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1998 - 99 canadian network television schedule | https://en.wikipedia.org/wiki/1998%E2%80%9399_Canadian_network_television_schedule | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15184672-4.html.csv | unique | jeopardy! was only on at 7:30 on one channel . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'jeopardy!', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '7:30', 'jeopardy!'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 7:30 record fuzzily matches to jeopardy! .', 'tostr': 'filter_eq { all_rows ; 7:30 ; jeopardy! }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 7:30 ; jeopardy! } } = true', 'tointer': 'select the rows whose 7:30 record fuzzily matches to jeopardy! . there is only one such row in the table .'} | only { filter_eq { all_rows ; 7:30 ; jeopardy! } } = true | select the rows whose 7:30 record fuzzily matches to jeopardy! . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, '7:30_4': 4, 'jeopardy!_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', '7:30_4': '7:30', 'jeopardy!_5': 'jeopardy!'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], '7:30_4': [0], 'jeopardy!_5': [0]} | ['7:00', '7:30', '8:00', '8:30', '9:00', '9:30', '10:00', '10:30'] | [['on the road again', 'country canada', 'this hour has 22 minutes', 'comics !', "da vinci 's inquest", "da vinci 's inquest", 'the national', 'the national'], ['wheel of fortune', 'jeopardy!', 'due south', 'due south', 'the drew carey show', 'the secret lives of men', 'law & order', 'law & order'], ['entertainment tonight', 'clueless', 'beverly hills , 90210', 'beverly hills , 90210', 'party of five', 'party of five', 'chicago hope', 'chicago hope'], ['virginie', 'caserne 24', 'various programs', 'various programs', 'various programs', 'various programs', 'le téléjournal / le point', 'le téléjournal / le point'], ["la poule aux oeufs d'or", 'sportive / caméra choc', 'le retour', 'le retour', 'sauve qui peut', 'sauve qui peut', 'news', 'le poing j'], ['les simpson', 'movies', 'movies', 'movies', 'movies', 'le grand journal', 'fin du monde', '110 pour cent']] |
1962 baltimore colts season | https://en.wikipedia.org/wiki/1962_Baltimore_Colts_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14984078-1.html.csv | ordinal | the game on november 18 , 1962 had the 2nd lowest attendance of all games during the baltimore colts season . | {'row': '10', 'col': '7', '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', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; attendance ; 2 }'}, 'date'], 'result': 'november 18 , 1962', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; attendance ; 2 } ; date }'}, 'november 18 , 1962'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; attendance ; 2 } ; date } ; november 18 , 1962 } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd minimum . the date record of this row is november 18 , 1962 .'} | eq { hop { nth_argmin { all_rows ; attendance ; 2 } ; date } ; november 18 , 1962 } = true | select the row whose attendance record of all rows is 2nd minimum . the date record of this row is november 18 , 1962 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, 'november 18 , 1962_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', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', 'november 18 , 1962_8': 'november 18 , 1962'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], 'november 18 , 1962_8': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 16 , 1962', 'los angeles rams', 'w 30 - 27', '1 - 0', 'memorial stadium', '54796'], ['2', 'september 23 , 1962', 'minnesota vikings', 'w 34 - 7', '2 - 0', 'metropolitan stadium', '30787'], ['3', 'september 30 , 1962', 'detroit lions', 'l 20 - 29', '2 - 1', 'memorial stadium', '57966'], ['4', 'october 7 , 1962', 'san francisco 49ers', 'l 13 - 21', '2 - 2', 'memorial stadium', '54158'], ['5', 'october 14 , 1962', 'cleveland browns', 'w 36 - 14', '3 - 2', 'cleveland municipal stadium', '80132'], ['6', 'october 21 , 1962', 'chicago bears', 'l 15 - 35', '3 - 3', 'wrigley field', '49066'], ['7', 'october 28 , 1962', 'green bay packers', 'l 6 - 17', '3 - 4', 'memorial stadium', '57966'], ['8', 'november 4 , 1962', 'san francisco 49ers', 'w 22 - 3', '4 - 4', 'kezar stadium', '44875'], ['9', 'november 11 , 1962', 'los angeles rams', 'w 14 - 2', '5 - 4', 'los angeles memorial coliseum', '39502'], ['10', 'november 18 , 1962', 'green bay packers', 'l 13 - 17', '5 - 5', 'lambeau field', '38669'], ['11', 'november 25 , 1962', 'chicago bears', 'l 0 - 57', '5 - 6', 'memorial stadium', '56164'], ['12', 'december 2 , 1962', 'detroit lions', 'l 14 - 21', '5 - 7', 'tiger stadium', '53012'], ['13', 'december 8 , 1962', 'washington redskins', 'w 34 - 21', '6 - 7', 'memorial stadium', '56964'], ['14', 'december 16 , 1962', 'minnesota vikings', 'w 42 - 17', '7 - 7', 'memorial stadium', '53645']] |
cbf - fm | https://en.wikipedia.org/wiki/CBF-FM | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1873415-1.html.csv | aggregation | the city of license had a total power average of 8260 across all frequencies . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '8260', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'power'], 'result': '8260', 'ind': 0, 'tostr': 'avg { all_rows ; power }'}, '8260'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; power } ; 8260 } = true', 'tointer': 'the average of the power record of all rows is 8260 .'} | round_eq { avg { all_rows ; power } ; 8260 } = true | the average of the power record of all rows is 8260 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'power_4': 4, '8260_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'power_4': 'power', '8260_5': '8260'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'power_4': [0], '8260_5': [1]} | ['city of license', 'identifier', 'frequency', 'power', 'class', 'recnet'] | [["l'annonciation ( riviã ¨ re - rouge )", 'cbf - fm - 15', '88.3 fm', '4600 s watt', 'b', 'query'], ['mont - laurier', 'cbf - fm - 9', '91.9 fm', '38000 watts', 'b', 'query'], ['radisson', 'cbf - fm - 7', '100.1 fm', '199 watts', 'a', 'query'], ['saint - donat ( matawinie rcm )', 'cbf - fm - 20', '89.7', '5460 watts', 'b', 'query'], ['saint - jovite ( mont - tremblant )', 'cbf - fm - 14', '95.5 fm', '835 watts', 'a', 'query'], ['saint - michel - des - saints', 'cbf - fm - 13', '90.9 fm', '466 watts', 'a', 'query']] |
2010 fedex cup playoffs | https://en.wikipedia.org/wiki/2010_FedEx_Cup_Playoffs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28498999-3.html.csv | count | four of the players in the 2010 fedex cup playoffs were -9 under par . | {'scope': 'all', 'criterion': 'equal', 'value': '- 9', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'to par', '- 9'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose to par record fuzzily matches to - 9 .', 'tostr': 'filter_eq { all_rows ; to par ; - 9 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; to par ; - 9 } }', 'tointer': 'select the rows whose to par record fuzzily matches to - 9 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; to par ; - 9 } } ; 4 } = true', 'tointer': 'select the rows whose to par record fuzzily matches to - 9 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; to par ; - 9 } } ; 4 } = true | select the rows whose to par record fuzzily matches to - 9 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'to par_5': 5, '- 9_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'to par_5': 'to par', '- 9_6': '- 9', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'to par_5': [0], '- 9_6': [0], '4_7': [2]} | ['', 'player', 'country', 'score', 'to par', 'winnings', 'after', 'before'] | [['1', 'matt kuchar', 'united states', '68 + 69 + 69 + 66 = 272', '- 12', '1350000', '1', '9'], ['2', 'martin laird', 'scotland', '69 + 67 + 65 + 71 = 272', '- 12', '810000', '3', '95'], ['t3', 'kevin streelman', 'united states', '72 + 63 + 71 + 68 = 274', '- 10', '435000', '18', '102'], ['t3', 'steve stricker', 'united states', '70 + 70 + 68 + 66 = 274', '- 10', '435000', '2', '2'], ['t5', 'jason day', 'australia', '67 + 67 + 70 + 71 = 275', '- 9', '263438', '14', '28'], ['t5', 'ryan palmer', 'united states', '66 + 74 + 66 + 69 = 275', '- 9', '263438', '13', '23'], ['t5', 'rory sabbatini', 'south africa', '68 + 74 + 69 + 64 = 275', '- 9', '263438', '33', '60'], ['t5', 'vaughn taylor', 'united states', '65 + 70 + 71 + 69 = 275', '- 9', '263438', '21', '38'], ['t9', 'dustin johnson', 'united states', '71 + 69 + 64 + 72 = 276', '- 8', '202500', '6', '11'], ['t9', 'adam scott', 'australia', '66 + 71 + 68 + 71 = 276', '- 8', '202500', '19', '32']] |
1981 formula one season | https://en.wikipedia.org/wiki/1981_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1140077-2.html.csv | count | alain prost had a total of two pole positions in the 1981 formula one season . | {'scope': 'all', 'criterion': 'equal', 'value': 'alain prost', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pole position', 'alain prost'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pole position record fuzzily matches to alain prost .', 'tostr': 'filter_eq { all_rows ; pole position ; alain prost }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; pole position ; alain prost } }', 'tointer': 'select the rows whose pole position record fuzzily matches to alain prost . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; pole position ; alain prost } } ; 2 } = true', 'tointer': 'select the rows whose pole position record fuzzily matches to alain prost . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; pole position ; alain prost } } ; 2 } = true | select the rows whose pole position record fuzzily matches to alain prost . 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, 'pole position_5': 5, 'alain prost_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', 'pole position_5': 'pole position', 'alain prost_6': 'alain prost', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'pole position_5': [0], 'alain prost_6': [0], '2_7': [2]} | ['rnd', 'race', 'date', 'location', 'pole position', 'fastest lap', 'race winner', 'constructor', 'report'] | [['1', 'united states grand prix west', '15 march', 'long beach', 'riccardo patrese', 'alan jones', 'alan jones', 'williams - ford', 'report'], ['2', 'brazilian grand prix', '29 march', 'jacarepaguá', 'nelson piquet', 'marc surer', 'carlos reutemann', 'williams - ford', 'report'], ['3', 'argentine grand prix', '12 april', 'buenos aires', 'nelson piquet', 'nelson piquet', 'nelson piquet', 'brabham - ford', 'report'], ['4', 'san marino grand prix', '3 may', 'imola', 'gilles villeneuve', 'gilles villeneuve', 'nelson piquet', 'brabham - ford', 'report'], ['5', 'belgian grand prix', '17 may', 'zolder', 'carlos reutemann', 'carlos reutemann', 'carlos reutemann', 'williams - ford', 'report'], ['6', 'monaco grand prix', '31 may', 'monaco', 'nelson piquet', 'alan jones', 'gilles villeneuve', 'ferrari', 'report'], ['7', 'spanish grand prix', '21 june', 'jarama', 'jacques laffite', 'alan jones', 'gilles villeneuve', 'ferrari', 'report'], ['8', 'french grand prix', '5 july', 'dijon - prenois', 'rené arnoux', 'alain prost', 'alain prost', 'renault', 'report'], ['9', 'british grand prix', '18 july', 'silverstone', 'rené arnoux', 'rené arnoux', 'john watson', 'mclaren - ford', 'report'], ['10', 'german grand prix', '2 august', 'hockenheimring', 'alain prost', 'alan jones', 'nelson piquet', 'brabham - ford', 'report'], ['11', 'austrian grand prix', '16 august', 'österreichring', 'rené arnoux', 'jacques laffite', 'jacques laffite', 'ligier - matra', 'report'], ['12', 'dutch grand prix', '30 august', 'zandvoort', 'alain prost', 'alan jones', 'alain prost', 'renault', 'report'], ['13', 'italian grand prix', '13 september', 'monza', 'rené arnoux', 'carlos reutemann', 'alain prost', 'renault', 'report'], ['14', 'canadian grand prix', '27 september', 'île notre - dame', 'nelson piquet', 'john watson', 'jacques laffite', 'ligier - matra', 'report']] |
list of collaborative software | https://en.wikipedia.org/wiki/List_of_collaborative_software | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1779657-3.html.csv | count | 11 of the collaborative software programs do not have business intelligence . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'no', 'result': '11', 'col': '14', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'business intelligence', 'no'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose business intelligence record fuzzily matches to no .', 'tostr': 'filter_eq { all_rows ; business intelligence ; no }'}], 'result': '11', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; business intelligence ; no } }', 'tointer': 'select the rows whose business intelligence record fuzzily matches to no . the number of such rows is 11 .'}, '11'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; business intelligence ; no } } ; 11 } = true', 'tointer': 'select the rows whose business intelligence record fuzzily matches to no . the number of such rows is 11 .'} | eq { count { filter_eq { all_rows ; business intelligence ; no } } ; 11 } = true | select the rows whose business intelligence record fuzzily matches to no . the number of such rows is 11 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'business intelligence_5': 5, 'no_6': 6, '11_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'business intelligence_5': 'business intelligence', 'no_6': 'no', '11_7': '11'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'business intelligence_5': [0], 'no_6': [0], '11_7': [2]} | ['name', 'wikis', 'web publishing', 'calendaring software', 'project management', 'workflow system', 'document management', 'list management', 'xml forms management and workflow', 'discussion', 'blogs', 'surveys', 'time tracking', 'business intelligence', 'charting', 'bookmarking , tagging , rating and comments', 'social software', 'enterprise search', 'office suite'] | [['google apps', 'yes , sites', 'yes , sites', 'yes', 'no', 'no', 'yes , simple', 'no', 'yes , simple', 'yes', 'yes', 'yes', 'no', 'no', 'yes', 'yes', 'yes', 'yes', 'yes'], ['ibm connections', 'yes', 'yes', 'yes', 'yes , simple', 'yes', 'yes , simple', 'no', 'no', 'yes', 'yes', 'no', 'no', 'no', 'no', 'yes', 'yes', 'no', 'no'], ['ibm lotus domino', 'no', 'no', 'yes', 'yes , simple', 'yes', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no'], ['ibm quickr', 'yes', 'yes', 'yes', 'yes , simple', 'yes', 'yes , simple', 'yes', 'no', 'yes', 'yes', 'no', 'yes', 'no', 'no', 'no', 'no', 'no', 'no'], ['kune', 'yes', 'in development', 'yes', 'yes , simple', 'no', 'yes', 'yes , wave - based', 'no', 'yes', 'yes', 'yes ( gadget )', 'no', 'no', 'no', 'in development', 'yes', 'no', 'real - time collaborative documents'], ['microsoft exchange server', 'no', 'no', 'yes', 'yes , simple', 'yes', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'no'], ['microsoft office', 'no', 'no', 'no', 'no', 'no', 'yes , simple', 'no', 'yes', 'no', 'no', 'no', 'no', 'no', 'yes', 'no', 'no', 'no', 'yes , desktop'], ['microsoft project server', 'no', 'no', 'yes', 'yes', 'no', 'no', 'no', 'no', 'no', 'no', 'no', 'yes', 'no', 'no', 'no', 'no', 'no', 'no'], ['microsoft sharepoint', 'yes', 'yes', 'yes', 'yes , simple', 'yes', 'yes', 'yes', 'yes , microsoft infopath', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes , web'], ['microsoft team foundation server', 'no', 'no', 'yes', 'yes', 'yes', 'yes', 'no', 'no', 'yes', 'no', 'no', 'yes', 'no', 'yes', 'yes', 'no', 'yes', 'no'], ['mindview', 'no', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'no', 'yes', 'yes', 'yes', 'no', 'no', 'no', 'ms office interface'], ['traction teampage', 'yes', 'yes', 'yes', 'yes', 'yes ( basic )', 'yes', 'no', 'no', 'yes', 'yes', 'no', 'yes', 'yes', 'yes , metrics', 'yes', 'yes', 'yes', 'no'], ['tiki wiki cms groupware', 'yes', 'yes', 'yes', 'yes , simple', 'yes', 'yes', 'yes ( newsletter )', 'yes', 'yes', 'yes', 'yes', 'yes', 'no', 'yes ( basic )', 'yes', 'yes', 'yes', 'yes , web'], ['wrike', 'no', 'no', 'yes', 'yes', 'yes', 'yes', 'no', 'no', 'yes', 'no', 'no', 'yes', 'no', 'yes', 'yes', 'yes', 'no', 'yes , web'], ['name', 'wikis', 'web publishing', 'calendaring software', 'project management', 'workflow system', 'document management', 'list management', 'xml forms management and workflow', 'discussion', 'blogs', 'surveys', 'time tracking', 'business intelligence', 'charting', 'bookmarking , tagging , rating and comments', 'social software', 'enterprise search', 'office suite']] |
1952 vfl season | https://en.wikipedia.org/wiki/1952_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10750694-12.html.csv | unique | in the 1952 vfl season , the only game that took place at lake oval was when south melbourne was the home team . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'lake oval', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'lake oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to lake oval .', 'tostr': 'filter_eq { all_rows ; venue ; lake oval }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; venue ; lake oval } }', 'tointer': 'select the rows whose venue record fuzzily matches to lake oval . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'lake oval'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to lake oval .', 'tostr': 'filter_eq { all_rows ; venue ; lake oval }'}, 'home team'], 'result': 'south melbourne', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; lake oval } ; home team }'}, 'south melbourne'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; venue ; lake oval } ; home team } ; south melbourne }', 'tointer': 'the home team record of this unqiue row is south melbourne .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; venue ; lake oval } } ; eq { hop { filter_eq { all_rows ; venue ; lake oval } ; home team } ; south melbourne } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to lake oval . there is only one such row in the table . the home team record of this unqiue row is south melbourne .'} | and { only { filter_eq { all_rows ; venue ; lake oval } } ; eq { hop { filter_eq { all_rows ; venue ; lake oval } ; home team } ; south melbourne } } = true | select the rows whose venue record fuzzily matches to lake oval . there is only one such row in the table . the home team record of this unqiue row is south melbourne . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'lake oval_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'home team_9': 9, 'south melbourne_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'lake oval_8': 'lake oval', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'home team_9': 'home team', 'south melbourne_10': 'south melbourne'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'venue_7': [0], 'lake oval_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'home team_9': [2], 'south melbourne_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '10.17 ( 77 )', 'st kilda', '6.8 ( 44 )', 'punt road oval', '9000', '12 july 1952'], ['footscray', '4.11 ( 35 )', 'hawthorn', '9.4 ( 58 )', 'western oval', '12218', '12 july 1952'], ['fitzroy', '13.11 ( 89 )', 'north melbourne', '10.11 ( 71 )', 'brunswick street oval', '10500', '12 july 1952'], ['carlton', '6.14 ( 50 )', 'melbourne', '6.14 ( 50 )', 'princes park', '24839', '12 july 1952'], ['south melbourne', '8.12 ( 60 )', 'essendon', '9.15 ( 69 )', 'lake oval', '27000', '12 july 1952'], ['geelong', '9.8 ( 62 )', 'collingwood', '4.9 ( 33 )', 'kardinia park', '36145', '12 july 1952']] |
marta domachowska | https://en.wikipedia.org/wiki/Marta_Domachowska | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15746889-4.html.csv | majority | most of marta domachowska 's tournaments took place on a hard surface . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'hard', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': True, 'ind': 0, 'tointer': 'for the surface records of all rows , most of them fuzzily match to hard .', 'tostr': 'most_eq { all_rows ; surface ; hard } = true'} | most_eq { all_rows ; surface ; hard } = true | for the surface records of all rows , most of them fuzzily match to hard . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'surface_3': 3, 'hard_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'surface_3': 'surface', 'hard_4': 'hard'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'surface_3': [0], 'hard_4': [0]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponent in final', 'score in final'] | [['runner - up', 'january 31 , 2005', 'pattaya city , thailand', 'hard', 'silvija talaja', 'rosa maría andrés rodríguez andreea vanc', '6 - 3 , 6 - 1'], ['runner - up', 'may 21 , 2005', 'strasbourg , france', 'clay', 'marlene weingärtner', 'marion bartoli anna - lena grönefeld', '6 - 3 , 6 - 2'], ['winner', 'january 13 , 2006', 'canberra , australia', 'hard', 'roberta vinci', 'claire curran liga dekmeijere', '7 - 6 ( 5 ) , 6 - 3'], ['runner - up', 'july 23 , 2006', 'cincinnati , united states', 'hard', 'sania mirza', 'gisela dulko maria elena camerin', '6 - 4 , 3 - 6 , 6 - 2'], ['runner - up', 'september 14 , 2008', 'bali , indonesia', 'hard', 'nadia petrova', 'hsieh su - wei peng shuai', '6 - 7 ( 4 ) , 7 - 6 ( 3 ) ,']] |
ray sefo | https://en.wikipedia.org/wiki/Ray_Sefo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1533651-2.html.csv | unique | ray sefo only had 1 fight that went to decision . | {'scope': 'all', 'row': '5', 'col': '5', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'decision', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'decision'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to decision .', 'tostr': 'filter_eq { all_rows ; method ; decision }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; method ; decision } } = true', 'tointer': 'select the rows whose method record fuzzily matches to decision . there is only one such row in the table .'} | only { filter_eq { all_rows ; method ; decision } } = true | select the rows whose method record fuzzily matches to decision . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'method_4': 4, 'decision_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'method_4': 'method', 'decision_5': 'decision'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'method_4': [0], 'decision_5': [0]} | ['date', 'result', 'opponent', 'location', 'method', 'round', 'record'] | [['2001 - 09 - 02', 'loss', 'chester hughes', 'elgin , illinois , usa', 'ko', '1', '5 - 1 - 0'], ['2001 - 06 - 03', 'win', 'joe lenhart', 'elgin , illinois , usa', 'tko', '1', '5 - 0 - 0'], ['2001 - 02 - 11', 'win', 'steve griffin', 'elgin , illinois , usa', 'tko', '1', '4 - 0 - 0'], ['1996 - 10 - 05', 'win', 'nicky faamata', 'auckland , new zealand', 'tko', '3', '3 - 0 - 0'], ['1995 - 03 - 16', 'win', 'paul baker', 'auckland , new zealand', 'decision', '4', '2 - 0 - 0'], ['1994 - 11 - 24', 'win', 'alex katu', 'auckland , new zealand', 'tko', '1', '1 - 0 - 0']] |
miguel amaral | https://en.wikipedia.org/wiki/Miguel_Amaral | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1616765-1.html.csv | majority | most of the 24 hours of le mans races that miguel amaral participated in , he did not finish . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'dnf', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'pos', 'dnf'], 'result': True, 'ind': 0, 'tointer': 'for the pos records of all rows , most of them fuzzily match to dnf .', 'tostr': 'most_eq { all_rows ; pos ; dnf } = true'} | most_eq { all_rows ; pos ; dnf } = true | for the pos records of all rows , most of them fuzzily match to dnf . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'pos_3': 3, 'dnf_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'pos_3': 'pos', 'dnf_4': 'dnf'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'pos_3': [0], 'dnf_4': [0]} | ['year', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2006', 'warren hughes miguel ángel de castro', 'lmp2', '196', 'dnf', 'dnf'], ['2007', 'warren hughes miguel ángel de castro', 'lmp2', '137', 'dnf', 'dnf'], ['2008', 'olivier pla guy smith', 'lmp2', '325', '20th', '4th'], ['2009', 'olivier pla guy smith', 'lmp2', '46', 'dnf', 'dnf'], ['2010', 'olivier pla warren hughes', 'lmp2', '318', '20th', '7th'], ['2011', 'olivier pla warren hughes', 'lmp1', '48', 'dnf', 'dnf']] |
justin lee collins : good times | https://en.wikipedia.org/wiki/Justin_Lee_Collins%3A_Good_Times | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26733129-1.html.csv | comparative | jermaine jackson appeared on the three dart challenge after meat loaf did . | {'row_1': '5', 'row_2': '4', 'col': '1', 'col_other': '4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'three darts challenge', 'jermaine jackson'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose three darts challenge record fuzzily matches to jermaine jackson .', 'tostr': 'filter_eq { all_rows ; three darts challenge ; jermaine jackson }'}, 'episode number'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; three darts challenge ; jermaine jackson } ; episode number }', 'tointer': 'select the rows whose three darts challenge record fuzzily matches to jermaine jackson . take the episode number record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'three darts challenge', 'meat loaf'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose three darts challenge record fuzzily matches to meat loaf .', 'tostr': 'filter_eq { all_rows ; three darts challenge ; meat loaf }'}, 'episode number'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; three darts challenge ; meat loaf } ; episode number }', 'tointer': 'select the rows whose three darts challenge record fuzzily matches to meat loaf . take the episode number record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; three darts challenge ; jermaine jackson } ; episode number } ; hop { filter_eq { all_rows ; three darts challenge ; meat loaf } ; episode number } } = true', 'tointer': 'select the rows whose three darts challenge record fuzzily matches to jermaine jackson . take the episode number record of this row . select the rows whose three darts challenge record fuzzily matches to meat loaf . take the episode number record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; three darts challenge ; jermaine jackson } ; episode number } ; hop { filter_eq { all_rows ; three darts challenge ; meat loaf } ; episode number } } = true | select the rows whose three darts challenge record fuzzily matches to jermaine jackson . take the episode number record of this row . select the rows whose three darts challenge record fuzzily matches to meat loaf . take the episode number 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, 'three darts challenge_7': 7, 'jermaine jackson_8': 8, 'episode number_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'three darts challenge_11': 11, 'meat loaf_12': 12, 'episode number_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', 'three darts challenge_7': 'three darts challenge', 'jermaine jackson_8': 'jermaine jackson', 'episode number_9': 'episode number', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'three darts challenge_11': 'three darts challenge', 'meat loaf_12': 'meat loaf', 'episode number_13': 'episode number'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'three darts challenge_7': [0], 'jermaine jackson_8': [0], 'episode number_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'three darts challenge_11': [1], 'meat loaf_12': [1], 'episode number_13': [3]} | ['episode number', 'air date', 'guests', 'three darts challenge', 'musical performance'] | [['2', '5 april 2010', 'aaron johnson , patsy palmer , sharleen spiteri', 'joanna lumley', 'sharleen spiteri - xandu'], ['3', '12 april 2010', 'katy brand , james corden , paloma faith', 'ewan mcgregor', 'paloma faith - upside down'], ['7', '10 may 2010', 'gok wan , yvette fielding , alphabeat', 'sharon osbourne', 'alphabeat - dj ( i could be dancing )'], ['8', '17 may 2010', 'matthew horne , rihanna , the cast of jersey boys', 'meat loaf', 'the cast of jersey boys'], ['9', '7 june 2010', 'joe swash , arlene phillips , mary j blige', 'jermaine jackson', 'mary j blige - each tear']] |
jak oni śpiewają | https://en.wikipedia.org/wiki/Jak_oni_%C5%9Bpiewaj%C4%85 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11680517-4.html.csv | majority | most of the seasons of jak oni śpiewają had a total of 13 weeks . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '13', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'of weeks', '13'], 'result': True, 'ind': 0, 'tointer': 'for the of weeks records of all rows , most of them are equal to 13 .', 'tostr': 'most_eq { all_rows ; of weeks ; 13 } = true'} | most_eq { all_rows ; of weeks ; 13 } = true | for the of weeks records of all rows , most of them are equal to 13 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'of weeks_3': 3, '13_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'of weeks_3': 'of weeks', '13_4': '13'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'of weeks_3': [0], '13_4': [0]} | ['season', 'of stars', 'of weeks', 'season premiere date', 'season finale date', 'winner', 'runner - up', 'third place'] | [['1 - spring 2007', '13', '13', 'march 16 , 2007', 'june 2 , 2007', 'agnieszka włodarczyk', 'natasza urbańska', 'robert moskwa'], ['2 - autumn 2007', '13', '13', 'september 8 , 2007', 'december 15 , 2007', 'joanna liszowska', 'piotr polk', 'patricia kazadi'], ['3 - spring 2008', '13', '13', 'march 8 , 2008', 'may 31 , 2008', 'krzysztof respondek', 'joanna jabłczyńska', 'kacper kuszewski'], ['4 - autumn 2008', '15', '13', 'september 6 , 2008', 'december 6 , 2008', 'artur chamski', 'karolina nowakowska', 'aleksandra szwed'], ['5 - spring 2009', '14', '12', 'march 7 , 2009', 'may 23 , 2009', 'laura samojłowicz', 'maciej jachowski', 'robert kudelski'], ['6 - autumn 2009', '11', '10', 'september 12 , 2009', 'november 23 , 2009', 'krzysztof respondek', 'agnieszka włodarczyk', 'artur chamski']] |
