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snowy mountains scheme | https://en.wikipedia.org/wiki/Snowy_Mountains_Scheme | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-177948-2.html.csv | ordinal | in the dams of the snowy mountains scheme listed , the first dam was completed in 1955 . | {'row': '5', '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', 'year completed', '1'], 'result': '1955', 'ind': 0, 'tostr': 'nth_min { all_rows ; year completed ; 1 }', 'tointer': 'the 1st minimum year completed record of all rows is 1955 .'}, '1955'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; year completed ; 1 } ; 1955 } = true', 'tointer': 'the 1st minimum year completed record of all rows is 1955 .'} | eq { nth_min { all_rows ; year completed ; 1 } ; 1955 } = true | the 1st minimum year completed record of all rows is 1955 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'year completed_4': 4, '1_5': 5, '1955_6': 6} | {'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'year completed_4': 'year completed', '1_5': '1', '1955_6': '1955'} | {'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'year completed_4': [0], '1_5': [0], '1955_6': [1]} | ['dam constructed', 'year completed', 'impounded body of water', 'reservoir capacity', 'dam wall height', 'dam type'] | [['blowering dam', '1968', 'blowering reservoir', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['deep creek dam', '1961', 'deep creek reservoir', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['eucumbene dam', '1958', 'lake eucumbene', 'ml ( 10 6cuft )', '-', 'earthfill embankment'], ['geehi dam', '1966', 'geehi reservoir', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['guthega dam', '1955', 'guthega reservoir', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['happy jacks dam', '1959', 'happy jacks pondage', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['island bend dam', '1965', 'island bend pondage', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['jindabyne dam', '1967', 'lake jindabyne', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['jounama dam', '1968', 'jounama pondage', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['khancoban dam', '1966', 'khancoban reservoir', 'ml ( 10 6cuft )', '-', 'earthfill embankment'], ['murray two dam', '1968', 'murray two pondage', 'ml ( 10 6cuft )', '-', 'concrete arch'], ['talbingo dam', '1970', 'talbingo reservoir', 'ml ( 10 6cuft )', '-', 'rockfill embankment'], ['tantangara dam', '1960', 'tantangara reservoir', 'ml ( 10 6cuft )', '-', 'concrete gravity'], ['tooma dam', '1961', 'tooma reservoir', 'ml ( 10 6cuft )', '-', 'concrete embankment'], ['tumut pond dam', '1959', 'tumut pond reservoir', 'ml ( 10 6cuft )', '-', 'concrete arch'], ['tumut two dam', '1961', 'tumut two pondage', 'ml ( 10 6cuft )', '-', 'concrete gravity']] |
1983 formula one season | https://en.wikipedia.org/wiki/1983_Formula_One_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1140074-2.html.csv | ordinal | for the 1983 formula one season , the 2nd to last race was the italian grand prix . | {'row': '13', 'col': '3', 'order': '13', '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', '13'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 13 }'}, 'race'], 'result': 'italian grand prix', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 13 } ; race }'}, 'italian grand prix'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 13 } ; race } ; italian grand prix } = true', 'tointer': 'select the row whose date record of all rows is 13th minimum . the race record of this row is italian grand prix .'} | eq { hop { nth_argmin { all_rows ; date ; 13 } ; race } ; italian grand prix } = true | select the row whose date record of all rows is 13th minimum . the race record of this row is italian grand prix . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '13_6': 6, 'race_7': 7, 'italian grand prix_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', '13_6': '13', 'race_7': 'race', 'italian grand prix_8': 'italian grand prix'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '13_6': [0], 'race_7': [1], 'italian grand prix_8': [2]} | ['rnd', 'race', 'date', 'location', 'pole position', 'fastest lap', 'race winner', 'constructor', 'report'] | [['1', 'brazilian grand prix', '13 march', 'jacarepaguá', 'keke rosberg', 'nelson piquet', 'nelson piquet', 'brabham - bmw', 'report'], ['2', 'united states grand prix west', '27 march', 'long beach', 'patrick tambay', 'niki lauda', 'john watson', 'mclaren - ford', 'report'], ['3', 'french grand prix', '17 april', 'paul ricard', 'alain prost', 'alain prost', 'alain prost', 'renault', 'report'], ['4', 'san marino grand prix', '1 may', 'imola', 'rené arnoux', 'riccardo patrese', 'patrick tambay', 'ferrari', 'report'], ['5', 'monaco grand prix', '15 may', 'monaco', 'alain prost', 'nelson piquet', 'keke rosberg', 'williams - ford', 'report'], ['6', 'belgian grand prix', '22 may', 'spa - francorchamps', 'alain prost', 'andrea de cesaris', 'alain prost', 'renault', 'report'], ['7', 'detroit grand prix', '5 june', 'detroit', 'rené arnoux', 'john watson', 'michele alboreto', 'tyrrell - ford', 'report'], ['8', 'canadian grand prix', '12 june', 'circuit gilles villeneuve', 'rené arnoux', 'patrick tambay', 'rené arnoux', 'ferrari', 'report'], ['9', 'british grand prix', '16 july', 'silverstone', 'rené arnoux', 'alain prost', 'alain prost', 'renault', 'report'], ['10', 'german grand prix', '7 august', 'hockenheimring', 'patrick tambay', 'rené arnoux', 'rené arnoux', 'ferrari', 'report'], ['11', 'austrian grand prix', '14 august', 'österreichring', 'patrick tambay', 'alain prost', 'alain prost', 'renault', 'report'], ['12', 'dutch grand prix', '28 august', 'zandvoort', 'nelson piquet', 'rené arnoux', 'rené arnoux', 'ferrari', 'report'], ['13', 'italian grand prix', '11 september', 'monza', 'riccardo patrese', 'nelson piquet', 'nelson piquet', 'brabham - bmw', 'report'], ['14', 'european grand prix', '25 september', 'brands hatch', 'elio de angelis', 'nigel mansell', 'nelson piquet', 'brabham - bmw', 'report']] |
1995 - 96 atlanta hawks season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Atlanta_Hawks_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18493036-5.html.csv | count | in the 1995 - 96 atlanta hawks season , six of the game played in the omni were lost by atlanta hawks . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'l', 'result': '6', 'col': '4', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'the omni'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location / attendance', 'the omni'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location / attendance ; the omni }', 'tointer': 'select the rows whose location / attendance record fuzzily matches to the omni .'}, 'score', 'l'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location / attendance record fuzzily matches to the omni . among these rows , select the rows whose score record fuzzily matches to l .', 'tostr': 'filter_eq { filter_eq { all_rows ; location / attendance ; the omni } ; score ; l }'}], 'result': '6', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; location / attendance ; the omni } ; score ; l } }', 'tointer': 'select the rows whose location / attendance record fuzzily matches to the omni . among these rows , select the rows whose score record fuzzily matches to l . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; location / attendance ; the omni } ; score ; l } } ; 6 } = true', 'tointer': 'select the rows whose location / attendance record fuzzily matches to the omni . among these rows , select the rows whose score record fuzzily matches to l . the number of such rows is 6 .'} | eq { count { filter_eq { filter_eq { all_rows ; location / attendance ; the omni } ; score ; l } } ; 6 } = true | select the rows whose location / attendance record fuzzily matches to the omni . among these rows , select the rows whose score record fuzzily matches to l . the number of such rows is 6 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'location / attendance_6': 6, 'the omni_7': 7, 'score_8': 8, 'l_9': 9, '6_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'location / attendance_6': 'location / attendance', 'the omni_7': 'the omni', 'score_8': 'score', 'l_9': 'l', '6_10': '6'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'location / attendance_6': [0], 'the omni_7': [0], 'score_8': [1], 'l_9': [1], '6_10': [3]} | ['game', 'date', 'opponent', 'score', 'location / attendance', 'record'] | [['15', 'december 1', 'dallas mavericks', 'l 98 - 106', 'the omni', '9 - 6'], ['game', 'date', 'opponent', 'score', 'location / attendance', 'record'], ['16', 'december 2', 'detroit pistons', 'l 96 - 104', 'the palace of auburn hills', '9 - 7'], ['17', 'december 6', 'washington bullets', 'l 79 - 96', 'us airways arena', '9 - 8'], ['18', 'december 7', 'san antonio spurs', 'l 102 - 104', 'the omni', '9 - 9'], ['19', 'december 9', 'new york knicks', 'l 92 - 101', 'the omni', '9 - 10'], ['20', 'december', 'boston celtics', 'w 108 - 103', 'fleet center', '10 - 10'], ['21', 'december 12', 'minnesota timberwolves', 'l 78 - 85', 'the omni', '10 - 11'], ['22', 'december 14', 'chicago bulls', 'l 108 - 127', 'the omni', '10 - 12'], ['23', 'december 16', 'denver nuggets', 'w 95 - 86', 'the omni', '11 - 12'], ['24', 'december 22', 'new jersey nets', 'w 94 - 91', 'the omni', '12 - 12'], ['25', 'december 23', 'milwaukee bucks', 'l 111 - 115', 'bradley center', '12 - 13'], ['26', 'december 26', 'los angeles clippers', 'w 94 - 88', 'the omni', '13 - 13'], ['27', 'december 29', 'golden state warriors', 'l 96 - 117', 'the omni', '13 - 14'], ['28', 'december 30', 'chicago bulls', 'l 93 - 95', 'united center', '13 - 15']] |
46th united states congress | https://en.wikipedia.org/wiki/46th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2417395-4.html.csv | count | three of the successors in the 46th united states congress were seated due to the vacator passing away . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'died', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'reason for change', 'died'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose reason for change record fuzzily matches to died .', 'tostr': 'filter_eq { all_rows ; reason for change ; died }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; reason for change ; died } }', 'tointer': 'select the rows whose reason for change record fuzzily matches to died . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; reason for change ; died } } ; 3 } = true', 'tointer': 'select the rows whose reason for change record fuzzily matches to died . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; reason for change ; died } } ; 3 } = true | select the rows whose reason for change record fuzzily matches to died . 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, 'reason for change_5': 5, 'died_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', 'reason for change_5': 'reason for change', 'died_6': 'died', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'reason for change_5': [0], 'died_6': [0], '3_7': [2]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['iowa 5th', 'rush clark ( r )', 'died april 29 , 1879', 'william g thompson ( r )', 'october 14 , 1879'], ['ohio 19th', 'james a garfield ( r )', 'resigned 1880', 'ezra b taylor ( r )', 'december 13 , 1880'], ['missouri 7th', 'alfred m lay ( d )', 'died december 8 , 1879', 'john f philips ( d )', 'january 10 , 1880'], ['new york 32nd', 'ray v pierce ( r )', 'resigned september 18 , 1880', 'jonathan scoville ( d )', 'november 12 , 1880'], ['new hampshire 3rd', 'evarts w farr ( r )', 'died november 30 , 1880', 'ossian ray ( r )', 'january 8 , 1881'], ['florida 2nd', 'noble a hull ( d )', 'lost contested election january 22 , 1881', 'horatio bisbee , jr ( r )', 'january 22 , 1881'], ['north carolina 1st', 'joseph j martin ( r )', 'lost contested election january 29 , 1881', 'jesse j yeates ( d )', 'january 29 , 1881']] |
john r. wooden award | https://en.wikipedia.org/wiki/John_R._Wooden_Award | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1243492-3.html.csv | count | for the john r wooden award , when the class is senior , there were two players who had the position of guard . | {'scope': 'subset', 'criterion': 'equal', 'value': 'guard', 'result': '2', 'col': '4', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'senior'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'senior'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; class ; senior }', 'tointer': 'select the rows whose class record fuzzily matches to senior .'}, 'position', 'guard'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose class record fuzzily matches to senior . among these rows , select the rows whose position record fuzzily matches to guard .', 'tostr': 'filter_eq { filter_eq { all_rows ; class ; senior } ; position ; guard }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; class ; senior } ; position ; guard } }', 'tointer': 'select the rows whose class record fuzzily matches to senior . among these rows , select the rows whose position record fuzzily matches to guard . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; class ; senior } ; position ; guard } } ; 2 } = true', 'tointer': 'select the rows whose class record fuzzily matches to senior . among these rows , select the rows whose position record fuzzily matches to guard . the number of such rows is 2 .'} | eq { count { filter_eq { filter_eq { all_rows ; class ; senior } ; position ; guard } } ; 2 } = true | select the rows whose class record fuzzily matches to senior . among these rows , select the rows whose position record fuzzily matches to guard . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'class_6': 6, 'senior_7': 7, 'position_8': 8, 'guard_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'class_6': 'class', 'senior_7': 'senior', 'position_8': 'position', 'guard_9': 'guard', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'class_6': [0], 'senior_7': [0], 'position_8': [1], 'guard_9': [1], '2_10': [3]} | ['season', 'player', 'school', 'position', 'class'] | [['2003 - 04', 'alana beard', 'duke', 'guard', 'senior'], ['2004 - 05', 'seimone augustus', 'lsu', 'guard', 'junior'], ['2005 - 06', 'seimone augustus ( 2 )', 'lsu', 'guard', 'senior'], ['2006 - 07', 'candace parker', 'tennessee', 'center', 'junior'], ['2007 - 08', 'candace parker ( 2 )', 'tennessee', 'center', 'senior'], ['2008 - 09', 'maya moore', 'connecticut', 'forward', 'sophomore'], ['2009 - 10', 'tina charles', 'connecticut', 'center', 'senior'], ['2010 - 11', 'maya moore ( 2 )', 'connecticut', 'forward', 'senior'], ['2011 - 12', 'brittney griner', 'baylor', 'center', 'junior'], ['2012 - 13', 'brittney griner ( 2 )', 'baylor', 'center', 'senior']] |
conan silveira | https://en.wikipedia.org/wiki/Conan_Silveira | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17447030-2.html.csv | majority | the majority of conan silveira 's fights ended in the 1st round . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'round', '1'], 'result': True, 'ind': 0, 'tointer': 'for the round records of all rows , most of them are equal to 1 .', 'tostr': 'most_eq { all_rows ; round ; 1 } = true'} | most_eq { all_rows ; round ; 1 } = true | for the round records of all rows , most of them are equal to 1 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'round_3': 3, '1_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'round_3': 'round', '1_4': '1'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'round_3': [0], '1_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['win', '6 - 4 ( 1 )', 'johnathan ivey', 'tko ( punches )', 'pfl - genesis', '2', 'florida , united states'], ['loss', '5 - 4 ( 1 )', 'wes sims', 'tko', 'hooknshoot - absolute fighting championships 1', '2', 'florida , united states'], ['loss', '5 - 3 ( 1 )', 'dan severn', 'submission ( arm triangle choke )', 'wef 9 - world class', '1', 'indiana , united states'], ['win', '5 - 2 ( 1 )', 'maurice smith', 'submission ( arm triangle choke )', 'wef 7 - stomp in the swamp', '2', 'louisiana , united states'], ['win', '4 - 2 ( 1 )', 'patrick smith', 'dq ( knees on a grounded opponent )', 'wef 6 - world extreme fighting 6', '2', 'florida , united states'], ['loss', '3 - 2 ( 1 )', 'kazushi sakuraba', 'submission ( armbar )', 'ufc japan : ultimate japan', '1', 'yokohama , japan'], ['nc', '3 - 1 ( 1 )', 'kazushi sakuraba', 'no contest ( premature stoppage )', 'ufc japan : ultimate japan', '1', 'yokohama , japan'], ['loss', '3 - 1', 'maurice smith', 'tko ( kick )', 'ef 3 - extreme fighting 3', '3', 'oklahoma , united states'], ['win', '3 - 0', 'carl franks', 'tko', 'ef 2 - extreme fighting 2', '1', 'montreal , quebec , canada'], ['win', '2 - 0', 'victor tatarkin', 'submission', 'ef 1 - extreme fighting 1', '1', 'north carolina , united states'], ['win', '1 - 0', 'gary myers', 'submission ( guillotine choke )', 'ef 1 - extreme fighting 1', '1', 'north carolina , united states']] |
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 | superlative | in the 1952 vfl season , the largest crowd was at the game where the venue was kardinia park . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', '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': 'kardinia park', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; crowd } ; venue }'}, 'kardinia park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; crowd } ; venue } ; kardinia park } = true', 'tointer': 'select the row whose crowd record of all rows is maximum . the venue record of this row is kardinia park .'} | eq { hop { argmax { all_rows ; crowd } ; venue } ; kardinia park } = true | select the row whose crowd record of all rows is maximum . the venue record of this row is kardinia 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, 'kardinia 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', 'kardinia park_7': 'kardinia park'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], 'venue_6': [1], 'kardinia park_7': [2]} | ['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']] |
2010 - 11 scottish premier league | https://en.wikipedia.org/wiki/2010%E2%80%9311_Scottish_Premier_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26980923-2.html.csv | count | only three of the premier league stadiums averaged a higher attendance than 10000 fans per game . | {'scope': 'all', 'criterion': 'greater_than', 'value': '10000', 'result': '3', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'average', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose average record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; average ; 10000 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; average ; 10000 } }', 'tointer': 'select the rows whose average record is greater than 10000 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; average ; 10000 } } ; 3 } = true', 'tointer': 'select the rows whose average record is greater than 10000 . the number of such rows is 3 .'} | eq { count { filter_greater { all_rows ; average ; 10000 } } ; 3 } = true | select the rows whose average record is greater than 10000 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'average_5': 5, '10000_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'average_5': 'average', '10000_6': '10000', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'average_5': [0], '10000_6': [0], '3_7': [2]} | ['team', 'stadium', 'capacity', 'total', 'highest', 'lowest', 'average'] | [['aberdeen', 'pittodrie stadium', '22199', '173460', '15307', '5955', '9129'], ['celtic', 'celtic park', '60832', '930395', '58874', '40750', '48968'], ['dundee united', 'tannadice park', '14209', '140391', '11790', '4918', '7389'], ['hamilton academical', 'new douglas park', '6096', '55056', '5356', '2011', '2898'], ['heart of midlothian', 'tynecastle stadium', '17420', '269506', '17420', '12009', '14185'], ['inverness ct', 'caledonian stadium', '7500', '85998', '7547', '3241', '4526'], ['kilmarnock', 'rugby park', '18128', '122106', '16173', '4214', '6427'], ['motherwell', 'fir park', '13742', '99838', '9716', '3324', '5255'], ['rangers', 'ibrox stadium', '51082', '860793', '50248', '41514', '45305'], ['st johnstone', 'mcdiarmid park', '10673', '72982', '6866', '2253', '3841']] |
kathy whitworth | https://en.wikipedia.org/wiki/Kathy_Whitworth | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1075064-4.html.csv | ordinal | the 1967 women 's western open was kathy whitworth 's second highest winning score . | {'row': '4', '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', 'winning score', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; winning score ; 2 }'}, 'championship'], 'result': "women 's western open", 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; winning score ; 2 } ; championship }'}, "women 's western open"], 'result': True, 'ind': 2, 'tostr': "eq { hop { nth_argmax { all_rows ; winning score ; 2 } ; championship } ; women 's western open } = true", 'tointer': "select the row whose winning score record of all rows is 2nd maximum . the championship record of this row is women 's western open ."} | eq { hop { nth_argmax { all_rows ; winning score ; 2 } ; championship } ; women 's western open } = true | select the row whose winning score record of all rows is 2nd maximum . the championship record of this row is women 's western open . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'winning score_5': 5, '2_6': 6, 'championship_7': 7, "women 's western open_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', 'winning score_5': 'winning score', '2_6': '2', 'championship_7': 'championship', "women 's western open_8": "women 's western open"} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'winning score_5': [0], '2_6': [0], 'championship_7': [1], "women 's western open_8": [2]} | ['year', 'championship', 'winning score', 'margin', 'runner ( s ) - up'] | [['1965', 'titleholders championship', '- 1 ( 71 + 71 + 74 + 71 = 287 )', '10 strokes', 'peggy wilson'], ['1966', 'titleholders championship', '+ 3 ( 74 + 70 + 74 + 73 = 291 )', '2 strokes', 'judy kimball - simon , mary mills'], ['1967', 'lpga championship', '- 8 ( 69 + 74 + 72 + 69 = 284 )', '1 stroke', 'shirley englehorn'], ['1967', "women 's western open", '11 ( 71 + 74 + 73 + 71 = 289 )', '3 strokes', 'sandra haynie'], ['1971', 'eve - lpga championship', '- 4 ( 71 + 73 + 70 + 74 = 288 )', '3 strokes', 'kathy ahern'], ['1975', 'lpga championship', '- 4 ( 70 + 70 + 75 + 73 = 288 )', '1 stroke', 'sandra haynie']] |
1988 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1988_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17231125-7.html.csv | aggregation | in the 1988 u.s. open , the average score of the players was 281 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '281', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '281', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '281'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 281 } = true', 'tointer': 'the average of the score record of all rows is 281 .'} | round_eq { avg { all_rows ; score } ; 281 } = true | the average of the score record of all rows is 281 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '281_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '281_5': '281'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '281_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'curtis strange', 'united states', '70 + 67 + 69 + 72 = 278', '- 6', 'playoff'], ['t1', 'nick faldo', 'england', '72 + 67 + 68 + 71 = 278', '- 6', 'playoff'], ['t3', "mark o'meara", 'united states', '71 + 72 + 66 + 71 = 280', '- 4', '41370'], ['t3', 'steve pate', 'united states', '72 + 69 + 72 + 67 = 280', '- 4', '41370'], ['t3', 'd a weibring', 'united states', '71 + 69 + 68 + 72 = 280', '- 4', '41370'], ['t6', 'paul azinger', 'united states', '69 + 70 + 76 + 66 = 281', '- 3', '25414'], ['t6', 'scott simpson', 'united states', '69 + 66 + 72 + 74 = 281', '- 3', '25414'], ['t8', 'bob gilder', 'united states', '68 + 69 + 70 + 75 = 282', '- 2', '20903'], ['t8', 'fuzzy zoeller', 'united states', '73 + 72 + 71 + 66 = 282', '- 2', '20903'], ['t10', 'fred couples', 'united states', '72 + 67 + 71 + 73 = 283', '- 1', '17870'], ['t10', 'payne stewart', 'united states', '73 + 73 + 70 + 67 = 283', '- 1', '17870']] |
1903 in paleontology | https://en.wikipedia.org/wiki/1903_in_paleontology | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15689683-1.html.csv | count | in 1903 paleontology , there were 3 recordings in colorado . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'colorado', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'unit', 'colorado'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose unit record fuzzily matches to colorado .', 'tostr': 'filter_eq { all_rows ; unit ; colorado }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; unit ; colorado } }', 'tointer': 'select the rows whose unit record fuzzily matches to colorado . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; unit ; colorado } } ; 3 } = true', 'tointer': 'select the rows whose unit record fuzzily matches to colorado . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; unit ; colorado } } ; 3 } = true | select the rows whose unit record fuzzily matches to colorado . 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, 'unit_5': 5, 'colorado_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', 'unit_5': 'unit', 'colorado_6': 'colorado', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'unit_5': [0], 'colorado_6': [0], '3_7': [2]} | ['name', 'novelty', 'status', 'authors', 'unit', 'location'] | [['brachiosaurus', 'gen et sp', 'valid', 'riggs', 'morrison formation , colorado', 'usa'], ['haplocanthosaurus', 'gen et sp', 'valid , nomen conservandum', 'hatcher', 'morrison formation , colorado', 'usa'], ['haplocanthus', 'gen et sp', 'nomen oblitum', 'hatcher', 'morrison formation , colorado', 'usa'], ['ornitholestes', 'gen et sp', 'valid', 'osborn', 'morrison formation , wyoming', 'usa'], ['telmatosaurus', 'gen', 'valid', 'nopcsa', 'sãnpetru formation , transylvania', 'romania']] |
1966 major league baseball draft | https://en.wikipedia.org/wiki/1966_Major_League_Baseball_Draft | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15667202-1.html.csv | majority | the majority of the players in the 1966 major league baseball draft played rhp . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'rhp', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'position', 'rhp'], 'result': True, 'ind': 0, 'tointer': 'for the position records of all rows , most of them fuzzily match to rhp .', 'tostr': 'most_eq { all_rows ; position ; rhp } = true'} | most_eq { all_rows ; position ; rhp } = true | for the position records of all rows , most of them fuzzily match to rhp . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'rhp_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'rhp_4': 'rhp'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'rhp_4': [0]} | ['pick', 'player', 'team', 'position', 'hometown / school'] | [['1', 'steve chilcott', 'new york mets', 'c', 'lancaster , ca'], ['2', 'reggie jackson', 'kansas city athletics', 'of', 'arizona state'], ['3', 'wayne twitchell', 'houston astros', 'rhp', 'portland , or'], ['4', 'ken brett', 'boston red sox', 'lhp', 'el segundo , ca'], ['5', 'dean burk', 'chicago cubs', 'rhp', 'highland , il'], ['6', 'tom grieve', 'washington senators', 'of', 'pittsfield , ma'], ['7', 'leron lee', 'st louis cardinals', 'of', 'sacramento , ca'], ['8', 'jim deneff', 'california angels', 'ss', 'indiana university'], ['9', 'mike biko', 'philadelphia phillies', 'rhp', 'dallas , tx'], ['10', 'jim lyttle', 'new york yankees', 'of', 'florida state'], ['11', 'al santorini', 'milwaukee braves', 'rhp', 'union , nj'], ['12', 'john curtis', 'cleveland indians', 'lhp', 'smithtown , ny'], ['13', 'gary nolan', 'cincinnati reds', 'rhp', 'oroville , ca'], ['14', 'rick konik', 'detroit tigers', '1b', 'detroit , mi'], ['15', 'richie hebner', 'pittsburgh pirates', 'ss', 'norwood , ma'], ['16', 'ted parks', 'baltimore orioles', 'ss', 'university of california'], ['17', 'bob reynolds', 'san francisco giants', 'rhp', 'seattle , wa'], ['18', 'carlos may', 'chicago white sox', 'of', 'birmingham , al'], ['19', 'larry hutton', 'los angeles dodgers', 'rhp', 'greenfield , in'], ['20', 'bob jones', 'minnesota twins', '3b', 'dawson , ga']] |
ernie irvan | https://en.wikipedia.org/wiki/Ernie_Irvan | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1256150-1.html.csv | superlative | the last year that ernie irvan was part of team ulrich was when he started 33rd . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3,5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'ulrich'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'ulrich'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; team ; ulrich }', 'tointer': 'select the rows whose team record fuzzily matches to ulrich .'}, 'year'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; team ; ulrich } ; year }'}, 'start'], 'result': '33', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; team ; ulrich } ; year } ; start }'}, '33'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; team ; ulrich } ; year } ; start } ; 33 } = true', 'tointer': 'select the rows whose team record fuzzily matches to ulrich . select the row whose year record of these rows is maximum . the start record of this row is 33 .'} | eq { hop { argmax { filter_eq { all_rows ; team ; ulrich } ; year } ; start } ; 33 } = true | select the rows whose team record fuzzily matches to ulrich . select the row whose year record of these rows is maximum . the start record of this row is 33 . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'team_6': 6, 'ulrich_7': 7, 'year_8': 8, 'start_9': 9, '33_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'team_6': 'team', 'ulrich_7': 'ulrich', 'year_8': 'year', 'start_9': 'start', '33_10': '33'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'team_6': [0], 'ulrich_7': [0], 'year_8': [1], 'start_9': [2], '33_10': [3]} | ['year', 'manufacturer', 'start', 'finish', 'team'] | [['1988', 'pontiac', 'dnq', 'dnq', 'ulrich'], ['1989', 'pontiac', '33', '41', 'ulrich'], ['1990', 'ford', '18', '13', 'donlavey'], ['1991', 'chevrolet', '2', '1', 'morgan - mcclure'], ['1992', 'chevrolet', '7', '28', 'morgan - mcclure'], ['1993', 'chevrolet', '8', '37', 'morgan - mcclure'], ['1994', 'ford', '3', '2', 'yates'], ['1996', 'ford', '2', '35', 'yates'], ['1997', 'ford', '5', '20', 'yates'], ['1998', 'pontiac', '10', '6', 'mb2'], ['1999', 'pontiac', '31', '14', 'mb2']] |
