godson - 3 ( multicore )', 'l3b', '1050', 'mips64', '8', '65'], ['godson - 3 ( multicore )', 'l3c', '1500 +', 'mips64', '16', '28'], ['godson - t ( manycore )', 'godson - t', '1000', 'mips32', '64', '28'], ['name / generation', 'model', 'frequency', 'architecture version', 'cores', 'process']] |
2003 mls superdraft | https://en.wikipedia.org/wiki/2003_MLS_SuperDraft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1014145-2.html.csv | unique | doug warren was the only player in this round of the draft that played position gk . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'gk', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'gk'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to gk .', 'tostr': 'filter_eq { all_rows ; position ; gk }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; gk } }', 'tointer': 'select the rows whose position record fuzzily matches to gk . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'gk'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to gk .', 'tostr': 'filter_eq { all_rows ; position ; gk }'}, 'player'], 'result': 'doug warren', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; position ; gk } ; player }'}, 'doug warren'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; position ; gk } ; player } ; doug warren }', 'tointer': 'the player record of this unqiue row is doug warren .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; position ; gk } } ; eq { hop { filter_eq { all_rows ; position ; gk } ; player } ; doug warren } } = true', 'tointer': 'select the rows whose position record fuzzily matches to gk . there is only one such row in the table . the player record of this unqiue row is doug warren .'} | and { only { filter_eq { all_rows ; position ; gk } } ; eq { hop { filter_eq { all_rows ; position ; gk } ; player } ; doug warren } } = true | select the rows whose position record fuzzily matches to gk . there is only one such row in the table . the player record of this unqiue row is doug warren . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'position_7': 7, 'gk_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'doug warren_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'position_7': 'position', 'gk_8': 'gk', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'doug warren_10': 'doug warren'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'position_7': [0], 'gk_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'doug warren_10': [3]} | ['pick', 'mls team', 'player', 'position', 'affiliation'] | [['11', 'dc united', 'brian carroll', 'm', 'wake forest university'], ['12', 'metrostars', 'eddie gaven', 'm', 'nike project - 40'], ['13', 'san jose earthquakes', 'arturo alvarez', 'm', 'nike project - 40'], ['14', 'dc united', 'doug warren', 'gk', 'clemson university'], ['15', 'dallas burn', 'jason thompson', 'f', 'eastern illinois university'], ['16', 'los angeles galaxy', 'scot thompson', 'd', 'ucla'], ['17', 'metrostars', 'tim regan', 'd', 'bradley university'], ['18', 'chicago fire', 'damani ralph', 'f', 'university of connecticut'], ['19', 'los angeles galaxy', 'arturo torres', 'm', 'loyola marymount university'], ['20', 'los angeles galaxy', 'ricky lewis', 'd', 'clemson university']] |
economy of south america | https://en.wikipedia.org/wiki/Economy_of_South_America | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1222653-11.html.csv | unique | the us dollar is the only currency whose central bank does not have the word bank in their title . | {'scope': 'all', 'row': '6', 'col': '5', 'col_other': '2', 'criterion': 'not_equal', 'value': 'bank', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'central bank', 'bank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose central bank record does not match to bank .', 'tostr': 'filter_not_eq { all_rows ; central bank ; bank }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_not_eq { all_rows ; central bank ; bank } }', 'tointer': 'select the rows whose central bank record does not match to bank . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'central bank', 'bank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose central bank record does not match to bank .', 'tostr': 'filter_not_eq { all_rows ; central bank ; bank }'}, 'currency'], 'result': 'us dollar ( usd )', 'ind': 2, 'tostr': 'hop { filter_not_eq { all_rows ; central bank ; bank } ; currency }'}, 'us dollar ( usd )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_not_eq { all_rows ; central bank ; bank } ; currency } ; us dollar ( usd ) }', 'tointer': 'the currency record of this unqiue row is us dollar ( usd ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_not_eq { all_rows ; central bank ; bank } } ; eq { hop { filter_not_eq { all_rows ; central bank ; bank } ; currency } ; us dollar ( usd ) } } = true', 'tointer': 'select the rows whose central bank record does not match to bank . there is only one such row in the table . the currency record of this unqiue row is us dollar ( usd ) .'} | and { only { filter_not_eq { all_rows ; central bank ; bank } } ; eq { hop { filter_not_eq { all_rows ; central bank ; bank } ; currency } ; us dollar ( usd ) } } = true | select the rows whose central bank record does not match to bank . there is only one such row in the table . the currency record of this unqiue row is us dollar ( usd ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_6': 6, 'central bank_7': 7, 'bank_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'currency_9': 9, 'us dollar (usd)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_6': 'all_rows', 'central bank_7': 'central bank', 'bank_8': 'bank', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'currency_9': 'currency', 'us dollar (usd)_10': 'us dollar ( usd )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_not_eq_0': [1, 2], 'all_rows_6': [0], 'central bank_7': [0], 'bank_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'currency_9': [2], 'us dollar (usd)_10': [3]} | ['country', 'currency', '1 euro =', '1 usd =', 'central bank'] | [['argentina', 'argentine peso ( ars )', '5.65', '4.20', 'central bank of argentina'], ['bolivia', 'bolivian boliviano ( bob )', '11.0985', '7.57080', 'central bank of bolivia'], ['brazil', 'brazilian real ( brl )', '2.58963', '1.76650', 'central bank of brazil'], ['chile', 'chilean peso ( clp )', '701.020', '507.580', 'central bank of chile'], ['colombia', 'colombian peso ( cop )', '2593.20', '1885.74', 'bank of the republic'], ['ecuador', 'us dollar ( usd )', '1.46611', '1', 'federal reserve'], ['guyana', 'guyanese dollar ( gyd )', '297.547', '202.950', 'bank of guyana'], ['paraguay', 'paraguayan guaraní ( pyg )', '6802.74', '4640.00', 'central bank of paraguay'], ['peru', 'peruvian nuevo sol ( pen )', '4.26966', '2.72440', 'central reserve bank of peru'], ['suriname', 'surinamese dollar ( srd )', '4.10543', '2.80000', 'central bank of suriname'], ['uruguay', 'uruguayan peso ( uyu )', '31.1529', '21.2470', 'central bank of uruguay'], ['venezuela', 'venezuelan bolívar fuerte ( vef )', '6.16331', '4.30000', 'central bank of venezuela']] |
list of virginia covered bridges | https://en.wikipedia.org/wiki/List_of_Virginia_covered_bridges | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14218015-1.html.csv | unique | the bob white bridge was the only one of virginia 's covered bridges that was built in 1921 . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '1921', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'built', '1921'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose built record is equal to 1921 .', 'tostr': 'filter_eq { all_rows ; built ; 1921 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; built ; 1921 } }', 'tointer': 'select the rows whose built record is equal to 1921 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'built', '1921'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose built record is equal to 1921 .', 'tostr': 'filter_eq { all_rows ; built ; 1921 }'}, 'name'], 'result': 'bob white', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; built ; 1921 } ; name }'}, 'bob white'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; built ; 1921 } ; name } ; bob white }', 'tointer': 'the name record of this unqiue row is bob white .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; built ; 1921 } } ; eq { hop { filter_eq { all_rows ; built ; 1921 } ; name } ; bob white } } = true', 'tointer': 'select the rows whose built record is equal to 1921 . there is only one such row in the table . the name record of this unqiue row is bob white .'} | and { only { filter_eq { all_rows ; built ; 1921 } } ; eq { hop { filter_eq { all_rows ; built ; 1921 } ; name } ; bob white } } = true | select the rows whose built record is equal to 1921 . there is only one such row in the table . the name record of this unqiue row is bob white . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'built_7': 7, '1921_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'bob white_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'built_7': 'built', '1921_8': '1921', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'bob white_10': 'bob white'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'built_7': [0], '1921_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'bob white_10': [3]} | ['name', 'county', 'location', 'built', 'length ( ft )', 'spans'] | [['biedler farm', 'rockingham', 'broadway', '1896', '93', 'smith creek'], ['bob white', 'patrick', 'woolwine', '1921', '80', 'smith river'], ['ck reynolds', 'giles', 'newport', '1919', '36', 'sinking creek'], ['humpback', 'alleghany', 'covington', '1857', '109', 'dunlap creek'], ["jack 's creek", 'patrick', 'woolwine', '1914', '48', 'smith river'], ['link farm', 'giles', 'newport', '1912', '49', 'sinking creek'], ["meem 's bottom", 'shenandoah', 'mount jackson', '1894', '204', 'north fork of the shenandoah river'], ['sinking creek', 'giles', 'newport', 'ca 1916', '71', 'sinking creek']] |
united states presidential election in new jersey , 2008 | https://en.wikipedia.org/wiki/United_States_presidential_election_in_New_Jersey%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20278716-2.html.csv | majority | most of the counties in new jersey voted for obama in the 2008 us presidential election . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '50.0 %', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'obama %', '50.0 %'], 'result': True, 'ind': 0, 'tointer': 'for the obama % records of all rows , most of them are greater than 50.0 % .', 'tostr': 'most_greater { all_rows ; obama % ; 50.0 % } = true'} | most_greater { all_rows ; obama % ; 50.0 % } = true | for the obama % records of all rows , most of them are greater than 50.0 % . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'obama %_3': 3, '50.0%_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'obama %_3': 'obama %', '50.0%_4': '50.0 %'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'obama %_3': [0], '50.0%_4': [0]} | ['county', 'obama %', 'obama', 'mccain %', 'mccain', 'others %', 'others'] | [['atlantic', '56.9 %', '67830', '41.8 %', '49902', '1.3 %', '1157'], ['bergen', '54.2 %', '225367', '44.7 %', '186118', '1.1 %', '4424'], ['burlington', '58.6 %', '131219', '40.1 %', '89626', '1.3 %', '2930'], ['camden', '67.2 %', '159259', '31.2 %', '68317', '1.4 %', '3304'], ['cape may', '44.9 %', '22893', '53.5 %', '27288', '1.6 %', '802'], ['cumberland', '60.0 %', '34919', '38.4 %', '22360', '1.6 %', '915'], ['essex', '75.9 %', '240306', '23.4 %', '73975', '0.7 %', '2181'], ['gloucester', '55.2 %', '77267', '43.1 %', '60315', '1.7 %', '2364'], ['hudson', '72.8 %', '154140', '26.2 %', '52354', '1.0 %', '2116'], ['hunterdon', '42.5 %', '29776', '55.8 %', '39092', '1.6 %', '1147'], ['mercer', '67.3 %', '107926', '31.3 %', '50397', '1.4 %', '2229'], ['middlesex', '60.2 %', '193812', '38.4 %', '122586', '1.4 %', '4367'], ['monmouth', '47.5 %', '148737', '51.2 %', '160433', '1.4 %', '4244'], ['morris', '45.4 %', '112275', '53.5 %', '132331', '1.2 %', '2913'], ['ocean', '40.1 %', '110189', '58.4 %', '16067', '1.5 %', '4111'], ['passaic', '60.3 %', '113257', '38.7 %', '71850', '1.0 %', '1904'], ['salem', '50.9 %', '16044', '47.0 %', '14816', '2.1 %', '672'], ['somerset', '52.4 %', '79321', '46.3 %', '70085', '1.3 %', '2024'], ['sussex', '38.8 %', '28840', '59.4 %', '44184', '1.9 %', '1393'], ['union', '63.6 %', '141417', '35.4 %', '78768', '1.0 %', '2241']] |
2002 new england patriots season | https://en.wikipedia.org/wiki/2002_New_England_Patriots_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10716117-3.html.csv | aggregation | in 2002 the new england patriots scored an average of 26 points at gillette stadium . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '26', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'gillette stadium'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'gillette stadium'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; game site ; gillette stadium }', 'tointer': 'select the rows whose game site record fuzzily matches to gillette stadium .'}, 'result'], 'result': '26', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; game site ; gillette stadium } ; result }'}, '26'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; game site ; gillette stadium } ; result } ; 26 } = true', 'tointer': 'select the rows whose game site record fuzzily matches to gillette stadium . the average of the result record of these rows is 26 .'} | round_eq { avg { filter_eq { all_rows ; game site ; gillette stadium } ; result } ; 26 } = true | select the rows whose game site record fuzzily matches to gillette stadium . the average of the result record of these rows is 26 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'gillette stadium_6': 6, 'result_7': 7, '26_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'gillette stadium_6': 'gillette stadium', 'result_7': 'result', '26_8': '26'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'gillette stadium_6': [0], 'result_7': [1], '26_8': [2]} | ['week', 'kickoff', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', '9:00 pm edt', 'september 9 , 2002', 'pittsburgh steelers', 'w 30 - 14', '1 - 0', 'gillette stadium', '68436'], ['2', '1:00 pm edt', 'september 15 , 2002', 'new york jets', 'w 44 - 7', '2 - 0', 'giants stadium', '78726'], ['3', '1:00 pm edt', 'september 22 , 2002', 'kansas city chiefs', 'w 41 - 38 ( ot )', '3 - 0', 'gillette stadium', '68436'], ['4', '4:15 pm edt', 'september 29 , 2002', 'san diego chargers', 'l 14 - 21', '3 - 1', 'qualcomm stadium', '66463'], ['5', '1:00 pm edt', 'october 6 , 2002', 'miami dolphins', 'l 13 - 26', '3 - 2', 'pro player stadium', '73369'], ['6', '1:00 pm edt', 'october 13 , 2002', 'green bay packers', 'l 10 - 28', '3 - 3', 'gillette stadium', '68436'], ['7', '-', '-', '-', '-', '-', '-', ''], ['8', '4:15 pm est', 'october 27 , 2002', 'denver broncos', 'l 16 - 24', '3 - 4', 'gillette stadium', '68436'], ['9', '1:00 pm est', 'november 3 , 2002', 'buffalo bills', 'w 38 - 7', '4 - 4', 'ralph wilson stadium', '73448'], ['10', '4:15 pm est', 'november 10 , 2002', 'chicago bears', 'w 33 - 30', '5 - 4', 'memorial stadium', '63105'], ['11', '8:30 pm est', 'november 17 , 2002', 'oakland raiders', 'l 20 - 27', '5 - 5', 'network associates coliseum', '62552'], ['12', '1:00 pm est', 'november 24 , 2002', 'minnesota vikings', 'w 24 - 17', '6 - 5', 'gillette stadium', '68436'], ['13', '12:30 pm est', 'november 28 , 2002', 'detroit lions', 'w 20 - 12', '7 - 5', 'ford field', '62109'], ['14', '1:00 pm est', 'december 8 , 2002', 'buffalo bills', 'w 27 - 17', '8 - 5', 'gillette stadium', '68436'], ['15', '9:00 pm est', 'december 16 , 2002', 'tennessee titans', 'l 7 - 24', '8 - 6', 'the coliseum', '68809'], ['16', '8:30 pm est', 'december 22 , 2002', 'new york jets', 'l 17 - 30', '8 - 7', 'gillette stadium', '68436'], ['17', '1:00 pm est', 'december 29 , 2002', 'miami dolphins', 'w 27 - 24 ( ot )', '9 - 7', 'gillette stadium', '68436']] |
1983 - 84 fa cup | https://en.wikipedia.org/wiki/1983%E2%80%9384_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17437287-6.html.csv | superlative | the replay match between southampton and sheffield wednesday had the most goals scored . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1,2,4', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'tie no'], 'result': 'replay', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; tie no }'}, 'replay'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; tie no } ; replay }', 'tointer': 'select the row whose score record of all rows is maximum . the tie no record of this row is replay .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'home team'], 'result': 'southampton', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; score } ; home team }'}, 'southampton'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; score } ; home team } ; southampton }', 'tointer': 'the home team record of this row is southampton .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'away team'], 'result': 'sheffield wednesday', 'ind': 5, 'tostr': 'hop { argmax { all_rows ; score } ; away team }'}, 'sheffield wednesday'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { argmax { all_rows ; score } ; away team } ; sheffield wednesday }', 'tointer': 'the away team record of this row is sheffield wednesday .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { argmax { all_rows ; score } ; home team } ; southampton } ; eq { hop { argmax { all_rows ; score } ; away team } ; sheffield wednesday } }', 'tointer': 'the home team record of this row is southampton . the away team record of this row is sheffield wednesday .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { argmax { all_rows ; score } ; tie no } ; replay } ; and { eq { hop { argmax { all_rows ; score } ; home team } ; southampton } ; eq { hop { argmax { all_rows ; score } ; away team } ; sheffield wednesday } } } = true', 'tointer': 'select the row whose score record of all rows is maximum . the tie no record of this row is replay . the home team record of this row is southampton . the away team record of this row is sheffield wednesday .'} | and { eq { hop { argmax { all_rows ; score } ; tie no } ; replay } ; and { eq { hop { argmax { all_rows ; score } ; home team } ; southampton } ; eq { hop { argmax { all_rows ; score } ; away team } ; sheffield wednesday } } } = true | select the row whose score record of all rows is maximum . the tie no record of this row is replay . the home team record of this row is southampton . the away team record of this row is sheffield wednesday . | 11 | 9 | {'and_8': 8, 'result_9': 9, 'str_eq_2': 2, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_10': 10, 'score_11': 11, 'tie no_12': 12, 'replay_13': 13, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'home team_14': 14, 'southampton_15': 15, 'str_eq_6': 6, 'str_hop_5': 5, 'away team_16': 16, 'sheffield wednesday_17': 17} | {'and_8': 'and', 'result_9': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_10': 'all_rows', 'score_11': 'score', 'tie no_12': 'tie no', 'replay_13': 'replay', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'home team_14': 'home team', 'southampton_15': 'southampton', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'away team_16': 'away team', 'sheffield wednesday_17': 'sheffield wednesday'} | {'and_8': [9], 'result_9': [], 'str_eq_2': [8], 'str_hop_1': [2], 'argmax_0': [1, 3, 5], 'all_rows_10': [0], 'score_11': [0], 'tie no_12': [1], 'replay_13': [2], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'home team_14': [3], 'southampton_15': [4], 'str_eq_6': [7], 'str_hop_5': [6], 'away team_16': [5], 'sheffield wednesday_17': [6]} | ['tie no', 'home team', 'score', 'away team', 'date'] | [['1', 'notts county', '1 - 2', 'everton', '10 march 1984'], ['2', 'sheffield wednesday', '0 - 0', 'southampton', '11 march 1984'], ['replay', 'southampton', '5 - 1', 'sheffield wednesday', '20 march 1984'], ['3', 'plymouth argyle', '0 - 0', 'derby county', '10 march 1984'], ['replay', 'derby county', '0 - 1', 'plymouth argyle', '14 march 1984'], ['4', 'birmingham city', '1 - 3', 'watford', '10 march 1984']] |
federal league ( ohsaa ) | https://en.wikipedia.org/wiki/Federal_League_%28OHSAA%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26466528-1.html.csv | ordinal | in the federal league , the school that joined second to last was lake . | {'row': '5', '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', 'join date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; join date ; 2 }'}, 'school'], 'result': 'lake', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; join date ; 2 } ; school }'}, 'lake'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; join date ; 2 } ; school } ; lake } = true', 'tointer': 'select the row whose join date record of all rows is 2nd maximum . the school record of this row is lake .'} | eq { hop { nth_argmax { all_rows ; join date ; 2 } ; school } ; lake } = true | select the row whose join date record of all rows is 2nd maximum . the school record of this row is lake . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'join date_5': 5, '2_6': 6, 'school_7': 7, 'lake_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', 'join date_5': 'join date', '2_6': '2', 'school_7': 'school', 'lake_8': 'lake'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'join date_5': [0], '2_6': [0], 'school_7': [1], 'lake_8': [2]} | ['school', 'nickname', 'location', 'colors', 'join date'] | [['canton mckinley', 'bulldogs', 'canton', 'red , black', '2003'], ['glenoak', 'golden eagles', 'canton', 'forest green , vegas gold', '1975'], ['hoover', 'vikings', 'north canton', 'black , orange', '1968'], ['jackson', 'polar bears', 'jackson township', 'purple , gold', '1964'], ['lake', 'blue streaks', 'uniontown', 'blue , red , white', '1987']] |
2008 - 09 miami heat season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Miami_Heat_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17311783-8.html.csv | aggregation | in the 2008 - 09 miami heat season , when mario chalmers had at least a portion of the high assists , his average number of assists was 8.33 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '8.33', 'subset': {'col': '6', 'criterion': 'fuzzily_match', 'value': 'mario chalmers'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'mario chalmers'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; high assists ; mario chalmers }', 'tointer': 'select the rows whose high assists record fuzzily matches to mario chalmers .'}, 'high assists'], 'result': '8.33', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; high assists ; mario chalmers } ; high assists }'}, '8.33'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; high assists ; mario chalmers } ; high assists } ; 8.33 } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to mario chalmers . the average of the high assists record of these rows is 8.33 .'} | round_eq { avg { filter_eq { all_rows ; high assists ; mario chalmers } ; high assists } ; 8.33 } = true | select the rows whose high assists record fuzzily matches to mario chalmers . the average of the high assists record of these rows is 8.33 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'high assists_5': 5, 'mario chalmers_6': 6, 'high assists_7': 7, '8.33_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'high assists_5': 'high assists', 'mario chalmers_6': 'mario chalmers', 'high assists_7': 'high assists', '8.33_8': '8.33'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'high assists_5': [0], 'mario chalmers_6': [0], 'high assists_7': [1], '8.33_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high assists', 'location attendance', 'record'] | [['47', 'february 2', 'la clippers', 'w 119 - 95 ( ot )', 'dwyane wade ( 32 )', 'dwyane wade ( 9 )', 'american airlines arena 15985', '26 - 21'], ['48', 'february 4', 'detroit', 'l 90 - 93 ( ot )', 'dwyane wade ( 29 )', 'dwyane wade ( 13 )', 'the palace of auburn hills 21720', '26 - 22'], ['49', 'february 7', 'philadelphia', 'l 84 - 94 ( ot )', 'dwyane wade ( 21 )', 'dwyane wade , mario chalmers ( 7 )', 'wachovia center 17216', '26 - 23'], ['50', 'february 8', 'charlotte', 'w 96 - 92 ( ot )', 'dwyane wade ( 22 )', 'mario chalmers ( 13 )', 'american airlines arena 17656', '27 - 23'], ['51', 'february 10', 'denver', 'l 82 - 99 ( ot )', 'dwyane wade ( 33 )', 'mario chalmers ( 5 )', 'american airlines arena 16784', '27 - 24'], ['52', 'february 12', 'chicago', 'w 95 - 93 ( ot )', 'dwyane wade ( 24 )', 'dwyane wade ( 7 )', 'united center 21801', '28 - 24'], ['53', 'february 18', 'minnesota', 'l 104 - 111 ( ot )', 'dwyane wade ( 37 )', 'dwyane wade ( 12 )', 'american airlines arena 17525', '28 - 25'], ['54', 'february 21', 'philadelphia', 'w 97 - 91 ( ot )', 'dwyane wade ( 25 )', 'dwyane wade ( 9 )', 'american airlines arena 19600', '29 - 25'], ['55', 'february 22', 'orlando', 'l 99 - 122 ( ot )', 'dwyane wade ( 50 )', 'dwyane wade ( 5 )', 'amway arena 17461', '29 - 26'], ['56', 'february 24', 'detroit', 'w 103 - 91 ( ot )', 'dwyane wade ( 31 )', 'dwyane wade ( 16 )', 'american airlines arena 19600', '30 - 26'], ['57', 'february 27', 'atlanta', 'l 83 - 91 ( ot )', 'michael beasley ( 23 )', 'dwyane wade ( 10 )', 'philips arena 19157', '30 - 27'], ['58', 'february 28', 'new york', 'w 120 - 115 ( ot )', 'dwyane wade ( 46 )', 'dwyane wade ( 10 )', 'american airlines arena 19600', '31 - 27']] |