rustavi 2 | https://en.wikipedia.org/wiki/Rustavi_2 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1544974-1.html.csv | unique | for rustavi 2 , in mexico , the only time the series premiere was on september 2 was when the telenovela was mentir para vivir . | {'scope': 'subset', 'row': '1', 'col': '4', 'col_other': '2', 'criterion': 'equal', 'value': 'september 2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'mentir para vivir'}} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'telenovela', 'mentir para vivir'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; telenovela ; mentir para vivir }', 'tointer': 'select the rows whose telenovela record fuzzily matches to mentir para vivir .'}, 'series premiere', 'september 2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose telenovela record fuzzily matches to mentir para vivir . among these rows , select the rows whose series premiere record fuzzily matches to september 2 .', 'tostr': 'filter_eq { filter_eq { all_rows ; telenovela ; mentir para vivir } ; series premiere ; september 2 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; telenovela ; mentir para vivir } ; series premiere ; september 2 } } = true', 'tointer': 'select the rows whose telenovela record fuzzily matches to mentir para vivir . among these rows , select the rows whose series premiere record fuzzily matches to september 2 . there is only one such row in the table .'} | only { filter_eq { filter_eq { all_rows ; telenovela ; mentir para vivir } ; series premiere ; september 2 } } = true | select the rows whose telenovela record fuzzily matches to mentir para vivir . among these rows , select the rows whose series premiere record fuzzily matches to september 2 . there is only one such row in the table . | 3 | 3 | {'only_2': 2, 'result_3': 3, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'telenovela_5': 5, 'mentir para vivir_6': 6, 'series premiere_7': 7, 'september 2_8': 8} | {'only_2': 'only', 'result_3': 'true', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'telenovela_5': 'telenovela', 'mentir para vivir_6': 'mentir para vivir', 'series premiere_7': 'series premiere', 'september 2_8': 'september 2'} | {'only_2': [3], 'result_3': [], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'telenovela_5': [0], 'mentir para vivir_6': [0], 'series premiere_7': [1], 'september 2_8': [1]} | ['country', 'telenovela', 'translation', 'series premiere', 'series finale', 'weekly schedule', 'timeslot'] | [['mexico', 'mentir para vivir', 'ოჰ ეს ცრემლები / პარალელური საიდუმლო', 'september 2 , 2013', 'present', 'monday to friday', '10:10'], ['mexico', 'corazon indomable', 'კატური სულის საიდუმლო', 'june 24 , 2013', 'present', 'monday to friday', '10:55'], ['mexico', 'cachito de cielo', 'მცირე ნაწილი', 'october 7 , 2013', 'present', 'monday to sunday', '16:45'], ['eeuu', 'la patrona', 'მკაწრავი უკვდავება', 'september 22 , 2013', 'present', 'monday to sunday', '19:45'], ['mexico', 'amores verdaderos', 'უყვარს კალოჩე', 'july 17 , 2013', 'cancelled since october 6 , 2013', 'monday to friday', '17:45'], ['mexico', 'la tempestad', 'შტორმის მოტანილს შტორმი წაიყვანს', 'october 7 , 2013', 'present', 'monday to friday', '17:45'], ['brazil', 'avenida brasil', 'ბრაზილიის უბანი', 'october 14 , 2013', 'present', 'monday to friday', '11:00'], ['turkey', 'lale devri', 'ტიტების ტყვეობაში', 'july 25 , 2013', 'present', 'monday to sunday', '18:45 - 21:00']] |
2007 - 08 leb season | https://en.wikipedia.org/wiki/2007%E2%80%9308_LEB_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16176685-4.html.csv | superlative | with a total of 38 , andrew panko played in the most games during the 2007 - 08 leb season . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'games'], 'result': '38', 'ind': 0, 'tostr': 'max { all_rows ; games }', 'tointer': 'the maximum games record of all rows is 38 .'}, '38'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; games } ; 38 }', 'tointer': 'the maximum games record of all rows is 38 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'games'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; games }'}, 'name'], 'result': 'andrew panko', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; games } ; name }'}, 'andrew panko'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; games } ; name } ; andrew panko }', 'tointer': 'the name record of the row with superlative games record is andrew panko .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; games } ; 38 } ; eq { hop { argmax { all_rows ; games } ; name } ; andrew panko } } = true', 'tointer': 'the maximum games record of all rows is 38 . the name record of the row with superlative games record is andrew panko .'} | and { eq { max { all_rows ; games } ; 38 } ; eq { hop { argmax { all_rows ; games } ; name } ; andrew panko } } = true | the maximum games record of all rows is 38 . the name record of the row with superlative games record is andrew panko . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'games_8': 8, '38_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'games_11': 11, 'name_12': 12, 'andrew panko_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'games_8': 'games', '38_9': '38', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'games_11': 'games', 'name_12': 'name', 'andrew panko_13': 'andrew panko'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'games_8': [0], '38_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'games_11': [2], 'name_12': [3], 'andrew panko_13': [4]} | ['rank', 'name', 'team', 'games', 'points'] | [['1', 'jakim donaldson', 'ciudad de la laguna', '36', '357'], ['2', 'oriol junyent', 'ciudad de huelva', '21', '204'], ['3', 'serge ibaka', "l'hospitalet", '28', '234'], ['4', 'ondrej starosta', 'cai zaragoza', '34', '259'], ['5', 'andrew panko', 'bruesa gbc', '38', '287']] |
j. l. van den heuvel orgelbouw | https://en.wikipedia.org/wiki/J._L._van_den_Heuvel_Orgelbouw | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11898040-1.html.csv | unique | the j. l. van den heuvel orgelbouw organ in victoria hall is the only one in the country of switzerland . | {'scope': 'all', 'row': '4', 'col': '2', 'col_other': '4', 'criterion': 'equal', 'value': 'ch', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'ch'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to ch .', 'tostr': 'filter_eq { all_rows ; country ; ch }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; country ; ch } }', 'tointer': 'select the rows whose country record fuzzily matches to ch . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'ch'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to ch .', 'tostr': 'filter_eq { all_rows ; country ; ch }'}, 'building'], 'result': 'victoria hall', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; ch } ; building }'}, 'victoria hall'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; country ; ch } ; building } ; victoria hall }', 'tointer': 'the building record of this unqiue row is victoria hall .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; country ; ch } } ; eq { hop { filter_eq { all_rows ; country ; ch } ; building } ; victoria hall } } = true', 'tointer': 'select the rows whose country record fuzzily matches to ch . there is only one such row in the table . the building record of this unqiue row is victoria hall .'} | and { only { filter_eq { all_rows ; country ; ch } } ; eq { hop { filter_eq { all_rows ; country ; ch } ; building } ; victoria hall } } = true | select the rows whose country record fuzzily matches to ch . there is only one such row in the table . the building record of this unqiue row is victoria hall . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'ch_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'building_9': 9, 'victoria hall_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'ch_8': 'ch', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'building_9': 'building', 'victoria hall_10': 'victoria hall'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'ch_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'building_9': [2], 'victoria hall_10': [3]} | ['date', 'country', 'place', 'building', 'size'] | [['1970', 'nl', 'ridderkerk', 'singelkerk', 'iiip / 32'], ['1979', 'nl', 'katwijk aan zee', 'nieuwe kerk', 'ivp / 80'], ['1989', 'fr', 'paris', 'église saint - eustache', 'vp / 101'], ['1992', 'ch', 'geneva', 'victoria hall', 'ivp / 71'], ['1993', 'gb', 'london', "royal academy of music , duke 's hall", 'iip / 24'], ['1994', 'usa', 'new york city', 'church of the holy apostles', 'iiip / 32'], ['1995', 'se', 'stockholm', 'kungliga musikhögskolan', 'iiip / 25'], ['1995', 'nl', 'rotterdam', 'maranatha kerk', 'iiip / 25'], ['1997', 'de', 'berlin', 'st franziskus kirche', 'iiip / 51'], ['2000', 'se', 'stockholm', 'katarina kyrka', 'iiip / 62'], ['2000', 'nl', 'the hague', 'residence of ben van oosten', 'iiip / 16'], ['2000', 'fi', 'mänttä', 'church', 'iiip / 30'], ['2006', 'dk', 'copenhagen', 'copenhagen concert hall', 'ivp / 91']] |
1949 vfl season | https://en.wikipedia.org/wiki/1949_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809351-8.html.csv | superlative | princes park was the venue in the 1949 vfl season that drew the highest crowd attendance . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'crowd'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; crowd }'}, 'venue'], 'result': 'princes park', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'princes park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; princes park } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is princes park .'} | eq { hop { argmax { all_rows ; crowd } ; venue } ; princes park } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is princes park . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, 'venue_6': 6, 'princes park_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', 'venue_6': 'venue', 'princes park_7': 'princes park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'princes park_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '10.15 ( 75 )', 'richmond', '11.13 ( 79 )', 'kardinia park', '22500', '4 june 1949'], ['collingwood', '21.22 ( 148 )', 'st kilda', '4.12 ( 36 )', 'victoria park', '12000', '4 june 1949'], ['carlton', '14.13 ( 97 )', 'north melbourne', '10.7 ( 67 )', 'princes park', '29500', '4 june 1949'], ['melbourne', '10.17 ( 77 )', 'hawthorn', '10.6 ( 66 )', 'mcg', '11000', '4 june 1949'], ['south melbourne', '12.7 ( 79 )', 'fitzroy', '14.14 ( 98 )', 'lake oval', '12500', '4 june 1949'], ['footscray', '7.17 ( 59 )', 'essendon', '10.12 ( 72 )', 'western oval', '12500', '4 june 1949']] |
2006 - 07 acb season | https://en.wikipedia.org/wiki/2006%E2%80%9307_ACB_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11194153-4.html.csv | aggregation | the top 5 ranking players during the 2006-07 acb season averaged 269 rebounds . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '269', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'rebounds'], 'result': '269', 'ind': 0, 'tostr': 'avg { all_rows ; rebounds }'}, '269'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; rebounds } ; 269 } = true', 'tointer': 'the average of the rebounds record of all rows is 269 .'} | round_eq { avg { all_rows ; rebounds } ; 269 } = true | the average of the rebounds record of all rows is 269 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'rebounds_4': 4, '269_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'rebounds_4': 'rebounds', '269_5': '269'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'rebounds_4': [0], '269_5': [1]} | ['rank', 'name', 'team', 'games', 'rebounds'] | [['1', 'curtis borchardt', 'cb granada', '26', '274'], ['2', 'michael bradley', 'bruesa gbc', '32', '270'], ['3', 'bud eley', 'grupo capitol valladolid', '34', '275'], ['4', 'frédéric weis', 'lagun aro bilbao', '34', '266'], ['5', 'charles gaines', 'dkv joventut', '34', '264']] |
1980 indycar season | https://en.wikipedia.org/wiki/1980_IndyCar_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10527215-2.html.csv | ordinal | the datsun twin 200 was the earliest race in the 1980 indycar season . | {'row': '1', 'col': '5', 'order': '1', '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', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'race name'], 'result': 'datsun twin 200', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; race name }'}, 'datsun twin 200'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 1 } ; race name } ; datsun twin 200 } = true', 'tointer': 'select the row whose date record of all rows is 1st minimum . the race name record of this row is datsun twin 200 .'} | eq { hop { nth_argmin { all_rows ; date ; 1 } ; race name } ; datsun twin 200 } = true | select the row whose date record of all rows is 1st minimum . the race name record of this row is datsun twin 200 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'race name_7': 7, 'datsun twin 200_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '1_6': '1', 'race name_7': 'race name', 'datsun twin 200_8': 'datsun twin 200'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'race name_7': [1], 'datsun twin 200_8': [2]} | ['sanctioning', 'race name', 'circuit', 'city / location', 'date'] | [['joint cart / usac ( crl )', 'datsun twin 200', 'ontario motor speedway', 'ontario , california', 'april 13'], ['joint cart / usac ( crl )', 'indianapolis 500 - mile race', 'indianapolis motor speedway', 'indianapolis , indiana', 'may 26'], ['joint cart / usac ( crl )', 'gould rex mays classic 150', 'milwaukee mile', 'west allis , wisconsin', 'june 8'], ['joint cart / usac ( crl )', 'true value 500', 'pocono raceway', 'long pond , pennsylvania', 'june 22'], ['joint cart / usac ( crl )', 'red roof inns 150', 'mid - ohio sports car course', 'lexington , ohio', 'july 13'], ['cart', 'norton 200', 'michigan international speedway', 'brooklyn , michigan', 'july 20'], ['cart', 'kent oil 150', 'watkins glen international', 'watkins glen , new york', 'august 3'], ['cart', 'tony bettenhausen 200', 'milwaukee mile', 'west allis , wisconsin', 'august 10'], ['cart', 'california 500', 'ontario motor speedway', 'ontario , california', 'august 31'], ['cart', 'gould grand prix 150', 'michigan international speedway', 'brooklyn , michigan', 'september 20'], ['cart', 'i copa méxico 150', 'autódromo hermanos rodríguez', 'mexico city , mexico', 'october 26'], ['cart', 'miller high life 150', 'phoenix international raceway', 'avondale , arizona', 'november 8']] |
cultural interest fraternities and sororities | https://en.wikipedia.org/wiki/Cultural_interest_fraternities_and_sororities | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2538117-5.html.csv | unique | alpha epsilon phi 2 sorority was the only one founded by barnard college . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'barnard college', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'founding university', 'barnard college'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose founding university record fuzzily matches to barnard college .', 'tostr': 'filter_eq { all_rows ; founding university ; barnard college }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; founding university ; barnard college } }', 'tointer': 'select the rows whose founding university record fuzzily matches to barnard college . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'founding university', 'barnard college'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose founding university record fuzzily matches to barnard college .', 'tostr': 'filter_eq { all_rows ; founding university ; barnard college }'}, 'organization'], 'result': 'alpha epsilon phi 2', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; founding university ; barnard college } ; organization }'}, 'alpha epsilon phi 2'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; founding university ; barnard college } ; organization } ; alpha epsilon phi 2 }', 'tointer': 'the organization record of this unqiue row is alpha epsilon phi 2 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; founding university ; barnard college } } ; eq { hop { filter_eq { all_rows ; founding university ; barnard college } ; organization } ; alpha epsilon phi 2 } } = true', 'tointer': 'select the rows whose founding university record fuzzily matches to barnard college . there is only one such row in the table . the organization record of this unqiue row is alpha epsilon phi 2 .'} | and { only { filter_eq { all_rows ; founding university ; barnard college } } ; eq { hop { filter_eq { all_rows ; founding university ; barnard college } ; organization } ; alpha epsilon phi 2 } } = true | select the rows whose founding university record fuzzily matches to barnard college . there is only one such row in the table . the organization record of this unqiue row is alpha epsilon phi 2 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'founding university_7': 7, 'barnard college_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'organization_9': 9, 'alpha epsilon phi 2_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'founding university_7': 'founding university', 'barnard college_8': 'barnard college', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'organization_9': 'organization', 'alpha epsilon phi 2_10': 'alpha epsilon phi 2'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'founding university_7': [0], 'barnard college_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'organization_9': [2], 'alpha epsilon phi 2_10': [3]} | ['letters', 'organization', 'nickname', 'founding date', 'founding university', 'type'] | [['αεπ', 'alpha epsilon pi 1', 'aepi', '1913 - 11 - 07', 'new york university', 'fraternity'], ['αεφ', 'alpha epsilon phi 2', 'aephi', '1909 - 10 - 24', 'barnard college', 'sorority'], ['σαεπ', 'sigma alpha epsilon pi 3', 'sigma', '1998 - 10 - 01', 'university of california , davis', 'sorority'], ['σαμ', 'sigma alpha mu 1', 'sammy', '1909 - 11 - 26', 'city college of new york', 'fraternity'], ['σδτ', 'sigma delta tau 2', 'sdt or sig delts', '1917 - 03 - 25', 'cornell university', 'sorority'], ['τεφ', 'tau epsilon phi 1', 'tep , tau boys', '1910 - 10 - 10', 'columbia university', 'fraternity'], ['ζβτ', 'zeta beta tau 1', 'zbt', '1898 - 12 - 29', 'city college of new york', 'fraternity']] |
target house 200 | https://en.wikipedia.org/wiki/Target_House_200 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17801022-1.html.csv | majority | all of the drivers in the target house 200 completed 197 laps . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '197', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'laps', '197'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , all of them are equal to 197 .', 'tostr': 'all_eq { all_rows ; laps ; 197 } = true'} | all_eq { all_rows ; laps ; 197 } = true | for the laps records of all rows , all of them are equal to 197 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '197_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '197_4': '197'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '197_4': [0]} | ['year', 'date', 'driver', 'manufacturer', 'laps', '-', 'race time', 'average speed ( mph )'] | [['1984', 'october 20', 'geoffrey bodine', 'pontiac', '197', '200.349 ( 322.43 )', '2:06:51', '94.765'], ['1985', 'october 19', 'brett bodine', 'pontiac', '197', '200.349 ( 322.43 )', '1:56:00', '103.629'], ['1986', 'october 18', 'morgan shepherd', 'buick', '197', '200.349 ( 322.43 )', '1:39:08', '101.177'], ['1987', 'october 24', 'morgan shepherd', 'buick', '197', '200.349 ( 322.43 )', '1:52:29', '106.396'], ['1988', 'october 22', 'harry gant', 'buick', '197', '200.349 ( 322.43 )', '1:50:09', '109.132'], ['1989', 'october 21', 'harry gant', 'buick', '197', '200.349 ( 322.43 )', '1:47:32', '111.788'], ['1990', 'october 20', 'steve grissom', 'oldsmobile', '197', '200.349 ( 322.43 )', '1:53:31', '105.896'], ['1991', 'october 19', 'ernie irvan', 'chevrolet', '197', '200.349 ( 322.43 )', '1:55:13', '104.333'], ['1992', 'october 24', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:41:30', '118.433'], ['1993', 'october 23', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:42:37', '117.144'], ['1994', 'october 22', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:49:15', '110.032'], ['1995', 'october 21', 'todd bodine', 'chevrolet', '197', '200.349 ( 322.43 )', '2:01:48', '98.694'], ['1996', 'october 19', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:36:38', '124.397'], ['1997', 'october 25', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:59:42', '100.426'], ['1998', 'october 31', 'elliott sadler', 'chevrolet', '197', '200.349 ( 322.43 )', '1:43:31', '116.126'], ['1999', 'october 23', 'mark martin', 'ford', '197', '200.349 ( 322.43 )', '1:45:36', '113.835'], ['2000', 'october 21', 'jeff green', 'chevrolet', '197', '200.349 ( 322.43 )', '1:46:15', '113.138'], ['2001', 'november 3', 'kenny wallace', 'chevrolet', '197', '200.349 ( 322.43 )', '1:36:56', '124.012'], ['2002', 'november 2', 'jamie mcmurray', 'chevrolet', '197', '200.349 ( 322.43 )', '1:41:18', '118.667']] |
galicia , spain | https://en.wikipedia.org/wiki/Galicia%2C_Spain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12837-1.html.csv | unique | a coruña is the only city in galicia , spain which usually has no frost in a year . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'days with frost', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose days with frost record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; days with frost ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; days with frost ; 0 } }', 'tointer': 'select the rows whose days with frost record is equal to 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'days with frost', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose days with frost record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; days with frost ; 0 }'}, 'city / town'], 'result': 'a coruña', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; days with frost ; 0 } ; city / town }'}, 'a coruña'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; days with frost ; 0 } ; city / town } ; a coruña }', 'tointer': 'the city / town record of this unqiue row is a coruña .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; days with frost ; 0 } } ; eq { hop { filter_eq { all_rows ; days with frost ; 0 } ; city / town } ; a coruña } } = true', 'tointer': 'select the rows whose days with frost record is equal to 0 . there is only one such row in the table . the city / town record of this unqiue row is a coruña .'} | and { only { filter_eq { all_rows ; days with frost ; 0 } } ; eq { hop { filter_eq { all_rows ; days with frost ; 0 } ; city / town } ; a coruña } } = true | select the rows whose days with frost record is equal to 0 . there is only one such row in the table . the city / town record of this unqiue row is a coruña . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'days with frost_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'city / town_9': 9, 'a coruña_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'days with frost_7': 'days with frost', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'city / town_9': 'city / town', 'a coruña_10': 'a coruña'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'days with frost_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'city / town_9': [2], 'a coruña_10': [3]} | ['city / town', 'july av t', 'rain', 'days with rain ( year / summer )', 'days with frost', 'sunlight hours'] | [['santiago de compostela', 'degree', 'mm ( in )', '141 / 19', '15', '1998'], ['a coruña', 'degree', 'mm ( in )', '131 / 19', '0', '1966'], ['lugo', 'degree', 'mm ( in )', '131 / 18', '42', '1821'], ['vigo', 'degree', 'mm ( in )', '130 / 18', '5', '2212'], ['ourense', 'degree', 'mm ( in )', '97 / 12', '30', '2043']] |
united states house of representatives elections , 1954 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1954 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342013-34.html.csv | unique | james g polk was the only member of the democratic party to win re-election in the 1954 us house of representatives elections . | {'scope': 'all', 'row': '2', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; party ; democratic } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}, 'incumbent'], 'result': 'james g polk', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; party ; democratic } ; incumbent }'}, 'james g polk'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; party ; democratic } ; incumbent } ; james g polk }', 'tointer': 'the incumbent record of this unqiue row is james g polk .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; party ; democratic } } ; eq { hop { filter_eq { all_rows ; party ; democratic } ; incumbent } ; james g polk } } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . there is only one such row in the table . the incumbent record of this unqiue row is james g polk .'} | and { only { filter_eq { all_rows ; party ; democratic } } ; eq { hop { filter_eq { all_rows ; party ; democratic } ; incumbent } ; james g polk } } = true | select the rows whose party record fuzzily matches to democratic . there is only one such row in the table . the incumbent record of this unqiue row is james g polk . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'party_7': 7, 'democratic_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'incumbent_9': 9, 'james g polk_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'party_7': 'party', 'democratic_8': 'democratic', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'incumbent_9': 'incumbent', 'james g polk_10': 'james g polk'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'party_7': [0], 'democratic_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'incumbent_9': [2], 'james g polk_10': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['ohio 2', 'william e hess', 'republican', '1950', 're - elected', 'william e hess ( r ) 58.4 % earl t wagner ( d ) 41.6 %'], ['ohio 6', 'james g polk', 'democratic', '1948', 're - elected', 'james g polk ( d ) 52.2 % leo blackburn ( r ) 47.8 %'], ['ohio 12', 'john m vorys', 'republican', '1938', 're - elected', 'john m vorys ( r ) 61.5 % jacob f myers ( d ) 38.5 %'], ['ohio 14', 'william h ayres', 'republican', '1950', 're - elected', 'william h ayres ( r ) 54.6 % john l smith ( d ) 45.4 %'], ['ohio 16', 'frank t bow', 'republican', '1950', 're - elected', 'frank t bow ( r ) 58.3 % thomas h nichols ( d ) 41.7 %']] |
list of countries with mcdonald 's restaurants | https://en.wikipedia.org/wiki/List_of_countries_with_McDonald%27s_restaurants | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1875327-2.html.csv | comparative | the mcdonald 's in san bernardino opened 27 years before the mcdonald 's in san juan . | {'row_1': '1', 'row_2': '2', 'col': '5', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'san bernardino'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose city record fuzzily matches to san bernardino .', 'tostr': 'filter_eq { all_rows ; city ; san bernardino }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; city ; san bernardino } ; year }', 'tointer': 'select the rows whose city record fuzzily matches to san bernardino . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'city', 'san juan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose city record fuzzily matches to san juan .', 'tostr': 'filter_eq { all_rows ; city ; san juan }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; city ; san juan } ; year }', 'tointer': 'select the rows whose city record fuzzily matches to san juan . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; city ; san bernardino } ; year } ; hop { filter_eq { all_rows ; city ; san juan } ; year } } = true', 'tointer': 'select the rows whose city record fuzzily matches to san bernardino . take the year record of this row . select the rows whose city record fuzzily matches to san juan . take the year record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; city ; san bernardino } ; year } ; hop { filter_eq { all_rows ; city ; san juan } ; year } } = true | select the rows whose city record fuzzily matches to san bernardino . take the year record of this row . select the rows whose city record fuzzily matches to san juan . take the year record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'city_7': 7, 'san bernardino_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'city_11': 11, 'san juan_12': 12, 'year_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'city_7': 'city', 'san bernardino_8': 'san bernardino', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'city_11': 'city', 'san juan_12': 'san juan', 'year_13': 'year'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'city_7': [0], 'san bernardino_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'city_11': [1], 'san juan_12': [1], 'year_13': [3]} | ['continent', 'location', 'city', 'date', 'year'] | [['north america', 'united states', 'san bernardino', 'may 15', '1940'], ['caribbean', 'puerto rico', 'san juan', 'november 10', '1967'], ['central america', 'costa rica', 'san josã', 'december 28', '1970'], ['oceania', 'australia', 'sydney', 'may 30', '1971'], ['asia 1', 'japan', 'tokyo', 'july 20', '1971'], ['europe', 'netherlands', 'zaandam', 'august 21', '1971'], ['south america', 'brazil', 'rio de janeiro', 'february 13', '1979'], ['asia 2', 'philippines', 'manila', 'september 27', '1981'], ['africa', 'morocco', 'casablanca', 'december 18', '1992'], ['middle east', 'israel', 'tel aviv', 'october 14', '1993']] |
1987 - 88 coupe de france | https://en.wikipedia.org/wiki/1987%E2%80%9388_Coupe_de_France | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17747000-1.html.csv | unique | thea only team competing in the tournament that was from d3 was us créteil . | {'scope': 'all', 'row': '8', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'd3', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team 2', 'd3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team 2 record fuzzily matches to d3 .', 'tostr': 'filter_eq { all_rows ; team 2 ; d3 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; team 2 ; d3 } } = true', 'tointer': 'select the rows whose team 2 record fuzzily matches to d3 . there is only one such row in the table .'} | only { filter_eq { all_rows ; team 2 ; d3 } } = true | select the rows whose team 2 record fuzzily matches to d3 . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'team 2_4': 4, 'd3_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'team 2_4': 'team 2', 'd3_5': 'd3'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'team 2_4': [0], 'd3_5': [0]} | ['team 1', 'score', 'team 2', '1st round', '2nd round'] | [['toulouse fc ( d1 )', '2 - 2', 'ogc nice ( d1 )', '1 - 1', '1 - 1'], ['lille osc ( d1 )', '2 - 2', 'aj auxerre ( d1 )', '1 - 0', '1 - 2'], ['montpellier hsc ( d1 )', '2 - 3', 'fc sochaux - montbéliard ( d2 )', '2 - 2', '0 - 1'], ['stade de reims ( d2 )', '2 - 1', 'le havre ac ( d1 )', '2 - 0', '0 - 1'], ['fc metz ( d1 )', '3 - 0', 'fc mulhouse ( d2 )', '1 - 0', '2 - 0'], ['fc sète ( d2 )', '0 - 1', 'rc lens ( d1 )', '0 - 0', '0 - 1'], ['aep bourg sous la roche ( d2 )', '3 - 5', 'stade quimpérois ( d2 )', '1 - 3', '2 - 2'], ['so chtellerault ( d2 )', '0 - 0', 'us créteil ( d3 )', '0 - 0', '0 - 0']] |
1986 icf canoe sprint world championships | https://en.wikipedia.org/wiki/1986_ICF_Canoe_Sprint_World_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18715280-4.html.csv | superlative | of the nations competing in the 1986 icf canoe sprint world championships , the soviet union won the most silver medals . | {'scope': 'all', 'col_superlative': '4', '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', 'silver'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; silver }'}, 'nation'], 'result': 'soviet union', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; silver } ; nation }'}, 'soviet union'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; silver } ; nation } ; soviet union } = true', 'tointer': 'select the row whose silver record of all rows is maximum . the nation record of this row is soviet union .'} | eq { hop { argmax { all_rows ; silver } ; nation } ; soviet union } = true | select the row whose silver record of all rows is maximum . the nation record of this row is soviet union . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'silver_5': 5, 'nation_6': 6, 'soviet union_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'silver_5': 'silver', 'nation_6': 'nation', 'soviet union_7': 'soviet union'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'silver_5': [0], 'nation_6': [1], 'soviet union_7': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'hungary', '7', '3', '1', '11'], ['2', 'soviet union', '1', '6', '3', '10'], ['3', 'romania', '3', '3', '2', '8'], ['4', 'east germany', '2', '3', '2', '7'], ['5', 'poland', '1', '1', '1', '3'], ['6', 'bulgaria', '1', '0', '2', '3'], ['7', 'west germany', '1', '0', '2', '3'], ['8', 'united kingdom', '2', '0', '0', '2'], ['9', 'france', '0', '1', '1', '2'], ['10', 'yugoslavia', '0', '1', '1', '2'], ['11', 'denmark', '0', '0', '2', '2'], ['12', 'australia', '0', '0', '1', '1'], ['total', 'total', '18', '18', '18', '54']] |