eurovision song contest 1962 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1962 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-181142-1.html.csv | comparative | lola novaković scored more points in the 1962 eurovision song contest than claudio villa . | {'row_1': '12', 'row_2': '15', 'col': '6', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'lola novaković'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose artist record fuzzily matches to lola novaković .', 'tostr': 'filter_eq { all_rows ; artist ; lola novaković }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; artist ; lola novaković } ; points }', 'tointer': 'select the rows whose artist record fuzzily matches to lola novaković . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'claudio villa'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose artist record fuzzily matches to claudio villa .', 'tostr': 'filter_eq { all_rows ; artist ; claudio villa }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; artist ; claudio villa } ; points }', 'tointer': 'select the rows whose artist record fuzzily matches to claudio villa . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; artist ; lola novaković } ; points } ; hop { filter_eq { all_rows ; artist ; claudio villa } ; points } } = true', 'tointer': 'select the rows whose artist record fuzzily matches to lola novaković . take the points record of this row . select the rows whose artist record fuzzily matches to claudio villa . take the points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; artist ; lola novaković } ; points } ; hop { filter_eq { all_rows ; artist ; claudio villa } ; points } } = true | select the rows whose artist record fuzzily matches to lola novaković . take the points record of this row . select the rows whose artist record fuzzily matches to claudio villa . take the points record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'artist_7': 7, 'lola novaković_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'artist_11': 11, 'claudio villa_12': 12, 'points_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'artist_7': 'artist', 'lola novaković_8': 'lola novaković', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'artist_11': 'artist', 'claudio villa_12': 'claudio villa', 'points_13': 'points'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'artist_7': [0], 'lola novaković_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'artist_11': [1], 'claudio villa_12': [1], 'points_13': [3]} | ['draw', 'language', 'artist', 'english translation', 'place', 'points'] | [['01', 'finnish', 'marion rung', 'chirpy chirp', '7', '4'], ['02', 'french', 'fud leclerc', 'your name', '13', '0'], ['03', 'spanish', 'victor balaguer', 'call me', '13', '0'], ['04', 'german', 'eleonore schwarz', 'only in the vienna air', '13', '0'], ['05', 'danish', 'ellen winther', 'lullaby', '10', '2'], ['06', 'swedish', 'inger berggren', 'sun and spring', '7', '4'], ['07', 'german', 'conny froboess', 'two little italians', '6', '9'], ['08', 'dutch', 'de spelbrekers', '-', '13', '0'], ['09', 'french', 'isabelle aubret', 'a first love', '1', '26'], ['10', 'norwegian', 'inger jacobsen', 'come sun , come rain', '10', '2'], ['11', 'french', 'jean philippe', 'the return', '10', '2'], ['12', 'serbian', 'lola novaković', "do n't turn the lights on at twilight", '4', '10'], ['13', 'english', 'ronnie carroll', '-', '4', '10'], ['14', 'french', 'camillo felgen', 'little chap', '3', '11'], ['15', 'italian', 'claudio villa', 'goodbye , goodbye', '9', '3'], ['16', 'french', 'françois deguelt', 'say nothing', '2', '13']] |
2006 kansas city brigade season | https://en.wikipedia.org/wiki/2006_Kansas_City_Brigade_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11974088-4.html.csv | superlative | jerel meyers had the most yards covered in the 2006 kansas city brigade season games . | {'scope': 'all', 'col_superlative': '3', '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', 'yards'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; yards }'}, 'player'], 'result': 'jerel meyers', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; yards } ; player }'}, 'jerel meyers'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; yards } ; player } ; jerel meyers } = true', 'tointer': 'select the row whose yards record of all rows is maximum . the player record of this row is jerel meyers .'} | eq { hop { argmax { all_rows ; yards } ; player } ; jerel meyers } = true | select the row whose yards record of all rows is maximum . the player record of this row is jerel meyers . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'yards_5': 5, 'player_6': 6, 'jerel meyers_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'yards_5': 'yards', 'player_6': 'player', 'jerel meyers_7': 'jerel meyers'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'yards_5': [0], 'player_6': [1], 'jerel meyers_7': [2]} | ['player', 'rec', 'yards', 'avg', "td 's", 'long'] | [['jerel meyers', '122', '1245', '10.2', '16', '46'], ['james jordan', '69', '797', '11.6', '14', '45'], ['aaron boone', '66', '748', '11.3', '19', '40'], ['sam simmons', '24', '221', '9.2', '2', '34'], ['calvin spears', '15', '152', '10.1', '2', '17'], ['rob johnson', '15', '137', '9.1', '2', '32'], ['john booth', '11', '104', '9.5', '2', '39'], ['brian poli - dixon', '6', '40', '6.7', '0', '11'], ['bryan henderson', '3', '34', '11.3', '2', '23'], ['bj cohen', '3', '33', '11', '0', '11'], ['nathan black', '2', '15', '7.5', '0', '9'], ['tremaine neal', '3', '14', '4.7', '0', '6'], ['jeremy beutler', '1', '12', '12', '0', '12'], ['cyron brown', '1', '9', '9', '0', '9']] |
united states house of representatives elections , 1890 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1890 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1431450-2.html.csv | unique | district 1 is the only district to have a vacant seat . | {'scope': 'all', 'row': '1', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'vacant', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'vacant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to vacant .', 'tostr': 'filter_eq { all_rows ; incumbent ; vacant }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; incumbent ; vacant } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to vacant . there is only one such row in the table .'} | only { filter_eq { all_rows ; incumbent ; vacant } } = true | select the rows whose incumbent record fuzzily matches to vacant . 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, 'incumbent_4': 4, 'vacant_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'incumbent_4': 'incumbent', 'vacant_5': 'vacant'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'incumbent_4': [0], 'vacant_5': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result'] | [['california 1', 'vacant', 'vacant', 'vacant', 'democratic gain'], ['california 2', 'marion biggs', 'democratic', '1886', 'retired democratic hold'], ['california 3', 'joseph mckenna', 'republican', '1884', 're - elected'], ['california 4', 'william w morrow', 'republican', '1884', 'retired republican hold'], ['california 5', 'thomas j clunie', 'democratic', '1888', 'lost re - election republican gain'], ['california 6', 'william vandever', 'republican', '1886', 'retired republican hold']] |
2008 - 09 cardiff city f.c. season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Cardiff_City_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17596418-5.html.csv | comparative | chopra started on an earlier date on cardiff city f.c. than routledge did . | {'row_1': '3', 'row_2': '4', 'col': '7', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'chopra'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to chopra .', 'tostr': 'filter_eq { all_rows ; name ; chopra }'}, 'started'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; chopra } ; started }', 'tointer': 'select the rows whose name record fuzzily matches to chopra . take the started record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'routledge'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to routledge .', 'tostr': 'filter_eq { all_rows ; name ; routledge }'}, 'started'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; routledge } ; started }', 'tointer': 'select the rows whose name record fuzzily matches to routledge . take the started record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; chopra } ; started } ; hop { filter_eq { all_rows ; name ; routledge } ; started } } = true', 'tointer': 'select the rows whose name record fuzzily matches to chopra . take the started record of this row . select the rows whose name record fuzzily matches to routledge . take the started record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; name ; chopra } ; started } ; hop { filter_eq { all_rows ; name ; routledge } ; started } } = true | select the rows whose name record fuzzily matches to chopra . take the started record of this row . select the rows whose name record fuzzily matches to routledge . take the started 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, 'name_7': 7, 'chopra_8': 8, 'started_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'routledge_12': 12, 'started_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', 'name_7': 'name', 'chopra_8': 'chopra', 'started_9': 'started', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'routledge_12': 'routledge', 'started_13': 'started'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'chopra_8': [0], 'started_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'routledge_12': [1], 'started_13': [3]} | ['no', 'p', 'name', 'country', 'age', 'loan club', 'started', 'ended', 'start source', 'end source'] | [['13', 'gk', 'heaton', 'eng', '23', 'manchester united', '5 may', '30 june', 'bbc sport', 'south wales echo'], ['9', 'fw', 'e johnson', 'usa', '25', 'fulham', '22 august', '30 june', 'bbc sport', 'south wales echo'], ['18', 'fw', 'chopra', 'eng', '25', 'sunderland', '6 november', '30 december', 'bbc sport', 'bbc sport'], ['14', 'mf', 'routledge', 'eng', '23', 'aston villa', '20 november', '2 january', 'cardiff city', 'bbc sport'], ['14', 'mf', 'owusu - abeyie', 'ghana', '23', 'spartak moscow', '31 january', '30 june', 'bbc sport', 'south wales echo'], ['18', 'fw', 'chopra', 'eng', '25', 'sunderland', '2 february', '30 june', 'bbc sport', 'south wales echo'], ['22', 'gk', 'konstantopoulos', 'gre', '30', 'coventry city', '9 february', '30 june', 'bbc sport', 'south wales echo']] |
1971 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1971_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245565-8.html.csv | unique | jim simons was the only amateur in the 1971 us open . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': '( a )', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', '( a )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to ( a ) .', 'tostr': 'filter_eq { all_rows ; player ; ( a ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; player ; ( a ) } }', 'tointer': 'select the rows whose player record fuzzily matches to ( a ) . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', '( a )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to ( a ) .', 'tostr': 'filter_eq { all_rows ; player ; ( a ) }'}, 'player'], 'result': 'jim simons ( a )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; player ; ( a ) } ; player }'}, 'jim simons ( a )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; player ; ( a ) } ; player } ; jim simons ( a ) }', 'tointer': 'the player record of this unqiue row is jim simons ( a ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; player ; ( a ) } } ; eq { hop { filter_eq { all_rows ; player ; ( a ) } ; player } ; jim simons ( a ) } } = true', 'tointer': 'select the rows whose player record fuzzily matches to ( a ) . there is only one such row in the table . the player record of this unqiue row is jim simons ( a ) .'} | and { only { filter_eq { all_rows ; player ; ( a ) } } ; eq { hop { filter_eq { all_rows ; player ; ( a ) } ; player } ; jim simons ( a ) } } = true | select the rows whose player record fuzzily matches to ( a ) . there is only one such row in the table . the player record of this unqiue row is jim simons ( a ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'player_7': 7, '(a)_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'jim simons (a)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'player_7': 'player', '(a)_8': '( a )', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'jim simons (a)_10': 'jim simons ( a )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'player_7': [0], '(a)_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'jim simons (a)_10': [3]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'lee trevino', 'united states', '70 + 72 + 69 + 69 = 280', 'e', 'playoff'], ['t1', 'jack nicklaus', 'united states', '69 + 72 + 68 + 71 = 280', 'e', 'playoff'], ['t3', 'jim colbert', 'united states', '69 + 69 + 73 + 71 = 282', '+ 2', '9000'], ['t3', 'bob rosburg', 'united states', '71 + 72 + 70 + 69 = 282', '+ 2', '9000'], ['t5', 'george archer', 'united states', '71 + 70 + 70 + 72 = 283', '+ 3', '6500'], ['t5', 'johnny miller', 'united states', '70 + 73 + 70 + 70 = 283', '+ 3', '6500'], ['t5', 'jim simons ( a )', 'united states', '71 + 71 + 65 + 76 = 283', '+ 3', '0'], ['8', 'raymond floyd', 'united states', '71 + 75 + 67 + 71 = 284', '+ 4', '5000'], ['t9', 'gay brewer', 'united states', '70 + 70 + 73 + 72 = 285', '+ 5', '3325'], ['t9', 'larry hinson', 'united states', '71 + 71 + 70 + 73 = 285', '+ 5', '3325'], ['t9', 'bobby nichols', 'united states', '69 + 72 + 69 + 75 = 285', '+ 5', '3325'], ['t9', 'bert yancey', 'united states', '75 + 69 + 69 + 72 = 285', '+ 5', '3325']] |
1980 african cup of champions clubs | https://en.wikipedia.org/wiki/1980_African_Cup_of_Champions_Clubs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12483185-2.html.csv | count | only 1 team had an agg of zero across all games . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '0', 'result': '1', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'agg', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose agg record fuzzily matches to 0 .', 'tostr': 'filter_eq { all_rows ; agg ; 0 }'}], 'result': '1', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; agg ; 0 } }', 'tointer': 'select the rows whose agg record fuzzily matches to 0 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; agg ; 0 } } ; 1 } = true', 'tointer': 'select the rows whose agg record fuzzily matches to 0 . the number of such rows is 1 .'} | eq { count { filter_eq { all_rows ; agg ; 0 } } ; 1 } = true | select the rows whose agg record fuzzily matches to 0 . the number of such rows is 1 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'agg_5': 5, '0_6': 6, '1_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'agg_5': 'agg', '0_6': '0', '1_7': '1'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'agg_5': [0], '0_6': [0], '1_7': [2]} | ['team 1', 'agg', 'team 2', '1st leg', '2nd leg'] | [['djoliba ac', '1 - 2', 'hearts of oak', '1 - 1', '0 - 1'], ['etoile du congo', '1 - 1 ( 3 - 1 pen )', 'hafia fc', '0 - 1', '1 - 0'], ['simba sc', '2 - 5', 'union douala', '2 - 4', '0 - 1'], ['silures', '0 - 4', 'canon yaoundé', '0 - 1', '0 - 3'], ['ac semassi', '1 - 2', 'asf police', '1 - 1', '0 - 1'], ["stella club d'adjamé", '5 - 5', 'mp algiers', '4 - 2', '1 - 3'], ['bendel insurance', '4 - 4', 'gor mahia', '1 - 2', '3 - 2'], ['as bilima', '4 - 1', 'fortior mahajanga', '3 - 0', '1 - 1']] |
1924 in brazilian football | https://en.wikipedia.org/wiki/1924_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15387537-1.html.csv | superlative | team corinthians had the most points in the 1924 brazil games . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'corinthians', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'corinthians'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; team } ; corinthians } = true', 'tointer': 'select the row whose points record of all rows is maximum . the team record of this row is corinthians .'} | eq { hop { argmax { all_rows ; points } ; team } ; corinthians } = true | select the row whose points record of all rows is maximum . the team record of this row is corinthians . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'corinthians_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'corinthians_7': 'corinthians'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'corinthians_7': [2]} | ['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference'] | [['1', 'corinthians', '25', '17', '1', '4', '23', '23'], ['2', 'paulistano', '23', '17', '3', '4', '15', '16'], ['3', 'aa são bento', '22', '17', '4', '4', '20', '10'], ['4', 'santos', '21', '17', '3', '5', '29', '15'], ['5', 'ypiranga - sp', '20', '17', '2', '6', '24', '5'], ['6', 'sírio', '17', '17', '5', '6', '26', '3'], ['7', 'brás', '10', '16', '4', '9', '41', '- 17'], ['8', 'portuguesa', '8', '16', '2', '11', '39', '- 21']] |
list of the listener episodes | https://en.wikipedia.org/wiki/List_of_The_Listener_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25131572-2.html.csv | unique | only one episode of the listener was directed by tj scott . | {'scope': 'all', 'row': '10', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'tj scott', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'tj scott'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to tj scott .', 'tostr': 'filter_eq { all_rows ; directed by ; tj scott }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; directed by ; tj scott } } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to tj scott . there is only one such row in the table .'} | only { filter_eq { all_rows ; directed by ; tj scott } } = true | select the rows whose directed by record fuzzily matches to tj scott . 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, 'directed by_4': 4, 'tj scott_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'directed by_4': 'directed by', 'tj scott_5': 'tj scott'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'directed by_4': [0], 'tj scott_5': [0]} | ['series', 'season', 'title', 'directed by', 'written by', 'original canadian air date', 'fox int channels air date'] | [['1', '1', "i 'm an adult now", 'clement virgo', 'michael amo', 'june 3 , 2009', 'march 3 , 2009'], ['2', '2', 'emotional rescue', 'ken girotti', 'russ cochrane', 'june 4 , 2009', 'march 10 , 2009'], ['3', '3', 'a voice in the dark', 'clement virgo', 'michael amo', 'june 11 , 2009', 'march 17 , 2009'], ['4', '4', 'some kind of love', 'clement virgo', 'larry lalonde , phil bedard', 'june 18 , 2009', 'march 24 , 2009'], ['5', '5', 'lisa says', 'kari skogland', 'dennis heaton', 'july 2 , 2009', 'march 31 , 2009'], ['6', '6', 'foggy notion', 'clement virgo', 'jeremy boxen', 'july 9 , 2009', 'april 7 , 2009'], ['7', '7', 'iris', 'stephen surjik', 'michael amo', 'july 16 , 2009', 'april 14 , 2009'], ['10', '8', 'one way or another', 'stephen surjik', 'dennis heaton', 'july 23 , 2009', 'april 21 , 2009'], ['9', '9', 'inside the man', 'clement virgo', 'michael amo', 'july 30 , 2009', 'april 28 , 2009'], ['10', '10', 'missing', 'tj scott', 'avrum jacobson', 'august 6 , 2009', 'may 5 , 2009'], ['11', '11', 'beginning to see the light', 'clement virgo', 'avrum jacobson story by : travis mcdonald', 'august 13 , 2009', 'may 12 , 2009'], ['12', '12', "the 13th juror / my sister 's keeper", 'kari skogland', 'ross cochrane', 'august 20 , 2009', 'may 19 , 2009']] |
eurovision song contest 2008 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11173692-2.html.csv | superlative | in the eurovision song contest of 2008 , the artist with the highest number of points was kalomira . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '19', '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', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'artist'], 'result': 'kalomira', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; artist }'}, 'kalomira'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; artist } ; kalomira } = true', 'tointer': 'select the row whose points record of all rows is maximum . the artist record of this row is kalomira .'} | eq { hop { argmax { all_rows ; points } ; artist } ; kalomira } = true | select the row whose points record of all rows is maximum . the artist record of this row is kalomira . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'artist_6': 6, 'kalomira_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'artist_6': 'artist', 'kalomira_7': 'kalomira'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'artist_6': [1], 'kalomira_7': [2]} | ['draw', 'language', 'artist', 'song', 'place', 'points'] | [['01', 'montenegrin', 'stefan filipović', 'zauvijek volim te', '14', '23'], ['02', 'hebrew , english', "boaz ma'uda", 'the fire in your eyes', '5', '104'], ['03', 'serbian , german , finnish', 'kreisiraadio', 'leto svet', '18', '8'], ['04', 'english', 'geta burlacu', 'a century of love', '12', '36'], ['05', 'italian', 'miodio', 'complice', '19', '5'], ['06', 'imaginary', 'ishtar', 'o julissi', '17', '16'], ['07', 'english', 'elnur and samir', 'day after day', '6', '96'], ['08', 'slovene', 'rebeka dremelj', 'vrag naj vzame', '11', '36'], ['09', 'english', 'maria haukaas storeng', 'hold on be strong', '4', '106'], ['10', 'english', 'isis gee', 'for life', '10', '42'], ['11', 'english , french', 'dustin the turkey', 'irelande douze pointe', '15', '22'], ['12', 'english , catalan', 'gisela', 'casanova', '16', '22'], ['13', 'bosnian', 'laka', 'pokušaj', '9', '72'], ['14', 'english , armenian', 'sirusho', 'qélé , qélé ( քելե քելե )', '2', '139'], ['15', 'english', 'hind', 'your heart belongs to me', '13', '27'], ['16', 'finnish', 'teräsbetoni', 'missä miehet ratsastaa', '8', '79'], ['17', 'romanian , italian', 'nico and vlad', 'pe - o margine de lume', '7', '94'], ['18', 'english', 'dima bilan', 'believe', '3', '135'], ['19', 'english', 'kalomira', 'secret combination', '1', '156']] |
abdel sattar sabry | https://en.wikipedia.org/wiki/Abdel_Sattar_Sabry | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15553431-1.html.csv | majority | in the events played by abdel sattar sabry in june , most events had a score of 2-0 . | {'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '2-0', 'subset': {'col': '1', 'criterion': 'fuzzily_match', 'value': 'june'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'june'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; june }', 'tointer': 'select the rows whose date record fuzzily matches to june .'}, 'score', '2-0'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to june . for the score records of these rows , most of them fuzzily match to 2-0 .', 'tostr': 'most_eq { filter_eq { all_rows ; date ; june } ; score ; 2-0 } = true'} | most_eq { filter_eq { all_rows ; date ; june } ; score ; 2-0 } = true | select the rows whose date record fuzzily matches to june . for the score records of these rows , most of them fuzzily match to 2-0 . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'june_5': 5, 'score_6': 6, '2-0_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'june_5': 'june', 'score_6': 'score', '2-0_7': '2-0'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'june_5': [0], 'score_6': [1], '2-0_7': [1]} | ['date', 'venue', 'score', 'result', 'competition'] | [['30 june 1995', 'alexandria stadium , alexandria', '2 - 0', '6 - 0', '1996 africa cup of nations qualifier'], ['5 june 1997', 'cairo international stadium , cairo', '2 - 0', '2 - 0', 'friendly'], ['16 june 1997', 'seoul , south korea', '2 - 0', '2 - 0', '1997 korea cup'], ['17 august 1997', 'cairo international stadium , cairo', '3 - 0', '5 - 0', '1998 fifa world cup qualifier'], ['18 december 1997', 'aswan stadium , aswan', '7 - 2', '7 - 2', 'friendly'], ['25 july 1999', 'estadio azteca , mexico city , mexico', '1 - 0', '2 - 2', '1999 fifa confederations cup'], ['9 january 2001', 'cairo international stadium , cairo', '1 - 0', '3 - 0', 'friendly'], ['9 january 2001', 'cairo international stadium , cairo', '3 - 0', '3 - 0', 'friendly'], ['17 january 2001', 'cairo international stadium , cairo', '4 - 0', '4 - 0', '2002 african cup of nations qualifier'], ['11 march 2001', 'cairo international stadium , cairo', '2 - 0', '5 - 2', '2002 fifa world cup qualifier'], ['13 july 2001', 'alexandria stadium , alexandria', '8 - 2', '8 - 2', '2002 fifa world cup qualifier']] |
list of apollo astronauts | https://en.wikipedia.org/wiki/List_of_Apollo_astronauts | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-129540-2.html.csv | comparative | in the list of apollo astronauts shown frank norman was born before jim lovell . | {'row_1': '1', 'row_2': '2', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'frank borman'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to frank borman .', 'tostr': 'filter_eq { all_rows ; name ; frank borman }'}, 'born'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; frank borman } ; born }', 'tointer': 'select the rows whose name record fuzzily matches to frank borman . take the born record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'jim lovell'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to jim lovell .', 'tostr': 'filter_eq { all_rows ; name ; jim lovell }'}, 'born'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; jim lovell } ; born }', 'tointer': 'select the rows whose name record fuzzily matches to jim lovell . take the born record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; frank borman } ; born } ; hop { filter_eq { all_rows ; name ; jim lovell } ; born } } = true', 'tointer': 'select the rows whose name record fuzzily matches to frank borman . take the born record of this row . select the rows whose name record fuzzily matches to jim lovell . take the born record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; name ; frank borman } ; born } ; hop { filter_eq { all_rows ; name ; jim lovell } ; born } } = true | select the rows whose name record fuzzily matches to frank borman . take the born record of this row . select the rows whose name record fuzzily matches to jim lovell . take the born 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, 'name_7': 7, 'frank borman_8': 8, 'born_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'jim lovell_12': 12, 'born_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', 'name_7': 'name', 'frank borman_8': 'frank borman', 'born_9': 'born', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'jim lovell_12': 'jim lovell', 'born_13': 'born'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'frank borman_8': [0], 'born_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'jim lovell_12': [1], 'born_13': [3]} | ['name', 'born', 'age on mission', 'mission', 'mission dates', 'service'] | [['frank borman', 'march 14 , 1928 ( age85 )', '40', 'apollo 8', 'december 21 - 27 , 1968', 'air force'], ['jim lovell', 'march 25 , 1928 ( age85 )', '40', 'apollo 8', 'december 21 - 27 , 1968', 'navy'], ['bill anders', 'october 17 , 1933 ( age80 )', '35', 'apollo 8', 'december 21 - 27 , 1968', 'air force'], ['tom stafford', 'september 17 , 1930 ( age83 )', '38', 'apollo 10', 'may 18 - 26 , 1969', 'air force'], ['john young', 'september 24 , 1930 ( age83 )', '38', 'apollo 10', 'may 18 - 26 , 1969', 'navy'], ['eugene cernan', 'march 14 , 1934 ( age79 )', '35', 'apollo 10', 'may 18 - 26 , 1969', 'navy'], ['mike collins', 'october 31 , 1930 ( age83 )', '38', 'apollo 11', 'july 16 - 24 , 1969', 'air force'], ['dick gordon', 'october 5 , 1929 ( age84 )', '40', 'apollo 12', 'november 14 - 24 , 1969', 'navy'], ['jim lovell', 'march 25 , 1928 ( age85 )', '42', 'apollo 13', 'april 11 - 17 , 1970', 'navy'], ['jack swigert', 'august 30 , 1931', '38', 'apollo 13', 'april 11 - 17 , 1970', 'nasa'], ['fred haise', 'november 14 , 1933 ( age80 )', '36', 'apollo 13', 'april 11 - 17 , 1970', 'nasa'], ['stu roosa', 'august 16 , 1933', '37', 'apollo 14', 'january 31 - february 9 , 1971', 'air force'], ['al worden', 'february 7 , 1932 ( age81 )', '39', 'apollo 15', 'july 26 - august 7 , 1971', 'air force'], ['ken mattingly', 'march 17 , 1936 ( age77 )', '36', 'apollo 16', 'april 16 - 27 , 1972', 'navy'], ['ron evans', 'november 10 , 1933', '39', 'apollo 17', 'december 7 - 19 , 1972', 'navy']] |
list of malmö ff records and statistics | https://en.wikipedia.org/wiki/List_of_Malm%C3%B6_FF_records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29701419-2.html.csv | ordinal | according to the list of list of malmö ff records and statistics , player with second highest number of total goals had 371 total appearances . | {'scope': 'all', 'row': '4', 'col': '7', 'order': '2', 'col_other': '6', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'total goals', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; total goals ; 2 }'}, 'total appearances'], 'result': '371', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; total goals ; 2 } ; total appearances }'}, '371'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; total goals ; 2 } ; total appearances } ; 371 } = true', 'tointer': 'select the row whose total goals record of all rows is 2nd maximum . the total appearances record of this row is 371 .'} | eq { hop { nth_argmax { all_rows ; total goals ; 2 } ; total appearances } ; 371 } = true | select the row whose total goals record of all rows is 2nd maximum . the total appearances record of this row is 371 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'total goals_5': 5, '2_6': 6, 'total appearances_7': 7, '371_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'total goals_5': 'total goals', '2_6': '2', 'total appearances_7': 'total appearances', '371_8': '371'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'total goals_5': [0], '2_6': [0], 'total appearances_7': [1], '371_8': [2]} | ['name', 'nationality', 'malmö ff career', 'league appearances', 'league goals', 'total appearances', 'total goals'] | [['hans håkansson', 'sweden', '1927 - 1938', '192', '163', '350', '341'], ['bo larsson', 'sweden', '1962 - 1966 1969 - 1979', '302', '119', '546', '289'], ['egon jönsson', 'sweden', '1943 - 1955', '200', '99', '405', '269'], ['börje tapper', 'sweden', '1939 - 1951', '191', '91', '371', '298'], ['thomas sjöberg', 'sweden', '1974 - 1976 1977 - 1978 1979 - 1982', '180', '80', '334', '157'], ['ivar roslund', 'sweden', '1925 - 1937', '169', '71', '311', '179'], ['ingvar rydell', 'sweden', '1948 - 1953', '106', '68', '210', '162'], ['stellan nilsson', 'sweden', '1940 - 1950', '179', '68', '336', '166'], ['gustaf nilsson', 'sweden', '1940 - 1950', '132', '65', '265', '205']] |
european poker tour | https://en.wikipedia.org/wiki/European_Poker_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1296513-5.html.csv | comparative | the ept barcelona open started earlier than the 2008 european poker championships . | {'row_1': '1', 'row_2': '2', 'col': '1', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', 'ept barcelona open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose event record fuzzily matches to ept barcelona open .', 'tostr': 'filter_eq { all_rows ; event ; ept barcelona open }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; event ; ept barcelona open } ; date }', 'tointer': 'select the rows whose event record fuzzily matches to ept barcelona open . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'event', '2008 european poker championships'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose event record fuzzily matches to 2008 european poker championships .', 'tostr': 'filter_eq { all_rows ; event ; 2008 european poker championships }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; event ; 2008 european poker championships } ; date }', 'tointer': 'select the rows whose event record fuzzily matches to 2008 european poker championships . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; event ; ept barcelona open } ; date } ; hop { filter_eq { all_rows ; event ; 2008 european poker championships } ; date } } = true', 'tointer': 'select the rows whose event record fuzzily matches to ept barcelona open . take the date record of this row . select the rows whose event record fuzzily matches to 2008 european poker championships . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; event ; ept barcelona open } ; date } ; hop { filter_eq { all_rows ; event ; 2008 european poker championships } ; date } } = true | select the rows whose event record fuzzily matches to ept barcelona open . take the date record of this row . select the rows whose event record fuzzily matches to 2008 european poker championships . 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, 'event_7': 7, 'ept barcelona open_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'event_11': 11, '2008 european poker championships_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', 'event_7': 'event', 'ept barcelona open_8': 'ept barcelona open', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'event_11': 'event', '2008 european poker championships_12': '2008 european poker championships', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'event_7': [0], 'ept barcelona open_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'event_11': [1], '2008 european poker championships_12': [1], 'date_13': [3]} | ['date', 'city', 'event', 'winner', 'prize'] | [['10 - 14 september 2008', 'barcelona', 'ept barcelona open', 'sebastian ruthenberg', '1361000'], ['1 - 5 october 2008', 'london', '2008 european poker championships', 'michael martin', '1000000'], ['5 - 6 october 2008', 'london', 'ept london 1 million showdown', 'jason mercier', '516000'], ['28 oct - 1 nov 2008', 'budapest', 'ept hungarian open', 'will fry', '595839'], ['15 - 19 november 2008', 'warsaw', 'ept polish open', 'joão barbosa', 'zł1358420'], ['9 - 13 december 2008', 'prague', 'ept prague', 'salvatore bonavena', '774000'], ['5 - 10 january 2009', 'paradise island', 'ept pokerstars caribbean adventure', 'poorya nazari', '3000000'], ['20 - 24 january 2009', 'deauville', 'ept deauville', 'moritz kranich', '851400'], ['17 - 21 february 2009', 'copenhagen', 'ept scandinavian open', 'jens kyllönen', 'kr6542208'], ['10 - 14 march 2009', 'dortmund', 'ept german open', 'sandra naujoks', '917000'], ['18 - 23 april 2009', 'sanremo', 'ept sanremo', 'constant rijkenberg', '1508000'], ['28 apr - 3 may 2009', 'monte carlo', 'european poker tour grand final', 'pieter de korver', '2300000']] |