thomaz bellucci | https://en.wikipedia.org/wiki/Thomaz_Bellucci | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17436425-8.html.csv | comparative | of the tournaments that thomaz bellucci played in , the tournament in tunisia was 7 days before the tournament in morocco . | {'row_1': '5', 'row_2': '6', 'col': '2', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '7 days', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'tunis , tunisia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to tunis , tunisia .', 'tostr': 'filter_eq { all_rows ; tournament ; tunis , tunisia }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; tunis , tunisia } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to tunis , tunisia . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'rabat , morocco'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to rabat , morocco .', 'tostr': 'filter_eq { all_rows ; tournament ; rabat , morocco }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; rabat , morocco } ; date }', 'tointer': 'select the rows whose tournament record fuzzily matches to rabat , morocco . take the date record of this row .'}], 'result': '-7 days', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; tournament ; tunis , tunisia } ; date } ; hop { filter_eq { all_rows ; tournament ; rabat , morocco } ; date } }'}, '-7 days'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; tournament ; tunis , tunisia } ; date } ; hop { filter_eq { all_rows ; tournament ; rabat , morocco } ; date } } ; -7 days } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to tunis , tunisia . take the date record of this row . select the rows whose tournament record fuzzily matches to rabat , morocco . take the date record of this row . the second record is 7 days larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; tournament ; tunis , tunisia } ; date } ; hop { filter_eq { all_rows ; tournament ; rabat , morocco } ; date } } ; -7 days } = true | select the rows whose tournament record fuzzily matches to tunis , tunisia . take the date record of this row . select the rows whose tournament record fuzzily matches to rabat , morocco . take the date record of this row . the second record is 7 days larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'tournament_8': 8, 'tunis , tunisia_9': 9, 'date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'tournament_12': 12, 'rabat , morocco_13': 13, 'date_14': 14, '-7 days_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'tournament_8': 'tournament', 'tunis , tunisia_9': 'tunis , tunisia', 'date_10': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'tournament_12': 'tournament', 'rabat , morocco_13': 'rabat , morocco', 'date_14': 'date', '-7 days_15': '-7 days'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'tournament_8': [0], 'tunis , tunisia_9': [0], 'date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'tournament_12': [1], 'rabat , morocco_13': [1], 'date_14': [3], '-7 days_15': [5]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', '15 july 2007', 'bogotá , colombia', 'clay', 'carlos salamanca', '6 - 4 , 3 - 6 , 2 - 6'], ['runner - up', '22 july 2007', 'cuenca , ecuador', 'clay', 'leonardo mayer', '3 - 6 , 2 - 6'], ['winner', '2 march 2008', 'santiago , chile', 'clay', 'eduardo schwank', '6 - 4 , 7 - 6 ( 7 - 3 )'], ['winner', '14 april 2008', 'florianapolis , brazil', 'clay', 'franco ferreiro', '4 - 6 , 6 - 4 , 6 - 2'], ['winner', '4 may 2008', 'tunis , tunisia', 'clay', 'dušan vemić', '6 - 2 , 6 - 4'], ['winner', '11 may 2008', 'rabat , morocco', 'clay', 'martín vassallo argüello', '6 - 2 , 6 - 2'], ['winner', '19 july 2009', 'rimini , italy', 'clay', 'juan pablo brzezicki', '3 - 6 , 6 - 3 , 6 - 1'], ['winner', '1 november 2009', 'são paulo , brazil', 'clay', 'nicolás lapentti', '6 - 4 , 6 - 4'], ['runner - up', '30 october 2010', 'são paulo , brazil', 'clay', 'marcos daniel', '1 - 6 , 6 - 3 , 3 - 6'], ['winner', '7 july 2012', 'braunschweig , germany', 'clay', 'tobias kamke', '7 - 6 ( 7 - 4 ) , 6 - 3'], ['winner', '3 november 2013', 'montevideo , uruguay', 'clay', 'diego sebastián schwartzman', '6 - 4 , 6 - 4']] |
89th united states congress | https://en.wikipedia.org/wiki/89th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1847180-3.html.csv | majority | most of the people to fill the vacant positions were democrats . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '( d )', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'successor', '( d )'], 'result': True, 'ind': 0, 'tointer': 'for the successor records of all rows , most of them fuzzily match to ( d ) .', 'tostr': 'most_eq { all_rows ; successor ; ( d ) } = true'} | most_eq { all_rows ; successor ; ( d ) } = true | for the successor records of all rows , most of them fuzzily match to ( d ) . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'successor_3': 3, '(d)_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'successor_3': 'successor', '(d)_4': '( d )'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'successor_3': [0], '(d)_4': [0]} | ['state ( class )', 'vacator', 'reason for change', 'successor', 'date of successors formal installation'] | [['south carolina ( 3 )', 'olin d johnston ( d )', 'died april 18 , 1965', 'donald s russell ( d )', 'april 22 , 1965'], ['south carolina ( 3 )', 'donald s russell ( d )', 'successor elected november 8 , 1965', 'ernest hollings ( d )', 'november 9 , 1965'], ['virginia ( 1 )', 'harry f byrd ( d )', 'resigned november 10 , 1965', 'harry f byrd , jr ( d )', 'november 12 , 1965'], ['michigan ( 2 )', 'patrick v mcnamara ( d )', 'died april 30 , 1966', 'robert p griffin ( r )', 'may 11 , 1966'], ['virginia ( 2 )', 'a willis robertson ( d )', 'resigned december 30 , 1966', 'william b spong , jr ( d )', 'december 31 , 1966']] |
2008 - 09 denver nuggets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Denver_Nuggets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17355408-4.html.csv | superlative | in the 2008 - 09 denver nuggets season , when the game was at the pepsi center , the highest attendance was on november 1 . | {'scope': 'subset', 'col_superlative': '8', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': {'col': '8', 'criterion': 'fuzzily_match', 'value': 'pepsi center'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'pepsi center'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location attendance ; pepsi center }', 'tointer': 'select the rows whose location attendance record fuzzily matches to pepsi center .'}, 'location attendance'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance }'}, 'date'], 'result': 'november 1', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance } ; date }'}, 'november 1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance } ; date } ; november 1 } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to pepsi center . select the row whose location attendance record of these rows is maximum . the date record of this row is november 1 .'} | eq { hop { argmax { filter_eq { all_rows ; location attendance ; pepsi center } ; location attendance } ; date } ; november 1 } = true | select the rows whose location attendance record fuzzily matches to pepsi center . select the row whose location attendance record of these rows is maximum . the date record of this row is november 1 . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location attendance_6': 6, 'pepsi center_7': 7, 'location attendance_8': 8, 'date_9': 9, 'november 1_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location attendance_6': 'location attendance', 'pepsi center_7': 'pepsi center', 'location attendance_8': 'location attendance', 'date_9': 'date', 'november 1_10': 'november 1'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location attendance_6': [0], 'pepsi center_7': [0], 'location attendance_8': [1], 'date_9': [2], 'november 1_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['3', 'november 1', 'la lakers', 'l 97 - 104 ( ot )', 'anthony carter ( 20 )', 'chris andersen ( 7 )', 'allen iverson ( 7 )', 'pepsi center 19651', '1 - 2'], ['4', 'november 5', 'golden state', 'l 101 - 111 ( ot )', 'carmelo anthony ( 28 )', 'nenê ( 15 )', 'anthony carter ( 11 )', 'oracle arena 18194', '1 - 3'], ['5', 'november 7', 'dallas', 'w 108 - 105 ( ot )', 'carmelo anthony ( 28 )', 'carmelo anthony ( 8 )', 'anthony carter ( 7 )', 'pepsi center 19175', '2 - 3'], ['6', 'november 9', 'memphis', 'w 100 - 90 ( ot )', 'carmelo anthony ( 24 )', 'nenê ( 12 )', 'chauncey billups ( 10 )', 'pepsi center 14359', '3 - 3'], ['7', 'november 11', 'charlotte', 'w 88 - 80 ( ot )', 'carmelo anthony ( 25 )', 'nenê , linas kleiza ( 8 )', 'anthony carter ( 6 )', 'time warner cable arena 10753', '4 - 3'], ['8', 'november 13', 'cleveland', 'l 99 - 110 ( ot )', 'chauncey billups ( 26 )', 'kenyon martin ( 10 )', 'chauncey billups ( 6 )', 'quicken loans arena 20562', '4 - 4'], ['9', 'november 14', 'boston', 'w 94 - 85 ( ot )', 'chauncey billups , carmelo anthony ( 18 )', 'carmelo anthony ( 13 )', 'chauncey billups ( 7 )', 'td banknorth garden 18624', '5 - 4'], ['10', 'november 16', 'minnesota', 'w 90 - 84 ( ot )', 'chauncey billups ( 26 )', 'carmelo anthony ( 12 )', 'chauncey billups ( 5 )', 'pepsi center 16721', '6 - 4'], ['11', 'november 18', 'milwaukee', 'w 114 - 105 ( ot )', 'linas kleiza ( 25 )', 'nenê ( 6 )', 'chauncey billups ( 5 )', 'pepsi center 14413', '7 - 4'], ['12', 'november 19', 'san antonio', 'w 91 - 81 ( ot )', 'chauncey billups ( 22 )', 'carmelo anthony , nenê ( 9 )', 'carmelo anthony ( 7 )', 'at & t center 16559', '8 - 4'], ['13', 'november 21', 'la lakers', 'l 90 - 104 ( ot )', 'j r smith , nenê ( 18 )', 'carmelo anthony ( 10 )', 'chauncey billups ( 9 )', 'staples center 18997', '8 - 5'], ['14', 'november 23', 'chicago', 'w 114 - 101 ( ot )', 'kenyon martin ( 26 )', 'carmelo anthony ( 13 )', 'chauncey billups , carmelo anthony ( 8 )', 'pepsi center 16202', '9 - 5'], ['15', 'november 26', 'la clippers', 'w 106 - 105 ( ot )', 'carmelo anthony ( 30 )', 'carmelo anthony ( 11 )', 'chauncey billups ( 11 )', 'staples center 14934', '10 - 5'], ['16', 'november 27', 'new orleans', 'l 101 - 105 ( ot )', 'j r smith ( 32 )', 'chris andersen ( 8 )', 'anthony carter ( 8 )', 'pepsi center 15563', '10 - 6'], ['17', 'november 29', 'minnesota', 'w 106 - 97 ( ot )', 'chauncey billups ( 27 )', 'carmelo anthony ( 10 )', 'chucky atkins ( 5 )', 'target center 14197', '11 - 6']] |
middle atlantic conferences | https://en.wikipedia.org/wiki/Middle_Atlantic_Conferences | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-261906-2.html.csv | superlative | the school in the middle atlantic conferences with the most students is eastern university . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'institution'], 'result': 'eastern university', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; institution }'}, 'eastern university'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; institution } ; eastern university } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the institution record of this row is eastern university .'} | eq { hop { argmax { all_rows ; enrollment } ; institution } ; eastern university } = true | select the row whose enrollment record of all rows is maximum . the institution record of this row is eastern university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'institution_6': 6, 'eastern university_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'institution_6': 'institution', 'eastern university_7': 'eastern university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'institution_6': [1], 'eastern university_7': [2]} | ['institution', 'location', 'nickname', 'founded', 'type', 'enrollment', 'joined mac'] | [['delaware valley college', 'doylestown , pennsylvania', 'aggies', '1917', 'private / non - sectarian', '2241', '1965'], ['desales university', 'center valley , pennsylvania', 'bulldogs', '1965', 'private / catholic', '3199', '1997'], ['eastern university', 'st davids , pennsylvania', 'eagles', '1952', 'private / baptist', '4235', '2008'], ['fairleigh dickinson university - florham', 'madison , new jersey', 'devils', '1942', 'private / non - sectarian', '3288', '1977'], ["king 's college", 'wilkes - barre , pennsylvania', 'monarchs', '1946', 'private / catholic', '2725', '1977'], ['manhattanville college', 'purchase , new york', 'valiants', '1841', 'private / non - sectarian', '2695', '2007'], ['misericordia university', 'dallas , pennsylvania', 'cougars', '1924', 'private / catholic', '2830', '2008']] |
ireland in the eurovision song contest 1998 | https://en.wikipedia.org/wiki/Ireland_in_the_Eurovision_Song_Contest_1998 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15696018-1.html.csv | unique | the song cold shoulder was the only song to have less than 40 points . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '2', 'criterion': 'less_than', 'value': '40', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is less than 40 .', 'tostr': 'filter_less { all_rows ; points ; 40 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; points ; 40 } }', 'tointer': 'select the rows whose points record is less than 40 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'points', '40'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is less than 40 .', 'tostr': 'filter_less { all_rows ; points ; 40 }'}, 'song'], 'result': 'cold shoulder', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; points ; 40 } ; song }'}, 'cold shoulder'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; points ; 40 } ; song } ; cold shoulder }', 'tointer': 'the song record of this unqiue row is cold shoulder .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; points ; 40 } } ; eq { hop { filter_less { all_rows ; points ; 40 } ; song } ; cold shoulder } } = true', 'tointer': 'select the rows whose points record is less than 40 . there is only one such row in the table . the song record of this unqiue row is cold shoulder .'} | and { only { filter_less { all_rows ; points ; 40 } } ; eq { hop { filter_less { all_rows ; points ; 40 } ; song } ; cold shoulder } } = true | select the rows whose points record is less than 40 . there is only one such row in the table . the song record of this unqiue row is cold shoulder . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'points_7': 7, '40_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'song_9': 9, 'cold shoulder_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'points_7': 'points', '40_8': '40', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'song_9': 'song', 'cold shoulder_10': 'cold shoulder'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '40_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'song_9': [2], 'cold shoulder_10': [3]} | ['draw', 'song', 'performer', 'points', 'rank'] | [['1', 'is always over now', 'dawn martin', '95', '1st'], ['2', 'shine on', 'partners in crime', '63', '5th'], ['3', 'cold shoulder', 'ray doherty', '39', '8th'], ['4', 'seol ( sail )', 'the vard sisters', '92', '2nd'], ['5', 'save this dance for me', 'family', '57', '6th'], ['6', 'ina measc ( among them )', 'sean monagahan', '43', '7th'], ['7', 'make the change', 'the carter twins', '77', '4th'], ['8', 'overload', 'jo collins', '84', '3rd']] |
statues of the liberators | https://en.wikipedia.org/wiki/Statues_of_the_Liberators | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13846706-1.html.csv | aggregation | the average year in which the virginia avenue statues of the liberators were erected was around 1965 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1965', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'year erected'], 'result': '1965', 'ind': 0, 'tostr': 'avg { all_rows ; year erected }'}, '1965'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; year erected } ; 1965 } = true', 'tointer': 'the average of the year erected record of all rows is 1965 .'} | round_eq { avg { all_rows ; year erected } ; 1965 } = true | the average of the year erected record of all rows is 1965 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'year erected_4': 4, '1965_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'year erected_4': 'year erected', '1965_5': '1965'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'year erected_4': [0], '1965_5': [1]} | ['statue', 'liberator', 'country', 'year erected', 'artist'] | [['general josé gervasio artigas', 'josé gervasio artigas', 'uruguay', '1950', 'juan manuel blanes ( 1830 - 1901 )'], ['equestrian of simón bolívar', 'simón bolívar', 'venezuela', '1958', 'felix de weldon ( 1907 - 2003 )'], ['general jose de san martin memorial', 'josé de san martín', 'argentina', '1970s', 'augustin - alexandre dumont ( 1801 - 1884 )'], ['bernardo de gálvez', 'bernardo de gálvez', 'spain', '1976', 'juan de ávalos ( 1911 - 2006 )'], ['benito juarez', 'benito juárez', 'mexico', '1969', 'enrique alciati']] |
list of game of the year awards | https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-48.html.csv | ordinal | the first game of the year award went to the game space invaders . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '2,3,4,5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 1 }'}, 'arcade'], 'result': 'space invaders', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ; 1 } ; arcade }'}, 'space invaders'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 1 } ; arcade } ; space invaders }', 'tointer': 'select the row whose year record of all rows is 1st minimum . the arcade record of this row is space invaders .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 1 }'}, 'standalone'], 'result': 'space invaders', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; year ; 1 } ; standalone }'}, 'space invaders'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 1 } ; standalone } ; space invaders }', 'tointer': 'the standalone record of this row is space invaders .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 1 }'}, 'console'], 'result': 'space invaders', 'ind': 5, 'tostr': 'hop { nth_argmin { all_rows ; year ; 1 } ; console }'}, 'space invaders'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 1 } ; console } ; space invaders }', 'tointer': 'the console record of this row is space invaders .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'year', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ; 1 }'}, 'computer'], 'result': 'space invaders', 'ind': 7, 'tostr': 'hop { nth_argmin { all_rows ; year ; 1 } ; computer }'}, 'space invaders'], 'result': True, 'ind': 8, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ; 1 } ; computer } ; space invaders }', 'tointer': 'the computer record of this row is space invaders .'}], 'result': True, 'ind': 9, 'tostr': 'and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; console } ; space invaders } ; eq { hop { nth_argmin { all_rows ; year ; 1 } ; computer } ; space invaders } }', 'tointer': 'the console record of this row is space invaders . the computer record of this row is space invaders .'}], 'result': True, 'ind': 10, 'tostr': 'and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; standalone } ; space invaders } ; and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; console } ; space invaders } ; eq { hop { nth_argmin { all_rows ; year ; 1 } ; computer } ; space invaders } } }', 'tointer': 'the standalone record of this row is space invaders . the console record of this row is space invaders . the computer record of this row is space invaders .'}], 'result': True, 'ind': 11, 'tostr': 'and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; arcade } ; space invaders } ; and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; standalone } ; space invaders } ; and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; console } ; space invaders } ; eq { hop { nth_argmin { all_rows ; year ; 1 } ; computer } ; space invaders } } } } = true', 'tointer': 'select the row whose year record of all rows is 1st minimum . the arcade record of this row is space invaders . the standalone record of this row is space invaders . the console record of this row is space invaders . the computer record of this row is space invaders .'} | and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; arcade } ; space invaders } ; and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; standalone } ; space invaders } ; and { eq { hop { nth_argmin { all_rows ; year ; 1 } ; console } ; space invaders } ; eq { hop { nth_argmin { all_rows ; year ; 1 } ; computer } ; space invaders } } } } = true | select the row whose year record of all rows is 1st minimum . the arcade record of this row is space invaders . the standalone record of this row is space invaders . the console record of this row is space invaders . the computer record of this row is space invaders . | 15 | 12 | {'and_11': 11, 'result_12': 12, 'str_eq_2': 2, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_13': 13, 'year_14': 14, '1_15': 15, 'arcade_16': 16, 'space invaders_17': 17, 'and_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'standalone_18': 18, 'space invaders_19': 19, 'and_9': 9, 'str_eq_6': 6, 'str_hop_5': 5, 'console_20': 20, 'space invaders_21': 21, 'str_eq_8': 8, 'str_hop_7': 7, 'computer_22': 22, 'space invaders_23': 23} | {'and_11': 'and', 'result_12': 'true', 'str_eq_2': 'str_eq', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_13': 'all_rows', 'year_14': 'year', '1_15': '1', 'arcade_16': 'arcade', 'space invaders_17': 'space invaders', 'and_10': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'standalone_18': 'standalone', 'space invaders_19': 'space invaders', 'and_9': 'and', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'console_20': 'console', 'space invaders_21': 'space invaders', 'str_eq_8': 'str_eq', 'str_hop_7': 'str_hop', 'computer_22': 'computer', 'space invaders_23': 'space invaders'} | {'and_11': [12], 'result_12': [], 'str_eq_2': [11], 'str_hop_1': [2], 'nth_argmin_0': [1, 3, 5, 7], 'all_rows_13': [0], 'year_14': [0], '1_15': [0], 'arcade_16': [1], 'space invaders_17': [2], 'and_10': [11], 'str_eq_4': [10], 'str_hop_3': [4], 'standalone_18': [3], 'space invaders_19': [4], 'and_9': [10], 'str_eq_6': [9], 'str_hop_5': [6], 'console_20': [5], 'space invaders_21': [6], 'str_eq_8': [9], 'str_hop_7': [8], 'computer_22': [7], 'space invaders_23': [8]} | ['year', 'arcade', 'standalone', 'console', 'computer'] | [['1979 ( 1st )', 'space invaders', 'space invaders', 'space invaders', 'space invaders'], ['1980 ( 2nd )', 'asteroids', 'asteroids', 'superman', 'superman'], ['1981 ( 3rd )', 'pac - man', 'pac - man', 'asteroids', 'star raiders'], ['1982 ( 4th )', 'tron', 'galaxian', 'demon attack', "david 's midnight magic"], ['1983 ( 5th )', 'pole position', 'qbert', 'under 16k : ms pac - man over 16k : lady bug', 'lode runner'], ['1984 ( 6th )', 'star wars', 'zaxxon', 'space shuttle', 'ultima iii : exodus'], ['1992 ( 7th )', 'street fighter ii', 'street fighter ii', "nhlpa hockey '93 sonic the hedgehog 2", "nhlpa hockey '93 sonic the hedgehog 2"]] |