1969 vfl season | https://en.wikipedia.org/wiki/1969_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809157-17.html.csv | count | all 6 matches occurred on 9 august 1969 . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record is arbitrary .', 'tostr': 'filter_all { all_rows ; date }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; date } }', 'tointer': 'select the rows whose date record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; date } } ; 6 } = true', 'tointer': 'select the rows whose date record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; date } } ; 6 } = true | select the rows whose date record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'date_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'date_5': 'date', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'date_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '9.14 ( 68 )', 'south melbourne', '15.10 ( 100 )', 'moorabbin oval', '13400', '9 august 1969'], ['hawthorn', '22.12 ( 144 )', 'north melbourne', '18.18 ( 126 )', 'glenferrie oval', '13504', '9 august 1969'], ['essendon', '19.18 ( 132 )', 'fitzroy', '14.11 ( 95 )', 'windy hill', '15548', '9 august 1969'], ['carlton', '14.11 ( 95 )', 'geelong', '17.8 ( 110 )', 'princes park', '27166', '9 august 1969'], ['richmond', '19.11 ( 125 )', 'melbourne', '12.13 ( 85 )', 'mcg', '23519', '9 august 1969'], ['footscray', '11.16 ( 82 )', 'collingwood', '16.8 ( 104 )', 'western oval', '21201', '9 august 1969']] |
american dad ! ( season 1 ) | https://en.wikipedia.org/wiki/American_Dad%21_%28season_1%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23242933-2.html.csv | superlative | episode 1 of american dad ! ( season 1 ) had the highest number of viewers . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'us viewers ( millions )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; us viewers ( millions ) }'}, 'no in series'], 'result': '1', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; us viewers ( millions ) } ; no in series }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; us viewers ( millions ) } ; no in series } ; 1 } = true', 'tointer': 'select the row whose us viewers ( millions ) record of all rows is maximum . the no in series record of this row is 1 .'} | eq { hop { argmax { all_rows ; us viewers ( millions ) } ; no in series } ; 1 } = true | select the row whose us viewers ( millions ) record of all rows is maximum . the no in series record of this row is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, 'no in series_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'us viewers (millions)_5': 'us viewers ( millions )', 'no in series_6': 'no in series', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], 'no in series_6': [1], '1_7': [2]} | ['no in series', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )'] | [['1', 'pilot', 'ron hughart', 'seth macfarlane , mike barker & matt weitzman', 'february 6 , 2005', '1ajn01', '15.10'], ['2', 'threat levels', 'brent woods', 'david zuckerman', 'may 1 , 2005', '1ajn02', '9.47'], ['3', 'stan knows best', 'pam cooke', 'mike barker & matt weitzman', 'may 8 , 2005', '1ajn03', '8.23'], ['4', "francine 's flashback", 'caleb meurer & brent woods', 'rick wiener & kenny schwartz', 'may 15 , 2005', '1ajn05', '7.84'], ['5', 'roger codger', 'albert calleros', 'dan vebber', 'june 5 , 2005', '1ajn04', '6.09'], ['6', 'homeland insecurity', 'rodney clouden', "neal boushell & sam o'neal", 'june 12 , 2005', '1ajn06', '6.85']] |
nbc sunday night football results ( 2006 - present ) | https://en.wikipedia.org/wiki/NBC_Sunday_Night_Football_results_%282006%E2%80%93present%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10944289-12.html.csv | count | according to the nbc sunday night football results ( 2006 - present ) , among the afc conferences , 2 of them have 10 wins each . | {'scope': 'subset', 'criterion': 'equal', 'value': '10', 'result': '2', 'col': '4', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'afc'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'conference', 'afc'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; conference ; afc }', 'tointer': 'select the rows whose conference record fuzzily matches to afc .'}, 'wins', '10'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose conference record fuzzily matches to afc . among these rows , select the rows whose wins record is equal to 10 .', 'tostr': 'filter_eq { filter_eq { all_rows ; conference ; afc } ; wins ; 10 }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; conference ; afc } ; wins ; 10 } }', 'tointer': 'select the rows whose conference record fuzzily matches to afc . among these rows , select the rows whose wins record is equal to 10 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; conference ; afc } ; wins ; 10 } } ; 2 } = true', 'tointer': 'select the rows whose conference record fuzzily matches to afc . among these rows , select the rows whose wins record is equal to 10 . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; conference ; afc } ; wins ; 10 } } ; 2 } = true | select the rows whose conference record fuzzily matches to afc . among these rows , select the rows whose wins record is equal to 10 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'conference_6': 6, 'afc_7': 7, 'wins_8': 8, '10_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_eq_1': 'filter_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'conference_6': 'conference', 'afc_7': 'afc', 'wins_8': 'wins', '10_9': '10', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'conference_6': [0], 'afc_7': [0], 'wins_8': [1], '10_9': [1], '2_10': [3]} | ['conference', 'division', 'appearances', 'wins', 'losses'] | [['afc', 'east', '18', '10', '8'], ['afc', 'north', '22', '10', '12'], ['afc', 'south', '24', '15', '9'], ['afc', 'west', '20', '11', '9'], ['nfc', 'east', '60', '26', '34'], ['nfc', 'north', '29', '13', '16'], ['nfc', 'south', '15', '8', '7'], ['nfc', 'west', '16', '9', '7']] |
jimmy davies | https://en.wikipedia.org/wiki/Jimmy_Davies | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1236195-3.html.csv | unique | 1956 was the only year that jimmy davies drove with a novi v8 type engine . | {'scope': 'all', 'row': '6', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'novi v8', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'novi v8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to novi v8 .', 'tostr': 'filter_eq { all_rows ; engine ; novi v8 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; engine ; novi v8 } }', 'tointer': 'select the rows whose engine record fuzzily matches to novi v8 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', 'novi v8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to novi v8 .', 'tostr': 'filter_eq { all_rows ; engine ; novi v8 }'}, 'year'], 'result': '1956', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; engine ; novi v8 } ; year }'}, '1956'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; engine ; novi v8 } ; year } ; 1956 }', 'tointer': 'the year record of this unqiue row is 1956 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; engine ; novi v8 } } ; eq { hop { filter_eq { all_rows ; engine ; novi v8 } ; year } ; 1956 } } = true', 'tointer': 'select the rows whose engine record fuzzily matches to novi v8 . there is only one such row in the table . the year record of this unqiue row is 1956 .'} | and { only { filter_eq { all_rows ; engine ; novi v8 } } ; eq { hop { filter_eq { all_rows ; engine ; novi v8 } ; year } ; 1956 } } = true | select the rows whose engine record fuzzily matches to novi v8 . there is only one such row in the table . the year record of this unqiue row is 1956 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'engine_7': 7, 'novi v8_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1956_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'engine_7': 'engine', 'novi v8_8': 'novi v8', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1956_10': '1956'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'engine_7': [0], 'novi v8_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1956_10': [3]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1950', 'pat clancy', 'ewing', 'offenhauser l4', '0'], ['1951', 'parks offenhauser / le parks', 'pawl', 'offenhauser l4', '0'], ['1953', 'pat clancy', 'kurtis kraft 500b', 'offenhauser l4', '0'], ['1954', 'bardahl / ed walsh', 'kurtis kraft 4000', 'offenhauser l4', '0'], ['1955', 'bardahl / pat clancy', 'kurtis kraft 500b', 'offenhauser l4', '4'], ['1956', 'novi racing', 'kurtis kraft 500f', 'novi v8', '0'], ['1957', 'trio brdeact wind allass', 'kurtis kraft 500d', 'offenhauser l4', '0'], ['1959', 'sumar / chapman root', 'kurtis kraft 500 g', 'offenhauser l4', '0']] |
hans - joachim stuck | https://en.wikipedia.org/wiki/Hans-Joachim_Stuck | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1217995-3.html.csv | count | hans - joachim stuck had a dnf position result in a total of six different years . | {'scope': 'all', 'criterion': 'equal', 'value': 'dnf', 'result': '7', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', 'dnf'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record fuzzily matches to dnf .', 'tostr': 'filter_eq { all_rows ; pos ; dnf }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; pos ; dnf } }', 'tointer': 'select the rows whose pos record fuzzily matches to dnf . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; pos ; dnf } } ; 7 } = true', 'tointer': 'select the rows whose pos record fuzzily matches to dnf . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; pos ; dnf } } ; 7 } = true | select the rows whose pos record fuzzily matches to dnf . 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, 'pos_5': 5, 'dnf_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', 'pos_5': 'pos', 'dnf_6': 'dnf', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'pos_5': [0], 'dnf_6': [0], '7_7': [2]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1972', 'ford motor company deutschland', 'jochen mass', 's 3.0', '152', 'dnf', 'dnf'], ['1973', 'bmw motorsport', 'chris amon', 't 5.0', '160', 'dnf', 'dnf'], ['1980', 'bmw motorsport gmbh', 'hans - georg bürger dominique lacaud', 'imsa', '283', '15th', '5th'], ['1981', 'basf cassetten team gs sport', 'jean - pierre jarier helmut henzler', 'imsa gtx', '57', 'dnf', 'dnf'], ['1982', 'basf cassetten team gs sport', 'jean - louis schlesser dieter quester', 'c', '76', 'dnf', 'dnf'], ['1985', 'rothmans porsche', 'derek bell', 'c1', '367', '3rd', '3rd'], ['1986', 'rothmans porsche', 'derek bell al holbert', 'c1', '368', '1st', '1st'], ['1987', 'rothmans porsche ag', 'derek bell al holbert', 'c1', '368', '1st', '1st'], ['1988', 'porsche ag', 'klaus ludwig derek bell', 'c1', '394', '2nd', '2nd'], ['1989', 'joest racing', 'bob wollek', 'c1', '382', '3rd', '3rd'], ['1990', 'joest porsche racing', 'derek bell frank jelinski', 'c1', '350', '4th', '4th'], ['1991', 'konrad motorsport', 'derek bell frank jelinski', 'c2', '347', '7th', '7th'], ['1993', 'le mans porsche team', 'walter röhrl hurley haywood', 'gt', '79', 'dnf', 'dnf'], ['1994', 'le mans porsche team joest racing', 'thierry boutsen danny sullivan', 'gt1', '343', '3rd', '2nd'], ['1995', 'porsche kremer racing', 'thierry boutsen christophe bouchut', 'wsc', '289', '6th', '2nd'], ['1996', 'porsche ag', 'thierry boutsen bob wollek', 'gt1', '353', '2nd', '1st'], ['1997', 'porsche ag', 'thierry boutsen bob wollek', 'gt1', '238', 'dnf', 'dnf'], ['1998', 'team bmw motorsport', 'steve soper tom kristensen', 'lmp1', '60', 'dnf', 'dnf']] |
united states house of representatives elections , 1964 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1964 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341865-11.html.csv | comparative | robert l f sikes was first elected sooner than donald ray matthews . | {'row_1': '1', 'row_2': '7', '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', 'incumbent', 'robert l f sikes'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to robert l f sikes .', 'tostr': 'filter_eq { all_rows ; incumbent ; robert l f sikes }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; robert l f sikes } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to robert l f sikes . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'donald ray matthews'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to donald ray matthews .', 'tostr': 'filter_eq { all_rows ; incumbent ; donald ray matthews }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; donald ray matthews } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to donald ray matthews . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; robert l f sikes } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; donald ray matthews } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to robert l f sikes . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to donald ray matthews . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; robert l f sikes } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; donald ray matthews } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to robert l f sikes . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to donald ray matthews . take the first elected 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, 'incumbent_7': 7, 'robert l f sikes_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'donald ray matthews_12': 12, 'first elected_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', 'incumbent_7': 'incumbent', 'robert l f sikes_8': 'robert l f sikes', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_11': 'incumbent', 'donald ray matthews_12': 'donald ray matthews', 'first elected_13': 'first elected'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'robert l f sikes_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'donald ray matthews_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['florida 1', 'robert l f sikes', 'democratic', '1940', 're - elected', 'robert l f sikes ( d ) unopposed'], ['florida 3', 'claude pepper', 'democratic', '1962', 're - elected', "claude pepper ( d ) 65.7 % paul j o'neill ( r ) 34.3 %"], ['florida 4', 'dante fascell', 'democratic', '1954', 're - elected', 'dante fascell ( d ) 63.9 % jay mcglon ( r ) 36.1 %'], ['florida 5', 'albert s herlong , jr', 'democratic', '1948', 're - elected', 'albert s herlong , jr ( d ) unopposed'], ['florida 6', 'paul rogers', 'democratic', '1954', 're - elected', 'paul rogers ( d ) 66.0 % john d steele ( r ) 34.0 %'], ['florida 7', 'james a haley', 'democratic', '1952', 're - elected', 'james a haley ( d ) unopposed'], ['florida 8', 'donald ray matthews', 'democratic', '1952', 're - elected', 'donald ray matthews ( d ) unopposed'], ['florida 9', 'don fuqua', 'democratic', '1962', 're - elected', 'don fuqua ( d ) unopposed']] |
2007 tour of the basque country | https://en.wikipedia.org/wiki/2007_Tour_of_the_Basque_Country | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10571391-13.html.csv | superlative | the member representing spain got the most points in the 2007 tour of the basque country . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'uci protour points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; uci protour points }'}, 'country'], 'result': 'spain', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; uci protour points } ; country }'}, 'spain'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; uci protour points } ; country } ; spain } = true', 'tointer': 'select the row whose uci protour points record of all rows is maximum . the country record of this row is spain .'} | eq { hop { argmax { all_rows ; uci protour points } ; country } ; spain } = true | select the row whose uci protour points record of all rows is maximum . the country record of this row is spain . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'uci protour points_5': 5, 'country_6': 6, 'spain_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'uci protour points_5': 'uci protour points', 'country_6': 'country', 'spain_7': 'spain'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'uci protour points_5': [0], 'country_6': [1], 'spain_7': [2]} | ['cyclist', 'country', 'team', 'time', 'uci protour points'] | [['juan josé cobo', 'spain', 'saunier duval - prodir', "21h 56 ' 38", '50'], ['ángel vicioso', 'spain', 'relax - gam', '+ 37', 'n / a'], ['samuel sánchez', 'spain', 'euskaltel - euskadi', "+ 1 ' 16", '35'], ['damiano cunego', 'italy', 'lampre - fondital', "+ 2 ' 26", '30'], ['alejandro valverde', 'spain', "caisse d'epargne", "+ 2 ' 42", '25'], ['davide rebellin', 'italy', 'gerolsteiner', "+ 2 ' 50", '20'], ['tadej valjavec', 'slovenia', 'lampre - fondital', "+ 2 ' 57", '15'], ['fränk schleck', 'luxembourg', 'team csc', "+ 3 ' 13", '10'], ['joaquin rodríguez', 'spain', "caisse d'epargne", "+ 3 ' 21", '5'], ['koldo gil', 'spain', 'saunier duval - prodir', "+ 3 ' 41", '2']] |
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 | comparative | the townsville crocodiles scored more points in their basketball game than the carins taipans did in theirs . | {'row_1': '2', 'row_2': '5', 'col': '3', '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', 'home team', 'townsville crocodiles'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to townsville crocodiles .', 'tostr': 'filter_eq { all_rows ; home team ; townsville crocodiles }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; home team ; townsville crocodiles } ; score }', 'tointer': 'select the rows whose home team record fuzzily matches to townsville crocodiles . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'cairns taipans'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team record fuzzily matches to cairns taipans .', 'tostr': 'filter_eq { all_rows ; home team ; cairns taipans }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; home team ; cairns taipans } ; score }', 'tointer': 'select the rows whose home team record fuzzily matches to cairns taipans . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; home team ; townsville crocodiles } ; score } ; hop { filter_eq { all_rows ; home team ; cairns taipans } ; score } } = true', 'tointer': 'select the rows whose home team record fuzzily matches to townsville crocodiles . take the score record of this row . select the rows whose home team record fuzzily matches to cairns taipans . take the score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; home team ; townsville crocodiles } ; score } ; hop { filter_eq { all_rows ; home team ; cairns taipans } ; score } } = true | select the rows whose home team record fuzzily matches to townsville crocodiles . take the score record of this row . select the rows whose home team record fuzzily matches to cairns taipans . take the score record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'home team_7': 7, 'townsville crocodiles_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'cairns taipans_12': 12, 'score_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'home team_7': 'home team', 'townsville crocodiles_8': 'townsville crocodiles', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'home team_11': 'home team', 'cairns taipans_12': 'cairns taipans', 'score_13': 'score'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'townsville crocodiles_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'cairns taipans_12': [1], 'score_13': [3]} | ['date', 'home team', 'score', 'away team', 'venue', 'box score', 'report'] | [['26 november', 'south dragons', '102 - 64', 'cairns taipans', 'hisense arena', 'box score', '-'], ['26 november', 'townsville crocodiles', '113 - 105', 'melbourne tigers', 'townsville entertainment centre', 'box score', '-'], ['27 november', 'new zealand breakers', '108 - 94', 'perth wildcats', 'north shore events centre', 'box score', '-'], ['29 november', 'adelaide 36ers', '101 - 96', 'wollongong hawks', 'distinctive homes dome', 'box score', '-'], ['29 november', 'cairns taipans', '90 - 94', 'townsville crocodiles', 'cairns convention centre', 'box score', '-'], ['29 november', 'gold coast blaze', '88 - 110', 'new zealand breakers', 'gold coast convention centre', 'box score', '-'], ['29 november', 'perth wildcats', '95 - 108', 'melbourne tigers', 'marrara stadium', 'box score', '-'], ['29 november', 'sydney spirit', '103 - 94', 'south dragons', 'state sports centre', 'box score', '-']] |
2001 st. louis rams season | https://en.wikipedia.org/wiki/2001_St._Louis_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10659538-3.html.csv | superlative | the highest attendance was for the game where the new york jets were the opponents . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'opponent'], 'result': 'new york jets', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; opponent }'}, 'new york jets'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; opponent } ; new york jets } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the opponent record of this row is new york jets .'} | eq { hop { argmax { all_rows ; attendance } ; opponent } ; new york jets } = true | select the row whose attendance record of all rows is maximum . the opponent record of this row is new york jets . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'opponent_6': 6, 'new york jets_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'opponent_6': 'opponent', 'new york jets_7': 'new york jets'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'opponent_6': [1], 'new york jets_7': [2]} | ['week', 'date', 'opponent', 'result', 'record', 'tv time', 'attendance'] | [['1', 'september 9 , 2001', 'philadelphia eagles', 'w 20 - 17 ( ot )', '1 - 0', 'fox 3:15 pm', '66243'], ['2', 'september 23 , 2001', 'san francisco 49ers', 'w 30 - 26', '2 - 0', 'fox 3:15 pm', '67536'], ['3', 'september 30 , 2001', 'miami dolphins', 'w 42 - 10', '3 - 0', 'cbs 12:00 pm', '66046'], ['4', 'october 8 , 2001', 'detroit lions', 'w 35 - 0', '4 - 0', 'abc 8:00 pm', '77765'], ['5', 'october 14 , 2001', 'new york giants', 'w 15 - 14', '5 - 0', 'fox 12:00 pm', '65992'], ['6', 'october 21 , 2001', 'new york jets', 'w 34 - 14', '6 - 0', 'fox 12:00 pm', '78766'], ['7', 'october 28 , 2001', 'new orleans saints', 'l 34 - 31', '6 - 1', 'fox 12:00 pm', '66189'], ['8', '-', '-', '-', '-', '-', ''], ['9', 'november 11 , 2001', 'carolina panthers', 'w 48 - 14', '7 - 1', 'fox 12:00 pm', '66069'], ['10', 'november 18 , 2001', 'new england patriots', 'w 24 - 17', '8 - 1', 'espn 7:30 pm', '60292'], ['11', 'november 26 , 2001', 'tampa bay buccaneers', 'l 24 - 17', '8 - 2', 'abc 8:00 pm', '66198'], ['12', 'december 2 , 2001', 'atlanta falcons', 'w 35 - 6', '9 - 2', 'fox 3:15 pm', '60787'], ['13', 'december 9 , 2001', 'san francisco 49ers', 'w 27 - 14', '10 - 2', 'fox 12:00 pm', '66218'], ['14', 'december 17 , 2001', 'new orleans saints', 'w 34 - 21', '11 - 2', 'abc 8:00 pm', '70332'], ['15', 'december 23 , 2001', 'carolina panthers', 'w 38 - 32', '12 - 2', 'fox 12:00 pm', '72438'], ['16', 'december 30 , 2001', 'indianapolis colts', 'w 42 - 17', '13 - 2', 'cbs 12:00 pm', '66084'], ['17', 'january 6 , 2002', 'atlanta falcons', 'w 31 - 13', '14 - 2', 'fox 3:15 pm', '66033']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-8.html.csv | aggregation | all districts which participated in the 2006 house elections had incumbents with an average first elected year of around 1991 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '1991', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'first elected'], 'result': '1991', 'ind': 0, 'tostr': 'avg { all_rows ; first elected }'}, '1991'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; first elected } ; 1991 } = true', 'tointer': 'the average of the first elected record of all rows is 1991 .'} | round_eq { avg { all_rows ; first elected } ; 1991 } = true | the average of the first elected record of all rows is 1991 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'first elected_4': 4, '1991_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'first elected_4': 'first elected', '1991_5': '1991'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'first elected_4': [0], '1991_5': [1]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['connecticut 1', 'john larson', 'democratic', '1998', 're - elected'], ['connecticut 2', 'rob simmons', 'republican', '2000', 'lost re - election democratic gain'], ['connecticut 3', 'rosa delauro', 'democratic', '1990', 're - elected'], ['connecticut 4', 'chris shays', 'republican', '1987', 're - elected'], ['connecticut 5', 'nancy johnson', 'republican', '1982', 'lost re - election democratic gain']] |
dominik meffert | https://en.wikipedia.org/wiki/Dominik_Meffert | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13141391-4.html.csv | count | on 2 different occasions , dominik meffert partnered with philipp oswald against their opponents . | {'scope': 'all', 'criterion': 'equal', 'value': 'philipp oswald', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'partner', 'philipp oswald'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose partner record fuzzily matches to philipp oswald .', 'tostr': 'filter_eq { all_rows ; partner ; philipp oswald }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; partner ; philipp oswald } }', 'tointer': 'select the rows whose partner record fuzzily matches to philipp oswald . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; partner ; philipp oswald } } ; 2 } = true', 'tointer': 'select the rows whose partner record fuzzily matches to philipp oswald . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; partner ; philipp oswald } } ; 2 } = true | select the rows whose partner record fuzzily matches to philipp oswald . 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, 'partner_5': 5, 'philipp oswald_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', 'partner_5': 'partner', 'philipp oswald_6': 'philipp oswald', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'partner_5': [0], 'philipp oswald_6': [0], '2_7': [2]} | ['tournament', 'surface', 'partner', 'opponents in the final', 'score in the final'] | [['freudenstadt', 'clay', 'tomas behrend', 'alexandre sidorenko mischa zverev', '7 - 5 , 7 - 6 5'], ['durban', 'hard', 'rik de voest', 'stéphane bohli noam okun', '6 - 4 , 6 - 2'], ['tanger', 'clay', 'steve darcis', 'uladzimir ignatik martin kližan', '5 - 7 , 7 - 5 ,'], ['pereira', 'clay', 'philipp oswald', 'gero kretschmer alex satschko', '6 - 7 4 , 7 - 6 6 ,'], ['curitiba', 'clay', 'leonardo tavares', 'ramón delgado andré sá', '3 - 6 , 6 - 2 ,'], ['nouméa', 'hard', 'frederik nielsen', 'flavio cipolla simone vagnozzi', '7 - 6 4 , 5 - 7 ,'], ['kyoto', 'carpet ( i )', 'simon stadler', 'andre begemann james lemke', '7 - 5 , 2 - 6 ,'], ['dortmund', 'clay', 'björn phau', 'teymuraz gabashvili andrey kuznetsov', '6 - 4 , 6 - 3'], ['tunis', 'clay', 'philipp oswald', 'jamie delgado andreas siljeström', '3 - 6 , 7 - 6 ( 7 - 0 ) ,']] |
jason leffler | https://en.wikipedia.org/wiki/Jason_Leffler | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1637041-4.html.csv | aggregation | jason leffler 's average winnings per year from 1999-2012 is 884656 . | {'scope': 'all', 'col': '9', 'type': 'average', 'result': '884656', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'winnings'], 'result': '884656', 'ind': 0, 'tostr': 'avg { all_rows ; winnings }'}, '884656'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; winnings } ; 884656 } = true', 'tointer': 'the average of the winnings record of all rows is 884656 .'} | round_eq { avg { all_rows ; winnings } ; 884656 } = true | the average of the winnings record of all rows is 884656 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'winnings_4': 4, '884656_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'winnings_4': 'winnings', '884656_5': '884656'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'winnings_4': [0], '884656_5': [1]} | ['year', 'starts', 'wins', 'top 5', 'top 10', 'poles', 'avg start', 'avg finish', 'winnings', 'position', 'team ( s )'] | [['1999', '4', '0', '0', '0', '0', '28.0', '26.8', '36400', '74th', '18 joe gibbs racing'], ['2000', '31', '0', '2', '4', '3', '24.3', '23.0', '513068', '20th', '18 joe gibbs racing'], ['2003', '6', '0', '1', '1', '0', '15.0', '14.3', '113345', '52nd', '00 haas cnc racing'], ['2004', '27', '1', '8', '17', '1', '9.4', '11.0', '1168779', '12th', '00 haas cnc racing'], ['2005', '15', '0', '2', '7', '0', '19.0', '14.6', '400883', '30th', '32 braun racing'], ['2006', '35', '0', '3', '7', '2', '20.2', '21.2', '1182579', '13th', '32 / 38 braun racing'], ['2007', '35', '1', '7', '11', '2', '17.6', '17.5', '1691099', '3rd', '38 braun racing'], ['2008', '35', '0', '3', '13', '0', '14.5', '16.2', '1350927', '9th', '38 braun racing'], ['2009', '35', '0', '8', '20', '0', '15.9', '12.4', '1699080', '4th', '38 braun racing'], ['2010', '35', '0', '6', '14', '0', '16.1', '17.5', '1272165', '9th', '10 / 38 braun racing'], ['2011', '34', '0', '2', '12', '0', '13.0', '13.9', '1131158', '6th', '30 / 38 turner motorsports'], ['2012', '2', '0', '0', '1', '0', '6.5', '10.0', '56388', '120th 1', '30 turner motorsports']] |
washington redskins draft history | https://en.wikipedia.org/wiki/Washington_Redskins_draft_history | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-32.html.csv | ordinal | billy neighbors had the fourth highest overall pick number by the washington redskins in the nfl draft . | {'row': '4', 'col': '3', 'order': '4', 'col_other': '4', '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', 'overall', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; overall ; 4 }'}, 'name'], 'result': 'billy neighbors', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; overall ; 4 } ; name }'}, 'billy neighbors'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; overall ; 4 } ; name } ; billy neighbors } = true', 'tointer': 'select the row whose overall record of all rows is 4th minimum . the name record of this row is billy neighbors .'} | eq { hop { nth_argmin { all_rows ; overall ; 4 } ; name } ; billy neighbors } = true | select the row whose overall record of all rows is 4th minimum . the name record of this row is billy neighbors . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'overall_5': 5, '4_6': 6, 'name_7': 7, 'billy neighbors_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', 'overall_5': 'overall', '4_6': '4', 'name_7': 'name', 'billy neighbors_8': 'billy neighbors'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'overall_5': [0], '4_6': [0], 'name_7': [1], 'billy neighbors_8': [2]} | ['round', 'pick', 'overall', 'name', 'position', 'college'] | [['1', '1', '1', 'ernie davis', 'rb', 'syracuse'], ['2', '1', '15', 'joe hernandez', 'wr', 'arizona'], ['3', '1', '29', 'bob mitinger', 'lb', 'penn state'], ['4', '1', '43', 'billy neighbors', 'g', 'alabama'], ['7', '1', '85', 'bert coan', 'hb', 'kansas'], ['8', '1', '99', 'ron hatcher', 'fb', 'michigan state'], ['9', '1', '113', 'dave viti', 'e', 'boston university'], ['10', '1', '127', 'john childress', 'g', 'arkansas'], ['11', '1', '141', 'carl palazzo', 'ot', 'adams state'], ['12', '1', '155', 'terry terrebonne', 'hb', 'tulane'], ['13', '1', '169', 'bill whisler', 'e', 'iowa'], ['14', '1', '183', 'jim costen', 'hb', 'south carolina'], ['15', '1', '197', 'len velia', 'ot', 'georgia'], ['16', '1', '211', 'tommy brooker', 'e', 'alabama'], ['17', '1', '225', 'allen miller', 'lb', 'ohio'], ['18', '1', '239', 'carl charon', 'db', 'michigan state'], ['19', '1', '253', 'claude crabb', 'db', 'colorado'], ['20', '1', '267', 'ed trancygier', 'qb', 'florida state']] |
