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wu liufang | https://en.wikipedia.org/wiki/Wu_Liufang | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26681728-1.html.csv | majority | wu liufang competed the most in ghent than in any other location . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'ghent', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'location', 'ghent'], 'result': True, 'ind': 0, 'tointer': 'for the location records of all rows , most of them fuzzily match to ghent .', 'tostr': 'most_eq { all_rows ; location ; ghent } = true'} | most_eq { all_rows ; location ; ghent } = true | for the location records of all rows , most of them fuzzily match to ghent . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'location_3': 3, 'ghent_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'location_3': 'location', 'ghent_4': 'ghent'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'location_3': [0], 'ghent_4': [0]} | ['year', 'competition', 'location', 'apparatus', 'rank - final', 'score - final', 'rank - qualifying', 'score - qualifying'] | [['2011', 'world cup', 'ghent', 'uneven bars', '3', '15.350', '1', '15.350'], ['2011', 'world cup', 'ghent', 'balance beam', '1', '14.975', '2', '14.850'], ['2011', 'world cup', 'ghent', 'floor exercise', '2', '13.650', '3', '13.475'], ['2010', 'world cup', 'ghent', 'uneven bars', '1', '15.050', '2', '14.775'], ['2010'... |
1986 pittsburgh steelers season | https://en.wikipedia.org/wiki/1986_Pittsburgh_Steelers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14520977-1.html.csv | majority | most of the games in the 1986 pittsburgh steelers season aired on nbc . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nbc', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'tv', 'nbc'], 'result': True, 'ind': 0, 'tointer': 'for the tv records of all rows , most of them fuzzily match to nbc .', 'tostr': 'most_eq { all_rows ; tv ; nbc } = true'} | most_eq { all_rows ; tv ; nbc } = true | for the tv records of all rows , most of them fuzzily match to nbc . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'tv_3': 3, 'nbc_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'tv_3': 'tv', 'nbc_4': 'nbc'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'tv_3': [0], 'nbc_4': [0]} | ['week', 'date', 'opponent', 'location', 'time ( et )', 'tv', 'result', 'record'] | [['1', 'sun sep 7', 'seattle seahawks', 'kingdome', '4:00 pm', 'nbc', 'l 30 - 0', '0 - 1'], ['2', 'mon sep 15', 'denver broncos', 'three rivers stadium', '9:00 pm', 'abc', 'l 21 - 10', '0 - 2'], ['3', 'sun sep 21', 'minnesota vikings', 'hubert h humphrey metrodome', '1:00 pm', 'nbc', 'l 31 - 7', '0 - 3'], ['4', 'sun se... |
1995 - 96 chicago bulls season | https://en.wikipedia.org/wiki/1995%E2%80%9396_Chicago_Bulls_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13480122-5.html.csv | ordinal | during the 1995 - 96 season , the chicago bulls ' game against toronto recorded the highest attendance . | {'row': '8', 'col': '8', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'location attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 1 }'}, 'team'], 'result': 'toronto', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ;... | eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; toronto } = true | select the row whose location attendance record of all rows is 1st maximum . the team record of this row is toronto . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '1_6': 6, 'team_7': 7, 'toronto_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', 'location attendance_5': 'location attendance', '1_6': '1', 'team_7': 'team', 'toronto_8': 'toronto'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '1_6': [0], 'team_7': [1], 'toronto_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['29', 'january 3', 'houston', 'w 100 - 86', 'michael jordan ( 38 )', 'dennis rodman ( 15 )', 'scottie pippen ( 9 )', 'united center 23854', '26 - 3'], ['30', 'january 4', 'charlotte', 'w 117 - 93', 'michael jordan ( 27 )', 'dennis rodman ( 11 )', 'ron harper ( 7 )', 'charlotte coliseum 24042', '27 - 3'], ['31', 'janu... |
yakushiji ryōko no kaiki jikenbo | https://en.wikipedia.org/wiki/Yakushiji_Ry%C5%8Dko_no_Kaiki_Jikenbo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18443854-1.html.csv | comparative | paris , the strange attractive capital was published before visitor 's fog was published . | {'row_1': '3', 'row_2': '7', 'col': '3', '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', 'english title', 'paris , the strange attractive capital'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose english title record fuzzily matches to paris , the strange attractive capital .', 'tostr': 'filte... | less { hop { filter_eq { all_rows ; english title ; paris , the strange attractive capital } ; year } ; hop { filter_eq { all_rows ; english title ; visitor 's fog } ; year } } = true | select the rows whose english title record fuzzily matches to paris , the strange attractive capital . take the year record of this row . select the rows whose english title record fuzzily matches to visitor 's fog . take the year record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'english title_7': 7, 'paris , the strange attractive capital_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'english title_11': 11, "visitor 's fog_12": 12, 'year_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'english title_7': 'english title', 'paris , the strange attractive capital_8': 'paris , the strange attractive capital', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'english title_7': [0], 'paris , the strange attractive capital_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'english title_11': [1], "visitor 's fog_12": [1], 'year_13': [3]} | ['japanese title', 'english title', 'year', 'first publisher', 'isbn'] | [['魔天楼 ( matenrō )', 'demon skyscraper', '1996', 'kodansha bunko', 'isbn 4 - 06 - 263346 - 9'], ['東京ナイトメア ( tokyo nightmare )', 'tokyo nightmare', '1999', 'kodansha novels', 'isbn 4 - 06 - 182042 - 7'], ['巴里 ・ 妖都変 ( paris yōto - hen )', 'paris , the strange attractive capital', '2000', 'kobunsha kappa novels', 'isbn 4 ... |
1998 masters tournament | https://en.wikipedia.org/wiki/1998_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514546-2.html.csv | count | there were 10 players who participated in the 1998 masters tournament . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '10', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'player'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record is arbitrary .', 'tostr': 'filter_all { all_rows ; player }'}], 'result': '10', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player }... | eq { count { filter_all { all_rows ; player } } ; 10 } = true | select the rows whose player record is arbitrary . the number of such rows is 10 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '10_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '10_6': '10'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '10_6': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['t1', 'fred couples', 'united states', '69 + 70 = 139', '- 5'], ['t1', 'david duval', 'united states', '71 + 68 = 139', '- 5'], ['3', 'scott hoch', 'united states', '70 + 71 = 141', '- 3'], ['t4', 'paul azinger', 'united states', '71 + 72 = 143', '- 1'], ['t4', 'jay haas', 'united states', '72 + 71 = 143', '- 1'], ['... |
list of t.u.f.f. puppy episodes | https://en.wikipedia.org/wiki/List_of_T.U.F.F._Puppy_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28787871-3.html.csv | count | nine of the episodes aired for the first time in the year 2012 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2012', 'result': '9', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', '2012'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to 2012 .', 'tostr': 'filter_eq { all_rows ; original air date ; 2012 }'}], 'result': '9', ... | eq { count { filter_eq { all_rows ; original air date ; 2012 } } ; 9 } = true | select the rows whose original air date record fuzzily matches to 2012 . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '2012_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', '2012_6': '2012', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '2012_6': [0], '9_7': [2]} | ['no in series', 'no in season', 'title', 'original air date', 'production code', 'us viewers ( millions )'] | [['21', '1', 'a doomed christmas', 'december 10 , 2011', '121', 'n / a'], ['22', '2', "big dog on campus / dog 's best friend", 'january 16 , 2012', '122', 'n / a'], ['23', '3', 'monkey business / diary of a mad cat', 'april 21 , 2012', '125', 'n / a'], ['24', '4', 'dudley do - wrong / puppy unplugged', 'may 6 , 2012',... |
independent girls ' schools sports association ( south australia ) | https://en.wikipedia.org/wiki/Independent_Girls%27_Schools_Sports_Association_%28South_Australia%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22043925-1.html.csv | superlative | pembroke school has the highest enrollment of schools in the independent girls ' schools sports association . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '4', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrolment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrolment }'}, 'school'], 'result': 'pembroke school', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrolment } ; school }'}, 'pembroke school'], 'resul... | eq { hop { argmax { all_rows ; enrolment } ; school } ; pembroke school } = true | select the row whose enrolment record of all rows is maximum . the school record of this row is pembroke school . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrolment_5': 5, 'school_6': 6, 'pembroke school_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrolment_5': 'enrolment', 'school_6': 'school', 'pembroke school_7': 'pembroke school'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrolment_5': [0], 'school_6': [1], 'pembroke school_7': [2]} | ['school', 'location', 'enrolment', 'founded', 'denomination', 'boys / girls', 'day / boarding', 'school colors'] | [['annesley college', 'wayville', '530', '1902', 'uniting church', 'girls', 'day & boarding', 'maroon & white'], ['concordia college', 'highgate', '700', '1890', 'lutheran', 'boys & girls', 'day', 'blue & gold'], ['immanuel college', 'novar gardens', '800', '1895', 'lutheran', 'boys & girls', 'day & boarding', 'blue , ... |
list of my place episodes | https://en.wikipedia.org/wiki/List_of_My_Place_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25390694-2.html.csv | count | shawn seet directed 3 episodes of the series titled ' my place ' . | {'scope': 'all', 'criterion': 'equal', 'value': 'shawn seet', 'result': '3', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'director', 'shawn seet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose director record fuzzily matches to shawn seet .', 'tostr': 'filter_eq { all_rows ; director ; shawn seet }'}], 'result': '3', 'ind': 1,... | eq { count { filter_eq { all_rows ; director ; shawn seet } } ; 3 } = true | select the rows whose director record fuzzily matches to shawn seet . 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, 'director_5': 5, 'shawn seet_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', 'director_5': 'director', 'shawn seet_6': 'shawn seet', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'director_5': [0], 'shawn seet_6': [0], '3_7': [2]} | ['series', 'title', 'director', 'writer', 'air date', 'production code'] | [['1', 'laura 2008', 'shawn seet', 'leah purcell', 'december 4 , 2009', '101'], ['2', 'mohammed 1998', 'shawn seet', 'brendan cowell', 'december 7 , 2009', '102'], ['3', 'lily 1988', 'shawn seet', 'greg waters', 'december 8 , 2009', '103'], ['4', 'mike 1978', 'michael james rowland', 'nicholas parsons', 'december 9 , 2... |
wind power in the republic of ireland | https://en.wikipedia.org/wiki/Wind_power_in_the_Republic_of_Ireland | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14101606-2.html.csv | count | there are 17 wind farms generating wind power in the republic of ireland . | {'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', 'wind farm'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose wind farm record is arbitrary .', 'tostr': 'filter_all { all_rows ; wind farm }'}], 'result': '17', 'ind': 1, 'tostr': 'count { filter_all { all_rows ;... | eq { count { filter_all { all_rows ; wind farm } } ; 17 } = true | select the rows whose wind farm 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, 'wind farm_5': 5, '17_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'wind farm_5': 'wind farm', '17_6': '17'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'wind farm_5': [0], '17_6': [2]} | ['wind farm', 'scheduled', 'capacity ( mw )', 'turbines', 'type', 'location'] | [['codling', 'unknown', '1100', '220', 'unknown', 'county wicklow'], ['carrowleagh', '2012', '36.8', '16', 'enercon e - 70 2.3', 'county cork'], ['dublin array', '2015', '364', '145', 'unknown', 'county dublin'], ['glenmore', '2009 summer', '30', '10', 'vestas v90', 'county clare'], ['glenough', '2010 winter', '32.5', ... |
list of ireland cricket captains | https://en.wikipedia.org/wiki/List_of_Ireland_cricket_captains | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11783487-3.html.csv | superlative | jason mollins is the ireland cricket captain with the highest win percentage . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '5', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', '% win'], 'result': '100.00', 'ind': 0, 'tostr': 'max { all_rows ; % win }', 'tointer': 'the maximum % win record of all rows is 100.00 .'}, '100.00'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; % win } ; 100.00 }', 'to... | and { eq { max { all_rows ; % win } ; 100.00 } ; eq { hop { argmax { all_rows ; % win } ; player } ; jason molins } } = true | the maximum % win record of all rows is 100.00 . the player record of the row with superlative % win record is jason molins . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, '% win_8': 8, '100.00_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, '% win_11': 11, 'player_12': 12, 'jason molins_13': 13} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', '% win_8': '% win', '100.00_9': '100.00', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', '% win_11': '% win', 'player_12': 'player', 'jason molins_13': 'jason molins'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], '% win_8': [0], '100.00_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], '% win_11': [2], 'player_12': [3], 'jason molins_13': [4]} | ['player', 'dates of captaincy', 'lost', 'tied', 'no result', '% win'] | [['alan lewis', '1993 / 94', '4', '0', '0', '42.86'], ['justin benson', '1996 / 97', '3', '0', '1', '66.66'], ['kyle mccallan', '2001 - 2005', '5', '1', '0', '44.44'], ['dekker curry', '2005', '1', '0', '0', '0.00'], ['jason molins', '2005', '0', '0', '0', '100.00'], ['william porterfield', '2009', '2', '0', '0', '80.0... |