steam locomotives of ireland | https://en.wikipedia.org/wiki/Steam_locomotives_of_Ireland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1290024-2.html.csv | ordinal | the class c had the fourth highest quantity of locomotives made regarding the steam locomotives of ireland . | {'row': '3', 'col': '4', 'order': '4', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'quantity made', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; quantity made ; 4 }'}, 'class'], 'result': 'c', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; quantity made ; 4 } ; class }'}, 'c'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; quantity made ; 4 } ; class } ; c } = true', 'tointer': 'select the row whose quantity made record of all rows is 4th maximum . the class record of this row is c .'} | eq { hop { nth_argmax { all_rows ; quantity made ; 4 } ; class } ; c } = true | select the row whose quantity made record of all rows is 4th maximum . the class record of this row is c . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'quantity made_5': 5, '4_6': 6, 'class_7': 7, 'c_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', 'quantity made_5': 'quantity made', '4_6': '4', 'class_7': 'class', 'c_8': 'c'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'quantity made_5': [0], '4_6': [0], 'class_7': [1], 'c_8': [2]} | ['class', 'type', 'fleet numbers', 'quantity made', 'manufacturer', 'date made', 'date withdrawn'] | [['a', '4 - 4 - 0', '3 - 5 , 9 , 17 , 20 , 34 , 63 - 68', '13', 'york road works ( 7 ) derby works ( 6 )', '1901 - 1908', '1929 - 1936'], ['b', '4 - 4 - 0', '24 , 59 - 62', '5', 'beyer , peacock & co', '1897 - 1898', '1924 - 1932'], ['c', '2 - 4 - 0', '21 , 33 , 50 - 52 , 56 - 57', '7', 'beyer , peacock & co', '1890 - 1895', '1926 - 1942'], ['d', '2 - 4 - 0', '50 , 55', '2', 'beyer , peacock & co', '1895', '1944 - 1946'], ['e', '0 - 6 - 0', '53 - 54', '2', 'beyer , peacock & co', '1892', '1934 - 1944'], ['f', '2 - 4 - 0', '45 - 46 , 23', '3', 'beyer , peacock & co', '1880 - 1885', '1938 - 1942'], ['g', '2 - 4 - 0', '6 , 8 , 10 - 11 , 22 , 27 , 29 , 40 - 41', '9', 'sharp , stewart & co ( 7 ) beyer , peacock & co ( 2 )', '1872 - 1878', '1925 - 1933'], ['h', '2 - 4 - 0', '12 - 17', '6', 'sharp , stewart & co', '1856', '1908 - 1924'], ['i', '2 - 4 - 0', '40 - 41', '2', 'beyer , peacock & co', '1868', '1924'], ['j', '2 - 4 - 0t', '25 , 47 - 49', '4', 'beyer , peacock & co', '1883', '1932 - 1934'], ['k', '0 - 6 - 0', '7 , 28 , 30 - 32 , 38 - 39 , 43 - 44', '9', 'sharp , stewart & co ( 7 ) beyer , peacock & co ( 2 )', '1867 - 1880', '1925 - 1947'], ['l', '0 - 6 - 0', '18 - 19 , 35', '3', 'sharp , stewart & co', '1857 - 1861', '1925 - 1933'], ['l1', '0 - 6 - 0', '36 - 37', '2', 'beyer , peacock & co', '1863', '1928 - 1932'], ['m', '0 - 4 - 2', '26', '1', 'york road works', '1873', '1925'], ['n', '0 - 4 - 0st', '42', '1', 'sharp , stewart & co', '1875', '1925'], ['o', '0 - 4 - 2st', '60 - 62', '3', 'black , hawthorn & co', '1874 - 1875', '1911 - 1923'], ['p', '2 - 4 - 0t', '63 - 64', '2', 'beyer , peacock & co', '1877 - 1878', '1920 - 1928'], ['q', '0 - 6 - 0t', '65 - 67', '3', 'beyer , peacock & co', '1977 - 1882', '1931 - 1933'], ['r', '2 - 6 - 0st', '68', '1', 'beyer , peacock & co', '1880', '1934'], ['s', '2 - 4 - 2t', '69 - 70', '2', 'beyer , peacock & co', '1882', '1946 - 1954']] |
fai world grand prix 2008 | https://en.wikipedia.org/wiki/FAI_World_Grand_Prix_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277703-1.html.csv | count | there were two pilots that were from poland . | {'scope': 'all', 'criterion': 'equal', 'value': 'poland', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'poland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to poland .', 'tostr': 'filter_eq { all_rows ; country ; poland }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; country ; poland } }', 'tointer': 'select the rows whose country record fuzzily matches to poland . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; country ; poland } } ; 2 } = true', 'tointer': 'select the rows whose country record fuzzily matches to poland . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; country ; poland } } ; 2 } = true | select the rows whose country record fuzzily matches to poland . 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, 'country_5': 5, 'poland_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', 'country_5': 'country', 'poland_6': 'poland', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'poland_6': [0], '2_7': [2]} | ['position', 'pilot', 'country', 'glider', 'points'] | [['1', 'sebastian kawa', 'poland', 'diana sailplanes - diana 2', '69'], ['2', 'carlos rocca vidal', 'chile', 'schempp - hirth flugzeugbau gmbh - ventus 2b', '55'], ['3', 'mario kiessling', 'germany', 'schempp - hirth flugzeugbau gmbh - ventus 2ax', '47'], ['4', 'uli schwenk', 'germany', 'schempp - hirth flugzeugbau gmbh - ventus 2ax', '40'], ['5', 'thomas gostner', 'italy', 'diana sailplanes - diana 2', '43'], ['6', 'tilo holighaus', 'germany', 'schempp - hirth flugzeugbau gmbh - ventus 2ax', '24'], ['7', 'wolfgang janowitsch', 'austria', 'schempp - hirth flugzeugbau gmbh - ventus 2cxa', '15'], ['8', 'rene vidal', 'chile', 'schempp - hirth flugzeugbau gmbh - ventus 2c', '14'], ['8', 'stanislaw wujczak', 'poland', 'alexander schleicher gmbh & co - asg 29', '14'], ['10', 'eduard supersperger', 'austria', 'schempp - hirth flugzeugbau gmbh - ventus 2b', '12'], ['11', 'heimo demmerer', 'austria', 'schempp - hirth flugzeugbau gmbh - ventus 2b', '11'], ['12', 'patrick puskeiler', 'germany', 'schempp - hirth flugzeugbau gmbh - discus 2ax', '8'], ['13', 'petr krejcirik', 'czech republic', 'schempp - hirth flugzeugbau gmbh - ventus 2ax', '4'], ['13', 'graham parker', 'australia', 'alexander schleicher gmbh & co - asg 29', '4'], ['15', 'olli teronen', 'finland', 'alexander schleicher gmbh & co - asg 29', '2']] |
the chicago code | https://en.wikipedia.org/wiki/The_Chicago_Code | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27401228-1.html.csv | unique | the pilot episode was the only time more than 9 million viewers watched the show . | {'scope': 'all', 'row': '1', 'col': '7', 'col_other': '2', 'criterion': 'greater_than', 'value': '9.0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( million )', '9.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is greater than 9.0 .', 'tostr': 'filter_greater { all_rows ; us viewers ( million ) ; 9.0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } }', 'tointer': 'select the rows whose us viewers ( million ) record is greater than 9.0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( million )', '9.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is greater than 9.0 .', 'tostr': 'filter_greater { all_rows ; us viewers ( million ) ; 9.0 }'}, 'title'], 'result': 'pilot', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } ; title }'}, 'pilot'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } ; title } ; pilot }', 'tointer': 'the title record of this unqiue row is pilot .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } ; title } ; pilot } } = true', 'tointer': 'select the rows whose us viewers ( million ) record is greater than 9.0 . there is only one such row in the table . the title record of this unqiue row is pilot .'} | and { only { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 9.0 } ; title } ; pilot } } = true | select the rows whose us viewers ( million ) record is greater than 9.0 . there is only one such row in the table . the title record of this unqiue row is pilot . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'us viewers (million)_7': 7, '9.0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'pilot_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'us viewers (million)_7': 'us viewers ( million )', '9.0_8': '9.0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'pilot_10': 'pilot'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'us viewers (million)_7': [0], '9.0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'pilot_10': [3]} | ['no', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( million )'] | [['1', 'pilot', 'charles mcdougall', 'shawn ryan', 'february 7 , 2011', '1ata79', '9.43'], ['2', 'hog butcher', 'clark johnson', 'patrick massett & john zinman', 'february 14 , 2011', '1ata01', '7.35'], ['3', 'gillis , chase & babyface', 'guy ferland', 'davey holmes', 'february 21 , 2011', '1ata09', '7.87'], ['4', 'cabrini - green', 'jean de segonzac', 'tim minear & jon worley', 'february 28 , 2011', '1ata10', '8.04'], ['5', "o'leary 's cow", 'clark johnson', 'kevin townsley', 'march 7 , 2011', '1ata03', '7.46'], ['6', 'the gold coin kid', 'lesli linka glatter', 'heather mitchell', 'march 14 , 2011', '1ata02', '7.30'], ['7', 'black hand and the shotgun man', 'billy gierhart', 'davey holmes', 'march 21 , 2011', '1ata04', '6.16'], ['8', 'wild onions', 'adam arkin', 'virgil williams', 'april 11 , 2011', '1ata05', '5.94'], ['9', "st valentine 's day massacre", 'michael offer', 'christal henry', 'april 18 , 2011', '1ata06', '6.38'], ['10', 'bathhouse & hinky dink', "terrence o'hara", 'patrick massett & john zinman', 'may 2 , 2011', '1ata07', '5.60'], ['11', 'black sox', 'michael offer', 'heather mitchell & kevin townsley', 'may 9 , 2011', '1ata08', '5.67'], ['12', 'greylord & gambat', 'paris barclay', 'virgil williams', 'may 16 , 2011', '1ata11', '5.86']] |
partnership ( cricket ) | https://en.wikipedia.org/wiki/Partnership_%28cricket%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1670921-3.html.csv | aggregation | during the parntnership ( cricket ) a grand total of 4832 runs were scored . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '4832', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'runs'], 'result': '4832', 'ind': 0, 'tostr': 'sum { all_rows ; runs }'}, '4832'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; runs } ; 4832 } = true', 'tointer': 'the sum of the runs record of all rows is 4832 .'} | round_eq { sum { all_rows ; runs } ; 4832 } = true | the sum of the runs record of all rows is 4832 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'runs_4': 4, '4832_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'runs_4': 'runs', '4832_5': '4832'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'runs_4': [0], '4832_5': [1]} | ['wicket', 'runs', 'battling partners', 'battling team', 'fielding team', 'venue', 'season'] | [['1st', '561', 'waheed mirza and mansoor akhtar', 'karachi whites', 'quetta', 'karachi', '1976 / 77'], ['2nd', '580', 'rafatullah mohmand and aamer sajjad', 'wapda', 'ssgc', 'sheikhupura', '2009 / 10'], ['3rd', '624', 'mahela jayawardene and kumar sangakkara', 'sri lanka', 'south africa', 'colombo', '2006'], ['4th', '577', 'vijay hazare and gul mohammad', 'baroda', 'holkar', 'baroda', '1946 / 47'], ['5th', '520', 'cheteshwar pujara and ravi jadeja', 'saurashtra', 'orissa', 'rajkot', '2008 / 09'], ['6th', '487', 'george headley and clarence passailaigue', 'jamaica', "lord tennyson 's xi", 'kingston', '1931 / 32'], ['7th', '460', 'bhupinder singh and pankaj dharmani', 'punjab', 'delhi', 'delhi', '1994 / 95'], ['8th', '433', 'arthur sims and victor trumper', 'australia', 'canterbury', 'christchurch', '1913 / 14'], ['9th', '283', 'john chapman and arnold warren', 'derbyshire', 'warwickshire', 'blackwell', '1910'], ['10th', '307', 'alan kippax and hal hooker', 'new south wales', 'victoria', 'mcg', '1928 / 29']] |
united states house of representatives elections , 1822 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1822 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668298-19.html.csv | aggregation | all districts in the 1822 house elections have incumbents with an average first elected year of 1819 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1819', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'first elected'], 'result': '1819', 'ind': 0, 'tostr': 'avg { all_rows ; first elected }'}, '1819'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; first elected } ; 1819 } = true', 'tointer': 'the average of the first elected record of all rows is 1819 .'} | round_eq { avg { all_rows ; first elected } ; 1819 } = true | the average of the first elected record of all rows is 1819 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'first elected_4': 4, '1819_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'first elected_4': 'first elected', '1819_5': '1819'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'first elected_4': [0], '1819_5': [1]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['north carolina 2', 'hutchins g burton', 'democratic - republican', '1819', 're - elected', 'hutchins g burton ( c - dr ) jesse a dawson'], ['north carolina 4', 'william s blackledge', 'democratic - republican', '1821', 'retired democratic - republican hold', 'richard dobbs spaight , jr ( c - dr )'], ['north carolina 5', 'charles hooks', 'democratic - republican', '1816 ( special ) 1819', 're - elected', 'charles hooks ( c - dr ) john d jones'], ['north carolina 6', 'weldon n edwards', 'democratic - republican', '1816 ( special )', 're - elected', 'weldon n edwards ( c - dr ) 100 %'], ['north carolina 7', 'archibald mcneill', 'federalist', '1821', 'retired federalist hold', 'john culpepper ( a - f ) 50.9 % alexander mcneill 49.1 %'], ['north carolina 9', 'romulus m saunders', 'democratic - republican', '1821', 're - elected', 'romulus m saunders ( c - dr ) 100 %'], ['north carolina 10', 'john long', 'democratic - republican', '1821', 're - elected', 'john long ( c - dr ) 66.9 % john macclelland 33.1 %']] |
2008 - 09 segunda división b | https://en.wikipedia.org/wiki/2008%E2%80%9309_Segunda_Divisi%C3%B3n_B | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18160020-4.html.csv | ordinal | in 2008-09 segunda division b , the 2nd highest number of matches was for joel rodriguez . | {'row': '2', 'col': '3', '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', 'matches', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; matches ; 2 }'}, 'goalkeeper'], 'result': 'joel rodríguez', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; matches ; 2 } ; goalkeeper }'}, 'joel rodríguez'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; matches ; 2 } ; goalkeeper } ; joel rodríguez } = true', 'tointer': 'select the row whose matches record of all rows is 2nd maximum . the goalkeeper record of this row is joel rodríguez .'} | eq { hop { nth_argmax { all_rows ; matches ; 2 } ; goalkeeper } ; joel rodríguez } = true | select the row whose matches record of all rows is 2nd maximum . the goalkeeper record of this row is joel rodríguez . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'matches_5': 5, '2_6': 6, 'goalkeeper_7': 7, 'joel rodríguez_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', 'matches_5': 'matches', '2_6': '2', 'goalkeeper_7': 'goalkeeper', 'joel rodríguez_8': 'joel rodríguez'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'matches_5': [0], '2_6': [0], 'goalkeeper_7': [1], 'joel rodríguez_8': [2]} | ['goalkeeper', 'goals', 'matches', 'average', 'team'] | [['josé bermúdez', '18', '33', '0.55', 'cultural leonesa'], ['joel rodríguez', '24', '36', '0.67', 'celta b'], ['igor etxebarrieta', '21', '30', '0.7', 'lemona'], ['daniel giménez', '34', '38', '0.89', 'zamora'], ['miguel escalona', '34', '34', '1', 'guijuelo']] |
economy of the united states by sector | https://en.wikipedia.org/wiki/Economy_of_the_United_States_by_sector | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23802822-1.html.csv | aggregation | the total annual payroll ( 1000 ) for the given sectors of the united states economy is 3,521,267,581 . | {'scope': 'all', 'col': '4', 'type': 'sum', 'result': '3,521,267,581', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'annual payroll ( 1000 )'], 'result': '3,521,267,581', 'ind': 0, 'tostr': 'sum { all_rows ; annual payroll ( 1000 ) }'}, '3,521,267,581'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; annual payroll ( 1000 ) } ; 3,521,267,581 } = true', 'tointer': 'the sum of the annual payroll ( 1000 ) record of all rows is 3,521,267,581 .'} | round_eq { sum { all_rows ; annual payroll ( 1000 ) } ; 3,521,267,581 } = true | the sum of the annual payroll ( 1000 ) record of all rows is 3,521,267,581 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'annual payroll (1000)_4': 4, '3,521,267,581_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'annual payroll (1000)_4': 'annual payroll ( 1000 )', '3,521,267,581_5': '3,521,267,581'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'annual payroll (1000)_4': [0], '3,521,267,581_5': [1]} | ['sector', 'establishments', 'sales , receipts , or shipments ( 1000 )', 'annual payroll ( 1000 )', 'paid employees'] | [['mining', '24087', '182911093', '21173895', '477840'], ['utilities', '17103', '398907044', '42417830', '663044'], ['construction', '710307', '1196555587', '254292144', '7193069'], ['manufacturing', '350828', '3916136712', '576170541', '14699536'], ['wholesale trade', '435521', '4634755112', '259653080', '5878405'], ['retail trade', '1114637', '3056421997', '302113581', '14647675'], ['transportation & warehousing', '199618', '382152040', '115988733', '3650859'], ['information', '137678', '891845956', '194670163', '3736061'], ['finance & insurance', '440268', '2803854868', '377790172', '6578817'], ['real estate & rental & leasing', '322815', '335587706', '60222584', '1948657'], ['professional , scientific , & technical services', '771305', '886801038', '376090052', '7243505'], ['management of companies & enterprises', '49308', '107064264', '178996060', '2605292'], ['educational services', '49319', '30690707', '10164378', '430164'], ['health care & social assistance', '704526', '1207299734', '495845829', '15052255'], ['arts , entertainment , & recreation', '110313', '141904109', '45169117', '1848674'], ['accommodation & food services', '565590', '449498718', '127554483', '10120951'], ['other services ( except public administration )', '537576', '307049461', '82954939', '3475310']] |
1991 foster 's cup | https://en.wikipedia.org/wiki/1991_Foster%27s_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16387700-1.html.csv | comparative | at the 1991 foster 's cup , the match at geelong had a bigger crowd than the match at melbourne . | {'row_1': '4', 'row_2': '6', 'col': '6', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'geelong'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to geelong .', 'tostr': 'filter_eq { all_rows ; home team ; geelong }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; home team ; geelong } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to geelong . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'melbourne'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team record fuzzily matches to melbourne .', 'tostr': 'filter_eq { all_rows ; home team ; melbourne }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; home team ; melbourne } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to melbourne . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; home team ; geelong } ; crowd } ; hop { filter_eq { all_rows ; home team ; melbourne } ; crowd } } = true', 'tointer': 'select the rows whose home team record fuzzily matches to geelong . take the crowd record of this row . select the rows whose home team record fuzzily matches to melbourne . take the crowd record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; home team ; geelong } ; crowd } ; hop { filter_eq { all_rows ; home team ; melbourne } ; crowd } } = true | select the rows whose home team record fuzzily matches to geelong . take the crowd record of this row . select the rows whose home team record fuzzily matches to melbourne . take the crowd record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'home team_7': 7, 'geelong_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'melbourne_12': 12, 'crowd_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'home team_7': 'home team', 'geelong_8': 'geelong', 'crowd_9': 'crowd', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'home team_11': 'home team', 'melbourne_12': 'melbourne', 'crowd_13': 'crowd'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'geelong_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'melbourne_12': [1], 'crowd_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'ground', 'crowd', 'date'] | [['carlton', '27.9 ( 171 )', 'fitzroy', '13.8 ( 86 )', 'north hobart oval', '10100', 'sunday 3 february'], ['footscray', '9.6 ( 60 )', 'hawthorn', '19.25 ( 139 )', 'waverley park', '13196', 'wednesday 6 february'], ['collingwood', '11.17 ( 83 )', 'brisbane', '20.20 ( 140 )', 'gabba', '12461', 'saturday 10 february'], ['geelong', '11.13 ( 79 )', 'adelaide', '23.18 ( 156 )', 'football park', '20069', 'wednesday 13 february'], ['st kilda', '12.10 ( 82 )', 'west coast', '9.11 ( 65 )', 'waverley park', '13625', 'saturday 16 february'], ['melbourne', '15.13 ( 103 )', 'richmond', '12.10 ( 82 )', 'waverley park', '14993', 'wednesday 20 february'], ['north melbourne', '19.20 ( 134 )', 'sydney', '13.17 ( 95 )', 'bruce stadium', '5120', 'sunday 24 february']] |
lost souls ( doves album ) | https://en.wikipedia.org/wiki/Lost_Souls_%28Doves_album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1523661-2.html.csv | unique | japan is the only country in which lost souls was released by the toshiba - emi label . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'toshiba - emi', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'toshiba - emi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to toshiba - emi .', 'tostr': 'filter_eq { all_rows ; label ; toshiba - emi }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; label ; toshiba - emi } }', 'tointer': 'select the rows whose label record fuzzily matches to toshiba - emi . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'label', 'toshiba - emi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose label record fuzzily matches to toshiba - emi .', 'tostr': 'filter_eq { all_rows ; label ; toshiba - emi }'}, 'country'], 'result': 'japan', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; label ; toshiba - emi } ; country }'}, 'japan'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; label ; toshiba - emi } ; country } ; japan }', 'tointer': 'the country record of this unqiue row is japan .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; label ; toshiba - emi } } ; eq { hop { filter_eq { all_rows ; label ; toshiba - emi } ; country } ; japan } } = true', 'tointer': 'select the rows whose label record fuzzily matches to toshiba - emi . there is only one such row in the table . the country record of this unqiue row is japan .'} | and { only { filter_eq { all_rows ; label ; toshiba - emi } } ; eq { hop { filter_eq { all_rows ; label ; toshiba - emi } ; country } ; japan } } = true | select the rows whose label record fuzzily matches to toshiba - emi . there is only one such row in the table . the country record of this unqiue row is japan . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'label_7': 7, 'toshiba - emi_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'japan_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'label_7': 'label', 'toshiba - emi_8': 'toshiba - emi', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'japan_10': 'japan'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'label_7': [0], 'toshiba - emi_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'japan_10': [3]} | ['country', 'date', 'label', 'format', 'catalogue'] | [['united kingdom', '3 april 2000', 'heavenly records', 'cd', 'hvnlp26cd'], ['united kingdom', '3 april 2000', 'heavenly records', 'double lp ( heavyweight vinyl , gatefold sleeve )', 'hvnlp26'], ['united states', '17 october 2000', 'astralwerks records', 'cd ( 3 bonus tracks )', 'asw 50248 ( 724385024825 )'], ['united states', '17 october 2000', 'astralwerks records', 'double lp ( numbered edition , gatefold sleeve )', 'asw 50248 ( 724385024818 )'], ['japan', '7 march 2001', 'toshiba - emi', 'cd ( 3 bonus tracks )', 'tocp - 65682']] |
2008 - 09 nbl season | https://en.wikipedia.org/wiki/2008%E2%80%9309_NBL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16653153-18.html.csv | ordinal | the sydney spirit were the home team that scored the third most points in the 2008 - 09 nbl season . | {'row': '8', 'col': '3', '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', 'score', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; score ; 3 }'}, 'home team'], 'result': 'sydney spirit', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; score ; 3 } ; home team }'}, 'sydney spirit'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; score ; 3 } ; home team } ; sydney spirit } = true', 'tointer': 'select the row whose score record of all rows is 3rd maximum . the home team record of this row is sydney spirit .'} | eq { hop { nth_argmax { all_rows ; score ; 3 } ; home team } ; sydney spirit } = true | select the row whose score record of all rows is 3rd maximum . the home team record of this row is sydney spirit . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, '3_6': 6, 'home team_7': 7, 'sydney spirit_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', 'score_5': 'score', '3_6': '3', 'home team_7': 'home team', 'sydney spirit_8': 'sydney spirit'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], '3_6': [0], 'home team_7': [1], 'sydney spirit_8': [2]} | ['date', 'home team', 'score', 'away team', 'venue', 'box score', 'report'] | [['26 november', 'south dragons', '102 - 64', 'cairns taipans', 'hisense arena', 'box score', '-'], ['26 november', 'townsville crocodiles', '113 - 105', 'melbourne tigers', 'townsville entertainment centre', 'box score', '-'], ['27 november', 'new zealand breakers', '108 - 94', 'perth wildcats', 'north shore events centre', 'box score', '-'], ['29 november', 'adelaide 36ers', '101 - 96', 'wollongong hawks', 'distinctive homes dome', 'box score', '-'], ['29 november', 'cairns taipans', '90 - 94', 'townsville crocodiles', 'cairns convention centre', 'box score', '-'], ['29 november', 'gold coast blaze', '88 - 110', 'new zealand breakers', 'gold coast convention centre', 'box score', '-'], ['29 november', 'perth wildcats', '95 - 108', 'melbourne tigers', 'marrara stadium', 'box score', '-'], ['29 november', 'sydney spirit', '103 - 94', 'south dragons', 'state sports centre', 'box score', '-']] |