csi ( franchise ) | https://en.wikipedia.org/wiki/CSI_%28franchise%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10819266-8.html.csv | aggregation | the average viewership for seasons of csi is 12.56 million . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '12.56', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'viewers ( in millions )'], 'result': '12.56', 'ind': 0, 'tostr': 'avg { all_rows ; viewers ( in millions ) }'}, '12.56'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; viewers ( in millions ) } ; 12.56 } = true', 'tointer': 'the average of the viewers ( in millions ) record of all rows is 12.56 .'} | round_eq { avg { all_rows ; viewers ( in millions ) } ; 12.56 } = true | the average of the viewers ( in millions ) record of all rows is 12.56 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'viewers (in millions)_4': 4, '12.56_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'viewers (in millions)_4': 'viewers ( in millions )', '12.56_5': '12.56'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'viewers (in millions)_4': [0], '12.56_5': [1]} | ['season', 'episodes', 'time slot ( est )', 'season premiere', 'season finale', 'tv season', 'rank', 'viewers ( in millions )'] | [['1', '23', 'wednesday 10 pm / 9c', 'september 22 , 2004', 'may 18 , 2005', '2004 - 2005', '21', '13.59'], ['2', '24', 'wednesday 10 pm / 9c', 'september 28 , 2005', 'may 17 , 2006', '2005 - 2006', '22', '14.04'], ['3', '24', 'wednesday 10 pm / 9c', 'september 20 , 2006', 'may 16 , 2007', '2006 - 2007', '25', '13.92'], ['4', '21', 'wednesday 10 pm / 9c', 'september 26 , 2007', 'may 21 , 2008', '2007 - 2008', '28', '11.71'], ['5', '25', 'wednesday 10 pm / 9c', 'september 24 , 2008', 'may 14 , 2009', '2008 - 2009', '17', '13.50'], ['6', '23', 'wednesday 10 pm / 9c', 'september 23 , 2009', 'may 26 , 2010', '2009 - 2010', '23', '12.66'], ['7', '22', 'friday 9 pm / 8c', 'september 24 , 2010', 'may 13 , 2011', '2010 - 2011', '37', '10.73'], ['8', '18', 'friday 9 pm / 8c', 'september 23 , 2011', 'may 11 , 2012', '2011 - 2012', '38', '10.34']] |
1985 los angeles rams season | https://en.wikipedia.org/wiki/1985_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11157122-2.html.csv | count | only one of the games that the rams played in november of 1985 had more than 60,000 people in attendance . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '60000', 'result': '1', 'col': '9', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'november'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; november }', 'tointer': 'select the rows whose date record fuzzily matches to november .'}, 'attendance', '60000'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose attendance record is greater than 60000 .', 'tostr': 'filter_greater { filter_eq { all_rows ; date ; november } ; attendance ; 60000 }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_greater { filter_eq { all_rows ; date ; november } ; attendance ; 60000 } }', 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose attendance record is greater than 60000 . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_greater { filter_eq { all_rows ; date ; november } ; attendance ; 60000 } } ; 1 } = true', 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose attendance record is greater than 60000 . the number of such rows is 1 .'} | eq { count { filter_greater { filter_eq { all_rows ; date ; november } ; attendance ; 60000 } } ; 1 } = true | select the rows whose date record fuzzily matches to november . among these rows , select the rows whose attendance record is greater than 60000 . the number of such rows is 1 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'november_7': 7, 'attendance_8': 8, '60000_9': 9, '1_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'november_7': 'november', 'attendance_8': 'attendance', '60000_9': '60000', '1_10': '1'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'november_7': [0], 'attendance_8': [1], '60000_9': [1], '1_10': [3]} | ['game', 'date', 'opponent', 'result', 'rams points', 'opponents', 'record', 'venue', 'attendance'] | [['1', 'september 8 , 1985', 'denver broncos', 'w', '20', '16', '1 - 0', 'anaheim stadium', '52522'], ['2', 'september 15 , 1985', 'philadelphia eagles', 'w', '17', '6', '2 - 0', 'veterans stadium', '60920'], ['3', 'september 23 , 1985', 'seattle seahawks', 'w', '35', '24', '3 - 0', 'kingdome', '63292'], ['4', 'september 29 , 1985', 'atlanta falcons', 'w', '17', '6', '4 - 0', 'anaheim stadium', '49870'], ['5', 'october 6 , 1985', 'minnesota vikings', 'w', '13', '10', '5 - 0', 'anaheim stadium', '61139'], ['6', 'october 13 , 1985', 'tampa bay buccaneers', 'w', '31', '27', '6 - 0', 'tampa stadium', '39607'], ['7', 'october 20 , 1985', 'kansas city chiefs', 'w', '16', '0', '7 - 0', 'arrowhead stadium', '64474'], ['8', 'october 27 , 1985', 'san francisco 49ers', 'l', '14', '28', '7 - 1', 'anaheim stadium', '65939'], ['9', 'november 3 , 1985', 'new orleans saints', 'w', '28', '10', '8 - 1', 'anaheim stadium', '49030'], ['10', 'november 10 , 1985', 'new york giants', 'l', '19', '24', '8 - 2', 'giants stadium', '74663'], ['11', 'november 17 , 1985', 'atlanta falcons', 'l', '14', '30', '8 - 3', 'atlanta - fulton county stadium', '29960'], ['12', 'november 24 , 1985', 'green bay packers', 'w', '34', '17', '9 - 3', 'anaheim stadium', '52710'], ['13', 'december 1 , 1985', 'new orleans saints', 'l', '3', '29', '9 - 4', 'louisiana superdome', '44122'], ['14', 'december 9 , 1985', 'san francisco 49ers', 'w', '27', '20', '10 - 4', 'candlestick park', '60581'], ['15', 'december 15 , 1985', 'st louis cardinals', 'w', '46', '14', '11 - 4', 'anaheim stadium', '52052'], ['16', 'december 23 , 1985', 'los angeles raiders', 'l', '6', '16', '11 - 5', 'anaheim stadium', '66676'], ['divisional playoff', 'january 4 , 1986', 'dallas cowboys', 'w', '20', '0', '12 - 5', 'anaheim stadium', '66351'], ['conference championship', 'january 12 , 1986', 'chicago bears', 'l', '0', '24', '12 - 6', 'soldier field', '65522']] |
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/1-1342256-32.html.csv | ordinal | louis capozzoli is the second lastest candidate to become first elected . | {'row': '4', 'col': '4', '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', 'first elected', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; first elected ; 2 }'}, 'incumbent'], 'result': 'louis capozzoli', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; first elected ; 2 } ; incumbent }'}, 'louis capozzoli'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; first elected ; 2 } ; incumbent } ; louis capozzoli } = true', 'tointer': 'select the row whose first elected record of all rows is 2nd maximum . the incumbent record of this row is louis capozzoli .'} | eq { hop { nth_argmax { all_rows ; first elected ; 2 } ; incumbent } ; louis capozzoli } = true | select the row whose first elected record of all rows is 2nd maximum . the incumbent record of this row is louis capozzoli . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'first elected_5': 5, '2_6': 6, 'incumbent_7': 7, 'louis capozzoli_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', 'first elected_5': 'first elected', '2_6': '2', 'incumbent_7': 'incumbent', 'louis capozzoli_8': 'louis capozzoli'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'first elected_5': [0], '2_6': [0], 'incumbent_7': [1], 'louis capozzoli_8': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['new york 7', 'john j delaney', 'democratic', '1931', 're - elected', 'john j delaney ( d ) 72.8 % harry boyarsky ( r ) 27.2 %'], ['new york 10', 'emanuel celler', 'democratic', '1922', 're - elected', 'emanuel celler ( d ) 68.6 % jerome lewis ( r ) 31.4 %'], ['new york 12', 'samuel dickstein', 'democratic', '1922', 're - elected', 'samuel dickstein ( d ) 87.0 % hyman hecht ( r ) 13.0 %'], ['new york 13', 'louis capozzoli', 'democratic', '1940', 're - elected', 'louis capozzoli ( d ) 74.0 % john rosenberg ( r ) 26.0 %'], ['new york 17', 'joseph c baldwin', 'republican', '1941', 're - elected', 'joseph c baldwin ( r ) 61.0 % carl sherman ( d ) 39.0 %'], ['new york 19', 'sol bloom', 'democratic', '1923', 're - elected', 'sol bloom ( d ) 67.5 % clarence mcmillan ( r ) 32.5 %'], ['new york 20', 'vito marcantonio', 'labor', '1938', 're - elected', 'vito marcantonio ( american labor ) unopposed'], ['new york 27', 'lewis k rockefeller', 'republican', '1937', 'retired republican hold', 'jay le fevre ( r ) 63.1 % sharon j mauhs ( d ) 36.9 %'], ['new york 29', 'e harold cluett', 'republican', '1936', 'retired republican hold', 'dean p taylor ( r ) 68.8 % john t degnan ( d ) 31.2 %'], ['new york 36', 'john taber', 'republican', '1922', 're - elected', 'john taber ( r ) 62.6 % charles osborne ( d ) 37.4 %'], ['new york 38', "joseph j o'brien", 'republican', '1938', 're - elected', "joseph j o'brien ( r ) 59.1 % walden moore ( d ) 40.9 %"], ['new york 39', 'james wolcott wadsworth , jr', 'republican', '1932', 're - elected', 'james wolcott wadsworth , jr ( r ) unopposed']] |
1975 minnesota vikings season | https://en.wikipedia.org/wiki/1975_Minnesota_Vikings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10361480-2.html.csv | superlative | the highest amount of points the minnesota vikings scored in the 1975 nfl season is 42 . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': 'n/a', 'subset': None} | {'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'result'], 'result': 'w 42 - 10', 'ind': 0, 'tostr': 'max { all_rows ; result }', 'tointer': 'the maximum result record of all rows is w 42 - 10 .'}, 'w 42 - 10'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; result } ; w 42 - 10 } = true', 'tointer': 'the maximum result record of all rows is w 42 - 10 .'} | eq { max { all_rows ; result } ; w 42 - 10 } = true | the maximum result record of all rows is w 42 - 10 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'max_0': 0, 'all_rows_3': 3, 'result_4': 4, 'w 42 - 10_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'max_0': 'max', 'all_rows_3': 'all_rows', 'result_4': 'result', 'w 42 - 10_5': 'w 42 - 10'} | {'eq_1': [2], 'result_2': [], 'max_0': [1], 'all_rows_3': [0], 'result_4': [0], 'w 42 - 10_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 21 , 1975', 'san francisco 49ers', 'w 27 - 17', '46479'], ['2', 'september 28 , 1975', 'cleveland browns', 'w 42 - 10', '68064'], ['3', 'october 5 , 1975', 'chicago bears', 'w 28 - 3', '47578'], ['4', 'october 12 , 1975', 'new york jets', 'w 29 - 21', '47739'], ['5', 'october 19 , 1975', 'detroit lions', 'w 25 - 19', '47872'], ['6', 'october 27 , 1975', 'chicago bears', 'w 13 - 9', '51259'], ['7', 'november 2 , 1975', 'green bay packers', 'w 28 - 17', '57267'], ['8', 'november 9 , 1975', 'atlanta falcons', 'w 38 - 0', '43751'], ['9', 'november 16 , 1975', 'new orleans saints', 'w 20 - 7', '52765'], ['10', 'november 23 , 1975', 'san diego chargers', 'w 28 - 13', '43737'], ['11', 'november 30 , 1975', 'washington redskins', 'l 30 - 31', '54498'], ['12', 'december 7 , 1975', 'green bay packers', 'w 24 - 3', '46147'], ['13', 'december 14 , 1975', 'detroit lions', 'l 10 - 17', '73130'], ['14', 'december 20 , 1975', 'buffalo bills', 'w 35 - 13', '54993']] |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-15.html.csv | ordinal | during the 1941 vfl season , punt road oval had the largest crowd on august 9th with 26000 people . | {'scope': 'all', 'row': '5', 'col': '6', 'order': '1', 'col_other': '5,7', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'crowd', '1'], 'result': '26000', 'ind': 0, 'tostr': 'nth_max { all_rows ; crowd ; 1 }', 'tointer': 'the 1st maximum crowd record of all rows is 26000 .'}, '26000'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; crowd ; 1 } ; 26000 }', 'tointer': 'the 1st maximum crowd record of all rows is 26000 .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'punt road oval', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'punt road oval'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; punt road oval }', 'tointer': 'the venue record of the row with 1st maximum crowd record is punt road oval .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'crowd', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'date'], 'result': '9 august 1941', 'ind': 5, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; date }'}, '9 august 1941'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; date } ; 9 august 1941 }', 'tointer': 'the date record of the row with 1st maximum crowd record is 9 august 1941 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; punt road oval } ; eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; date } ; 9 august 1941 } }', 'tointer': 'the venue record of the row with 1st maximum crowd record is punt road oval . the date record of the row with 1st maximum crowd record is 9 august 1941 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { nth_max { all_rows ; crowd ; 1 } ; 26000 } ; and { eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; punt road oval } ; eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; date } ; 9 august 1941 } } } = true', 'tointer': 'the 1st maximum crowd record of all rows is 26000 . the venue record of the row with 1st maximum crowd record is punt road oval . the date record of the row with 1st maximum crowd record is 9 august 1941 .'} | and { eq { nth_max { all_rows ; crowd ; 1 } ; 26000 } ; and { eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; punt road oval } ; eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; date } ; 9 august 1941 } } } = true | the 1st maximum crowd record of all rows is 26000 . the venue record of the row with 1st maximum crowd record is punt road oval . the date record of the row with 1st maximum crowd record is 9 august 1941 . | 10 | 9 | {'and_8': 8, 'result_9': 9, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_10': 10, 'crowd_11': 11, '1_12': 12, '26000_13': 13, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_14': 14, 'crowd_15': 15, '1_16': 16, 'venue_17': 17, 'punt road oval_18': 18, 'str_eq_6': 6, 'str_hop_5': 5, 'date_19': 19, '9 august 1941_20': 20} | {'and_8': 'and', 'result_9': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_10': 'all_rows', 'crowd_11': 'crowd', '1_12': '1', '26000_13': '26000', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_14': 'all_rows', 'crowd_15': 'crowd', '1_16': '1', 'venue_17': 'venue', 'punt road oval_18': 'punt road oval', 'str_eq_6': 'str_eq', 'str_hop_5': 'str_hop', 'date_19': 'date', '9 august 1941_20': '9 august 1941'} | {'and_8': [9], 'result_9': [], 'eq_1': [8], 'nth_max_0': [1], 'all_rows_10': [0], 'crowd_11': [0], '1_12': [0], '26000_13': [1], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'nth_argmax_2': [3, 5], 'all_rows_14': [2], 'crowd_15': [2], '1_16': [2], 'venue_17': [3], 'punt road oval_18': [4], 'str_eq_6': [7], 'str_hop_5': [6], 'date_19': [5], '9 august 1941_20': [6]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['geelong', '22.12 ( 144 )', 'hawthorn', '19.15 ( 129 )', 'kardinia park', '4500', '9 august 1941'], ['fitzroy', '16.17 ( 113 )', 'south melbourne', '11.14 ( 80 )', 'brunswick street oval', '8000', '9 august 1941'], ['carlton', '25.19 ( 169 )', 'north melbourne', '17.15 ( 117 )', 'princes park', '10000', '9 august 1941'], ['st kilda', '12.13 ( 85 )', 'melbourne', '14.17 ( 101 )', 'junction oval', '7000', '9 august 1941'], ['richmond', '14.11 ( 95 )', 'essendon', '12.16 ( 88 )', 'punt road oval', '26000', '9 august 1941'], ['footscray', '7.10 ( 52 )', 'collingwood', '10.21 ( 81 )', 'western oval', '16000', '9 august 1941']] |
1987 pittsburgh gladiators season | https://en.wikipedia.org/wiki/1987_Pittsburgh_Gladiators_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11938731-7.html.csv | count | a total of two defensive players scored touchdowns during the 1987 pittsburgh gladiators season . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '1', 'result': '2', 'col': '7', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', "td 's", '1'], 'result': None, 'ind': 0, 'tointer': "select the rows whose td 's record is greater than or equal to 1 .", 'tostr': "filter_greater_eq { all_rows ; td 's ; 1 }"}], 'result': '2', 'ind': 1, 'tostr': "count { filter_greater_eq { all_rows ; td 's ; 1 } }", 'tointer': "select the rows whose td 's record is greater than or equal to 1 . the number of such rows is 2 ."}, '2'], 'result': True, 'ind': 2, 'tostr': "eq { count { filter_greater_eq { all_rows ; td 's ; 1 } } ; 2 } = true", 'tointer': "select the rows whose td 's record is greater than or equal to 1 . the number of such rows is 2 ."} | eq { count { filter_greater_eq { all_rows ; td 's ; 1 } } ; 2 } = true | select the rows whose td 's record is greater than or equal to 1 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, "td 's_5": 5, '1_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', "td 's_5": "td 's", '1_6': '1', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], "td 's_5": [0], '1_6': [0], '2_7': [2]} | ['player', 'tackles', 'solo', 'assisted', 'sack', 'yards', "td 's"] | [['joel gueli', '31', '29', '4', '3', '31', '1'], ['craig walls', '19', '15', '8', '13', '0', '0'], ['russell hairston', '17.5', '16', '0', '0', '50', '1'], ['creig federico', '17', '12', '10', '3', '0', '0'], ['scott dmitrenko', '15', '13', '4', '3', '0', '0'], ['mike stoops', '14.5', '11', '7', '0', '0', '0'], ['john mcclennon', '12.5', '9', '7', '0', '5', '0'], ['ricky mitchell', '11', '10', '2', '2', '0', '0'], ['jim rafferty', '10.5', '8', '2', '0', '4', '0'], ['thomas weaver', '9', '7', '4', '3', '2', '0'], ['earnest adams', '8', '6', '4', '5', '0', '0'], ['mike powell', '6', '5', '2', '0', '0', '0'], ['greg best', '6', '6', '0', '0', '0', '0'], ['willis yates', '5', '4', '2', '6', '0', '0'], ['lee larsen', '2.5', '2', '1', '0', '0', '0']] |
brett lunger | https://en.wikipedia.org/wiki/Brett_Lunger | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1219630-1.html.csv | majority | brett lunger recorded 0 points in all participation with teams . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '0', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'points', '0'], 'result': True, 'ind': 0, 'tointer': 'for the points records of all rows , all of them are equal to 0 .', 'tostr': 'all_eq { all_rows ; points ; 0 } = true'} | all_eq { all_rows ; points ; 0 } = true | for the points records of all rows , all of them are equal to 0 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'points_3': 3, '0_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'points_3': 'points', '0_4': '0'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'points_3': [0], '0_4': [0]} | ['year', 'team', 'chassis', 'engine', 'points'] | [['1975', 'hesketh racing', 'hesketh 308', 'ford cosworth dfv 3.0 v8', '0'], ['1976', 'team surtees', 'surtees ts19', 'ford cosworth dfv 3.0 v8', '0'], ['1977', 'chesterfield racing', 'march 761', 'ford cosworth dfv 3.0 v8', '0'], ['1977', 'chesterfield racing', 'mclaren m23b', 'ford cosworth dfv 3.0 v8', '0'], ['1978', 'liggett group / b & s fabrications', 'mclaren m23b', 'ford cosworth dfv 3.0 v8', '0'], ['1978', 'liggett group / b & s fabrications', 'mclaren m26', 'ford cosworth dfv 3.0 v8', '0'], ['1978', 'team tissot ensign', 'ensign n177', 'ford cosworth dfv 3.0 v8', '0']] |
catriona matthew | https://en.wikipedia.org/wiki/Catriona_Matthew | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2167226-3.html.csv | superlative | catriona matthew had her highest margin of victory in the aberdeen ladies scottish open in 2011 , considering her participations on the ladies european tour . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '4', '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', 'margin of victory'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; margin of victory }'}, 'tournament'], 'result': 'aberdeen ladies scottish open', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; margin of victory } ; tournament }'}, 'aberdeen ladies scottish open'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; margin of victory } ; tournament } ; aberdeen ladies scottish open } = true', 'tointer': 'select the row whose margin of victory record of all rows is maximum . the tournament record of this row is aberdeen ladies scottish open .'} | eq { hop { argmax { all_rows ; margin of victory } ; tournament } ; aberdeen ladies scottish open } = true | select the row whose margin of victory record of all rows is maximum . the tournament record of this row is aberdeen ladies scottish open . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'margin of victory_5': 5, 'tournament_6': 6, 'aberdeen ladies scottish open_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'margin of victory_5': 'margin of victory', 'tournament_6': 'tournament', 'aberdeen ladies scottish open_7': 'aberdeen ladies scottish open'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'margin of victory_5': [0], 'tournament_6': [1], 'aberdeen ladies scottish open_7': [2]} | ['no', 'date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up', 'winners share'] | [['1', '9 aug 1998', "mcdonald 's wpga championship", '71 + 69 + 67 + 69 = 276', '- 12', '5 strokes', 'helen alfredsson laura davies', '45000'], ['2', '12 aug 2007', 'scandinavian tpc hosted by annika', '71 + 74 + 66 + 68 = 279', '- 10', '3 strokes', 'sophie gustafson laura diaz', '78750'], ['3', '2 aug 2009', "ricoh women 's british open 1", '74 + 67 + 71 + 73 = 285', '- 3', '3 strokes', 'karrie webb', '235036'], ['4', '20 aug 2011', 'aberdeen ladies scottish open', '70 + 65 + 76 = 201', '- 15', '10 strokes', 'hannah jun', '33000'], ['5', '5 aug 2012', 'ladies irish open', '67 + 71 + 71 = 209', '- 7', '1 stroke', 'suzann pettersen', '52500']] |
1992 minnesota vikings season | https://en.wikipedia.org/wiki/1992_Minnesota_Vikings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10362150-2.html.csv | aggregation | in the 1992 minnesota vikings season , the average attendance for games in october was 57635.3 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '57635.3', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '57635.3', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '57635.3'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 57635.3 } = true', 'tointer': 'the average of the attendance record of all rows is 57635.3 .'} | round_eq { avg { all_rows ; attendance } ; 57635.3 } = true | the average of the attendance record of all rows is 57635.3 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '57635.3_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '57635.3_5': '57635.3'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '57635.3_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 6 , 1992', 'green bay packers', 'w 23 - 20 ( ot )', '58617'], ['2', 'september 13 , 1992', 'detroit lions', 'l 31 - 17', '57519'], ['3', 'september 20 , 1992', 'tampa bay buccaneers', 'w 26 - 20', '48113'], ['4', 'september 27 , 1992', 'cincinnati bengals', 'w 42 - 7', '53847'], ['5', 'october 4 , 1992', 'chicago bears', 'w 21 - 20', '60992'], ['7', 'october 15 , 1992', 'detroit lions', 'w 31 - 14', '52816'], ['8', 'october 25 , 1992', 'washington redskins', 'l 15 - 13', '59098'], ['9', 'november 2 , 1992', 'chicago bears', 'w 38 - 10', '61257'], ['10', 'november 8 , 1992', 'tampa bay buccaneers', 'w 35 - 7', '49095'], ['11', 'november 15 , 1992', 'houston oilers', 'l 17 - 13', '56726'], ['12', 'november 22 , 1992', 'cleveland browns', 'w 17 - 13', '53323'], ['13', 'november 29 , 1992', 'los angeles rams', 'w 31 - 17', '54831'], ['14', 'december 6 , 1992', 'philadelphia eagles', 'l 28 - 17', '65280'], ['15', 'december 13 , 1992', 'san francisco 49ers', 'l 20 - 17', '60685'], ['16', 'december 20 , 1992', 'pittsburgh steelers', 'w 6 - 3', '53613'], ['17', 'december 27 , 1992', 'green bay packers', 'w 27 - 7', '61461']] |
royal canadian mint numismatic coins ( 2000s ) | https://en.wikipedia.org/wiki/Royal_Canadian_Mint_numismatic_coins_%282000s%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11916083-39.html.csv | comparative | regarding the royal canadian mint numismatic coins ( 2000s ) , the coin with " the russell light four " theme had a higher mintage than the " hmcs bras dor " theme . | {'row_1': '4', 'row_2': '10', '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', 'theme', 'the russell light four'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose theme record fuzzily matches to the russell light four .', 'tostr': 'filter_eq { all_rows ; theme ; the russell light four }'}, 'mintage'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; theme ; the russell light four } ; mintage }', 'tointer': 'select the rows whose theme record fuzzily matches to the russell light four . take the mintage record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'theme', 'hmcs bras dor'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose theme record fuzzily matches to hmcs bras dor .', 'tostr': 'filter_eq { all_rows ; theme ; hmcs bras dor }'}, 'mintage'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; theme ; hmcs bras dor } ; mintage }', 'tointer': 'select the rows whose theme record fuzzily matches to hmcs bras dor . take the mintage record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; theme ; the russell light four } ; mintage } ; hop { filter_eq { all_rows ; theme ; hmcs bras dor } ; mintage } } = true', 'tointer': 'select the rows whose theme record fuzzily matches to the russell light four . take the mintage record of this row . select the rows whose theme record fuzzily matches to hmcs bras dor . take the mintage record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; theme ; the russell light four } ; mintage } ; hop { filter_eq { all_rows ; theme ; hmcs bras dor } ; mintage } } = true | select the rows whose theme record fuzzily matches to the russell light four . take the mintage record of this row . select the rows whose theme record fuzzily matches to hmcs bras dor . take the mintage 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, 'theme_7': 7, 'the russell light four_8': 8, 'mintage_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'theme_11': 11, 'hmcs bras dor_12': 12, 'mintage_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', 'theme_7': 'theme', 'the russell light four_8': 'the russell light four', 'mintage_9': 'mintage', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'theme_11': 'theme', 'hmcs bras dor_12': 'hmcs bras dor', 'mintage_13': 'mintage'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'theme_7': [0], 'the russell light four_8': [0], 'mintage_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'theme_11': [1], 'hmcs bras dor_12': [1], 'mintage_13': [3]} | ['year', 'theme', 'artist', 'mintage', 'issue price'] | [['2000', 'steam buggy', 'john mardon', '44367', '59.95'], ['2000', 'the bluenose', 'j franklin wright', 'included in steam buggy', '59.95'], ['2000', 'the toronto', 'john mardon', 'included in steam buggy', '59.95'], ['2001', 'the russell light four', 'john mardon', '41828', '59.95'], ['2001', 'the marco polo', 'j franklin wright', 'included in the russell', '59.95'], ['2001', 'the scotia', 'don curley', 'included in the russell', '59.95'], ['2002', 'the gray - dort', 'john mardon', '35944', '59.95'], ['2002', 'the william lawrence', 'bonnie ross', 'included in the gray - dort', '59.95'], ['2002', 'd - 10 locomotive', 'dan fell', 'included in the gray - dort', '59.95'], ['2003', 'hmcs bras dor', 'don curley', '31997', '59.95'], ['2003', 'cnr fa - 1 diesel electric', 'john mardon', 'included in hmcs bras dor', '59.95'], ['2003', 'bricklin sv - 1', 'brian hughes', 'included in hmcs bras dor', '59.95']] |
maneater ( film series ) | https://en.wikipedia.org/wiki/Maneater_%28film_series%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19982699-1.html.csv | count | in the maneater film series , there were two titles that were at least partly produced by charles salmon . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'charles salmon', 'result': '3', 'col': '8', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'producer', 'charles salmon'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose producer record fuzzily matches to charles salmon .', 'tostr': 'filter_eq { all_rows ; producer ; charles salmon }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; producer ; charles salmon } }', 'tointer': 'select the rows whose producer record fuzzily matches to charles salmon . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; producer ; charles salmon } } ; 3 } = true', 'tointer': 'select the rows whose producer record fuzzily matches to charles salmon . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; producer ; charles salmon } } ; 3 } = true | select the rows whose producer record fuzzily matches to charles salmon . 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, 'producer_5': 5, 'charles salmon_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', 'producer_5': 'producer', 'charles salmon_6': 'charles salmon', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'producer_5': [0], 'charles salmon_6': [0], '3_7': [2]} | ['', 'title', 'maneater', 'television premiere', 'dvd release', 'writer', 'director', 'producer'] | [['1', 'blood monkey', 'chimpanzees', 'january 27 , 2007', 'november 6 , 2007', 'george lavoo gary dauberman', 'robert young', 'charles salmon'], ['2', "in the spider 's web", 'venomous spiders', 'august 26 , 2007', 'november 6 , 2007', 'gary dauberman', 'terry windsor', 'charles salmon'], ['7', 'grizzly rage', 'grizzly bear', 'june 7 , 2007', 'may 6 , 2008', 'arne olsen', 'david decoteau', 'robert halmi , sr phyllis lain'], ['8', 'the hive', 'army ants', 'february 17 , 2008', 'august 5 , 2008', 'ts cook', 'peter manus', 'charles salmon robert halmi sr robert halmi jr'], ['17', 'sand serpents', 'prehistoric s worm', 'july 11 , 2009', 'november 3 , 2009', 'raul inglis', 'jeff renfroe', 'ric nish'], ['23', 'behemoth', 'behemoth', 'january 15 , 2011', 'april 5 , 2011', 'rachelle s howie', 'wd hogan', 'john prince'], ['24', 'ferocious planet', 'beasts from parallel dimension', 'april 9 , 2011', 'july 5 , 2011', 'douglas g davis', "billy o'brien", 'mary callery']] |
victorian railways c class ( diesel ) | https://en.wikipedia.org/wiki/Victorian_Railways_C_class_%28diesel%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14880117-1.html.csv | majority | the majority of victorian railways c class locomotives are owned by greentrains . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'greentrains', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'owner', 'greentrains'], 'result': True, 'ind': 0, 'tointer': 'for the owner records of all rows , most of them fuzzily match to greentrains .', 'tostr': 'most_eq { all_rows ; owner ; greentrains } = true'} | most_eq { all_rows ; owner ; greentrains } = true | for the owner records of all rows , most of them fuzzily match to greentrains . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'owner_3': 3, 'greentrains_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'owner_3': 'owner', 'greentrains_4': 'greentrains'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'owner_3': [0], 'greentrains_4': [0]} | ['locomotive', 'entered service', 'owner', 'operator', 'livery', 'status'] | [['c501', '14 may 1977', 'seymour railway heritage centre', 'el zorro', 'vr blue & gold', 'preserved - operational'], ['c502', '22 june 1977', 'chicago freight car leasing australia', 'el zorro', 'cfcla blue & yellow', 'operational'], ['c503', '19 july 1977', 'chicago freight car leasing australia', 'southern shorthaul railroad', 'ssr yellow & black', 'operational'], ['c504', '18 august 1977', 'greentrains', 'pacific national', 'blue & yellow', 'operational'], ['c505', '13 september 1977', 'greentrains', 'pacific national', 'blue & yellow', 'operational'], ['c506', '6 october 1977', 'greentrains', 'pacific national', 'greentrains green & yellow', 'operational'], ['c507', '4 november 1977', 'greentrains', 'pacific national', 'blue & yellow', 'operational'], ['c508', '16 december 1977', 'chicago freight car leasing australia', 'el zorro', 'blue & yellow', 'operational'], ['c509', '10 march 1978', 'greentrains', 'pacific national', 'greentrains green & yellow', 'operational'], ['c510', '11 july 1978', 'greentrains', 'pacific national', 'greentrains green & yellow', 'operational']] |