2004 arizona cardinals season | https://en.wikipedia.org/wiki/2004_Arizona_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18722259-2.html.csv | count | during the 2004 season , the arizona cardinals played four games in october . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'october', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to october .', 'tostr': 'filter_eq { all_rows ; date ; october }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; october } }', 'tointer': 'select the rows whose date record fuzzily matches to october . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; october } } ; 4 } = true', 'tointer': 'select the rows whose date record fuzzily matches to october . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; date ; october } } ; 4 } = true | select the rows whose date record fuzzily matches to october . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'October_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'October_6': 'october', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'October_6': [0], '4_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 12 , 2004', 'st louis rams', 'l 17 - 10', '65538'], ['2', 'september 19 , 2004', 'new england patriots', 'l 23 - 12', '51557'], ['3', 'september 26 , 2004', 'atlanta falcons', 'l 6 - 3', '70534'], ['4', 'october 3 , 2004', 'new orleans saints', 'w 34 - 10', '28109'], ['5', 'october 10 , 2004', 'san francisco 49ers', 'l 31 - 28 ot', '62836'], ['7', 'october 24 , 2004', 'seattle seahawks', 'w 25 - 17', '35695'], ['8', 'october 31 , 2004', 'buffalo bills', 'l 38 - 14', '65887'], ['9', 'november 7 , 2004', 'miami dolphins', 'w 24 - 23', '72612'], ['10', 'november 14 , 2004', 'new york giants', 'w 17 - 14', '42297'], ['11', 'november 21 , 2004', 'carolina panthers', 'l 35 - 10', '72796'], ['12', 'november 28 , 2004', 'new york jets', 'l 13 - 3', '35820'], ['13', 'december 5 , 2004', 'detroit lions', 'l 26 - 12', '62262'], ['14', 'december 12 , 2004', 'san francisco 49ers', 'l 31 - 28 ot', '35069'], ['15', 'december 19 , 2004', 'st louis rams', 'w 31 - 7', '40070'], ['16', 'december 26 , 2004', 'seattle seahawks', 'l 24 - 21', '65825'], ['17', 'january 2 , 2005', 'tampa bay buccaneers', 'w 12 - 7', '31650']] |
b " gymnastics at the 2008 summer olympics - women 's uneven bars " | https://en.wikipedia.org/wiki/Gymnastics_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_uneven_bars | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662048-4.html.csv | count | 2 gymnasts represented china ( chn ) at the 2008 summer olympics - women 's uneven bars . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '( chn )', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'gymnast', '( chn )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gymnast record fuzzily matches to ( chn ) .', 'tostr': 'filter_eq { all_rows ; gymnast ; ( chn ) }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; gymnast ; ( chn ) } }', 'tointer': 'select the rows whose gymnast record fuzzily matches to ( chn ) . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; gymnast ; ( chn ) } } ; 2 } = true', 'tointer': 'select the rows whose gymnast record fuzzily matches to ( chn ) . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; gymnast ; ( chn ) } } ; 2 } = true | select the rows whose gymnast record fuzzily matches to ( chn ) . 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, 'gymnast_5': 5, '(chn)_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', 'gymnast_5': 'gymnast', '(chn)_6': '( chn )', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'gymnast_5': [0], '(chn)_6': [0], '2_7': [2]} | ['position', 'gymnast', 'a score', 'b score', 'total'] | [['1', 'yang yilin ( chn )', '7.700', '8.950', '16.650'], ['2', 'ksenia semenova ( rus )', '7.400', '9.075', '16.475'], ['3', 'anastasia koval ( ukr )', '7.300', '9.025', '16.325'], ['4', 'steliana nistor ( rou )', '7.300', '8.675', '15.975'], ['5', 'nastia liukin ( usa )', '7.700', '8.250', '15.950'], ['6', 'he kexin ( chn )', '7.500', '8.225', '15.725'], ['7', 'dariya zgoba ( ukr )', '6.900', '8.875', '15.675'], ['8', 'beth tweddle ( gbr )', '7.600', '8.050', '15.650']] |
2010 - 11 dallas mavericks season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Dallas_Mavericks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27723526-17.html.csv | ordinal | the dallas mavericks ' game on may 31st was the earliest in the 2010 - 11 season . | {'row': '1', 'col': '2', 'order': '1', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'date', '1'], 'result': 'may 31', 'ind': 0, 'tostr': 'nth_min { all_rows ; date ; 1 }', 'tointer': 'the 1st minimum date record of all rows is may 31 .'}, 'may 31'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; date ; 1 } ; may 31 } = true', 'tointer': 'the 1st minimum date record of all rows is may 31 .'} | eq { nth_min { all_rows ; date ; 1 } ; may 31 } = true | the 1st minimum date record of all rows is may 31 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'date_4': 4, '1_5': 5, 'may 31_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'date_4': 'date', '1_5': '1', 'may 31_6': 'may 31'} | {'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'date_4': [0], '1_5': [0], 'may 31_6': [1]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'may 31', 'miami', 'l 84 - 92 ( ot )', 'dirk nowitzki ( 27 )', 'shawn marion ( 10 )', 'jason kidd ( 6 )', 'american airlines arena 20003', '0 - 1'], ['2', 'june 2', 'miami', 'w 95 - 93 ( ot )', 'dirk nowitzki ( 24 )', 'dirk nowitzki ( 11 )', 'jason kidd , jason terry ( 5 )', 'american airlines arena 20003', '1 - 1'], ['3', 'june 5', 'miami', 'l 86 - 88 ( ot )', 'dirk nowitzki ( 34 )', 'tyson chandler , dirk nowitzki ( 11 )', 'jason kidd ( 10 )', 'american airlines center 20340', '1 - 2'], ['4', 'june 7', 'miami', 'w 86 - 83 ( ot )', 'dirk nowitzki ( 21 )', 'tyson chandler ( 16 )', 'josé juan barea ( 4 )', 'american airlines center 20430', '2 - 2'], ['5', 'june 9', 'miami', 'w 112 - 103 ( ot )', 'dirk nowitzki ( 29 )', 'tyson chandler ( 7 )', 'jason kidd , jason terry ( 6 )', 'american airlines center 20433', '3 - 2']] |
nova scotia voyageurs | https://en.wikipedia.org/wiki/Nova_Scotia_Voyageurs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1166259-1.html.csv | ordinal | with 378 goals , 1982-83 was the nova scotia voyageurs highest scoring season . | {'row': '14', 'col': '7', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'goals against', '1'], 'result': '333', 'ind': 0, 'tostr': 'nth_max { all_rows ; goals against ; 1 }', 'tointer': 'the 1st maximum goals against record of all rows is 333 .'}, '333'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; goals against ; 1 } ; 333 }', 'tointer': 'the 1st maximum goals against record of all rows is 333 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'goals against', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; goals against ; 1 }'}, 'season'], 'result': '1982 - 83', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; goals against ; 1 } ; season }'}, '1982 - 83'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; goals against ; 1 } ; season } ; 1982 - 83 }', 'tointer': 'the season record of the row with 1st maximum goals against record is 1982 - 83 .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; goals against ; 1 } ; 333 } ; eq { hop { nth_argmax { all_rows ; goals against ; 1 } ; season } ; 1982 - 83 } } = true', 'tointer': 'the 1st maximum goals against record of all rows is 333 . the season record of the row with 1st maximum goals against record is 1982 - 83 .'} | and { eq { nth_max { all_rows ; goals against ; 1 } ; 333 } ; eq { hop { nth_argmax { all_rows ; goals against ; 1 } ; season } ; 1982 - 83 } } = true | the 1st maximum goals against record of all rows is 333 . the season record of the row with 1st maximum goals against record is 1982 - 83 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'goals against_8': 8, '1_9': 9, '333_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'goals against_12': 12, '1_13': 13, 'season_14': 14, '1982 - 83_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'goals against_8': 'goals against', '1_9': '1', '333_10': '333', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'goals against_12': 'goals against', '1_13': '1', 'season_14': 'season', '1982 - 83_15': '1982 - 83'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'goals against_8': [0], '1_9': [0], '333_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'goals against_12': [2], '1_13': [2], 'season_14': [3], '1982 - 83_15': [4]} | ['season', 'games', 'lost', 'tied', 'points', 'goals for', 'goals against', 'standing'] | [['1969 - 70', '72', '15', '14', '100', '327', '195', '1st , east'], ['1970 - 71', '72', '31', '14', '68', '215', '239', '2nd , east'], ['1971 - 72', '76', '21', '14', '96', '274', '202', '2nd , east'], ['1972 - 73', '76', '18', '15', '101', '316', '191', '1st , east'], ['1973 - 74', '76', '27', '12', '86', '263', '223', '3rd , north'], ['1974 - 75', '75', '26', '9', '89', '270', '227', '3rd , north'], ['1975 - 76', '76', '20', '8', '104', '326', '209', '1st , north'], ['1976 - 77', '80', '22', '6', '110', '308', '225', '1st , ahl'], ['1977 - 78', '81', '28', '16', '90', '304', '250', '2nd , north'], ['1978 - 79', '80', '37', '4', '82', '313', '302', '3rd , north'], ['1979 - 80', '79', '29', '7', '93', '331', '271', '2nd , north'], ['1980 - 81', '80', '37', '5', '81', '335', '298', '3rd , north'], ['1981 - 82', '80', '35', '10', '80', '330', '313', '3rd , north'], ['1982 - 83', '80', '34', '5', '87', '378', '333', '2nd , north'], ['1983 - 84', '80', '37', '11', '75', '277', '288', '4th , north']] |
bobby grim | https://en.wikipedia.org/wiki/Bobby_Grim | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252052-1.html.csv | aggregation | during the 1960s , driver bobby grim completed a total of 974 laps in the indianapolis 500 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '974', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'laps'], 'result': '974', 'ind': 0, 'tostr': 'sum { all_rows ; laps }'}, '974'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; laps } ; 974 } = true', 'tointer': 'the sum of the laps record of all rows is 974 .'} | round_eq { sum { all_rows ; laps } ; 974 } = true | the sum of the laps record of all rows is 974 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'laps_4': 4, '974_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '974_5': '974'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'laps_4': [0], '974_5': [1]} | ['year', 'start', 'qual', 'rank', 'finish', 'laps'] | [['1959', '5', '144.225', '6', '26', '85'], ['1960', '21', '143.158', '25', '16', '194'], ['1961', '24', '144.029', '33', '32', '26'], ['1962', '15', '146.604', '22', '19', '96'], ['1963', '20', '148.717', '19', '25', '79'], ['1964', '20', '151.038', '27', '10', '196'], ['1966', '31', '158.367', '33', '31', '0'], ['1967', '12', '164.084', '14', '13', '187'], ['1968', '25', '162.866', '25', '10', '196']] |
volleyball at the 2006 asian games | https://en.wikipedia.org/wiki/Volleyball_at_the_2006_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17877429-1.html.csv | comparative | at the 2006 asian games , japan won 2 more silver medals in volleyball than indonesia won . | {'row_1': '3', 'row_2': '5', 'col': '4', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'japan ( jpn )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to japan ( jpn ) .', 'tostr': 'filter_eq { all_rows ; nation ; japan ( jpn ) }'}, 'silver'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; japan ( jpn ) } ; silver }', 'tointer': 'select the rows whose nation record fuzzily matches to japan ( jpn ) . take the silver record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'indonesia ( ina )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to indonesia ( ina ) .', 'tostr': 'filter_eq { all_rows ; nation ; indonesia ( ina ) }'}, 'silver'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; indonesia ( ina ) } ; silver }', 'tointer': 'select the rows whose nation record fuzzily matches to indonesia ( ina ) . take the silver record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; nation ; japan ( jpn ) } ; silver } ; hop { filter_eq { all_rows ; nation ; indonesia ( ina ) } ; silver } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to japan ( jpn ) . take the silver record of this row . select the rows whose nation record fuzzily matches to indonesia ( ina ) . take the silver record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; nation ; japan ( jpn ) } ; silver } ; hop { filter_eq { all_rows ; nation ; indonesia ( ina ) } ; silver } } = true | select the rows whose nation record fuzzily matches to japan ( jpn ) . take the silver record of this row . select the rows whose nation record fuzzily matches to indonesia ( ina ) . take the silver 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, 'nation_7': 7, 'japan (jpn)_8': 8, 'silver_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'nation_11': 11, 'indonesia (ina)_12': 12, 'silver_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', 'nation_7': 'nation', 'japan (jpn)_8': 'japan ( jpn )', 'silver_9': 'silver', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'indonesia (ina)_12': 'indonesia ( ina )', 'silver_13': 'silver'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'nation_7': [0], 'japan (jpn)_8': [0], 'silver_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'nation_11': [1], 'indonesia (ina)_12': [1], 'silver_13': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'china ( chn )', '3', '2', '1', '6'], ['2', 'south korea ( kor )', '1', '0', '0', '1'], ['3', 'japan ( jpn )', '0', '2', '0', '2'], ['4', 'chinese taipei ( tpe )', '0', '0', '1', '1'], ['4', 'indonesia ( ina )', '0', '0', '1', '1'], ['4', 'saudi arabia ( ksa )', '0', '0', '1', '1'], ['total', 'total', '4', '4', '4', '12']] |
2005 new england patriots season | https://en.wikipedia.org/wiki/2005_New_England_Patriots_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10716255-4.html.csv | comparative | the patriots played against the carolina panthers earlier than the atlanta falcons in the 2005 new england patriots season . | {'row_1': '2', 'row_2': '5', 'col': '3', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'carolina panthers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to carolina panthers .', 'tostr': 'filter_eq { all_rows ; opponent ; carolina panthers }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; carolina panthers } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to carolina panthers . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'atlanta falcons'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to atlanta falcons .', 'tostr': 'filter_eq { all_rows ; opponent ; atlanta falcons }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; atlanta falcons } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to atlanta falcons . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; carolina panthers } ; date } ; hop { filter_eq { all_rows ; opponent ; atlanta falcons } ; date } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to carolina panthers . take the date record of this row . select the rows whose opponent record fuzzily matches to atlanta falcons . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; carolina panthers } ; date } ; hop { filter_eq { all_rows ; opponent ; atlanta falcons } ; date } } = true | select the rows whose opponent record fuzzily matches to carolina panthers . take the date record of this row . select the rows whose opponent record fuzzily matches to atlanta falcons . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'carolina panthers_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'atlanta falcons_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'carolina panthers_8': 'carolina panthers', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'atlanta falcons_12': 'atlanta falcons', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'carolina panthers_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'atlanta falcons_12': [1], 'date_13': [3]} | ['week', 'kickoff', 'date', 'opponent', 'result', 'record', 'game site', 'nflcom recap'] | [['1', '9:00 pm edt', 'september 8 , 2005', 'oakland raiders', 'w 30 - 20', '1 - 0', 'gillette stadium', 'recap'], ['2', '1:00 pm edt', 'september 18 , 2005', 'carolina panthers', 'l 17 - 27', '1 - 1', 'bank of america stadium', 'recap'], ['3', '4:15 pm edt', 'september 25 , 2005', 'pittsburgh steelers', 'w 23 - 20', '2 - 1', 'heinz field', 'recap'], ['4', '1:00 pm edt', 'october 2 , 2005', 'san diego chargers', 'l 17 - 41', '2 - 2', 'gillette stadium', 'recap'], ['5', '1:00 pm edt', 'october 9 , 2005', 'atlanta falcons', 'w 31 - 28', '3 - 2', 'georgia dome', 'recap'], ['6', '4:15 pm edt', 'october 16 , 2005', 'denver broncos', 'l 20 - 28', '3 - 3', 'invesco field at mile high', 'recap'], ['7', '-', '-', '-', '-', '-', '-', ''], ['8', '8:30 pm est', 'october 30 , 2005', 'buffalo bills', 'w 21 - 16', '4 - 3', 'gillette stadium', 'recap'], ['9', '9:00 pm est', 'november 7 , 2005', 'indianapolis colts', 'l 21 - 40', '4 - 4', 'gillette stadium', 'recap'], ['10', '1:00 pm est', 'november 13 , 2005', 'miami dolphins', 'w 23 - 16', '5 - 4', 'dolphins stadium', 'recap'], ['11', '1:00 pm est', 'november 20 , 2005', 'new orleans saints', 'w 24 - 17', '6 - 4', 'gillette stadium', 'recap'], ['12', '1:00 pm est', 'november 27 , 2005', 'kansas city chiefs', 'l 16 - 26', '6 - 5', 'arrowhead stadium', 'recap'], ['13', '4:15 pm est', 'december 4 , 2005', 'new york jets', 'w 16 - 3', '7 - 5', 'gillette stadium', 'recap'], ['14', '1:00 pm est', 'december 11 , 2005', 'buffalo bills', 'w 35 - 7', '8 - 5', 'ralph wilson stadium', 'recap'], ['15', '1:30 pm est', 'december 17 , 2005', 'tampa bay buccaneers', 'w 28 - 0', '9 - 5', 'gillette stadium', 'recap'], ['16', '9:00 pm est', 'december 26 , 2005', 'new york jets', 'w 31 - 21', '10 - 5', 'giants stadium', 'recap'], ['17', '1:00 pm est', 'january 1 , 2006', 'miami dolphins', 'l 26 - 28', '10 - 6', 'gillette stadium', 'recap']] |
2009 - 10 cleveland cavaliers season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Cleveland_Cavaliers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22654073-6.html.csv | unique | in only one game did lebron james tie with someone else for high points . | {'scope': 'all', 'row': '2', 'col': '9', 'col_other': '5', 'criterion': 'equal', 'value': '3 - 3', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'record', '3 - 3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose record record fuzzily matches to 3 - 3 .', 'tostr': 'filter_eq { all_rows ; record ; 3 - 3 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; record ; 3 - 3 } }', 'tointer': 'select the rows whose record record fuzzily matches to 3 - 3 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'record', '3 - 3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose record record fuzzily matches to 3 - 3 .', 'tostr': 'filter_eq { all_rows ; record ; 3 - 3 }'}, 'high points'], 'result': 'lebron james ( 25 )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; record ; 3 - 3 } ; high points }'}, 'lebron james ( 25 )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; record ; 3 - 3 } ; high points } ; lebron james ( 25 ) }', 'tointer': 'the high points record of this unqiue row is lebron james ( 25 ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; record ; 3 - 3 } } ; eq { hop { filter_eq { all_rows ; record ; 3 - 3 } ; high points } ; lebron james ( 25 ) } } = true', 'tointer': 'select the rows whose record record fuzzily matches to 3 - 3 . there is only one such row in the table . the high points record of this unqiue row is lebron james ( 25 ) .'} | and { only { filter_eq { all_rows ; record ; 3 - 3 } } ; eq { hop { filter_eq { all_rows ; record ; 3 - 3 } ; high points } ; lebron james ( 25 ) } } = true | select the rows whose record record fuzzily matches to 3 - 3 . there is only one such row in the table . the high points record of this unqiue row is lebron james ( 25 ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'record_7': 7, '3 - 3_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'high points_9': 9, 'lebron james (25)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'record_7': 'record', '3 - 3_8': '3 - 3', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'high points_9': 'high points', 'lebron james (25)_10': 'lebron james ( 25 )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'record_7': [0], '3 - 3_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'high points_9': [2], 'lebron james (25)_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['5', 'november 3', 'washington wizards', 'w 102 - 90 ( ot )', 'lebron james ( 27 )', 'anderson varejao ( 10 )', 'lebron james , mo williams ( 6 )', 'quicken loans arena 20562', '3 - 2'], ['6', 'november 5', 'chicago bulls', 'l 85 - 86 ( ot )', 'lebron james ( 25 )', 'anderson varejao ( 13 )', 'lebron james , mo williams ( 6 )', 'quicken loans arena 20562', '3 - 3'], ['7', 'november 6', 'new york knicks', 'w 100 - 91 ( ot )', 'lebron james ( 33 )', 'anderson varejao ( 14 )', 'lebron james ( 9 )', 'madison square garden 19763', '4 - 3'], ['8', 'november 11', 'orlando magic', 'w 102 - 93 ( ot )', 'lebron james ( 36 )', 'lebron james ( 8 )', 'mo williams ( 6 )', 'amway arena 17461', '5 - 3'], ['9', 'november 12', 'miami heat', 'w 111 - 104 ( ot )', 'lebron james ( 34 )', 'jamario moon ( 6 )', 'lebron james ( 7 )', 'american airlines arena 19600', '6 - 3'], ['10', 'november 14', 'utah jazz', 'w 107 - 103 ( ot )', 'lebron james , mo williams ( 21 )', 'lebron james , zydrunas ilgauskas ( 6 )', 'lebron james ( 9 )', 'quicken loans arena 20562', '7 - 3'], ['11', 'november 17', 'golden state warriors', 'w 114 - 108 ( ot )', 'lebron james ( 31 )', 'jj hickson ( 9 )', 'lebron james ( 12 )', 'quicken loans arena 20562', '8 - 3'], ['12', 'november 18', 'washington wizards', 'l 91 - 108 ( ot )', 'lebron james ( 34 )', 'zydrunas ilgauskas ( 9 )', 'lebron james ( 8 )', 'verizon center 20173', '8 - 4'], ['13', 'november 20', 'indiana pacers', 'w 105 - 95 ( ot )', 'lebron james ( 40 )', 'zydrunas ilgauskas ( 11 )', 'lebron james ( 7 )', 'conseco fieldhouse 18165', '9 - 4'], ['14', 'november 21', 'philadelphia 76ers', 'w 97 - 91 ( ot )', 'lebron james ( 32 )', 'zydrunas ilgauskas ( 8 )', 'lebron james ( 9 )', 'quicken loans arena 20562', '10 - 4'], ['15', 'november 25', 'detroit pistons', 'w 98 - 88 ( ot )', 'lebron james ( 34 )', 'lebron james , anderson varejão ( 8 )', 'mo williams ( 8 )', 'the palace of auburn hills 22076', '11 - 4'], ['16', 'november 27', 'charlotte bobcats', 'l 87 - 94 ( ot )', 'lebron james ( 25 )', 'anderson varejão ( 11 )', 'mo williams ( 6 )', 'time warner cable arena 19168', '11 - 5']] |
1949 vfl season | https://en.wikipedia.org/wiki/1949_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809351-7.html.csv | aggregation | the average crowd attendance at vfl games was 16667 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '16667', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '16667', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '16667'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 16667 } = true', 'tointer': 'the average of the crowd record of all rows is 16667 .'} | round_eq { avg { all_rows ; crowd } ; 16667 } = true | the average of the crowd record of all rows is 16667 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '16667_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '16667_5': '16667'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '16667_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '6.12 ( 48 )', 'south melbourne', '12.15 ( 87 )', 'glenferrie oval', '10000', '28 may 1949'], ['essendon', '11.9 ( 75 )', 'melbourne', '13.12 ( 90 )', 'windy hill', '15000', '28 may 1949'], ['north melbourne', '8.13 ( 61 )', 'geelong', '8.7 ( 55 )', 'arden street oval', '17000', '28 may 1949'], ['richmond', '21.21 ( 147 )', 'fitzroy', '9.12 ( 66 )', 'punt road oval', '28000', '28 may 1949'], ['footscray', '8.10 ( 58 )', 'collingwood', '12.15 ( 87 )', 'western oval', '17000', '28 may 1949'], ['st kilda', '8.14 ( 62 )', 'carlton', '14.11 ( 95 )', 'junction oval', '13000', '28 may 1949']] |
list of carnivàle episodes | https://en.wikipedia.org/wiki/List_of_Carniv%C3%A0le_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12722302-2.html.csv | count | in the list of carnivàle episodes , the number of episodes directed by jeremy podeswa is two . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'jeremy podeswa', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'jeremy podeswa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to jeremy podeswa .', 'tostr': 'filter_eq { all_rows ; directed by ; jeremy podeswa }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; jeremy podeswa } }', 'tointer': 'select the rows whose directed by record fuzzily matches to jeremy podeswa . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; jeremy podeswa } } ; 2 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to jeremy podeswa . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; directed by ; jeremy podeswa } } ; 2 } = true | select the rows whose directed by record fuzzily matches to jeremy podeswa . 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, 'directed by_5': 5, 'jeremy podeswa_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', 'directed by_5': 'directed by', 'jeremy podeswa_6': 'jeremy podeswa', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'jeremy podeswa_6': [0], '2_7': [2]} | ['no', 'title', 'directed by', 'written by', 'bens location', 'original air date', 'us viewers ( million )'] | [['1', 'milfay', 'rodrigo garcía', 'daniel knauf', 'milfay , oklahoma', 'september 14 , 2003', '5.3'], ['2', 'after the ball is over', 'jeremy podeswa', 'daniel knauf & ronald d moore', 'n / a', 'september 21 , 2003', '3.49'], ['4', 'black blizzard', 'peter medak', 'william schmidt', 'n / a', 'october 5 , 2003', '2.87'], ['5', 'babylon', 'tim hunter', 'dawn prestwich & nicole yorkin', 'babylon , texas', 'october 12 , 2003', '3.31'], ['6', 'pick a number', 'rodrigo garcía', 'ronald d moore', 'babylon , texas', 'october 19 , 2003', '3.40'], ['7', 'the river', 'alison maclean', 'toni graphia', 'texas', 'october 26 , 2003', '3.90'], ['8', 'lonnigan , texas', 'scott winant', 'daniel knauf', 'lonnigan , texas', 'november 2 , 2003', '2.96'], ['9', 'insomnia', 'jack bender', 'william schmidt', 'n / a', 'november 9 , 2003', '3.41'], ['10', 'hot and bothered', 'jeremy podeswa', 'dawn prestwich & nicole yorkin', 'loving , new mexico', 'november 16 , 2003', '3.19'], ['11', 'day of the dead', 'john patterson', 'toni graphia', 'loving , new mexico', 'november 23 , 2003', '2.56']] |
test matches ( 1991 - 2000 ) | https://en.wikipedia.org/wiki/Test_matches_%281991%E2%80%932000%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12410929-9.html.csv | comparative | the test matches that took place at the sydney cricket ground were the month before the test matches at the waca ground . | {'row_1': '3', 'row_2': '5', 'col': '1', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'sydney cricket ground'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to sydney cricket ground .', 'tostr': 'filter_eq { all_rows ; venue ; sydney cricket ground }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; venue ; sydney cricket ground } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to sydney cricket ground . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'waca ground'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose venue record fuzzily matches to waca ground .', 'tostr': 'filter_eq { all_rows ; venue ; waca ground }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; venue ; waca ground } ; date }', 'tointer': 'select the rows whose venue record fuzzily matches to waca ground . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; venue ; sydney cricket ground } ; date } ; hop { filter_eq { all_rows ; venue ; waca ground } ; date } } = true', 'tointer': 'select the rows whose venue record fuzzily matches to sydney cricket ground . take the date record of this row . select the rows whose venue record fuzzily matches to waca ground . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; venue ; sydney cricket ground } ; date } ; hop { filter_eq { all_rows ; venue ; waca ground } ; date } } = true | select the rows whose venue record fuzzily matches to sydney cricket ground . take the date record of this row . select the rows whose venue record fuzzily matches to waca ground . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'venue_7': 7, 'sydney cricket ground_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'venue_11': 11, 'waca ground_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'venue_7': 'venue', 'sydney cricket ground_8': 'sydney cricket ground', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'venue_11': 'venue', 'waca ground_12': 'waca ground', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'venue_7': [0], 'sydney cricket ground_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'venue_11': [1], 'waca ground_12': [1], 'date_13': [3]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['29 , 30 november , 1 , 2 december 1991', 'allan border', 'mohammad azharuddin', 'brisbane cricket ground', 'aus by 10 wkts'], ['26 , 27 , 28 , 29 december 1991', 'allan border', 'mohammad azharuddin', 'melbourne cricket ground', 'aus by 8 wkts'], ['2 , 3 , 4 , 5 , 6 january 1992', 'allan border', 'mohammad azharuddin', 'sydney cricket ground', 'draw'], ['25 , 26 , 27 , 28 , 29 january 1992', 'allan border', 'mohammad azharuddin', 'adelaide oval', 'aus by 38 runs'], ['1 , 2 , 3 , 4 , 5 february 1992', 'allan border', 'mohammad azharuddin', 'waca ground', 'aus by 300 runs']] |