2005 - 06 coventry city f.c. season | https://en.wikipedia.org/wiki/2005%E2%80%9306_Coventry_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18884038-6.html.csv | ordinal | michael doyle had the second highest total in the 2005-06 coventry city f.c. season . | {'row': '2', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total ; 2 }'}, 'name'], 'result': 'michael doyle', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total ; 2 } ; name }'}, 'michael doyle'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total ; 2 } ; name } ; michael doyle } = true', 'tointer': 'select the row whose total record of all rows is 2nd maximum . the name record of this row is michael doyle .'} | eq { hop { nth_argmax { all_rows ; total ; 2 } ; name } ; michael doyle } = true | select the row whose total record of all rows is 2nd maximum . the name record of this row is michael doyle . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, '2_6': 6, 'name_7': 7, 'michael doyle_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', '2_6': '2', 'name_7': 'name', 'michael doyle_8': 'michael doyle'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], '2_6': [0], 'name_7': [1], 'michael doyle_8': [2]} | ['name', 'championship', 'league cup', 'fa cup', 'total'] | [['gary mcsheffrey', '10', '1', '0', '11'], ['michael doyle', '9', '0', '0', '9'], ['richard duffy', '7', '0', '1', '8'], ['robert page', '8', '0', '0', '8'], ['dennis wise', '7', '0', '0', '7'], ['dele adebola', '4', '0', '1', '5'], ['don hutchison', '4', '0', '1', '5'], ['stern john', '4', '1', '0', '5'], ['marcus hall', '3', '1', '0', '4'], ['matt heath', '4', '0', '0', '4'], ['james scowcroft', '3', '0', '1', '4'], ['adrian williams', '4', '0', '0', '4'], ['stephen hughes', '2', '0', '1', '3'], ['richard shaw', '3', '0', '0', '3'], ['willo flood', '2', '0', '0', '2'], ['claus bech jãrgensen', '2', '0', '0', '2'], ['isaac osbourne', '1', '1', '0', '2'], ['kevin thornton', '2', '0', '0', '2'], ['andrew whing', '2', '0', '0', '2']] |
mark mccumber | https://en.wikipedia.org/wiki/Mark_McCumber | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1598242-3.html.csv | comparative | golfer mark mccumber has had the same number of consecutive cuts in the us open and pga championship . | {'row_1': '2', 'row_2': '4', 'col': '7', 'col_other': '1', 'relation': 'equal', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'us open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to us open .', 'tostr': 'filter_eq { all_rows ; tournament ; us open }'}, 'cuts made'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; us open } ; cuts made }', 'tointer': 'select the rows whose tournament record fuzzily matches to us open . take the cuts made record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'pga championship'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to pga championship .', 'tostr': 'filter_eq { all_rows ; tournament ; pga championship }'}, 'cuts made'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; pga championship } ; cuts made }', 'tointer': 'select the rows whose tournament record fuzzily matches to pga championship . take the cuts made record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; tournament ; us open } ; cuts made } ; hop { filter_eq { all_rows ; tournament ; pga championship } ; cuts made } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to us open . take the cuts made record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the cuts made record of this row . the first record is equal to the second record .'} | eq { hop { filter_eq { all_rows ; tournament ; us open } ; cuts made } ; hop { filter_eq { all_rows ; tournament ; pga championship } ; cuts made } } = true | select the rows whose tournament record fuzzily matches to us open . take the cuts made record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the cuts made record of this row . the first record is equal to the second record . | 5 | 5 | {'eq_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'us open_8': 8, 'cuts made_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'pga championship_12': 12, 'cuts made_13': 13} | {'eq_4': 'eq', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'us open_8': 'us open', 'cuts made_9': 'cuts made', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'pga championship_12': 'pga championship', 'cuts made_13': 'cuts made'} | {'eq_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'us open_8': [0], 'cuts made_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'pga championship_12': [1], 'cuts made_13': [3]} | ['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '0', '0', '5', '12', '10'], ['us open', '0', '1', '2', '5', '13', '9'], ['the open championship', '0', '1', '2', '2', '7', '5'], ['pga championship', '0', '1', '1', '2', '16', '9'], ['totals', '0', '3', '5', '14', '48', '33']] |
conservative party of canada candidates , 2008 canadian federal election | https://en.wikipedia.org/wiki/Conservative_Party_of_Canada_candidates%2C_2008_Canadian_federal_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12890271-1.html.csv | unique | only one male conservative party candidate in the 2008 election received fewer than 3000 votes . | {'scope': 'subset', 'row': '3', 'col': '6', 'col_other': '2', 'criterion': 'less_than', 'value': '3000', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'm'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gender', 'm'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; gender ; m }', 'tointer': 'select the rows whose gender record fuzzily matches to m .'}, 'votes', '3000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose gender record fuzzily matches to m . among these rows , select the rows whose votes record is less than 3000 .', 'tostr': 'filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 } }', 'tointer': 'select the rows whose gender record fuzzily matches to m . among these rows , select the rows whose votes record is less than 3000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gender', 'm'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; gender ; m }', 'tointer': 'select the rows whose gender record fuzzily matches to m .'}, 'votes', '3000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose gender record fuzzily matches to m . among these rows , select the rows whose votes record is less than 3000 .', 'tostr': 'filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 }'}, "candidate 's name"], 'result': 'lorne robinson', 'ind': 3, 'tostr': "hop { filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 } ; candidate 's name }"}, 'lorne robinson'], 'result': True, 'ind': 4, 'tostr': "eq { hop { filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 } ; candidate 's name } ; lorne robinson }", 'tointer': "the candidate 's name record of this unqiue row is lorne robinson ."}], 'result': True, 'ind': 5, 'tostr': "and { only { filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 } } ; eq { hop { filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 } ; candidate 's name } ; lorne robinson } } = true", 'tointer': "select the rows whose gender record fuzzily matches to m . among these rows , select the rows whose votes record is less than 3000 . there is only one such row in the table . the candidate 's name record of this unqiue row is lorne robinson ."} | and { only { filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 } } ; eq { hop { filter_less { filter_eq { all_rows ; gender ; m } ; votes ; 3000 } ; candidate 's name } ; lorne robinson } } = true | select the rows whose gender record fuzzily matches to m . among these rows , select the rows whose votes record is less than 3000 . there is only one such row in the table . the candidate 's name record of this unqiue row is lorne robinson . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'gender_8': 8, 'm_9': 9, 'votes_10': 10, '3000_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, "candidate 's name_12": 12, 'lorne robinson_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'gender_8': 'gender', 'm_9': 'm', 'votes_10': 'votes', '3000_11': '3000', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', "candidate 's name_12": "candidate 's name", 'lorne robinson_13': 'lorne robinson'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_less_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'gender_8': [0], 'm_9': [0], 'votes_10': [1], '3000_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], "candidate 's name_12": [3], 'lorne robinson_13': [4]} | ['riding', "candidate 's name", 'gender', 'residence', 'occupation', 'votes', 'rank'] | [['avalon', 'fabian manning', 'm', "st bride 's", 'parliamentarian', '11542', '2nd'], ['bonavista-gander-grand falls-windsor', 'andrew house', 'm', 'gander', 'lawyer', '4354', '2nd'], ['humber-st barbe-baie verte', 'lorne robinson', 'm', 'pasadena', 'financial planner', '2799', '3rd'], ['labrador', 'lacey lewis', 'f', 'ottawa', 'office assistant', '615', '3rd'], ["random-burin-st george 's", 'herb davis', 'm', 'gatineau', 'policy advisor', '4791', '3rd'], ["st john 's east", 'craig westcott', 'm', 'conception bay south', 'journalist', '3836', '3rd'], ["st john 's south-mount pearl", 'merv wiseman', 'm', 'north harbour', 'maritime search & rescue coordinator', '4324', '3rd']] |
united states house of representatives elections , 1970 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1970 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341718-44.html.csv | ordinal | the incumbent that ran in the 1970 united states house of representatives elections for district one in texas was also first elected before any other incumbents running in the other districts of texas . | {'row': '1', 'col': '4', 'order': '1', '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', 'first elected', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; first elected ; 1 }'}, 'district'], 'result': 'texas 1', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; first elected ; 1 } ; district }'}, 'texas 1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; district } ; texas 1 } = true', 'tointer': 'select the row whose first elected record of all rows is 1st minimum . the district record of this row is texas 1 .'} | eq { hop { nth_argmin { all_rows ; first elected ; 1 } ; district } ; texas 1 } = true | select the row whose first elected record of all rows is 1st minimum . the district record of this row is texas 1 . | 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, '1_6': 6, 'district_7': 7, 'texas 1_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', '1_6': '1', 'district_7': 'district', 'texas 1_8': 'texas 1'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '1_6': [0], 'district_7': [1], 'texas 1_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) 78.5 % james hogan ( r ) 21.5 %'], ['texas 2', 'john dowdy', 'democratic', '1952', 're - elected', 'john dowdy ( d ) unopposed'], ['texas 3', 'james m collins', 'republican', '1968', 're - elected', 'james m collins ( r ) 60.6 % john mead ( d ) 39.4 %'], ['texas 4', 'ray roberts', 'democratic', '1962', 're - elected', 'ray roberts ( d ) unopposed'], ['texas 5', 'earle cabell', 'democratic', '1964', 're - elected', 'earle cabell ( d ) 59.7 % frank crowley ( r ) 40.3 %'], ['texas 6', 'olin e teague', 'democratic', '1946', 're - elected', 'olin e teague ( d ) unopposed'], ['texas 8', 'robert c eckhardt', 'democratic', '1966', 're - elected', 'robert c eckhardt ( d ) unopposed'], ['texas 9', 'jack brooks', 'democratic', '1952', 're - elected', 'jack brooks ( d ) 64.5 % henry c pressler ( d ) 35.5 %'], ['texas 10', 'j j pickle', 'democratic', '1963', 're - elected', 'j j pickle ( d ) unopposed'], ['texas 11', 'william r poage', 'democratic', '1936', 're - elected', 'william r poage ( d ) unopposed'], ['texas 12', 'jim wright', 'democratic', '1954', 're - elected', 'jim wright ( d ) unopposed'], ['texas 14', 'john andrew young', 'democratic', '1956', 're - elected', 'john andrew young ( d ) unopposed'], ['texas 17', 'omar burleson', 'democratic', '1946', 're - elected', 'omar burleson ( d ) unopposed'], ['texas 18', 'bob price', 'republican', '1966', 're - elected', 'bob price ( r ) unopposed'], ['texas 19', 'george h mahon', 'democratic', '1934', 're - elected', 'george h mahon ( d ) unopposed'], ['texas 20', 'henry b gonzalez', 'democratic', '1961', 're - elected', 'henry b gonzalez ( d ) unopposed'], ['texas 21', 'o c fisher', 'democratic', '1942', 're - elected', 'o c fisher ( d ) 61.4 % richard gill ( r ) 38.6 %'], ['texas 22', 'robert r casey', 'democratic', '1958', 're - elected', 'robert r casey ( d ) 55.6 % arthur busch ( r ) 44.4 %']] |
nfl europe | https://en.wikipedia.org/wiki/NFL_Europe | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-160994-4.html.csv | comparative | of the stadiums used by nfl europe , white hart lane opened before ashton gate . | {'row_1': '14', 'row_2': '10', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'stadium', 'white hart lane'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose stadium record fuzzily matches to white hart lane .', 'tostr': 'filter_eq { all_rows ; stadium ; white hart lane }'}, 'opened'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; stadium ; white hart lane } ; opened }', 'tointer': 'select the rows whose stadium record fuzzily matches to white hart lane . take the opened record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'stadium', 'ashton gate'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose stadium record fuzzily matches to ashton gate .', 'tostr': 'filter_eq { all_rows ; stadium ; ashton gate }'}, 'opened'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; stadium ; ashton gate } ; opened }', 'tointer': 'select the rows whose stadium record fuzzily matches to ashton gate . take the opened record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; stadium ; white hart lane } ; opened } ; hop { filter_eq { all_rows ; stadium ; ashton gate } ; opened } } = true', 'tointer': 'select the rows whose stadium record fuzzily matches to white hart lane . take the opened record of this row . select the rows whose stadium record fuzzily matches to ashton gate . take the opened record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; stadium ; white hart lane } ; opened } ; hop { filter_eq { all_rows ; stadium ; ashton gate } ; opened } } = true | select the rows whose stadium record fuzzily matches to white hart lane . take the opened record of this row . select the rows whose stadium record fuzzily matches to ashton gate . take the opened record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'stadium_7': 7, 'white hart lane_8': 8, 'opened_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'stadium_11': 11, 'ashton gate_12': 12, 'opened_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'stadium_7': 'stadium', 'white hart lane_8': 'white hart lane', 'opened_9': 'opened', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'stadium_11': 'stadium', 'ashton gate_12': 'ashton gate', 'opened_13': 'opened'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'stadium_7': [0], 'white hart lane_8': [0], 'opened_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'stadium_11': [1], 'ashton gate_12': [1], 'opened_13': [3]} | ['team', 'stadium', 'capacity', 'opened', 'city'] | [['amsterdam admirals', 'amsterdam arena', '51859', '1996', 'amsterdam , the netherlands'], ['amsterdam admirals', 'olympisch stadion', '31600', '1928', 'amsterdam , the netherlands'], ['barcelona dragons', 'mini estadi', '15276', '1982', 'barcelona , spain'], ['barcelona dragons', 'estadi olímpic lluís companys', '56000', '1929', 'barcelona , spain'], ['berlin thunder', 'olympiastadion', '76000', '1936', 'berlin , germany'], ['berlin thunder', 'f l jahn sportpark', '19500', '1951', 'berlin , germany'], ['cologne centurions', 'rheinenergiestadion', '50374', '1923', 'cologne , germany'], ['frankfurt galaxy', 'commerzbank - arena waldstadion ( 1925 - 2005 )', '52000', '1925', 'frankfurt , germany'], ['hamburg sea devils', 'aol arena', '55989', '2000', 'hamburg , germany'], ['london / england monarchs', 'ashton gate', '21500', '1900', 'bristol , england'], ['london / england monarchs', 'alexander stadium', '7600', '1976', 'birmingham , england'], ['london / england monarchs', 'crystal palace national sports centre', '15500', '1964', 'london , england'], ['london / england monarchs', 'stamford bridge', '42449', '1877', 'london , england'], ['london / england monarchs', 'white hart lane', '36240', '1899', 'london , england'], ['london / england monarchs', 'wembley stadium', '80000', '1923', 'london , england'], ['rhein fire', 'ltu arena', '51500', '2004', 'düsseldorf , germany'], ['rhein fire', 'arena aufschalke', '61524', '2001', 'gelsenkirchen , germany'], ['rhein fire', 'rheinstadion', '55900', '1926', 'düsseldorf , germany'], ['scottish claymores', 'hampden park', '52500', '1903', 'glasgow , scotland'], ['scottish claymores', 'murrayfield stadium', '67500', '1925', 'edinburgh , scotland']] |
list of kentucky derby broadcasters | https://en.wikipedia.org/wiki/List_of_Kentucky_Derby_broadcasters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22514845-4.html.csv | majority | all of the kentucky derby broadcasts were shown on the abc network . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'abc', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'network', 'abc'], 'result': True, 'ind': 0, 'tointer': 'for the network records of all rows , all of them fuzzily match to abc .', 'tostr': 'all_eq { all_rows ; network ; abc } = true'} | all_eq { all_rows ; network ; abc } = true | for the network records of all rows , all of them fuzzily match to abc . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'network_3': 3, 'abc_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'network_3': 'network', 'abc_4': 'abc'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'network_3': [0], 'abc_4': [0]} | ['year', 'network', 'race caller', 's host', 's analyst', 'reporters', 'trophy presentation'] | [['1989', 'abc', 'dave johnson', 'jim mckay and al michaels', 'charlsie cantey and dave johnson', 'jack whitaker and lynn swann', 'jim mckay'], ['1988', 'abc', 'dave johnson', 'jim mckay and al michaels', 'charlsie cantey and dave johnson', 'jack whitaker and lynn swann', 'jim mckay'], ['1987', 'abc', 'dave johnson', 'jim mckay and al michaels', 'charlsie cantey and dave johnson', 'jack whitaker and lynn swann', 'jim mckay'], ['1986', 'abc', 'mike battaglia', 'jim mckay and al michaels', 'charlsie cantey and bill hartack', 'jack whitaker and lynn swann', 'jim mckay'], ['1985', 'abc', 'mike battaglia', 'jim mckay', 'bill hartack', 'howard cosell and jack whitaker', 'jim mckay'], ['1984', 'abc', 'mike battaglia', 'jim mckay', 'bill hartack', 'howard cosell and jack whitaker', 'jim mckay'], ['1983', 'abc', 'mike battaglia', 'jim mckay', 'bill hartack', 'howard cosell , frank gifford , and jack whitaker', 'jim mckay'], ['1982', 'abc', 'mike battaglia', 'jim mckay', 'john m veitch', 'howard cosell and jack whitaker', 'jim mckay'], ['1981', 'abc', 'mike battaglia', 'jim mckay', 'eddie arcaro', 'howard cosell', 'jim mckay and howard cosell']] |
2010 ucla bruins baseball team | https://en.wikipedia.org/wiki/2010_UCLA_Bruins_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27862483-4.html.csv | unique | the may 25th game against cal state fullerton is the only time during the month of may for the 2010 ucla bruins baseball season that they played at goodwin field . | {'scope': 'all', 'row': '15', 'col': '4', 'col_other': '2,3', 'criterion': 'equal', 'value': 'goodwin field', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'site / stadium', 'goodwin field'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose site / stadium record fuzzily matches to goodwin field .', 'tostr': 'filter_eq { all_rows ; site / stadium ; goodwin field }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; site / stadium ; goodwin field } }', 'tointer': 'select the rows whose site / stadium record fuzzily matches to goodwin field . 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', 'site / stadium', 'goodwin field'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose site / stadium record fuzzily matches to goodwin field .', 'tostr': 'filter_eq { all_rows ; site / stadium ; goodwin field }'}, 'date'], 'result': 'may 25', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; date }'}, 'may 25'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; date } ; may 25 }', 'tointer': 'the date record of this unqiue row is may 25 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'site / stadium', 'goodwin field'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose site / stadium record fuzzily matches to goodwin field .', 'tostr': 'filter_eq { all_rows ; site / stadium ; goodwin field }'}, 'opponent'], 'result': 'cal state fullerton', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; opponent }'}, 'cal state fullerton'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; opponent } ; cal state fullerton }', 'tointer': 'the opponent record of this unqiue row is cal state fullerton .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; date } ; may 25 } ; eq { hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; opponent } ; cal state fullerton } }', 'tointer': 'the date record of this unqiue row is may 25 . the opponent record of this unqiue row is cal state fullerton .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; site / stadium ; goodwin field } } ; and { eq { hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; date } ; may 25 } ; eq { hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; opponent } ; cal state fullerton } } } = true', 'tointer': 'select the rows whose site / stadium record fuzzily matches to goodwin field . there is only one such row in the table . the date record of this unqiue row is may 25 . the opponent record of this unqiue row is cal state fullerton .'} | and { only { filter_eq { all_rows ; site / stadium ; goodwin field } } ; and { eq { hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; date } ; may 25 } ; eq { hop { filter_eq { all_rows ; site / stadium ; goodwin field } ; opponent } ; cal state fullerton } } } = true | select the rows whose site / stadium record fuzzily matches to goodwin field . there is only one such row in the table . the date record of this unqiue row is may 25 . the opponent record of this unqiue row is cal state fullerton . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'site / stadium_10': 10, 'goodwin field_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'date_12': 12, 'may 25_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'opponent_14': 14, 'cal state fullerton_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'site / stadium_10': 'site / stadium', 'goodwin field_11': 'goodwin field', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_12': 'date', 'may 25_13': 'may 25', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'opponent_14': 'opponent', 'cal state fullerton_15': 'cal state fullerton'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'site / stadium_10': [0], 'goodwin field_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'date_12': [2], 'may 25_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'opponent_14': [4], 'cal state fullerton_15': [5]} | ['', 'date', 'opponent', 'site / stadium', 'score', 'win', 'loss', 'save', 'attendance', 'overall record', 'pac - 10 record'] | [['39', 'may 1', 'arizona state', 'jackie robinson stadium', '6 - 1', 'm kelly ( 9 - 0 )', 't bauer ( 6 - 3 )', 'b rodgers ( 3 )', '1725', '30 - 9', '7 - 7'], ['40', 'may 2', 'arizona state', 'jackie robinson stadium', '12 - 3', 'j borup ( 9 - 1 )', 'r rasmussen ( 6 - 2 )', 'none', '1921', '30 - 10', '7 - 8'], ['41', 'may 4', 'pepperdine', 'eddy d field stadium', '5 - 1', 'g claypool ( 7 - 1 )', 'r dickmann ( 6 - 4 )', 'none', '261', '31 - 10', '7 - 8'], ['42', 'may 7', 'washington', 'husky ballpark', '7 - 2', 'g cole ( 7 - 2 )', 'g brown ( 1 - 4 )', 'none', '485', '32 - 10', '8 - 8'], ['43', 'may 8', 'washington', 'husky ballpark', '14 - 6', 't bauer ( 7 - 3 )', 'a kittredge ( 6 - 4 )', 'd klein ( 9 )', '716', '33 - 10', '9 - 8'], ['44', 'may 9', 'washington', 'husky ballpark', '7 - 6', 'r rasmussen ( 7 - 2 )', 'f snow ( 4 - 2 )', 'none', '562', '34 - 10', '10 - 8'], ['45', 'may 11', 'uc irvine', 'cicerone field', '2 - 1', 'n hoover ( 2 - 0 )', 'g claypool ( 7 - 2 )', 'e brock ( 1 )', '1172', '34 - 11', '10 - 8'], ['46', 'may 14', 'usc', 'jackie robinson stadium', '13 - 7', 'g cole ( 8 - 2 )', 'b mount ( 5 - 4 )', 'none', '1707', '35 - 11', '11 - 8'], ['47', 'may 15', 'usc', 'jackie robinson stadium', '15 - 2', 't bauer ( 8 - 3 )', 'c mezger ( 4 - 1 )', 'none', '1360', '36 - 11', '12 - 8'], ['48', 'may 16', 'usc', 'jackie robinson stadium', '2 - 1', 'd klein ( 4 - 0 )', 'c smith ( 4 - 6 )', 'none', '1531', '37 - 11', '13 - 8'], ['49', 'may 18', 'uc santa barbara', 'jackie robinson stadium', '6 - 2', 'g claypool ( 8 - 2 )', 'n capito ( 4 - 6 )', 'none', '587', '38 - 11', '13 - 8'], ['50', 'may 21', 'california', 'evans diamond', '8 - 7', 'd klein ( 5 - 0 )', 'm flemer ( 2 - 3 )', 'none', '417', '39 - 11', '14 - 8'], ['51', 'may 22', 'california', 'evans diamond', '12 - 4', 't bauer ( 9 - 3 )', 'd anderson ( 4 - 3 )', 'none', '534', '40 - 11', '15 - 8'], ['52', 'may 23', 'california', 'evans diamond', '11 - 2', 'r rasmussen ( 8 - 2 )', 'j jones ( 9 - 5 )', 'none', '737', '41 - 11', '16 - 8'], ['53', 'may 25', 'cal state fullerton', 'goodwin field', '5 - 2', 'no ramirez ( 9 - 1 )', 'g claypool ( 8 - 3 )', 'ni ramirez ( 9 )', '2376', '41 - 12', '16 - 8'], ['54', 'may 28', 'washington state', 'jackie robinson stadium', '6 - 1', 'g cole ( 9 - 2 )', 'c arnold ( 5 - 3 )', 'none', '1006', '42 - 12', '17 - 8'], ['55', 'may 29', 'washington state', 'jackie robinson stadium', '6 - 4', 's harvey ( 3 - 1 )', 'm grace ( 0 - 1 )', 'a conley ( 11 )', '1170', '42 - 13', '17 - 9']] |