2010 - 11 houston rockets season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Houston_Rockets_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27744976-6.html.csv | count | for the 2010 - 11 houston rockets season , when the rockets won , there were 3 times kevin martin had the high points . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'kevin martin', 'result': '3', 'col': '5', 'subset': {'col': '4', 'criterion': 'fuzzily_match', 'value': 'w'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; score ; w }', 'tointer': 'select the rows whose score record fuzzily matches to w .'}, 'high points', 'kevin martin'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high points record fuzzily matches to kevin martin .', 'tostr': 'filter_eq { filter_eq { all_rows ; score ; w } ; high points ; kevin martin }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; score ; w } ; high points ; kevin martin } }', 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high points record fuzzily matches to kevin martin . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; score ; w } ; high points ; kevin martin } } ; 3 } = true', 'tointer': 'select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high points record fuzzily matches to kevin martin . the number of such rows is 3 .'} | eq { count { filter_eq { filter_eq { all_rows ; score ; w } ; high points ; kevin martin } } ; 3 } = true | select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high points record fuzzily matches to kevin martin . the number of such rows is 3 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'score_6': 6, 'w_7': 7, 'high points_8': 8, 'kevin martin_9': 9, '3_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'score_6': 'score', 'w_7': 'w', 'high points_8': 'high points', 'kevin martin_9': 'kevin martin', '3_10': '3'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'score_6': [0], 'w_7': [0], 'high points_8': [1], 'kevin martin_9': [1], '3_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['4', 'november 3', 'new orleans', 'l 99 - 107 ( ot )', 'aaron brooks , kevin martin ( 18 )', 'luis scola ( 16 )', 'luis scola ( 5 )', 'toyota center 13484', '0 - 4'], ['5', 'november 6', 'san antonio', 'l 121 - 124 ( ot )', 'kevin martin ( 24 )', 'chuck hayes ( 13 )', 'ishmael smith ( 7 )', 'at & t center 17740', '0 - 5'], ['6', 'november 7', 'minnesota', 'w 120 - 94 ( ot )', 'luis scola ( 24 )', 'luis scola ( 8 )', 'ishmael smith ( 6 )', 'toyota center 15058', '1 - 5'], ['7', 'november 10', 'washington', 'l 91 - 98 ( ot )', 'kevin martin ( 31 )', 'chuck hayes , kevin martin ( 7 )', 'kevin martin ( 6 )', 'verizon center 13665', '1 - 6'], ['8', 'november 12', 'indiana', 'w 102 - 99 ( ot )', 'brad miller ( 23 )', 'luis scola ( 9 )', 'kyle lowry ( 7 )', 'conseco fieldhouse 14414', '2 - 6'], ['9', 'november 14', 'new york', 'w 104 - 96 ( ot )', 'kevin martin ( 28 )', 'chuck hayes ( 9 )', 'kyle lowry ( 6 )', 'madison square garden 19763', '3 - 6'], ['11', 'november 17', 'oklahoma city', 'l 99 - 116 ( ot )', 'luis scola ( 26 )', 'luis scola ( 8 )', 'ishmael smith ( 5 )', 'oklahoma city arena 17509', '3 - 8'], ['12', 'november 19', 'toronto', 'l 96 - 106 ( ot )', 'kevin martin ( 31 )', 'kyle lowry ( 7 )', 'kyle lowry ( 12 )', 'air canada centre 17369', '3 - 9'], ['13', 'november 22', 'phoenix', 'l 116 - 123 ( ot )', 'kevin martin ( 19 )', 'jordan hill ( 10 )', 'kyle lowry ( 8 )', 'toyota center 15080', '3 - 10'], ['14', 'november 24', 'golden state', 'w 111 - 101 ( ot )', 'kevin martin ( 25 )', 'luis scola ( 12 )', 'kyle lowry ( 10 )', 'toyota center 13847', '4 - 10'], ['15', 'november 26', 'charlotte', 'l 89 - 99 ( ot )', 'chase budinger ( 19 )', 'chuck hayes ( 10 )', 'kyle lowry ( 6 )', 'time warner cable arena 16473', '4 - 11'], ['16', 'november 28', 'oklahoma city', 'w 99 - 98 ( ot )', 'kevin martin ( 23 )', 'jordan hill , brad miller ( 7 )', 'kyle lowry ( 8 )', 'toyota center 15316', '5 - 11']] |
hawthorne ( season 2 ) | https://en.wikipedia.org/wiki/Hawthorne_%28season_2%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30030477-1.html.csv | count | 3 episodes of hawthorne ( season 2 ) were directed by jeff bleckner . | {'scope': 'all', 'criterion': 'equal', 'value': 'jeff bleckner', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'jeff bleckner'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to jeff bleckner .', 'tostr': 'filter_eq { all_rows ; directed by ; jeff bleckner }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; directed by ; jeff bleckner } }', 'tointer': 'select the rows whose directed by record fuzzily matches to jeff bleckner . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; directed by ; jeff bleckner } } ; 3 } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to jeff bleckner . the number of such rows is 3 .'} | eq { count { filter_eq { all_rows ; directed by ; jeff bleckner } } ; 3 } = true | select the rows whose directed by record fuzzily matches to jeff bleckner . 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, 'directed by_5': 5, 'jeff bleckner_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', 'directed by_5': 'directed by', 'jeff bleckner_6': 'jeff bleckner', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'directed by_5': [0], 'jeff bleckner_6': [0], '3_7': [2]} | ['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'viewers ( million )'] | [['11', '1', 'no excuses', 'jeff bleckner', 'glen mazzara', 'june 22 , 2010', '3.42'], ['12', '2', 'the starting line', 'ed bianchi', 'john masius & erica shelton', 'june 29 , 2010', '2.95'], ['13', '3', 'road narrows', 'ed bianchi', 'sang kyu kim', 'july 6 , 2010', '2.73'], ['14', '4', 'afterglow', 'jeff bleckner', 'darin goldberg & shelley meals', 'july 13 , 2010', '2.64'], ['15', '5', 'the match', 'mike robe', 'adam e fierro & glen mazzara', 'july 20 , 2010', '2.86'], ['16', '6', 'final curtain', 'tricia brock', 'sarah thorp', 'july 27 , 2010', '2.63'], ['17', '7', 'hidden truths', 'jeff bleckner', 'darin goldberg & shelley meals', 'august 3 , 2010', '3.12'], ['18', '8', 'a mother knows', 'tricia brock', 'erica shelton', 'august 10 , 2010', '3.24']] |
list of tallest buildings in quebec city | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Quebec_City | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11111275-1.html.csv | ordinal | hôtel loews le concorde has the 3rd highest number of floors among the tallest buildings in quebec city . | {'row': '4', 'col': '4', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'floors', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; floors ; 3 }'}, 'name'], 'result': 'hôtel loews le concorde', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; floors ; 3 } ; name }'}, 'hôtel loews le concorde'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; floors ; 3 } ; name } ; hôtel loews le concorde } = true', 'tointer': 'select the row whose floors record of all rows is 3rd maximum . the name record of this row is hôtel loews le concorde .'} | eq { hop { nth_argmax { all_rows ; floors ; 3 } ; name } ; hôtel loews le concorde } = true | select the row whose floors record of all rows is 3rd maximum . the name record of this row is hôtel loews le concorde . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'floors_5': 5, '3_6': 6, 'name_7': 7, 'hôtel loews le concorde_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', 'floors_5': 'floors', '3_6': '3', 'name_7': 'name', 'hôtel loews le concorde_8': 'hôtel loews le concorde'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'floors_5': [0], '3_6': [0], 'name_7': [1], 'hôtel loews le concorde_8': [2]} | ['rank', 'name', 'height m ( ft )', 'floors', 'year'] | [['1', 'édifice marie - guyart', '-', '33', '1972'], ['2', 'complexe jules dallaire ii', '-', '28', '2013'], ['3', 'place hauteville', '-', '34', '1974'], ['4', 'hôtel loews le concorde', '-', '31', '1974'], ['5', 'hôtel hilton québec', '-', '28', '1974'], ['6', 'édifice price', '-', '18', '1930'], ['7', 'place de la capitale', '-', '21', '1974'], ['8', 'le samuel - holland i', '-', '24', '1981'], ['9', 'chteau frontenac', '-', '18', '1893'], ['10', "édifice d'youville", '-', '21', '1969'], ['11', 'complexe jules - dallaire i', '-', '17', '2010']] |
english open ( table tennis ) | https://en.wikipedia.org/wiki/English_Open_%28table_tennis%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28211988-1.html.csv | unique | the 1998/99 season of the english open was the only one hosted in hopton-on-sea . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'hopton - on - sea', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'host', 'hopton - on - sea'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose host record fuzzily matches to hopton - on - sea .', 'tostr': 'filter_eq { all_rows ; host ; hopton - on - sea }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; host ; hopton - on - sea } }', 'tointer': 'select the rows whose host record fuzzily matches to hopton - on - sea . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'host', 'hopton - on - sea'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose host record fuzzily matches to hopton - on - sea .', 'tostr': 'filter_eq { all_rows ; host ; hopton - on - sea }'}, 'season'], 'result': '1998 / 99', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; host ; hopton - on - sea } ; season }'}, '1998 / 99'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; host ; hopton - on - sea } ; season } ; 1998 / 99 }', 'tointer': 'the season record of this unqiue row is 1998 / 99 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; host ; hopton - on - sea } } ; eq { hop { filter_eq { all_rows ; host ; hopton - on - sea } ; season } ; 1998 / 99 } } = true', 'tointer': 'select the rows whose host record fuzzily matches to hopton - on - sea . there is only one such row in the table . the season record of this unqiue row is 1998 / 99 .'} | and { only { filter_eq { all_rows ; host ; hopton - on - sea } } ; eq { hop { filter_eq { all_rows ; host ; hopton - on - sea } ; season } ; 1998 / 99 } } = true | select the rows whose host record fuzzily matches to hopton - on - sea . there is only one such row in the table . the season record of this unqiue row is 1998 / 99 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'host_7': 7, 'hopton - on - sea_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'season_9': 9, '1998 / 99_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'host_7': 'host', 'hopton - on - sea_8': 'hopton - on - sea', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'season_9': 'season', '1998 / 99_10': '1998 / 99'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'host_7': [0], 'hopton - on - sea_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'season_9': [2], '1998 / 99_10': [3]} | ['season', 'host', 'mens singles', 'womens singles', 'mens doubles', 'womens doubles'] | [['1995 / 96', 'kettering', 'kong linghui', 'yang ying', 'werner schlager karl jindrak', 'yang ying wang hui'], ['1996 / 97', 'kettering', 'jean - michel saive', 'chen - tong fei - ming', 'christophe legout patrick chila', 'chai po wa qiao yunping'], ['1998 / 99', 'hopton - on - sea', 'ma wenge', 'jie schoepp', 'trinko keen danny heister', 'lee eun - sil ryu ji - hae'], ['2000 / 01', 'chatham', 'wang liqin', 'yoshie takada', 'timo boll zoltan fejer - konnerth', 'kim hyang mi kim hyon hui'], ['2008 / 09', 'sheffield', 'ma long', 'guo yan', 'ma long wang liqin', 'kim kyung ah park mi young']] |
bharatiya janata party | https://en.wikipedia.org/wiki/Bharatiya_Janata_Party | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-149330-1.html.csv | aggregation | the average number of seats won per year by the bharatiya janata party is 112 . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '112', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'seats won'], 'result': '112', 'ind': 0, 'tostr': 'avg { all_rows ; seats won }'}, '112'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; seats won } ; 112 } = true', 'tointer': 'the average of the seats won record of all rows is 112 .'} | round_eq { avg { all_rows ; seats won } ; 112 } = true | the average of the seats won record of all rows is 112 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'seats won_4': 4, '112_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'seats won_4': 'seats won', '112_5': '112'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'seats won_4': [0], '112_5': [1]} | ['year', 'general election', 'seats won', 'change in seat', '% of votes', 'votes swing'] | [['indian general election , 1980', '7th lok sabha', '12', '12', '8.75 %', '8.75'], ['indian general election , 1984', '8th lok sabha', '2', '10', '7.74 %', '1.01'], ['indian general election , 1989', '9th lok sabha', '85', '83', '11.36', '3.62'], ['indian general election , 1991', '10th lok sabha', '120', '37', '20.11', '8.75'], ['indian general election , 1996', '11th lok sabha', '161', '41', '20.29', '0.18'], ['indian general election , 1998', '12th lok sabha', '183', '21', '25.59 %', '5.30'], ['indian general election , 1999', '13th lok sabha', '189', '6', '23.75', '1.84'], ['indian general election , 2004', '14th lok sabha', '144', '45', '22.16 %', '1.69']] |
asian youth volleyball championship | https://en.wikipedia.org/wiki/Asian_Youth_Volleyball_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16744545-5.html.csv | comparative | the rank 2 team in the asian youth volleyball championship received more silver medals than the rank 1 team . | {'row_1': '2', 'row_2': '1', 'col': '3', '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', 'rank', '2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rank record fuzzily matches to 2 .', 'tostr': 'filter_eq { all_rows ; rank ; 2 }'}, 'silver'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; rank ; 2 } ; silver }', 'tointer': 'select the rows whose rank record fuzzily matches to 2 . take the silver record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rank', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rank record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; rank ; 1 }'}, 'silver'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; rank ; 1 } ; silver }', 'tointer': 'select the rows whose rank record fuzzily matches to 1 . take the silver record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; rank ; 2 } ; silver } ; hop { filter_eq { all_rows ; rank ; 1 } ; silver } } = true', 'tointer': 'select the rows whose rank record fuzzily matches to 2 . take the silver record of this row . select the rows whose rank record fuzzily matches to 1 . take the silver record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; rank ; 2 } ; silver } ; hop { filter_eq { all_rows ; rank ; 1 } ; silver } } = true | select the rows whose rank record fuzzily matches to 2 . take the silver record of this row . select the rows whose rank record fuzzily matches to 1 . 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, 'rank_7': 7, '2_8': 8, 'silver_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'rank_11': 11, '1_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', 'rank_7': 'rank', '2_8': '2', 'silver_9': 'silver', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'rank_11': 'rank', '1_12': '1', 'silver_13': 'silver'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'rank_7': [0], '2_8': [0], 'silver_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'rank_11': [1], '1_12': [1], 'silver_13': [3]} | ['rank', 'gold', 'silver', 'bronze', 'total'] | [['1', '5', '2', '0', '7'], ['2', '4', '3', '2', '9'], ['3', '0', '3', '1', '4'], ['4', '0', '1', '0', '1'], ['5', '0', '0', '3', '3'], ['total', '9', '9', '9', '27']] |
history of test cricket from 1901 to 1914 | https://en.wikipedia.org/wiki/History_of_Test_cricket_from_1901_to_1914 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1598207-1.html.csv | comparative | hugh trumble served as the captain of the team after joe darling had been the captain . | {'row_1': '3', 'row_2': '4', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home captain', 'joe darling'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home captain record fuzzily matches to joe darling .', 'tostr': 'filter_eq { all_rows ; home captain ; joe darling }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; home captain ; joe darling } ; date }', 'tointer': 'select the rows whose home captain record fuzzily matches to joe darling . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home captain', 'hugh trumble'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose home captain record fuzzily matches to hugh trumble .', 'tostr': 'filter_eq { all_rows ; home captain ; hugh trumble }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; home captain ; hugh trumble } ; date }', 'tointer': 'select the rows whose home captain record fuzzily matches to hugh trumble . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; home captain ; joe darling } ; date } ; hop { filter_eq { all_rows ; home captain ; hugh trumble } ; date } } = true', 'tointer': 'select the rows whose home captain record fuzzily matches to joe darling . take the date record of this row . select the rows whose home captain record fuzzily matches to hugh trumble . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; home captain ; joe darling } ; date } ; hop { filter_eq { all_rows ; home captain ; hugh trumble } ; date } } = true | select the rows whose home captain record fuzzily matches to joe darling . take the date record of this row . select the rows whose home captain record fuzzily matches to hugh trumble . 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, 'home captain_7': 7, 'joe darling_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'home captain_11': 11, 'hugh trumble_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', 'home captain_7': 'home captain', 'joe darling_8': 'joe darling', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'home captain_11': 'home captain', 'hugh trumble_12': 'hugh trumble', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'home captain_7': [0], 'joe darling_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'home captain_11': [1], 'hugh trumble_12': [1], 'date_13': [3]} | ['date', 'home captain', 'away captain', 'venue', 'result'] | [['13 , 14 , 16 dec 1901', 'joe darling', 'archie maclaren', 'sydney cricket ground', 'eng by inns & 124 runs'], ['1 , 2 , 3 , 4 jan 1902', 'joe darling', 'archie maclaren', 'melbourne cricket ground', 'aus by 229 runs'], ['17 , 18 , 20 , 21 , 22 , 23 jan 1902', 'joe darling', 'archie maclaren', 'adelaide oval', 'aus by 4 wkts'], ['14 , 15 , 17 , 18 feb 1902', 'hugh trumble', 'archie maclaren', 'sydney cricket ground', 'aus by 7 wkts'], ['28 feb , 1 , 3 , 4 mar 1902', 'hugh trumble', 'archie maclaren', 'melbourne cricket ground', 'aus by 32 runs']] |
list of ben 10 : alien force episodes | https://en.wikipedia.org/wiki/List_of_Ben_10%3A_Alien_Force_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16581695-4.html.csv | unique | " simple " was the only episode of ben 10 : alien force written by stan berkowitz . | {'scope': 'all', 'row': '4', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'stan berkowitz', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'stan berkowitz'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to stan berkowitz .', 'tostr': 'filter_eq { all_rows ; written by ; stan berkowitz }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; written by ; stan berkowitz } }', 'tointer': 'select the rows whose written by record fuzzily matches to stan berkowitz . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'stan berkowitz'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to stan berkowitz .', 'tostr': 'filter_eq { all_rows ; written by ; stan berkowitz }'}, 'title'], 'result': 'simple', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; written by ; stan berkowitz } ; title }'}, 'simple'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; written by ; stan berkowitz } ; title } ; simple }', 'tointer': 'the title record of this unqiue row is simple .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; written by ; stan berkowitz } } ; eq { hop { filter_eq { all_rows ; written by ; stan berkowitz } ; title } ; simple } } = true', 'tointer': 'select the rows whose written by record fuzzily matches to stan berkowitz . there is only one such row in the table . the title record of this unqiue row is simple .'} | and { only { filter_eq { all_rows ; written by ; stan berkowitz } } ; eq { hop { filter_eq { all_rows ; written by ; stan berkowitz } ; title } ; simple } } = true | select the rows whose written by record fuzzily matches to stan berkowitz . there is only one such row in the table . the title record of this unqiue row is simple . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'written by_7': 7, 'stan berkowitz_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'simple_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'written by_7': 'written by', 'stan berkowitz_8': 'stan berkowitz', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'simple_10': 'simple'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'written by_7': [0], 'stan berkowitz_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'simple_10': [3]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original airdate', 'production code'] | [['27 - 28', '1 - 2', 'vengeance of vilgax', 'dan riba and butch lukic', 'dwayne mcduffie', 'september 11 , 2009', '301 - 302'], ['29', '3', 'inferno', 'john fang', 'len uhley', 'september 18 , 2009', '303'], ['30', '4', "fool 's gold", 'dan riba', 'eugene son', 'september 25 , 2009', '304'], ['31', '5', 'simple', 'butch lukic', 'stan berkowitz', 'october 9 , 2009', '305'], ['32', '6', 'vreedle , vreedle', 'john fang', 'charlotte fullerton', 'october 16 , 2009', '306'], ['33', '7', 'singlehanded', 'dan riba', 'marty isenberg', 'october 23 , 2009', '307'], ['34', '8', 'if all else fails', 'butch lukic', 'adam beecham', 'november 6 , 2009', '308'], ['35', '9', "in charm 's way", 'john fang and rick morales', 'peter david', 'november 13 , 2009', '309'], ['36', '10', 'ghost town', 'dan riba', 'nicole dubuc', 'november 20 , 2009', '310'], ['37', '11', 'trade - off', 'dan riba', 'len wein', 'december 4 , 2009', '311'], ['38', '12', 'busy box', 'rick morales', 'jake black', 'december 11 , 2009', '312'], ['39', '13', 'con of rath', 'dan riba', 'len uhley', 'january 8 , 2010', '313'], ['40', '14', 'primus', 'butch lukic', 'charlotte fullerton', 'january 15 , 2010', '314'], ['41', '15', 'time heals', 'rick morales', 'len ulhey', 'january 22 , 2010', '315'], ['42', '16', 'the secret of chromastone', 'dan riba', 'rick fogel', 'january 29 , 2010', '316'], ['43', '17', 'above and beyond', 'butch lukic', 'eugene son', 'march 12 , 2010', '317'], ['44', '18', 'vendetta', 'rick morales', 'len wein', 'march 19 , 2010', '318']] |
list of metropolitan areas in sweden | https://en.wikipedia.org/wiki/List_of_metropolitan_areas_in_Sweden | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1245658-3.html.csv | ordinal | malmö is the municipality with the highest density square among sweden 's metropolitan areas . | {'row': '1', 'col': '5', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'density square', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; density square ; 1 }'}, 'municipality'], 'result': 'malmö', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; density square ; 1 } ; municipality }'}, 'malmö'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; density square ; 1 } ; municipality } ; malmö } = true', 'tointer': 'select the row whose density square record of all rows is 1st maximum . the municipality record of this row is malmö .'} | eq { hop { nth_argmax { all_rows ; density square ; 1 } ; municipality } ; malmö } = true | select the row whose density square record of all rows is 1st maximum . the municipality record of this row is malmö . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'density square_5': 5, '1_6': 6, 'municipality_7': 7, 'malmö_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', 'density square_5': 'density square', '1_6': '1', 'municipality_7': 'municipality', 'malmö_8': 'malmö'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'density square_5': [0], '1_6': [0], 'municipality_7': [1], 'malmö_8': [2]} | ['municipality', 'number', 'population', 'area', 'density square'] | [['malmö', '1', '309912', '335.14', '925'], ['vellinge', '2', '33725', '143.18', '236'], ['trelleborg', '3', '42744', '342.07', '125'], ['skurup', '4', '15000', '195.17', '77'], ['svedala', '5', '20039', '218.97', '92'], ['lund', '6', '112925', '430.27', '262'], ['staffanstorp', '7', '22572', '107.61', '210'], ['burlöv', '8', '17079', '18.84', '907'], ['lomma', '9', '22415', '55.64', '403'], ['kävlinge', '10', '29513', '153.83', '192'], ['eslöv', '11', '31761', '421.66', '75'], ['höör', '12', '15591', '292.96', '53'], ['total', '12', '673276', '2715.34', '247.95']] |
2008 - 09 golden state warriors season | https://en.wikipedia.org/wiki/2008%E2%80%9309_Golden_State_Warriors_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17080868-9.html.csv | unique | the game on march 3 was the only game played at target center . | {'scope': 'all', 'row': '2', 'col': '8', 'col_other': '2', 'criterion': 'equal', 'value': 'target center', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'target center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to target center .', 'tostr': 'filter_eq { all_rows ; location attendance ; target center }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location attendance ; target center } }', 'tointer': 'select the rows whose location attendance record fuzzily matches to target center . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'target center'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to target center .', 'tostr': 'filter_eq { all_rows ; location attendance ; target center }'}, 'date'], 'result': 'march 3', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location attendance ; target center } ; date }'}, 'march 3'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location attendance ; target center } ; date } ; march 3 }', 'tointer': 'the date record of this unqiue row is march 3 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location attendance ; target center } } ; eq { hop { filter_eq { all_rows ; location attendance ; target center } ; date } ; march 3 } } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to target center . there is only one such row in the table . the date record of this unqiue row is march 3 .'} | and { only { filter_eq { all_rows ; location attendance ; target center } } ; eq { hop { filter_eq { all_rows ; location attendance ; target center } ; date } ; march 3 } } = true | select the rows whose location attendance record fuzzily matches to target center . there is only one such row in the table . the date record of this unqiue row is march 3 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location attendance_7': 7, 'target center_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'march 3_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location attendance_7': 'location attendance', 'target center_8': 'target center', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'march 3_10': 'march 3'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location attendance_7': [0], 'target center_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'march 3_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 1', 'utah', 'l 104 - 112 ( ot )', 'corey maggette ( 27 )', 'andris biedriņš ( 12 )', 'c j watson ( 5 )', 'oracle arena 18347', '20 - 39'], ['60', 'march 3', 'minnesota', 'w 118 - 94 ( ot )', 'stephen jackson ( 23 )', 'andris biedriņš ( 13 )', 'stephen jackson ( 6 )', 'target center 14780', '21 - 39'], ['61', 'march 4', 'chicago', 'l 88 - 110 ( ot )', 'stephen jackson ( 19 )', 'anthony randolph ( 10 )', 'stephen jackson ( 6 )', 'united center 20108', '21 - 40'], ['62', 'march 6', 'detroit', 'l 91 - 108 ( ot )', 'jamal crawford ( 25 )', 'jermareo davidson ( 10 )', 'jamal crawford ( 8 )', 'the palace of auburn hills 22076', '21 - 41'], ['63', 'march 7', 'milwaukee', 'l 120 - 127 ( ot )', 'jamal crawford ( 32 )', 'anthony randolph ( 8 )', 'stephen jackson ( 11 )', 'bradley center 15569', '21 - 42'], ['64', 'march 11', 'new jersey', 'w 116 - 112 ( ot )', 'stephen jackson ( 29 )', 'andris biedriņš ( 13 )', 'stephen jackson ( 7 )', 'oracle arena 18203', '22 - 42'], ['65', 'march 13', 'dallas', 'w 119 - 110 ( ot )', 'stephen jackson ( 31 )', 'ronny turiaf ( 12 )', 'stephen jackson ( 10 )', 'oracle arena 18751', '23 - 42'], ['66', 'march 15', 'phoenix', 'l 130 - 154 ( ot )', 'monta ellis ( 26 )', 'anthony randolph , ronny turiaf ( 6 )', 'stephen jackson ( 9 )', 'oracle arena 19596', '23 - 43'], ['67', 'march 17', 'la clippers', 'w 127 - 120 ( ot )', 'monta ellis ( 29 )', 'kelenna azubuike ( 9 )', 'ronny turiaf ( 8 )', 'oracle arena 18223', '24 - 43'], ['68', 'march 19', 'la lakers', 'l 106 - 114 ( ot )', 'monta ellis ( 27 )', 'brandan wright ( 10 )', 'corey maggette ( 7 )', 'staples center 18997', '24 - 44'], ['69', 'march 20', 'philadelphia', 'w 119 - 111 ( ot )', 'brandan wright ( 25 )', 'stephen jackson ( 10 )', 'stephen jackson ( 9 )', 'oracle arena 19596', '25 - 44'], ['70', 'march 22', 'new orleans', 'l 89 - 99 ( ot )', 'stephen jackson ( 22 )', 'stephen jackson ( 10 )', 'stephen jackson ( 5 )', 'new orleans arena 16351', '25 - 45'], ['71', 'march 24', 'san antonio', 'l 106 - 107 ( ot )', 'monta ellis ( 27 )', 'anthony randolph ( 9 )', 'stephen jackson ( 4 )', 'at & t center 18797', '25 - 46'], ['72', 'march 25', 'dallas', 'l 106 - 128 ( ot )', 'anthony morrow ( 29 )', 'anthony randolph ( 6 )', 'monta ellis , stephen jackson ( 5 )', 'american airlines center 19862', '25 - 47'], ['73', 'march 28', 'denver', 'l 116 - 129 ( ot )', 'jamal crawford ( 30 )', 'anthony randolph ( 14 )', 'jamal crawford ( 5 )', 'pepsi center 19155', '25 - 48'], ['74', 'march 30', 'memphis', 'l 109 - 114 ( ot )', 'monta ellis ( 29 )', 'anthony randolph ( 12 )', 'monta ellis ( 5 )', 'oracle arena 18471', '25 - 49']] |
1965 vfl season | https://en.wikipedia.org/wiki/1965_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10788451-9.html.csv | count | there were 6 game venues used during the 1965 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '14.10 ( 94 )', 'north melbourne', '14.13 ( 97 )', 'glenferrie oval', '11000', '12 june 1965'], ['south melbourne', '20.9 ( 129 )', 'geelong', '17.13 ( 115 )', 'lake oval', '32260', '12 june 1965'], ['essendon', '7.12 ( 54 )', 'collingwood', '12.14 ( 86 )', 'windy hill', '34900', '12 june 1965'], ['melbourne', '9.7 ( 61 )', 'st kilda', '18.14 ( 122 )', 'mcg', '72114', '14 june 1965'], ['footscray', '9.11 ( 65 )', 'richmond', '9.17 ( 71 )', 'western oval', '25345', '14 june 1965'], ['fitzroy', '9.7 ( 61 )', 'carlton', '14.18 ( 102 )', 'brunswick street oval', '20140', '14 june 1965']] |