man of la mancha | https://en.wikipedia.org/wiki/Man_of_La_Mancha | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-177860-1.html.csv | count | two of the awards that the play titled man of la mancha was nominated for in the year 1966 , the musical did not win . | {'scope': 'all', 'criterion': 'not_equal', 'value': 'won', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record does not match to won .', 'tostr': 'filter_not_eq { all_rows ; result ; won }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_not_eq { all_rows ; result ; won } }', 'tointer': 'select the rows whose result record does not match to won . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_not_eq { all_rows ; result ; won } } ; 2 } = true', 'tointer': 'select the rows whose result record does not match to won . the number of such rows is 2 .'} | eq { count { filter_not_eq { all_rows ; result ; won } } ; 2 } = true | select the rows whose result record does not match to won . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'won_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'won_6': 'won', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'won_6': [0], '2_7': [2]} | ['year', 'award ceremony', 'category', 'nominee', 'result'] | [['1966', 'tony award', 'best musical', 'best musical', 'won'], ['1966', 'tony award', 'best performance by a leading actor in a musical', 'richard kiley', 'won'], ['1966', 'tony award', 'best direction of a musical', 'albert marre', 'won'], ['1966', 'tony award', 'best original score', 'mitch leigh and joe darion', 'won'], ['1966', 'tony award', 'best choreography', 'jack cole', 'nominated'], ['1966', 'tony award', 'best scenic design', 'howard bay', 'won'], ['1966', 'tony award', 'best costume design', 'howard bay and patton campbell', 'nominated']] |
forbes global 2000 | https://en.wikipedia.org/wiki/Forbes_Global_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1682026-1.html.csv | superlative | wal-mart stores was the company that had the highest sales number in the forbes global 2000 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '16', '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', 'sales ( billion )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; sales ( billion ) }'}, 'company'], 'result': 'wal - mart stores', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; sales ( billion ) } ; company }'}, 'wal - mart stores'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; sales ( billion ) } ; company } ; wal - mart stores } = true', 'tointer': 'select the row whose sales ( billion ) record of all rows is maximum . the company record of this row is wal - mart stores .'} | eq { hop { argmax { all_rows ; sales ( billion ) } ; company } ; wal - mart stores } = true | select the row whose sales ( billion ) record of all rows is maximum . the company record of this row is wal - mart stores . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'sales (billion )_5': 5, 'company_6': 6, 'wal - mart stores_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'sales (billion )_5': 'sales ( billion )', 'company_6': 'company', 'wal - mart stores_7': 'wal - mart stores'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'sales (billion )_5': [0], 'company_6': [1], 'wal - mart stores_7': [2]} | ['rank', 'company', 'headquarters', 'industry', 'sales ( billion )', 'profits ( billion )', 'assets ( billion )', 'market value ( billion )'] | [['01 1', 'icbc', 'china', 'banking', '134.8', '37.8', '2813.5', '237.3'], ['02 2', 'china construction bank', 'china', 'banking', '113.1', '30.6', '2241.0', '202.0'], ['03 3', 'jpmorgan chase', 'united states', 'banking', '108.2', '21.3', '2359.1', '191.4'], ['04 4', 'general electric', 'united states', 'conglomerate', '147.4', '13.6', '685.3', '243.7'], ['05 5', 'exxon mobil', 'united states', 'oil and gas', '420.7', '44.9', '333.8', '400.4'], ['06 6', 'hsbc', 'united kingdom', 'banking', '104.9', '14.3', '2684.1', '201.3'], ['07 7', 'royal dutch shell', 'netherlands', 'oil and gas', '467.2', '26.6', '360.3', '213.1'], ['08 8', 'agricultural bank of china', 'china', 'banking', '103.0', '23.0', '2124.2', '150.8'], ['09 9', 'berkshire hathaway', 'united states', 'conglomerate', '162.5', '14.8', '427.5', '252.8'], ['09 9', 'petrochina', 'china', 'oil and gas', '308.9', '18.3', '347.8', '261.2'], ['11 11', 'bank of china', 'china', 'banking', '98.1', '22.1', '2033.8', '131.7'], ['12 12', 'wells fargo', 'united states', 'banking', '91.2', '18.9', '1423.0', '201.3'], ['13 13', 'chevron', 'united states', 'oil and gas', '222.6', '26.2', '233.0', '232.5'], ['14 14', 'volkswagen group', 'germany', 'automotive', '254.0', '28.6', '408.2', '94.4'], ['15 15', 'apple', 'united states', 'computer hardware', '164.7', '41.7', '196.1', '416.6'], ['15 15', 'wal - mart stores', 'united states', 'retail', '469.2', '17.0', '203.1', '242.5'], ['17 17', 'gazprom', 'russia', 'oil and gas', '144.0', '40.6', '339.3', '111.4'], ['18 18', 'bp', 'united kingdom', 'oil and gas', '370.9', '11.6', '301.0', '130.4'], ['19 19', 'citigroup', 'united states', 'banking', '90.7', '7.5', '1864.7', '143.6'], ['20 20', 'petrobras', 'brazil', 'oil and gas', '144.1', '11.0', '331.6', '120.7']] |
tripura legislative assembly election , 2008 | https://en.wikipedia.org/wiki/Tripura_Legislative_Assembly_election%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20728138-1.html.csv | superlative | of the parties contesting more than 40 seats in the 2008 tripura legislative assembly election , bharatiya janata party had the lowest number of votes . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '40'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'seats contested', '40'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; seats contested ; 40 }', 'tointer': 'select the rows whose seats contested record is greater than 40 .'}, 'no of votes'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_greater { all_rows ; seats contested ; 40 } ; no of votes }'}, 'party'], 'result': 'bharatiya janata party', 'ind': 2, 'tostr': 'hop { argmin { filter_greater { all_rows ; seats contested ; 40 } ; no of votes } ; party }'}, 'bharatiya janata party'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_greater { all_rows ; seats contested ; 40 } ; no of votes } ; party } ; bharatiya janata party } = true', 'tointer': 'select the rows whose seats contested record is greater than 40 . select the row whose no of votes record of these rows is minimum . the party record of this row is bharatiya janata party .'} | eq { hop { argmin { filter_greater { all_rows ; seats contested ; 40 } ; no of votes } ; party } ; bharatiya janata party } = true | select the rows whose seats contested record is greater than 40 . select the row whose no of votes record of these rows is minimum . the party record of this row is bharatiya janata party . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'seats contested_6': 6, '40_7': 7, 'no of votes_8': 8, 'party_9': 9, 'bharatiya janata party_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', 'seats contested_6': 'seats contested', '40_7': '40', 'no of votes_8': 'no of votes', 'party_9': 'party', 'bharatiya janata party_10': 'bharatiya janata party'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'seats contested_6': [0], '40_7': [0], 'no of votes_8': [1], 'party_9': [2], 'bharatiya janata party_10': [3]} | ['party', 'seats contested', 'seats won', 'no of votes', '% of votes', '% in seats contested', 'seats forfeited', '2003 seats'] | [['bharatiya janata party', '49', '0', '28102', '1.49 %', '1.79 %', '49', '0'], ['communist party of india', '2', '1', '27891', '1.48 %', '48.65 %', '0', '1'], ['communist party of india ( marxist )', '56', '46', '903009', '48.01 %', '51.21 %', '0', '38'], ['indian national congress', '48', '10', '684207', '36.38 %', '44.38 %', '1', '13'], ['nationalist congress party', '5', '0', '1882', '0.10 %', '0.92 %', '5', '0'], ['all india forward bloc', '12', '0', '2961', '0.16 %', '0.74 %', '12', '0'], ['all india trinamool congress', '22', '0', '6620', '0.35 %', '0.92 %', '22', '0'], ['indigenous nationalist party of twipra', '11', '1', '116761', '6.21 %', '38.23 %', '2', '6'], ['janata dal ( united )', '2', '0', '1081', '0.06 %', '1.74 %', '2', '0'], ['lok janshakti party', '8', '0', '2738', '0.15 %', '1.07 %', '8', '0'], ['revolutionary socialist party', '2', '2', '31717', '1.69 %', '52.58 %', '0', '2'], ['amra bangalee', '19', '0', '5532', '0.29 %', '0.96 %', '19', '0'], ['party of democratic socialism', '1', '0', '2062', '0.11 %', '6.13 %', '1', '0'], ['independents', '62', '0', '61010', '3.24 %', '4.94 %', '58', '0']] |
1962 - 63 illinois fighting illini men 's basketball team | https://en.wikipedia.org/wiki/1962%E2%80%9363_Illinois_Fighting_Illini_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22824297-1.html.csv | majority | most of the players on the 1962 - 63 illinois fighting illini men 's basketball team weigh under 200 pounds . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '200', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'weight', '200'], 'result': True, 'ind': 0, 'tointer': 'for the weight records of all rows , most of them are less than 200 .', 'tostr': 'most_less { all_rows ; weight ; 200 } = true'} | most_less { all_rows ; weight ; 200 } = true | for the weight records of all rows , most of them are less than 200 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'weight_3': 3, '200_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'weight_3': 'weight', '200_4': '200'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'weight_3': [0], '200_4': [0]} | ['no', 'player', 'hometown', 'class', 'position', 'height', 'weight'] | [['10', 'larry bauer', 'springfield , illinois', 'so', 'forward', '6 - 7', '207'], ['11', 'bob meadows', 'collinsville , illinois', 'so', 'guard', '5 - 7', '157'], ['12', 'tal brody', 'trenton , new jersey / central high school', 'so', 'guard', '6 - 2', '165'], ['14', 'john love', 'ottawa , illinois', 'jr', 'forward', '6 - 3', '199'], ['22', 'jay lovelace', 'carbondale , illinois', 'sr', 'guard', '6 - 0', '164'], ['25', 'bill burwell', 'brooklyn , new york / boys high school', 'sr', 'center', '6 - 8', '227'], ['30', 'jeff ferguson', 'benton , illinois', 'sr', 'forward', '6 - 3', '195'], ['31', 'tony latham', 'waukegan , illinois', 'so', 'guard', '6 - 10', '163'], ['32', 'bill edwards', 'windsor , illinois', 'jr', 'guard', '6 - 2', '208'], ['33', 'bogie redmon', 'collinsville , illinois', 'so', 'forward', '6 - 5', '218'], ['34', 'bill mckeown', 'clinton , illinois', 'so', 'guard', '6 - 2', '185'], ['35', 'skip thoren', 'rockford , illinois / rockford east high school', 'so', 'center', '6 - 8', '201'], ['40', 'dave downey', 'canton , illinois', 'sr', 'forward', '6 - 4', '204']] |
6 mm caliber | https://en.wikipedia.org/wiki/6_mm_caliber | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1058122-4.html.csv | majority | the majority of the 6 mm caliber cartilages has a base length of at lesat 11.5 mm . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '11.5', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'base', '11.5'], 'result': True, 'ind': 0, 'tointer': 'for the base records of all rows , most of them are greater than or equal to 11.5 .', 'tostr': 'most_greater_eq { all_rows ; base ; 11.5 } = true'} | most_greater_eq { all_rows ; base ; 11.5 } = true | for the base records of all rows , most of them are greater than or equal to 11.5 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'base_3': 3, '11.5_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'base_3': 'base', '11.5_4': '11.5'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'base_3': [0], '11.5_4': [0]} | ['name', 'bullet', 'length', 'base', 'shoulder', 'neck'] | [['6.5 x 50 sr arisaka', '6.705 ( 264 )', '50.39 ( 1.984 )', '11.35 ( 447 )', '10.59 ( 417 )', '7.34 ( 289 )'], ['6.5 x 53.5 r dutch mannlicher', '6.756 ( 266 )', '53.59 ( 2.110 )', '11.48 ( 453 )', '10.75 ( 423 )', '7.55 ( 297 )'], ['6.5 x54 mm mannlicher - schãnauer', '6.705 ( 264 )', '53.65 ( 2.112 )', '11.47 ( 452 )', '10.87 ( 428 )', '7.56 ( 288 )'], ['6.5 x55 mm swedish ( aka 6.5 x55 mm krag )', '6.7 ( 264 )', '54.864 ( 2.16 )', '12.17 ( 479 )', '10.688 ( 420 )', '7.468 ( 294 )'], ['6.5 x58 mm vergueiro', '6.65 ( 262 )', '57.85 ( 2.278 )', '11.88 ( 468 )', '10.94 ( 431 )', '7.56 ( 298 )'], ['6.5 x 68', '6.70 ( 264 )', '75.02 ( 2.956 )', '13.30 ( 524 )', '12.18 ( 480 )', '7.60 ( 299 )'], ['6.5 - 284', '6.70 ( 264 )', '55.118 ( 2.170 )', '12.725 ( 501 )', '12.065 ( 475 )', '7.544 ( 297 )'], ['.260 remington', '6.70 ( 264 )', '51.7 ( 2.035 )', '11.9 ( 470 )', '11.5 ( 454 )', '7.5 ( 297 )'], ['6.5 mm creedmoor', '6.70 ( 264 )', '48.8 ( 1.924 )', '11.9 ( 470 )', '11.7 ( 459 )', '7.54 ( 297 )'], ['6.5 x47 mm lapua', '6.70 ( 264 )', '47 ( 1.9 )', '11.95 ( 470 )', '11.53 ( 454 )', '7.41 ( 292 )'], ['6.5 mm grendel', '6.70 ( 264 )', '38.7 ( 1.524 )', '11.14 ( 439 )', '10.87 ( 428 )', '7.44 ( 293 )'], ['.264 win magnum', '6.70 ( 264 )', '64 ( 2.5 )', '13.1 ( 515 )', '12.5 ( 491 )', '7.6 ( 299 )'], ['6.5 x 52 mm carcano', '6.80 ( 268 )', '52.50 ( 2.067 )', '11.42 ( 450 )', '10.85 ( 427 )', '7.52 ( 296 )']] |
mikael pernfors | https://en.wikipedia.org/wiki/Mikael_Pernfors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1828774-4.html.csv | superlative | the first time mikael pernfors played in the finals on a hard surface , his opponent was andre agassi . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4,5', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'hard'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; hard }', 'tointer': 'select the rows whose surface record fuzzily matches to hard .'}, 'date'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; surface ; hard } ; date }'}, 'opponent in the final'], 'result': 'andre agassi', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; surface ; hard } ; date } ; opponent in the final }'}, 'andre agassi'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; surface ; hard } ; date } ; opponent in the final } ; andre agassi } = true', 'tointer': 'select the rows whose surface record fuzzily matches to hard . select the row whose date record of these rows is minimum . the opponent in the final record of this row is andre agassi .'} | eq { hop { argmin { filter_eq { all_rows ; surface ; hard } ; date } ; opponent in the final } ; andre agassi } = true | select the rows whose surface record fuzzily matches to hard . select the row whose date record of these rows is minimum . the opponent in the final record of this row is andre agassi . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'surface_6': 6, 'hard_7': 7, 'date_8': 8, 'opponent in the final_9': 9, 'andre agassi_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'surface_6': 'surface', 'hard_7': 'hard', 'date_8': 'date', 'opponent in the final_9': 'opponent in the final', 'andre agassi_10': 'andre agassi'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'surface_6': [0], 'hard_7': [0], 'date_8': [1], 'opponent in the final_9': [2], 'andre agassi_10': [3]} | ['outcome', 'date', 'championship', 'surface', 'opponent in the final', 'score in the final'] | [['runner - up', '26 may 1986', 'french open , paris , france', 'clay', 'ivan lendl', '3 - 6 , 2 - 6 , 4 - 6'], ['runner - up', '15 february 1988', 'memphis , usa', 'hard ( i )', 'andre agassi', '4 - 6 , 4 - 6 , 5 - 7'], ['winner', '19 september 1988', 'los angeles , usa', 'hard', 'andre agassi', '6 - 2 , 7 - 5'], ['winner', '3 october 1988', 'scottsdale , usa', 'hard', 'glenn layendecker', '6 - 2 , 6 - 4'], ['winner', '28 february 1993', 'montreal , canada', 'hard', 'todd martin', '2 - 6 , 6 - 2 , 7 - 5']] |
galina voskoboeva | https://en.wikipedia.org/wiki/Galina_Voskoboeva | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15272585-8.html.csv | ordinal | the game against matea mezak was the earliest tournament of galina voskoboeva 's career . | {'row': '1', 'col': '2', 'order': '1', 'col_other': '5', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 1 }'}, 'opponent'], 'result': 'matea mezak', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 1 } ; opponent }'}, 'matea mezak'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 1 } ; opponent } ; matea mezak } = true', 'tointer': 'select the row whose date record of all rows is 1st minimum . the opponent record of this row is matea mezak .'} | eq { hop { nth_argmin { all_rows ; date ; 1 } ; opponent } ; matea mezak } = true | select the row whose date record of all rows is 1st minimum . the opponent record of this row is matea mezak . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '1_6': 6, 'opponent_7': 7, 'matea mezak_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '1_6': '1', 'opponent_7': 'opponent', 'matea mezak_8': 'matea mezak'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '1_6': [0], 'opponent_7': [1], 'matea mezak_8': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', '28 january 2003', 'tipton', 'hard ( i )', 'matea mezak', '6 - 4 , 4 - 6 , 4 - 6'], ['winner', '29 june 2003', 'mont - de - marsan', 'hard ( i )', 'oleksandra kravets', '6 - 4 , 6 - 2'], ['runner - up', '3 october 2003', 'latina', 'clay', 'roberta vinci', '3 - 6 , 4 - 6'], ['runner - up', '8 november 2005', 'pittsburgh', 'hard', 'lilia osterloh', '6 - 7 , 4 - 6'], ['winner', '6 june 2006', 'cuneo , italy', 'clay', 'alice canepa', '6 - 1 , 6 - 2']] |
united states house of representatives elections , 1942 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1942 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342256-10.html.csv | count | 4 incumbents were re - elected during the 1942 united states house of representatives elections . | {'scope': 'all', 'criterion': 'equal', 'value': 're-elected', 'result': '4', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re-elected .', 'tostr': 'filter_eq { all_rows ; result ; re-elected }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; re-elected } }', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; re-elected } } ; 4 } = true', 'tointer': 'select the rows whose result record fuzzily matches to re-elected . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; result ; re-elected } } ; 4 } = true | select the rows whose result record fuzzily matches to re-elected . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're-elected_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're-elected_6': 're-elected', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're-elected_6': [0], '4_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['florida 1', 'j hardin peterson', 'democratic', '1932', 're - elected', 'j hardin peterson ( d ) unopposed'], ['florida 2', 'robert a green', 'democratic', '1932', 'ran in at - large district democratic hold', 'emory h price ( d ) unopposed'], ['florida 3', 'robert l f sikes', 'democratic', '1940', 're - elected', 'robert l f sikes ( d ) unopposed'], ['florida 4', 'pat cannon', 'democratic', '1938', 're - elected', 'pat cannon ( d ) 81.4 % bert leigh acker ( r ) 18.6 %'], ['florida 5', 'joe hendricks', 'democratic', '1936', 're - elected', 'joe hendricks ( d ) 70.9 % emory akerman ( r ) 29.1 %']] |
russian football premier league | https://en.wikipedia.org/wiki/Russian_Football_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1167698-1.html.csv | count | spartak moscow was the champion of the russian football premier league seven times . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'spartak moscow', 'result': '7', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'champion', 'spartak moscow'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose champion record fuzzily matches to spartak moscow .', 'tostr': 'filter_eq { all_rows ; champion ; spartak moscow }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; champion ; spartak moscow } }', 'tointer': 'select the rows whose champion record fuzzily matches to spartak moscow . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; champion ; spartak moscow } } ; 7 } = true', 'tointer': 'select the rows whose champion record fuzzily matches to spartak moscow . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; champion ; spartak moscow } } ; 7 } = true | select the rows whose champion record fuzzily matches to spartak moscow . 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, 'champion_5': 5, 'spartak moscow_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', 'champion_5': 'champion', 'spartak moscow_6': 'spartak moscow', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'champion_5': [0], 'spartak moscow_6': [0], '7_7': [2]} | ['season', 'champion', 'runner - up', 'third place', 'top scorer'] | [['1994', 'spartak moscow ( 3 )', 'dynamo moscow', 'lokomotiv moscow', 'igor simutenkov ( dinamo moscow , 21 goals )'], ['1995', 'alania vladikavkaz', 'lokomotiv moscow', 'spartak moscow', 'oleg veretennikov ( rotor volgograd , 25 goals )'], ['1996', 'spartak moscow ( 4 )', 'alania vladikavkaz', 'rotor volgograd', 'aleksandr maslov ( rostselmash , 23 goals )'], ['1997', 'spartak moscow ( 5 )', 'rotor volgograd', 'dynamo moscow', 'oleg veretennikov ( rotor volgograd , 22 goals )'], ['1998', 'spartak moscow ( 6 )', 'cska moscow', 'lokomotiv moscow', 'oleg veretennikov ( rotor volgograd , 22 goals )'], ['1999', 'spartak moscow ( 7 )', 'lokomotiv moscow', 'cska moscow', 'georgi demetradze ( alania vladikavkaz , 21 goals )'], ['2000', 'spartak moscow ( 8 )', 'lokomotiv moscow', 'torpedo moscow', 'dmitri loskov ( lokomotiv moscow , 18 goals )'], ['2001', 'spartak moscow ( 9 )', 'lokomotiv moscow', 'zenit saint petersburg', 'dmitri vyazmikin ( torpedo moscow , 18 goals )'], ['2003', 'cska moscow', 'zenit saint petersburg', 'rubin kazan', 'dmitri loskov ( lokomotiv moscow , 14 goals )'], ['2005', 'cska moscow ( 2 )', 'spartak moscow', 'lokomotiv moscow', 'dmitri kirichenko ( fc moscow , 14 goals )'], ['2006', 'cska moscow ( 3 )', 'spartak moscow', 'lokomotiv moscow', 'roman pavlyuchenko ( spartak moscow , 18 goals )'], ['2008', 'rubin kazan', 'cska moscow', 'dynamo moscow', 'vã ¡ gner love ( cska moscow , 20 goals )'], ['2009', 'rubin kazan ( 2 )', 'spartak moscow', 'zenit saint petersburg', 'welliton ( spartak moscow , 21 goals )'], ['2010', 'zenit saint petersburg ( 2 )', 'cska moscow', 'rubin kazan', 'welliton ( spartak moscow , 19 goals )']] |
2005 open championship | https://en.wikipedia.org/wiki/2005_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16225902-5.html.csv | superlative | tiger woods had the highest number to par during the 2005 open championship . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'to par'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; to par }'}, 'player'], 'result': 'tiger woods', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; to par } ; player }'}, 'tiger woods'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; to par } ; player } ; tiger woods } = true', 'tointer': 'select the row whose to par record of all rows is maximum . the player record of this row is tiger woods .'} | eq { hop { argmax { all_rows ; to par } ; player } ; tiger woods } = true | select the row whose to par record of all rows is maximum . the player record of this row is tiger woods . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'to par_5': 5, 'player_6': 6, 'tiger woods_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'to par_5': 'to par', 'player_6': 'player', 'tiger woods_7': 'tiger woods'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'to par_5': [0], 'player_6': [1], 'tiger woods_7': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'tiger woods', 'united states', '66 + 67 = 133', '11'], ['2', 'colin montgomerie', 'scotland', '71 + 66 = 137', '7'], ['t3', 'robert allenby', 'australia', '70 + 68 = 138', '6'], ['t3', 'brad faxon', 'united states', '72 + 66 = 138', '6'], ['t3', 'trevor immelman', 'south africa', '68 + 70 = 138', '6'], ['t3', 'peter lonard', 'australia', '68 + 70 = 138', '6'], ['t3', 'josé maría olazábal', 'spain', '68 + 70 = 138', '6'], ['t3', 'vijay singh', 'fiji', '69 + 69 = 138', '6'], ['t3', 'scott verplank', 'united states', '68 + 70 = 138', '6'], ['t10', 'bart bryant', 'united states', '69 + 70 = 139', '5'], ['t10', 'fred couples', 'united states', '68 + 71 = 139', '5'], ['t10', 'sergio garcía', 'spain', '70 + 69 = 139', '5'], ['t10', 'simon khan', 'england', '69 + 70 = 139', '5'], ['t10', 'bo van pelt', 'united states', '72 + 67 = 139', '5']] |
national assembly for wales election , 2011 | https://en.wikipedia.org/wiki/National_Assembly_for_Wales_election%2C_2011 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11099297-2.html.csv | unique | october 27 , 2010 , was the only time in the national assembly for wales election , that the percentage for cons was 18 % . | {'scope': 'all', 'row': '8', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '18 %', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cons', '18 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cons record fuzzily matches to 18 % .', 'tostr': 'filter_eq { all_rows ; cons ; 18 % }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; cons ; 18 % } }', 'tointer': 'select the rows whose cons record fuzzily matches to 18 % . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cons', '18 %'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cons record fuzzily matches to 18 % .', 'tostr': 'filter_eq { all_rows ; cons ; 18 % }'}, 'date ( s ) conducted'], 'result': '27 october 2010', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; cons ; 18 % } ; date ( s ) conducted }'}, '27 october 2010'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; cons ; 18 % } ; date ( s ) conducted } ; 27 october 2010 }', 'tointer': 'the date ( s ) conducted record of this unqiue row is 27 october 2010 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; cons ; 18 % } } ; eq { hop { filter_eq { all_rows ; cons ; 18 % } ; date ( s ) conducted } ; 27 october 2010 } } = true', 'tointer': 'select the rows whose cons record fuzzily matches to 18 % . there is only one such row in the table . the date ( s ) conducted record of this unqiue row is 27 october 2010 .'} | and { only { filter_eq { all_rows ; cons ; 18 % } } ; eq { hop { filter_eq { all_rows ; cons ; 18 % } ; date ( s ) conducted } ; 27 october 2010 } } = true | select the rows whose cons record fuzzily matches to 18 % . there is only one such row in the table . the date ( s ) conducted record of this unqiue row is 27 october 2010 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'cons_7': 7, '18%_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date (s) conducted_9': 9, '27 october 2010_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'cons_7': 'cons', '18%_8': '18 %', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date (s) conducted_9': 'date ( s ) conducted', '27 october 2010_10': '27 october 2010'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'cons_7': [0], '18%_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date (s) conducted_9': [2], '27 october 2010_10': [3]} | ['date ( s ) conducted', 'cons', 'plaid cymru', 'lib dem', 'ukip', 'green', 'others', 'lead'] | [['5 may 2011', '22.5 %', '17.9 %', '8.0 %', '4.6 %', '3.4 %', '6.7 %', '14.4 %'], ['14 april 2011', '20 %', '18 %', '8 %', '4 %', '2 %', '4 %', '24 %'], ['30 march 2011', '20 %', '16 %', '8 %', '6 %', '2 %', '2 %', '25 %'], ['8 march 2011', '20 %', '18 %', '5 %', '5 %', '4 %', '2 %', '25 %'], ['26 january 2011', '20 %', '21 %', '8 %', '4 %', '2 %', '4 %', '21 %'], ['22 december 2010', '22 %', '21 %', '5 %', '5 %', '3 %', '2 %', '20 %'], ['24 november 2010', '20 %', '20 %', '9 %', '4 %', '3 %', '4 %', '21 %'], ['27 october 2010', '18 %', '23 %', '9 %', '6 %', '2 %', '3 %', '21 %'], ['3 may 2007', '21.4 %', '21.0 %', '11.7 %', '4.0 %', '3.5 %', '8.8 %', '8.6 %']] |
volleyball at the 2002 asian games | https://en.wikipedia.org/wiki/Volleyball_at_the_2002_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17978030-6.html.csv | count | 2 volley ball games took place each day on oct 3rd , 5th and 6th at the 2002 asian games . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'oct', 'result': '6', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'oct'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to oct .', 'tostr': 'filter_eq { all_rows ; date ; oct }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; oct } }', 'tointer': 'select the rows whose date record fuzzily matches to oct . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; oct } } ; 6 } = true', 'tointer': 'select the rows whose date record fuzzily matches to oct . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; date ; oct } } ; 6 } = true | select the rows whose date record fuzzily matches to oct . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'oct_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'oct_6': 'oct', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'oct_6': [0], '6_7': [2]} | ['date', 'time', 'score', 'set 1', 'set 2', 'set 3', 'total'] | [['03 oct', '12:00', '1 - 3', '25 - 21', '20 - 25', '16 - 25', '83 - 96'], ['03 oct', '14:00', '0 - 3', '18 - 25', '19 - 25', '26 - 28', '63 - 78'], ['05 oct', '12:00', '3 - 1', '29 - 27', '25 - 23', '24 - 26', '103 - 96'], ['05 oct', '14:00', '3 - 0', '25 - 16', '25 - 18', '25 - 13', '75 - 47'], ['06 oct', '10:00', '1 - 3', '16 - 25', '16 - 25', '25 - 17', '78 - 92'], ['06 oct', '12:00', '2 - 3', '21 - 25', '18 - 25', '25 - 21', '99 - 105']] |
2007 - 08 rangers f.c. season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Rangers_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11221038-3.html.csv | majority | most of the players that left rangers f.c. during the 2007 - 08 season did so because it was the end of their contract . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'end of contract', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'type', 'end of contract'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , most of them fuzzily match to end of contract .', 'tostr': 'most_eq { all_rows ; type ; end of contract } = true'} | most_eq { all_rows ; type ; end of contract } = true | for the type records of all rows , most of them fuzzily match to end of contract . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'end of contract_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'end of contract_4': 'end of contract'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'end of contract_4': [0]} | ['nat', 'name', 'moving to', 'type', 'transfer window', 'transfer fee'] | [['sco', 'martin ure', "queen 's park", 'end of contract', 'summer', 'n / a'], ['sco', 'scott hadden', 'ross county', 'end of contract', 'summer', 'n / a'], ['sco', 'steven campbell', 'free agent', 'end of contract', 'summer', 'n / a'], ['england', 'joe sagar', 'free agent', 'end of contract', 'summer', 'n / a'], ['sen', "makhtar n'diaye", 'free agent', 'end of contract', 'summer', 'n / a'], ['fra', 'antoine ponroy', 'free agent', 'end of contract', 'summer', 'n / a'], ['ger', 'stefan klos', 'retired', 'end of contract', 'summer', 'n / a'], ['croatia', 'dado pršo', 'retired', 'end of contract', 'summer', 'n / a'], ['sco', 'gavin rae', 'cardiff city', 'end of contract', 'summer', 'n / a'], ['sco', 'brian gilmour', 'queen of the south', 'end of contract', 'summer', 'n / a'], ['swe', 'karl svensson', 'caen', 'transfer', 'summer', '0.7 m'], ['eng', 'lee robinson', 'greenock morton', 'loan', 'summer', 'n / a'], ['cze', 'libor sionko', 'copenhagen', 'transfer', 'summer', '0.09 m'], ['slovakia', 'filip šebo', 'valenciennes', 'loan', 'summer', 'n / a'], ['sco', 'ian murray', 'norwich city', 'transfer', 'summer', 'free'], ['eng', 'ugo ehiogu', 'sheffield united', 'transfer', 'winter', 'free'], ['sco', 'alan hutton', 'tottenham hotspur', 'transfer', 'winter', '9 m'], ['nir', 'roy carroll', 'derby county', 'transfer', 'winter', 'free']] |