glasvegas ( album ) | https://en.wikipedia.org/wiki/Glasvegas_%28album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18268852-4.html.csv | unique | only in the united kingdom was the album " glasvegas " released as an lp . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'lp', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'lp'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose format record fuzzily matches to lp .', 'tostr': 'filter_eq { all_rows ; format ; lp }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; format ; lp } }', 'tointer': 'select the rows whose format record fuzzily matches to lp . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'format', 'lp'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose format record fuzzily matches to lp .', 'tostr': 'filter_eq { all_rows ; format ; lp }'}, 'country'], 'result': 'united kingdom', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; format ; lp } ; country }'}, 'united kingdom'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; format ; lp } ; country } ; united kingdom }', 'tointer': 'the country record of this unqiue row is united kingdom .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; format ; lp } } ; eq { hop { filter_eq { all_rows ; format ; lp } ; country } ; united kingdom } } = true', 'tointer': 'select the rows whose format record fuzzily matches to lp . there is only one such row in the table . the country record of this unqiue row is united kingdom .'} | and { only { filter_eq { all_rows ; format ; lp } } ; eq { hop { filter_eq { all_rows ; format ; lp } ; country } ; united kingdom } } = true | select the rows whose format record fuzzily matches to lp . there is only one such row in the table . the country record of this unqiue row is united kingdom . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'format_7': 7, 'lp_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'country_9': 9, 'united kingdom_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'format_7': 'format', 'lp_8': 'lp', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'country_9': 'country', 'united kingdom_10': 'united kingdom'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'format_7': [0], 'lp_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'country_9': [2], 'united kingdom_10': [3]} | ['country', 'date', 'label', 'format', 'catalogue'] | [['united kingdom', '8 september 2008', 'columbia', 'cd , download', '886973273920 ( gowow010 )'], ['united kingdom', '8 september 2008', 'columbia', 'limited edition cd / dvd', '886973738924 ( gowow011 )'], ['united kingdom', '8 september 2008', 'columbia', 'lp', '886973273913 ( gowow012 )'], ['japan', '12 november 2008', 'sony music', 'cd', 'sicp - 2070'], ['united states', '6 january 2009', 'columbia', 'cd', '886974356523']] |
2008 - 09 f.c. copenhagen season | https://en.wikipedia.org/wiki/2008%E2%80%9309_F.C._Copenhagen_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17637370-3.html.csv | majority | most of the new players on f.c. copenhagen during the 2008 - 09 season came during the summer transfer window . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'summer', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'transfer window', 'summer'], 'result': True, 'ind': 0, 'tointer': 'for the transfer window records of all rows , most of them fuzzily match to summer .', 'tostr': 'most_eq { all_rows ; transfer window ; summer } = true'} | most_eq { all_rows ; transfer window ; summer } = true | for the transfer window records of all rows , most of them fuzzily match to summer . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'transfer window_3': 3, 'summer_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'transfer window_3': 'transfer window', 'summer_4': 'summer'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'transfer window_3': [0], 'summer_4': [0]} | ['nat', 'name', 'moving from', 'type', 'transfer window', 'ends', 'transfer fee', 'source'] | [['dnk', 'd jensen', 'youth system', 'promoted', 'summer', '2011', 'youth system', 'fckdk'], ['dnk', 'albrechtsen', 'youth system', 'promoted', 'summer', '2010', 'youth system', 'fckdk'], ['dnk', 'bertolt', 'viborg', 'end of loan', 'summer', '2009', 'n / a', 'fckdk'], ['dnk', 'kristensen', 'nordsjãlland', 'transfer', 'summer', '2012', 'undisclosed', 'fckdk'], ['bra', 'santin', 'kalmar ff', 'transfer', 'summer', '2013', 'dkk 15000000', 'fckdk'], ['swe', 'larsson', 'halmstads bk', 'transfer', 'summer', '2013', 'dkk 15000000', 'fckdk'], ['swe', 'wiland', 'if elfsborg', 'transfer', 'winter', '2013', 'dkk 8000000', 'fckdk'], ['dnk', 'vingaard', 'esbjerg', 'transfer', 'winter', '2012', 'dkk 8000000', 'fckdk'], ['sen', "n'doye", 'ofi', 'transfer', 'winter', '2013', 'dkk 15000000', 'fckdk']] |
list of how it 's made episodes | https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15187735-6.html.csv | unique | episode 71 was the only one that covered the topic of wigs . | {'scope': 'all', 'row': '6', 'col': '7', 'col_other': '2', 'criterion': 'equal', 'value': 'wigs', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment d', 'wigs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment d record fuzzily matches to wigs .', 'tostr': 'filter_eq { all_rows ; segment d ; wigs }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; segment d ; wigs } }', 'tointer': 'select the rows whose segment d record fuzzily matches to wigs . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment d', 'wigs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment d record fuzzily matches to wigs .', 'tostr': 'filter_eq { all_rows ; segment d ; wigs }'}, 'episode'], 'result': '71', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; segment d ; wigs } ; episode }'}, '71'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; segment d ; wigs } ; episode } ; 71 }', 'tointer': 'the episode record of this unqiue row is 71 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; segment d ; wigs } } ; eq { hop { filter_eq { all_rows ; segment d ; wigs } ; episode } ; 71 } } = true', 'tointer': 'select the rows whose segment d record fuzzily matches to wigs . there is only one such row in the table . the episode record of this unqiue row is 71 .'} | and { only { filter_eq { all_rows ; segment d ; wigs } } ; eq { hop { filter_eq { all_rows ; segment d ; wigs } ; episode } ; 71 } } = true | select the rows whose segment d record fuzzily matches to wigs . there is only one such row in the table . the episode record of this unqiue row is 71 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'segment d_7': 7, 'wigs_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'episode_9': 9, '71_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', 'wigs_8': 'wigs', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'episode_9': 'episode', '71_10': '71'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'segment d_7': [0], 'wigs_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'episode_9': [2], '71_10': [3]} | ['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d'] | [['6 - 01', '66', 's03e14', 'three wheeled vehicles', 'baseball bats', 'artificial bonsai', 's trombone'], ['6 - 02', '67', 's03e15', 's spring', 's paver', 's piano ( part 1 )', 's piano ( part 2 )'], ['6 - 03', '68', 's03e16', 's rope', 's billiard table', 's sailboard', 's cymbal'], ['6 - 04', '69', 's03e17', 's seatbelt', 's window', 'wax figurines', 'hot air balloons'], ['6 - 05', '70', 's03e18', 'air filters', 'billiard cues', 'ice sculptures', 's suit'], ['6 - 06', '71', 's03e19', 'escalator s handrail', 's highlighter', 'guitar s string', 'wigs'], ['6 - 07', '72', 's03e20', 'traditional bows', 's coffee machine', 's mascot', 's hammock'], ['6 - 08', '73', 's03e21', 'fibreglass insulation', 's wooden duck', 'gumball machines', 'exhaust systems'], ['6 - 09', '74', 's03e22', 's chain', 's bagel', 'vinyl records ( part 1 )', 'vinyl records ( part 2 )'], ['6 - 10', '75', 's03e23', 's windshield', 'english saddles', 'butter', 'post clocks'], ['6 - 11', '76', 's03e24', 'individual transporters', 'cedar canoes', 'electric guitars ( part 1 )', 'electric guitars ( part 2 )'], ['6 - 12', '77', 's03e25', 'residential water heaters', 'air bags', 'jelly beans', 'ice resurfacers'], ['6 - 13', '78', 's03e26', 'amphibious vehicles', 's putter', 'model ships', 's drumhead']] |
list of new york undercover episodes | https://en.wikipedia.org/wiki/List_of_New_York_Undercover_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11951237-4.html.csv | count | the new york undercover drama have a total of 10 seasons . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '10', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'season'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record is arbitrary .', 'tostr': 'filter_all { all_rows ; season }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; season } }', 'tointer': 'select the rows whose season record is arbitrary . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; season } } ; 10 } = true', 'tointer': 'select the rows whose season record is arbitrary . the number of such rows is 10 .'} | eq { count { filter_all { all_rows ; season } } ; 10 } = true | select the rows whose season record is arbitrary . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'season_5': 5, '10_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'season_5': 'season', '10_6': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'season_5': [0], '10_6': [2]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'production code'] | [['77', '1', 'change , change , change', 'don kurt', 'brad kern', 'january 8 , 1998', 'k2701'], ['78', '2', 'drop dead gorgeous', 'norberto barba', 'kim newton', 'january 15 , 1998', 'k2704'], ['79', '3', 'pipeline', 'norberto barba', 'darin goldberg & shelley meals', 'january 22 , 1998', 'k2705'], ['80', '4', 'spare parts', 'frederick k keller', 'edward tivnan', 'january 29 , 1998', 'k2702'], ['81', '5', 'mob street', 'don kurt', 'brad kern', 'february 12 , 1998', 'k2706'], ['82', '6', 'rat trap', 'timothy van patten', 'kim newton', 'march 12 , 1998', 'k2708'], ['83', '7', 'quid pro quo', 'martha mitchell', 'denitria harris - lawrence', 'march 19 , 1998', 'k2709'], ['84', '8', 'capital punishment', 'melanie mayron', 'edward tivnan', 'march 26 , 1998', 'k2707'], ['85', '9', 'the unusual suspects', 'allen coulter', 'denitria harris - lawrence', 'may 28 , 1998', 'k2703'], ['86', '10', "sign o ' the times", 'timothy van patten', 'darin goldberg & shelley meals', 'june 4 , 1998', 'k2710']] |
malaysia at the olympics | https://en.wikipedia.org/wiki/Malaysia_at_the_Olympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14812763-1.html.csv | count | lee chong wei won two silver medals in the men 's singles for malaysia at the olympics . | {'scope': 'subset', 'criterion': 'equal', 'value': 'lee chong wei', 'result': '2', 'col': '2', 'subset': {'col': '5', 'criterion': 'equal', 'value': "men 's singles"}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', "men 's singles"], 'result': None, 'ind': 0, 'tostr': "filter_eq { all_rows ; event ; men 's singles }", 'tointer': "select the rows whose event record fuzzily matches to men 's singles ."}, 'name', 'lee chong wei'], 'result': None, 'ind': 1, 'tointer': "select the rows whose event record fuzzily matches to men 's singles . among these rows , select the rows whose name record fuzzily matches to lee chong wei .", 'tostr': "filter_eq { filter_eq { all_rows ; event ; men 's singles } ; name ; lee chong wei }"}], 'result': '2', 'ind': 2, 'tostr': "count { filter_eq { filter_eq { all_rows ; event ; men 's singles } ; name ; lee chong wei } }", 'tointer': "select the rows whose event record fuzzily matches to men 's singles . among these rows , select the rows whose name record fuzzily matches to lee chong wei . the number of such rows is 2 ."}, '2'], 'result': True, 'ind': 3, 'tostr': "eq { count { filter_eq { filter_eq { all_rows ; event ; men 's singles } ; name ; lee chong wei } } ; 2 } = true", 'tointer': "select the rows whose event record fuzzily matches to men 's singles . among these rows , select the rows whose name record fuzzily matches to lee chong wei . the number of such rows is 2 ."} | eq { count { filter_eq { filter_eq { all_rows ; event ; men 's singles } ; name ; lee chong wei } } ; 2 } = true | select the rows whose event record fuzzily matches to men 's singles . among these rows , select the rows whose name record fuzzily matches to lee chong wei . 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, 'event_6': 6, "men 's singles_7": 7, 'name_8': 8, 'lee chong wei_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', 'event_6': 'event', "men 's singles_7": "men 's singles", 'name_8': 'name', 'lee chong wei_9': 'lee chong wei', '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], 'event_6': [0], "men 's singles_7": [0], 'name_8': [1], 'lee chong wei_9': [1], '2_10': [3]} | ['medal', 'name', 'games', 'sport', 'event'] | [['bronze', 'razif sidek & jalani sidek', '1992 barcelona', 'badminton', "men 's doubles"], ['silver', 'cheah soon kit & yap kim hock', '1996 atlanta', 'badminton', "men 's doubles"], ['bronze', 'rashid sidek', '1996 atlanta', 'badminton', "men 's singles"], ['silver', 'lee chong wei', '2008 beijing', 'badminton', "men 's singles"], ['silver', 'lee chong wei', '2012 london', 'badminton', "men 's singles"], ['bronze', 'pandelela rinong pamg', '2012 london', 'diving', "women 's 10 metre platform"]] |
united states district court for the eastern district of california | https://en.wikipedia.org/wiki/United_States_District_Court_for_the_Eastern_District_of_California | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1065275-2.html.csv | count | of the judges in the united states district court for the eastern district of california , seven died while in office . | {'scope': 'all', 'criterion': 'equal', 'value': 'death', 'result': '7', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for termination', 'death'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for termination record fuzzily matches to death .', 'tostr': 'filter_eq { all_rows ; reason for termination ; death }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; reason for termination ; death } }', 'tointer': 'select the rows whose reason for termination record fuzzily matches to death . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; reason for termination ; death } } ; 7 } = true', 'tointer': 'select the rows whose reason for termination record fuzzily matches to death . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; reason for termination ; death } } ; 7 } = true | select the rows whose reason for termination record fuzzily matches to death . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'reason for termination_5': 5, 'death_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'reason for termination_5': 'reason for termination', 'death_6': 'death', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'reason for termination_5': [0], 'death_6': [0], '7_7': [2]} | ['state', 'born / died', 'active service', 'chief judge', 'senior status', 'appointed by', 'reason for termination'] | [['ca', '1914 - 2010', '1966 - 1981', '1966 - 1967', '1981 - 2010', 'eisenhower', 'death'], ['ca', '1901 - 1991', '1966 - 1969', '-', '1969 - 1991', 'eisenhower', 'death'], ['ca', '1914 - 2000', '1966 - 1979', '1967 - 1979', '1979 - 2000', 'kennedy', 'death'], ['ca', '1913 - 1998', '1969 - 1983', '1979 - 1983', '1983 - 1998', 'nixon', 'death'], ['ca', '1920 - 2005', '1979 - 1990', '-', '1990 - 2005', 'carter', 'death'], ['ca', '1919 - 1997', '1979 - 1989', '-', '1989 - 1997', 'carter', 'death'], ['ca', '1944 - present', '1980 - 1989', '-', '-', 'carter', 'resignation'], ['ca', '1930 - 2012', '1982 - 1996', '1990 - 1996', '1996 - 2006', 'reagan', 'death'], ['ca', '1928 - present', '1984 - 1996', '-', '1996 - 2012', 'reagan', 'retirement'], ['ca', '1952 - present', '1990 - 2007', '2003 - 2007', '-', 'ghw bush', 'resignation'], ['ca', '1940 - present', '1991 - 2006', '-', '2006 - 2011', 'ghw bush', 'retirement'], ['ca', '1938 - present', '1997 - 2008', '-', '2008 - 2011', 'clinton', 'retirement']] |
1963 - 64 segunda división | https://en.wikipedia.org/wiki/1963%E2%80%9364_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17740819-4.html.csv | superlative | the ud las palmas club had the most points in the 1963 - 64 segunda división season . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'club'], 'result': 'ud las palmas', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; club }'}, 'ud las palmas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; club } ; ud las palmas } = true', 'tointer': 'select the row whose points record of all rows is maximum . the club record of this row is ud las palmas .'} | eq { hop { argmax { all_rows ; points } ; club } ; ud las palmas } = true | select the row whose points record of all rows is maximum . the club record of this row is ud las palmas . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'club_6': 6, 'ud las palmas_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'club_6': 'club', 'ud las palmas_7': 'ud las palmas'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'club_6': [1], 'ud las palmas_7': [2]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'ud las palmas', '30', '40', '17', '6', '7', '45', '25', '+ 20'], ['2', 'hércules cf', '30', '38', '15', '8', '7', '48', '38', '+ 10'], ['3', 'rcd mallorca', '30', '37', '16', '5', '9', '52', '32', '+ 20'], ['4', 'cd mestalla', '30', '33', '13', '7', '10', '60', '38', '+ 22'], ['5', 'cd tenerife', '30', '32', '14', '4', '12', '30', '40', '- 10'], ['6', 'granada cf', '30', '32', '12', '8', '10', '41', '32', '+ 9'], ['7', 'cádiz cf', '30', '30', '13', '4', '13', '45', '41', '+ 4'], ['8', 'algeciras cf', '30', '30', '13', '4', '13', '40', '53', '- 13'], ['9', 'cd málaga', '30', '30', '12', '6', '12', '38', '33', '+ 5'], ['10', 'onteniente cf', '30', '29', '10', '9', '11', '33', '29', '+ 4'], ['11', 'recreativo de huelva', '30', '29', '10', '9', '11', '41', '34', '+ 7'], ['12', 'melilla cf', '30', '28', '10', '8', '12', '34', '38', '- 4'], ['13', 'cd abarán', '30', '26', '10', '6', '14', '38', '49', '- 11'], ['14', 'atlético ceuta', '30', '26', '10', '6', '14', '29', '49', '- 20'], ['15', 'cd san fernando', '30', '21', '9', '3', '18', '24', '45', '- 21'], ['16', 'cd eldense', '30', '19', '7', '5', '18', '33', '55', '- 22']] |
tenerife ladies open | https://en.wikipedia.org/wiki/Tenerife_Ladies_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11177563-1.html.csv | count | the golf costa adeje was the venue of the tenerife ladies open a total of three times . | {'scope': 'all', 'criterion': 'equal', 'value': 'golf costa adeje', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'golf costa adeje'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to golf costa adeje .', 'tostr': 'filter_eq { all_rows ; venue ; golf costa adeje }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; venue ; golf costa adeje } }', 'tointer': 'select the rows whose venue record fuzzily matches to golf costa adeje . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; venue ; golf costa adeje } } ; 3 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to golf costa adeje . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; venue ; golf costa adeje } } ; 3 } = true | select the rows whose venue record fuzzily matches to golf costa adeje . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'golf costa adeje_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'golf costa adeje_6': 'golf costa adeje', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'golf costa adeje_6': [0], '3_7': [2]} | ['year', 'date', 'venue', 'winner', 'country', 'score', 'to par', 'margin of victory', 'runner ( s ) - up', "winner 's share"] | [['tenerife ladies match play', 'tenerife ladies match play', 'tenerife ladies match play', 'tenerife ladies match play', 'tenerife ladies match play', 'tenerife ladies match play', 'tenerife ladies match play', 'tenerife ladies match play', 'tenerife ladies match play', 'tenerife ladies match play'], ['2011', '12 jun', 'golf las américas', 'becky brewerton', 'wales', '68', '4', '1 stroke', 'carlota ciganda', '40000'], ['2011', '12 jun', 'golf las américas', 'becky brewerton', 'wales', '68', '4', '1 stroke', 'nikki garrett', '40000'], ['tenerife ladies open', 'tenerife ladies open', 'tenerife ladies open', 'tenerife ladies open', 'tenerife ladies open', 'tenerife ladies open', 'tenerife ladies open', 'tenerife ladies open', 'tenerife ladies open', 'tenerife ladies open'], ['2010', '4 jul', 'buenavista golf club', 'trish johnson', 'england', '274', '14', '1 stroke', 'virginie lagoutte - clément', '41250'], ['2009', '27 sep', 'golf costa adeje', 'felicity johnson', 'england', '274', '14', '2 strokes', 'becky brewerton', '45000'], ['2008', '22 jun', 'golf costa adeje', 'rebecca hudson', 'england', '278', '10', 'playoff', 'anne - lise caudal', '45000'], ['2007', '6 may', 'golf del sur tenerife', 'nikki garrett', 'australia', '287', '1', '2 strokes', 'trish johnson', '41250'], ['2007', '6 may', 'golf del sur tenerife', 'nikki garrett', 'australia', '287', '1', '2 strokes', 'tania elosegui', '41250'], ['2006', '30 apr', 'abama', 'riikka hakkarainen', 'finland', '288', 'e', '2 strokes', 'tania elosegui', '37500'], ['2005', '10 apr', 'golf costa adeje', 'ludivine kreutz', 'france', '277', '11', '2 strokes', 'miriam nagl', '36300'], ['2004', '2 may', 'buenavista golf club', 'diana luna', 'italy', '279', '9', '2 strokes', 'becky brewerton', '33000'], ['2003', '4 may', 'golf las américas', 'elisabeth esterl', 'germany', '276', '12', '1 stroke', 'becky brewerton', '30000'], ['2002', '5 may', 'golf del sur tenerife', 'raquel carriedo', 'spain', '292', '+ 4', '1 stroke', 'johanna head', '30000']] |
1965 vfl season | https://en.wikipedia.org/wiki/1965_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10788451-6.html.csv | aggregation | the average crowd for games on the 22nd may during the 1965 vfl season was 24662 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '24662', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '24662', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '24662'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 24662 } = true', 'tointer': 'the average of the crowd record of all rows is 24662 .'} | round_eq { avg { all_rows ; crowd } ; 24662 } = true | the average of the crowd record of all rows is 24662 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '24662_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '24662_5': '24662'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '24662_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '8.10 ( 58 )', 'st kilda', '14.12 ( 96 )', 'city of coburg oval', '13291', '22 may 1965'], ['fitzroy', '8.8 ( 56 )', 'geelong', '11.21 ( 87 )', 'brunswick street oval', '11925', '22 may 1965'], ['carlton', '8.13 ( 61 )', 'richmond', '6.9 ( 45 )', 'princes park', '29949', '22 may 1965'], ['hawthorn', '12.9 ( 81 )', 'footscray', '10.14 ( 74 )', 'glenferrie oval', '11800', '22 may 1965'], ['south melbourne', '14.12 ( 96 )', 'essendon', '12.16 ( 88 )', 'lake oval', '24200', '22 may 1965'], ['melbourne', '6.13 ( 49 )', 'collingwood', '7.5 ( 47 )', 'mcg', '56808', '22 may 1965']] |