list of cold feet episodes | https://en.wikipedia.org/wiki/List_of_Cold_Feet_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12919003-2.html.csv | aggregation | the first five episodes of cold feet averaged 7.52 million viewers . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '7.52', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'viewers ( millions )'], 'result': '7.52', 'ind': 0, 'tostr': 'avg { all_rows ; viewers ( millions ) }'}, '7.52'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; viewers ( millions ) } ; 7.52 } = true', 'tointer': 'the average of the viewers ( millions ) record of all rows is 7.52 .'} | round_eq { avg { all_rows ; viewers ( millions ) } ; 7.52 } = true | the average of the viewers ( millions ) record of all rows is 7.52 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'viewers (millions)_4': 4, '7.52_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'viewers (millions)_4': 'viewers ( millions )', '7.52_5': '7.52'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'viewers (millions)_4': [0], '7.52_5': [1]} | ['no', 'episode', 'writer', 'director', 'viewers ( millions )', 'original airdate'] | [['1', 'episode 1', 'mike bullen', 'declan lowney', '7.47', '15 november 1998'], ['2', 'episode 2', 'mike bullen', 'declan lowney', '7.33', '22 november 1998'], ['3', 'episode 3', 'mike bullen', 'mark mylod', '7.46', '29 november 1998'], ['4', 'episode 4', 'mike bullen', 'mark mylod', '7.44', '6 december 1998'], ['5', 'episode 5', 'mike bullen', 'nigel cole', '7.91', '13 december 1998']] |
dancing on ice ( series 4 ) | https://en.wikipedia.org/wiki/Dancing_on_Ice_%28series_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19744915-4.html.csv | aggregation | in the show dancing on ice series 4 , the total score given by the jury for participant couples was on average 15 points . | {'scope': 'all', 'col': '8', 'type': 'average', 'result': '15', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total'], 'result': '15', 'ind': 0, 'tostr': 'avg { all_rows ; total }'}, '15'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total } ; 15 } = true', 'tointer': 'the average of the total record of all rows is 15 .'} | round_eq { avg { all_rows ; total } ; 15 } = true | the average of the total record of all rows is 15 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total_4': 4, '15_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total_4': 'total', '15_5': '15'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total_4': [0], '15_5': [1]} | ['order', 'couple', 'karen', 'nicky', 'jason', 'ruthie', 'robin', 'total', 'skating song', 'scoreboard', 'public vote'] | [['1', 'roxanne & daniel', '3.5', '3.0', '2.5', '3.0', '3.5', '15.0', 'take a bow - rihanna', '4th', '13.563 %'], ['2', 'melinda & fred', '3.5', '3.5', '2.5', '3.5', '3.5', '15.5', 'love song - sara bareilles', '3rd', '2.922 %'], ['3', 'coleen & stuart', '2.5', '2.5', '2.0', '2.5', '3.0', '12.5', 'dream a little dream of me - ella fitzgerald', '6th', '61.801 %'], ['4', 'zöe & matt', '4.0', '4.0', '3.0', '3.5', '4.0', '18.5', 'i wan na dance with somebody - whitney houston', '2nd', '7.593 %'], ['5', 'gemma & andrei', '2.5', '3.0', '2.0', '2.5', '3.0', '13.5', 'the power of love - jennifer rush', '5th', '3.901 %']] |
sunline | https://en.wikipedia.org/wiki/Sunline | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2581397-4.html.csv | majority | most of sunline 's wins occured in the the 1400 meter race . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1400 m', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'won'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 'won'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; result ; won }', 'tointer': 'select the rows whose result record fuzzily matches to won .'}, 'distance', '1400 m'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose result record fuzzily matches to won . for the distance records of these rows , most of them fuzzily match to 1400 m .', 'tostr': 'most_eq { filter_eq { all_rows ; result ; won } ; distance ; 1400 m } = true'} | most_eq { filter_eq { all_rows ; result ; won } ; distance ; 1400 m } = true | select the rows whose result record fuzzily matches to won . for the distance records of these rows , most of them fuzzily match to 1400 m . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'result_4': 4, 'won_5': 5, 'distance_6': 6, '1400 m_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'result_4': 'result', 'won_5': 'won', 'distance_6': 'distance', '1400 m_7': '1400 m'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'result_4': [0], 'won_5': [0], 'distance_6': [1], '1400 m_7': [1]} | ['result', 'date', 'race', 'venue', 'group', 'distance', 'weight ( kg )', 'jockey', 'winner / 2nd'] | [['won', '19 august 2000', 'manikato stakes', 'moonee valley', 'g1', '1200 m', '55', 'g childs', '2nd - honour the name'], ['won', '3 september 2000', 'memsie stakes', 'caulfield', 'g2', '1400 m', '55.5', 'g childs', '2nd - umrum'], ['won', '16 september 2000', 'j f feehan stakes', 'moonee valley', 'g2', '1600 m', '55.5', 'g childs', '2nd - le zagaletta'], ['2nd', '7 october 2000', 'turnbull stakes', 'flemington', 'g2', '2000 m', '56.5', 'g childs', '1st - fairway'], ['won', '28 october 2000', 'cox plate', 'moonee valley', 'g1', '2040 m', '55.5', 'g childs', '2nd - diatribe'], ['won', '25 november 2000', 'breeders stakes', 'pukekohe', 'g2', '1400 m', '55.5', 'g childs', '2nd - amnesia'], ['won', '17 december 2000', 'hong kong mile', 'sha tin', 'g1', '1600 m', '56', 'g childs', '2nd - fairy king prawn'], ['won', '10 february 2001', 'waikato sprint', 'te rapa', 'g1', '1400 m', '56', 'g childs', '2nd - fritz'], ['won', '3 march 2001', 'apollo stakes', 'warwick farm', 'g2', '1400 m', '55.5', 'g childs', '2nd - celestial choir'], ['3rd', '24 march 2001', 'dubai duty free stakes', 'nad al sheba', 'g2', '1777 m', '55', 'g childs', '1st - jim and tonic']] |
latin americans | https://en.wikipedia.org/wiki/Latin_Americans | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1333612-1.html.csv | aggregation | the average population of the countries in latin america is 28114713 . | {'scope': 'all', 'col': '2', 'type': 'average', 'result': '28114713', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'population'], 'result': '28114713', 'ind': 0, 'tostr': 'avg { all_rows ; population }'}, '28114713'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; population } ; 28114713 } = true', 'tointer': 'the average of the population record of all rows is 28114713 .'} | round_eq { avg { all_rows ; population } ; 28114713 } = true | the average of the population record of all rows is 28114713 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'population_4': 4, '28114713_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'population_4': 'population', '28114713_5': '28114713'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'population_4': [0], '28114713_5': [1]} | ['country', 'population', 'native american', 'whites', 's mestizo', 'es mulatto', 'blacks', 's zambo', 'asians'] | [['argentina', '40134425', '1.0 %', '85.0 %', '11.1 %', '0.0 %', '0.0 %', '0.0 %', '2.9 %'], ['bolivia', '10907778', '55.0 %', '15.0 %', '28.0 %', '2.0 %', '0.0 %', '0.0 %', '0.0 %'], ['brazil', '192272890', '0.4 %', '53.8 %', '0.0 %', '39.1 %', '6.2 %', '0.0 %', '0.5 %'], ['chile', '17063000', '3.2 %', '52.7 %', '44.1 %', '0.0 %', '0.0 %', '0.0 %', '0.0 %'], ['colombia', '45393050', '1.8 %', '20.0 %', '53.2 %', '21.0 %', '3.9 %', '0.1 %', '0.0 %'], ['costa rica', '4253897', '0.8 %', '82.0 %', '15.0 %', '0.0 %', '0.0 %', '2.0 %', '0.2 %'], ['cuba', '11236444', '0.0 %', '37.0 %', '0.0 %', '51.0 %', '11.0 %', '0.0 %', '1.0 %'], ['dominican republic', '8562541', '0.0 %', '14.6 %', '0.0 %', '75.0 %', '7.7 %', '2.3 %', '0.4 %'], ['ecuador', '13625000', '39.0 %', '9.9 %', '41.0 %', '5.0 %', '5.0 %', '0.0 %', '0.1 %'], ['el salvador', '6134000', '1.0 %', '12.0 %', '86.0 %', '0.0 %', '0.0 %', '0.0 %', '0.0 %'], ['guatemala', '13276517', '53.0 %', '4.0 %', '42.0 %', '0.0 %', '0.0 %', '0.2 %', '0.8 %'], ['honduras', '7810848', '7.7 %', '1.0 %', '85.6 %', '1.7 %', '0.0 %', '3.3 %', '0.7 %'], ['mexico', '112322757', '14 %', '15 %', '70 %', '0.5 %', '0.0 %', '0.0 %', '0.5 %'], ['nicaragua', '5891199', '6.9 %', '14.0 %', '78.3 %', '0.0 %', '0.0 %', '0.6 %', '0.2 %'], ['panama', '3322576', '8.0 %', '10.0 %', '32.0 %', '27.0 %', '5.0 %', '14.0 %', '4.0 %'], ['paraguay', '6349000', '1.5 %', '20.0 %', '74.5 %', '3.5 %', '0.0 %', '0.0 %', '0.5 %'], ['peru', '29461933', '45.5 %', '12.0 %', '32.0 %', '9.7 %', '0.0 %', '0.0 %', '0.8 %'], ['puerto rico', '3967179', '0.0 %', '74.8 %', '0.0 %', '10.0 %', '15.0 %', '0.0 %', '0.2 %'], ['uruguay', '3494382', '0.0 %', '88.0 %', '8.0 %', '4.0 %', '0.0 %', '0.0 %', '0.0 %'], ['venezuela', '26814843', '2.7 %', '42.2 %', '42.9 %', '0.7 %', '2.8 %', '0.0 %', '2.2 %']] |
1985 pga tour | https://en.wikipedia.org/wiki/1985_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14640372-4.html.csv | majority | most of the golfers on the 1985 pga tour had more than 20 wins . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '20', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'wins', '20'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , most of them are greater than 20 .', 'tostr': 'most_greater { all_rows ; wins ; 20 } = true'} | most_greater { all_rows ; wins ; 20 } = true | for the wins records of all rows , most of them are greater than 20 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '20_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '20_4': '20'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '20_4': [0]} | ['rank', 'player', 'country', 'earnings', 'wins'] | [['1', 'jack nicklaus', 'united states', '4686280', '72'], ['2', 'tom watson', 'united states', '3806940', '36'], ['3', 'lee trevino', 'united states', '3177975', '29'], ['4', 'raymond floyd', 'united states', '2868951', '19'], ['5', 'hale irwin', 'united states', '2751050', '17']] |
kelly dullanty | https://en.wikipedia.org/wiki/Kelly_Dullanty | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17445415-2.html.csv | unique | kelly dullanty lost one match due to submission ( triangle choke ) . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'submission ( triangle choke )', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'submission ( triangle choke )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to submission ( triangle choke ) .', 'tostr': 'filter_eq { all_rows ; method ; submission ( triangle choke ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; method ; submission ( triangle choke ) } }', 'tointer': 'select the rows whose method record fuzzily matches to submission ( triangle choke ) . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'submission ( triangle choke )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to submission ( triangle choke ) .', 'tostr': 'filter_eq { all_rows ; method ; submission ( triangle choke ) }'}, 'res'], 'result': 'loss', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; method ; submission ( triangle choke ) } ; res }'}, 'loss'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; method ; submission ( triangle choke ) } ; res } ; loss }', 'tointer': 'the res record of this unqiue row is loss .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; method ; submission ( triangle choke ) } } ; eq { hop { filter_eq { all_rows ; method ; submission ( triangle choke ) } ; res } ; loss } } = true', 'tointer': 'select the rows whose method record fuzzily matches to submission ( triangle choke ) . there is only one such row in the table . the res record of this unqiue row is loss .'} | and { only { filter_eq { all_rows ; method ; submission ( triangle choke ) } } ; eq { hop { filter_eq { all_rows ; method ; submission ( triangle choke ) } ; res } ; loss } } = true | select the rows whose method record fuzzily matches to submission ( triangle choke ) . there is only one such row in the table . the res record of this unqiue row is loss . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'method_7': 7, 'submission (triangle choke)_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'res_9': 9, 'loss_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'method_7': 'method', 'submission (triangle choke)_8': 'submission ( triangle choke )', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'res_9': 'res', 'loss_10': 'loss'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'method_7': [0], 'submission (triangle choke)_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'res_9': [2], 'loss_10': [3]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'location'] | [['loss', '4 - 2', 'lance wipf', 'ko ( punch )', 'purecombat - bring the pain', '1', 'california , united states'], ['loss', '4 - 1', 'matt serra', 'submission ( triangle choke )', 'ufc 36', '1', 'nevada , united states'], ['win', '4 - 0', 'nuri shakir', 'decision', 'ifc wc 13 - warriors challenge 13', '4', 'california , united states'], ['win', '3 - 0', 'rudy vallederas', 'tko', 'ifc wc 13 - warriors challenge 13', 'n / a', 'california , united states'], ['win', '2 - 0', 'duane ludwig', 'decision', 'kotc 6 - road warriors', '3', 'michigan , united states'], ['win', '1 - 0', 'shad smith', 'tko ( strikes )', 'kotc 3 - knockout nightmare', '1', 'california , united states']] |
daniel gimeno - traver | https://en.wikipedia.org/wiki/Daniel_Gimeno-Traver | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16965329-5.html.csv | unique | daniel gimeno - traver only played one match in july of 2010 . | {'scope': 'all', 'row': '6', 'col': '1', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'july 2010', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'july 2010'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to july 2010 .', 'tostr': 'filter_eq { all_rows ; date ; july 2010 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; date ; july 2010 } } = true', 'tointer': 'select the rows whose date record fuzzily matches to july 2010 . there is only one such row in the table .'} | only { filter_eq { all_rows ; date ; july 2010 } } = true | select the rows whose date record fuzzily matches to july 2010 . 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, 'date_4': 4, 'july 2010_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'july 2010_5': 'july 2010'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'july 2010_5': [0]} | ['date', 'tournament', 'surface', 'opponent', 'score'] | [['5 september 2005', 'brasov', 'clay', 'daniel elsner', '5 - 7 , 2 - 6'], ['5 november 2007', 'guayaquil', 'clay', 'nicolás lapentti', '3 - 6 , 7 - 6 ( 6 ) , 5 - 7'], ['10 march 2008', 'tanger', 'clay', 'marcel granollers', '4 - 6 , 4 - 6'], ['15 september 2008', 'banja luka', 'clay', 'ilija bozoljac', '4 - 6 , 4 - 6'], ['12 october 2009', 'asunción', 'clay', 'ramón delgado', '6 - 7 ( 2 - 7 ) , 6 - 1 , 3 - 6'], ['5 july 2010', 'san benedetto', 'clay', 'carlos berlocq', '3 - 6 , 6 - 4 , 4 - 6'], ['2 october 2011', 'madrid', 'clay', 'jérémy chardy', '1 - 6 , 7 - 5 , 6 - 7 ( 3 - 7 )'], ['12 august 2012', 'cordenos', 'clay', 'paolo lorenzi', '6 - 7 ( 5 - 7 ) , 3 - 6']] |
1968 cleveland browns season | https://en.wikipedia.org/wiki/1968_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652150-2.html.csv | aggregation | the average crowd attendance in the 1968 cleveland browns season was 58246 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '58246', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '58246', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '58246'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 58246 } = true', 'tointer': 'the average of the attendance record of all rows is 58246 .'} | round_eq { avg { all_rows ; attendance } ; 58246 } = true | the average of the attendance record of all rows is 58246 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '58246_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '58246_5': '58246'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '58246_5': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'august 9 , 1968', 'los angeles rams', 'l 23 - 21', '64020'], ['2', 'august 18 , 1968', 'san francisco 49ers', 'w 31 - 17', '26801'], ['3', 'august 24 , 1968', 'new orleans saints', 'l 40 - 27', '70045'], ['4', 'august 30 , 1968', 'buffalo bills', 'w 22 - 12', '45448'], ['5', 'september 7 , 1968', 'green bay packers', 'l 31 - 9', '84918']] |
dakota athletic conference | https://en.wikipedia.org/wiki/Dakota_Athletic_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-262505-1.html.csv | ordinal | the school in the dakota conference with the second highest enrollment is minot state university . | {'row': '6', 'col': '6', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'enrollment', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; enrollment ; 2 }'}, 'institution'], 'result': 'minot state university', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; enrollment ; 2 } ; institution }'}, 'minot state university'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; institution } ; minot state university } = true', 'tointer': 'select the row whose enrollment record of all rows is 2nd maximum . the institution record of this row is minot state university .'} | eq { hop { nth_argmax { all_rows ; enrollment ; 2 } ; institution } ; minot state university } = true | select the row whose enrollment record of all rows is 2nd maximum . the institution record of this row is minot state university . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, '2_6': 6, 'institution_7': 7, 'minot state university_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', 'enrollment_5': 'enrollment', '2_6': '2', 'institution_7': 'institution', 'minot state university_8': 'minot state university'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], '2_6': [0], 'institution_7': [1], 'minot state university_8': [2]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'current conference'] | [['black hills state university', 'yellow jackets', 'spearfish , south dakota', '1881', 'public', '4739', 'rmac ( ncaa division ii )'], ['dakota state university', 'trojans', 'madison , south dakota', '1881', 'public', '2282', 'naia independent'], ['dickinson state university', 'blue hawks', 'dickinson , north dakota', '1916', 'public', '2572', 'frontier conference'], ['jamestown college', 'jimmies', 'jamestown , north dakota', '1883', 'private', '900', 'naia independent'], ['mayville state university', 'comets', 'mayville , north dakota', '1889', 'public', '780', 'naia independent'], ['minot state university', 'beavers', 'minot , north dakota', '1913', 'public', '3851', 'nsic ( ncaa division ii )'], ['si tanka university at huron', 'screaming eagles', 'huron , south dakota', '1883', 'private', 'n / a', 'school closed in 2005'], ['south dakota school of mines and technology', 'hardrockers', 'rapid city , south dakota', '1885', 'public', '2345', 'ncaa d - ii independent'], ['university of mary', 'marauders', 'bismarck , north dakota', '1959', 'private', '2758', 'nsic ( ncaa division ii )']] |
worcestershire county cricket club | https://en.wikipedia.org/wiki/Worcestershire_County_Cricket_Club | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1156428-2.html.csv | comparative | the worcestershire county cricket club played more worcs la matches at the chester road north ground than at the racecourse ground . | {'row_1': '3', 'row_2': '6', 'col': '6', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name of ground', 'chester road north ground'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name of ground record fuzzily matches to chester road north ground .', 'tostr': 'filter_eq { all_rows ; name of ground ; chester road north ground }'}, 'worcs la matches'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name of ground ; chester road north ground } ; worcs la matches }', 'tointer': 'select the rows whose name of ground record fuzzily matches to chester road north ground . take the worcs la matches record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name of ground', 'racecourse ground'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name of ground record fuzzily matches to racecourse ground .', 'tostr': 'filter_eq { all_rows ; name of ground ; racecourse ground }'}, 'worcs la matches'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name of ground ; racecourse ground } ; worcs la matches }', 'tointer': 'select the rows whose name of ground record fuzzily matches to racecourse ground . take the worcs la matches record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name of ground ; chester road north ground } ; worcs la matches } ; hop { filter_eq { all_rows ; name of ground ; racecourse ground } ; worcs la matches } } = true', 'tointer': 'select the rows whose name of ground record fuzzily matches to chester road north ground . take the worcs la matches record of this row . select the rows whose name of ground record fuzzily matches to racecourse ground . take the worcs la matches record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name of ground ; chester road north ground } ; worcs la matches } ; hop { filter_eq { all_rows ; name of ground ; racecourse ground } ; worcs la matches } } = true | select the rows whose name of ground record fuzzily matches to chester road north ground . take the worcs la matches record of this row . select the rows whose name of ground record fuzzily matches to racecourse ground . take the worcs la matches 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, 'name of ground_7': 7, 'chester road north ground_8': 8, 'worcs la matches_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name of ground_11': 11, 'racecourse ground_12': 12, 'worcs la matches_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', 'name of ground_7': 'name of ground', 'chester road north ground_8': 'chester road north ground', 'worcs la matches_9': 'worcs la matches', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name of ground_11': 'name of ground', 'racecourse ground_12': 'racecourse ground', 'worcs la matches_13': 'worcs la matches'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name of ground_7': [0], 'chester road north ground_8': [0], 'worcs la matches_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name of ground_11': [1], 'racecourse ground_12': [1], 'worcs la matches_13': [3]} | ['name of ground', 'location', 'first - class span', 'worcs f - c matches', 'list a span', 'worcs la matches'] | [['bournville cricket ground', 'bournville , birmingham', '1910 - 1911', '2', 'n / a', '0'], ['chain wire club ground', 'stourport - on - severn , worcestershire', '1980', '1', 'n / a', '0'], ['chester road north ground', 'kidderminster , worcestershire', '1921 - 2008', '68', '1969 - 2008', '5'], ['evesham cricket club ground', 'evesham , worcestershire', '1951', '1', 'n / a', '0'], ['new road ( county ground )', 'worcester', '1899 - present', '1072', '1963 - present', '425'], ['racecourse ground', 'hereford', '1919 - 1983', '5', '1983 - 1987', '3'], ['seth somers park', 'halesowen , west midlands', '1964 - 1969', '2', 'n / a', '0'], ['tipton road', 'dudley , west midlands', '1911 - 1971', '88', '1969 - 1977', '14']] |
united states house of representatives elections , 1936 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1936 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342315-4.html.csv | comparative | david d terry has a first elected year which is earlier than that of john little mcclellan . | {'row_1': '5', 'row_2': '6', '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', 'david d terry'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to david d terry .', 'tostr': 'filter_eq { all_rows ; incumbent ; david d terry }'}, 'first elected'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; david d terry } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to david d terry . take the first elected record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'incumbent', 'john little mcclellan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose incumbent record fuzzily matches to john little mcclellan .', 'tostr': 'filter_eq { all_rows ; incumbent ; john little mcclellan }'}, 'first elected'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; incumbent ; john little mcclellan } ; first elected }', 'tointer': 'select the rows whose incumbent record fuzzily matches to john little mcclellan . take the first elected record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; incumbent ; david d terry } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; john little mcclellan } ; first elected } } = true', 'tointer': 'select the rows whose incumbent record fuzzily matches to david d terry . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to john little mcclellan . take the first elected record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; incumbent ; david d terry } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; john little mcclellan } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to david d terry . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to john little mcclellan . 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, 'david d terry_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'john little mcclellan_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', 'david d terry_8': 'david d terry', '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', 'john little mcclellan_12': 'john little mcclellan', '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], 'david d terry_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'john little mcclellan_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['arkansas 1', 'william j driver', 'democratic', '1920', 're - elected', 'william j driver ( d ) unopposed'], ['arkansas 2', 'john e miller', 'democratic', '1930', 're - elected', 'john e miller ( d ) unopposed'], ['arkansas 3', 'claude fuller', 'democratic', '1928', 're - elected', 'claude fuller ( d ) unopposed'], ['arkansas 4', 'william b cravens', 'democratic', '1932', 're - elected', 'william b cravens ( d ) unopposed'], ['arkansas 5', 'david d terry', 'democratic', '1933', 're - elected', 'david d terry ( d ) unopposed'], ['arkansas 6', 'john little mcclellan', 'democratic', '1934', 're - elected', 'john little mcclellan ( d ) unopposed']] |
15 equal temperament | https://en.wikipedia.org/wiki/15_equal_temperament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18955077-1.html.csv | aggregation | on the 15 equal temperament scale among intervals with a step size above 4 , the average size ( cents ) is 510 . | {'scope': 'subset', 'col': '3', 'type': 'average', 'result': '510', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '4'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'size ( steps )', '4'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; size ( steps ) ; 4 }', 'tointer': 'select the rows whose size ( steps ) record is greater than 4 .'}, 'size ( cents )'], 'result': '510', 'ind': 1, 'tostr': 'avg { filter_greater { all_rows ; size ( steps ) ; 4 } ; size ( cents ) }'}, '510'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_greater { all_rows ; size ( steps ) ; 4 } ; size ( cents ) } ; 510 } = true', 'tointer': 'select the rows whose size ( steps ) record is greater than 4 . the average of the size ( cents ) record of these rows is 510 .'} | round_eq { avg { filter_greater { all_rows ; size ( steps ) ; 4 } ; size ( cents ) } ; 510 } = true | select the rows whose size ( steps ) record is greater than 4 . the average of the size ( cents ) record of these rows is 510 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'size (steps)_5': 5, '4_6': 6, 'size (cents)_7': 7, '510_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'size (steps)_5': 'size ( steps )', '4_6': '4', 'size (cents)_7': 'size ( cents )', '510_8': '510'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'size (steps)_5': [0], '4_6': [0], 'size (cents)_7': [1], '510_8': [2]} | ['interval name', 'size ( steps )', 'size ( cents )', 'just ratio', 'just ( cents )', 'error', 'audio'] | [['perfect fifth', '9', '720', '3:2', '701.96', '+ 18.04', 'play category : articles with haudio microformats'], ['septimal tritone', '7', '560', '7:5', '582.51', '22.51', 'play category : articles with haudio microformats'], ['11:8 wide fourth', '7', '560', '11:8', '551.32', '+ 8.68', 'play category : articles with haudio microformats'], ['15:11 wide fourth', '7', '560', '15:11', '536.95', '+ 23.05', 'play category : articles with haudio microformats'], ['perfect fourth', '6', '480', '4:3', '498.04', '18.04', 'play category : articles with haudio microformats'], ['septimal major third', '5', '400', '9:7', '435.08', '35.08', 'play category : articles with haudio microformats'], ['undecimal major third', '5', '400', '14:11', '417.51', '17.51', 'play category : articles with haudio microformats'], ['major third', '5', '400', '5:4', '386.31', '+ 13.69', 'play category : articles with haudio microformats'], ['minor third', '4', '320', '6:5', '315.64', '+ 4.36', 'play category : articles with haudio microformats'], ['septimal minor third', '3', '240', '7:6', '266.87', '26.87', 'play category : articles with haudio microformats'], ['septimal whole tone', '3', '240', '8:7', '231.17', '+ 8.83', 'play category : articles with haudio microformats'], ['major tone', '3', '240', '9:8', '203.91', '+ 36.09', 'play category : articles with haudio microformats'], ['minor tone', '2', '160', '10:9', '182.40', '22.40', 'play category : articles with haudio microformats'], ['greater undecimal neutral second', '2', '160', '11:10', '165.00', '5.00', 'play category : articles with haudio microformats'], ['lesser undecimal neutral second', '2', '160', '12:11', '150.63', '+ 9.36', 'play category : articles with haudio microformats'], ['just diatonic semitone', '1', '80', '16:15', '111.73', '31.73', 'play category : articles with haudio microformats'], ['septimal chromatic semitone', '1', '80', '21:20', '84.46', '4.47', 'play category : articles with haudio microformats']] |
todd woodbridge | https://en.wikipedia.org/wiki/Todd_Woodbridge | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1547951-3.html.csv | majority | the majority of the championships for todd woodbridge were played 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', 'year', 'championship', 'surface', 'partner', 'opponents', 'score'] | [['winner', '1990', 'us open', 'hard', 'elizabeth sayers smylie', 'jim pugh natasha zvereva', '6 - 4 , 6 - 2'], ['runner - up', '1992', 'australian open', 'hard', 'arantxa sánchez vicario', 'mark woodforde nicole provis', '3 - 6 , 6 - 4 , 9 - 11'], ['winner', '1992', 'french open', 'clay', 'arantxa sánchez vicario', 'bryan shelton lori mcneil', '6 - 2 , 6 - 3'], ['winner', '1993', 'australian open', 'hard', 'arantxa sánchez vicario', 'rick leach zina garrison', '7 - 5 , 6 - 4'], ['winner', '1993', 'us open', 'hard', 'helena suková', 'mark woodforde martina navratilova', '6 - 3 , 7 - 6'], ['runner - up', '1994', 'australian open', 'hard', 'helena suková', 'andrei olhovskiy larisa savchenko neiland', '5 - 7 , 7 - 6 ( 9 - 7 ) , 2 - 6'], ['winner', '1994', 'wimbledon', 'grass', 'helena suková', 't j middleton lori mcneil', '3 - 6 , 7 - 5 , 6 - 3'], ['runner - up', '1994', 'us open', 'hard', 'jana novotná', 'patrick galbraith elna reinach', '2 - 6 , 4 - 6'], ['winner', '1995', 'french open', 'clay', 'larisa savchenko', 'john - laffnie de jager jill hetherington', '7 - 6 ( 10 - 8 ) , 7 - 6 ( 7 - 4 )'], ['runner - up', '2000', 'australian open', 'hard', 'arantxa sánchez vicario', 'jared palmer rennae stubbs', '5 - 7 , 6 - 7 ( 3 - 7 )'], ['runner - up', '2000', 'french open', 'clay', 'rennae stubbs', 'david adams mariaan de swardt', '3 - 6 , 6 - 3 , 3 - 6'], ['winner', '2001', 'us open', 'hard', 'rennae stubbs', 'leander paes lisa raymond', '6 - 4 , 5 - 7 , 7 - 6'], ['runner - up', '2003', 'australian open', 'hard', 'eleni daniilidou', 'leander paes martina navrátilová', '4 - 6 , 5 - 7'], ['runner - up', '2004', 'wimbledon', 'grass', 'alicia molik', 'wayne black cara black', '6 - 3 , 6 - 7 , 4 - 6']] |