liberty league | https://en.wikipedia.org/wiki/Liberty_League | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1974482-1.html.csv | majority | all of the institutions in the liberty league are private type institutions . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'private', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'type', 'private'], 'result': True, 'ind': 0, 'tointer': 'for the type records of all rows , all of them fuzzily match to private .', 'tostr': 'all_eq { all_rows ; type ; private } = true'} | all_eq { all_rows ; type ; private } = true | for the type records of all rows , all of them fuzzily match to private . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'type_3': 3, 'private_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'type_3': 'type', 'private_4': 'private'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'type_3': [0], 'private_4': [0]} | ['institution', 'nickname', 'location', 'founded', 'type', 'enrollment', 'joined'] | [['bard college', 'raptors', 'annandale - on - hudson , new york', '1860', 'private', '1958', '2011'], ['clarkson university', 'golden knights', 'potsdam , new york', '1896', 'private', '2848', '1995'], ['hobart college', 'statesmen', 'geneva , new york', '1822', 'private', '905', '1995'], ['rensselaer polytechnic inst... |
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 | aggregation | the average issued price of the royal canadian mint numismatic coins ( 2000s ) was 59.95 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '59.95', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'issue price'], 'result': '59.95', 'ind': 0, 'tostr': 'avg { all_rows ; issue price }'}, '59.95'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; issue price } ; 59.95 } = true', 'tointer': 'the average of the issue price record of all ... | round_eq { avg { all_rows ; issue price } ; 59.95 } = true | the average of the issue price record of all rows is 59.95 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'issue price_4': 4, '59.95_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'issue price_4': 'issue price', '59.95_5': '59.95'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'issue price_4': [0], '59.95_5': [1]} | ['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 fra... |
xavier malisse | https://en.wikipedia.org/wiki/Xavier_Malisse | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551805-6.html.csv | unique | the 11 october game was the only game xavier malisse competed in that was played on a carpet surface . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'carpet', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_eq { all_rows ; surface ; carpet } } ; eq { hop { filter_eq { all_rows ; surface ; carpet } ; year } ; 11 october 2004 } } = true | select the rows whose surface record fuzzily matches to carpet . there is only one such row in the table . the year record of this unqiue row is 11 october 2004 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'surface_7': 7, 'carpet_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'year_9': 9, '11 october 2004_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'surface_7': 'surface', 'carpet_8': 'carpet', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'year_9': 'year', '11 october 2004_10': '11 october 2004'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'surface_7': [0], 'carpet_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'year_9': [2], '11 october 2004_10': [3]} | ['outcome', 'year', 'surface', 'opponent', 'score'] | [['runner - up', '2 november 1998', 'clay', 'jiří novák', '3 - 6 , 3 - 6'], ['runner - up', '10 may 1999', 'clay', 'lleyton hewitt', '4 - 6 , 7 - 6 ( 7 - 2 ) , 1 - 6'], ['runner - up', '12 march 2001', 'hard', 'jan - michael gambill', '5 - 7 , 4 - 6'], ['runner - up', '30 april 2001', 'clay', 'andy roddick', '2 - 6 , 4... |
within these walls | https://en.wikipedia.org/wiki/Within_These_Walls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2582519-6.html.csv | comparative | of the episodes of within these walls , the episode titled " new girls " aired 7 days after the episode titled " freedom . " . | {'row_1': '10', 'row_2': '9', 'col': '6', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'new girls'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to new girls .', 'tostr': 'filter_eq { all_rows ; title ; new girls }'}, 'orig... | and { greater { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; hop { filter_eq { all_rows ; title ; freedom } ; original airdate } } ; and { eq { hop { filter_eq { all_rows ; title ; new girls } ; original airdate } ; 25 march 1978 } ; eq { hop { filter_eq { all_rows ; title ; freedom } ; origi... | select the rows whose title record fuzzily matches to new girls . take the original airdate record of this row . select the rows whose title record fuzzily matches to freedom . take the original airdate record of this row . the first record is greater than the second record . the original airdate record of the first ro... | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'title_11': 11, 'new girls_12': 12, 'original airdate_13': 13, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'title_15': 15, 'freedom_16': 16, 'original airdate_17': 17, 'and_7': 7, 'str_eq_5': 5, '25 march 1... | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'new girls_12': 'new girls', 'original airdate_13': 'original airdate', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all... | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'str_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'title_11': [0], 'new girls_12': [0], 'original airdate_13': [2], 'str_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'title_15': [1], 'freedom_16': [1], 'original airdate_17': [3], 'and_7': [8... | ['total', 'series', 'title', 'director', 'writer ( s )', 'original airdate'] | [['60', '1', 'mixer', 'christopher hodson', 'david butler', '21 january 1978'], ['61', '2', 'arrivals , departures', 'paul annett', 'david butler', '28 january 1978'], ['62', '3', 'raft', 'christphoer hodson', 'pj hammond', '4 february 1978'], ['63', '4', 'public opinion', 'marek kanievska', 'mona bruce and robert jame... |
1978 houston oilers season | https://en.wikipedia.org/wiki/1978_Houston_Oilers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15984957-2.html.csv | majority | the houston oilers won the majority of games during the 1978 season . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; result ; win } = true'} | most_eq { all_rows ; result ; win } = true | for the result records of all rows , most of them fuzzily match to win . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'win_4': [0]} | ['game', 'date', 'opponent', 'result', 'oilers points', 'opponents', 'oilers first downs', 'record', 'attendance'] | [['1', 'sept 3', 'atlanta falcons', 'loss', '14', '20', '13', '0 - 1', '57328'], ['2', 'sept 10', 'kansas city chiefs', 'win', '20', '17', '15', '1 - 1', '40213'], ['3', 'sept 17', 'san francisco 49ers', 'win', '20', '19', '23', '2 - 1', '46161'], ['4', 'sept 24', 'los angeles rams', 'loss', '6', '10', '10', '2 - 2', '... |
henlopen conference | https://en.wikipedia.org/wiki/Henlopen_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-5.html.csv | majority | the majority of teams in the henlopen conference failed to make the playoffs . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'failed to make playoffs', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'season outcome', 'failed to make playoffs'], 'result': True, 'ind': 0, 'tointer': 'for the season outcome records of all rows , most of them fuzzily match to failed to make playoffs .', 'tostr': 'most_eq { all_rows ; season outcome ; failed to make playoffs } = true'} | most_eq { all_rows ; season outcome ; failed to make playoffs } = true | for the season outcome records of all rows , most of them fuzzily match to failed to make playoffs . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'season outcome_3': 3, 'failed to make playoffs_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'season outcome_3': 'season outcome', 'failed to make playoffs_4': 'failed to make playoffs'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'season outcome_3': [0], 'failed to make playoffs_4': [0]} | ['school', 'team', 'division record', 'overall record', 'season outcome'] | [['dover', 'senators', '5 - 0', '8 - 3', 'loss in first round of div i playoffs'], ['caesar rodney', 'riders', '3 - 2', '4 - 6', 'failed to make playoffs'], ['sussex central', 'golden knights', '2 - 3', '6 - 5', 'loss in first round of div i playoffs'], ['sussex tech', 'ravens', '2 - 3', '5 - 5', 'failed to make playof... |
mike di meglio | https://en.wikipedia.org/wiki/Mike_Di_Meglio | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16678131-2.html.csv | count | there were 4 years when mike di meglio had 16 races . | {'scope': 'all', 'criterion': 'equal', 'value': '16', 'result': '4', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'races', '16'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose races record is equal to 16 .', 'tostr': 'filter_eq { all_rows ; races ; 16 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; ra... | eq { count { filter_eq { all_rows ; races ; 16 } } ; 4 } = true | select the rows whose races record is equal to 16 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'races_5': 5, '16_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'races_5': 'races', '16_6': '16', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'races_5': [0], '16_6': [0], '4_7': [2]} | ['season', 'races', 'wins', 'podiums', 'poles', 'fastest laps'] | [['2003', '10', '0', '0', '0', '0'], ['2003', '5', '0', '0', '0', '0'], ['2004', '14', '0', '0', '0', '0'], ['2005', '16', '1', '2', '0', '0'], ['2006', '14', '0', '0', '0', '0'], ['2007', '15', '0', '0', '0', '0'], ['2008', '17', '4', '9', '2', '4'], ['2009', '16', '0', '2', '1', '0'], ['2010', '16', '0', '0', '0', '0... |
list of tallest buildings in kansas city , missouri | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Kansas_City%2C_Missouri | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12815540-4.html.csv | ordinal | the building located at 1111 main street has the 3rd highest number of floors among the tallest buildings in kansas city , missouri . | {'row': '8', 'col': '5', '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 }'}, 'street address'], 'result': '1111 main street', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; floors ; 3 } ; street addres... | eq { hop { nth_argmax { all_rows ; floors ; 3 } ; street address } ; 1111 main street } = true | select the row whose floors record of all rows is 3rd maximum . the street address record of this row is 1111 main street . | 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, 'street address_7': 7, '1111 main street_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', 'street address_7': 'street address', '1111 main street_8': '1111 main street'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'floors_5': [0], '3_6': [0], 'street address_7': [1], '1111 main street_8': [2]} | ['name', 'street address', 'years as tallest', 'height feet / m', 'floors'] | [['new york life insurance building', '20 w ninth street', '1890 - 1906', '180 / 55', '12'], ['commerce trust building', '922 walnut street', '1906 - 1921', '258 / 79', '17'], ['historic federal reserve bank', '925 grand avenue', '1921 - 1929', '298 / 91', '16'], ['oak tower', '324 e 11th street', '1929 - 1931', '379 /... |
2006 african swimming championships | https://en.wikipedia.org/wiki/2006_African_Swimming_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13023411-1.html.csv | aggregation | the total number of gold medals won by the top 5 countries in the medal table at the 2006 african swimming championships is 42 . | {'scope': 'subset', 'col': '3', 'type': 'sum', 'result': '42', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '6'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'rank', '6'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; rank ; 6 }', 'tointer': 'select the rows whose rank record is less than 6 .'}, 'gold'], 'result': '42', 'ind': 1, 'tostr': 'sum { filter_less { a... | round_eq { sum { filter_less { all_rows ; rank ; 6 } ; gold } ; 42 } = true | select the rows whose rank record is less than 6 . the sum of the gold record of these rows is 42 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'rank_5': 5, '6_6': 6, 'gold_7': 7, '42_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '6_6': '6', 'gold_7': 'gold', '42_8': '42'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'rank_5': [0], '6_6': [0], 'gold_7': [1], '42_8': [2]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'south africa', '20', '10', '9', '39'], ['2', 'algeria', '8', '9', '8', '25'], ['3', 'tunisia', '5', '10', '5', '20'], ['4', 'kenya', '4', '4', '1', '9'], ['5', 'egypt', '2', '4', '7', '13'], ['6', 'seychelles', '1', '1', '3', '5'], ['7', 'senegal', '0', '1', '2', '3'], ['7', 'morocco', '0', '1', '2', '3'], ['9'... |
gardline group | https://en.wikipedia.org/wiki/Gardline_group | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28132970-5.html.csv | aggregation | the gardline group 's windfarm support vessels have an average max speed of 29 knots . | {'scope': 'all', 'col': '3', 'type': 'average', 'result': '29', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'max speed'], 'result': '29', 'ind': 0, 'tostr': 'avg { all_rows ; max speed }'}, '29'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; max speed } ; 29 } = true', 'tointer': 'the average of the max speed record of all rows is 29 .'} | round_eq { avg { all_rows ; max speed } ; 29 } = true | the average of the max speed record of all rows is 29 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'max speed_4': 4, '29_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'max speed_4': 'max speed', '29_5': '29'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'max speed_4': [0], '29_5': [1]} | ['vessel', 'built', 'max speed', 'length', 'breadth', 'flag', 'propulsion'] | [['gallion', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 1', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 2', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian 7', '2010', '30 knots', '20 m', '6.5 m', 'united kingdom', 'prop'], ['gardian... |