ekaterina ivanova ( tennis ) | https://en.wikipedia.org/wiki/Ekaterina_Ivanova_%28tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15272102-3.html.csv | count | in tournaments that ekaterina ivanova played in , there were 5 occasions where the surface was clay . | {'scope': 'all', 'criterion': 'equal', 'value': 'clay', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; surface ; clay } }', 'tointer': 'select the rows whose surface record fuzzily matches to clay . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; surface ; clay } } ; 5 } = true', 'tointer': 'select the rows whose surface record fuzzily matches to clay . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; surface ; clay } } ; 5 } = true | select the rows whose surface record fuzzily matches to clay . 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, 'surface_5': 5, 'clay_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', 'surface_5': 'surface', 'clay_6': 'clay', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'clay_6': [0], '5_7': [2]} | ['date', 'tournament', 'surface', 'partner', 'opponent in the final', 'score'] | [['aug 08 , 2005', 'moscow , russia', 'clay', 'olga panova', 'anna bastrikova vasilisa davydova', '7 - 5 , 6 - 3'], ['sept 18 , 2006', 'lecce , italy', 'clay', 'teodora mirčić', 'kildine chevalier adriana serra zanetti', '7 - 6 ( 4 ) , 6 - 4'], ['apr 23 , 2007', 'torrent , spain', 'clay', 'evgeniya rodina', 'marta marrero carla suárez navarro', '7 - 6 ( 7 ) , 3 - 6 , 6 - 2'], ['feb 16 , 2009', 'surprise , usa', 'hard', 'jorgelina cravero', 'ahsha rolle yanina wickmayer', '6 - 1 , 6 - 1'], ['aug 03 , 2009', 'moscow , russia', 'clay', 'arina rodionova', 'veronika kapshay melanie klaffner', '7 - 6 ( 7 ) , 3 - 6 , 6 - 2'], ['aug 10 , 2009', 'moscow , russia', 'clay', 'arina rodionova', 'valeria savinykh marina shamayko', '6 - 3 , 6 - 3']] |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16494599-3.html.csv | count | two of the players on the roster had the position point guard . | {'scope': 'all', 'criterion': 'equal', 'value': 'point guard', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'point guard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to point guard .', 'tostr': 'filter_eq { all_rows ; position ; point guard }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; point guard } }', 'tointer': 'select the rows whose position record fuzzily matches to point guard . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; point guard } } ; 2 } = true', 'tointer': 'select the rows whose position record fuzzily matches to point guard . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; position ; point guard } } ; 2 } = true | select the rows whose position record fuzzily matches to point guard . 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, 'position_5': 5, 'point guard_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', 'position_5': 'position', 'point guard_6': 'point guard', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'point guard_6': [0], '2_7': [2]} | ['player', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['brian cardinal', 'united states', 'forward', '2004 - 2008', 'purdue'], ['rodney carney', 'united states', 'forward', '2011', 'memphis'], ['antoine carr', 'united states', 'forward / center', '1999 - 2000', 'wichita state'], ['demarre carroll', 'united states', 'forward', '2009 - 2012', 'missouri'], ['pete chilcutt', 'united states', 'power forward', '1996 - 1999', 'north carolina'], ['jason collins', 'united states', 'center', '2008', 'stanford'], ['mike conley , jr', 'united states', 'point guard', '2007present', 'ohio state'], ['will conroy', 'united states', 'guard', '2007', 'washington'], ['javaris crittenton', 'united states', 'point guard', '2008', 'georgia tech'], ['dante cunningham', 'united states', 'forward', '2011 - 2012', 'villanova']] |
disk loading | https://en.wikipedia.org/wiki/Disk_loading | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10006830-1.html.csv | ordinal | mil mi - 26 aircraft has the highest max gross weight among those described as heavy - lift helicopter . | {'scope': 'subset', 'row': '4', 'col': '3', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'heavy - lift helicopter'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'description', 'heavy - lift helicopter'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; description ; heavy - lift helicopter }', 'tointer': 'select the rows whose description record fuzzily matches to heavy - lift helicopter .'}, 'max gross weight', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; description ; heavy - lift helicopter } ; max gross weight ; 1 }'}, 'aircraft'], 'result': 'mil mi - 26', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; description ; heavy - lift helicopter } ; max gross weight ; 1 } ; aircraft }'}, 'mil mi - 26'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; description ; heavy - lift helicopter } ; max gross weight ; 1 } ; aircraft } ; mil mi - 26 } = true', 'tointer': 'select the rows whose description record fuzzily matches to heavy - lift helicopter . select the row whose max gross weight record of these rows is 1st maximum . the aircraft record of this row is mil mi - 26 .'} | eq { hop { nth_argmax { filter_eq { all_rows ; description ; heavy - lift helicopter } ; max gross weight ; 1 } ; aircraft } ; mil mi - 26 } = true | select the rows whose description record fuzzily matches to heavy - lift helicopter . select the row whose max gross weight record of these rows is 1st maximum . the aircraft record of this row is mil mi - 26 . | 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, 'description_6': 6, 'heavy - lift helicopter_7': 7, 'max gross weight_8': 8, '1_9': 9, 'aircraft_10': 10, 'mil mi - 26_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', 'description_6': 'description', 'heavy - lift helicopter_7': 'heavy - lift helicopter', 'max gross weight_8': 'max gross weight', '1_9': '1', 'aircraft_10': 'aircraft', 'mil mi - 26_11': 'mil mi - 26'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'description_6': [0], 'heavy - lift helicopter_7': [0], 'max gross weight_8': [1], '1_9': [1], 'aircraft_10': [2], 'mil mi - 26_11': [3]} | ['aircraft', 'description', 'max gross weight', 'total disk area', 'max disk loading'] | [['robinson r - 22', 'light utility helicopter', '1370 lb ( 635 kg )', '497 ft square ( 46.2 m square )', '2.6 lb / ft square ( 14 kg / m square )'], ['bell 206b3 jetranger', 'turboshaft utility helicopter', '3200 lb ( 1451 kg )', '872 ft square ( 81.1 m square )', '3.7 lb / ft square ( 18 kg / m square )'], ['ch - 47d chinook', 'tandem rotor helicopter', '50000 lb ( 22680 kg )', '5655 ft square ( 526 m square )', '8.8 lb / ft square ( 43 kg / m square )'], ['mil mi - 26', 'heavy - lift helicopter', '123500 lb ( 56000 kg )', '8495 ft square ( 789 m square )', '14.5 lb / ft square ( 71 kg / m square )'], ['ch - 53e super stallion', 'heavy - lift helicopter', '73500 lb ( 33300 kg )', '4900 ft square ( 460 m square )', '15 lb / ft square ( 72 kg / m square )']] |
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 | majority | the majority of seattle supersonics all time players were from the us . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'nationality', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the nationality records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; nationality ; united states } = true'} | most_eq { all_rows ; nationality ; united states } = true | for the nationality records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'united states_4': [0]} | ['player', 'nationality', 'jersey number ( s )', 'position', 'years', 'from'] | [['mark radford', 'united states', '30', 'pg / sg', '1981 - 1983', 'oregon state'], ['vladimir radmanović', 'serbia', '77', 'sf / pf', '2001 - 2006', 'kk fmp'], ['jerry reynolds', 'united states', '35', 'sg / sf', '1988 - 1989', 'louisiana state'], ['luke ridnour', 'united states', '8', 'pg', '2003 - 2008', 'oregon'], ['jackie robinson', 'united states', '22', 'sf', '1979', 'unlv'], ['bob rule', 'united states', '45', 'pf / c', '1967 - 1971', 'colorado state']] |
carlos andino | https://en.wikipedia.org/wiki/Carlos_Andino | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16055831-2.html.csv | superlative | osvaldo castuera is carlos andino 's newest vale tudo fight opponent . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '8', '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', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; date }'}, 'opponent'], 'result': 'osvaldo castuera', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; date } ; opponent }'}, 'osvaldo castuera'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; date } ; opponent } ; osvaldo castuera } = true', 'tointer': 'select the row whose date record of all rows is maximum . the opponent record of this row is osvaldo castuera .'} | eq { hop { argmax { all_rows ; date } ; opponent } ; osvaldo castuera } = true | select the row whose date record of all rows is maximum . the opponent record of this row is osvaldo castuera . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, 'opponent_6': 6, 'osvaldo castuera_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'date_5': 'date', 'opponent_6': 'opponent', 'osvaldo castuera_7': 'osvaldo castuera'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], 'opponent_6': [1], 'osvaldo castuera_7': [2]} | ['result', 'record', 'opponent', 'method', 'date', 'round', 'location', 'notes'] | [['win', '1 - 0 - 0', 'joa mendes', 'knockout ( strikes )', '1995', '1', 'itapeua , brazil', 'vale tudo'], ['win', '2 - 0 - 0', 'larry reynolds', 'knockout ( strikes )', '1995', '1', 'itapeua , brazil', 'vale tudo'], ['win', '3 - 0 - 0', 'héctor rodríguez', 'knockout ( strikes )', '1995', '1', 'itapeua , brazil', 'vale tudo'], ['win', '4 - 0 - 0', 'larry reynolds', 'knockout ( strikes )', '1996', '1', 'itapeua , brazil', 'vale tudo'], ['win', '5 - 0 - 0', 'luigi maiolini', 'knockout ( strikes )', '1999', '1', 'itapeua , brazil', 'vale tudo'], ['loss', '5 - 1 - 0', 'junior pitbull', 'knockout ( strikes )', '2003', '1', 'itapeua , brazil', 'vale tudo'], ['loss', '5 - 2 - 0', 'zuluzinho', 'knockout ( strikes )', '4 november 2003', '1', 'itapeua , brazil', 'vale tudo'], ['loss', '5 - 3 - 0', 'osvaldo castuera', 'submission ( armbar )', '2007', '1', 'itapeua , brazil', 'vale tudo']] |
1988 green bay packers season | https://en.wikipedia.org/wiki/1988_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14650373-1.html.csv | aggregation | the average pick number for the 1988 green bay packers was 114 . | {'scope': 'all', 'col': '1', 'type': 'average', 'result': '114', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pick'], 'result': '114', 'ind': 0, 'tostr': 'avg { all_rows ; pick }'}, '114'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pick } ; 114 } = true', 'tointer': 'the average of the pick record of all rows is 114 .'} | round_eq { avg { all_rows ; pick } ; 114 } = true | the average of the pick record of all rows is 114 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pick_4': 4, '114_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pick_4': 'pick', '114_5': '114'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pick_4': [0], '114_5': [1]} | ['pick', 'nfl team', 'player', 'position', 'college'] | [['7', 'green bay packers', 'sterling sharpe', 'wide receiver', 'south carolina'], ['34', 'green bay packers', 'shawn patterson', 'defensive end', 'arizona state'], ['61', 'green bay packers', 'keith woodside', 'running back', 'texas a & m'], ['88', 'green bay packers', 'rollin putzier', 'nose tackle', 'oregon'], ['89', 'green bay packers', 'chuck cecil', 'safety', 'arizona'], ['144', 'green bay packers', 'nate hill', 'defensive end', 'auburn'], ['173', 'green bay packers', 'gary richard', 'cornerback', 'pittsburgh'], ['200', 'green bay packers', 'patrick collins', 'running back', 'oklahoma'], ['228', 'green bay packers', 'neal wilkinson', 'tight end', 'james madison']] |
1993 - 94 manchester united f.c. season | https://en.wikipedia.org/wiki/1993%E2%80%9394_Manchester_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18223552-5.html.csv | count | there are 3 away games in the 1993-94 manchester united f.c. season . | {'scope': 'all', 'criterion': 'equal', 'value': 'a', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'h / a', 'a'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose h / a record fuzzily matches to a .', 'tostr': 'filter_eq { all_rows ; h / a ; a }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; h / a ; a } }', 'tointer': 'select the rows whose h / a record fuzzily matches to a . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; h / a ; a } } ; 3 } = true', 'tointer': 'select the rows whose h / a record fuzzily matches to a . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; h / a ; a } } ; 3 } = true | select the rows whose h / a record fuzzily matches to a . 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, 'h / a_5': 5, 'a_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', 'h / a_5': 'h / a', 'a_6': 'a', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'h / a_5': [0], 'a_6': [0], '3_7': [2]} | ['date', 'round', 'opponents', 'h / a', 'result f - a', 'attendance'] | [['9 january 1994', 'round 3', 'sheffield united', 'a', '1 - 0', '22019'], ['30 january 1994', 'round 4', 'norwich city', 'a', '2 - 0', '21060'], ['20 february 1994', 'round 5', 'wimbledon', 'a', '3 - 0', '27511'], ['12 march 1994', 'round 6', 'charlton athletic', 'h', '3 - 1', '44347'], ['10 april 1994', 'semi - final', 'oldham athletic', 'n', '1 - 1', '56399'], ['13 april 1994', 'semi - final replay', 'oldham athletic', 'n', '4 - 1', '32311'], ['14 may 1994', 'final', 'chelsea', 'n', '4 - 0', '79634']] |
1986 san francisco 49ers season | https://en.wikipedia.org/wiki/1986_San_Francisco_49ers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16714751-1.html.csv | count | the san francisco 49ers won 10 of the games . | {'scope': 'all', 'criterion': 'equal', 'value': 'w', 'result': '10', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; result ; w }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; result ; w } }', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; result ; w } } ; 10 } = true', 'tointer': 'select the rows whose result record fuzzily matches to w . the number of such rows is 10 .'} | eq { count { filter_eq { all_rows ; result ; w } } ; 10 } = true | select the rows whose result record fuzzily matches to w . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 'w_6': 6, '10_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 'w_6': 'w', '10_7': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 'w_6': [0], '10_7': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 7 , 1986', 'tampa bay buccaneers', 'w 31 - 7', '50780'], ['2', 'september 14 , 1986', 'los angeles rams', 'l 13 - 16', '65195'], ['3', 'september 21 , 1986', 'new orleans saints', 'w 26 - 17', '58297'], ['4', 'september 28 , 1986', 'miami dolphins', 'w 31 - 16', '70264'], ['5', 'october 5 , 1986', 'indianapolis colts', 'w 35 - 15', '57252'], ['6', 'october 12 , 1986', 'minnesota vikings', 'l 24 - 27 ( ot )', '58637'], ['7', 'october 19 , 1986', 'atlanta falcons', 't 10 - 10 ( ot )', '55306'], ['8', 'october 26 , 1986', 'green bay packers ( at milwaukee )', 'w 31 - 17', '50557'], ['9', 'november 2 , 1986', 'new orleans saints', 'l 10 - 23', '53234'], ['10', 'november 9 , 1986', 'st louis cardinals', 'w 43 - 17', '59172'], ['11', 'november 17 , 1986 ( mon )', 'washington redskins', 'l 6 - 14', '54774'], ['12', 'november 23 , 1986', 'atlanta falcons', 'w 20 - 0', '58747'], ['13', 'december 1 , 1986 ( mon )', 'new york giants', 'l 17 - 21', '59777'], ['14', 'december 7 , 1986', 'new york jets', 'w 24 - 10', '58091'], ['15', 'december 14 , 1986', 'new england patriots', 'w 29 - 24', '60787'], ['16', 'december 19 , 1986 ( fri )', 'los angeles rams', 'w 24 - 14', '60366']] |
list of european ultra prominent peaks | https://en.wikipedia.org/wiki/List_of_European_ultra_prominent_peaks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18918776-1.html.csv | comparative | the peak store lenangstind has a lower elevation than the peak galdhøpiggen . | {'row_1': '5', 'row_2': '1', 'col': '3', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'peak', 'store lenangstind'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose peak record fuzzily matches to store lenangstind .', 'tostr': 'filter_eq { all_rows ; peak ; store lenangstind }'}, 'elevation ( m )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; peak ; store lenangstind } ; elevation ( m ) }', 'tointer': 'select the rows whose peak record fuzzily matches to store lenangstind . take the elevation ( m ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'peak', 'galdhøpiggen'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose peak record fuzzily matches to galdhøpiggen .', 'tostr': 'filter_eq { all_rows ; peak ; galdhøpiggen }'}, 'elevation ( m )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; peak ; galdhøpiggen } ; elevation ( m ) }', 'tointer': 'select the rows whose peak record fuzzily matches to galdhøpiggen . take the elevation ( m ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; peak ; store lenangstind } ; elevation ( m ) } ; hop { filter_eq { all_rows ; peak ; galdhøpiggen } ; elevation ( m ) } } = true', 'tointer': 'select the rows whose peak record fuzzily matches to store lenangstind . take the elevation ( m ) record of this row . select the rows whose peak record fuzzily matches to galdhøpiggen . take the elevation ( m ) record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; peak ; store lenangstind } ; elevation ( m ) } ; hop { filter_eq { all_rows ; peak ; galdhøpiggen } ; elevation ( m ) } } = true | select the rows whose peak record fuzzily matches to store lenangstind . take the elevation ( m ) record of this row . select the rows whose peak record fuzzily matches to galdhøpiggen . take the elevation ( m ) 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, 'peak_7': 7, 'store lenangstind_8': 8, 'elevation (m)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'peak_11': 11, 'galdhøpiggen_12': 12, 'elevation (m)_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', 'peak_7': 'peak', 'store lenangstind_8': 'store lenangstind', 'elevation (m)_9': 'elevation ( m )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'peak_11': 'peak', 'galdhøpiggen_12': 'galdhøpiggen', 'elevation (m)_13': 'elevation ( m )'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'peak_7': [0], 'store lenangstind_8': [0], 'elevation (m)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'peak_11': [1], 'galdhøpiggen_12': [1], 'elevation (m)_13': [3]} | ['peak', 'country', 'elevation ( m )', 'prominence ( m )', 'col ( m )'] | [['galdhøpiggen', 'norway', '2469', '2372', '97'], ['kebnekaise', 'sweden', '2113', '1754', '359'], ['jiehkkevárri', 'norway', '1834', '1741', '93'], ['snøhetta', 'norway', '2286', '1675', '611'], ['store lenangstind', 'norway', '1624', '1576', '48'], ['sarektjåhkkå', 'sweden', '2089', '1519', '570']] |
list of locomotives in china | https://en.wikipedia.org/wiki/List_of_locomotives_in_China | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10285177-5.html.csv | aggregation | the average top speed for the locomotives is 106.33 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '106.33', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'top speed ( in operation ) （ km / h ）'], 'result': '106.33', 'ind': 0, 'tostr': 'avg { all_rows ; top speed ( in operation ) （ km / h ） }'}, '106.33'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; top speed ( in operation ) （ km / h ） } ; 106.33 } = true', 'tointer': 'the average of the top speed ( in operation ) （ km / h ） record of all rows is 106.33 .'} | round_eq { avg { all_rows ; top speed ( in operation ) （ km / h ） } ; 106.33 } = true | the average of the top speed ( in operation ) （ km / h ） record of all rows is 106.33 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'top speed (in operation) （km / h）_4': 4, '106.33_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'top speed (in operation) （km / h）_4': 'top speed ( in operation ) （ km / h ）', '106.33_5': '106.33'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'top speed (in operation) （km / h）_4': [0], '106.33_5': [1]} | ['model', 'build year', 'transmission', 'top speed ( in operation ) （ km / h ）', 'power output （ kw ）', 'builder ( family )', 'total production'] | [['nd1', '1958 ,1965', 'dc - dc', '80', '440', 'hungary ganz ( hungarian state railways class m44 )', '26'], ['nd2', '1972 - 1987', 'dc - dc', '120', '1280', 'electroputere , romania craiova ( cfr 060da )', '284'], ['nd3', '1985', 'dc - dc', '100', '1540', 'electroputere , romania craiova', '88'], ['nd4', '1973 - 1975', 'ac - dc', '100', '2150', 'alstom , france', '50'], ['nd5', '1984 － 1986', 'ac - dc', '118', '2550', 'ge , usa ( ge c36 - 7 )', '422'], ['nj2', '2005 - 2006', 'ac - dc - ac', '120', '3800', 'ge , usa', '78']] |
2008 pga tour | https://en.wikipedia.org/wiki/2008_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14473512-2.html.csv | majority | the majority of players in the 2008 pga golf tournaments were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['rank', 'player', 'country', 'events', 'prize money'] | [['1', 'vijay singh', 'fiji', '23', '6601094'], ['2', 'tiger woods', 'united states', '6', '5775000'], ['3', 'phil mickelson', 'united states', '21', '5118875'], ['4', 'sergio garcía', 'spain', '19', '4858224'], ['5', 'kenny perry', 'united states', '26', '4663794'], ['6', 'anthony kim', 'united states', '22', '4656265'], ['7', 'camilo villegas', 'colombia', '22', '4422641'], ['8', 'pádraig harrington', 'ireland', '15', '4313551'], ['9', 'stewart cink', 'united states', '22', '3963661'], ['10', 'justin leonard', 'united states', '25', '3943542']] |
1990 african cup of champions clubs | https://en.wikipedia.org/wiki/1990_African_Cup_of_Champions_Clubs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16163549-1.html.csv | superlative | al-ittihad is the club that scored the most goals in the 1990 african cup of champions . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '4', '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', 'agg'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; agg }'}, 'team 1'], 'result': 'al - ittihad', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; agg } ; team 1 }'}, 'al - ittihad'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; agg } ; team 1 } ; al - ittihad } = true', 'tointer': 'select the row whose agg record of all rows is maximum . the team 1 record of this row is al - ittihad .'} | eq { hop { argmax { all_rows ; agg } ; team 1 } ; al - ittihad } = true | select the row whose agg record of all rows is maximum . the team 1 record of this row is al - ittihad . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'agg_5': 5, 'team 1_6': 6, 'al - ittihad_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'agg_5': 'agg', 'team 1_6': 'team 1', 'al - ittihad_7': 'al - ittihad'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'agg_5': [0], 'team 1_6': [1], 'al - ittihad_7': [2]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['as sotema', '( a ) 2 - 2', 'defence force xi', '1 - 0', '1 - 2'], ['as kaloum star', '3 - 0', 'benfica de bissau', '2 - 0', '1 - 0'], ['asko kara', '3 - 0', 'asfa yennenga', '1 - 0', '2 - 0'], ['al - ittihad', '6 - 3', 'olympic fc de niamey', '6 - 1', '0 - 2'], ['arsenal', '4 - 0', 'denver sundowns', '1 - 0', '3 - 0'], ["dragons de l'ouémé", '0 - 3', 'mighty barolle', '0 - 0', '0 - 3'], ['fc inter - star', '2 - 3', 'petro atlético', '2 - 0', '0 - 3'], ['mogadishu municipality', '3 - 4', 'saint louis', '1 - 0', '2 - 4'], ['malindi', '1 - 2', 'mukungwa', '0 - 0', '1 - 2'], ['renaissance', '2 - 3', 'scaf tocages', '2 - 2', '0 - 1']] |
1948 vfl season | https://en.wikipedia.org/wiki/1948_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809529-2.html.csv | aggregation | in the 1948 vfl season , when the away team was from melbourne , or a part of melbourne , the average crowd size was 24500 . | {'scope': 'subset', 'col': '6', 'type': 'average', 'result': '24500', 'subset': {'col': '3', 'criterion': 'fuzzily_match', 'value': 'melbourne'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'away team', 'melbourne'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; away team ; melbourne }', 'tointer': 'select the rows whose away team record fuzzily matches to melbourne .'}, 'crowd'], 'result': '24500', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; away team ; melbourne } ; crowd }'}, '24500'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; away team ; melbourne } ; crowd } ; 24500 } = true', 'tointer': 'select the rows whose away team record fuzzily matches to melbourne . the average of the crowd record of these rows is 24500 .'} | round_eq { avg { filter_eq { all_rows ; away team ; melbourne } ; crowd } ; 24500 } = true | select the rows whose away team record fuzzily matches to melbourne . the average of the crowd record of these rows is 24500 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'away team_5': 5, 'melbourne_6': 6, 'crowd_7': 7, '24500_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'away team_5': 'away team', 'melbourne_6': 'melbourne', 'crowd_7': 'crowd', '24500_8': '24500'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'away team_5': [0], 'melbourne_6': [0], 'crowd_7': [1], '24500_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '15.17 ( 107 )', 'north melbourne', '10.8 ( 68 )', 'kardinia park', '17500', '24 april 1948'], ['carlton', '8.10 ( 58 )', 'fitzroy', '10.18 ( 78 )', 'princes park', '32000', '24 april 1948'], ['st kilda', '7.6 ( 48 )', 'melbourne', '11.13 ( 79 )', 'junction oval', '9000', '24 april 1948'], ['richmond', '20.12 ( 132 )', 'footscray', '8.9 ( 57 )', 'punt road oval', '29000', '24 april 1948'], ['essendon', '11.16 ( 82 )', 'hawthorn', '8.11 ( 59 )', 'windy hill', '16000', '26 april 1948'], ['collingwood', '18.17 ( 125 )', 'south melbourne', '10.12 ( 72 )', 'victoria park', '47000', '26 april 1948']] |
1964 vfl season | https://en.wikipedia.org/wiki/1964_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10784349-7.html.csv | comparative | in the 1964 vfl season , the attendance when carlton was the home team was 15277 less than when collingwood was the home team . | {'row_1': '4', 'row_2': '3', 'col': '6', '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', 'home team', 'carlton'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to carlton .', 'tostr': 'filter_eq { all_rows ; home team ; carlton }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; home team ; carlton } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to carlton . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'collingwood'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team record fuzzily matches to collingwood .', 'tostr': 'filter_eq { all_rows ; home team ; collingwood }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; home team ; collingwood } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to collingwood . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; home team ; carlton } ; crowd } ; hop { filter_eq { all_rows ; home team ; collingwood } ; crowd } } = true', 'tointer': 'select the rows whose home team record fuzzily matches to carlton . take the crowd record of this row . select the rows whose home team record fuzzily matches to collingwood . take the crowd record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; home team ; carlton } ; crowd } ; hop { filter_eq { all_rows ; home team ; collingwood } ; crowd } } = true | select the rows whose home team record fuzzily matches to carlton . take the crowd record of this row . select the rows whose home team record fuzzily matches to collingwood . take the crowd 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, 'home team_7': 7, 'carlton_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'collingwood_12': 12, 'crowd_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', 'home team_7': 'home team', 'carlton_8': 'carlton', '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', 'collingwood_12': 'collingwood', 'crowd_13': 'crowd'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'carlton_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'collingwood_12': [1], 'crowd_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '13.11 ( 89 )', 'richmond', '7.16 ( 58 )', 'glenferrie oval', '22000', '30 may 1964'], ['geelong', '11.23 ( 89 )', 'st kilda', '13.8 ( 86 )', 'kardinia park', '28000', '30 may 1964'], ['collingwood', '22.18 ( 150 )', 'north melbourne', '6.6 ( 42 )', 'victoria park', '34222', '30 may 1964'], ['carlton', '8.12 ( 60 )', 'fitzroy', '8.11 ( 59 )', 'princes park', '18945', '30 may 1964'], ['melbourne', '12.14 ( 86 )', 'footscray', '6.8 ( 44 )', 'mcg', '33129', '30 may 1964'], ['south melbourne', '11.18 ( 84 )', 'essendon', '14.12 ( 96 )', 'lake oval', '20470', '30 may 1964']] |