1998 - 99 fa cup | https://en.wikipedia.org/wiki/1998%E2%80%9399_FA_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15154539-6.html.csv | unique | in the 1998 - 99 fa cup , the only game with no one scoring was on 14 february 1999 . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '5', 'criterion': 'equal', 'value': '0-0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '0-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 0-0 .', 'tostr': 'filter_eq { all_rows ; score ; 0-0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; 0-0 } }', 'tointer': 'select the rows whose score record fuzzily matches to 0-0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', '0-0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to 0-0 .', 'tostr': 'filter_eq { all_rows ; score ; 0-0 }'}, 'attendance'], 'result': '14 february 1999', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; 0-0 } ; attendance }'}, '14 february 1999'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; 0-0 } ; attendance } ; 14 february 1999 }', 'tointer': 'the attendance record of this unqiue row is 14 february 1999 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; 0-0 } } ; eq { hop { filter_eq { all_rows ; score ; 0-0 } ; attendance } ; 14 february 1999 } } = true', 'tointer': 'select the rows whose score record fuzzily matches to 0-0 . there is only one such row in the table . the attendance record of this unqiue row is 14 february 1999 .'} | and { only { filter_eq { all_rows ; score ; 0-0 } } ; eq { hop { filter_eq { all_rows ; score ; 0-0 } ; attendance } ; 14 february 1999 } } = true | select the rows whose score record fuzzily matches to 0-0 . there is only one such row in the table . the attendance record of this unqiue row is 14 february 1999 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, '0-0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'attendance_9': 9, '14 february 1999_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', '0-0_8': '0-0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'attendance_9': 'attendance', '14 february 1999_10': '14 february 1999'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], '0-0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'attendance_9': [2], '14 february 1999_10': [3]} | ['tie no', 'home team', 'score', 'away team', 'attendance'] | [['1', 'sheffield wednesday', '0 - 1', 'chelsea', '13 february 1999'], ['2', 'everton', '2 - 1', 'coventry city', '13 february 1999'], ['3', 'newcastle united', '0 - 0', 'blackburn rovers', '14 february 1999'], ['replay', 'blackburn rovers', '0 - 1', 'newcastle united', '24 february 1999'], ['4', 'barnsley', '4 - 1', 'bristol rovers', '13 february 1999'], ['5', 'manchester united', '1 - 0', 'fulham', '14 february 1999'], ['6', 'huddersfield town', '2 - 2', 'derby county', '13 february 1999'], ['replay', 'derby county', '3 - 1', 'huddersfield town', '24 february 1999'], ['7', 'arsenal', '2 - 1', 'sheffield united', '13 february 1999'], ['replay', 'arsenal', '2 - 1', 'sheffield united', '23 february 1999'], ['8', 'leeds united', '1 - 1', 'tottenham hotspur', '13 february 1999'], ['replay', 'tottenham hotspur', '2 - 0', 'leeds united', '24 february 1999']] |
swimming at the 2000 summer olympics - women 's 200 metre individual medley | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Women%27s_200_metre_individual_medley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446647-4.html.csv | unique | federica biscia was the only swimmer from italy in the 2000 summer olympics - women 's 200 metre individual medley . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'italy', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; nationality ; italy }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; italy } }', 'tointer': 'select the rows whose nationality record fuzzily matches to italy . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; nationality ; italy }'}, 'name'], 'result': 'federica biscia', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; italy } ; name }'}, 'federica biscia'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; italy } ; name } ; federica biscia }', 'tointer': 'the name record of this unqiue row is federica biscia .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; italy } } ; eq { hop { filter_eq { all_rows ; nationality ; italy } ; name } ; federica biscia } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to italy . there is only one such row in the table . the name record of this unqiue row is federica biscia .'} | and { only { filter_eq { all_rows ; nationality ; italy } } ; eq { hop { filter_eq { all_rows ; nationality ; italy } ; name } ; federica biscia } } = true | select the rows whose nationality record fuzzily matches to italy . there is only one such row in the table . the name record of this unqiue row is federica biscia . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'italy_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'federica biscia_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'italy_8': 'italy', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'federica biscia_10': 'federica biscia'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'italy_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'federica biscia_10': [3]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '4', 'beatrice cäƒslaru', 'romania', '2:13.31'], ['2', '5', 'joanne malar', 'canada', '2:13.59'], ['3', '3', 'marianne limpert', 'canada', '2:13.90'], ['4', '6', 'gabrielle rose', 'united states', '2:14.40'], ['5', '2', 'federica biscia', 'italy', '2:15.71'], ['6', '1', 'elli overton', 'australia', '2:15.74'], ['7', '7', 'yseult gervy', 'belgium', '2:17.19'], ['8', '8', 'sabine herbst', 'germany', '2:17.51']] |
athletics at the 2008 summer olympics - men 's 110 metres hurdles | https://en.wikipedia.org/wiki/Athletics_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_110_metres_hurdles | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18578891-4.html.csv | aggregation | the athletes in the 2008 olympics men 's 110 metres hurdles on average completed the race at around 13.4 seconds . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '13.4', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'time'], 'result': '13.4', 'ind': 0, 'tostr': 'avg { all_rows ; time }'}, '13.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; time } ; 13.4 } = true', 'tointer': 'the average of the time record of all rows is 13.4 .'} | round_eq { avg { all_rows ; time } ; 13.4 } = true | the average of the time record of all rows is 13.4 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'time_4': 4, '13.4_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'time_4': 'time', '13.4_5': '13.4'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'time_4': [0], '13.4_5': [1]} | ['rank', 'lane', 'athlete', 'nationality', 'time', 'notes'] | [['1', '4', 'dayron robles', 'cuba', '13.12', 'q'], ['2', '6', 'david payne', 'united states', '13.21', 'q , sb'], ['3', '5', 'ladji doucourã', 'france', '13.22', 'q , sb'], ['4', '3', 'richard phillips', 'jamaica', '13.43', 'q , sb'], ['5', '2', 'konstadinos douvalidis', 'greece', '13.55', '| | 0.157'], ['6', '8', 'gregory sedoc', 'netherlands', '13.60', '| | 0.162'], ['7', '7', 'petr svoboda', 'czech republic', '13.60', '| | 0.182'], ['8', '9', 'paulo villar', 'colombia', '13.85', '| | 0.153']] |
tri - state collegiate hockey league | https://en.wikipedia.org/wiki/Tri-State_Collegiate_Hockey_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16384648-2.html.csv | majority | most of the teams joined tri - state collegiate hockey league in 2010 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '2010', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'joined tschl', '2010'], 'result': True, 'ind': 0, 'tointer': 'for the joined tschl records of all rows , most of them are equal to 2010 .', 'tostr': 'most_eq { all_rows ; joined tschl ; 2010 } = true'} | most_eq { all_rows ; joined tschl ; 2010 } = true | for the joined tschl records of all rows , most of them are equal to 2010 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'joined tschl_3': 3, '2010_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'joined tschl_3': 'joined tschl', '2010_4': '2010'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'joined tschl_3': [0], '2010_4': [0]} | ['institution', 'location', 'team nickname', 'joined tschl', 'home arena', 'capacity', 'team website'] | [['university of akron', 'akron , oh', 'zips', '2010', 'center ice sports complex', '900', 'zips hockey'], ['university of cincinnati', 'cincinnati , oh', 'bearcats', '2010', 'cincinnati gardens', '10208', 'cincinnati hockey'], ['university of dayton', 'dayton , oh', 'flyers', '2010', 'kettering rec center', '700', 'dayton hockey'], ['indiana university of pennsylvania', 'indiana , pa', 'crimson hawks', '2010', 's & t bank arena', '1000', 'iup hockey'], ['ohio university', 'athens , oh', 'bobcats', '2011', 'bird arena', '2000', 'ohio hockey'], ['university of toledo', 'toledo , oh', 'rockets', '2010', 'team toledo ice house', '1100', 'toledo hockey'], ['university of pittsburgh', 'pittsburgh , pa', 'panthers', '2010', 'bladerunners harmarville', '1200', 'pitt hockey'], ['west virginia university', 'morgantown , wv', 'mountaineers', '2010', 'morgantown municipal ice arena', '500', 'wvu hockey']] |
2007 gran premio tecate | https://en.wikipedia.org/wiki/2007_Gran_Premio_Tecate | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14171191-2.html.csv | majority | most of the drivers who completed 64 laps in the 2007 gran premio tecate were awarded at least 15 points . | {'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '15', 'subset': {'col': '3', 'criterion': 'equal', 'value': '64'}} | {'func': 'most_greater_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '64'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; laps ; 64 }', 'tointer': 'select the rows whose laps record is equal to 64 .'}, 'points', '15'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose laps record is equal to 64 . for the points records of these rows , most of them are greater than or equal to 15 .', 'tostr': 'most_greater_eq { filter_eq { all_rows ; laps ; 64 } ; points ; 15 } = true'} | most_greater_eq { filter_eq { all_rows ; laps ; 64 } ; points ; 15 } = true | select the rows whose laps record is equal to 64 . for the points records of these rows , most of them are greater than or equal to 15 . | 2 | 2 | {'most_greater_eq_1': 1, 'result_2': 2, 'filter_eq_0': 0, 'all_rows_3': 3, 'laps_4': 4, '64_5': 5, 'points_6': 6, '15_7': 7} | {'most_greater_eq_1': 'most_greater_eq', 'result_2': 'true', 'filter_eq_0': 'filter_eq', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '64_5': '64', 'points_6': 'points', '15_7': '15'} | {'most_greater_eq_1': [2], 'result_2': [], 'filter_eq_0': [1], 'all_rows_3': [0], 'laps_4': [0], '64_5': [0], 'points_6': [1], '15_7': [1]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['sébastien bourdais', 'n / h / l racing', '64', '1:45:02.885', '2', '32'], ['will power', 'team australia', '64', '+ 1.906', '1', '29'], ['oriol servià', 'pkv racing', '64', '+ 3.364', '4', '25'], ['graham rahal', 'n / h / l racing', '64', '+ 7.346', '7', '23'], ['paul tracy', 'forsythe racing', '64', '+ 8.593', '8', '21'], ['simon pagenaud', 'team australia', '64', '+ 9.638', '6', '19'], ['bruno junqueira', 'dale coyne racing', '64', '+ 15.823', '12', '17'], ['mario domínguez', 'pacific coast motorsports', '64', '+ 16.077', '15', '16'], ['neel jani', 'pkv racing', '64', '+ 16.199', '11', '13'], ['justin wilson', 'rusport', '64', '+ 16.954', '5', '11'], ['alex figge', 'pacific coast motorsports', '63', '+ 1 lap', '17', '10'], ['nelson philippe', 'conquest racing', '63', '+ 1 lap', '13', '9'], ['alex tagliani', 'rocketsports racing', '62', '+ 2 laps', '14', '8'], ['david martínez', 'forsythe racing', '58', '+ 6 laps', '10', '7'], ['katherine legge', 'dale coyne racing', '56', 'mechanical', '16', '6'], ['robert doornbos', 'minardi team usa', '12', 'mechanical', '3', '6'], ['dan clarke', 'minardi team usa', '0', 'mechanical', '9', '4']] |
1965 - 66 segunda división | https://en.wikipedia.org/wiki/1965%E2%80%9366_Segunda_Divisi%C3%B3n | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17832085-2.html.csv | majority | all clubs in the 1965 - 66 segunda división each played 30 games . | {'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': '30', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'played', '30'], 'result': True, 'ind': 0, 'tointer': 'for the played records of all rows , all of them are equal to 30 .', 'tostr': 'all_eq { all_rows ; played ; 30 } = true'} | all_eq { all_rows ; played ; 30 } = true | for the played records of all rows , all of them are equal to 30 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'played_3': 3, '30_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'played_3': 'played', '30_4': '30'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'played_3': [0], '30_4': [0]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'deportivo de la coruña', '30', '43', '18', '7', '5', '53', '19', '+ 34'], ['2', 'celta de vigo', '30', '39', '17', '5', '8', '54', '28', '+ 26'], ['3', 'real gijón', '30', '36', '15', '6', '9', '67', '50', '+ 17'], ['4', 'real oviedo', '30', '34', '13', '8', '9', '38', '22', '+ 16'], ['5', 'burgos cf', '30', '32', '13', '6', '11', '42', '41', '+ 1'], ['6', 'sd indauchu', '30', '32', '14', '4', '12', '47', '47', '0'], ['7', 'cd condal', '30', '32', '14', '4', '12', '55', '46', '+ 9'], ['8', 'real santander', '30', '31', '11', '9', '10', '38', '40', '- 2'], ['9', 'ca osasuna', '30', '31', '13', '5', '12', '39', '41', '- 2'], ['10', 'real sociedad', '30', '31', '13', '5', '12', '50', '48', '+ 2'], ['11', 'ud lérida', '30', '30', '10', '10', '10', '37', '31', '+ 6'], ['12', 'cf badalona', '30', '30', '13', '4', '13', '32', '41', '- 9'], ['13', 'up langreo', '30', '23', '10', '3', '17', '37', '58', '- 21'], ['14', 'cd europa', '30', '23', '9', '5', '16', '33', '49', '- 16'], ['15', 'cd hospitalet', '30', '19', '9', '1', '20', '37', '63', '- 26'], ['16', 'baracaldo ah', '30', '14', '5', '4', '21', '24', '59', '- 35']] |
list of longest - serving soap opera actors | https://en.wikipedia.org/wiki/List_of_longest-serving_soap_opera_actors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18772558-9.html.csv | ordinal | of the longest serving soap opera actors , the second shortest duration of service is nina soldano . | {'row': '17', 'col': '5', 'order': '2', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'duration', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; duration ; 2 }'}, 'actor'], 'result': 'nina soldano', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; duration ; 2 } ; actor }'}, 'nina soldano'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; duration ; 2 } ; actor } ; nina soldano } = true', 'tointer': 'select the row whose duration record of all rows is 2nd minimum . the actor record of this row is nina soldano .'} | eq { hop { nth_argmin { all_rows ; duration ; 2 } ; actor } ; nina soldano } = true | select the row whose duration record of all rows is 2nd minimum . the actor record of this row is nina soldano . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'duration_5': 5, '2_6': 6, 'actor_7': 7, 'nina soldano_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', 'duration_5': 'duration', '2_6': '2', 'actor_7': 'actor', 'nina soldano_8': 'nina soldano'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'duration_5': [0], '2_6': [0], 'actor_7': [1], 'nina soldano_8': [2]} | ['actor', 'character', 'soap opera', 'years', 'duration'] | [['patrizio rispo', 'raffaele giordano', 'un posto al sole', '1996 -', '18 years'], ['luisa amatucci', 'silvia graziani', 'un posto al sole', '1996 -', '18 years'], ['alberto rossi', 'michele saviani', 'un posto al sole', '1996 -', '18 years'], ['germano bellavia', 'guido del bue', 'un posto al sole', '1996 -', '18 years'], ['marzio honorato', 'renato poggi', 'un posto al sole', '1996 -', '18 years'], ['carmen scivittaro', 'teresa diacono', 'un posto al sole', '1998 -', '16 years'], ['peppe zarbo', 'franco boschi', 'un posto al sole', '1998 -', '16 years'], ['marina tagliaferri', 'giulia poggi', 'un posto al sole', '1996 - 2008 , 2011 -', '15 years'], ['claudia ruffo', 'angela poggi', 'un posto al sole', '1996 - 2007 , 2010 -', '15 years'], ['luca turco', 'niko poggi', 'un posto al sole', '1999 -', '15 years'], ['ilenia lazzarin', 'viola bruni', 'un posto al sole', '2001 -', '13 years'], ['marina giulia cavalli', 'ornella bruni', 'un posto al sole', '2001 -', '13 years'], ['riccardo polizzy carbonelli', 'roberto ferri', 'un posto al sole', '2001 -', '13 years'], ['elisabetta coraini', 'laura beccaria', 'centovetrine', '2001 -', '13 years'], ['pietro genuardi', 'ivan bettini', 'centovetrine', '2001 -', '13 years'], ['sergio troiano', 'valerio bettini', 'centovetrine', '2001 -', '13 years'], ['nina soldano', 'marina giordano', 'un posto al sole', '2003 -', '11 years'], ['delia boccardo', 'tilly nardi', 'incantesimo', '1998 - 2008', '10 years']] |
radiopharmacology | https://en.wikipedia.org/wiki/Radiopharmacology | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1035507-12.html.csv | majority | in radiopharmacology , the route of administration of all somatostatin receptor imaging investigation is iv . | {'scope': 'subset', 'col': '3', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'iv', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'somatostatin receptor imaging'}} | {'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'investigation', 'somatostatin receptor imaging'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; investigation ; somatostatin receptor imaging }', 'tointer': 'select the rows whose investigation record fuzzily matches to somatostatin receptor imaging .'}, 'route of administration', 'iv'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose investigation record fuzzily matches to somatostatin receptor imaging . for the route of administration records of these rows , all of them fuzzily match to iv .', 'tostr': 'all_eq { filter_eq { all_rows ; investigation ; somatostatin receptor imaging } ; route of administration ; iv } = true'} | all_eq { filter_eq { all_rows ; investigation ; somatostatin receptor imaging } ; route of administration ; iv } = true | select the rows whose investigation record fuzzily matches to somatostatin receptor imaging . for the route of administration records of these rows , all of them fuzzily match to iv . | 2 | 2 | {'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'investigation_4': 4, 'somatostatin receptor imaging_5': 5, 'route of administration_6': 6, 'iv_7': 7} | {'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'investigation_4': 'investigation', 'somatostatin receptor imaging_5': 'somatostatin receptor imaging', 'route of administration_6': 'route of administration', 'iv_7': 'iv'} | {'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'investigation_4': [0], 'somatostatin receptor imaging_5': [0], 'route of administration_6': [1], 'iv_7': [1]} | ['name', 'investigation', 'route of administration', 'in - vitro / in - vivo', 'imaging / non - imaging'] | [['in111 - dtpa ( diethylenetriaminepenta - acetic acid )', 'ventriculo - peritoneal shunt ( laveen shunt )', 'intraperitoneal injection', 'in - vivo', 'imaging'], ['in111 - dtpa ( diethylenetriaminepenta - acetic acid )', 'cisternography', 'intra - cisternal', 'in - vivo', 'imaging'], ['in111 - s leukocyte', 'infection / inflammation imaging', 'iv', 'in - vivo', 'imaging'], ['in111 - s platelet', 'thrombus imaging', 'iv', 'in - vivo', 'imaging'], ['in111 - pentetreotide', 'somatostatin receptor imaging', 'iv', 'in - vivo', 'imaging'], ['in111 - octreotide', 'somatostatin receptor imaging ( octreoscan )', 'iv', 'in - vivo', 'imaging']] |
1992 washington redskins season | https://en.wikipedia.org/wiki/1992_Washington_Redskins_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14610267-2.html.csv | majority | in the 1992 washington redskins season , most of the games on october had an attendance of more than 50000 . | {'scope': 'subset', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '50000', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'october'}} | {'func': 'most_greater', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; october }', 'tointer': 'select the rows whose date record fuzzily matches to october .'}, 'attendance', '50000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to october . for the attendance records of these rows , most of them are greater than 50000 .', 'tostr': 'most_greater { filter_eq { all_rows ; date ; october } ; attendance ; 50000 } = true'} | most_greater { filter_eq { all_rows ; date ; october } ; attendance ; 50000 } = true | select the rows whose date record fuzzily matches to october . for the attendance records of these rows , most of them are greater than 50000 . | 2 | 2 | {'most_greater_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'date_4': 4, 'october_5': 5, 'attendance_6': 6, '50000_7': 7} | {'most_greater_1': 'most_greater', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'date_4': 'date', 'october_5': 'october', 'attendance_6': 'attendance', '50000_7': '50000'} | {'most_greater_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'date_4': [0], 'october_5': [0], 'attendance_6': [1], '50000_7': [1]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 7 , 1992', 'dallas cowboys', 'l 10 - 23', '63538'], ['2', 'september 13 , 1992', 'atlanta falcons', 'w 24 - 17', '54343'], ['3', 'september 20 , 1992', 'detroit lions', 'w 13 - 10', '55818'], ['5', 'october 4 , 1992', 'phoenix cardinals', 'l 24 - 27', '34488'], ['6', 'october 12 , 1992', 'denver broncos', 'w 34 - 3', '56371'], ['7', 'october 18 , 1992', 'philadelphia eagles', 'w 16 - 12', '56380'], ['8', 'october 25 , 1992', 'minnesota vikings', 'w 15 - 13', '59098'], ['9', 'november 1 , 1992', 'new york giants', 'l 7 - 24', '53647'], ['10', 'november 8 , 1992', 'seattle seahawks', 'w 16 - 3', '53616'], ['11', 'november 15 , 1992', 'kansas city chiefs', 'l 16 - 35', '75238'], ['12', 'november 23 , 1992', 'new orleans saints', 'l 3 - 20', '68591'], ['13', 'november 29 , 1992', 'phoenix cardinals', 'w 41 - 3', '53541'], ['14', 'december 6 , 1992', 'new york giants', 'w 28 - 10', '62998'], ['15', 'december 13 , 1992', 'dallas cowboys', 'w 20 - 17', '56437'], ['16', 'december 20 , 1992', 'philadelphia eagles', 'l 13 - 17', '65841'], ['17', 'december 26 , 1992', 'los angeles raiders', 'l 20 - 21', '53032']] |
doppler spectroscopy | https://en.wikipedia.org/wiki/Doppler_spectroscopy | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10932739-2.html.csv | unique | neptune is the only ice giant planet that was detected by doppler spectroscopy . | {'scope': 'all', 'row': '7', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'ice giant', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'planet type', 'ice giant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose planet type record fuzzily matches to ice giant .', 'tostr': 'filter_eq { all_rows ; planet type ; ice giant }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; planet type ; ice giant } }', 'tointer': 'select the rows whose planet type record fuzzily matches to ice giant . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'planet type', 'ice giant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose planet type record fuzzily matches to ice giant .', 'tostr': 'filter_eq { all_rows ; planet type ; ice giant }'}, 'planet'], 'result': 'neptune', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; planet type ; ice giant } ; planet }'}, 'neptune'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; planet type ; ice giant } ; planet } ; neptune }', 'tointer': 'the planet record of this unqiue row is neptune .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; planet type ; ice giant } } ; eq { hop { filter_eq { all_rows ; planet type ; ice giant } ; planet } ; neptune } } = true', 'tointer': 'select the rows whose planet type record fuzzily matches to ice giant . there is only one such row in the table . the planet record of this unqiue row is neptune .'} | and { only { filter_eq { all_rows ; planet type ; ice giant } } ; eq { hop { filter_eq { all_rows ; planet type ; ice giant } ; planet } ; neptune } } = true | select the rows whose planet type record fuzzily matches to ice giant . there is only one such row in the table . the planet record of this unqiue row is neptune . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'planet type_7': 7, 'ice giant_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'planet_9': 9, 'neptune_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'planet type_7': 'planet type', 'ice giant_8': 'ice giant', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'planet_9': 'planet', 'neptune_10': 'neptune'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'planet type_7': [0], 'ice giant_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'planet_9': [2], 'neptune_10': [3]} | ['planet', 'planet type', 'semimajor axis ( au )', 'orbital period', 'radial velocity ( m / s )', 'detectable by :'] | [['51 pegasi b', 'hot jupiter', '0.05', '4.23 days', '55.9', 'first - generation spectrograph'], ['55 cancri d', 'gas giant', '5.77', '14.29 years', '45.2', 'first - generation spectrograph'], ['jupiter', 'gas giant', '5.20', '11.86 years', '12.4', 'first - generation spectrograph'], ['gliese 581c', 'super - earth', '0.07', '12.92 days', '3.18', 'second - generation spectrograph'], ['saturn', 'gas giant', '9.58', '29.46 years', '2.75', 'second - generation spectrograph'], ['alpha centauri bb', 'terrestrial planet', '0.04', '3.23 days', '0.510', 'second - generation spectrograph'], ['neptune', 'ice giant', '30.10', '164.79 years', '0.281', 'third - generation spectrograph'], ['earth', 'habitable planet', '1.00', '365.26 days', '0.089', 'third - generation spectrograph ( likely )'], ['pluto', 'dwarf planet', '39.26', '246.04 years', '0.00003', 'not detectable']] |
arantxa rus | https://en.wikipedia.org/wiki/Arantxa_Rus | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18586543-6.html.csv | comparative | through october 2013 , arantxa rus was more successful in doubles matches played on hard surfaces than on clay surfaces . | {'row_1': '1', 'row_2': '3', 'col': '7', 'col_other': '4', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'hard'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to hard .', 'tostr': 'filter_eq { all_rows ; surface ; hard }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; surface ; hard } ; score }', 'tointer': 'select the rows whose surface record fuzzily matches to hard . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'clay'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to clay .', 'tostr': 'filter_eq { all_rows ; surface ; clay }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; surface ; clay } ; score }', 'tointer': 'select the rows whose surface record fuzzily matches to clay . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; surface ; hard } ; score } ; hop { filter_eq { all_rows ; surface ; clay } ; score } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to hard . take the score record of this row . select the rows whose surface record fuzzily matches to clay . take the score record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; surface ; hard } ; score } ; hop { filter_eq { all_rows ; surface ; clay } ; score } } = true | select the rows whose surface record fuzzily matches to hard . take the score record of this row . select the rows whose surface record fuzzily matches to clay . 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, 'surface_7': 7, 'hard_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'surface_11': 11, 'clay_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', 'surface_7': 'surface', 'hard_8': 'hard', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'surface_11': 'surface', 'clay_12': 'clay', 'score_13': 'score'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'surface_7': [0], 'hard_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'surface_11': [1], 'clay_12': [1], 'score_13': [3]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents', 'score'] | [['winner', '27 . october 2007', 'mexico city', 'hard', 'nicole thijssen', 'ivana abramović maria abramović', '6 - 0 , 6 - 1'], ['runner - up', '19 november 2008', 'opole', 'carpet', 'katarzyna piter', 'karolina kosińska aleksandra rosolska', '6 - 2 , 6 - 7 ( 6 ) ,'], ['runner - up', '31 may 2010', 'rome', 'clay', 'iryna bremond', 'christina mchale olivia rogowska', '4 - 6 , 1 - 6'], ['winner', '11 . february 2011', 'stockholm', 'hard ( i )', 'anastasiya yakimova', 'claire feuerstein ksenia lykina', '6 - 3 , 2 - 6 ,'], ['winner', '12 . may 2013', 'cagnes - sur - mer', 'clay', 'vania king', 'catalina castaño teliana pereira', '4 - 6 , 7 - 5 ,'], ['runner - up', '6 october 2013', 'vallduxo', 'clay', 'cindy burger', 'florencia molinero laura thorpe', '1 - 6 , 4 - 6']] |
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/1-1342013-42.html.csv | count | 17 of the candidates who ran in the 1954 u.s. house of representatives elections in texas were unopposed . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'unopposed', 'result': '17', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'candidates', 'unopposed'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed .', 'tostr': 'filter_eq { all_rows ; candidates ; unopposed }'}], 'result': '17', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; candidates ; unopposed } }', 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed . the number of such rows is 17 .'}, '17'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; candidates ; unopposed } } ; 17 } = true', 'tointer': 'select the rows whose candidates record fuzzily matches to unopposed . the number of such rows is 17 .'} | eq { count { filter_eq { all_rows ; candidates ; unopposed } } ; 17 } = true | select the rows whose candidates record fuzzily matches to unopposed . the number of such rows is 17 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'candidates_5': 5, 'unopposed_6': 6, '17_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'candidates_5': 'candidates', 'unopposed_6': 'unopposed', '17_7': '17'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'candidates_5': [0], 'unopposed_6': [0], '17_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['texas 1', 'wright patman', 'democratic', '1928', 're - elected', 'wright patman ( d ) unopposed'], ['texas 2', 'jack brooks', 'democratic', '1952', 're - elected', 'jack brooks ( d ) unopposed'], ['texas 3', 'brady p gentry', 'democratic', '1952', 're - elected', 'brady p gentry ( d ) unopposed'], ['texas 4', 'sam rayburn', 'democratic', '1912', 're - elected', 'sam rayburn ( d ) unopposed'], ['texas 5', 'joseph franklin wilson', 'democratic', '1946', 'retired republican gain', 'bruce r alger ( r ) 52.9 % wallace savage ( d ) 47.1 %'], ['texas 6', 'olin e teague', 'democratic', '1946', 're - elected', 'olin e teague ( d ) unopposed'], ['texas 7', 'john dowdy', 'democratic', '1952', 're - elected', 'john dowdy ( d ) unopposed'], ['texas 9', 'clark w thompson', 'democratic', '1947', 're - elected', 'clark w thompson ( d ) unopposed'], ['texas 10', 'homer thornberry', 'democratic', '1948', 're - elected', 'homer thornberry ( d ) unopposed'], ['texas 11', 'william r poage', 'democratic', '1936', 're - elected', 'william r poage ( d ) unopposed'], ['texas 12', 'wingate h lucas', 'democratic', '1946', 'lost renomination democratic hold', 'jim wright ( d ) unopposed'], ['texas 13', 'frank n ikard', 'democratic', '1951', 're - elected', 'frank n ikard ( d ) unopposed'], ['texas 14', 'john e lyle , jr', 'democratic', '1944', 'retired democratic hold', 'john j bell ( d ) 93.8 % d c dewitt ( r ) 6.2 %'], ['texas 15', 'lloyd bentsen', 'democratic', '1948', 'retired democratic hold', 'joe m kilgore ( d ) unopposed'], ['texas 16', 'kenneth m regan', 'democratic', '1947', 'lost renomination democratic hold', 'j t rutherford ( d ) unopposed'], ['texas 17', 'omar burleson', 'democratic', '1946', 're - elected', 'omar burleson ( d ) unopposed'], ['texas 19', 'george h mahon', 'democratic', '1934', 're - elected', 'george h mahon ( d ) unopposed'], ['texas 20', 'paul j kilday', 'democratic', '1938', 're - elected', 'paul j kilday ( d ) unopposed'], ['texas 21', 'o c fisher', 'democratic', '1942', 're - elected', 'o c fisher ( d ) unopposed']] |