list of intel core i7 microprocessors | https://en.wikipedia.org/wiki/List_of_Intel_Core_i7_microprocessors | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18823880-15.html.csv | unique | the only intel core i7 microprocessor with a 8mb l3 cache to have a 3 ghz frequency is the core i7 - 3940xm . | {'scope': 'subset', 'row': '11', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '3 ghz', 'subset': {'col': '7', 'criterion': 'equal', 'value': '8 mb'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'l3 cache', '8 mb'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; l3 cache ; 8 mb }', 'tointer': 'select the rows whose l3 cache record fuzzily matches to 8 mb .'}, 'frequen... | and { only { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } } ; eq { hop { filter_eq { filter_eq { all_rows ; l3 cache ; 8 mb } ; frequency ; 3 ghz } ; model number } ; core i7 - 3940xm } } = true | select the rows whose l3 cache record fuzzily matches to 8 mb . among these rows , select the rows whose frequency record fuzzily matches to 3 ghz . there is only one such row in the table . the model number record of this unqiue row is core i7 - 3940xm . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'l3 cache_8': 8, '8 mb_9': 9, 'frequency_10': 10, '3 ghz_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'model number_12': 12, 'core i7 - 3940xm_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'l3 cache_8': 'l3 cache', '8 mb_9': '8 mb', 'frequency_10': 'frequency', '3 ghz_11': '3 ghz', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'model number_12': 'model n... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'l3 cache_8': [0], '8 mb_9': [0], 'frequency_10': [1], '3 ghz_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'model number_12': [3], 'core i7 - 3940xm_13': [4]} | ['model number', 'sspec number', 'cores', 'frequency', 'turbo', 'l2 cache', 'l3 cache', 'gpu model', 'gpu frequency', 'socket', 'i / o bus', 'release date', 'part number ( s )', 'release price ( usd )'] | [['standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power', 'standard power'], ['core i7 - 3610qm', 'sr0 mn ( e1 )', '4', '2.3 ghz', '8 / 8 / 9 ... |
usa today all - usa high school baseball team | https://en.wikipedia.org/wiki/USA_Today_All-USA_high_school_baseball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11677100-17.html.csv | majority | the majority of players on the usa today all - usa school baseball team were picked in the mlb draft . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'draft', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'mlb draft', 'draft'], 'result': True, 'ind': 0, 'tointer': 'for the mlb draft records of all rows , most of them fuzzily match to draft .', 'tostr': 'most_eq { all_rows ; mlb draft ; draft } = true'} | most_eq { all_rows ; mlb draft ; draft } = true | for the mlb draft records of all rows , most of them fuzzily match to draft . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'mlb draft_3': 3, 'draft_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'mlb draft_3': 'mlb draft', 'draft_4': 'draft'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'mlb draft_3': [0], 'draft_4': [0]} | ['player', 'position', 'school', 'hometown', 'mlb draft'] | [['dylan bundy', 'pitcher / infielder', 'owasso high school', 'owasso , ok', '1st round - 4th pick of 2010 draft ( rangers )'], ['kevin cron', 'catcher / pitcher', 'mountain pointe high school', 'phoenix , az', 'attended tcu'], ['francisco lindor', 'infielder', 'montverde academy', 'montverde , fl', '1st round - 9th pi... |
list of england national rugby union team results 1980 - 89 | https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1980%E2%80%9389 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178608-2.html.csv | count | england 's national rugby union team played against two different opposing teams in the venue of twickenham , london . | {'scope': 'all', 'criterion': 'equal', 'value': 'twickenham , london', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'twickenham , london'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record fuzzily matches to twickenham , london .', 'tostr': 'filter_eq { all_rows ; venue ; twickenham , london }'}], 'resul... | eq { count { filter_eq { all_rows ; venue ; twickenham , london } } ; 2 } = true | select the rows whose venue record fuzzily matches to twickenham , london . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'twickenham , london_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'twickenham , london_6': 'twickenham , london', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'twickenham , london_6': [0], '2_7': [2]} | ['opposing teams', 'against', 'date', 'venue', 'status'] | [['wales', '21', '17 / 01 / 1981', 'cardiff arms park , cardiff', 'five nations'], ['scotland', '17', '21 / 02 / 1981', 'twickenham , london', 'five nations'], ['ireland', '6', '07 / 03 / 1981', 'lansdowne road , dublin', 'five nations'], ['france', '16', '21 / 03 / 1981', 'twickenham , london', 'five nations'], ['arge... |
2008 german motorcycle grand prix | https://en.wikipedia.org/wiki/2008_German_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16878651-1.html.csv | majority | most of the competitors in the 2008 german motorcycle grand prix completed 30 laps . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '30', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'laps', '30'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are equal to 30 .', 'tostr': 'most_eq { all_rows ; laps ; 30 } = true'} | most_eq { all_rows ; laps ; 30 } = true | for the laps records of all rows , most of them are equal to 30 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '30_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '30_4': '30'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '30_4': [0]} | ['rider', 'manufacturer', 'laps', 'time', 'grid'] | [['casey stoner', 'ducati', '30', '47:30.057', '1'], ['valentino rossi', 'yamaha', '30', '+ 3.708', '7'], ['chris vermeulen', 'suzuki', '30', '+ 14.002', '14'], ['alex de angelis', 'honda', '30', '+ 14.124', '10'], ['andrea dovizioso', 'honda', '30', '+ 42.022', '4'], ['sylvain guintoli', 'ducati', '30', '+ 46.648', '1... |
2010 - 11 oklahoma city thunder season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Oklahoma_City_Thunder_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27712702-11.html.csv | superlative | in the 2010 - 11 oklahoma city thunder season , the highest attendance was on march 16th . | {'scope': 'all', 'col_superlative': '8', 'row_superlative': '9', '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', 'location attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; location attendance }'}, 'date'], 'result': 'march 16', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; location attendance } ; date }'}, 'march ... | eq { hop { argmax { all_rows ; location attendance } ; date } ; march 16 } = true | select the row whose location attendance record of all rows is maximum . the date record of this row is march 16 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, 'date_6': 6, 'march 16_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'location attendance_5': 'location attendance', 'date_6': 'date', 'march 16_7': 'march 16'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], 'date_6': [1], 'march 16_7': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['59', 'march 2', 'indiana', 'w 113 - 89 ( ot )', 'kevin durant , russell westbrook ( 21 )', 'serge ibaka ( 12 )', 'russell westbrook ( 9 )', 'oklahoma city arena 18203', '37 - 22'], ['60', 'march 4', 'atlanta', 'w 111 - 104 ( ot )', 'kevin durant ( 29 )', 'kevin durant ( 8 )', 'russell westbrook ( 9 )', 'philips aren... |
new zealand national football team | https://en.wikipedia.org/wiki/New_Zealand_national_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1023035-3.html.csv | count | 5 players in the team 's history scored 10 goals . | {'scope': 'all', 'criterion': 'equal', 'value': '10', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goals', '10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goals record is equal to 10 .', 'tostr': 'filter_eq { all_rows ; goals ; 10 }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; go... | eq { count { filter_eq { all_rows ; goals ; 10 } } ; 5 } = true | select the rows whose goals record is equal to 10 . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'goals_5': 5, '10_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'goals_5': 'goals', '10_6': '10', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'goals_5': [0], '10_6': [0], '5_7': [2]} | ['name', 'career', 'goals', 'caps', 'first cap', 'most recent cap'] | [['vaughan coveny', '1992 - 2006', '28', '64', '7 june 1992', '4 june 2006'], ['shane smeltz', '2003 -', '23', '49', 'united states 9 june 2003', 'new caledonia 21 march 2013'], ['steve sumner', '1976 - 1988', '22', '58', 'burma 13 september 1976', '23 june 1988'], ['brian turner', '1967 - 1982', '21', '59', 'australia... |
fiba eurobasket 2007 squads | https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12962773-16.html.csv | count | of the players in the fiba eurobasket 2007 squads , three came from the bot turów club . | {'scope': 'all', 'criterion': 'equal', 'value': 'bot turów', 'result': '3', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'current club', 'bot turów'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose current club record fuzzily matches to bot turów .', 'tostr': 'filter_eq { all_rows ; current club ; bot turów }'}], 'result': '3', ... | eq { count { filter_eq { all_rows ; current club ; bot turów } } ; 3 } = true | select the rows whose current club record fuzzily matches to bot turów . 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, 'current club_5': 5, 'bot turów_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', 'current club_5': 'current club', 'bot turów_6': 'bot turów', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'current club_5': [0], 'bot turów_6': [0], '3_7': [2]} | ['player', 'height', 'position', 'year born', 'current club'] | [['bartłomiej wołoszyn', '1.97', 'forward', '1986', 'anwil wloclawek'], ['andrzej pluta', '1.81', 'guard', '1974', 'anwil wloclawek'], ['robert skibniewski', '1.82', 'guard', '1983', 'bot turów'], ['robert witka', '2.06', 'forward', '1981', 'bot turów'], ['filip dylewicz', '2.02', 'forward', '1980', 'prokom trefl sopot... |
e. w. scripps company | https://en.wikipedia.org/wiki/E._W._Scripps_Company | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1847523-2.html.csv | count | there were eight different owners of the company in the year 2011 . | {'scope': 'all', 'criterion': 'equal', 'value': '2011', 'result': '9', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'owned since', '2011'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose owned since record is equal to 2011 .', 'tostr': 'filter_eq { all_rows ; owned since ; 2011 }'}], 'result': '9', 'ind': 1, 'tostr': 'count { f... | eq { count { filter_eq { all_rows ; owned since ; 2011 } } ; 9 } = true | select the rows whose owned since record is equal to 2011 . the number of such rows is 9 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'owned since_5': 5, '2011_6': 6, '9_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'owned since_5': 'owned since', '2011_6': '2011', '9_7': '9'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'owned since_5': [0], '2011_6': [0], '9_7': [2]} | ['city of license / market', 'station', 'channel ( tv / rf )', 'owned since', 'affiliation'] | [['phoenix', 'knxv - tv', '15 ( 15 )', '1985', 'abc'], ['bakersfield , california', 'kero - tv', '23 ( 10 )', '2011', 'abc'], ['bakersfield , california', 'kzkc - lp', '42', '2011', 'azteca américa'], ['san diego', 'kgtv', '10 ( 10 )', '2011', 'abc'], ['san diego', 'kzsd - lp', '41', '2011', 'azteca américa'], ['colora... |
list of street railways in canada | https://en.wikipedia.org/wiki/List_of_street_railways_in_Canada | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16927321-1.html.csv | superlative | the edmonton radial railway is the oldest railway that serves canada . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date ( from )'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date ( from ) }'}, 'name of system'], 'result': 'edmonton radial railway', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date ( from ) } ; name of sy... | eq { hop { argmin { all_rows ; date ( from ) } ; name of system } ; edmonton radial railway } = true | select the row whose date ( from ) record of all rows is minimum . the name of system record of this row is edmonton radial railway . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date (from)_5': 5, 'name of system_6': 6, 'edmonton radial railway_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date (from)_5': 'date ( from )', 'name of system_6': 'name of system', 'edmonton radial railway_7': 'edmonton radial railway'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date (from)_5': [0], 'name of system_6': [1], 'edmonton radial railway_7': [2]} | ['name of system', 'location', 'traction type', 'date ( from )', 'date ( to )'] | [['calgary municipal railway', 'calgary', 'electric', '5 jul 1909 25 may 1981', '29 dec 1950 -'], ['edmonton radial railway', 'edmonton', 'electric', '30 oct 1908 22 apr 1978', '1 sep 1951 -'], ['edmonton radial railway', 'edmonton', 'petrol ( gasoline )', '30 sep 1913', '1 apr 1914'], ['lake louise tramway', 'lake lou... |