thomas wheatley ( locomotive engineer ) | https://en.wikipedia.org/wiki/Thomas_Wheatley_%28locomotive_engineer%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10668727-1.html.csv | superlative | the 396 nbr class locomotive was the highest total produced locomotive that was designed by thomas wheatley . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '10', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total }'}, 'nbr class'], 'result': '396', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total } ; nbr class }'}, '396'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total } ; nbr class } ; 396 } = true', 'tointer': 'select the row whose total record of all rows is maximum . the nbr class record of this row is 396 .'} | eq { hop { argmax { all_rows ; total } ; nbr class } ; 396 } = true | select the row whose total record of all rows is maximum . the nbr class record of this row is 396 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total_5': 5, 'nbr class_6': 6, '396_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total_5': 'total', 'nbr class_6': 'nbr class', '396_7': '396'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total_5': [0], 'nbr class_6': [1], '396_7': [2]} | ['nbr class', 'type', 'introduced', 'driving wheel', 'total', 'extinct'] | [['141', '2 - 4 - 0', '1869', 'ft6in ( mm )', '2', '1915'], ['38', '2 - 4 - 0', '1869', 'ft0in ( mm )', '1', '1912'], ['418', '2 - 4 - 0', '1873', 'ft0in ( mm )', '8', '1927'], ['40', '2 - 4 - 0', '1873', 'ft0in ( mm )', '2', '1903'], ['224', '4 - 4 - 0', '1871', 'ft6in ( mm )', '2', '1919'], ['420', '4 - 4 - 0', '1873', 'ft6in ( mm )', '4', '1918'], ['251', '0 - 6 - 0', '1867', 'ft3in ( mm )', '38', '1924'], ['56', '0 - 6 - 0', '1868', 'ft0in ( mm )', '8', '1914'], ['17', '0 - 6 - 0', '1869', 'ft6in ( mm )', '1', '1914'], ['396', '0 - 6 - 0', '1867', 'ft0in ( mm )', '88', '1937'], ['293', '0 - 6 - 0', '1872', 'ft0in ( mm )', '1', '1907'], ['357', '0 - 4 - 0', '1868', 'ft3in ( mm )', '2', '1925'], ['226', '0 - 6 - 0st', '1870', 'ft0in ( mm )', '2', '1924'], ['229', '0 - 6 - 0st', '1871', 'ft0in ( mm )', '15', '1924'], ['112', '0 - 6 - 0st', '1870', 'ft6in ( mm )', '3', '1910'], ['282', '0 - 6 - 0st', '1866', 'ft1in ( mm )', '3', '1921'], ['130', '0 - 6 - 0st', '1870', 'ft3in ( mm )', '10', '1924'], ['32', '0 - 6 - 0st', '1874', 'ft6in ( mm )', '6', '1907'], ['18', '0 - 4 - 0st', '1872', 'ft0in ( mm )', '2', '1906']] |
1970 isle of man tt | https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-5.html.csv | superlative | the rider representing australia won first place with 15 points during the 1970 isle of man tt . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1,3', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'points'], 'result': '15', 'ind': 0, 'tostr': 'max { all_rows ; points }', 'tointer': 'the maximum points record of all rows is 15 .'}, '15'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; points } ; 15 }', 'tointer': 'the maximum points record of all rows is 15 .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; points }'}, 'place'], 'result': '1', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; points } ; place }'}, '1'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; points } ; place } ; 1 }', 'tointer': 'the place record of the row with superlative points record is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; points }'}, 'country'], 'result': 'australia', 'ind': 5, 'tostr': 'hop { argmax { all_rows ; points } ; country }'}, 'australia'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { argmax { all_rows ; points } ; country } ; australia }', 'tointer': 'the country record of the row with superlative points record is australia .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { argmax { all_rows ; points } ; place } ; 1 } ; eq { hop { argmax { all_rows ; points } ; country } ; australia } }', 'tointer': 'the place record of the row with superlative points record is 1 . the country record of the row with superlative points record is australia .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { max { all_rows ; points } ; 15 } ; and { eq { hop { argmax { all_rows ; points } ; place } ; 1 } ; eq { hop { argmax { all_rows ; points } ; country } ; australia } } } = true', 'tointer': 'the maximum points record of all rows is 15 . the place record of the row with superlative points record is 1 . the country record of the row with superlative points record is australia .'} | and { eq { max { all_rows ; points } ; 15 } ; and { eq { hop { argmax { all_rows ; points } ; place } ; 1 } ; eq { hop { argmax { all_rows ; points } ; country } ; australia } } } = true | the maximum points record of all rows is 15 . the place record of the row with superlative points record is 1 . the country record of the row with superlative points record is australia . | 10 | 9 | {'and_8': 8, 'result_9': 9, 'eq_1': 1, 'max_0': 0, 'all_rows_10': 10, 'points_11': 11, '15_12': 12, 'and_7': 7, 'eq_4': 4, 'num_hop_3': 3, 'argmax_2': 2, 'all_rows_13': 13, 'points_14': 14, 'place_15': 15, '1_16': 16, 'str_eq_6': 6, 'str_hop_5': 5, 'country_17': 17, 'australia_18': 18} | {'and_8': 'and', 'result_9': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_10': 'all_rows', 'points_11': 'points', '15_12': '15', 'and_7': 'and', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'argmax_2': 'argmax', 'all_rows_13': 'all_rows', 'points_14': 'points', 'place_15': 'place', '1_16': '1', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'country_17': 'country', 'australia_18': 'australia'} | {'and_8': [9], 'result_9': [], 'eq_1': [8], 'max_0': [1], 'all_rows_10': [0], 'points_11': [0], '15_12': [1], 'and_7': [8], 'eq_4': [7], 'num_hop_3': [4], 'argmax_2': [3, 5], 'all_rows_13': [2], 'points_14': [2], 'place_15': [3], '1_16': [4], 'str_eq_6': [7], 'str_hop_5': [6], 'country_17': [5], 'australia_18': [6]} | ['place', 'rider', 'country', 'machine', 'speed', 'time', 'points'] | [['1', 'kel carruthers', 'australia', 'yamaha', '96.13 mph', '2:21.19.2', '15'], ['2', 'rod gould', 'united kingdom', 'yamaha', '93.75 mph', '2:24.54.0', '12'], ['3', 'günter bartusch', 'east germany', 'mz', '93.75 mph', '2:26.58.0', '10'], ['4', 'chas mortimer', 'united kingdom', 'yamaha', '91.95 mph', '2:27.44.2', '8'], ['5', 'peter berwick', 'united kingdom', 'suzuki', '91.93 mph', '2:27.46.0', '6'], ['6', 'alex george', 'united kingdom', 'yamaha', '91.42 mph', '2:28.35.8', '5'], ['7', 'ian richardson', 'united kingdom', 'yamaha', '91.22 mph', '2:28.53.6', '4'], ['8', 'börje jansson', 'sweden', 'yamaha', '90.57 mph', '2:29.59.6', '3'], ['9', 'tony smith', 'united kingdom', 'yamaha', '90.44 mph', '2:30.12.2', '2'], ['10', 'bill smith', 'united kingdom', 'yamaha', '90.20 mph', '2:30.36.2', '1']] |
united states house of representatives elections , 2012 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2012 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25030512-41.html.csv | superlative | in the 2012 election for the united states house of representatives , the incumbent with the earliest date of first election was mike doyle . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '11', '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', 'first elected'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; first elected }'}, 'incumbent'], 'result': 'mike doyle', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; first elected } ; incumbent }'}, 'mike doyle'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; first elected } ; incumbent } ; mike doyle } = true', 'tointer': 'select the row whose first elected record of all rows is minimum . the incumbent record of this row is mike doyle .'} | eq { hop { argmin { all_rows ; first elected } ; incumbent } ; mike doyle } = true | select the row whose first elected record of all rows is minimum . the incumbent record of this row is mike doyle . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'first elected_5': 5, 'incumbent_6': 6, 'mike doyle_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'first elected_5': 'first elected', 'incumbent_6': 'incumbent', 'mike doyle_7': 'mike doyle'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'first elected_5': [0], 'incumbent_6': [1], 'mike doyle_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['pennsylvania 1', 'bob brady', 'democratic', '1998', 're - elected', 'bob brady ( d ) 85.1 % john featherman ( r ) 15.0 %'], ['pennsylvania 5', 'glenn thompson', 'republican', '2008', 're - elected', 'glenn thompson ( r ) 62.9 % charles dumas ( d ) 37.1 %'], ['pennsylvania 6', 'jim gerlach', 'republican', '2002', 're - elected', 'jim gerlach ( r ) 57.1 % manan trivedi ( d ) 42.9 %'], ['pennsylvania 7', 'pat meehan', 'republican', '2010', 're - elected', 'pat meehan ( r ) 59.5 % george badey ( d ) 40.5 %'], ['pennsylvania 9', 'bill shuster', 'republican', '2000', 're - elected', 'bill shuster ( r ) 61.6 % karen ramsburg ( d ) 38.4 %'], ['pennsylvania 10', 'tom marino', 'republican', '2010', 're - elected', 'tom marino ( r ) 65.9 % phil scollo ( d ) 34.1 %'], ['pennsylvania 11', 'lou barletta', 'republican', '2010', 're - elected', 'lou barletta ( r ) 58.5 % gene stilp ( d ) 41.5 %'], ['pennsylvania 12', 'mark critz', 'democratic', '2010', 'lost re - election republican gain', 'keith rothfus ( r ) 51.5 % mark critz ( d ) 48.5 %'], ['pennsylvania 12', 'jason altmire redistricted from the 4th district', 'democratic', '2006', 'lost renomination democratic loss', 'keith rothfus ( r ) 51.5 % mark critz ( d ) 48.5 %'], ['pennsylvania 13', 'allyson schwartz', 'democratic', '2004', 're - elected', 'allyson schwartz ( d ) 69.0 % joe rooney ( r ) 31.0 %'], ['pennsylvania 14', 'mike doyle', 'democratic', '1994', 're - elected', 'mike doyle ( d ) 77.0 % hans lessmann ( r ) 23.1 %'], ['pennsylvania 15', 'charlie dent', 'republican', '2004', 're - elected', 'charlie dent ( r ) 56.6 % rick daugherty ( d ) 43.4 %']] |
list of australia one day international cricket records | https://en.wikipedia.org/wiki/List_of_Australia_One_Day_International_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21100348-10.html.csv | comparative | adam voges has a higher number of runs compared to callum ferguson , regarding the australia one day international cricket records . | {'row_1': '3', 'row_2': '9', 'col': '4', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'adam voges'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to adam voges .', 'tostr': 'filter_eq { all_rows ; player ; adam voges }'}, 'runs'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; adam voges } ; runs }', 'tointer': 'select the rows whose player record fuzzily matches to adam voges . take the runs record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'callum ferguson'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose player record fuzzily matches to callum ferguson .', 'tostr': 'filter_eq { all_rows ; player ; callum ferguson }'}, 'runs'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; player ; callum ferguson } ; runs }', 'tointer': 'select the rows whose player record fuzzily matches to callum ferguson . take the runs record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; player ; adam voges } ; runs } ; hop { filter_eq { all_rows ; player ; callum ferguson } ; runs } } = true', 'tointer': 'select the rows whose player record fuzzily matches to adam voges . take the runs record of this row . select the rows whose player record fuzzily matches to callum ferguson . take the runs record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; player ; adam voges } ; runs } ; hop { filter_eq { all_rows ; player ; callum ferguson } ; runs } } = true | select the rows whose player record fuzzily matches to adam voges . take the runs record of this row . select the rows whose player record fuzzily matches to callum ferguson . take the runs record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, 'adam voges_8': 8, 'runs_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'player_11': 11, 'callum ferguson_12': 12, 'runs_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', 'adam voges_8': 'adam voges', 'runs_9': 'runs', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'player_11': 'player', 'callum ferguson_12': 'callum ferguson', 'runs_13': 'runs'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'player_7': [0], 'adam voges_8': [0], 'runs_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'player_11': [1], 'callum ferguson_12': [1], 'runs_13': [3]} | ['rank', 'average', 'player', 'runs', 'innings', 'not out', 'period'] | [['1', '56.85', 'george bailey', '1535', '33', '4', '2012 -'], ['2', '53.58', 'michael bevan', '6912', '196', '67', '1994 - 2004'], ['3', '52.53', 'adam voges', '683', '20', '7', '2007 -'], ['4', '48.15', 'mike hussey', '5442', '157', '44', '2004 - 2012'], ['5', '45.08', 'michael clarke', '7484', '209', '43', '2003 -'], ['6', '44.61', 'dean jones', '6068', '161', '25', '1984 - 1994'], ['7', '44.10', 'matthew hayden', '6131', '154', '15', '1993 - 2008'], ['8', '41.81', 'ricky ponting', '13589', '364', '39', '1995 - 2012'], ['9', '41.43', 'callum ferguson', '663', '25', '9', '2009 - 2011']] |
bears - packers rivalry | https://en.wikipedia.org/wiki/Bears%E2%80%93Packers_rivalry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11650849-7.html.csv | unique | the sunday , september 27 game was the only one where both teams scored under 10 points each . | {'scope': 'all', 'row': '19', 'col': '4', 'col_other': '2', 'criterion': 'less_than', 'value': '10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'result', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record is less than 10 .', 'tostr': 'filter_less { all_rows ; result ; 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; result ; 10 } }', 'tointer': 'select the rows whose result record is less than 10 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'result', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record is less than 10 .', 'tostr': 'filter_less { all_rows ; result ; 10 }'}, 'date'], 'result': 'sunday , september 27', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; result ; 10 } ; date }'}, 'sunday , september 27'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; result ; 10 } ; date } ; sunday , september 27 }', 'tointer': 'the date record of this unqiue row is sunday , september 27 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; result ; 10 } } ; eq { hop { filter_less { all_rows ; result ; 10 } ; date } ; sunday , september 27 } } = true', 'tointer': 'select the rows whose result record is less than 10 . there is only one such row in the table . the date record of this unqiue row is sunday , september 27 .'} | and { only { filter_less { all_rows ; result ; 10 } } ; eq { hop { filter_less { all_rows ; result ; 10 } ; date } ; sunday , september 27 } } = true | select the rows whose result record is less than 10 . there is only one such row in the table . the date record of this unqiue row is sunday , september 27 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'result_7': 7, '10_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'sunday , september 27_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'result_7': 'result', '10_8': '10', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'sunday , september 27_10': 'sunday , september 27'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'result_7': [0], '10_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'sunday , september 27_10': [3]} | ['year', 'date', 'winner', 'result', 'loser', 'attendance', 'location'] | [['1950', 'sunday , october 1', 'green bay packers', '31 - 21', 'chicago bears', '24893', 'green bay'], ['1950', 'sunday , october 15', 'chicago bears', '28 - 14', 'green bay packers', '51065', 'chicago'], ['1951', 'sunday , september 30', 'chicago bears', '31 - 20', 'green bay packers', '24666', 'green bay'], ['1951', 'sunday , november 18', 'chicago bears', '24 - 13', 'green bay packers', '36771', 'chicago'], ['1952', 'sunday , september 28', 'chicago bears', '24 - 14', 'green bay packers', '24656', 'green bay'], ['1952', 'sunday , november 9', 'green bay packers', '41 - 28', 'chicago bears', '41751', 'chicago'], ['1953', 'sunday , october 4', 'chicago bears', '17 - 13', 'green bay packers', '24835', 'green bay'], ['1953', 'sunday , november 8', 'chicago bears', '21 - 21', 'green bay packers', '39889', 'chicago'], ['1954', 'sunday , october 3', 'chicago bears', '10 - 3', 'green bay packers', '24414', 'green bay'], ['1954', 'sunday , november 7', 'chicago bears', '28 - 23', 'green bay packers', '47038', 'chicago'], ['1955', 'sunday , october 2', 'green bay packers', '24 - 3', 'chicago bears', '24662', 'green bay'], ['1955', 'sunday , november 6', 'chicago bears', '52 - 31', 'green bay packers', '48890', 'chicago'], ['1956', 'sunday , october 7', 'chicago bears', '37 - 21', 'green bay packers', '24668', 'green bay'], ['1956', 'sunday , november 11', 'chicago bears', '38 - 14', 'green bay packers', '49172', 'chicago'], ['1957', 'sunday , september 29', 'green bay packers', '21 - 17', 'chicago bears', '32132', 'green bay'], ['1957', 'sunday , november 10', 'chicago bears', '21 - 14', 'green bay packers', '47153', 'chicago'], ['1958', 'sunday , september 28', 'chicago bears', '34 - 20', 'green bay packers', '32150', 'green bay'], ['1958', 'sunday , november 9', 'chicago bears', '24 - 10', 'green bay packers', '48424', 'chicago'], ['1959', 'sunday , september 27', 'green bay packers', '9 - 6', 'chicago bears', '32150', 'green bay'], ['1959', 'sunday , november 8', 'chicago bears', '28 - 17', 'green bay packers', '46205', 'chicago']] |
great midwest conference | https://en.wikipedia.org/wiki/Great_Midwest_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2419754-1.html.csv | comparative | university of dayton was founded at an earlier year than the university of memphis . | {'row_1': '2', 'row_2': '5', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'university of dayton'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to university of dayton .', 'tostr': 'filter_eq { all_rows ; institution ; university of dayton }'}, 'founded'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; institution ; university of dayton } ; founded }', 'tointer': 'select the rows whose institution record fuzzily matches to university of dayton . take the founded record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'university of memphis'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose institution record fuzzily matches to university of memphis .', 'tostr': 'filter_eq { all_rows ; institution ; university of memphis }'}, 'founded'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; institution ; university of memphis } ; founded }', 'tointer': 'select the rows whose institution record fuzzily matches to university of memphis . take the founded record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; institution ; university of dayton } ; founded } ; hop { filter_eq { all_rows ; institution ; university of memphis } ; founded } } = true', 'tointer': 'select the rows whose institution record fuzzily matches to university of dayton . take the founded record of this row . select the rows whose institution record fuzzily matches to university of memphis . take the founded record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; institution ; university of dayton } ; founded } ; hop { filter_eq { all_rows ; institution ; university of memphis } ; founded } } = true | select the rows whose institution record fuzzily matches to university of dayton . take the founded record of this row . select the rows whose institution record fuzzily matches to university of memphis . take the founded record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'institution_7': 7, 'university of dayton_8': 8, 'founded_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'institution_11': 11, 'university of memphis_12': 12, 'founded_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'institution_7': 'institution', 'university of dayton_8': 'university of dayton', 'founded_9': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'institution_11': 'institution', 'university of memphis_12': 'university of memphis', 'founded_13': 'founded'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'institution_7': [0], 'university of dayton_8': [0], 'founded_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'institution_11': [1], 'university of memphis_12': [1], 'founded_13': [3]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'joined', 'left'] | [['university of cincinnati', 'bearcats', 'cincinnati , ohio', '1819', 'public', '41357', '1991', '1995'], ['university of dayton', 'flyers', 'dayton , ohio', '1850', 'private', '11186', '1993', '1995'], ['depaul university', 'blue demons', 'chicago , illinois', '1898', 'private', '24966', '1991', '1995'], ['marquette university', 'golden eagles', 'milwaukee , wisconsin', '1881', 'private', '12002', '1991', '1995'], ['university of memphis', 'tigers', 'memphis , tennessee', '1912', 'public', '22365', '1991', '1995'], ['saint louis university', 'billikens', 'st louis , missouri', '1818', 'private', '13785', '1991', '1995']] |
georgia kokloni | https://en.wikipedia.org/wiki/Georgia_Kokloni | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16198032-1.html.csv | superlative | georgia kokloni had her best performance in the year of 2009 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'position'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; position }'}, 'year'], 'result': '2009', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; position } ; year }'}, '2009'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; position } ; year } ; 2009 } = true', 'tointer': 'select the row whose position record of all rows is minimum . the year record of this row is 2009 .'} | eq { hop { argmin { all_rows ; position } ; year } ; 2009 } = true | select the row whose position record of all rows is minimum . the year record of this row is 2009 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'position_5': 5, 'year_6': 6, '2009_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'position_5': 'position', 'year_6': 'year', '2009_7': '2009'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'position_5': [0], 'year_6': [1], '2009_7': [2]} | ['year', 'competition', 'venue', 'position', 'event'] | [['2002', 'european indoor championships', 'vienna , germany', '3rd', '60 m'], ['2002', 'european championships', 'munich , germany', '9th', '100 m'], ['2004', 'world indoor championships', 'budapest , hungary', '9th', '60 m'], ['2005', 'european indoor championships', 'madrid , spain', '2nd', '60 m'], ['2006', 'european championships', 'gothenburg , sweden', '9th', '100 m'], ['2006', 'world cup', 'athens , greece', '6th', '100 m'], ['2009', 'european team championships', 'leiria , portugal', '6th', '100 m'], ['2009', 'mediterranean games', 'pescara , italy', '1st', '100 m'], ['2010', 'european championships', 'barcelona , spain', '7th', '100 m'], ['2011', 'european indoor championships', 'paris , france', '9th', '60 m']] |
