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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... | 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 +... |
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 -... |
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 fuz... | 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': 'privat... | {'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 (... |
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 }'}, 'sta... | 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 ... |
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 ' }", 'to... | 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 -... |
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 }'},... | 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 1... |
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', 'm... |
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 }'}], 're... | 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', '... |
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,... | 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... |
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... | 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 j... |
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 }'}, 'en... | 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', 'curre... | {'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'], ['li... |
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 .'},... | 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 du... |
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 }'}], 're... | 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 dolp... |
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 }'}, 'ana... | 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... |
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 .'}, 'st... | 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 r... |
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 | 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', ... |
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 mins... | 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']... |
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': 'selec... | 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', '... |
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 .'}, 'capac... | 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 nefteperer... |
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', 'h... |
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_row... | 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', ... | {'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'... | ['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... |
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'... |
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', 'p... |
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'], ['... |
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 fer... |
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 }'}], ... | 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'], ['aus... |
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 )... | 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', '... |
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, 'in... | 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'], ... |
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, 'tos... | 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'... | {'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', 'm... |
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 ... | 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... |
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,... | 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'... | {'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', '... |
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 { filte... | 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', 'e... |
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': ... | 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',... |
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_row... | 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',... |
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 %',... |
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 .'}, ... | 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 - ... |
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': T... | 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... | {'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], 'sheffiel... | ['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', 'plymout... |
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'], 're... | 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', ... |
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 .'... | 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', 'philadel... |
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... | 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... | {'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... |
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... |
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 attenda... | 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': 'nov... | {'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',... |
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 u... | 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 / bapt... |
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... | 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 mona... |
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... | 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 - ... |
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 } ; arca... | 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 } ; sp... | 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... | {'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': 'sta... | {'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': ... | ['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 ... |
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'],... | 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 - ... |
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': 'coun... | 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 gmb... |
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 }'}], ... | 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', 'cab... |
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', '... |
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... | 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... |
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 }'}, ... | 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... | 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'], [... |
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... | 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', '... | {'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'], [... |
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... | 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... |
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 s... | 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 ce... |
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'], '... | 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 ha... |
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': No... | 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',... | {'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... | 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... | {'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', ... |
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 } ; distric... | 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 % jo... |
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']... | 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... | {'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', '560... |
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', '... |
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 }'}... | 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', '... | {'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', '... |
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 {... | 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 20... |
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', '... |
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': 'onl... | 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 sea... |
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 }... | 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 p... |
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 ... | 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... |
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 }'}... | 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 -... |
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': ... | 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', '1... |
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', ... | 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'... |
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'... |
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 {... | 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... |
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... | 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_h... | {'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... |
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']... | 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... |
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,... | 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 f... | {'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 -']... |
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... | 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',... |
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 ; universi... | 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', 'i... | {'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 ... |
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 ... | 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', 'europe... |
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... | 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... |
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... | 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', '243.3... |
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... | 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 }'}, 'don... | 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... |
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': '... | 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', '... |
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, 'tos... | 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', '2... |
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 ... | 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 se... | 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': 'fil... | {'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 (ce... | ['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 dzhordzh... |
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 }'... | 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', 'everto... |
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 | 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 }'... | 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', 'epi... |
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 }'}], 'resul... | 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'], ... |
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'... | 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.... |
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': 'filte... | 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'... | {'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... | {'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... | ['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 parabellu... |
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,... | 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': '... | {'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 ... |
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... | 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 gian... |
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... | 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 do... | {'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 , 199... |
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', ... |
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 { fi... | 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... |
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': ... | 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', 'franc... |
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 fee... |
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