wru division one north | https://en.wikipedia.org/wiki/WRU_Division_One_North | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14058433-5.html.csv | superlative | the caernarfon rfc club had the most points in the wru division one north . | {'scope': 'all', 'col_superlative': '12', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'club'], 'result': 'caernarfon rfc', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; club }'}, 'caernarfon rfc'], 'result': True, 'ind'... | eq { hop { argmax { all_rows ; points } ; club } ; caernarfon rfc } = true | select the row whose points record of all rows is maximum . the club record of this row is caernarfon rfc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'club_6': 6, 'caernarfon rfc_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'club_6': 'club', 'caernarfon rfc_7': 'caernarfon rfc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'club_6': [1], 'caernarfon rfc_7': [2]} | ['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['caernarfon rfc', '22', '18', '1', '3', '643', '235', '101', '24', '14', '1', '89'], ['colwyn bay rfc', '22', '18', '0', '4', '570', '256', '79', '29', '10', '3', '85'], ['n... |
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/2-11916083-28.html.csv | superlative | of all of the royal canadian mint numismatic coins from the 2000s , the one with the highest issue price was the great blue heron . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '7', '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', 'issue price'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; issue price }'}, 'theme'], 'result': 'great blue heron', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; issue price } ; theme }'}, 'great blue heron'], ... | eq { hop { argmax { all_rows ; issue price } ; theme } ; great blue heron } = true | select the row whose issue price record of all rows is maximum . the theme record of this row is great blue heron . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'issue price_5': 5, 'theme_6': 6, 'great blue heron_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'issue price_5': 'issue price', 'theme_6': 'theme', 'great blue heron_7': 'great blue heron'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'issue price_5': [0], 'theme_6': [1], 'great blue heron_7': [2]} | ['year', 'theme', 'artist', 'mintage', 'issue price'] | [['2002', '15th anniversary loonie', 'dora de pãdery - hunt', '67672', '39.95'], ['2004', 'jack miner bird sanctuary', 'susan taylor', 'n / a', '39.95'], ['2005', 'tufted puffin', 'n / a', 'n / a', '39.95'], ['2006', 'snowy owl', 'glen loates', '20000', '39.95'], ['2007', 'trumpeter swan', 'kerri burnett', '40000', '45... |
just legal | https://en.wikipedia.org/wiki/Just_Legal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2828803-1.html.csv | count | jonathan shapiro wrote who episodes of " just legal " . | {'scope': 'all', 'criterion': 'equal', 'value': 'jonathan shapiro', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'jonathan shapiro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to jonathan shapiro .', 'tostr': 'filter_eq { all_rows ; written by ; jonathan shapiro }'}], ... | eq { count { filter_eq { all_rows ; written by ; jonathan shapiro } } ; 2 } = true | select the rows whose written by record fuzzily matches to jonathan shapiro . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'written by_5': 5, 'jonathan shapiro_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'written by_5': 'written by', 'jonathan shapiro_6': 'jonathan shapiro', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'jonathan shapiro_6': [0], '2_7': [2]} | ['series', 'title', 'written by', 'directed by', 'original air date', 'production code', 'us viewers ( millions )'] | [['1', 'pilot', 'jonathan shapiro', 'andrew davis', 'september 19 , 2005', '475279', '3.440'], ['2', 'the runner', 'jonathan shapiro', 'dwight little', 'september 26 , 2005', '2t7001', '2.960'], ['3', 'the limit', 'rob bragin', 'john badham', 'october 3 , 2005', '2t7002', '2.880'], ['4', 'the body in the trunk', "craig... |
spain at the paralympics | https://en.wikipedia.org/wiki/Spain_at_the_Paralympics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12771081-2.html.csv | unique | the 1998 nagano games was the only time spain won 8 gold medals . | {'scope': 'all', 'row': '5', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '8', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '8'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 8 .', 'tostr': 'filter_eq { all_rows ; gold ; 8 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 8... | and { only { filter_eq { all_rows ; gold ; 8 } } ; eq { hop { filter_eq { all_rows ; gold ; 8 } ; games } ; 1998 nagano } } = true | select the rows whose gold record is equal to 8 . there is only one such row in the table . the games record of this unqiue row is 1998 nagano . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '8_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'games_9': 9, '1998 nagano_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '8_8': '8', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'games_9': 'games', '1998 nagano_10': '1998 nagano'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '8_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'games_9': [2], '1998 nagano_10': [3]} | ['games', 'gold', 'silver', 'bronze', 'total', 'rank'] | [['1984 innsbruck', '0', '0', '0', '0', '14'], ['1988 innsbruck', '1', '2', '1', '4', '11'], ['1992 tignes - albertsville', '0', '1', '3', '4', '16'], ['1994 lillehammer', '1', '6', '3', '10', '13'], ['1998 nagano', '8', '0', '0', '8', '7'], ['2002 salt lake city', '3', '3', '2', '8', '12'], ['2006 turin', '0', '1', '1... |
1978 u.s. open ( golf ) | https://en.wikipedia.org/wiki/1978_U.S._Open_%28golf%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17245471-4.html.csv | superlative | of the players tied second after two rounds of the 1978 us open , the largest number of strikes taken , by a player , in a single round was 73 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': 't2'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'place', 't2'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; place ; t2 }', 'tointer': 'select the rows whose place record fuzzily matches to t2 .'}, 'score'], 'result': '73 + 69 = 142', 'ind': 1, 'tostr': 'max... | eq { max { filter_eq { all_rows ; place ; t2 } ; score } ; 73 + 69 = 142 } = true | select the rows whose place record fuzzily matches to t2 . the maximum score record of these rows is 73 + 69 = 142 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'place_5': 5, 't2_6': 6, 'score_7': 7, '73 + 69 = 142_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'place_5': 'place', 't2_6': 't2', 'score_7': 'score', '73 + 69 = 142_8': '73 + 69 = 142'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'place_5': [0], 't2_6': [0], 'score_7': [1], '73 + 69 = 142_8': [2]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'andy north', 'united states', '70 + 70 = 140', '2'], ['t2', 'jack nicklaus', 'united states', '73 + 69 = 142', 'e'], ['t2', 'gary player', 'south africa', '71 + 71 = 142', 'e'], ['t2', 'j c snead', 'united states', '70 + 72 = 142', 'e'], ['t5', 'bobby clampett ( a )', 'united states', '70 + 73 = 143', '+ 1'], [... |
2010 - 11 orlando magic season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Orlando_Magic_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27700530-10.html.csv | count | in the 2010 - 11 orlando magic season , when the magic won , there were 5 times that dwight howard had at least a share of the high rebounds . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'dwight howard', 'result': '5', 'col': '6', '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 rebounds', 'dwight h... | eq { count { filter_eq { filter_eq { all_rows ; score ; w } ; high rebounds ; dwight howard } } ; 5 } = true | select the rows whose score record fuzzily matches to w . among these rows , select the rows whose high rebounds record fuzzily matches to dwight howard . the number of such rows is 5 . | 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 rebounds_8': 8, 'dwight howard_9': 9, '5_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 rebounds_8': 'high rebounds', 'dwight howard_9': 'dwight howard', '5_10': '5'} | {'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 rebounds_8': [1], 'dwight howard_9': [1], '5_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['18', 'december 1', 'chicago', 'w 107 - 78 ( ot )', 'jameer nelson ( 24 )', 'dwight howard ( 12 )', 'jameer nelson ( 9 )', 'united center 21435', '14 - 4'], ['19', 'december 3', 'detroit', 'w 104 - 91 ( ot )', 'brandon bass ( 27 )', 'marcin gortat ( 11 )', 'vince carter ( 9 )', 'the palace of auburn hills 18433', '15... |
2007 icc world twenty20 statistics | https://en.wikipedia.org/wiki/2007_ICC_World_Twenty20_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13219504-9.html.csv | comparative | the partnership of younis khan / shoaib malik had less runs than the partnership of gautam gambhir / virender sehwag . | {'row_1': '8', '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', 'partnerships', 'younis khan / shoaib malik'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose partnerships record fuzzily matches to younis khan / shoaib malik .', 'tostr': 'filter_eq { all_rows ; partners... | less { hop { filter_eq { all_rows ; partnerships ; younis khan / shoaib malik } ; runs ( balls ) } ; hop { filter_eq { all_rows ; partnerships ; gautam gambhir / virender sehwag } ; runs ( balls ) } } = true | select the rows whose partnerships record fuzzily matches to younis khan / shoaib malik . take the runs ( balls ) record of this row . select the rows whose partnerships record fuzzily matches to gautam gambhir / virender sehwag . take the runs ( balls ) record of this row . the first record is less than the second rec... | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'partnerships_7': 7, 'younis khan / shoaib malik_8': 8, 'runs (balls)_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'partnerships_11': 11, 'gautam gambhir / virender sehwag_12': 12, 'runs (balls)_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', 'partnerships_7': 'partnerships', 'younis khan / shoaib malik_8': 'younis khan / shoaib malik', 'runs (balls)_9': 'runs ( balls )', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'al... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'partnerships_7': [0], 'younis khan / shoaib malik_8': [0], 'runs (balls)_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'partnerships_11': [1], 'gautam gambhir / virender sehwag_12': [1], 'runs (balls)_... | ['runs ( balls )', 'wicket', 'partnerships', 'venue', 'date'] | [['145 ( 81 )', '1st', 'chris gayle / devon smith', 'johannesburg', '2007 - 09 - 11'], ['136 ( 88 )', '1st', 'gautam gambhir / virender sehwag', 'durban', '2007 - 09 - 19'], ['120 ( 57 )', '3rd', 'herschelle gibbs / justin kemp', 'johannesburg', '2007 - 09 - 11'], ['119 ( 75 )', '5th', 'shoaib malik / misbah - ul - haq... |
galicia , spain | https://en.wikipedia.org/wiki/Galicia%2C_Spain | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12837-1.html.csv | superlative | the highest number of sunlight hours in galicia , spain , is in the city of pontevedra . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '6', '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', 'sunlight hours'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; sunlight hours }'}, 'city / town'], 'result': 'pontevedra', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; sunlight hours } ; city / town }'}, 'ponte... | eq { hop { argmax { all_rows ; sunlight hours } ; city / town } ; pontevedra } = true | select the row whose sunlight hours record of all rows is maximum . the city / town record of this row is pontevedra . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'sunlight hours_5': 5, 'city / town_6': 6, 'pontevedra_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'sunlight hours_5': 'sunlight hours', 'city / town_6': 'city / town', 'pontevedra_7': 'pontevedra'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'sunlight hours_5': [0], 'city / town_6': [1], 'pontevedra_7': [2]} | ['city / town', 'july av t', 'rain', 'days with rain ( year / summer )', 'days with frost', 'sunlight hours'] | [['santiago de compostela', 'degree', 'mm ( in )', '141 / 19', '15', '1998'], ['a coruña', 'degree', 'mm ( in )', '131 / 19', '0', '1966'], ['lugo', 'degree', 'mm ( in )', '131 / 18', '42', '1821'], ['vigo', 'degree', 'mm ( in )', '130 / 18', '5', '2212'], ['ourense', 'degree', 'mm ( in )', '97 / 12', '30', '2043'], ['... |
2010 - 11 atlanta thrashers season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Atlanta_Thrashers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27537518-7.html.csv | unique | in the 2010-11 atlanta thrashers season , the only time the location was the bell centre was on january 2nd . | {'scope': 'all', 'row': '1', 'col': '7', 'col_other': '2', 'criterion': 'equal', 'value': 'bell centre', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'bell centre'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to bell centre .', 'tostr': 'filter_eq { all_rows ; location ; bell centre }'}], 'result': True, 'ind'... | and { only { filter_eq { all_rows ; location ; bell centre } } ; eq { hop { filter_eq { all_rows ; location ; bell centre } ; date } ; january 2 } } = true | select the rows whose location record fuzzily matches to bell centre . there is only one such row in the table . the date record of this unqiue row is january 2 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'bell centre_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'january 2_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'bell centre_8': 'bell centre', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'january 2_10': 'january 2'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'bell centre_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'january 2_10': [3]} | ['game', 'date', 'opponent', 'score', 'first star', 'decision', 'location', 'attendance', 'record', 'points'] | [['42', 'january 2', 'montreal canadiens', '4 - 3 ot', 'd byfuglien', 'o pavelec', 'bell centre', '21273', '21 - 15 - 6', '48'], ['43', 'january 5', 'florida panthers', '3 - 2', 'r peverley', 'o pavelec', 'bankatlantic center', '12803', '22 - 15 - 6', '50'], ['44', 'january 7', 'toronto maple leafs', '3 - 9', 'm grabov... |