list of gilmore girls episodes | https://en.wikipedia.org/wiki/List_of_Gilmore_Girls_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2602958-5.html.csv | superlative | the episode " the lorelais ' first day at yale " has the least number of us viewers . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'us viewers ( million )'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; us viewers ( million ) }'}, 'title'], 'result': "the lorelais ' first day at yale", 'ind': 1, 'tostr': 'hop { argmin { all_rows ; us viewers ( million ) } ; title }'}, "the lorelais ' first day at yale"], 'result': True, 'ind': 2, 'tostr': "eq { hop { argmin { all_rows ; us viewers ( million ) } ; title } ; the lorelais ' first day at yale } = true", 'tointer': "select the row whose us viewers ( million ) record of all rows is minimum . the title record of this row is the lorelais ' first day at yale ."} | eq { hop { argmin { all_rows ; us viewers ( million ) } ; title } ; the lorelais ' first day at yale } = true | select the row whose us viewers ( million ) record of all rows is minimum . the title record of this row is the lorelais ' first day at yale . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'us viewers (million)_5': 5, 'title_6': 6, "the lorelais' first day at yale_7": 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'us viewers (million)_5': 'us viewers ( million )', 'title_6': 'title', "the lorelais' first day at yale_7": "the lorelais ' first day at yale"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'us viewers (million)_5': [0], 'title_6': [1], "the lorelais' first day at yale_7": [2]} | ['no', '-', 'title', 'director', 'writer ( s )', 'original air date', 'prod code', 'us viewers ( million )'] | [['66', '1', 'ballrooms and biscotti', 'amy sherman - palladino', 'amy sherman - palladino', 'september 23 , 2003', '176151', '5.2'], ['67', '2', "the lorelais ' first day at yale", 'chris long', 'daniel palladino', 'september 30 , 2003', '176152', '3.9'], ['68', '3', 'the hobbit , the sofa and digger stiles', 'matthew diamond', 'amy sherman - palladino', 'october 7 , 2003', '176153', '4.9'], ['69', '4', 'chicken or beef', 'chris long', 'jane espenson', 'october 14 , 2003', '176154', '5.5'], ['70', '5', 'the fundamental things apply', 'neema barnette', 'john stephens', 'october 21 , 2003', '176155', '5.5'], ['71', '6', 'an affair to remember', 'matthew diamond', 'amy sherman - palladino', 'october 28 , 2003', '176156', '5.2'], ['72', '7', 'the festival of living art', 'chris long', 'daniel palladino', 'november 4 , 2003', '176157', '4.7'], ['73', '8', 'die , jerk', 'tom moore', 'daniel palladino', 'november 11 , 2003', '176158', '4.9'], ['74', '9', "ted koppel 's big night out", 'jamie babbit', 'amy sherman - palladino', 'november 18 , 2003', '176159', '5.2'], ['75', '10', 'the nanny and the professor', 'peter lauer', 'scott kaufer', 'january 20 , 2004', '176160', '4.1'], ['76', '11', 'in the clamor and the clangor', 'michael grossman', 'sheila r lawrence , janet leahy', 'january 27 , 2004', '176161', '4.4'], ['77', '12', 'a family matter', 'kenny ortega', 'daniel palladino', 'february 3 , 2004', '176162', '4.9'], ['79', '14', 'the incredible sinking lorelais', 'stephen clancy', 'amy sherman - palladino , daniel palladino', 'february 17 , 2004', '176164', '4.8'], ['80', '15', 'scene in a mall', 'chris long', 'daniel palladino', 'february 24 , 2004', '176165', '4.8'], ['81', '16', 'the reigning lorelai', 'marita grabiak', 'jane espenson', 'march 2 , 2004', '176166', '5.0'], ['82', '17', "girls in bikinis , boys doin ' the twist", 'jamie babbit', 'amy sherman - palladino', 'april 13 , 2004', '176167', '4.5'], ['83', '18', 'tick , tick , tick , boom !', 'daniel palladino', 'daniel palladino', 'april 20 , 2004', '176168', '4.2'], ['84', '19', 'afterboom', 'michael zinberg', 'sheila r lawrence', 'april 27 , 2004', '176169', '4.3'], ['85', '20', 'luke can see her face', 'matthew diamond', 'amy sherman - palladino , daniel palladino', 'may 4 , 2004', '176170', '4.2'], ['86', '21', 'last week fights , this week tights', 'chris long', 'daniel palladino', 'may 11 , 2004', '176171', '4.6']] |
carleton county , new brunswick | https://en.wikipedia.org/wiki/Carleton_County%2C_New_Brunswick | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-170961-2.html.csv | superlative | the parish of kent has the highest area ( km2 ) among the parishes in carleton county , new brunswick . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'area km 2'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; area km 2 }'}, 'official name'], 'result': 'kent', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; area km 2 } ; official name }'}, 'kent'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; area km 2 } ; official name } ; kent } = true', 'tointer': 'select the row whose area km 2 record of all rows is maximum . the official name record of this row is kent .'} | eq { hop { argmax { all_rows ; area km 2 } ; official name } ; kent } = true | select the row whose area km 2 record of all rows is maximum . the official name record of this row is kent . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'area km 2_5': 5, 'official name_6': 6, 'kent_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'area km 2_5': 'area km 2', 'official name_6': 'official name', 'kent_7': 'kent'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'area km 2_5': [0], 'official name_6': [1], 'kent_7': [2]} | ['official name', 'status', 'area km 2', 'population', 'census ranking'] | [['wakefield', 'parish', '196.42', '2703', '1079 of 5008'], ['kent', 'parish', '839.79', '2361', '1184 of 5008'], ['woodstock', 'parish', '197.45', '2148', '1258 of 5008'], ['brighton', 'parish', '508.30', '1834', '1402 of 5008'], ['wicklow', 'parish', '195.50', '1753', '1441 of 5008'], ['northampton', 'parish', '243.31', '1599', '1537 of 5008'], ['richmond', 'parish', '258.82', '1414', '1666 of 5008'], ['peel', 'parish', '113.12', '1257', '1779 of 5008'], ['wilmot', 'parish', '191.43', '1143', '1888 of 5008'], ['aberdeen', 'parish', '447.91', '959', '2105 of 5008'], ['simonds', 'parish', '75.54', '489', '3044 of 5008']] |
1985 senior pga tour | https://en.wikipedia.org/wiki/1985_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11622829-4.html.csv | aggregation | between them , the top two players from the united states had a total of 35 wins . | {'scope': 'subset', 'col': '5', 'type': 'sum', 'result': '35', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '2'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'rank', '2'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; rank ; 2 }', 'tointer': 'select the rows whose rank record is less than or equal to 2 .'}, 'wins'], 'result': '35', 'ind': 1, 'tostr': 'sum { filter_less_eq { all_rows ; rank ; 2 } ; wins }'}, '35'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_less_eq { all_rows ; rank ; 2 } ; wins } ; 35 } = true', 'tointer': 'select the rows whose rank record is less than or equal to 2 . the sum of the wins record of these rows is 35 .'} | round_eq { sum { filter_less_eq { all_rows ; rank ; 2 } ; wins } ; 35 } = true | select the rows whose rank record is less than or equal to 2 . the sum of the wins record of these rows is 35 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'rank_5': 5, '2_6': 6, 'wins_7': 7, '35_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '2_6': '2', 'wins_7': 'wins', '35_8': '35'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'rank_5': [0], '2_6': [0], 'wins_7': [1], '35_8': [2]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'don january', 'united states', '1038996', '18'], ['2', 'miller barber', 'united states', '962133', '17'], ['3', 'peter thomson', 'australia', '706812', '11'], ['4', 'arnold palmer', 'united states', '579998', '9'], ['5', 'gene littler', 'united states', '559751', '3']] |
cycling at the 2008 summer olympics - men 's bmx | https://en.wikipedia.org/wiki/Cycling_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_BMX | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18603914-7.html.csv | ordinal | donny robinson has the second fastest time in the first run . | {'row': '3', 'col': '3', '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', '1st run', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; 1st run ; 2 }'}, 'name'], 'result': 'donny robinson ( usa )', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; 1st run ; 2 } ; name }'}, 'donny robinson ( usa )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; 1st run ; 2 } ; name } ; donny robinson ( usa ) } = true', 'tointer': 'select the row whose 1st run record of all rows is 2nd minimum . the name record of this row is donny robinson ( usa ) .'} | eq { hop { nth_argmin { all_rows ; 1st run ; 2 } ; name } ; donny robinson ( usa ) } = true | select the row whose 1st run record of all rows is 2nd minimum . the name record of this row is donny robinson ( usa ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, '1st run_5': 5, '2_6': 6, 'name_7': 7, 'donny robinson ( usa )_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', '1st run_5': '1st run', '2_6': '2', 'name_7': 'name', 'donny robinson ( usa )_8': 'donny robinson ( usa )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], '1st run_5': [0], '2_6': [0], 'name_7': [1], 'donny robinson ( usa )_8': [2]} | ['rank', 'name', '1st run', '2nd run', '3rd run', 'total'] | [['1', 'mike day ( usa )', '36.470 ( 1 )', '36.219 ( 1 )', '37.461 ( 3 )', '5'], ['2', 'sifiso nhlapo ( rsa )', '37.197 ( 3 )', '36.597 ( 3 )', '36.457 ( 2 )', '8'], ['3', 'donny robinson ( usa )', '36.832 ( 2 )', '36.462 ( 2 )', '56.249 ( 6 )', '10'], ['4', 'andrés jiménez caicedo ( col )', '37.363 ( 4 )', '36.862 ( 4 )', '44.507 ( 5 )', '13'], ['5', 'raymon van der biezen ( ned )', '55.121 ( 7 )', '37.258 ( 6 )', '36.200 ( 1 )', '14'], ['6', 'kyle bennett ( usa )', '43.518 ( 5 )', '37.200 ( 5 )', '43.897 ( 4 )', '14'], ['7', 'artūrs matisons ( lat )', '53.379 ( 6 )', '1:17.170 ( 8 )', 'dnf ( 8 )', '22'], ['8', 'marc willers ( nzl )', '1:22.619 ( 8 )', '43.256 ( 7 )', 'dnf ( 8 )', '23']] |
high jump | https://en.wikipedia.org/wiki/High_jump | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13791-3.html.csv | unique | chaunté lowe is the only athlete whose nationality is the usa . | {'scope': 'all', 'row': '13', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'usa', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to usa .', 'tostr': 'filter_eq { all_rows ; nationality ; usa }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; usa } }', 'tointer': 'select the rows whose nationality record fuzzily matches to usa . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'usa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to usa .', 'tostr': 'filter_eq { all_rows ; nationality ; usa }'}, 'athlete'], 'result': 'chaunté lowe', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; usa } ; athlete }'}, 'chaunté lowe'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; usa } ; athlete } ; chaunté lowe }', 'tointer': 'the athlete record of this unqiue row is chaunté lowe .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; usa } } ; eq { hop { filter_eq { all_rows ; nationality ; usa } ; athlete } ; chaunté lowe } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to usa . there is only one such row in the table . the athlete record of this unqiue row is chaunté lowe .'} | and { only { filter_eq { all_rows ; nationality ; usa } } ; eq { hop { filter_eq { all_rows ; nationality ; usa } ; athlete } ; chaunté lowe } } = true | select the rows whose nationality record fuzzily matches to usa . there is only one such row in the table . the athlete record of this unqiue row is chaunté lowe . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'usa_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'athlete_9': 9, 'chaunté lowe_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'usa_8': 'usa', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'athlete_9': 'athlete', 'chaunté lowe_10': 'chaunté lowe'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'usa_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'athlete_9': [2], 'chaunté lowe_10': [3]} | ['pos', 'mark', 'athlete', 'nationality', 'venue', 'date'] | [['1', '2.09 m ( 6ft10 ¼ in )', 'stefka kostadinova', 'bulgaria', 'rome', '30 august 1987'], ['2', '2.08 m ( 6ft9 ¾ in )', 'blanka vlašić', 'croatia', 'zagreb', '31 august 2009'], ['3', '2.07 m ( 6ft9 ¼ in )', 'lyudmila andonova', 'bulgaria', 'berlin', '20 july 1984'], ['3', '2.07 m ( 6ft9 ¼ in )', 'anna chicherova', 'russia', 'cheboksary', '22 july 2011'], ['5', '2.06 m ( 6ft9in )', 'kajsa bergqvist', 'sweden', 'eberstadt', '26 july 2003'], ['5', '2.06 m ( 6ft9in )', 'hestrie cloete', 'south africa', 'paris', '31 august 2003'], ['5', '2.06 m ( 6ft9in )', 'yelena slesarenko', 'russia', 'athens', '28 august 2004'], ['5', '2.06 m ( 6ft9in )', 'ariane friedrich', 'germany', 'berlin', '14 june 2009'], ['9', '2.05 m ( 6ft8 ½ in )', 'tamara bykova', 'soviet union', 'kiev', '22 june 1984'], ['9', '2.05 m ( 6ft8 ½ in )', 'heike henkel', 'germany', 'tokyo', '31 august 1991'], ['9', '2.05 m ( 6ft8 ½ in )', 'inha babakova', 'ukraine', 'tokyo', '15 september 1995'], ['9', '2.05 m ( 6ft8 ½ in )', 'tia hellebaut', 'belgium', 'beijing', '23 august 2008'], ['9', '2.05 m ( 6ft8 ½ in )', 'chaunté lowe', 'usa', 'des moines', '26 june 2010']] |
1979 england rugby union tour of japan , fiji and tonga | https://en.wikipedia.org/wiki/1979_England_rugby_union_tour_of_Japan%2C_Fiji_and_Tonga | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18787978-1.html.csv | ordinal | during the 1979 england rugby union tour of japan , fiji and tonga , during may the highest score against england was 22 points . | {'scope': 'subset', 'row': '5', 'col': '2', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': '/ 05 /'}} | {'func': 'eq', 'args': [{'func': 'nth_max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '/ 05 /'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; / 05 / }', 'tointer': 'select the rows whose date record fuzzily matches to / 05 / .'}, 'against', '1'], 'result': '22', 'ind': 1, 'tostr': 'nth_max { filter_eq { all_rows ; date ; / 05 / } ; against ; 1 }', 'tointer': 'select the rows whose date record fuzzily matches to / 05 / . the 1st maximum against record of these rows is 22 .'}, '22'], 'result': True, 'ind': 2, 'tostr': 'eq { nth_max { filter_eq { all_rows ; date ; / 05 / } ; against ; 1 } ; 22 } = true', 'tointer': 'select the rows whose date record fuzzily matches to / 05 / . the 1st maximum against record of these rows is 22 .'} | eq { nth_max { filter_eq { all_rows ; date ; / 05 / } ; against ; 1 } ; 22 } = true | select the rows whose date record fuzzily matches to / 05 / . the 1st maximum against record of these rows is 22 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'nth_max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '/ 05 /_6': 6, 'against_7': 7, '1_8': 8, '22_9': 9} | {'eq_2': 'eq', 'result_3': 'true', 'nth_max_1': 'nth_max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '/ 05 /_6': '/ 05 /', 'against_7': 'against', '1_8': '1', '22_9': '22'} | {'eq_2': [3], 'result_3': [], 'nth_max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '/ 05 /_6': [0], 'against_7': [1], '1_8': [1], '22_9': [2]} | ['opposing team', 'against', 'date', 'venue', 'status'] | [["japan ' b '", '7', '10 / 05 / 1979', 'tokyo', 'tour match'], ['japan', '19', '13 / 05 / 1979', 'kintetsu hanazono stadium , osaka', "first ' test '"], ['kyūshū', '3', '16 / 05 / 1979', 'fukuoka', 'tour match'], ['japan', '18', '20 / 05 / 1979', 'olympic stadium , tokyo', "second ' test '"], ['fiji juniors', '22', '25 / 05 / 1979', 'lautoka', 'tour match'], ['fiji', '7', '29 / 05 / 1979', 'national stadium , suva', "' test ' match"], ['tonga', '17', '01 / 06 / 1979', 'teufaiva sport stadium , nuku alofa', "' test ' match"]] |
list of georgian submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Georgian_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18069789-1.html.csv | comparative | ' the other bank ' was submitted for best foreign language film earlier than ' keep smiling ' . | {'row_1': '8', 'row_2': '11', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'film title used in nomination', 'the other bank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose film title used in nomination record fuzzily matches to the other bank .', 'tostr': 'filter_eq { all_rows ; film title used in nomination ; the other bank }'}, 'year ( ceremony )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; film title used in nomination ; the other bank } ; year ( ceremony ) }', 'tointer': 'select the rows whose film title used in nomination record fuzzily matches to the other bank . take the year ( ceremony ) record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'film title used in nomination', 'keep smiling'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose film title used in nomination record fuzzily matches to keep smiling .', 'tostr': 'filter_eq { all_rows ; film title used in nomination ; keep smiling }'}, 'year ( ceremony )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; film title used in nomination ; keep smiling } ; year ( ceremony ) }', 'tointer': 'select the rows whose film title used in nomination record fuzzily matches to keep smiling . take the year ( ceremony ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; film title used in nomination ; the other bank } ; year ( ceremony ) } ; hop { filter_eq { all_rows ; film title used in nomination ; keep smiling } ; year ( ceremony ) } } = true', 'tointer': 'select the rows whose film title used in nomination record fuzzily matches to the other bank . take the year ( ceremony ) record of this row . select the rows whose film title used in nomination record fuzzily matches to keep smiling . take the year ( ceremony ) record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; film title used in nomination ; the other bank } ; year ( ceremony ) } ; hop { filter_eq { all_rows ; film title used in nomination ; keep smiling } ; year ( ceremony ) } } = true | select the rows whose film title used in nomination record fuzzily matches to the other bank . take the year ( ceremony ) record of this row . select the rows whose film title used in nomination record fuzzily matches to keep smiling . take the year ( ceremony ) 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, 'film title used in nomination_7': 7, 'the other bank_8': 8, 'year (ceremony)_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'film title used in nomination_11': 11, 'keep smiling_12': 12, 'year (ceremony)_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', 'film title used in nomination_7': 'film title used in nomination', 'the other bank_8': 'the other bank', 'year (ceremony)_9': 'year ( ceremony )', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'film title used in nomination_11': 'film title used in nomination', 'keep smiling_12': 'keep smiling', 'year (ceremony)_13': 'year ( ceremony )'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'film title used in nomination_7': [0], 'the other bank_8': [0], 'year (ceremony)_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'film title used in nomination_11': [1], 'keep smiling_12': [1], 'year (ceremony)_13': [3]} | ['year ( ceremony )', 'film title used in nomination', 'original title', 'director', 'main language ( s )', 'result'] | [['1996 ( 69th )', 'a chef in love', 'შეყვარებული მზარეულის 1001 რეცეპტი', 'nana dzhordzhadze', 'french , georgian', 'nominee'], ['1999 ( 72nd )', 'here comes the dawn', 'აქ თენდება', 'zaza urushadze', 'georgian', 'not nominated'], ['2000 ( 73rd )', '27 missing kisses', 'ზაფხული , ანუ 27 მოპარული კოცნა', 'nana dzhordzhadze', 'georgian , russian', 'not nominated'], ['2001 ( 74th )', 'migration of the angel', 'ანგელოზის გადაფრენა', 'nodar managadze', 'georgian', 'not nominated'], ['2005 ( 78th )', 'tbilisi , tbilisi', 'თბილისი - თბილისი', 'levan zaqareishvili', 'georgian', 'not nominated'], ['2007 ( 80th )', 'russian triangle', 'რუსული სამკუთხედი', 'aleko tsabadze', 'russian', 'not nominated'], ['2008 ( 81st )', 'mediator', 'მედიატორი', 'dito tsintsadze', 'english , german , russian', 'not nominated'], ['2009 ( 82nd )', 'the other bank', 'გაღმა ნაპირი', 'george ovashvili', 'georgian , abkhaz , russian', 'not nominated'], ['2010 ( 83rd )', 'street days', 'ქუჩის დღეები', 'levan koguashvili', 'georgian', 'not nominated'], ['2011 ( 84th )', 'chantrapas', 'შანტრაპა', 'otar iosseliani', 'french , georgian', 'not nominated'], ['2012 ( 85th )', 'keep smiling', 'გაიღიმეთ', 'rusudan chkonia', 'georgian', 'not nominated']] |
1973 - 74 football league cup | https://en.wikipedia.org/wiki/1973%E2%80%9374_Football_League_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24887326-6.html.csv | ordinal | the sunderland home team game recorded the highest attendance of the 1973 - 74 football league cup . | {'row': '14', 'col': '5', 'order': '1', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 1 }'}, 'home team'], 'result': 'sunderland', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 1 } ; home team }'}, 'sunderland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; home team } ; sunderland } = true', 'tointer': 'select the row whose attendance record of all rows is 1st maximum . the home team record of this row is sunderland .'} | eq { hop { nth_argmax { all_rows ; attendance ; 1 } ; home team } ; sunderland } = true | select the row whose attendance record of all rows is 1st maximum . the home team record of this row is sunderland . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '1_6': 6, 'home team_7': 7, 'sunderland_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '1_6': '1', 'home team_7': 'home team', 'sunderland_8': 'sunderland'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '1_6': [0], 'home team_7': [1], 'sunderland_8': [2]} | ['tie no', 'home team', 'score 1', 'away team', 'attendance', 'date'] | [['1', 'hull city', '4 - 1', 'stockport county', '13753', '06 - 11 - 1973'], ['2', 'birmingham city', '2 - 2', 'newcastle united', '13025', '30 - 10 - 1973'], ['3', 'southampton', '3 - 0', 'chesterfield', '13663', '30 - 10 - 1973'], ['4', 'stoke city', '1 - 1', 'middlesbrough', '19194', '31 - 10 - 1973'], ['5', 'everton', '0 - 1', 'norwich city', '22046', '30 - 10 - 1973'], ['6', 'millwall', '1 - 1', 'bolton wanderers', '9281', '31 - 10 - 1973'], ['7', 'fulham', '2 - 2', 'ipswich town', '8964', '31 - 10 - 1973'], ['8', 'tranmere rovers', '1 - 1', 'wolverhampton wanderers', '14442', '31 - 10 - 1973'], ['9', 'orient', '1 - 1', 'york city', '12061', '31 - 10 - 1973'], ['10', 'carlisle united', '0 - 1', 'manchester city', '14472', '06 - 11 - 1973'], ['11', 'bristol city', '2 - 2', 'coventry city', '19129', '30 - 10 - 1973'], ['12', 'queens park rangers', '8 - 2', 'sheffield wednesday', '16043', '06 - 11 - 1973'], ['13', 'burnley', '1 - 2', 'plymouth argyle', '11150', '30 - 10 - 1973'], ['14', 'sunderland', '0 - 2', 'liverpool', '36208', '21 - 11 - 1973'], ['15', 'west bromwich albion', '1 - 3', 'exeter city', '10783', '31 - 10 - 1973']] |
1995 pga tour | https://en.wikipedia.org/wiki/1995_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14611590-4.html.csv | superlative | of the players listed as winners on the 1995 pga tour the highest number of wins was by tom kite . | {'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', 'wins'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; wins }'}, 'player'], 'result': 'tom kite', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; wins } ; player }'}, 'tom kite'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; wins } ; player } ; tom kite } = true', 'tointer': 'select the row whose wins record of all rows is maximum . the player record of this row is tom kite .'} | eq { hop { argmax { all_rows ; wins } ; player } ; tom kite } = true | select the row whose wins record of all rows is maximum . the player record of this row is tom kite . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'wins_5': 5, 'player_6': 6, 'tom kite_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'wins_5': 'wins', 'player_6': 'player', 'tom kite_7': 'tom kite'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'wins_5': [0], 'player_6': [1], 'tom kite_7': [2]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'greg norman', 'australia', '9592829', '17'], ['2', 'tom kite', 'united states', '9337998', '19'], ['3', 'payne stewart', 'united states', '7389479', '9'], ['4', 'nick price', 'zimbabwe', '7338119', '15'], ['5', 'fred couples', 'united states', '7188408', '11']] |
brian watts | https://en.wikipedia.org/wiki/Brian_Watts | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10167122-1.html.csv | aggregation | brian watts has zero wins in all tournaments combined . | {'scope': 'all', 'col': '2', 'type': 'sum', 'result': '0', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'wins'], 'result': '0', 'ind': 0, 'tostr': 'sum { all_rows ; wins }'}, '0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; wins } ; 0 } = true', 'tointer': 'the sum of the wins record of all rows is 0 .'} | round_eq { sum { all_rows ; wins } ; 0 } = true | the sum of the wins record of all rows is 0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'wins_4': 4, '0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'wins_4': 'wins', '0_5': '0'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'wins_4': [0], '0_5': [1]} | ['tournament', 'wins', 'top - 5', 'top - 25', 'events', 'cuts made'] | [['masters tournament', '0', '0', '0', '2', '1'], ['us open', '0', '0', '1', '2', '1'], ['the open championship', '0', '1', '2', '7', '4'], ['pga championship', '0', '0', '0', '6', '4'], ['totals', '0', '1', '3', '17', '10']] |
list of cold feet episodes | https://en.wikipedia.org/wiki/List_of_Cold_Feet_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12919003-3.html.csv | superlative | episode 5 on the list of cold feet episodes had the greatest number of viewers . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; viewers ( millions ) }'}, 'episode'], 'result': 'episode 5', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; viewers ( millions ) } ; episode }'}, 'episode 5'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; viewers ( millions ) } ; episode } ; episode 5 } = true', 'tointer': 'select the row whose viewers ( millions ) record of all rows is maximum . the episode record of this row is episode 5 .'} | eq { hop { argmax { all_rows ; viewers ( millions ) } ; episode } ; episode 5 } = true | select the row whose viewers ( millions ) record of all rows is maximum . the episode record of this row is episode 5 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'viewers (millions)_5': 5, 'episode_6': 6, 'episode 5_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'viewers (millions)_5': 'viewers ( millions )', 'episode_6': 'episode', 'episode 5_7': 'episode 5'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'viewers (millions)_5': [0], 'episode_6': [1], 'episode 5_7': [2]} | ['', 'episode', 'writer', 'director', 'viewers ( millions )', 'original airdate'] | [['7', 'episode 1', 'mike bullen', 'tom hooper', '8.08', '26 september 1999'], ['8', 'episode 2', 'mike bullen', 'tom hooper', '7.95', '3 october 1999'], ['9', 'episode 3', 'mike bullen', 'tom vaughan', '7.96', '10 october 1999'], ['10', 'episode 4', 'mike bullen', 'tom vaughan', '8.64', '17 october 1999'], ['11', 'episode 5', 'mike bullen', 'pete travis', '9.14', '24 october 1999']] |