bojana jovanovski | https://en.wikipedia.org/wiki/Bojana_Jovanovski | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18183850-12.html.csv | comparative | bojana jovanovski played against daniela hantuchová earlier than she played against kirsten flipkens . | {'row_1': '1', 'row_2': '7', 'col': '2', 'col_other': '6', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'daniela hantuchová'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to daniela hantuchová .', 'tostr': 'filter_eq { all_rows ; opponent ; daniela hantuchová }'}, 'edition'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; daniela hantuchová } ; edition }', 'tointer': 'select the rows whose opponent record fuzzily matches to daniela hantuchová . take the edition record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'kirsten flipkens'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to kirsten flipkens .', 'tostr': 'filter_eq { all_rows ; opponent ; kirsten flipkens }'}, 'edition'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; kirsten flipkens } ; edition }', 'tointer': 'select the rows whose opponent record fuzzily matches to kirsten flipkens . take the edition record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; daniela hantuchová } ; edition } ; hop { filter_eq { all_rows ; opponent ; kirsten flipkens } ; edition } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to daniela hantuchová . take the edition record of this row . select the rows whose opponent record fuzzily matches to kirsten flipkens . take the edition record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; daniela hantuchová } ; edition } ; hop { filter_eq { all_rows ; opponent ; kirsten flipkens } ; edition } } = true | select the rows whose opponent record fuzzily matches to daniela hantuchová . take the edition record of this row . select the rows whose opponent record fuzzily matches to kirsten flipkens . take the edition 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, 'opponent_7': 7, 'daniela hantuchová_8': 8, 'edition_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'kirsten flipkens_12': 12, 'edition_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', 'opponent_7': 'opponent', 'daniela hantuchová_8': 'daniela hantuchová', 'edition_9': 'edition', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'kirsten flipkens_12': 'kirsten flipkens', 'edition_13': 'edition'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'daniela hantuchová_8': [0], 'edition_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'kirsten flipkens_12': [1], 'edition_13': [3]} | ['outcome', 'edition', 'round', 'opponent team', 'surface', 'opponent', 'score'] | [['loser', '2010', 'world group playoffs', 'slovakia', 'clay ( i )', 'daniela hantuchová', '6 - 2 , 6 - 2'], ['winner', '2010', 'world group playoffs', 'slovakia', 'clay ( i )', 'magdaléna rybáriková', '6 - 1 , 7 - 6 ( 7 - 4 )'], ['winner', '2011', 'world group ii', 'canada', 'hard ( i )', 'aleksandra wozniak', '6 - 4 , 7 - 5'], ['winner', '2011', 'world group ii', 'canada', 'hard ( i )', 'rebecca marino', '7 - 6 ( 7 - 3 ) , 6 - 3'], ['loser', '2011', 'world group playoffs', 'slovakia', 'clay ( i )', 'dominika cibulková', '6 - 4 , 3 - 6 , 1 - 6'], ['loser', '2012', 'world group', 'belgium', 'hard ( i )', 'yanina wickmayer', '4 - 6 , 4 - 6'], ['winner', '2012', 'world group', 'belgium', 'hard ( i )', 'kirsten flipkens', '6 - 2 , 6 - 4']] |
1967 tasman series | https://en.wikipedia.org/wiki/1967_Tasman_Series | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13729095-1.html.csv | count | jackie stewart won a total of two races in the 1967 tasman series . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'jackie stewart', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'winning driver', 'jackie stewart'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose winning driver record fuzzily matches to jackie stewart .', 'tostr': 'filter_eq { all_rows ; winning driver ; jackie stewart }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; winning driver ; jackie stewart } }', 'tointer': 'select the rows whose winning driver record fuzzily matches to jackie stewart . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; winning driver ; jackie stewart } } ; 2 } = true', 'tointer': 'select the rows whose winning driver record fuzzily matches to jackie stewart . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; winning driver ; jackie stewart } } ; 2 } = true | select the rows whose winning driver record fuzzily matches to jackie stewart . 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, 'winning driver_5': 5, 'jackie stewart_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', 'winning driver_5': 'winning driver', 'jackie stewart_6': 'jackie stewart', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'winning driver_5': [0], 'jackie stewart_6': [0], '2_7': [2]} | ['round', 'name', 'circuit', 'date', 'winning driver', 'winning car', 'winning team', 'report'] | [['new zealand', 'new zealand grand prix', 'pukekohe', '7 january', 'jackie stewart', 'brm p261', 'reg parnell racing', 'report'], ['new zealand', 'levin international', 'levin', '14 january', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['new zealand', 'lady wigram trophy', 'wigram', '21 january', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['new zealand', 'teretonga international', 'teretonga', '28 january', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['australia', 'lakeside international', 'lakeside', '12 february', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['australia', 'australian grand prix', 'warwick farm', '19 february', 'jackie stewart', 'brm p261', 'reg parnell racing', 'report'], ['australia', 'sandown international', 'sandown', '26 february', 'jim clark', 'lotus 33', 'team lotus', 'report'], ['australia', 'south pacific trophy', 'longford', '6 march', 'jack brabham', 'brabham bt23a', 'brabham', 'report']] |
hughes hall college boat club | https://en.wikipedia.org/wiki/Hughes_Hall_College_Boat_Club | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18880596-2.html.csv | aggregation | for the hughes hall college boat club , the average finish position was 29.8 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '29.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'finish position'], 'result': '29.8', 'ind': 0, 'tostr': 'avg { all_rows ; finish position }'}, '29.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; finish position } ; 29.8 } = true', 'tointer': 'the average of the finish position record of all rows is 29.8 .'} | round_eq { avg { all_rows ; finish position } ; 29.8 } = true | the average of the finish position record of all rows is 29.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'finish position_4': 4, '29.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'finish position_4': 'finish position', '29.8_5': '29.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'finish position_4': [0], '29.8_5': [1]} | ['year', 'finish position', '1st day', '2nd day', '3rd day', '4th day'] | [['2008', '33rd', 'bumped corpus christi / newnham', 'rowed - over', 'rowed - over', 'bumped wolfson'], ['2009', '31st', "bumped st edmund 's", 'rowed - over', 'bumped darwin', 'rowed - over'], ['2010', '31st', 'bumped by corpus christi', 'rowed - over', 'bumped caius', 'rowed - over'], ['2011', '27th', 'bumped anglia ruskin', 'bumped pembroke', 'bumped homerton', 'bumped robinson'], ['2012', '27th', 'bumped jesus', 'rowed - over', 'bumped by robinson', 'bumped by homerton']] |
rowing at the 2008 summer olympics - women 's coxless pair | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_coxless_pair | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662697-3.html.csv | superlative | belarus had the shortest time in the women 's coxless pair competition in rowing at the 2008 summer olympics . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', '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', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'country'], 'result': 'belarus', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; country }'}, 'belarus'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; time } ; country } ; belarus } = true', 'tointer': 'select the row whose time record of all rows is minimum . the country record of this row is belarus .'} | eq { hop { argmin { all_rows ; time } ; country } ; belarus } = true | select the row whose time record of all rows is minimum . the country record of this row is belarus . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'country_6': 6, 'belarus_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', 'country_6': 'country', 'belarus_7': 'belarus'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'country_6': [1], 'belarus_7': [2]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'yuliya bichyk , natallia helakh', 'belarus', '7:24.47', 'fa'], ['2', 'juliette haigh , nicola coles', 'new zealand', '7:31.45', 'r'], ['3', 'wu you , gao yulan', 'china', '7:32.50', 'r'], ['4', 'kim crow , sarah cook', 'australia', '7:44.04', 'r'], ['5', 'zoe hoskins , sabrina kolker', 'canada', 'boat under weight', 'r']] |
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/2-1222653-10.html.csv | ordinal | the second highest exchange rate for 1 euro in the countries of south america is found for the colombian peso . | {'row': '5', 'col': '3', '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', '1 euro =', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; 1 euro = ; 2 }'}, 'currency'], 'result': 'colombian peso ( cop )', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; 1 euro = ; 2 } ; currency }'}, 'colombian peso ( cop )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; 1 euro = ; 2 } ; currency } ; colombian peso ( cop ) } = true', 'tointer': 'select the row whose 1 euro = record of all rows is 2nd maximum . the currency record of this row is colombian peso ( cop ) .'} | eq { hop { nth_argmax { all_rows ; 1 euro = ; 2 } ; currency } ; colombian peso ( cop ) } = true | select the row whose 1 euro = record of all rows is 2nd maximum . the currency record of this row is colombian peso ( cop ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, '1 euro =_5': 5, '2_6': 6, 'currency_7': 7, 'colombian peso (cop)_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', '1 euro =_5': '1 euro =', '2_6': '2', 'currency_7': 'currency', 'colombian peso (cop)_8': 'colombian peso ( cop )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], '1 euro =_5': [0], '2_6': [0], 'currency_7': [1], 'colombian peso (cop)_8': [2]} | ['country', 'currency', '1 euro =', '1 usd =', 'central bank'] | [['argentina', 'argentine peso ( ars )', '5.72079', '4.34950', 'central bank of argentina'], ['bolivia', 'bolivian boliviano ( bob )', '9.02081', '6.86000', 'central bank of bolivia'], ['brazil', 'brazilian real ( brl )', '2.25592', '1.71577', 'central bank of brazil'], ['chile', 'chilean peso ( clp )', '635.134', '483.050', 'central bank of chile'], ['colombia', 'colombian peso ( cop )', '2353.40', '1790.00', 'bank of the republic'], ['ecuador', 'us dollar ( usd )', '1.46611', '1', 'federal reserve'], ['guyana', 'guyanese dollar ( gyd )', '264.192', '200.950', 'bank of guyana'], ['paraguay', 'paraguayan guaraní ( pyg )', '4500.00', '5916.27', 'central bank of paraguay'], ['peru', 'peruvian nuevo sol ( pen )', '3.53004', '2.68500', 'central reserve bank of peru'], ['suriname', 'surinamese dollar ( srd )', '4.27296', '3.25000', 'central bank of suriname'], ['uruguay', 'uruguayan peso ( uyu )', '25.3797', '19.3000', 'central bank of uruguay'], ['venezuela', 'venezuelan bolívar fuerte ( vef )', '5.65462', '4.30000', 'central bank of venezuela']] |
1963 vfl season | https://en.wikipedia.org/wiki/1963_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10783853-7.html.csv | majority | in the 1963 vfl season , a majority of games had over 17000 in attendance . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '17000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'crowd', '17000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 17000 .', 'tostr': 'most_greater { all_rows ; crowd ; 17000 } = true'} | most_greater { all_rows ; crowd ; 17000 } = true | for the crowd records of all rows , most of them are greater than 17000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '17000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '17000_4': '17000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '17000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '8.10 ( 58 )', 'st kilda', '9.12 ( 66 )', 'arden street oval', '17125', '1 june 1963'], ['geelong', '9.12 ( 66 )', 'hawthorn', '9.12 ( 66 )', 'kardinia park', '29374', '1 june 1963'], ['collingwood', '10.11 ( 71 )', 'essendon', '13.9 ( 87 )', 'victoria park', '44501', '1 june 1963'], ['south melbourne', '11.8 ( 74 )', 'melbourne', '8.22 ( 70 )', 'lake oval', '17160', '1 june 1963'], ['richmond', '17.13 ( 115 )', 'fitzroy', '13.8 ( 86 )', 'punt road oval', '16500', '1 june 1963'], ['footscray', '7.7 ( 49 )', 'carlton', '8.9 ( 57 )', 'western oval', '26107', '1 june 1963']] |
seiji ara | https://en.wikipedia.org/wiki/Seiji_Ara | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1617309-1.html.csv | unique | for seiji ara , when the class was imp900 , the only time the co-drivers were jan magnussen and marco werner was in 2003 . | {'scope': 'subset', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'jan magnussen marco werner', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'lmp900'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'lmp900'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; class ; lmp900 }', 'tointer': 'select the rows whose class record fuzzily matches to lmp900 .'}, 'co - drivers', 'jan magnussen marco werner'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose class record fuzzily matches to lmp900 . among these rows , select the rows whose co - drivers record fuzzily matches to jan magnussen marco werner .', 'tostr': 'filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner } }', 'tointer': 'select the rows whose class record fuzzily matches to lmp900 . among these rows , select the rows whose co - drivers record fuzzily matches to jan magnussen marco werner . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'lmp900'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; class ; lmp900 }', 'tointer': 'select the rows whose class record fuzzily matches to lmp900 .'}, 'co - drivers', 'jan magnussen marco werner'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose class record fuzzily matches to lmp900 . among these rows , select the rows whose co - drivers record fuzzily matches to jan magnussen marco werner .', 'tostr': 'filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner }'}, 'year'], 'result': '2003', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner } ; year }'}, '2003'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner } ; year } ; 2003 }', 'tointer': 'the year record of this unqiue row is 2003 .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner } } ; eq { hop { filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner } ; year } ; 2003 } } = true', 'tointer': 'select the rows whose class record fuzzily matches to lmp900 . among these rows , select the rows whose co - drivers record fuzzily matches to jan magnussen marco werner . there is only one such row in the table . the year record of this unqiue row is 2003 .'} | and { only { filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner } } ; eq { hop { filter_eq { filter_eq { all_rows ; class ; lmp900 } ; co - drivers ; jan magnussen marco werner } ; year } ; 2003 } } = true | select the rows whose class record fuzzily matches to lmp900 . among these rows , select the rows whose co - drivers record fuzzily matches to jan magnussen marco werner . there is only one such row in the table . the year record of this unqiue row is 2003 . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'class_8': 8, 'lmp900_9': 9, 'co - drivers_10': 10, 'jan magnussen marco werner_11': 11, 'eq_4': 4, 'num_hop_3': 3, 'year_12': 12, '2003_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'class_8': 'class', 'lmp900_9': 'lmp900', 'co - drivers_10': 'co - drivers', 'jan magnussen marco werner_11': 'jan magnussen marco werner', 'eq_4': 'eq', 'num_hop_3': 'num_hop', 'year_12': 'year', '2003_13': '2003'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'class_8': [0], 'lmp900_9': [0], 'co - drivers_10': [1], 'jan magnussen marco werner_11': [1], 'eq_4': [5], 'num_hop_3': [4], 'year_12': [3], '2003_13': [4]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['2001', 'viper team oreca', 'masahiko kondo ni amorim', 'lmp900', '243', 'dnf', 'dnf'], ['2002', 'audi sport japan team goh', 'hiroki katoh yannick dalmas', 'lmp900', '358', '7th', '6th'], ['2003', 'audi sport japan team goh', 'jan magnussen marco werner', 'lmp900', '370', '4th', '2nd'], ['2004', 'audi sport japan team goh', 'rinaldo capello tom kristensen', 'lmp900', '379', '1st', '1st'], ['2005', 'jim gainer international', 'ryo michigami katsutomo kaneishi', 'lmp1', '193', 'dnf', 'dnf'], ['2009', 'navi team goh', 'keisuke kunimoto sascha maassen', 'lmp2', '339', 'dnf', 'dnf'], ['2012', 'pescarolo team', 'nicolas minassian sãbastien bourdais', 'lmp1', '203', 'nc', 'nc']] |
list of england national rugby union team results 2000 - 09 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_2000%E2%80%9309 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178551-6.html.csv | count | on five different occasions , the status of the england national rugby union team was six nations . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'six', 'result': '5', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'six'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to six .', 'tostr': 'filter_eq { all_rows ; status ; six }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; status ; six } }', 'tointer': 'select the rows whose status record fuzzily matches to six . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; status ; six } } ; 5 } = true', 'tointer': 'select the rows whose status record fuzzily matches to six . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; status ; six } } ; 5 } = true | select the rows whose status record fuzzily matches to six . 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, 'status_5': 5, 'six_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', 'status_5': 'status', 'six_6': 'six', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'status_5': [0], 'six_6': [0], '5_7': [2]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['wales', '11', '05 / 02 / 2005', 'millennium stadium , cardiff', 'six nations'], ['france', '18', '13 / 02 / 2005', 'twickenham , london', 'six nations'], ['ireland', '19', '27 / 02 / 2005', 'lansdowne road , dublin', 'six nations'], ['italy', '7', '12 / 03 / 2005', 'twickenham , london', 'six nations'], ['scotland', '22', '19 / 03 / 2005', 'twickenham , london', 'six nations'], ['australia', '16', '12 / 11 / 2005', 'twickenham , london', 'test match'], ['new zealand', '23', '19 / 11 / 2005', 'twickenham , london', 'test match'], ['samoa', '3', '26 / 11 / 2005', 'twickenham , london', 'test match']] |
list of chilean submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Chilean_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20404716-1.html.csv | superlative | according to the list of chilean submissions for the academy award for best foreign language film , silvio caiozzi 's first submission took place in 1990 . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '4', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'silvio caiozzi'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'silvio caiozzi'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; director ; silvio caiozzi }', 'tointer': 'select the rows whose director record fuzzily matches to silvio caiozzi .'}, 'year ( ceremony )'], 'result': '1990 : ( 63rd )', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; director ; silvio caiozzi } ; year ( ceremony ) }', 'tointer': 'select the rows whose director record fuzzily matches to silvio caiozzi . the minimum year ( ceremony ) record of these rows is 1990 : ( 63rd ) .'}, '1990 : ( 63rd )'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; director ; silvio caiozzi } ; year ( ceremony ) } ; 1990 : ( 63rd ) } = true', 'tointer': 'select the rows whose director record fuzzily matches to silvio caiozzi . the minimum year ( ceremony ) record of these rows is 1990 : ( 63rd ) .'} | eq { min { filter_eq { all_rows ; director ; silvio caiozzi } ; year ( ceremony ) } ; 1990 : ( 63rd ) } = true | select the rows whose director record fuzzily matches to silvio caiozzi . the minimum year ( ceremony ) record of these rows is 1990 : ( 63rd ) . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'director_5': 5, 'silvio caiozzi_6': 6, 'year (ceremony)_7': 7, '1990: (63rd)_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'director_5': 'director', 'silvio caiozzi_6': 'silvio caiozzi', 'year (ceremony)_7': 'year ( ceremony )', '1990: (63rd)_8': '1990 : ( 63rd )'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'director_5': [0], 'silvio caiozzi_6': [0], 'year (ceremony)_7': [1], '1990: (63rd)_8': [2]} | ['year ( ceremony )', 'film title used in nomination', 'spanish title', 'director', 'result'] | [['1990 : ( 63rd )', 'the moon in the mirror', 'la luna en el espejo', 'silvio caiozzi', 'not nominated'], ['1991 : ( 64th )', 'the frontier', 'la frontera', 'ricardo larraín', 'not nominated'], ['1993 : ( 66th )', 'johnny 100 pesos', 'johnny 100 pesos', 'gustavo graef - marino', 'not nominated'], ['1994 : ( 67th )', 'amnesia', 'amnesia', 'gonzalo justiniano', 'not nominated'], ['2000 : ( 73rd )', 'coronation', 'coronación', 'silvio caiozzi', 'not nominated'], ['2001 : ( 74th )', 'a cab for three', 'taxi para tres', 'orlando lubbert', 'not nominated'], ['2002 : ( 75th )', 'ogu and mampato in rapa nui', 'ogu y mampato en rapa nui', 'alejandro rojas', 'not nominated'], ['2003 : ( 76th )', 'los debutantes', 'los debutantes', 'andres waissbluth', 'not nominated'], ['2004 : ( 77th )', 'machuca', 'machuca', 'andrés wood', 'not nominated'], ['2005 : ( 78th )', 'play', 'play', 'alicia scherson', 'not nominated'], ['2006 : ( 79th )', 'in bed', 'en la cama', 'matías bize', 'not nominated'], ['2007 : ( 80th )', 'padre nuestro', 'padre nuestro', 'rodrigo sepúlveda', 'not nominated'], ['2008 : ( 81st )', 'tony manero', 'tony manero', 'pablo larrain', 'not nominated'], ['2009 : ( 82nd )', 'dawson , island 10', 'dawson , isla 10', 'miguel littín', 'not nominated'], ['2010 : ( 83rd )', 'the life of fish', 'la vida de los peces', 'matías bize', 'not nominated'], ['2011 : ( 84th )', 'violeta went to heaven', 'violeta se fue a los cielos', 'andrés wood', 'not nominated'], ['2012 : ( 85th )', 'no', 'no', 'pablo larraín', 'nominee']] |
football records in spain | https://en.wikipedia.org/wiki/Football_records_in_Spain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17937080-8.html.csv | count | real madrid football club holds a total of nine of the football records in spain . | {'scope': 'all', 'criterion': 'equal', 'value': 'real madrid', 'result': '9', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'real madrid'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to real madrid .', 'tostr': 'filter_eq { all_rows ; club ; real madrid }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; club ; real madrid } }', 'tointer': 'select the rows whose club record fuzzily matches to real madrid . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; club ; real madrid } } ; 9 } = true', 'tointer': 'select the rows whose club record fuzzily matches to real madrid . the number of such rows is 9 .'} | eq { count { filter_eq { all_rows ; club ; real madrid } } ; 9 } = true | select the rows whose club record fuzzily matches to real madrid . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'club_5': 5, 'real madrid_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'club_5': 'club', 'real madrid_6': 'real madrid', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'club_5': [0], 'real madrid_6': [0], '9_7': [2]} | ['rank', 'name', 'season', 'club', 'goals', 'apps', 'goals per match'] | [['1', 'lionel messi', '2011 / 12', 'barcelona', '73', '60', '1.217'], ['2', 'lionel messi', '2012 / 13', 'barcelona', '60', '49', '1.224'], ['2', 'cristiano ronaldo', '2011 / 12', 'real madrid', '60', '55', '1.091'], ['4', 'cristiano ronaldo', '2012 / 13', 'real madrid', '55', '55', '1.000'], ['5', 'cristiano ronaldo', '2010 / 11', 'real madrid', '53', '54', '0.981'], ['5', 'lionel messi', '2010 / 11', 'barcelona', '53', '55', '0.964'], ['7', 'ferenc puskás', '1959 / 60', 'real madrid', '47', '38', '1.237'], ['7', 'ronaldo', '1996 / 97', 'barcelona', '47', '49', '0.964'], ['7', 'lionel messi', '2009 / 10', 'barcelona', '47', '53', '0.887'], ['10', 'telmo zarra', '1950 / 51', 'athletic bilbao', '46', '36', '1.278'], ['11', 'alfredo di stéfano', '1956 / 57', 'real madrid', '43', '43', '1.000'], ['12', 'mariano martín', '1942 / 43', 'barcelona', '42', '31', '1.355'], ['12', 'ferenc puskás', '1960 / 61', 'real madrid', '42', '39', '1.077'], ['12', 'hugo sánchez', '1989 / 90', 'real madrid', '42', '45', '0.933'], ['12', 'baltazar', '1988 / 89', 'atlético madrid', '42', '46', '0.913'], ['15', 'hugo sánchez', '1986 / 87', 'real madrid', '41', '54', '0.759'], ['16', 'ferenc puskás', '1961 / 62', 'real madrid', '40', '40', '1.000']] |
giorgio mazza | https://en.wikipedia.org/wiki/Giorgio_Mazza | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11881236-1.html.csv | majority | giorgio mazza finished in the top 5 the majority of years he competed . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '5', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'result', '5'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them are greater than or equal to 5 .', 'tostr': 'most_greater_eq { all_rows ; result ; 5 } = true'} | most_greater_eq { all_rows ; result ; 5 } = true | for the result records of all rows , most of them are greater than or equal to 5 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, '5_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', '5_4': '5'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], '5_4': [0]} | ['year', 'tournament', 'venue', 'result', 'extra'] | [['1958', 'european championships', 'stockholm , sweden', '5th', '110 m hurdles'], ['1959', 'universiade', 'turin , italy', '3rd', '110 m hurdles'], ['1962', 'european championships', 'belgrade , yugoslavia', '5th', '110 m hurdles'], ['1963', 'universiade', 'pãrto alegre , brazil', '2nd', '110 m hurdles'], ['1963', 'mediterranean games', 'naples , italy', '3rd', '110 m hurdles'], ['1964', 'olympic games', 'tokyo , japan', '8th', '110 m hurdles']] |
2011 newfoundland and labrador tankard | https://en.wikipedia.org/wiki/2011_Newfoundland_and_Labrador_Tankard | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29565858-2.html.csv | superlative | brad gushue had the highest amount of wins at the 2011 newfoundland and labrador tankard . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'w'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; w }'}, 'skip ( club )'], 'result': 'brad gushue ( bally haly )', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; w } ; skip ( club ) }'}, 'brad gushue ( bally haly )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; w } ; skip ( club ) } ; brad gushue ( bally haly ) } = true', 'tointer': 'select the row whose w record of all rows is maximum . the skip ( club ) record of this row is brad gushue ( bally haly ) .'} | eq { hop { argmax { all_rows ; w } ; skip ( club ) } ; brad gushue ( bally haly ) } = true | select the row whose w record of all rows is maximum . the skip ( club ) record of this row is brad gushue ( bally haly ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'w_5': 5, 'skip (club)_6': 6, 'brad gushue (bally haly)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'w_5': 'w', 'skip (club)_6': 'skip ( club )', 'brad gushue (bally haly)_7': 'brad gushue ( bally haly )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'w_5': [0], 'skip (club)_6': [1], 'brad gushue (bally haly)_7': [2]} | ['skip ( club )', 'w', 'l', 'pf', 'pa', 'ends won', 'ends lost', 'blank ends', 'stolen ends'] | [['brad gushue ( bally haly )', '5', '0', '35', '15', '22', '12', '9', '6'], ['alex smith ( re / max centre )', '3', '2', '39', '34', '21', '23', '3', '5'], ['andrew symonds ( re / max centre )', '3', '2', '35', '36', '20', '21', '6', '1'], ['keith ryan ( carroll )', '2', '3', '29', '32', '19', '23', '5', '5'], ['ken peddigrew ( re / max centre )', '1', '4', '24', '32', '19', '17', '7', '4']] |
list of doctor who audiobooks | https://en.wikipedia.org/wiki/List_of_Doctor_Who_audiobooks | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20174050-23.html.csv | majority | the majority of doctor who audio books were released by the bbc audio company . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'bbc audio', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'company', 'bbc audio'], 'result': True, 'ind': 0, 'tointer': 'for the company records of all rows , most of them fuzzily match to bbc audio .', 'tostr': 'most_eq { all_rows ; company ; bbc audio } = true'} | most_eq { all_rows ; company ; bbc audio } = true | for the company records of all rows , most of them fuzzily match to bbc audio . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'company_3': 3, 'bbc audio_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'company_3': 'company', 'bbc audio_4': 'bbc audio'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'company_3': [0], 'bbc audio_4': [0]} | ['title', 'author', 'reader', 'format', 'company', 'release date', 'notes'] | [['another life', 'anghelides , peter peter anghelides', 'barrowman , john john barrowman', '3 - cd', 'bbc audio', '2007 - 04 - 02 2 april 2007', 'abridged'], ['slow decay', 'lane , andy andy lane', 'gorman , burn burn gorman', '3 - cd', 'bbc audio', '2007 - 04 - 02 2 april 2007', 'abridged'], ['border princes', 'abnett , dan dan abnett', 'myles , eve eve myles', '3 - cd', 'bbc audio', '2007 - 04 - 02 2 april 2007', 'abridged'], ['hidden', 'saville , steven steven savile', 'mori , naoko naoko mori', '2 - cd', 'bbc audio', '2008 - 02 - 04 4 february 2008', 'an original audiobook , not published in book form'], ['everyone says hello', 'abnett , dan dan abnett', 'gorman , burn burn gorman', '2 - cd', 'bbc audio', '2008 - 02 - 04 4 february 2008', 'an original audiobook , not published in book form'], ['in the shadows', 'lidster , joseph joseph lidster', 'myles , eve eve myles', '2 - cd', 'bbc audio', '2009 - 05 - 07 7 may 2009', 'an original audiobook , not published in book form'], ['the sin eaters', 'minchin , brian brian minchin', 'david - lloyd , gareth gareth david - lloyd', '2 - cd', 'bbc audio', '2009 - 06 - 04 4 june 2009', 'an original audiobook , not published in book form'], ['department x', 'goss , james james goss', 'owen , kai kai owen', '2 - cd', 'bbc audio', '2011 - 04 - 03 3 march 2011', 'an original audiobook , not published in book form'], ['ghost train', 'goss , james james goss', 'owen , kai kai owen', '2 - cd', 'bbc audio', '2011 - 04 - 03 3 march 2011', 'an original audiobook , not published in book form'], ['long time dead', 'pinborough , sarah sarah pinborough', 'varma , idria indira varma', 'download', 'audiogo', '2011 - 10 - 01 october 2011', 'unabridged'], ['the men who sold the world', 'adams , guy guy adams', 'telfer , john john telfer', 'download', 'audiogo', '2011 - 10 - 01 october 2011', 'unabridged'], ['army of one', 'edginton , ian ian edginton', 'owen , kai kai owen', 'download / cd', 'audiogo', '2012 - 03 - 08 8 march 2012', 'an original audiobook , not published in book form'], ['fallout', 'llewellyn , david david llewellyn', 'price , tom tom price', 'download / cd', 'audiogo', '2012 - 04 - 05 5 april 2012', 'an original audiobook , not published in book form'], ['red skies', 'lidster , joseph joseph lidster', 'telfer , john john telfer', 'download / cd', 'audiogo', '2012 - 05 - 03 3 may 2012', 'an original audiobook , not published in book form']] |