1980 indycar season | https://en.wikipedia.org/wiki/1980_IndyCar_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10527215-2.html.csv | superlative | ontario city was the first location used in the 1980 indycar season . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date }'}, 'city / location'], 'result': 'ontario , california', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; city / location }'}, 'ontario , califor... | eq { hop { argmin { all_rows ; date } ; city / location } ; ontario , california } = true | select the row whose date record of all rows is minimum . the city / location record of this row is ontario , california . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'city / location_6': 6, 'ontario , california_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', 'city / location_6': 'city / location', 'ontario , california_7': 'ontario , california'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'city / location_6': [1], 'ontario , california_7': [2]} | ['sanctioning', 'race name', 'circuit', 'city / location', 'date'] | [['joint cart / usac ( crl )', 'datsun twin 200', 'ontario motor speedway', 'ontario , california', 'april 13'], ['joint cart / usac ( crl )', 'indianapolis 500 - mile race', 'indianapolis motor speedway', 'indianapolis , indiana', 'may 26'], ['joint cart / usac ( crl )', 'gould rex mays classic 150', 'milwaukee mile',... |
grey 's anatomy ( season 4 ) | https://en.wikipedia.org/wiki/Grey%27s_Anatomy_%28season_4%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11058032-1.html.csv | ordinal | the eighth episode in the season 4 series of grey 's anatomy had the second highest number of viewers in the season . | {'row': '8', 'col': '7', 'order': '2', 'col_other': '2', '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', 'us viewers ( millions )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; us viewers ( millions ) ; 2 }'}, 'no in season'], 'result': '8', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; us viewers ( mi... | eq { hop { nth_argmax { all_rows ; us viewers ( millions ) ; 2 } ; no in season } ; 8 } = true | select the row whose us viewers ( millions ) record of all rows is 2nd maximum . the no in season record of this row is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'us viewers (millions)_5': 5, '2_6': 6, 'no in season_7': 7, '8_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'us viewers (millions)_5': 'us viewers ( millions )', '2_6': '2', 'no in season_7': 'no in season', '8_8': '8'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'us viewers (millions)_5': [0], '2_6': [0], 'no in season_7': [1], '8_8': [2]} | ['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['62', '1', 'a change is gon na come', 'rob corn', 'shonda rhimes', 'september 27 , 2007', '20.93'], ['63', '2', 'love / addiction', 'james frawley', 'debora cahn', 'october 4 , 2007', '18.51'], ['64', '3', 'let the truth sting', 'dan minahan', 'mark wilding', 'october 11 , 2007', '19.04'], ['65', '4', 'the heart of t... |
toronto raptors all - time roster | https://en.wikipedia.org/wiki/Toronto_Raptors_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10015132-7.html.csv | comparative | chris garner began playing for the toronto raptors seven years before dion glover . | {'row_1': '3', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '7 years', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'chris garner'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to chris garner .', 'tostr': 'filter_eq { all_rows ; player ; chris garner }'... | eq { diff { hop { filter_eq { all_rows ; player ; chris garner } ; years in toronto } ; hop { filter_eq { all_rows ; player ; dion glover } ; years in toronto } } ; -7 years } = true | select the rows whose player record fuzzily matches to chris garner . take the years in toronto record of this row . select the rows whose player record fuzzily matches to dion glover . take the years in toronto record of this row . the second record is 7 years larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'chris garner_9': 9, 'years in toronto_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'dion glover_13': 13, 'years in toronto_14': 14, '-7 years_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'chris garner_9': 'chris garner', 'years in toronto_10': 'years in toronto', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11':... | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'chris garner_9': [0], 'years in toronto_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'dion glover_13': [1], 'years in toronto_14': [3], '-7 years_1... | ['player', 'no', 'nationality', 'position', 'years in toronto', 'school / club team'] | [['sundiata gaines', '2', 'united states', 'guard', '2011', 'georgia'], ['jorge garbajosa', '15', 'spain', 'forward', '2006 - 08', 'cb mã ¡ laga ( spain )'], ['chris garner', '0', 'united states', 'guard', '1997 - 98', 'memphis'], ['rudy gay', '22', 'united states', 'forward', '2013 - present', 'connecticut'], ['dion g... |
black swan - class sloop | https://en.wikipedia.org/wiki/Black_Swan-class_sloop | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1220125-3.html.csv | superlative | the chanticleer was the first sloop to be laid down in the black swan - class sloop . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'laid down'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; laid down }'}, 'name'], 'result': 'chanticleer', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; laid down } ; name }'}, 'chanticleer'], 'result': True, 'i... | eq { hop { argmin { all_rows ; laid down } ; name } ; chanticleer } = true | select the row whose laid down record of all rows is minimum . the name record of this row is chanticleer . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'laid down_5': 5, 'name_6': 6, 'chanticleer_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'laid down_5': 'laid down', 'name_6': 'name', 'chanticleer_7': 'chanticleer'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'laid down_5': [0], 'name_6': [1], 'chanticleer_7': [2]} | ['name', 'pennant', 'builder', 'laid down', 'launched', 'commissioned'] | [['chanticleer', 'u05', 'denny , dunbarton', '6 june 1941', '24 september 1942', '29 march 1943'], ['crane', 'u23', 'denny , dunbarton', '13 june 1941', '9 november 1942', '10 may 1943'], ['cygnet', 'u38', 'cammell laird , birkenhead', '30 august 1941', '28 july 1942', '1 december 1942'], ['kite', 'u87', 'cammell laird... |
nauru | https://en.wikipedia.org/wiki/Nauru | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-21302-1.html.csv | unique | boe is the only district that has less than 5 villages . | {'scope': 'all', 'row': '6', 'col': '6', 'col_other': '2', 'criterion': 'less_than', 'value': '5', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'no of villages', '5'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no of villages record is less than 5 .', 'tostr': 'filter_less { all_rows ; no of villages ; 5 }'}], 'result': True, 'ind': 1, 'tostr': 'onl... | and { only { filter_less { all_rows ; no of villages ; 5 } } ; eq { hop { filter_less { all_rows ; no of villages ; 5 } ; district } ; boe } } = true | select the rows whose no of villages record is less than 5 . there is only one such row in the table . the district record of this unqiue row is boe . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'no of villages_7': 7, '5_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'district_9': 9, 'boe_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'no of villages_7': 'no of villages', '5_8': '5', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'district_9': 'district', 'boe_10': 'boe'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'no of villages_7': [0], '5_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'district_9': [2], 'boe_10': [3]} | ['nr', 'district', 'former name', 'area ( ha )', 'population ( 2005 )', 'no of villages', 'density persons / ha'] | [['1', 'aiwo', 'aiue', '100', '1092', '8', '10.9'], ['2', 'anabar', 'anebwor', '143', '502', '15', '3.5'], ['3', 'anetan', 'añetañ', '100', '516', '12', '5.2'], ['4', 'anibare', 'anybody', '314', '160', '17', '0.5'], ['5', 'baiti', 'beidi', '123', '572', '15', '4.7'], ['6', 'boe', 'boi', '66', '795', '4', '12.0'], ['7'... |
kathleen horvath | https://en.wikipedia.org/wiki/Kathleen_Horvath | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17727652-3.html.csv | comparative | of the tournaments that kathleen horvath participated in , the one in indianapolis took place 21 days before the one in palm beach gardens . | {'row_1': '7', 'row_2': '8', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'indianapolis'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to indianapolis .', 'tostr': 'filter_eq { all_rows ; tournament ; indianapolis }'}, 'date'], ... | less { hop { filter_eq { all_rows ; tournament ; indianapolis } ; date } ; hop { filter_eq { all_rows ; tournament ; palm beach gardens } ; date } } = true | select the rows whose tournament record fuzzily matches to indianapolis . take the date record of this row . select the rows whose tournament record fuzzily matches to palm beach gardens . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'indianapolis_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'palm beach gardens_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'indianapolis_8': 'indianapolis', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tourname... | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'indianapolis_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'palm beach gardens_12': [1], 'date_13': [3]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['winner', 'january 19 , 1981', 'montreal', 'carpet ( i )', 'candy reynolds', '6 - 4 , 7 - 6'], ['winner', 'february 28 , 1983', 'nashville', 'carpet ( i )', 'marcela skuherská', '6 - 4 , 6 - 3'], ['runner - up', 'may 16 , 1983', 'berlin', 'clay', 'chris evert - lloyd', '4 - 6 , 6 - 7 ( 1 )'], ['winner', 'november 7 ,... |
1970 vfl season | https://en.wikipedia.org/wiki/1970_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1164217-19.html.csv | count | three of the games had crowds of over 25,000 people . | {'scope': 'all', 'criterion': 'greater_than', 'value': '25000', 'result': '3', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'crowd', '25000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose crowd record is greater than 25000 .', 'tostr': 'filter_greater { all_rows ; crowd ; 25000 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { fi... | eq { count { filter_greater { all_rows ; crowd ; 25000 } } ; 3 } = true | select the rows whose crowd record is greater than 25000 . 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, 'crowd_5': 5, '25000_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'crowd_5': 'crowd', '25000_6': '25000', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '25000_6': [0], '3_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '10.23 ( 83 )', 'north melbourne', '11.15 ( 81 )', 'western oval', '13118', '8 august 1970'], ['essendon', '12.16 ( 88 )', 'fitzroy', '14.10 ( 94 )', 'windy hill', '13572', '8 august 1970'], ['richmond', '9.10 ( 64 )', 'melbourne', '18.10 ( 118 )', 'mcg', '25158', '8 august 1970'], ['south melbourne', '1... |
gymnastics at the 2007 pan american games | https://en.wikipedia.org/wiki/Gymnastics_at_the_2007_Pan_American_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12320552-17.html.csv | unique | brazil is the only team to win 7 gold medals in gymnastics at the 2007 pan american games . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': '7', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 7 .', 'tostr': 'filter_eq { all_rows ; gold ; 7 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 7... | and { only { filter_eq { all_rows ; gold ; 7 } } ; eq { hop { filter_eq { all_rows ; gold ; 7 } ; nation } ; brazil ( bra ) } } = true | select the rows whose gold record is equal to 7 . there is only one such row in the table . the nation record of this unqiue row is brazil ( bra ) . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '7_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'brazil (bra)_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '7_8': '7', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'brazil (bra)_10': 'brazil ( bra )'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '7_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'brazil (bra)_10': [3]} | ['nation', 'gold', 'silver', 'bronze', 'total'] | [['united states ( usa )', '9', '10', '4', '23'], ['brazil ( bra )', '7', '2', '7', '16'], ['canada ( can )', '4', '2', '3', '9'], ['venezuela ( ven )', '3', '0', '1', '4'], ['puerto rico ( pur )', '2', '0', '3', '5'], ['colombia ( col )', '0', '3', '0', '3'], ['cuba ( cub )', '0', '3', '0', '3'], ['mexico ( mex )', '0... |
american idol ( season 10 ) | https://en.wikipedia.org/wiki/American_Idol_%28season_10%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27455867-1.html.csv | unique | september 22 , 2010 audition is the one for that month during the first auditions of american idol ( season 10 ) . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'september', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first audition date', 'september'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first audition date record fuzzily matches to september .', 'tostr': 'filter_eq { all_rows ; first audition date ; september }'}], 'result': True, 'in... | only { filter_eq { all_rows ; first audition date ; september } } = true | select the rows whose first audition date record fuzzily matches to september . 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, 'first audition date_4': 4, 'september_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'first audition date_4': 'first audition date', 'september_5': 'september'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'first audition date_4': [0], 'september_5': [0]} | ['episode air date', 'audition city', 'first audition date', 'audition venue', 'callback audition date', 'callback venue', 'golden tickets'] | [['january 19 , 2011', 'east rutherford , new jersey', 'august 3 , 2010', 'izod center', 'september 28 - 30 , 2010', 'liberty house restaurant', '51'], ['january 20 , 2011', 'new orleans , louisiana', 'july 26 , 2010', 'new orleans arena', 'october 17 - 18 , 2010', 'hilton riverside hotel', '37'], ['january 26 , 2011',... |