seattle supersonics all - time roster | https://en.wikipedia.org/wiki/Seattle_SuperSonics_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16772687-17.html.csv | count | 5 of the seattle supersonics all time players were of us nationality . | {'scope': 'all', 'criterion': 'equal', 'value': 'united states', 'result': '5', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; nationality ; united states }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; nationality ; united states } }', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; nationality ; united states } } ; 5 } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to united states . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; nationality ; united states } } ; 5 } = true | select the rows whose nationality record fuzzily matches to united states . 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, 'nationality_5': 5, 'united states_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', 'nationality_5': 'nationality', 'united states_6': 'united states', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'nationality_5': [0], 'united states_6': [0], '5_7': [2]} | ['player', 'nationality', 'jersey number ( s )', 'position', 'years', 'from'] | [['mark radford', 'united states', '30', 'pg / sg', '1981 - 1983', 'oregon state'], ['vladimir radmanović', 'serbia', '77', 'sf / pf', '2001 - 2006', 'kk fmp'], ['jerry reynolds', 'united states', '35', 'sg / sf', '1988 - 1989', 'louisiana state'], ['luke ridnour', 'united states', '8', 'pg', '2003 - 2008', 'oregon'], ['jackie robinson', 'united states', '22', 'sf', '1979', 'unlv'], ['bob rule', 'united states', '45', 'pf / c', '1967 - 1971', 'colorado state']] |
somerset county cricket club in 2010 | https://en.wikipedia.org/wiki/Somerset_County_Cricket_Club_in_2010 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28846752-9.html.csv | ordinal | max waller had the highest average in the 2010 season of the somerset county cricket club . | {'row': '3', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'average', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; average ; 1 }'}, 'player'], 'result': 'max waller', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; average ; 1 } ; player }'}, 'max waller'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; average ; 1 } ; player } ; max waller } = true', 'tointer': 'select the row whose average record of all rows is 1st maximum . the player record of this row is max waller .'} | eq { hop { nth_argmax { all_rows ; average ; 1 } ; player } ; max waller } = true | select the row whose average record of all rows is 1st maximum . the player record of this row is max waller . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'average_5': 5, '1_6': 6, 'player_7': 7, 'max waller_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', 'average_5': 'average', '1_6': '1', 'player_7': 'player', 'max waller_8': 'max waller'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'average_5': [0], '1_6': [0], 'player_7': [1], 'max waller_8': [2]} | ['player', 'matches', 'overs', 'wickets', 'average', 'economy', 'bbi', '4wi'] | [['murali kartik', '10', '69.3', '20', '16.05', '4.61', '4 / 30', '1'], ['alfonso thomas', '14', '81.1', '27', '15.92', '5.29', '4 / 34', '2'], ['max waller', '8', '39.0', '4', '51.75', '5.30', '2 / 24', '0'], ['ben phillips', '13', '83.5', '19', '24.52', '5.55', '4 / 31', '1'], ['peter trego', '14', '75.3', '13', '33.00', '5.68', '2 / 29', '0'], ['zander de bruyn', '12', '47.2', '15', '19.40', '6.14', '3 / 27', '0'], ['mark turner', '6', '31.5', '9', '26.00', '7.35', '4 / 36', '1']] |
list of multiple barrel firearms | https://en.wikipedia.org/wiki/List_of_multiple_barrel_firearms | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29474407-11.html.csv | comparative | of the multiple barrel firearms , the saturn machine pistol had an introduction year that was 5 years before the serlea . | {'row_1': '7', 'row_2': '8', 'col': '2', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '5 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name / designation', 'saturn machine pistol'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name / designation record fuzzily matches to saturn machine pistol .', 'tostr': 'filter_eq { all_rows ; name / designation ; saturn machine pistol }'}, 'year of intro'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name / designation ; saturn machine pistol } ; year of intro }', 'tointer': 'select the rows whose name / designation record fuzzily matches to saturn machine pistol . take the year of intro record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name / designation', 'serlea'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name / designation record fuzzily matches to serlea .', 'tostr': 'filter_eq { all_rows ; name / designation ; serlea }'}, 'year of intro'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name / designation ; serlea } ; year of intro }', 'tointer': 'select the rows whose name / designation record fuzzily matches to serlea . take the year of intro record of this row .'}], 'result': '-5 years', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; name / designation ; saturn machine pistol } ; year of intro } ; hop { filter_eq { all_rows ; name / designation ; serlea } ; year of intro } }'}, '-5 years'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; name / designation ; saturn machine pistol } ; year of intro } ; hop { filter_eq { all_rows ; name / designation ; serlea } ; year of intro } } ; -5 years } = true', 'tointer': 'select the rows whose name / designation record fuzzily matches to saturn machine pistol . take the year of intro record of this row . select the rows whose name / designation record fuzzily matches to serlea . take the year of intro record of this row . the second record is 5 years larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; name / designation ; saturn machine pistol } ; year of intro } ; hop { filter_eq { all_rows ; name / designation ; serlea } ; year of intro } } ; -5 years } = true | select the rows whose name / designation record fuzzily matches to saturn machine pistol . take the year of intro record of this row . select the rows whose name / designation record fuzzily matches to serlea . take the year of intro record of this row . the second record is 5 years larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'name / designation_8': 8, 'saturn machine pistol_9': 9, 'year of intro_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'name / designation_12': 12, 'serlea_13': 13, 'year of intro_14': 14, '-5 years_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'name / designation_8': 'name / designation', 'saturn machine pistol_9': 'saturn machine pistol', 'year of intro_10': 'year of intro', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'name / designation_12': 'name / designation', 'serlea_13': 'serlea', 'year of intro_14': 'year of intro', '-5 years_15': '-5 years'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'name / designation_8': [0], 'saturn machine pistol_9': [0], 'year of intro_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'name / designation_12': [1], 'serlea_13': [1], 'year of intro_14': [3], '-5 years_15': [5]} | ['name / designation', 'year of intro', 'country of origin', 'primary cartridge', 'major users'] | [['csmg', '2000', 'belgium', '9x19 mm parabellum 22 mm grenade', 'n / a'], ['flieger - doppelpistole 1919', '1919', 'switzerland', '7.65 x21 mm parabellum', 'n / a'], ['gordon close - support weapon system', '1972', 'australia', '9x19 mm parabellum', 'n / a'], ['itm model 4', '1990', 'united states', '9x19 mm parabellum', 'n / a'], ['neal submachine gun', '1948', 'united states', '22lr', 'n / a'], ['onorati smg', '1935', 'italy', '9x19 mm parabellum', 'n / a'], ['saturn machine pistol', '1985', 'colombia', '22lr', 'n / a'], ['serlea', '1990', 'lebanon', '9x19 mm parabellum', 'n / a']] |
2008 - 09 denver nuggets season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Denver_Nuggets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17355408-9.html.csv | comparative | during this period of the 2008-09 denver nuggets season , the denver nuggets had higher attendance in their april 2nd game than in their april 13th game . | {'row_1': '1', 'row_2': '6', 'col': '8', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'april 2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to april 2 .', 'tostr': 'filter_eq { all_rows ; date ; april 2 }'}, 'location attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; april 2 } ; location attendance }', 'tointer': 'select the rows whose date record fuzzily matches to april 2 . take the location attendance record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'april 13'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to april 13 .', 'tostr': 'filter_eq { all_rows ; date ; april 13 }'}, 'location attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; april 13 } ; location attendance }', 'tointer': 'select the rows whose date record fuzzily matches to april 13 . take the location attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; april 2 } ; location attendance } ; hop { filter_eq { all_rows ; date ; april 13 } ; location attendance } } = true', 'tointer': 'select the rows whose date record fuzzily matches to april 2 . take the location attendance record of this row . select the rows whose date record fuzzily matches to april 13 . take the location attendance record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; date ; april 2 } ; location attendance } ; hop { filter_eq { all_rows ; date ; april 13 } ; location attendance } } = true | select the rows whose date record fuzzily matches to april 2 . take the location attendance record of this row . select the rows whose date record fuzzily matches to april 13 . take the location attendance record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'april 2_8': 8, 'location attendance_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'april 13_12': 12, 'location attendance_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'april 2_8': 'april 2', 'location attendance_9': 'location attendance', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'april 13_12': 'april 13', 'location attendance_13': 'location attendance'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'april 2_8': [0], 'location attendance_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'april 13_12': [1], 'location attendance_13': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['76', 'april 2', 'utah', 'w 114 - 104 ( ot )', 'j r smith ( 28 )', 'chris andersen ( 10 )', 'j r smith ( 7 )', 'pepsi center 17969', '50 - 26'], ['77', 'april 4', 'la clippers', 'w 120 - 104 ( ot )', 'j r smith ( 34 )', 'chris andersen ( 8 )', 'chauncey billups ( 9 )', 'pepsi center 17880', '51 - 26'], ['78', 'april 5', 'minnesota', 'w 110 - 87 ( ot )', 'carmelo anthony ( 23 )', 'carmelo anthony , chris andersen ( 8 )', 'chauncey billups ( 7 )', 'target center 16839', '52 - 26'], ['79', 'april 8', 'oklahoma city', 'w 122 - 112 ( ot )', 'carmelo anthony ( 31 )', 'nenê ( 10 )', 'chauncey billups ( 9 )', 'pepsi center 16536', '53 - 26'], ['80', 'april 9', 'la lakers', 'l 102 - 116 ( ot )', 'carmelo anthony ( 23 )', 'nenê ( 10 )', 'chauncey billups ( 8 )', 'staples center 18997', '53 - 27'], ['81', 'april 13', 'sacramento', 'w 118 - 98 ( ot )', 'j r smith ( 45 )', 'chris andersen ( 10 )', 'carmelo anthony ( 9 )', 'pepsi center 15823', '54 - 27']] |
2002 world series | https://en.wikipedia.org/wiki/2002_World_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1103715-1.html.csv | aggregation | the average attendance at the 2002 world series games was a bit under 43,800 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '43800', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '43800', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '43800'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 43800 } = true', 'tointer': 'the average of the attendance record of all rows is 43800 .'} | round_eq { avg { all_rows ; attendance } ; 43800 } = true | the average of the attendance record of all rows is 43800 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '43800_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '43800_5': '43800'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '43800_5': [1]} | ['game', 'date', 'score', 'location', 'time', 'attendance'] | [['1', 'october 19', 'san francisco giants - 4 , anaheim angels - 3', 'edison international field of anaheim', '3:44', '44603'], ['2', 'october 20', 'san francisco giants - 10 , anaheim angels - 11', 'edison international field of anaheim', '3:57', '44584'], ['3', 'october 22', 'anaheim angels - 10 , san francisco giants - 4', 'pacific bell park', '3:37', '42707'], ['4', 'october 23', 'anaheim angels - 3 , san francisco giants - 4', 'pacific bell park', '3:02', '42703'], ['5', 'october 24', 'anaheim angels - 4 , san francisco giants - 16', 'pacific bell park', '3:53', '42713'], ['6', 'october 26', 'san francisco giants - 5 , anaheim angels - 6', 'edison international field of anaheim', '3:48', '44506'], ['7', 'october 27', 'san francisco giants - 1 , anaheim angels - 4', 'edison international field of anaheim', '3:16', '44598']] |
1990 indianapolis colts season | https://en.wikipedia.org/wiki/1990_Indianapolis_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14876127-2.html.csv | ordinal | the 1990 indianapolis colts game against the miami dolphins had the second highest attendance among games played at the hoosier dome . | {'scope': 'subset', 'row': '17', 'col': '7', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '6', 'criterion': 'equal', 'value': 'hoosier dome'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'hoosier dome'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; game site ; hoosier dome }', 'tointer': 'select the rows whose game site record fuzzily matches to hoosier dome .'}, 'attendance', '2'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; game site ; hoosier dome } ; attendance ; 2 }'}, 'opponent'], 'result': 'miami dolphins', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; game site ; hoosier dome } ; attendance ; 2 } ; opponent }'}, 'miami dolphins'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; game site ; hoosier dome } ; attendance ; 2 } ; opponent } ; miami dolphins } = true', 'tointer': 'select the rows whose game site record fuzzily matches to hoosier dome . select the row whose attendance record of these rows is 2nd maximum . the opponent record of this row is miami dolphins .'} | eq { hop { nth_argmax { filter_eq { all_rows ; game site ; hoosier dome } ; attendance ; 2 } ; opponent } ; miami dolphins } = true | select the rows whose game site record fuzzily matches to hoosier dome . select the row whose attendance record of these rows is 2nd maximum . the opponent record of this row is miami dolphins . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'game site_6': 6, 'hoosier dome_7': 7, 'attendance_8': 8, '2_9': 9, 'opponent_10': 10, 'miami dolphins_11': 11} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'game site_6': 'game site', 'hoosier dome_7': 'hoosier dome', 'attendance_8': 'attendance', '2_9': '2', 'opponent_10': 'opponent', 'miami dolphins_11': 'miami dolphins'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'game site_6': [0], 'hoosier dome_7': [0], 'attendance_8': [1], '2_9': [1], 'opponent_10': [2], 'miami dolphins_11': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 9 , 1990', 'buffalo bills', 'l 10 - 26', '0 - 1', 'ralph wilson stadium', '78899'], ['2', 'september 16 , 1990', 'new england patriots', 'l 14 - 16', '0 - 2', 'hoosier dome', '49256'], ['3', 'september 23 , 1990', 'houston oilers', 'l 10 - 24', '0 - 3', 'astrodome', '50093'], ['4', 'september 30 , 1990', 'philadelphia eagles', 'w 24 - 23', '1 - 3', 'veterans stadium', '62067'], ['5', 'october 7 , 1990', 'kansas city chiefs', 'w 23 - 19', '2 - 3', 'hoosier dome', '54950'], ['6', '-', '-', '-', '-', '-', ''], ['7', 'october 21 , 1990', 'denver broncos', 'l 17 - 24', '2 - 4', 'hoosier dome', '59850'], ['8', 'october 28 , 1990', 'miami dolphins', 'l 7 - 27', '2 - 5', 'hoosier dome', '59213'], ['9', 'november 5 , 1990', 'new york giants', 'l 7 - 24', '2 - 6', 'hoosier dome', '58688'], ['10', 'november 11 , 1990', 'new england patriots', 'w 13 - 10', '3 - 6', 'foxboro stadium', '28924'], ['11', 'november 18 , 1990', 'new york jets', 'w 17 - 14', '4 - 6', 'hoosier dome', '47283'], ['12', 'november 25 , 1990', 'cincinnati bengals', 'w 34 - 20', '5 - 6', 'riverfront stadium', '60051'], ['13', 'december 2 , 1990', 'phoenix cardinals', 'l 17 - 20', '5 - 7', 'sun devil stadium', '38043'], ['14', 'december 9 , 1990', 'buffalo bills', 'l 7 - 31', '5 - 8', 'hoosier dome', '53268'], ['15', 'december 16 , 1990', 'new york jets', 'w 29 - 21', '6 - 8', 'giants stadium', '41423'], ['16', 'december 22 , 1990', 'washington redskins', 'w 35 - 28', '7 - 8', 'hoosier dome', '58173'], ['17', 'december 30 , 1990', 'miami dolphins', 'l 17 - 23', '7 - 9', 'joe robbie stadium', '59547']] |
1984 seattle seahawks season | https://en.wikipedia.org/wiki/1984_Seattle_Seahawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13258851-2.html.csv | majority | the majority of games resulted in wins for the seahawks in the 1984 seattle seahawks season . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance'] | [['1', 'september 3 , 1984', 'cleveland browns', 'w 33 - 0', 'kingdome', '1 - 0', '59540'], ['2', 'september 9 , 1984', 'san diego chargers', 'w 31 - 17', 'kingdome', '2 - 0', '61314'], ['3', 'september 16 , 1984', 'new england patriots', 'l 23 - 38', 'sullivan stadium', '2 - 1', '43140'], ['4', 'september 23 , 1984', 'chicago bears', 'w 38 - 9', 'kingdome', '3 - 1', '61520'], ['5', 'september 30 , 1984', 'minnesota vikings', 'w 20 - 12', 'hubert h humphrey metrodome', '4 - 1', '57171'], ['6', 'october 7 , 1984', 'los angeles raiders', 'l 14 - 28', 'los angeles memorial coliseum', '4 - 2', '77904'], ['7', 'october 14 , 1984', 'buffalo bills', 'w 31 - 28', 'kingdome', '5 - 2', '59034'], ['8', 'october 21 , 1984', 'green bay packers', 'w 30 - 24', 'lambeau field', '6 - 2', '52286'], ['9', 'october 29 , 1984', 'san diego chargers', 'w 24 - 0', 'jack murphy stadium', '7 - 2', '53974'], ['10', 'november 4 , 1984', 'kansas city chiefs', 'w 45 - 0', 'kingdome', '8 - 2', '61396'], ['11', 'november 12 , 1984', 'los angeles raiders', 'w 17 - 14', 'kingdome', '9 - 2', '64001'], ['12', 'november 18 , 1984', 'cincinnati bengals', 'w 26 - 6', 'riverfront stadium', '10 - 2', '50280'], ['13', 'november 25 , 1984', 'denver broncos', 'w 27 - 24', 'mile high stadium', '11 - 2', '74922'], ['14', 'december 2 , 1984', 'detroit lions', 'w 38 - 17', 'kingdome', '12 - 2', '62441'], ['15', 'december 9 , 1984', 'kansas city chiefs', 'l 7 - 34', 'arrowhead stadium', '12 - 3', '34855']] |
united states presidential election in connecticut , 2004 | https://en.wikipedia.org/wiki/United_States_presidential_election_in_Connecticut%2C_2004 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1756284-1.html.csv | count | for the state of connecticut , in the 2004 presidential election , there were two counties where an " other " candidate received over 6000 votes . | {'scope': 'all', 'criterion': 'greater_than', 'value': '6000', 'result': '2', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'others', '6000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose others record is greater than 6000 .', 'tostr': 'filter_greater { all_rows ; others ; 6000 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; others ; 6000 } }', 'tointer': 'select the rows whose others record is greater than 6000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; others ; 6000 } } ; 2 } = true', 'tointer': 'select the rows whose others record is greater than 6000 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; others ; 6000 } } ; 2 } = true | select the rows whose others record is greater than 6000 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'others_5': 5, '6000_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'others_5': 'others', '6000_6': '6000', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'others_5': [0], '6000_6': [0], '2_7': [2]} | ['county', 'kerry %', 'kerry', 'bush %', 'bush', 'others %', 'others', '2000 result'] | [['hartford', '58.7 %', '229902', '39.5 %', '154919', '1.8 %', '6987', '1.5'], ['middlesex', '56.3 %', '47292', '42.0 %', '35252', '1.7 %', '1440', '+ 1.4'], ['new london', '55.8 %', '66062', '42.2 %', '49931', '2.0 %', '2367', '+ 0.4'], ['tolland', '54.6 %', '39146', '43.6 %', '31245', '1.9 %', '1338', '+ 1.6'], ['new haven', '54.3 %', '199060', '43.8 %', '160390', '1.9 %', '6942', '- 3.7'], ['windham', '52.1 %', '25477', '45.7 %', '22324', '2.2 %', '1060', '+ 2.5'], ['fairfield', '51.4 %', '205902', '47.3 %', '189605', '1.4 %', '5460', '- 0.9']] |
swimming at the 2000 summer olympics - men 's 100 metre butterfly | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Men%27s_100_metre_butterfly | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446342-5.html.csv | superlative | the competitor from australia has the shortest time in the men 's 100 metre butterfly during the 2000 summer olympics . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'nationality'], 'result': 'australia', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; nationality }'}, 'australia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; time } ; nationality } ; australia } = true', 'tointer': 'select the row whose time record of all rows is minimum . the nationality record of this row is australia .'} | eq { hop { argmin { all_rows ; time } ; nationality } ; australia } = true | select the row whose time record of all rows is minimum . the nationality record of this row is australia . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'nationality_6': 6, 'australia_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'nationality_6': 'nationality', 'australia_7': 'australia'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'nationality_6': [1], 'australia_7': [2]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'michael klim', 'australia', '52.63'], ['2', '2', 'ian crocker', 'united states', '52.82'], ['3', '3', 'lars frölander', 'sweden', '52.84'], ['4', '5', 'mike mintenko', 'canada', '53.00'], ['5', '1', 'thomas rupprath', 'germany', '53.18'], ['6', '6', 'anatoly polyakov', 'russia', '53.32'], ['7', '7', 'franck esposito', 'france', '53.38'], ['8', '8', 'jere hård', 'finland', '53.65']] |
colorado mountain passes | https://en.wikipedia.org/wiki/Colorado_mountain_passes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14926835-2.html.csv | majority | the majority of the colorado mountain passes have an asphalt surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'asphalt', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'asphalt'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to asphalt .', 'tostr': 'most_eq { all_rows ; surface ; asphalt } = true'} | most_eq { all_rows ; surface ; asphalt } = true | for the surface records of all rows , most of them fuzzily match to asphalt . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'asphalt_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'asphalt_4': 'asphalt'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'asphalt_4': [0]} | ['rank', 'highway', 'elevation', 'surface', 'route'] | [['1', 'mount evans scenic byway', '14160 feet 4316 m', 'asphalt', '005'], ['2', 'pikes peak highway', '14115 feet 4302 m', 'asphalt', '999'], ['3', 'trail ridge road', '12183 feet 3713 m', 'asphalt', '034'], ['4', 'eisenhower tunnel', '11158 feet 3401 m', 'concrete', '070'], ['5', 'warrior mountain summit', '11140 feet 3395 m', 'asphalt', '103'], ['6', 'grand mesa summit', '10839 feet 3304 m', 'asphalt', '065'], ['7', 'battle mountain summit', '0 9267 feet 2825 m', 'asphalt', '024'], ['8', 'black mesa summit', '0 9121 feet 2780 m', 'asphalt', '092'], ['9', 'wondervu hill', '0 8660 feet 2640 m', 'asphalt', '072']] |
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