2009 world championships in athletics - men 's 1500 metres | https://en.wikipedia.org/wiki/2009_World_Championships_in_Athletics_%E2%80%93_Men%27s_1500_metres | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23987362-2.html.csv | majority | most of the records have been run in under 3:30 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '3:30', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', '3:26.00', '3:30'], 'result': True, 'ind': 0, 'tointer': 'for the 3:26.00 records of all rows , most of them are less than 3:30 .', 'tostr': 'most_less { all_rows ; 3:26.00 ; 3:30 } = true'} | most_less { all_rows ; 3:26.00 ; 3:30 } = true | for the 3:26.00 records of all rows , most of them are less than 3:30 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, '3:26.00_3': 3, '3:30_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', '3:26.00_3': '3:26.00', '3:30_4': '3:30'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], '3:26.00_3': [0], '3:30_4': [0]} | ['world record', 'hicham el guerrouj ( mar )', '3:26.00', 'rome , italy', '14 july 1998'] | [['championship record', 'hicham el guerrouj ( mar )', '3:27.65', 'seville , spain', '14 august 1999'], ['world leading', 'augustine choge ( ken )', '3:29.47', 'berlin , germany', '14 june 2009'], ['african record', 'hicham el guerrouj ( mar )', '3:26.00', 'rome , italy', '14 july 1998'], ['asian record', 'rashid ramzi ( bhr )', '3:29.14', 'rome , italy', '14 july 2006'], ['north american record', 'bernard lagat ( usa )', '3:29.30', 'rieti , italy', '28 august 2005'], ['south american record', 'hudson de souza ( bra )', '3:33.25', 'rieti , italy', '28 august 2005'], ['european record', 'fermín cacho ( esp )', '3:28.95', 'zürich , switzerland', '13 august 1997']] |
1936 vfl season | https://en.wikipedia.org/wiki/1936_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790804-17.html.csv | aggregation | the total crowd at all games during the 1936 vfl season was 86100 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '86100', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '86100', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '86100'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 86100 } = true', 'tointer': 'the sum of the crowd record of all rows is 86100 .'} | round_eq { sum { all_rows ; crowd } ; 86100 } = true | the sum of the crowd record of all rows is 86100 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '86100_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '86100_5': '86100'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '86100_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['north melbourne', '15.7 ( 97 )', 'st kilda', '15.18 ( 108 )', 'arden street oval', '8000', '29 august 1936'], ['footscray', '8.17 ( 65 )', 'melbourne', '9.18 ( 72 )', 'western oval', '13000', '29 august 1936'], ['south melbourne', '16.10 ( 106 )', 'hawthorn', '15.11 ( 101 )', 'lake oval', '12000', '29 august 1936'], ['richmond', '8.7 ( 55 )', 'geelong', '12.9 ( 81 )', 'punt road oval', '14000', '29 august 1936'], ['fitzroy', '9.16 ( 70 )', 'essendon', '17.16 ( 118 )', 'brunswick street oval', '9000', '29 august 1936'], ['collingwood', '13.11 ( 89 )', 'carlton', '13.12 ( 90 )', 'victoria park', '30100', '29 august 1936']] |
2008 - 09 boston celtics season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Boston_Celtics_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17140608-6.html.csv | unique | in december of the 2008 - 09 boston celtics season , their game against new york was the only occasion in which kevin garnett had the highest individual assist total . | {'scope': 'all', 'row': '10', 'col': '7', 'col_other': '2,3', 'criterion': 'fuzzily_match', 'value': 'kevin garnett', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'kevin garnett'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to kevin garnett .', 'tostr': 'filter_eq { all_rows ; high assists ; kevin garnett }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; high assists ; kevin garnett } }', 'tointer': 'select the rows whose high assists record fuzzily matches to kevin garnett . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'kevin garnett'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to kevin garnett .', 'tostr': 'filter_eq { all_rows ; high assists ; kevin garnett }'}, 'date'], 'result': 'december 21', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; high assists ; kevin garnett } ; date }'}, 'december 21'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; date } ; december 21 }', 'tointer': 'the date record of this unqiue row is december 21 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'high assists', 'kevin garnett'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose high assists record fuzzily matches to kevin garnett .', 'tostr': 'filter_eq { all_rows ; high assists ; kevin garnett }'}, 'team'], 'result': 'new york', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; high assists ; kevin garnett } ; team }'}, 'new york'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; team } ; new york }', 'tointer': 'the team record of this unqiue row is new york .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; date } ; december 21 } ; eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; team } ; new york } }', 'tointer': 'the date record of this unqiue row is december 21 . the team record of this unqiue row is new york .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; high assists ; kevin garnett } } ; and { eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; date } ; december 21 } ; eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; team } ; new york } } } = true', 'tointer': 'select the rows whose high assists record fuzzily matches to kevin garnett . there is only one such row in the table . the date record of this unqiue row is december 21 . the team record of this unqiue row is new york .'} | and { only { filter_eq { all_rows ; high assists ; kevin garnett } } ; and { eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; date } ; december 21 } ; eq { hop { filter_eq { all_rows ; high assists ; kevin garnett } ; team } ; new york } } } = true | select the rows whose high assists record fuzzily matches to kevin garnett . there is only one such row in the table . the date record of this unqiue row is december 21 . the team record of this unqiue row is new york . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'high assists_10': 10, 'kevin garnett_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'date_12': 12, 'december 21_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'team_14': 14, 'new york_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'high assists_10': 'high assists', 'kevin garnett_11': 'kevin garnett', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_12': 'date', 'december 21_13': 'december 21', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'team_14': 'team', 'new york_15': 'new york'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'high assists_10': [0], 'kevin garnett_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'date_12': [2], 'december 21_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'team_14': [4], 'new york_15': [5]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['19', 'december 1', 'orlando', 'w 107 - 88 ( ot )', 'paul pierce ( 24 )', 'kendrick perkins ( 13 )', 'rajon rondo ( 12 )', 'td banknorth garden 18624', '17 - 2'], ['20', 'december 3', 'indiana', 'w 114 - 96 ( ot )', 'ray allen ( 31 )', 'kevin garnett ( 14 )', 'rajon rondo ( 17 )', 'td banknorth garden 18624', '18 - 2'], ['21', 'december 5', 'portland', 'w 93 - 78 ( ot )', 'ray allen ( 19 )', 'kendrick perkins ( 12 )', 'rajon rondo ( 7 )', 'td banknorth garden 18624', '19 - 2'], ['22', 'december 7', 'indiana', 'w 122 - 117 ( ot )', 'ray allen ( 35 )', 'kevin garnett ( 20 )', 'paul pierce ( 8 )', 'conseco fieldhouse 16102', '20 - 2'], ['23', 'december 11', 'washington', 'w 122 - 88 ( ot )', 'ray allen , paul pierce ( 22 )', 'kevin garnett ( 12 )', 'paul pierce ( 8 )', 'verizon center 20173', '21 - 2'], ['24', 'december 12', 'new orleans', 'w 94 - 82 ( ot )', 'paul pierce ( 28 )', 'kendrick perkins ( 13 )', 'paul pierce ( 6 )', 'td banknorth garden 18624', '22 - 2'], ['25', 'december 15', 'utah', 'w 100 - 91 ( ot )', 'rajon rondo ( 25 )', 'kendrick perkins ( 14 )', 'rajon rondo ( 8 )', 'td banknorth garden 18624', '23 - 2'], ['26', 'december 17', 'atlanta', 'w 88 - 85 ( ot )', 'kevin garnett , paul pierce ( 18 )', 'kendrick perkins ( 10 )', 'rajon rondo ( 7 )', 'philips arena 18729', '24 - 2'], ['27', 'december 19', 'chicago', 'w 126 - 108 ( ot )', 'ray allen ( 27 )', 'kendrick perkins ( 8 )', 'rajon rondo ( 15 )', 'td banknorth garden 18624', '25 - 2'], ['28', 'december 21', 'new york', 'w 124 - 105 ( ot )', 'rajon rondo ( 26 )', 'kendrick perkins ( 12 )', 'kevin garnett ( 8 )', 'td banknorth garden 18624', '26 - 2'], ['29', 'december 23', 'philadelphia', 'w 110 - 91 ( ot )', 'kevin garnett , rajon rondo ( 18 )', 'kendrick perkins ( 11 )', 'paul pierce ( 7 )', 'td banknorth garden 18624', '27 - 2'], ['30', 'december 25', 'la lakers', 'l 83 - 92 ( ot )', 'kevin garnett ( 22 )', 'paul pierce ( 10 )', 'rajon rondo ( 12 )', 'staples center 18997', '27 - 3'], ['31', 'december 26', 'golden state', 'l 89 - 99 ( ot )', 'paul pierce ( 21 )', 'rajon rondo ( 10 )', 'rajon rondo ( 9 )', 'oracle arena 19596', '27 - 4'], ['32', 'december 28', 'sacramento', 'w 108 - 63 ( ot )', 'kevin garnett ( 21 )', 'kendrick perkins ( 12 )', 'rajon rondo ( 6 )', 'arco arena 16029', '28 - 4'], ['33', 'december 30', 'portland', 'l 86 - 91 ( ot )', 'paul pierce ( 28 )', 'kevin garnett ( 8 )', 'rajon rondo ( 7 )', 'rose garden 20651', '28 - 5']] |
tnq | https://en.wikipedia.org/wiki/TNQ | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12112313-1.html.csv | superlative | for tnq , the earliest first air date was for the city of townsville . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '6', '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 air date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; first air date }'}, 'city'], 'result': 'townsville', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; first air date } ; city }'}, 'townsville'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; first air date } ; city } ; townsville } = true', 'tointer': 'select the row whose first air date record of all rows is minimum . the city record of this row is townsville .'} | eq { hop { argmin { all_rows ; first air date } ; city } ; townsville } = true | select the row whose first air date record of all rows is minimum . the city record of this row is townsville . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'first air date_5': 5, 'city_6': 6, 'townsville_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'first air date_5': 'first air date', 'city_6': 'city', 'townsville_7': 'townsville'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'first air date_5': [0], 'city_6': [1], 'townsville_7': [2]} | ['region served', 'city', 'channels ( analog / digital )', 'first air date', 'erp ( analog / digital )', 'haat ( analog / digital ) 1', 'transmitter location'] | [['cairns 2', 'cairns', '10 ( vhf ) 3 6 ( vhf )', '7 september 1966', '200 kw 50 kw', '1177 m 1190 m', 'mount bellenden ker'], ['darling downs', 'toowoomba', '41 ( uhf ) 3 40 ( uhf )', '31 december 1990', '1300 kw 500 kw', '515 m 520 m', 'mount mowbullan'], ['mackay', 'mackay', '33 ( uhf ) 3 32 ( uhf )', '31 december 1990', '1300 kw 360 kw', '612 m 630 m', 'mount blackwood'], ['rockhampton', 'rockhampton', '34 ( uhf ) 3 36 ( uhf )', '31 december 1990', '2000 kw 500 kw', '523 m 523 m', 'mount hopeful'], ['southern downs', 'warwick', '39 ( uhf ) 3 52 ( uhf )', '31 december 1990', '600 kw 500 kw', '301 m 301 m', 'passchendaele ridge'], ['townsville', 'townsville', '7 ( vhf ) 3 36 ( uhf )', '1 november 1962', '200 kw 200 kw', '612 m 655 m', 'mount stuart'], ['wide bay', 'maryborough', '33 ( uhf ) 3 9 ( vhf )', '31 december 1990', '1000 kw 60 kw', '646 m 646 m', 'mount goonaneman']] |
1979 detroit lions season | https://en.wikipedia.org/wiki/1979_Detroit_Lions_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18733329-2.html.csv | majority | the majority of games in the 1979 detroit lions season resulted in losses for the lions . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'} | most_eq { all_rows ; result ; l } = true | for the result records of all rows , most of them fuzzily match to l . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 1 , 1979', 'tampa bay buccaneers', 'l 31 - 16', '68225'], ['2', 'september 9 , 1979', 'washington redskins', 'l 27 - 24', '54991'], ['3', 'september 16 , 1979', 'new york jets', 'l 31 - 10', '49612'], ['4', 'september 23 , 1979', 'atlanta falcons', 'w 24 - 23', '56249'], ['5', 'september 30 , 1979', 'minnesota vikings', 'l 13 - 10', '75295'], ['6', 'october 7 , 1979', 'new england patriots', 'l 24 - 17', '60629'], ['7', 'october 14 , 1979', 'green bay packers', 'l 24 - 16', '53930'], ['8', 'october 21 , 1979', 'new orleans saints', 'l 17 - 7', '57428'], ['9', 'october 28 , 1979', 'buffalo bills', 'l 20 - 17', '61911'], ['10', 'november 4 , 1979', 'chicago bears', 'l 35 - 7', '50108'], ['11', 'november 11 , 1979', 'tampa bay buccaneers', 'l 16 - 14', '70461'], ['12', 'november 18 , 1979', 'minnesota vikings', 'l 14 - 7', '43650'], ['13', 'november 22 , 1979', 'chicago bears', 'w 20 - 0', '66219'], ['14', 'december 2 , 1979', 'philadelphia eagles', 'l 44 - 7', '66128'], ['15', 'december 9 , 1979', 'miami dolphins', 'l 28 - 10', '78087'], ['16', 'december 15 , 1979', 'green bay packers', 'l 18 - 13', '57376']] |
2007 oafl season | https://en.wikipedia.org/wiki/2007_OAFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15764109-1.html.csv | aggregation | in the 2007 oafl season , the average number of points for , for teams that had 13 wins , was 1174 . | {'scope': 'subset', 'col': '4', 'type': 'average', 'result': '1174', 'subset': {'col': '2', 'criterion': 'equal', 'value': '13'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'wins', '13'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; wins ; 13 }', 'tointer': 'select the rows whose wins record is equal to 13 .'}, 'points for'], 'result': '1174', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; wins ; 13 } ; points for }'}, '1174'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; wins ; 13 } ; points for } ; 1174 } = true', 'tointer': 'select the rows whose wins record is equal to 13 . the average of the points for record of these rows is 1174 .'} | round_eq { avg { filter_eq { all_rows ; wins ; 13 } ; points for } ; 1174 } = true | select the rows whose wins record is equal to 13 . the average of the points for record of these rows is 1174 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'wins_5': 5, '13_6': 6, 'points for_7': 7, '1174_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'wins_5': 'wins', '13_6': '13', 'points for_7': 'points for', '1174_8': '1174'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'wins_5': [0], '13_6': [0], 'points for_7': [1], '1174_8': [2]} | ['club', 'wins', 'loses', 'points for', 'points against', 'percentage', 'points'] | [['etobicoke kangaroos', '13', '1', '1173', '405', '289.63 %', '52'], ['toronto eagles', '13', '1', '1175', '592', '198.48 %', '52'], ['broadview hawks', '10', '4', '1040', '559', '186.05 %', '40'], ['toronto downtown dingos', '7', '7', '786', '707', '111.17 %', '28'], ['hamilton wildcats', '6', '8', '658', '943', '69.78 %', '24'], ['high park demons', '4', '10', '631', '863', '73.12 %', '16'], ['guelph gargoyles', '4', '10', '639', '894', '71.48 %', '16'], ['lakeshore rebels', '4', '10', '408', '956', '42.68 %', '16'], ['central blues', '2', '12', '438', '1029', '42.57 %', '8']] |
coleen sommer | https://en.wikipedia.org/wiki/Coleen_Sommer | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14987413-1.html.csv | majority | all of the events that coleen sommer competed in were high jump events . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'high jump', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'notes', 'high jump'], 'result': True, 'ind': 0, 'tointer': 'for the notes records of all rows , all of them fuzzily match to high jump .', 'tostr': 'all_eq { all_rows ; notes ; high jump } = true'} | all_eq { all_rows ; notes ; high jump } = true | for the notes records of all rows , all of them fuzzily match to high jump . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'notes_3': 3, 'high jump_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'notes_3': 'notes', 'high jump_4': 'high jump'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'notes_3': [0], 'high jump_4': [0]} | ['year', 'competition', 'venue', 'position', 'notes'] | [['1983', 'pan american games', 'caracas , venezuela', '1st', 'high jump'], ['1983', 'world championships', 'helsinki , finland', '4th', 'high jump'], ['1987', 'pan american games', 'indianapolis , united states', '1st', 'high jump'], ['1987', 'world championships', 'rome , italy', '11th', 'high jump'], ['1988', 'olympic games', 'seoul , south korea', '18th', 'high jump']] |
2008 baltimore ravens season | https://en.wikipedia.org/wiki/2008_Baltimore_Ravens_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15013564-4.html.csv | count | during the 2008 season , the ravens were on cbs twelve times . | {'scope': 'all', 'criterion': 'equal', 'value': 'cbs', 'result': '12', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tv network', 'cbs'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tv network record fuzzily matches to cbs .', 'tostr': 'filter_eq { all_rows ; tv network ; cbs }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; tv network ; cbs } }', 'tointer': 'select the rows whose tv network record fuzzily matches to cbs . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; tv network ; cbs } } ; 12 } = true', 'tointer': 'select the rows whose tv network record fuzzily matches to cbs . the number of such rows is 12 .'} | eq { count { filter_eq { all_rows ; tv network ; cbs } } ; 12 } = true | select the rows whose tv network record fuzzily matches to cbs . the number of such rows is 12 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'tv network_5': 5, 'cbs_6': 6, '12_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'tv network_5': 'tv network', 'cbs_6': 'cbs', '12_7': '12'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'tv network_5': [0], 'cbs_6': [0], '12_7': [2]} | ['week', 'opponent', 'date', 'tv network', 'time ( et )', 'stadium', 'location', 'results', 'record'] | [['1', 'cincinnati bengals', 'sunday , september 7 , 2008', 'cbs', '1:00 pm', 'm & t bank stadium', 'baltimore , maryland', 'w 17 - 10', '1 - 0'], ['2', 'bye week', 'bye week', 'bye week', 'bye week', 'bye week', 'bye week', 'bye week', 'bye week'], ['3', 'cleveland browns', 'sunday , september 21 , 2008', 'cbs', '4:15 pm', 'm & t bank stadium', 'baltimore , maryland', 'w 28 - 10', '2 - 0'], ['4', 'pittsburgh steelers', 'monday , september 29 , 2008', 'espn', '8:30 pm', 'heinz field', 'pittsburgh , pennsylvania', 'l 20 - 23 ot', '2 - 1'], ['5', 'tennessee titans', 'sunday , october 5 , 2008', 'cbs', '1:00 pm', 'm & t bank stadium', 'baltimore , maryland', 'l 10 - 13', '2 - 2'], ['6', 'indianapolis colts', 'sunday , october 12 , 2008', 'cbs', '1:00 pm', 'lucas oil stadium', 'indianapolis , indiana', 'l 3 - 31', '2 - 3'], ['7', 'miami dolphins', 'sunday , october 19 , 2008', 'cbs', '1:00 pm', 'dolphin stadium', 'miami , florida', 'w 27 - 13', '3 - 3'], ['8', 'oakland raiders', 'sunday , october 26 , 2008', 'cbs', '1:00 pm', 'm & t bank stadium', 'baltimore , maryland', 'w 29 - 10', '4 - 3'], ['9', 'cleveland browns', 'sunday , november 2 , 2008', 'cbs', '1:00 pm', 'cleveland browns stadium', 'cleveland , ohio', 'w 37 - 27', '5 - 3'], ['10', 'houston texans', 'sunday , november 9 , 2008', 'cbs', '1:00 pm', 'reliant stadium', 'houston , texas', 'w 41 - 13', '6 - 3'], ['11', 'new york giants', 'sunday , november 16 , 2008', 'cbs', '1:00 pm', 'giants stadium', 'east rutherford , new jersey', 'l 10 - 30', '6 - 4'], ['12', 'philadelphia eagles', 'sunday , november 23 , 2008', 'fox', '1:00 pm', 'm & t bank stadium', 'baltimore , maryland', 'w 36 - 7', '7 - 4'], ['13', 'cincinnati bengals', 'sunday , november 30 , 2008', 'cbs', '1:00 pm', 'paul brown stadium', 'cincinnati , ohio', 'w 34 - 3', '8 - 4'], ['14', 'washington redskins', 'sunday , december 7 , 2008', 'nbc', '8:15 pm', 'm & t bank stadium', 'baltimore , maryland', 'w 24 - 10', '9 - 4'], ['15', 'pittsburgh steelers', 'sunday , december 14 , 2008', 'cbs', '4:15 pm', 'm & t bank stadium', 'baltimore , maryland', 'l 9 - 13', '9 - 5'], ['16', 'dallas cowboys', 'saturday , december 20 , 2008', 'nfl network', '8:00 pm', 'texas stadium', 'irving , texas', 'w 33 - 24', '10 - 5'], ['17', 'jacksonville jaguars', 'sunday , december 28 , 2008', 'cbs', '4:15 pm', 'm & t bank stadium', 'baltimore , maryland', 'w 27 - 7', '11 - 5']] |
moroccan grand prix | https://en.wikipedia.org/wiki/Moroccan_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1167997-1.html.csv | unique | in the moroccan grand prix , when the location is casablanca , the only time the constructor was delage was when the driver was comte de vaugelas . | {'scope': 'subset', 'row': '16', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'delage', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'casablanca'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'casablanca'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; casablanca }', 'tointer': 'select the rows whose location record fuzzily matches to casablanca .'}, 'constructor', 'delage'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to casablanca . among these rows , select the rows whose constructor record fuzzily matches to delage .', 'tostr': 'filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage } }', 'tointer': 'select the rows whose location record fuzzily matches to casablanca . among these rows , select the rows whose constructor record fuzzily matches to delage . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'casablanca'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; casablanca }', 'tointer': 'select the rows whose location record fuzzily matches to casablanca .'}, 'constructor', 'delage'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to casablanca . among these rows , select the rows whose constructor record fuzzily matches to delage .', 'tostr': 'filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage }'}, 'driver'], 'result': 'comte de vaugelas', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage } ; driver }'}, 'comte de vaugelas'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage } ; driver } ; comte de vaugelas }', 'tointer': 'the driver record of this unqiue row is comte de vaugelas .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage } } ; eq { hop { filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage } ; driver } ; comte de vaugelas } } = true', 'tointer': 'select the rows whose location record fuzzily matches to casablanca . among these rows , select the rows whose constructor record fuzzily matches to delage . there is only one such row in the table . the driver record of this unqiue row is comte de vaugelas .'} | and { only { filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage } } ; eq { hop { filter_eq { filter_eq { all_rows ; location ; casablanca } ; constructor ; delage } ; driver } ; comte de vaugelas } } = true | select the rows whose location record fuzzily matches to casablanca . among these rows , select the rows whose constructor record fuzzily matches to delage . there is only one such row in the table . the driver record of this unqiue row is comte de vaugelas . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'location_8': 8, 'casablanca_9': 9, 'constructor_10': 10, 'delage_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'driver_12': 12, 'comte de vaugelas_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'location_8': 'location', 'casablanca_9': 'casablanca', 'constructor_10': 'constructor', 'delage_11': 'delage', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'driver_12': 'driver', 'comte de vaugelas_13': 'comte de vaugelas'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'location_8': [0], 'casablanca_9': [0], 'constructor_10': [1], 'delage_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'driver_12': [3], 'comte de vaugelas_13': [4]} | ['year', 'driver', 'constructor', 'category', 'location', 'report'] | [['1958', 'stirling moss', 'vanwall', 'formula one', 'ain - diab', 'report'], ['1957', 'jean behra', 'maserati', 'formula one', 'ain - diab', 'report'], ['1956', 'maurice trintignant', 'ferrari', 'sports cars', 'agadir', 'report'], ['1955', 'mike sparken', 'ferrari', 'sports cars', 'agadir', 'report'], ['1954', 'giuseppe farina', 'ferrari', 'sports cars', 'agadir', 'report'], ['1953 - 1935', 'not held', 'not held', 'not held', 'not held', 'not held'], ['1934', 'louis chiron', 'alfa romeo', 's touring car', 'anfa', 'report'], ['1933', 'not held', 'not held', 'not held', 'not held', 'not held'], ['1932', 'marcel lehoux', 'bugatti', 's touring car', 'anfa', 'report'], ['1931', 'stanisław czaykowski', 'bugatti', 's touring car', 'anfa', 'report'], ['1930', 'charles bénitah', 'amilcar', 's touring car', 'anfa', 'report'], ['1929', 'not held', 'not held', 'not held', 'not held', 'not held'], ['1928', 'e meyer', 'bugatti', 's touring car', 'casablanca', 'report'], ['1927', 'g roll', 'georges irat', 's touring car', 'casablanca', 'report'], ['1926', 'r meyerl', 'bugatti', 's touring car', 'casablanca', 'report'], ['1925', 'comte de vaugelas', 'delage', 's touring car', 'casablanca', 'report']] |
1942 vfl season | https://en.wikipedia.org/wiki/1942_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807990-7.html.csv | comparative | more people attended the richmond game than the footscray game . | {'row_1': '1', 'row_2': '5', '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', 'richmond'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team record fuzzily matches to richmond .', 'tostr': 'filter_eq { all_rows ; home team ; richmond }'}, 'crowd'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; home team ; richmond } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to richmond . take the crowd record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home team', 'footscray'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home team record fuzzily matches to footscray .', 'tostr': 'filter_eq { all_rows ; home team ; footscray }'}, 'crowd'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; home team ; footscray } ; crowd }', 'tointer': 'select the rows whose home team record fuzzily matches to footscray . take the crowd record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; home team ; richmond } ; crowd } ; hop { filter_eq { all_rows ; home team ; footscray } ; crowd } } = true', 'tointer': 'select the rows whose home team record fuzzily matches to richmond . take the crowd record of this row . select the rows whose home team record fuzzily matches to footscray . take the crowd record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; home team ; richmond } ; crowd } ; hop { filter_eq { all_rows ; home team ; footscray } ; crowd } } = true | select the rows whose home team record fuzzily matches to richmond . take the crowd record of this row . select the rows whose home team record fuzzily matches to footscray . 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, 'richmond_8': 8, 'crowd_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home team_11': 11, 'footscray_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', 'richmond_8': 'richmond', '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', 'footscray_12': 'footscray', 'crowd_13': 'crowd'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home team_7': [0], 'richmond_8': [0], 'crowd_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home team_11': [1], 'footscray_12': [1], 'crowd_13': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '10.9 ( 69 )', 'south melbourne', '11.20 ( 86 )', 'punt road oval', '18000', '20 june 1942'], ['fitzroy', '16.14 ( 110 )', 'hawthorn', '14.10 ( 94 )', 'brunswick street oval', '5000', '20 june 1942'], ['north melbourne', '11.10 ( 76 )', 'melbourne', '12.11 ( 83 )', 'arden street oval', '4000', '20 june 1942'], ['st kilda', '11.14 ( 80 )', 'collingwood', '9.14 ( 68 )', 'toorak park', '5000', '20 june 1942'], ['footscray', '12.19 ( 91 )', 'carlton', '10.12 ( 72 )', 'yarraville oval', '8500', '20 june 1942']] |
silpathorn award | https://en.wikipedia.org/wiki/Silpathorn_Award | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12896747-1.html.csv | unique | danu huntrakul was the only winner for music in 2004 . | {'scope': 'all', 'row': '1', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'danu huntrakul', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'music', 'danu huntrakul'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose music record fuzzily matches to danu huntrakul .', 'tostr': 'filter_eq { all_rows ; music ; danu huntrakul }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; music ; danu huntrakul } }', 'tointer': 'select the rows whose music record fuzzily matches to danu huntrakul . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'music', 'danu huntrakul'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose music record fuzzily matches to danu huntrakul .', 'tostr': 'filter_eq { all_rows ; music ; danu huntrakul }'}, 'year'], 'result': '2004', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; music ; danu huntrakul } ; year }'}, '2004'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; music ; danu huntrakul } ; year } ; 2004 }', 'tointer': 'the year record of this unqiue row is 2004 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; music ; danu huntrakul } } ; eq { hop { filter_eq { all_rows ; music ; danu huntrakul } ; year } ; 2004 } } = true', 'tointer': 'select the rows whose music record fuzzily matches to danu huntrakul . there is only one such row in the table . the year record of this unqiue row is 2004 .'} | and { only { filter_eq { all_rows ; music ; danu huntrakul } } ; eq { hop { filter_eq { all_rows ; music ; danu huntrakul } ; year } ; 2004 } } = true | select the rows whose music record fuzzily matches to danu huntrakul . there is only one such row in the table . the year record of this unqiue row is 2004 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'music_7': 7, 'danu huntrakul_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2004_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'music_7': 'music', 'danu huntrakul_8': 'danu huntrakul', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2004_10': '2004'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'music_7': [0], 'danu huntrakul_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2004_10': [3]} | ['year', 'literature', 'music', 'film', 'performing arts'] | [['2004', 'chart korbjitti', 'danu huntrakul', 'pen - ek ratanaruang', 'pradit prasarttong'], ['2005', 'saksiri meesomsueb', 'bundit ungrangsee', 'apichatpong weerasethakul', 'manop meejamrus'], ['2006', 'win lyovarin', 'nat yontararak', 'wisit sasanatieng', 'pichet klunchuen'], ['2007', 'siriworn kaewkan', 'narong prangcharoen', 'thunska pansittivorakul', 'nimit pipithkul'], ['2008', 'paiwarin khao - ngam khajornrit raksa', 'narongrit dhamabutra', 'nonzee nimibutr', 'sineenadh keitprapa'], ['2009', 'orasom suddhisakorn', 'den euprasert', 'pimpaka towira', 'janaprakal chandruang'], ['2010', 'saneh sangsuk', 'chaiyoot tosa - nga', 'aditya assarat', 'nikorn saetang']] |
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