list of united states national ice hockey team rosters | https://en.wikipedia.org/wiki/List_of_United_States_national_ice_hockey_team_rosters | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15715109-14.html.csv | superlative | phil verchota was the oldest person on the united states ice hockey roster . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '20', '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', 'birthdate'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; birthdate }'}, 'name'], 'result': 'phil verchota', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; birthdate } ; name }'}, 'phil verchota'], 'result': True... | eq { hop { argmin { all_rows ; birthdate } ; name } ; phil verchota } = true | select the row whose birthdate record of all rows is minimum . the name record of this row is phil verchota . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'birthdate_5': 5, 'name_6': 6, 'phil verchota_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'birthdate_5': 'birthdate', 'name_6': 'name', 'phil verchota_7': 'phil verchota'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'birthdate_5': [0], 'name_6': [1], 'phil verchota_7': [2]} | ['position', 'jersey', 'name', 'height ( cm )', 'weight ( kg )', 'birthdate', 'birthplace', 'previous club / team'] | [['g', '29', 'marc behrend', '185', '84', '11 january 1961', 'madison , wisconsin', 'university of wisconsin'], ['g', '1', 'bob mason', '185', '82', '22 april 1961', 'international falls , minnesota', 'university of minnesota - duluth'], ['d', '21', 'chris chelios', '185', '86', '25 january 1962', 'evergreen park , ill... |
swimming at the 2008 summer olympics - women 's 100 metre backstroke | https://en.wikipedia.org/wiki/Swimming_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_100_metre_backstroke | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18625437-4.html.csv | comparative | kseniya moskvina had a slower time than sophie edington . | {'row_1': '8', 'row_2': '7', 'col': '5', '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', 'name', 'kseniya moskvina'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to kseniya moskvina .', 'tostr': 'filter_eq { all_rows ; name ; kseniya moskvina }'}, 'time'], 're... | greater { hop { filter_eq { all_rows ; name ; kseniya moskvina } ; time } ; hop { filter_eq { all_rows ; name ; sophie edington } ; time } } = true | select the rows whose name record fuzzily matches to kseniya moskvina . take the time record of this row . select the rows whose name record fuzzily matches to sophie edington . take the time 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, 'name_7': 7, 'kseniya moskvina_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'sophie edington_12': 12, 'time_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', 'name_7': 'name', 'kseniya moskvina_8': 'kseniya moskvina', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'soph... | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'kseniya moskvina_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'sophie edington_12': [1], 'time_13': [3]} | ['rank', 'lane', 'name', 'nationality', 'time'] | [['1', '5', 'natalie coughlin', 'united states', '59.43'], ['2', '4', 'reiko nakamura', 'japan', '59.64'], ['3', '3', 'gemma spofforth', 'great britain', '59.79'], ['4', '6', 'hanae ito', 'japan', '1:00.13'], ['5', '7', 'elizabeth simmonds', 'great britain', '1:00.39'], ['6', '2', 'julia wilkinson', 'canada', '1:00.60'... |
united states house of representatives elections , 2000 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2000 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341423-22.html.csv | comparative | dale kildee has a first elected year which is earlier than that of fred upton . | {'row_1': '7', 'row_2': '5', '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', 'dale kildee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose incumbent record fuzzily matches to dale kildee .', 'tostr': 'filter_eq { all_rows ; incumbent ; dale kildee }'}, 'first elected'... | less { hop { filter_eq { all_rows ; incumbent ; dale kildee } ; first elected } ; hop { filter_eq { all_rows ; incumbent ; fred upton } ; first elected } } = true | select the rows whose incumbent record fuzzily matches to dale kildee . take the first elected record of this row . select the rows whose incumbent record fuzzily matches to fred upton . 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, 'dale kildee_8': 8, 'first elected_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'incumbent_11': 11, 'fred upton_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', 'dale kildee_8': 'dale kildee', 'first elected_9': 'first elected', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'incumbent_1... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'incumbent_7': [0], 'dale kildee_8': [0], 'first elected_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'incumbent_11': [1], 'fred upton_12': [1], 'first elected_13': [3]} | ['district', 'incumbent', 'party', 'first elected', 'results', 'candidates'] | [['michigan 1', 'bart stupak', 'democratic', '1992', 're - elected', 'bart stupak ( d ) 59 % chuck yob ( r ) 41 %'], ['michigan 2', 'pete hoekstra', 'republican', '1992', 're - elected', 'pete hoekstra ( r ) 65 % bob shrauger ( d ) 34 %'], ['michigan 3', 'vern ehlers', 'republican', '1993', 're - elected', 'vern ehlers... |
united states house of representatives elections in virginia , 2008 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections_in_Virginia%2C_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17503169-1.html.csv | majority | the majority of these politicians were successfully re-elected in 2008 . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 're - election', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', '2008 status', 're - election'], 'result': True, 'ind': 0, 'tointer': 'for the 2008 status records of all rows , most of them fuzzily match to re - election .', 'tostr': 'most_eq { all_rows ; 2008 status ; re - election } = true'} | most_eq { all_rows ; 2008 status ; re - election } = true | for the 2008 status records of all rows , most of them fuzzily match to re - election . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, '2008 status_3': 3, 're - election_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', '2008 status_3': '2008 status', 're - election_4': 're - election'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], '2008 status_3': [0], 're - election_4': [0]} | ['district', 'incumbent', '2008 status', 'democratic', 'republican', 'independent green', 'libertarian', 'other party'] | [['1', 'rob wittman', 're - election', 'bill day', 'rob wittman', 'none', 'nathan larson', 'none'], ['2', 'thelma drake', 're - election', 'glenn nye', 'thelma drake', 'none', 'none', 'none'], ['3', 'robert c scott', 're - election', 'robert c scott', 'none', 'none', 'none', 'none'], ['4', 'randy forbes', 're - electio... |
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/2-17832085-4.html.csv | aggregation | in the 1965 - 66 segunda división , the average number of losses was 10.94 . | {'scope': 'all', 'col': '7', 'type': 'average', 'result': '10.94', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'losses'], 'result': '10.94', 'ind': 0, 'tostr': 'avg { all_rows ; losses }'}, '10.94'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; losses } ; 10.94 } = true', 'tointer': 'the average of the losses record of all rows is 10.94 .'} | round_eq { avg { all_rows ; losses } ; 10.94 } = true | the average of the losses record of all rows is 10.94 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'losses_4': 4, '10.94_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'losses_4': 'losses', '10.94_5': '10.94'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'losses_4': [0], '10.94_5': [1]} | ['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference'] | [['1', 'hércules cf', '30', '39', '16', '7', '7', '44', '24', '+ 20'], ['2', 'granada cf', '30', '37', '16', '5', '9', '40', '29', '+ 11'], ['3', 'algeciras cf', '30', '35', '14', '7', '9', '42', '29', '+ 13'], ['4', 'real valladolid', '30', '35', '13', '9', '8', '49', '32', '+ 17'], ['5', 'levante ud', '30', '34', '13... |
wru division one east | https://en.wikipedia.org/wiki/WRU_Division_One_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12784856-5.html.csv | ordinal | for wru division one east , the 2nd highest number of losses was by fleur de lys rfc . | {'row': '11', 'col': '4', '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', 'lost', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; lost ; 2 }'}, 'club'], 'result': 'fleur de lys rfc', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; lost ; 2 } ; club }'}, 'fleur de lys rfc']... | eq { hop { nth_argmax { all_rows ; lost ; 2 } ; club } ; fleur de lys rfc } = true | select the row whose lost record of all rows is 2nd maximum . the club record of this row is fleur de lys rfc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'lost_5': 5, '2_6': 6, 'club_7': 7, 'fleur de lys rfc_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', 'lost_5': 'lost', '2_6': '2', 'club_7': 'club', 'fleur de lys rfc_8': 'fleur de lys rfc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'lost_5': [0], '2_6': [0], 'club_7': [1], 'fleur de lys rfc_8': [2]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['pontypool rfc', '22', '2', '2', '648', '274', '81', '32', '12', '1', '89'], ['caerphilly rfc', '22', '2', '4', '482', '316', '56', '37', '7', '3', '78'], ['blackwood rfc', '22', '2', '6', '512', '378', '60', '42', '8', '3', '71'], ['bargoed rfc', '22', '0', '8', '538', '449', '72', '52', '10', '4', '70'], ['uwic rfc... |
premier league of bosnia and herzegovina | https://en.wikipedia.org/wiki/Premier_League_of_Bosnia_and_Herzegovina | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1474099-1.html.csv | superlative | sarajevo b , c is the club of bosnia and herzegovina that has the highest number of seasons in the top division . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '9', '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', 'number of seasons in top division'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; number of seasons in top division }'}, 'club'], 'result': 'sarajevo b , c', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; number ... | eq { hop { argmax { all_rows ; number of seasons in top division } ; club } ; sarajevo b , c } = true | select the row whose number of seasons in top division record of all rows is maximum . the club record of this row is sarajevo b , c . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'number of seasons in top division_5': 5, 'club_6': 6, 'sarajevo b , c_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'number of seasons in top division_5': 'number of seasons in top division', 'club_6': 'club', 'sarajevo b , c_7': 'sarajevo b , c'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'number of seasons in top division_5': [0], 'club_6': [1], 'sarajevo b , c_7': [2]} | ['club', 'position in 2012 - 13', 'first season in top division', 'number of seasons in top division', 'number of seasons in premier league a', 'first season of current spell in top division', 'top division titles', 'last top division title'] | [['borac b', '003 3rd', '1961 - 62', '23', '9', '2008 - 09', '1', '2010 - 11'], ['čelik b , c', '004 4th', '1966 - 67', '30', '13', '2000 - 01', '3 d', '1996 - 97'], ['gošk ( r )', '015 15th', '2011 - 12', '2', '2', '2011 - 12', '0', 'n / a'], ['gradina ( r )', '016 16th', '2012 - 13', '1', '1', '2012 - 13', '0', 'n / ... |
max biaggi | https://en.wikipedia.org/wiki/Max_Biaggi | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1694580-3.html.csv | count | there were two years where max biaggi raced 28 times . | {'scope': 'all', 'criterion': 'equal', 'value': '28', 'result': '2', 'col': '2', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'race', '28'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose race record is equal to 28 .', 'tostr': 'filter_eq { all_rows ; race ; 28 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; race ... | eq { count { filter_eq { all_rows ; race ; 28 } } ; 2 } = true | select the rows whose race record is equal to 28 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'race_5': 5, '28_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'race_5': 'race', '28_6': '28', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'race_5': [0], '28_6': [0], '2_7': [2]} | ['season', 'race', 'podium', 'pole', 'flap'] | [['2007', '25', '17', '0', '5'], ['2008', '28', '7', '0', '1'], ['2009', '28', '9', '0', '1'], ['2010', '26', '14', '2', '2'], ['2011', '21', '12', '2', '5'], ['2012', '27', '11', '1', '5'], ['total', '155', '70', '5', '19']] |
sophie ferguson | https://en.wikipedia.org/wiki/Sophie_Ferguson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15179071-3.html.csv | count | two tournaments were played on a carpet surface by sophie ferguson . | {'scope': 'all', 'criterion': 'equal', 'value': 'carpet', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'carpet'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose surface record fuzzily matches to carpet .', 'tostr': 'filter_eq { all_rows ; surface ; carpet }'}], 'result': '2', 'ind': 1, 'tostr': 'coun... | eq { count { filter_eq { all_rows ; surface ; carpet } } ; 2 } = true | select the rows whose surface record fuzzily matches to carpet . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'surface_5': 5, 'carpet_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'surface_5': 'surface', 'carpet_6': 'carpet', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'carpet_6': [0], '2_7': [2]} | ['outcome', 'date', 'tournament', 'surface', 'partner', 'opponents in the final', 'score'] | [['runner - up', '14 august 2005', 'wuxi , china', 'hard', 'casey dellacqua', 'mi - ra jeon wynne prakusya', '2 - 6 6 - 7 ( 6 )'], ['runner - up', '12 november 2006', 'mount gambier , australia', 'hard', 'daniella dominikovic', 'natalie grandin christina wheeler', '4 - 6 6 - 4 4 - 6'], ['runner - up', '20 april 2007', ... |