list of teachers ( uk tv series ) episodes | https://en.wikipedia.org/wiki/List_of_Teachers_%28UK_TV_series%29_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18335117-5.html.csv | unique | for the uk tv series teachers , the only episode that was written by ed roe , had production code 402 . | {'scope': 'all', 'row': '2', 'col': '5', 'col_other': '7', 'criterion': 'equal', 'value': 'ed roe', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'writer', 'ed roe'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose writer record fuzzily matches to ed roe .', 'tostr': 'filter_eq { all_rows ; writer ; ed roe }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; writer ; ed roe } }', 'tointer': 'select the rows whose writer record fuzzily matches to ed roe . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'writer', 'ed roe'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose writer record fuzzily matches to ed roe .', 'tostr': 'filter_eq { all_rows ; writer ; ed roe }'}, 'production code'], 'result': '402', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; writer ; ed roe } ; production code }'}, '402'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; writer ; ed roe } ; production code } ; 402 }', 'tointer': 'the production code record of this unqiue row is 402 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; writer ; ed roe } } ; eq { hop { filter_eq { all_rows ; writer ; ed roe } ; production code } ; 402 } } = true', 'tointer': 'select the rows whose writer record fuzzily matches to ed roe . there is only one such row in the table . the production code record of this unqiue row is 402 .'} | and { only { filter_eq { all_rows ; writer ; ed roe } } ; eq { hop { filter_eq { all_rows ; writer ; ed roe } ; production code } ; 402 } } = true | select the rows whose writer record fuzzily matches to ed roe . there is only one such row in the table . the production code record of this unqiue row is 402 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'writer_7': 7, 'ed roe_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'production code_9': 9, '402_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'writer_7': 'writer', 'ed roe_8': 'ed roe', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'production code_9': 'production code', '402_10': '402'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'writer_7': [0], 'ed roe_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'production code_9': [2], '402_10': [3]} | ['no overall', 'no in series', 'title', 'director', 'writer', 'original air date', 'production code'] | [['32', '1', 'episode 1', 'barnaby southcomb', 'richard stoneman', '26 october 2004', '401'], ['33', '2', 'episode 2', 'barnaby southcomb', 'ed roe', '3 november 2004', '402'], ['34', '3', 'episode 3', 'barnaby southcomb', 'charlie martin', '10 november 2004', '403'], ['35', '4', 'episode 4', 'sean grundy', 'linton chiswick', '17 november 2004', '404'], ['36', '5', 'episode 5', 'sean grundy', 'jack lothian', '24 november 2004', '405'], ['37', '6', 'episode 6', 'sean grundy', 'tony basgallop', '1 december 2004', '406'], ['38', '7', 'episode 7', 'iain b macdonald', 'charlie martin', '8 december 2004', '407'], ['39', '8', 'episode 8', 'iain b macdonald', 'richard stoneman', '15 december 2004', '408']] |
wgrc | https://en.wikipedia.org/wiki/WGRC | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10317840-1.html.csv | count | 3 of the call signs for wgrc have a frequency mhz of over 100 . | {'scope': 'all', 'criterion': 'greater_than', 'value': '100', 'result': '3', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'frequency mhz', '100'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose frequency mhz record is greater than 100 .', 'tostr': 'filter_greater { all_rows ; frequency mhz ; 100 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; frequency mhz ; 100 } }', 'tointer': 'select the rows whose frequency mhz record is greater than 100 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; frequency mhz ; 100 } } ; 3 } = true', 'tointer': 'select the rows whose frequency mhz record is greater than 100 . the number of such rows is 3 .'} | eq { count { filter_greater { all_rows ; frequency mhz ; 100 } } ; 3 } = true | select the rows whose frequency mhz record is greater than 100 . the number of such rows is 3 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'frequency mhz_5': 5, '100_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'frequency mhz_5': 'frequency mhz', '100_6': '100', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'frequency mhz_5': [0], '100_6': [0], '3_7': [2]} | ['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info'] | [['wcrg', '90.7', 'williamsport , pennsylvania', '3000', 'a', 'fcc'], ['wjrc', '90.9', 'lewistown , pennsylvania', '94', 'a', 'fcc'], ['wzrg', '91.9', 'kulpmont , pennsylvania', '1450', 'a', 'fcc'], ['w269bz', '101.7', 'state college , pennsylvania', '4', 'd', 'fcc'], ['w296ap', '107.1', 'williamsport , pennsylvania', '5', 'd', 'fcc'], ['w299af', '107.7', 'catawissa , pennsylvania', '1', 'd', 'fcc']] |
satpura thermal power station | https://en.wikipedia.org/wiki/Satpura_Thermal_Power_Station | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28672269-1.html.csv | superlative | unit number 8 was the last unit commissioned at the satpura thermal power station . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'date of commissioning'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; date of commissioning }'}, 'unit number'], 'result': '8', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; date of commissioning } ; unit number }'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; date of commissioning } ; unit number } ; 8 } = true', 'tointer': 'select the row whose date of commissioning record of all rows is maximum . the unit number record of this row is 8 .'} | eq { hop { argmax { all_rows ; date of commissioning } ; unit number } ; 8 } = true | select the row whose date of commissioning record of all rows is maximum . the unit number record of this row is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'date of commissioning_5': 5, 'unit number_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'date of commissioning_5': 'date of commissioning', 'unit number_6': 'unit number', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'date of commissioning_5': [0], 'unit number_6': [1], '8_7': [2]} | ['stage', 'unit number', 'installed capacity ( mw )', 'date of commissioning', 'status', 'tg set provider', 'boiler provider'] | [['first', '1', '62.5', 'october , 1967', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '2', '62.5', 'march , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '3', '62.5', 'may , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '4', '62.5', 'july , 1968', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['first', '5', '62.5', 'april , 1970', 'running', 'ge , usa', 'the babcock & wilcox company ( b & w ) , usa'], ['second', '6', '200', 'july , 1979', 'running', 'bhel , india', 'bhel , india'], ['second', '7', '210', 'september , 1980', 'running', 'bhel , india', 'bhel , india'], ['second', '8', '210', 'january , 1983', 'running', 'bhel , india', 'bhel , india']] |
1989 buffalo bills season | https://en.wikipedia.org/wiki/1989_Buffalo_Bills_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16028499-2.html.csv | superlative | in the 1989 buffalo bills season , their first game against indianapolis colts occurred at hoosier dome . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '3,6', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'indianapolis colts'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'indianapolis colts'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; indianapolis colts }', 'tointer': 'select the rows whose opponent record fuzzily matches to indianapolis colts .'}, 'date'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; opponent ; indianapolis colts } ; date }'}, 'game site'], 'result': 'hoosier dome', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; opponent ; indianapolis colts } ; date } ; game site }'}, 'hoosier dome'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; opponent ; indianapolis colts } ; date } ; game site } ; hoosier dome } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to indianapolis colts . select the row whose date record of these rows is minimum . the game site record of this row is hoosier dome .'} | eq { hop { argmin { filter_eq { all_rows ; opponent ; indianapolis colts } ; date } ; game site } ; hoosier dome } = true | select the rows whose opponent record fuzzily matches to indianapolis colts . select the row whose date record of these rows is minimum . the game site record of this row is hoosier dome . | 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, 'opponent_6': 6, 'indianapolis colts_7': 7, 'date_8': 8, 'game site_9': 9, 'hoosier dome_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', 'opponent_6': 'opponent', 'indianapolis colts_7': 'indianapolis colts', 'date_8': 'date', 'game site_9': 'game site', 'hoosier dome_10': 'hoosier dome'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'opponent_6': [0], 'indianapolis colts_7': [0], 'date_8': [1], 'game site_9': [2], 'hoosier dome_10': [3]} | ['week', 'date', 'opponent', 'result', 'record', 'game site', 'attendance'] | [['1', 'september 10 , 1989', 'miami dolphins', 'w 27 - 24', '1 - 0', 'joe robbie stadium', '54541'], ['2', 'september 18 , 1989', 'denver broncos', 'l 14 - 28', '1 - 1', 'rich stadium', '78176'], ['3', 'september 24 , 1989', 'houston oilers', 'w 47 - 41', '2 - 1', 'houston astrodome', '57278'], ['4', 'october 1 , 1989', 'new england patriots', 'w 31 - 10', '3 - 1', 'rich stadium', '78921'], ['5', 'october 8 , 1989', 'indianapolis colts', 'l 14 - 37', '3 - 2', 'hoosier dome', '58890'], ['6', 'october 16 , 1989', 'los angeles rams', 'w 23 - 20', '4 - 2', 'rich stadium', '76231'], ['7', 'october 22 , 1989', 'new york jets', 'w 34 - 3', '5 - 2', 'rich stadium', '76811'], ['8', 'october 29 , 1989', 'miami dolphins', 'w 31 - 17', '6 - 2', 'rich stadium', '80208'], ['9', 'november 5 , 1989', 'atlanta falcons', 'l 28 - 30', '6 - 3', 'atlanta - fulton county stadium', '45267'], ['10', 'november 12 , 1989', 'indianapolis colts', 'w 30 - 7', '7 - 3', 'rich stadium', '79256'], ['11', 'november 19 , 1989', 'new england patriots', 'l 24 - 33', '7 - 4', 'sullivan stadium', '49663'], ['12', 'november 26 , 1989', 'cincinnati bengals', 'w 24 - 7', '8 - 4', 'rich stadium', '80074'], ['13', 'december 4 , 1989', 'seattle seahawks', 'l 16 - 17', '8 - 5', 'kingdome', '57682'], ['14', 'december 10 , 1989', 'new orleans saints', 'l 19 - 22', '8 - 6', 'rich stadium', '70037'], ['15', 'december 17 , 1989', 'san francisco 49ers', 'l 10 - 21', '8 - 7', 'candlestick park', '60927'], ['16', 'december 23 , 1989', 'new york jets', 'w 37 - 0', '9 - 7', 'the meadowlands', '21148']] |
swimming at the 2000 summer olympics - women 's 200 metre individual medley | https://en.wikipedia.org/wiki/Swimming_at_the_2000_Summer_Olympics_%E2%80%93_Women%27s_200_metre_individual_medley | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12446647-5.html.csv | majority | the majority of swimmers finished with a time in the 2:15 range . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': '2:15 .', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'time', '2:15 .'], 'result': True, 'ind': 0, 'tointer': 'for the time records of all rows , most of them fuzzily match to 2:15 . .', 'tostr': 'most_eq { all_rows ; time ; 2:15 . } = true'} | most_eq { all_rows ; time ; 2:15 . } = true | for the time records of all rows , most of them fuzzily match to 2:15 . . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'time_3': 3, '2:15._4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'time_3': 'time', '2:15._4': '2:15 .'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'time_3': [0], '2:15._4': [0]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '5', 'yana klochkova', 'ukraine', '2:13.08'], ['2', '3', 'cristina teuscher', 'united states', '2:13.47'], ['3', '4', 'oxana verevka', 'russia', '2:14.04'], ['4', '6', 'tomoko hagiwara', 'japan', '2:15.09'], ['5', '2', 'chen yan', 'china', '2:15.27'], ['6', '7', 'sue rolph', 'great britain', '2:15.98'], ['7', '1', 'zhan shu', 'china', '2:16.58'], ['8', '8', 'nicole hetzer', 'germany', '2:18.08']] |
savannah braves | https://en.wikipedia.org/wiki/Savannah_Braves | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18893381-2.html.csv | unique | in 1978 , the savannah braves made it as far as the league finals . | {'scope': 'all', 'row': '8', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'league finals', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'playoffs', 'league finals'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose playoffs record fuzzily matches to league finals .', 'tostr': 'filter_eq { all_rows ; playoffs ; league finals }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; playoffs ; league finals } }', 'tointer': 'select the rows whose playoffs record fuzzily matches to league finals . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'playoffs', 'league finals'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose playoffs record fuzzily matches to league finals .', 'tostr': 'filter_eq { all_rows ; playoffs ; league finals }'}, 'year'], 'result': '1978', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; playoffs ; league finals } ; year }'}, '1978'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; playoffs ; league finals } ; year } ; 1978 }', 'tointer': 'the year record of this unqiue row is 1978 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; playoffs ; league finals } } ; eq { hop { filter_eq { all_rows ; playoffs ; league finals } ; year } ; 1978 } } = true', 'tointer': 'select the rows whose playoffs record fuzzily matches to league finals . there is only one such row in the table . the year record of this unqiue row is 1978 .'} | and { only { filter_eq { all_rows ; playoffs ; league finals } } ; eq { hop { filter_eq { all_rows ; playoffs ; league finals } ; year } ; 1978 } } = true | select the rows whose playoffs record fuzzily matches to league finals . there is only one such row in the table . the year record of this unqiue row is 1978 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'playoffs_7': 7, 'league finals_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1978_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'playoffs_7': 'playoffs', 'league finals_8': 'league finals', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1978_10': '1978'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'playoffs_7': [0], 'league finals_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1978_10': [3]} | ['year', 'record', 'finish', 'manager', 'playoffs'] | [['1971', '57 - 84', '5th', 'eddie haas', 'not eligible'], ['1972', '80 - 59', '2nd', 'clint courtney', 'not eligible'], ['1973', '71 - 68', '3rd', 'clint courtney ( 34 - 23 ) / tommie aaron ( 37 - 45 )', 'not eligible'], ['1974', '73 - 65', '4th', 'tommie aaron', 'not eligible'], ['1975', '70 - 64', '3rd ( t )', 'tommie aaron', 'not eligible'], ['1976', '69 - 71', '5th', 'tommie aaron', 'not eligible'], ['1977', '77 - 63', '3rd', 'gene hassell', 'lost in 1st round'], ['1978', '72 - 72', '4th', 'bobby dews', 'lost league finals'], ['1979', '60 - 83', '10th', 'eddie haas', 'not eligible'], ['1980', '77 - 67', '3rd', 'eddie haas', 'lost in 1st round'], ['1981', '70 - 70', '5th', 'andy gilbert', 'lost in 1st round'], ['1982', '69 - 75', '8th', 'andy gilbert', 'not eligible'], ['1983', '81 - 64', '3rd', 'bobby dews', 'lost in 1st round']] |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-18.html.csv | superlative | in the 1941vfl season , the highest attendance at western oval was 7,000 . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'western oval'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'western oval'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; western oval }', 'tointer': 'select the rows whose venue record fuzzily matches to western oval .'}, 'crowd'], 'result': '7000', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; venue ; western oval } ; crowd }', 'tointer': 'select the rows whose venue record fuzzily matches to western oval . the maximum crowd record of these rows is 7000 .'}, '7000'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; venue ; western oval } ; crowd } ; 7000 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to western oval . the maximum crowd record of these rows is 7000 .'} | eq { max { filter_eq { all_rows ; venue ; western oval } ; crowd } ; 7000 } = true | select the rows whose venue record fuzzily matches to western oval . the maximum crowd record of these rows is 7000 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'western oval_6': 6, 'crowd_7': 7, '7000_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'western oval_6': 'western oval', 'crowd_7': 'crowd', '7000_8': '7000'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'western oval_6': [0], 'crowd_7': [1], '7000_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '16.14 ( 110 )', 'st kilda', '13.17 ( 95 )', 'western oval', '7000', '30 august 1941'], ['carlton', '16.17 ( 113 )', 'melbourne', '11.22 ( 88 )', 'princes park', '29000', '30 august 1941'], ['south melbourne', '7.12 ( 54 )', 'hawthorn', '11.17 ( 83 )', 'lake oval', '3000', '30 august 1941'], ['richmond', '20.12 ( 132 )', 'geelong', '12.11 ( 83 )', 'punt road oval', '9000', '30 august 1941'], ['fitzroy', '15.16 ( 106 )', 'essendon', '18.14 ( 122 )', 'brunswick street oval', '11000', '30 august 1941'], ['north melbourne', '12.8 ( 80 )', 'collingwood', '13.20 ( 98 )', 'arden street oval', '5000', '30 august 1941']] |
tomina province | https://en.wikipedia.org/wiki/Tomina_Province | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2509350-3.html.csv | unique | padilla is the only municipality with more than 10000 spanish speakers . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'greater_than', 'value': '10000', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'padilla municipality', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose padilla municipality record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; padilla municipality ; 10000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; padilla municipality ; 10000 } }', 'tointer': 'select the rows whose padilla municipality record is greater than 10000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'padilla municipality', '10000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose padilla municipality record is greater than 10000 .', 'tostr': 'filter_greater { all_rows ; padilla municipality ; 10000 }'}, 'language'], 'result': 'spanish', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; padilla municipality ; 10000 } ; language }'}, 'spanish'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; padilla municipality ; 10000 } ; language } ; spanish }', 'tointer': 'the language record of this unqiue row is spanish .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_greater { all_rows ; padilla municipality ; 10000 } } ; eq { hop { filter_greater { all_rows ; padilla municipality ; 10000 } ; language } ; spanish } } = true', 'tointer': 'select the rows whose padilla municipality record is greater than 10000 . there is only one such row in the table . the language record of this unqiue row is spanish .'} | and { only { filter_greater { all_rows ; padilla municipality ; 10000 } } ; eq { hop { filter_greater { all_rows ; padilla municipality ; 10000 } ; language } ; spanish } } = true | select the rows whose padilla municipality record is greater than 10000 . there is only one such row in the table . the language record of this unqiue row is spanish . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_6': 6, 'padilla municipality_7': 7, '10000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'language_9': 9, 'spanish_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_6': 'all_rows', 'padilla municipality_7': 'padilla municipality', '10000_8': '10000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'language_9': 'language', 'spanish_10': 'spanish'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_greater_0': [1, 2], 'all_rows_6': [0], 'padilla municipality_7': [0], '10000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'language_9': [2], 'spanish_10': [3]} | ['language', 'padilla municipality', 'tomina municipality', 'sopachuy municipality', 'villa alcalá municipality', 'el villar municipality'] | [['quechua', '2181', '7831', '6261', '1167', '1264'], ['aymara', '29', '23', '10', '7', '15'], ['guaraní', '6', '4', '3', '3', '1'], ['another native', '2', '2', '3', '1', '0'], ['spanish', '11585', '4418', '3003', '3576', '4190'], ['foreign', '27', '12', '9', '9', '4'], ['only native', '250', '4036', '3791', '176', '146'], ['native and spanish', '1951', '3803', '2478', '997', '1123']] |
2006 pga championship | https://en.wikipedia.org/wiki/2006_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12475284-6.html.csv | ordinal | geoff ogilvy had the fourth lowest total score in the 2006 pga tournament . | {'row': '4', 'col': '4', 'order': '4', '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', 'score', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; score ; 4 }'}, 'player'], 'result': 'geoff ogilvy', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; score ; 4 } ; player }'}, 'geoff ogilvy'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; score ; 4 } ; player } ; geoff ogilvy } = true', 'tointer': 'select the row whose score record of all rows is 4th minimum . the player record of this row is geoff ogilvy .'} | eq { hop { nth_argmin { all_rows ; score ; 4 } ; player } ; geoff ogilvy } = true | select the row whose score record of all rows is 4th minimum . the player record of this row is geoff ogilvy . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'score_5': 5, '4_6': 6, 'player_7': 7, 'geoff ogilvy_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', 'score_5': 'score', '4_6': '4', 'player_7': 'player', 'geoff ogilvy_8': 'geoff ogilvy'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'score_5': [0], '4_6': [0], 'player_7': [1], 'geoff ogilvy_8': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'tiger woods', 'united states', '69 + 68 + 65 = 202', '- 14'], ['t1', 'luke donald', 'england', '68 + 68 + 66 = 202', '- 14'], ['3', 'mike weir', 'canada', '72 + 67 + 65 = 204', '- 12'], ['4', 'geoff ogilvy', 'australia', '69 + 68 + 68 = 205', '- 11'], ['t5', 'shaun micheel', 'united states', '69 + 70 + 67 = 206', '- 10'], ['t5', 'sergio garcía', 'spain', '69 + 70 + 67 = 206', '- 10'], ['7', 'k j choi', 'south korea', '73 + 67 + 67 = 207', '- 9'], ['t8', 'chris dimarco', 'united states', '71 + 70 + 67 = 208', '- 8'], ['t8', 'tim herron', 'united states', '69 + 67 + 72 = 208', '- 8'], ['t8', 'phil mickelson', 'united states', '69 + 71 + 68 = 208', '- 8'], ['t8', 'ian poulter', 'england', '70 + 70 + 68 = 208', '- 8']] |
2008 italian motorcycle grand prix | https://en.wikipedia.org/wiki/2008_Italian_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16212245-1.html.csv | comparative | in the 2008 italian motorcycle grand prix , john hopkins completed more laps than marco melandri . | {'row_1': '17', 'row_2': '19', 'col': '3', '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', 'rider', 'john hopkins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rider record fuzzily matches to john hopkins .', 'tostr': 'filter_eq { all_rows ; rider ; john hopkins }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; rider ; john hopkins } ; laps }', 'tointer': 'select the rows whose rider record fuzzily matches to john hopkins . take the laps record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'rider', 'marco melandri'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose rider record fuzzily matches to marco melandri .', 'tostr': 'filter_eq { all_rows ; rider ; marco melandri }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; rider ; marco melandri } ; laps }', 'tointer': 'select the rows whose rider record fuzzily matches to marco melandri . take the laps record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; rider ; john hopkins } ; laps } ; hop { filter_eq { all_rows ; rider ; marco melandri } ; laps } } = true', 'tointer': 'select the rows whose rider record fuzzily matches to john hopkins . take the laps record of this row . select the rows whose rider record fuzzily matches to marco melandri . take the laps record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; rider ; john hopkins } ; laps } ; hop { filter_eq { all_rows ; rider ; marco melandri } ; laps } } = true | select the rows whose rider record fuzzily matches to john hopkins . take the laps record of this row . select the rows whose rider record fuzzily matches to marco melandri . take the laps 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, 'rider_7': 7, 'john hopkins_8': 8, 'laps_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'rider_11': 11, 'marco melandri_12': 12, 'laps_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', 'rider_7': 'rider', 'john hopkins_8': 'john hopkins', 'laps_9': 'laps', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'rider_11': 'rider', 'marco melandri_12': 'marco melandri', 'laps_13': 'laps'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'rider_7': [0], 'john hopkins_8': [0], 'laps_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'rider_11': [1], 'marco melandri_12': [1], 'laps_13': [3]} | ['rider', 'manufacturer', 'laps', 'time', 'grid'] | [['valentino rossi', 'yamaha', '23', '42:31.153', '1'], ['casey stoner', 'ducati', '23', '+ 2.201', '4'], ['dani pedrosa', 'honda', '23', '+ 4.867', '2'], ['alex de angelis', 'honda', '23', '+ 6.313', '10'], ['colin edwards', 'yamaha', '23', '+ 12.530', '5'], ['james toseland', 'yamaha', '23', '+ 13.806', '8'], ['loris capirossi', 'suzuki', '23', '+ 14.447', '3'], ['andrea dovizioso', 'honda', '23', '+ 15.319', '13'], ['shinya nakano', 'honda', '23', '+ 15.327', '9'], ['chris vermeulen', 'suzuki', '23', '+ 30.785', '11'], ['sylvain guintoli', 'ducati', '23', '+ 39.621', '17'], ['toni elias', 'ducati', '23', '+ 50.021', '16'], ['nicky hayden', 'honda', '23', '+ 50.440', '6'], ['tadayuki okada', 'honda', '23', '+ 58.849', '15'], ['anthony west', 'kawasaki', '23', '+ 1:00.736', '19'], ['jorge lorenzo', 'yamaha', '6', 'accident', '7'], ['john hopkins', 'kawasaki', '6', 'accident', '14'], ['randy de puniet', 'honda', '5', 'accident', '12'], ['marco melandri', 'ducati', '5', 'accident', '18']] |
cyprus in the eurovision song contest 1999 | https://en.wikipedia.org/wiki/Cyprus_in_the_Eurovision_Song_Contest_1999 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11522647-1.html.csv | comparative | in the cypriot final of the eurovision song contest 1999 , demos beke placed higher than lucas christodolou . | {'row_1': '9', 'row_2': '7', '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', 'artist', 'demos beke'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose artist record fuzzily matches to demos beke .', 'tostr': 'filter_eq { all_rows ; artist ; demos beke }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; artist ; demos beke } ; points }', 'tointer': 'select the rows whose artist record fuzzily matches to demos beke . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'artist', 'lucas christodolou'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose artist record fuzzily matches to lucas christodolou .', 'tostr': 'filter_eq { all_rows ; artist ; lucas christodolou }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; artist ; lucas christodolou } ; points }', 'tointer': 'select the rows whose artist record fuzzily matches to lucas christodolou . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; artist ; demos beke } ; points } ; hop { filter_eq { all_rows ; artist ; lucas christodolou } ; points } } = true', 'tointer': 'select the rows whose artist record fuzzily matches to demos beke . take the points record of this row . select the rows whose artist record fuzzily matches to lucas christodolou . take the points record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; artist ; demos beke } ; points } ; hop { filter_eq { all_rows ; artist ; lucas christodolou } ; points } } = true | select the rows whose artist record fuzzily matches to demos beke . take the points record of this row . select the rows whose artist record fuzzily matches to lucas christodolou . take the points record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'artist_7': 7, 'demos beke_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'artist_11': 11, 'lucas christodolou_12': 12, 'points_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'artist_7': 'artist', 'demos beke_8': 'demos beke', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'artist_11': 'artist', 'lucas christodolou_12': 'lucas christodolou', 'points_13': 'points'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'artist_7': [0], 'demos beke_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'artist_11': [1], 'lucas christodolou_12': [1], 'points_13': [3]} | ['draw', 'artist', 'song', 'points', 'place'] | [['1', 'marlen angelidou', "tha ' ne erotas", '225', '1'], ['2', 'riana athanasiou', 'moni', '107', '7'], ['3', 'elena tsolaki', 'aspro feggari', '116', '5'], ['4', 'christina saranti', 'adeio feggari', '102', '8'], ['5', 'stelios constantas', 'methysmeno feggari', '125', '4'], ['6', 'giorgos stamataris', 'maria', '143', '3'], ['7', 'lucas christodolou', 'an gyriseis', '113', '6'], ['8', 'giorgos gavriel', 'pios erotas glykos', '88', '9'], ['9', 'demos beke', 'tha sou edina oli mou ti zoi', '178', '2']] |
2005 centrix financial grand prix of denver | https://en.wikipedia.org/wiki/2005_Centrix_Financial_Grand_Prix_of_Denver | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15158976-2.html.csv | aggregation | 80.9 is the average number of laps per driver during the 2005 centrix financial grand prix of denver . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '80.9', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'laps'], 'result': '80.9', 'ind': 0, 'tostr': 'avg { all_rows ; laps }'}, '80.9'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; laps } ; 80.9 } = true', 'tointer': 'the average of the laps record of all rows is 80.9 .'} | round_eq { avg { all_rows ; laps } ; 80.9 } = true | the average of the laps record of all rows is 80.9 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'laps_4': 4, '80.9_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '80.9_5': '80.9'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'laps_4': [0], '80.9_5': [1]} | ['driver', 'team', 'laps', 'time / retired', 'grid', 'points'] | [['sébastien bourdais', 'newman / haas racing', '97', '1:49:45.135', '2', '33'], ['mario domínguez', 'forsythe racing', '97', '+ 15.269 secs', '3', '27'], ['a j allmendinger', 'rusport', '97', '+ 17.207 secs', '4', '25'], ['oriol servià', 'newman / haas racing', '97', '+ 35.775 secs', '8', '23'], ['rodolfo lavín', 'hvm racing', '97', '+ 37.629 secs', '13', '21'], ['ryan hunter - reay', 'rocketsports racing', '97', '+ 43.237 secs', '17', '20'], ['ronnie bremer', 'dale coyne racing', '97', '+ 47.487 secs', '16', '17'], ['ricardo sperafico', 'dale coyne racing', '97', '+ 52.470 secs', '12', '15'], ['nelson philippe', 'mi - jack conquest racing', '97', '+ 1:02.902', '15', '13'], ['andrew ranger', 'mi - jack conquest racing', '96', '+ 1 lap', '11', '11'], ['björn wirdheim', 'hvm racing', '96', '+ 1 lap', '14', '10'], ['marcus marshall', 'team australia', '94', '+ 3 laps', '18', '9'], ['timo glock', 'rocketsports racing', '88', 'gearbox', '10', '8'], ['alex tagliani', 'team australia', '82', '+ 15 laps', '7', '7'], ['jimmy vasser', 'pkv racing', '65', 'in pits', '6', '6'], ['paul tracy', 'forsythe racing', '62', 'contact', '1', '8'], ['justin wilson', 'rusport', '0', 'contact', '5', '4'], ['cristiano da matta', 'pkv racing', '0', 'contact', '9', '3']] |