tax parity for health plan beneficiaries act | https://en.wikipedia.org/wiki/Tax_Parity_for_Health_Plan_Beneficiaries_Act | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13829540-1.html.csv | count | for the tax parity for health plan beneficiaries act , there were 5 occasions where it was introduced in the month of june . | {'scope': 'all', 'criterion': 'equal', 'value': 'june', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date introduced', 'june'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date introduced record fuzzily matches to june .', 'tostr': 'filter_eq { all_rows ; date introduced ; june }'}], 'result': '5', 'ind':... | eq { count { filter_eq { all_rows ; date introduced ; june } } ; 5 } = true | select the rows whose date introduced record fuzzily matches to june . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date introduced_5': 5, 'june_6': 6, '5_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date introduced_5': 'date introduced', 'june_6': 'june', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date introduced_5': [0], 'june_6': [0], '5_7': [2]} | ['congress', 'bill number ( s )', 'date introduced', 'sponsor ( s )', 'of cosponsors', 'latest status'] | [['112th congress', 's 1171', 'june 9 , 2011', 'sen charles e schumer ( d - ny )', '19', 'referred to the senate committee on finance'], ['112th congress', 'hr 2088', 'june 2 , 2011', 'rep jim mcdermott ( d - wa )', '74', 'referred to the house committee on ways and means'], ['111th congress', 's 1153', 'may 21 , 2009'... |
list of west indies test wicket - keepers | https://en.wikipedia.org/wiki/List_of_West_Indies_Test_wicket-keepers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27771406-1.html.csv | aggregation | the average number of catches for all west indies test wicket - keepers is 19.5 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '19.5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'catches'], 'result': '19.5', 'ind': 0, 'tostr': 'avg { all_rows ; catches }'}, '19.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; catches } ; 19.5 } = true', 'tointer': 'the average of the catches record of all rows is 19.5 .'} | round_eq { avg { all_rows ; catches } ; 19.5 } = true | the average of the catches record of all rows is 19.5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'catches_4': 4, '19.5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'catches_4': 'catches', '19.5_5': '19.5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'catches_4': [0], '19.5_5': [1]} | ['no', 'player', 'club', 'test career', 'tests', 'catches', 'stumpings', 'total dismissals'] | [['2', 'errol hunte', 'trinidad and tobago', '1930', '3', '5', '0', '5'], ['3', 'ivan barrow', 'jamaica', '1930 - 1939', '11', '17', '5', '22'], ['4', 'cyril christiani', 'british guiana', '1935', '4', '6', '1', '7'], ['8', 'alfred binns', 'jamaica', '1953 - 1956', '5', '14', '3', '17'], ['9', 'ralph legall', 'trinidad... |
1962 - 63 illinois fighting illini men 's basketball team | https://en.wikipedia.org/wiki/1962%E2%80%9363_Illinois_Fighting_Illini_men%27s_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22824297-1.html.csv | unique | tony latham is the only player on 1962 - 63 illinois fighting illini men 's basketball team that has a height of 6-10 . | {'scope': 'all', 'row': '8', 'col': '6', 'col_other': '2', 'criterion': 'equal', 'value': '6 - 10', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'height', '6 - 10'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose height record fuzzily matches to 6 - 10 .', 'tostr': 'filter_eq { all_rows ; height ; 6 - 10 }'}], 'result': True, 'ind': 1, 'tostr': 'only {... | and { only { filter_eq { all_rows ; height ; 6 - 10 } } ; eq { hop { filter_eq { all_rows ; height ; 6 - 10 } ; player } ; tony latham } } = true | select the rows whose height record fuzzily matches to 6 - 10 . there is only one such row in the table . the player record of this unqiue row is tony latham . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'height_7': 7, '6 - 10_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'tony latham_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'height_7': 'height', '6 - 10_8': '6 - 10', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'tony latham_10': 'tony latham'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'height_7': [0], '6 - 10_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'tony latham_10': [3]} | ['no', 'player', 'hometown', 'class', 'position', 'height', 'weight'] | [['10', 'larry bauer', 'springfield , illinois', 'so', 'forward', '6 - 7', '207'], ['11', 'bob meadows', 'collinsville , illinois', 'so', 'guard', '5 - 7', '157'], ['12', 'tal brody', 'trenton , new jersey / central high school', 'so', 'guard', '6 - 2', '165'], ['14', 'john love', 'ottawa , illinois', 'jr', 'forward', ... |
nevada gaming area | https://en.wikipedia.org/wiki/Nevada_gaming_area | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25438110-5.html.csv | count | two of the counties in the nevada gaming area are serviced by the i-80 road . | {'scope': 'all', 'criterion': 'equal', 'value': 'i - 80', 'result': '2', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'road', 'i - 80'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose road record fuzzily matches to i - 80 .', 'tostr': 'filter_eq { all_rows ; road ; i - 80 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filte... | eq { count { filter_eq { all_rows ; road ; i - 80 } } ; 2 } = true | select the rows whose road record fuzzily matches to i - 80 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'road_5': 5, 'i - 80_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'road_5': 'road', 'i - 80_6': 'i - 80', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'road_5': [0], 'i - 80_6': [0], '2_7': [2]} | ['casinos', 'county', 'road', '1 - jul - 08', 'fy07 millions', 'fy08 millions', 'fy09 millions'] | [['149', 'clark', 'i - 15', '1865746', '10538', '10172', '9081'], ['32', 'washoe', 'i - 80', '410443', '1045', '977', '856'], ['17', 'elko', 'i - 80', '47071', '324', '303', '279'], ['5', 'south lake tahoe', 'route 50', '45180', '283', '307', '264'], ['14', 'carson valley', 'route 395', '54867', '120', '114', '102']] |
yanam | https://en.wikipedia.org/wiki/Yanam | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1404939-5.html.csv | majority | most of the colonies in the yanam have a treaty of cession of 28 may 1956 . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '28 may 1956', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'treaty of cession', '28 may 1956'], 'result': True, 'ind': 0, 'tointer': 'for the treaty of cession records of all rows , most of them fuzzily match to 28 may 1956 .', 'tostr': 'most_eq { all_rows ; treaty of cession ; 28 may 1956 } = true'} | most_eq { all_rows ; treaty of cession ; 28 may 1956 } = true | for the treaty of cession records of all rows , most of them fuzzily match to 28 may 1956 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'treaty of cession_3': 3, '28 may 1956_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'treaty of cession_3': 'treaty of cession', '28 may 1956_4': '28 may 1956'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'treaty of cession_3': [0], '28 may 1956_4': [0]} | ['colony', 'liberation', 'de facto transfer', 'treaty of cession', 'de jure transfer', 'merger'] | [['pondichéry', '-', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963'], ['chandernagore', '-', '26 june 1949', '28 february 1951', '9 june 1952', '1 october 1954'], ['karikal', '-', '1 november 1954', '28 may 1956', '16 august 1963', '1 july 1963'], ['mahé', '16 june 1954', '1 november 1954', '28 may 1... |
list of districts of west bengal | https://en.wikipedia.org/wiki/List_of_districts_of_West_Bengal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2527063-3.html.csv | superlative | out of all the districts in west bengal , kolkata has the worst growth rate . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '10', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'growth rate'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; growth rate }'}, 'district'], 'result': 'kolkata', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; growth rate } ; district }'}, 'kolkata'], 'result': Tr... | eq { hop { argmin { all_rows ; growth rate } ; district } ; kolkata } = true | select the row whose growth rate record of all rows is minimum . the district record of this row is kolkata . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'growth rate_5': 5, 'district_6': 6, 'kolkata_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'growth rate_5': 'growth rate', 'district_6': 'district', 'kolkata_7': 'kolkata'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'growth rate_5': [0], 'district_6': [1], 'kolkata_7': [2]} | ['rank', 'district', 'population', 'growth rate', 'sex ratio', 'literacy', 'density / km'] | [['2', 'north 24 parganas', '10082852', '12.86', '949', '84.95', '2463'], ['6', 'south 24 parganas', '8153176', '18.05', '949', '78.57', '819'], ['7', 'barddhaman', '7723663', '12.01', '943', '77.15', '1100'], ['9', 'murshidabad', '7102430', '21.07', '957', '67.53', '1334'], ['14', 'west midnapore', '5943300', '14.44',... |
2004 - 05 isu junior grand prix | https://en.wikipedia.org/wiki/2004%E2%80%9305_ISU_Junior_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12392757-3.html.csv | aggregation | for the 2004 - 05 isu junior grand prix the total number of gold medals was 36 . | {'scope': 'all', 'col': '3', 'type': 'sum', 'result': '36', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'gold'], 'result': '36', 'ind': 0, 'tostr': 'sum { all_rows ; gold }'}, '36'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; gold } ; 36 } = true', 'tointer': 'the sum of the gold record of all rows is 36 .'} | round_eq { sum { all_rows ; gold } ; 36 } = true | the sum of the gold record of all rows is 36 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'gold_4': 4, '36_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '36_5': '36'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'gold_4': [0], '36_5': [1]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'united states', '8', '13', '15', '36'], ['2', 'russia', '10', '7', '7', '24'], ['3', 'japan', '7', '4', '3', '14'], ['3', 'canada', '4', '6', '4', '14'], ['4', 'italy', '2', '1', '1', '4'], ['5', 'south korea', '1', '2', '0', '3'], ['5', 'france', '1', '0', '2', '3'], ['6', 'finland', '2', '0', '0', '2'], ['6',... |
2007 german motorcycle grand prix | https://en.wikipedia.org/wiki/2007_German_motorcycle_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12262589-1.html.csv | majority | most of the drivers completed 30 laps drive during the 2007 german motorcycle grand prix . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '30', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'laps', '30'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are equal to 30 .', 'tostr': 'most_eq { all_rows ; laps ; 30 } = true'} | most_eq { all_rows ; laps ; 30 } = true | for the laps records of all rows , most of them are equal to 30 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '30_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '30_4': '30'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '30_4': [0]} | ['rider', 'manufacturer', 'laps', 'time / retired', 'grid'] | [['dani pedrosa', 'honda', '30', '41:53.196', '2'], ['loris capirossi', 'ducati', '30', '+ 13.166', '7'], ['nicky hayden', 'honda', '30', '+ 16.771', '14'], ['colin edwards', 'yamaha', '30', '+ 18.299', '13'], ['casey stoner', 'ducati', '30', '+ 31.426', '1'], ['marco melandri', 'honda', '30', '+ 31.917', '3'], ['john ... |
kingsport mets | https://en.wikipedia.org/wiki/Kingsport_Mets | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1196050-1.html.csv | unique | 1977 was the only year that bob didier was the manager of the kingsport mets . | {'scope': 'all', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'bob didier', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manager', 'bob didier'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manager record fuzzily matches to bob didier .', 'tostr': 'filter_eq { all_rows ; manager ; bob didier }'}], 'result': True, 'ind': 1, '... | and { only { filter_eq { all_rows ; manager ; bob didier } } ; eq { hop { filter_eq { all_rows ; manager ; bob didier } ; year } ; 1977 } } = true | select the rows whose manager record fuzzily matches to bob didier . there is only one such row in the table . the year record of this unqiue row is 1977 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manager_7': 7, 'bob didier_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '1977_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manager_7': 'manager', 'bob didier_8': 'bob didier', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '1977_10': '1977'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manager_7': [0], 'bob didier_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '1977_10': [3]} | ['year', 'record', 'finish', 'manager', 'playoffs'] | [['1974', '31 - 39', '7th', 'hoyt wilhelm', 'none'], ['1975', '33 - 33', '6th', 'gene hassell', 'none'], ['1976', '25 - 42', '8th', 'bobby dews', 'none'], ['1977', '43 - 27', '2nd', 'bob didier', 'none'], ['1978', '33 - 37', '5th', 'eddie haas', 'none'], ['1979', '39 - 31', '2nd', 'gene hassell', 'none']] |
list of serbian submissions for the academy award for best foreign language film | https://en.wikipedia.org/wiki/List_of_Serbian_submissions_for_the_Academy_Award_for_Best_Foreign_Language_Film | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22265716-1.html.csv | count | two of the serbian submissions for the academy award for best foreign language film were after the year 2000 . | {'scope': 'all', 'criterion': 'greater_than_eq', 'value': '2000', 'result': '2', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'year ( ceremony )', '2000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year ( ceremony ) record is greater than or equal to 2000 .', 'tostr': 'filter_greater_eq { all_rows ; year ( ceremony ) ; 2000 ... | eq { count { filter_greater_eq { all_rows ; year ( ceremony ) ; 2000 } } ; 2 } = true | select the rows whose year ( ceremony ) record is greater than or equal to 2000 . 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, 'year (ceremony)_5': 5, '2000_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', 'year (ceremony)_5': 'year ( ceremony )', '2000_6': '2000', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'year (ceremony)_5': [0], '2000_6': [0], '2_7': [2]} | ['year ( ceremony )', 'film title used in nomination', 'original title', 'director', 'result'] | [['1994 ( 67th )', 'vukovar poste restante', 'вуковар , једна прича', 'boro drašković', 'not nominated'], ['1995 ( 68th )', 'underground', 'подземље', 'emir kusturica', 'not nominated'], ['1996 ( 69th )', 'pretty village , pretty flame', 'лепа села лепо горе', 'srđan dragojević', 'not nominated'], ['1997 ( 70th )', 'th... |