nathan ablett | https://en.wikipedia.org/wiki/Nathan_Ablett | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1756688-1.html.csv | comparative | nathan ablett played in more games in 2007 than he did in 2006 . | {'row_1': '3', 'row_2': '2', 'col': '3', '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', 'season', '2007'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose season record fuzzily matches to 2007 .', 'tostr': 'filter_eq { all_rows ; season ; 2007 }'}, 'games'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; season ; 2007 } ; games }', 'tointer': 'select the rows whose season record fuzzily matches to 2007 . take the games record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'season', '2006'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose season record fuzzily matches to 2006 .', 'tostr': 'filter_eq { all_rows ; season ; 2006 }'}, 'games'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; season ; 2006 } ; games }', 'tointer': 'select the rows whose season record fuzzily matches to 2006 . take the games record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; season ; 2007 } ; games } ; hop { filter_eq { all_rows ; season ; 2006 } ; games } } = true', 'tointer': 'select the rows whose season record fuzzily matches to 2007 . take the games record of this row . select the rows whose season record fuzzily matches to 2006 . take the games record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; season ; 2007 } ; games } ; hop { filter_eq { all_rows ; season ; 2006 } ; games } } = true | select the rows whose season record fuzzily matches to 2007 . take the games record of this row . select the rows whose season record fuzzily matches to 2006 . take the games 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, 'season_7': 7, '2007_8': 8, 'games_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'season_11': 11, '2006_12': 12, 'games_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', 'season_7': 'season', '2007_8': '2007', 'games_9': 'games', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'season_11': 'season', '2006_12': '2006', 'games_13': 'games'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'season_7': [0], '2007_8': [0], 'games_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'season_11': [1], '2006_12': [1], 'games_13': [3]} | ['season', 'team', 'games', 'disposals', 'kicks', 'handballs', 'marks', 'tackles', 'goals', 'behinds'] | [['2005', 'geelong', '4', '27 ( 6.8 )', '19 ( 4.8 )', '8 ( 2.0 )', '13 ( 3.2 )', '5 ( 1.2 )', '8 ( 2.0 )', '2 ( 0.5 )'], ['2006', 'geelong', '7', '56 ( 8.0 )', '33 ( 4.7 )', '23 ( 3.3 )', '27 ( 3.9 )', '5 ( 0.7 )', '4 ( 0.6 )', '3 ( 0.4 )'], ['2007', 'geelong', '21', '191 ( 9.1 )', '117 ( 5.6 )', '74 ( 3.5 )', '86 ( 4.1 )', '28 ( 1.3 )', '34 ( 1.6 )', '18 ( 0.9 )'], ['2008', 'geelong', '-', '-', '-', '-', '-', '-', '-', '-'], ['2011', 'gold coast', '2', '22 ( 11.0 )', '9 ( 4.5 )', '13 ( 6.5 )', '5 ( 2.5 )', '3 ( 1.5 )', '1 ( 0.5 )', '1 ( 0.5 )'], ['career totals', 'career totals', '34', '296 ( 8.7 )', '178 ( 5.2 )', '118 ( 3.5 )', '131 ( 3.9 )', '41 ( 1.2 )', '47 ( 1.4 )', '24 ( 0.7 )']] |
1999 - 2000 chelsea f.c. season | https://en.wikipedia.org/wiki/1999%E2%80%932000_Chelsea_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14768726-2.html.csv | ordinal | during the 1999-2000 chelsea f c season , the 2nd highest attendance was on april 9 , 2000 . | {'row': '5', 'col': '6', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'date'], 'result': '9 april 2000', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; date }'}, '9 april 2000'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; 9 april 2000 } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the date record of this row is 9 april 2000 .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; date } ; 9 april 2000 } = true | select the row whose attendance record of all rows is 2nd maximum . the date record of this row is 9 april 2000 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'date_7': 7, '9 april 2000_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'date_7': 'date', '9 april 2000_8': '9 april 2000'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'date_7': [1], '9 april 2000_8': [2]} | ['date', 'round', 'opponent', 'venue', 'result', 'attendance', 'scorers'] | [['11 december 1999', 'r3', 'hull city', 'a', '6 - 1', '10279', 'poyet ( 3 ) , sutton , di matteo , wise'], ['19 january 2000', 'r4', 'nottingham forest', 'h', '2 - 0', '30125', 'leboeuf , wise'], ['30 january 2000', 'r5', 'leicester city', 'h', '2 - 1', '30141', 'poyet , weah'], ['20 february 2000', 'qf', 'gillingham', 'h', '5 - 0', '34205', 'flo , terry , weah , zola ( pen ) , morris'], ['9 april 2000', 'sf', 'newcastle united', 'n', '2 - 1', '73876', 'poyet ( 2 )'], ['20 may 2000', 'f', 'aston villa', 'n', '1 - 0', '78217', 'di matteo']] |
yugoslavia national football team results | https://en.wikipedia.org/wiki/Yugoslavia_national_football_team_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14305653-47.html.csv | superlative | sweden was the first opponent of the yugoslavia national football team . | {'scope': 'all', 'col_superlative': '1', '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', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'opponent'], 'result': 'sweden', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; opponent }'}, 'sweden'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date } ; opponent } ; sweden } = true', 'tointer': 'select the row whose date record of all rows is minimum . the opponent record of this row is sweden .'} | eq { hop { argmin { all_rows ; date } ; opponent } ; sweden } = true | select the row whose date record of all rows is minimum . the opponent record of this row is sweden . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'opponent_6': 6, 'sweden_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', 'opponent_6': 'opponent', 'sweden_7': 'sweden'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'opponent_6': [1], 'sweden_7': [2]} | ['date', 'city', 'opponent', 'results', 'type of game'] | [['february 26', 'split', 'sweden', '2:1', 'friendly'], ['april 30', 'barcelona , spain', 'spain', '1:2', '1970 wcq'], ['june 4', 'helsinki , finland', 'finland', '5:1', '1970 wcq'], ['september 3', 'belgrade', 'romania', '1:1', 'friendly'], ['september 24', 'belgrade', 'ussr', '1:3', 'friendly'], ['october 19', 'skoplje', 'belgium', '4:0', '1970 wcq']] |
1985 masters tournament | https://en.wikipedia.org/wiki/1985_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16488699-1.html.csv | majority | in the 1985 masters tournament , most of the players were from the united states . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'united states', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': True, 'ind': 0, 'tointer': 'for the country records of all rows , most of them fuzzily match to united states .', 'tostr': 'most_eq { all_rows ; country ; united states } = true'} | most_eq { all_rows ; country ; united states } = true | for the country records of all rows , most of them fuzzily match to united states . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'country_3': 3, 'united states_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'country_3': 'country', 'united states_4': 'united states'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'country_3': [0], 'united states_4': [0]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'bernhard langer', 'west germany', '72 + 74 + 68 + 68 = 282', '- 6', '126000'], ['t2', 'seve ballesteros', 'spain', '72 + 71 + 71 + 70 = 284', '- 4', '52267'], ['t2', 'raymond floyd', 'united states', '70 + 73 + 69 + 72 = 284', '- 4', '52267'], ['t2', 'curtis strange', 'united states', '80 + 65 + 68 + 71 = 284', '- 4', '52267'], ['5', 'jay haas', 'united states', '73 + 73 + 72 + 67 = 285', '- 3', '28000'], ['t6', 'gary hallberg', 'united states', '68 + 73 + 75 + 70 = 286', '- 2', '22663'], ['t6', 'bruce lietzke', 'united states', '72 + 71 + 73 + 70 = 286', '- 2', '22663'], ['t6', 'jack nicklaus', 'united states', '71 + 74 + 72 + 69 = 286', '- 2', '22663'], ['t6', 'craig stadler', 'united states', '73 + 67 + 76 + 70 = 286', '- 2', '22663'], ['t10', 'fred couples', 'united states', '75 + 73 + 69 + 70 = 287', '- 1', '16800'], ['t10', 'david graham', 'australia', '74 + 71 + 71 + 71 = 287', '- 1', '16800'], ['t10', 'lee trevino', 'united states', '70 + 73 + 72 + 72 = 287', '- 1', '16800'], ['t10', 'tom watson', 'united states', '69 + 71 + 75 + 72 = 287', '- 1', '16800']] |
list of australian odi batsmen who have scored over 2500 odi runs | https://en.wikipedia.org/wiki/List_of_Australian_ODI_batsmen_who_have_scored_over_2500_ODI_runs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21486890-1.html.csv | count | there is a total of 17 australian odi batsmen to score over 2500 odi runs . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '17', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'name'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record is arbitrary .', 'tostr': 'filter_all { all_rows ; name }'}], 'result': '17', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; name } }', 'tointer': 'select the rows whose name record is arbitrary . the number of such rows is 17 .'}, '17'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; name } } ; 17 } = true', 'tointer': 'select the rows whose name record is arbitrary . the number of such rows is 17 .'} | eq { count { filter_all { all_rows ; name } } ; 17 } = true | select the rows whose name record is arbitrary . the number of such rows is 17 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'name_5': 5, '17_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'name_5': 'name', '17_6': '17'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'name_5': [0], '17_6': [2]} | ['name', 'career', 'matches', 'innings', 'not out', 'runs scored', 'high score', '50s', '100s', 'average'] | [['ricky ponting', '1995 - 2012', '374', '364', '39', '13589', '164', '82', '29', '41.81'], ['adam gilchrist', '1996 - 2008', '286', '278', '11', '9595', '172', '55', '16', '35.93'], ['mark waugh', '1988 - 2002', '244', '236', '20', '8500', '173', '50', '18', '39.35'], ['steve waugh', '1986 - 2002', '325', '288', '58', '7569', '120', '45', '3', '32.90'], ['michael clarke', '2003 -', '227', '207', '42', '7375', '130', '54', '7', '44.69'], ['michael bevan', '1994 - 2004', '232', '196', '67', '6912', '108', '46', '6', '53.58'], ['allan border', '1979 - 1994', '273', '252', '39', '6524', '127', '39', '3', '30.62'], ['matthew hayden', '1993 - 2008', '160', '154', '15', '6131', '181', '36', '10', '44.10'], ['dean jones', '1984 - 1994', '164', '161', '25', '6068', '145', '46', '7', '44.61'], ['david boon', '1984 - 1995', '181', '177', '16', '5964', '122', '37', '5', '37.04'], ['michael hussey', '2004 - 2012', '185', '157', '44', '5442', '109', '39', '3', '48.15'], ['damien martyn', '1992 - 2006', '208', '182', '51', '5346', '144', '37', '5', '40.80'], ['andrew symonds', '1998 - 2009', '198', '161', '33', '5088', '156', '30', '6', '39.75'], ['shane watson', '2002 -', '160', '140', '24', '4796', '185', '29', '7', '41.34'], ['geoff marsh', '1986 - 1992', '117', '115', '6', '4357', '126', '22', '9', '39.97'], ['mark taylor', '1989 - 1997', '113', '110', '1', '3514', '105', '28', '1', '32.23'], ['darren lehmann', '1996 - 2005', '117', '101', '22', '3078', '119', '17', '4', '38.96']] |
1954 vfl season | https://en.wikipedia.org/wiki/1954_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-12.html.csv | count | there were 6 game venues used during the 1954 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['essendon', '13.16 ( 94 )', 'hawthorn', '9.9 ( 63 )', 'windy hill', '20000', '10 july 1954'], ['collingwood', '8.6 ( 54 )', 'melbourne', '5.16 ( 46 )', 'victoria park', '29000', '10 july 1954'], ['carlton', '11.10 ( 76 )', 'south melbourne', '10.10 ( 70 )', 'princes park', '17000', '10 july 1954'], ['richmond', '14.14 ( 98 )', 'north melbourne', '6.15 ( 51 )', 'punt road oval', '27000', '10 july 1954'], ['st kilda', '9.8 ( 62 )', 'footscray', '13.14 ( 92 )', 'junction oval', '22500', '10 july 1954'], ['geelong', '10.8 ( 68 )', 'fitzroy', '6.6 ( 42 )', 'kardinia park', '15000', '10 july 1954']] |
luke donald | https://en.wikipedia.org/wiki/Luke_Donald | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1590652-4.html.csv | comparative | luke donald won the omega european masters by a higher margin of victory than the madrid masters . | {'row_1': '2', 'row_2': '3', 'col': '6', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'omega european masters'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to omega european masters .', 'tostr': 'filter_eq { all_rows ; tournament ; omega european masters }'}, 'margin of victory'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; omega european masters } ; margin of victory }', 'tointer': 'select the rows whose tournament record fuzzily matches to omega european masters . take the margin of victory record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'madrid masters'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to madrid masters .', 'tostr': 'filter_eq { all_rows ; tournament ; madrid masters }'}, 'margin of victory'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; madrid masters } ; margin of victory }', 'tointer': 'select the rows whose tournament record fuzzily matches to madrid masters . take the margin of victory record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; tournament ; omega european masters } ; margin of victory } ; hop { filter_eq { all_rows ; tournament ; madrid masters } ; margin of victory } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to omega european masters . take the margin of victory record of this row . select the rows whose tournament record fuzzily matches to madrid masters . take the margin of victory record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; tournament ; omega european masters } ; margin of victory } ; hop { filter_eq { all_rows ; tournament ; madrid masters } ; margin of victory } } = true | select the rows whose tournament record fuzzily matches to omega european masters . take the margin of victory record of this row . select the rows whose tournament record fuzzily matches to madrid masters . take the margin of victory 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, 'tournament_7': 7, 'omega european masters_8': 8, 'margin of victory_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'madrid masters_12': 12, 'margin of victory_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', 'tournament_7': 'tournament', 'omega european masters_8': 'omega european masters', 'margin of victory_9': 'margin of victory', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'madrid masters_12': 'madrid masters', 'margin of victory_13': 'margin of victory'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'omega european masters_8': [0], 'margin of victory_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'madrid masters_12': [1], 'margin of victory_13': [3]} | ['no', 'date', 'tournament', 'winning score', 'to par', 'margin of victory', 'runner ( s ) - up'] | [['1', '1 aug 2004', 'scandinavian masters by carlsberg', '69 + 65 + 69 + 69 = 272', '16', '5 strokes', 'peter hanson'], ['2', '5 sep 2004', 'omega european masters', '67 + 67 + 65 + 66 = 265', '19', '5 strokes', 'miguel ángel jiménez'], ['3', '30 may 2010', 'madrid masters', '65 + 67 + 68 + 67 = 267', '21', '1 stroke', 'rhys davies'], ['4', '27 feb 2011', 'wgc - accenture match play championship', '3 and 2', '3 and 2', '3 and 2', 'martin kaymer'], ['5', '29 may 2011', 'bmw pga championship', '64 + 72 + 72 + 70 = 278', '6', 'playoff', 'lee westwood'], ['6', '10 jul 2011', 'barclays scottish open', '67 + 67 + 63 = 197', '19', '4 strokes', 'fredrik andersson hed']] |
zaur tagizade | https://en.wikipedia.org/wiki/Zaur_Tagizade | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17911639-1.html.csv | superlative | of the competitions zaur tagizade participated in , the most recent was in tirana . | {'scope': 'all', 'col_superlative': '1', 'row_superlative': '6', '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', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; date }'}, 'venue'], 'result': 'qemal stafa stadium , tirana', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; date } ; venue }'}, 'qemal stafa stadium , tirana'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; date } ; venue } ; qemal stafa stadium , tirana } = true', 'tointer': 'select the row whose date record of all rows is maximum . the venue record of this row is qemal stafa stadium , tirana .'} | eq { hop { argmax { all_rows ; date } ; venue } ; qemal stafa stadium , tirana } = true | select the row whose date record of all rows is maximum . the venue record of this row is qemal stafa stadium , tirana . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, 'venue_6': 6, 'qemal stafa stadium , tirana_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', 'venue_6': 'venue', 'qemal stafa stadium , tirana_7': 'qemal stafa stadium , tirana'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], 'venue_6': [1], 'qemal stafa stadium , tirana_7': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['5 june 1999', 'tofiq bahramov stadium , baku', '3 - 0', '4 - 0', 'euro 2000 qualifying'], ['18 august 1999', 'dynamo samarkand stadium , samarkand', '3 - 1', '5 - 1', 'friendly'], ['4 september 1999', 'tofiq bahramov stadium , baku', '1 - 0', '1 - 1', 'euro 2000 qualifying'], ['26 february 2001', 'national sport base sportpalace , varna', '1 - 0', '1 - 0', 'friendly'], ['6 june 2001', 'tofiq bahramov stadium , baku', '2 - 0', '2 - 0', '2002 world cup qualification'], ['17 august 2005', 'qemal stafa stadium , tirana', '0 - 1', '2 - 1', 'friendly']] |
peel thunder football club | https://en.wikipedia.org/wiki/Peel_Thunder_Football_Club | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1165048-1.html.csv | ordinal | the peel thunder football club had their fourth highest number of wins in 2006 . | {'row': '10', 'col': '3', 'order': '4', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'win / loss', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; win / loss ; 4 }'}, 'season'], 'result': '2006', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; win / loss ; 4 } ; season }'}, '2006'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; win / loss ; 4 } ; season } ; 2006 } = true', 'tointer': 'select the row whose win / loss record of all rows is 4th maximum . the season record of this row is 2006 .'} | eq { hop { nth_argmax { all_rows ; win / loss ; 4 } ; season } ; 2006 } = true | select the row whose win / loss record of all rows is 4th maximum . the season record of this row is 2006 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'win / loss_5': 5, '4_6': 6, 'season_7': 7, '2006_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'win / loss_5': 'win / loss', '4_6': '4', 'season_7': 'season', '2006_8': '2006'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'win / loss_5': [0], '4_6': [0], 'season_7': [1], '2006_8': [2]} | ['season', 'position', 'win / loss', 'coach', 'captain', 'dudley tuckey medal', 'leading goalkicker'] | [['1997', '9', '1 - 19', 'geoff miles', 'phil gilbert', 'scott simister', 'scott simister ( 27 )'], ['1998', '9', '1 - 19', 'geoff miles troy wilson', 'phil gilbert', 'darren bolton', 'scott simister ( 31 )'], ['1999', '9', '0 - 20', 'troy wilson', 'scott simister', 'scott simister', 'scott simister ( 54 )'], ['2000', '8', '4 - 14', 'shane cable', 'bill monaghan', 'vance davison', 'dean buszan ( 32 )'], ['2001', '6', '7 - 11', 'shane cable', 'vance davison', 'derek hall', 'david mcpharlin ( 25 )'], ['2002', '8', '7 - 11', 'peter german', 'derek hall', 'darren bolton', 'scott simister ( 46 )'], ['2003', '9', '1 - 19', 'john ditchburn', 'derek hall', 'derek hall', 'derek hall ( 22 )'], ['2004', '8', '5 - 15', 'garry hocking', 'brandon hill', 'daniel haines', 'cameron gauci ( 40 )'], ['2005', '9', '3 - 17', 'garry hocking', 'grant welsh', 'pat travers', 'justin wood ( 29 )'], ['2006', '8', '6 - 14', 'chris waterman', 'grant welsh', "rory o'brien", 'dean buszan ( 44 )'], ['2007', '8', '5 - 15', 'chris waterman', 'grant welsh', 'daniel haines', 'dean buszan ( 30 )'], ['2008', '6', '8 - 12', 'chris waterman', 'grant welsh', 'hayden ballantyne', 'hayden ballantyne ( 75 )'], ['2009', '9', '5 - 15', 'chris waterman', 'daniel haines', 'ben howlett', 'kain robins ( 33 )'], ['2010', '8', '3 - 17', 'trevor williams', 'daniel haines brendon jones', "rory o'brien", 'matthew battye ( 27 )'], ['2011', '9', '5 - 15', 'trevor williams', 'brendon jones', 'kristin thornton', 'bradley holmes ( 36 )'], ['2012', '9', '5 - 15', 'trevor williams mark moody', 'brendon jones', 'brendon jones', 'bradley holmes ( 52 )'], ['2013', '9', '3 - 17', 'cam shepherd', 'brendon jones', 'viv michie', 'bradley holmes ( 33 )']] |
1982 in film | https://en.wikipedia.org/wiki/1982_in_film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-171649-1.html.csv | comparative | in 1982 gandhi had a higher gross than the dark crystal . | {'row_1': '12', 'row_2': '16', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'gandhi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to gandhi .', 'tostr': 'filter_eq { all_rows ; title ; gandhi }'}, 'gross'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; gandhi } ; gross }', 'tointer': 'select the rows whose title record fuzzily matches to gandhi . take the gross record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'the dark crystal'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to the dark crystal .', 'tostr': 'filter_eq { all_rows ; title ; the dark crystal }'}, 'gross'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; the dark crystal } ; gross }', 'tointer': 'select the rows whose title record fuzzily matches to the dark crystal . take the gross record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; title ; gandhi } ; gross } ; hop { filter_eq { all_rows ; title ; the dark crystal } ; gross } } = true', 'tointer': 'select the rows whose title record fuzzily matches to gandhi . take the gross record of this row . select the rows whose title record fuzzily matches to the dark crystal . take the gross record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; title ; gandhi } ; gross } ; hop { filter_eq { all_rows ; title ; the dark crystal } ; gross } } = true | select the rows whose title record fuzzily matches to gandhi . take the gross record of this row . select the rows whose title record fuzzily matches to the dark crystal . take the gross 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, 'title_7': 7, 'gandhi_8': 8, 'gross_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'the dark crystal_12': 12, 'gross_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', 'title_7': 'title', 'gandhi_8': 'gandhi', 'gross_9': 'gross', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'the dark crystal_12': 'the dark crystal', 'gross_13': 'gross'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'gandhi_8': [0], 'gross_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'the dark crystal_12': [1], 'gross_13': [3]} | ['rank', 'title', 'studio', 'director', 'gross'] | [['1', 'et the extra - terrestrial', 'universal', 'steven spielberg', '435110554'], ['2', 'tootsie', 'columbia', 'sydney pollack', '177200000'], ['3', 'an officer and a gentleman', 'paramount / lorimar', 'taylor hackford', '129795554'], ['4', 'rocky iii', 'united artists', 'sylvester stallone', '125049125'], ['5', "porky 's", '20th century fox', 'bob clark', '109492484'], ['6', 'star trek ii : the wrath of khan', 'paramount', 'nicholas meyer', '79912963'], ['7', '48 hrs', 'paramount', 'walter hill', '78868508'], ['8', 'poltergeist', 'mgm', 'tobe hooper', '76606280'], ['9', 'the best little whorehouse in texas', 'universal / rko', 'colin higgins', '69701637'], ['10', 'annie', 'columbia / rastar', 'john huston', '57059003'], ['11', 'the verdict', '20th century fox', 'sidney lumet', '53977250'], ['12', 'gandhi', 'columbia', 'richard attenborough', '52767889'], ['13', 'first blood', 'orion / carolco', 'ted kotcheff', '47212904'], ['14', 'the toy', 'columbia', 'richard donner', '47118057'], ['15', 'firefox', 'warner bros', 'clint eastwood', '46708276'], ['16', 'the dark crystal', 'universal', 'jim henson and frank oz', '40577001'], ['17', 'conan the barbarian', 'universal', 'john milius', '39565475'], ['18', 'the sword and the sorcerer', 'group 1', 'albert pyun', '39103425'], ['19', 'best friends', 'warner bros', 'norman jewison', '36821203'], ['20', 'richard pryor : live on the sunset strip', 'columbia', 'joe layton', '36299720']] |
the evian championship | https://en.wikipedia.org/wiki/The_Evian_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1529260-3.html.csv | count | in the evian championship , 1 of the games before 1998 was held in sweden . | {'scope': 'subset', 'criterion': 'equal', 'value': 'sweden', 'result': '1', 'col': '4', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '1998'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'year', '1998'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; year ; 1998 }', 'tointer': 'select the rows whose year record is less than 1998 .'}, 'country', 'sweden'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record is less than 1998 . among these rows , select the rows whose country record fuzzily matches to sweden .', 'tostr': 'filter_eq { filter_less { all_rows ; year ; 1998 } ; country ; sweden }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_eq { filter_less { all_rows ; year ; 1998 } ; country ; sweden } }', 'tointer': 'select the rows whose year record is less than 1998 . among these rows , select the rows whose country record fuzzily matches to sweden . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_less { all_rows ; year ; 1998 } ; country ; sweden } } ; 1 } = true', 'tointer': 'select the rows whose year record is less than 1998 . among these rows , select the rows whose country record fuzzily matches to sweden . the number of such rows is 1 .'} | eq { count { filter_eq { filter_less { all_rows ; year ; 1998 } ; country ; sweden } } ; 1 } = true | select the rows whose year record is less than 1998 . among these rows , select the rows whose country record fuzzily matches to sweden . the number of such rows is 1 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'year_6': 6, '1998_7': 7, 'country_8': 8, 'sweden_9': 9, '1_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'year_6': 'year', '1998_7': '1998', 'country_8': 'country', 'sweden_9': 'sweden', '1_10': '1'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'year_6': [0], '1998_7': [0], 'country_8': [1], 'sweden_9': [1], '1_10': [3]} | ['year', 'dates', 'champion', 'country', 'score', 'to par', 'margin of victory'] | [['1999', 'jun 9 - 12', 'catrin nilsmark', 'sweden', '69 + 70 + 72 + 68 = 279', '- 9', '2 strokes'], ['1998', 'jun 3 - 6', 'helen alfredsson', 'sweden', '70 + 69 + 73 + 65 = 277', '- 11', '4 strokes'], ['1997', 'jun 18 - 21', 'hiromi kobayashi', 'japan', '69 + 67 + 69 + 69 = 274', '- 14', 'playoff'], ['1996', 'jun 19 - 22', 'laura davies', 'england', '72 + 69 + 65 + 68 = 274', '- 14', '4 strokes'], ['1995', 'jun 7 - 10', 'laura davies', 'england', '68 + 67 + 69 + 67 = 271', '- 17', '5 strokes'], ['1994', 'jun 9 - 12', 'helen alfredsson', 'sweden', '71 + 73 + 73 + 70 = 287', '- 1', '3 strokes']] |
1982 vfl season | https://en.wikipedia.org/wiki/1982_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10824095-11.html.csv | superlative | in the venues that were at a " park " , the highest away team score was 21.10 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': 'park'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'park'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; park }', 'tointer': 'select the rows whose venue record fuzzily matches to park .'}, 'away team score'], 'result': '21.10 ( 136 )', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; venue ; park } ; away team score }', 'tointer': 'select the rows whose venue record fuzzily matches to park . the maximum away team score record of these rows is 21.10 ( 136 ) .'}, '21.10 ( 136 )'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; venue ; park } ; away team score } ; 21.10 ( 136 ) } = true', 'tointer': 'select the rows whose venue record fuzzily matches to park . the maximum away team score record of these rows is 21.10 ( 136 ) .'} | eq { max { filter_eq { all_rows ; venue ; park } ; away team score } ; 21.10 ( 136 ) } = true | select the rows whose venue record fuzzily matches to park . the maximum away team score record of these rows is 21.10 ( 136 ) . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'park_6': 6, 'away team score_7': 7, '21.10 (136)_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'park_6': 'park', 'away team score_7': 'away team score', '21.10 (136)_8': '21.10 ( 136 )'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'park_6': [0], 'away team score_7': [1], '21.10 (136)_8': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['richmond', '20.14 ( 134 )', 'swans', '18.25 ( 133 )', 'mcg', '28216', '5 june 1982'], ['hawthorn', '26.22 ( 178 )', 'melbourne', '14.15 ( 99 )', 'princes park', '14087', '5 june 1982'], ['collingwood', '26.16 ( 172 )', 'st kilda', '21.10 ( 136 )', 'victoria park', '26657', '5 june 1982'], ['geelong', '10.11 ( 71 )', 'essendon', '17.9 ( 111 )', 'kardinia park', '29884', '5 june 1982'], ['north melbourne', '13.18 ( 96 )', 'carlton', '15.15 ( 105 )', 'arden street oval', '26206', '5 june 1982'], ['fitzroy', '23.22 ( 160 )', 'footscray', '16.12 ( 108 )', 'vfl park', '13908', '5 june 1982']] |
1995 open championship | https://en.wikipedia.org/wiki/1995_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18103106-3.html.csv | aggregation | in the 1995 open championship , players from the united states averaged 9.67 strokes above par . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '9.67', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'united states'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'to par'], 'result': '9.67', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; country ; united states } ; to par }'}, '9.67'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; 9.67 } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . the average of the to par record of these rows is 9.67 .'} | round_eq { avg { filter_eq { all_rows ; country ; united states } ; to par } ; 9.67 } = true | select the rows whose country record fuzzily matches to united states . the average of the to par record of these rows is 9.67 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'united states_6': 6, 'to par_7': 7, '9.67_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'united states_6': 'united states', 'to par_7': 'to par', '9.67_8': '9.67'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'united states_6': [0], 'to par_7': [1], '9.67_8': [2]} | ['player', 'country', 'year ( s ) won', 'total', 'to par'] | [['bob charles', 'new zealand', '1963', '149', '+ 5'], ['tom weiskopf', 'united states', '1973', '151', '+ 7'], ['lee trevino', 'united states', '1971 , 1972', '152', '+ 8'], ['ian baker - finch', 'australia', '1991', '153', '+ 9'], ['arnold palmer', 'united states', '1961 , 1962', '158', '+ 14']] |
united states house of representatives elections , 1950 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1950 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342198-13.html.csv | majority | most of the incumbents in the 1950 house of representatives elections were members of the democratic party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democratic', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic .', 'tostr': 'most_eq { all_rows ; party ; democratic } = true'} | most_eq { all_rows ; party ; democratic } = true | for the party records of all rows , most of them fuzzily match to democratic . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 2', "barratt o'hara", 'democratic', '1948', 'lost re - election republican gain', "richard b vail ( r ) 53.6 % barratt o'hara ( d ) 46.4 %"], ['illinois 3', 'neil j linehan', 'democratic', '1948', 'lost re - election republican gain', 'fred e busbey ( r ) 57.2 % neil j linehan ( d ) 42.8 %'], ['illinois 6', "thomas j o'brien", 'democratic', '1942', 're - elected', "thomas j o'brien ( d ) 64.6 % john m fay ( r ) 35.4 %"], ['illinois 15', 'noah m mason', 'republican', '1936', 're - elected', 'noah m mason ( r ) 63.3 % wayne f caskey ( d ) 36.7 %'], ['illinois 20', 'sid simpson', 'republican', '1942', 're - elected', 'sid simpson ( r ) 59.3 % howard manning ( d ) 40.7 %'], ['illinois 25', 'melvin price', 'democratic', '1944', 're - elected', 'melvin price ( d ) 64.9 % roger d jones ( r ) 35.1 %']] |
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