1941 vfl season | https://en.wikipedia.org/wiki/1941_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-13.html.csv | unique | only one home team scored over 20 in the 1941 vfl season . | {'scope': 'all', 'row': '2', 'col': '2', 'col_other': 'n/a', 'criterion': 'greater_than', 'value': '20', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home team score record is greater than 20 .', 'tostr': 'filter_greater { all_rows ; home team score ; 20 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter... | only { filter_greater { all_rows ; home team score ; 20 } } = true | select the rows whose home team score record is greater than 20 . there is only one such row in the table . | 2 | 2 | {'only_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'home team score_4': 4, '20_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'home team score_4': 'home team score', '20_5': '20'} | {'only_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'home team score_4': [0], '20_5': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '18.16 ( 124 )', 'south melbourne', '10.13 ( 73 )', 'mcg', '23000', '26 july 1941'], ['collingwood', '22.20 ( 152 )', 'hawthorn', '12.13 ( 85 )', 'victoria park', '4000', '26 july 1941'], ['carlton', '12.11 ( 83 )', 'richmond', '11.18 ( 84 )', 'princes park', '27000', '26 july 1941'], ['st kilda', '18.14... |
wushu tournament beijing 2008 | https://en.wikipedia.org/wiki/Wushu_Tournament_Beijing_2008 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17660359-12.html.csv | count | in the wushu tournament beijing 2008 , among the top 3 ranked athletes , 2 of them have total score of 19.30 and higher . | {'scope': 'subset', 'criterion': 'greater_than_eq', 'value': '19.3', 'result': '2', 'col': '5', 'subset': {'col': '1', 'criterion': 'less_than', 'value': '4'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'rank', '4'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; rank ; 4 }', 'tointer': 'select the rows whose rank record is less than 4 .'}, 'total', '19.3'], 'result': Non... | eq { count { filter_greater_eq { filter_less { all_rows ; rank ; 4 } ; total ; 19.3 } } ; 2 } = true | select the rows whose rank record is less than 4 . among these rows , select the rows whose total record is greater than or equal to 19.3 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_eq_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'rank_6': 6, '4_7': 7, 'total_8': 8, '19.3_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_eq_1': 'filter_greater_eq', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'rank_6': 'rank', '4_7': '4', 'total_8': 'total', '19.3_9': '19.3', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_eq_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'rank_6': [0], '4_7': [0], 'total_8': [1], '19.3_9': [1], '2_10': [3]} | ['rank', 'athlete', 'qiangshu', 'jianshu', 'total'] | [['1', 'ma lingjuan ( chn )', '9.85', '9.75', '19.60'], ['2', 'han jing ( mac )', '9.65', '9.65', '19.30'], ['3', 'nguyen mai phuong ( vie )', '9.55', '9.60', '19.15'], ['4', 'chen shao - chi ( tpe )', '9.50', '9.59', '19.09'], ['5', 'evgeniya ragulina ( kaz )', '9.44', '9.50', '18.94'], ['6', 'lee tenyia ( usa )', '9.... |
phoenix suns all - time roster | https://en.wikipedia.org/wiki/Phoenix_Suns_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482079-2.html.csv | comparative | alvan adams began playing for the phoenix suns 11 years before rafael addison . | {'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '11', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'player', 'alvan adams'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose player record fuzzily matches to alvan adams .', 'tostr': 'filter_eq { all_rows ; player ; alvan adams }'}, ... | eq { diff { hop { filter_eq { all_rows ; player ; alvan adams } ; from } ; hop { filter_eq { all_rows ; player ; rafael addison } ; from } } ; -11 } = true | select the rows whose player record fuzzily matches to alvan adams . take the from record of this row . select the rows whose player record fuzzily matches to rafael addison . take the from record of this row . the second record is 11 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'player_8': 8, 'alvan adams_9': 9, 'from_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'player_12': 12, 'rafael addison_13': 13, 'from_14': 14, '-11_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'player_8': 'player', 'alvan adams_9': 'alvan adams', 'from_10': 'from', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'player_12': 'player'... | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'player_8': [0], 'alvan adams_9': [0], 'from_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'player_12': [1], 'rafael addison_13': [1], 'from_14': [3], '-11_15': [5]} | ['player', 'pos', 'from', 'school / country', 'rebs', 'asts'] | [['alvan adams', 'c / f', '1975', 'oklahoma', '6937', '4012'], ['rafael addison', 'g / f', '1986', 'syracuse', '106', '45'], ['danny ainge', 'sg', '1992', 'byu', '454', '650'], ['louis amundson', 'pf', '2008', 'unlv', '616', '59'], ['robert archibald', 'f / c', '2003', 'illinois', '1', '1'], ['dennis awtrey', 'c', '197... |
list of superleague formula drivers and teams | https://en.wikipedia.org/wiki/List_of_Superleague_Formula_drivers_and_teams | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19312274-2.html.csv | comparative | brazil has had more superleague formula teams than belgium has . | {'row_1': '3', 'row_2': '4', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'belgium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to belgium .', 'tostr': 'filter_eq { all_rows ; country ; belgium }'}, 'total'], 'result': None, 'ind': ... | less { hop { filter_eq { all_rows ; country ; belgium } ; total } ; hop { filter_eq { all_rows ; country ; brazil } ; total } } = true | select the rows whose country record fuzzily matches to belgium . take the total record of this row . select the rows whose country record fuzzily matches to brazil . take the total 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, 'country_7': 7, 'belgium_8': 8, 'total_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'brazil_12': 12, 'total_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', 'country_7': 'country', 'belgium_8': 'belgium', 'total_9': 'total', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'brazil_12': 'b... | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'belgium_8': [0], 'total_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'brazil_12': [1], 'total_13': [3]} | ['country', 'total', 'champions', 'current', 'first driver ( s )', 'last / current driver ( s )'] | [['argentina', '1', '0', '0', 'esteban guerrieri ( 2009 )', 'esteban guerrieri ( 2010 )'], ['australia', '1', '0', '1', 'john martin ( 2009 )', 'john martin'], ['belgium', '2', '0', '1', 'bertrand baguette ( 2008 )', 'frédéric vervisch'], ['brazil', '3', '0', '1', 'tuka rocha ( 2008 )', 'antônio pizzonia'], ['china', '... |
united states house of representatives elections , 1948 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1948 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342218-13.html.csv | count | six of the incumbents from illinois districts were re-elected in the 1948 united states house of representative elections . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 're-elected', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'result', 're-elected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose result record fuzzily matches to re-elected .', 'tostr': 'filter_eq { all_rows ; result ; re-elected }'}], 'result': '6', 'ind': 1, 'tost... | eq { count { filter_eq { all_rows ; result ; re-elected } } ; 6 } = true | select the rows whose result record fuzzily matches to re-elected . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'result_5': 5, 're-elected_6': 6, '6_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'result_5': 'result', 're-elected_6': 're-elected', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'result_5': [0], 're-elected_6': [0], '6_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 3', 'fred e busbey', 'republican', '1946', 'lost re - election democratic gain', 'neil j linehan ( d ) 52.9 % fred e busbey ( r ) 47.1 %'], ['illinois 5', 'martin gorski redistricted from 4th', 'democratic', '1942', 're - elected', 'martin gorski ( d ) 72.4 % john l waner ( r ) 27.6 %'], ['illinois 14', 'ch... |
2010 - 11 phoenix suns season | https://en.wikipedia.org/wiki/2010%E2%80%9311_Phoenix_Suns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27733258-6.html.csv | majority | all of the games between 4 and 16 were played during the month of november . | {'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'november', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to november .', 'tostr': 'all_eq { all_rows ; date ; november } = true'} | all_eq { all_rows ; date ; november } = true | for the date records of all rows , all of them fuzzily match to november . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'November_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'November_4': 'november'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'November_4': [0]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['4', 'november 3', 'san antonio', 'l 110 - 112 ( ot )', 'jason richardson ( 21 )', 'grant hill ( 8 )', 'goran dragić ( 8 )', 'us airways center 17060', '1 - 3'], ['5', 'november 5', 'memphis', 'w 123 - 118 ( 2ot )', 'jason richardson ( 38 )', 'channing frye ( 11 )', 'steve nash ( 9 )', 'us airways center 16470', '2 -... |
nino vaccarella | https://en.wikipedia.org/wiki/Nino_Vaccarella | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235134-1.html.csv | aggregation | for nino vaccarella the total points scored from 1961 to 1965 was 0 . | {'scope': 'all', 'col': '5', 'type': 'sum', 'result': '0', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points'], 'result': '0', 'ind': 0, 'tostr': 'sum { all_rows ; points }'}, '0'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points } ; 0 } = true', 'tointer': 'the sum of the points record of all rows is 0 .'} | round_eq { sum { all_rows ; points } ; 0 } = true | the sum of the points record of all rows is 0 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points_4': 4, '0_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points_4': 'points', '0_5': '0'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points_4': [0], '0_5': [1]} | ['year', 'entrant', 'chassis', 'engine', 'points'] | [['1961', 'scuderia serenissima', 'de tomaso f1', 'alfa romeo straight - 4', '0'], ['1962', 'scuderia sss republica di venezia', 'lotus 18 / 21', 'climax straight - 4', '0'], ['1962', 'scuderia sss republica di venezia', 'porsche 718', 'porsche flat - 4', '0'], ['1962', 'scuderia sss republica di venezia', 'lotus 24', ... |
2009 - 10 washington wizards season | https://en.wikipedia.org/wiki/2009%E2%80%9310_Washington_Wizards_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23274514-7.html.csv | ordinal | the washington wizards ' game against boston recorded their highest attendance of the 2009 - 10 season . | {'row': '1', 'col': '8', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'location attendance', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; location attendance ; 1 }'}, 'team'], 'result': 'boston', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; location attendance ; ... | eq { hop { nth_argmax { all_rows ; location attendance ; 1 } ; team } ; boston } = true | select the row whose location attendance record of all rows is 1st maximum . the team record of this row is boston . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'location attendance_5': 5, '1_6': 6, 'team_7': 7, 'boston_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', 'location attendance_5': 'location attendance', '1_6': '1', 'team_7': 'team', 'boston_8': 'boston'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'location attendance_5': [0], '1_6': [0], 'team_7': [1], 'boston_8': [2]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record'] | [['47', 'february 1', 'boston', 'l 88 - 99 ( ot )', 'caron butler ( 20 )', 'caron butler ( 11 )', 'randy foye ( 4 )', 'verizon center 20173', '16 - 31'], ['48', 'february 3', 'new york', 'l 85 - 107 ( ot )', 'foye & young ( 15 )', 'brendan haywood ( 8 )', 'earl boykins ( 6 )', 'madison square garden 19225', '16 - 32'],... |
jeep grand cherokee | https://en.wikipedia.org/wiki/Jeep_Grand_Cherokee | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1105695-9.html.csv | count | in jeep grand cherokee , the years of one of the cars with engine 4.7 l powertech v8 is 2005-2007 . | {'scope': 'subset', 'criterion': 'equal', 'value': '2005-2007', 'result': '1', 'col': '1', 'subset': {'col': '2', 'criterion': 'equal', 'value': '4.7 l powertech v8'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', '4.7 l powertech v8'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; engine ; 4.7 l powertech v8 }', 'tointer': 'select the rows whose engine record fuzzily matches... | eq { count { filter_eq { filter_eq { all_rows ; engine ; 4.7 l powertech v8 } ; years ; 2005-2007 } } ; 1 } = true | select the rows whose engine record fuzzily matches to 4.7 l powertech v8 . among these rows , select the rows whose years record fuzzily matches to 2005-2007 . the number of such rows is 1 . | 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, 'engine_6': 6, '4.7l powertech v8_7': 7, 'years_8': 8, '2005-2007_9': 9, '1_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', 'engine_6': 'engine', '4.7l powertech v8_7': '4.7 l powertech v8', 'years_8': 'years', '2005-2007_9': '2005-2007', '1_10': '1'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'engine_6': [0], '4.7l powertech v8_7': [0], 'years_8': [1], '2005-2007_9': [1], '1_10': [3]} | ['years', 'engine', 'power', 'torque', 'notes'] | [['2005 - 2010', '3.7 l powertech v6', '-', 'n / a', 'laredo , limited'], ['2005 - 2007', '4.7 l powertech v8', '-', 'n / a', 'laredo , limited'], ['2008 - 2009', '4.7 l powertech v8', '-', 'n / a', 'laredo , limited'], ['2005 - 2008', '5.7 l hemi v8', '-', 'n / a', 'limited , overland'], ['2009 - 2010', '5.7 l hemi v8... |
reinhold roth | https://en.wikipedia.org/wiki/Reinhold_Roth | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14860855-3.html.csv | aggregation | over his career , reinhold roth averaged over 48 points per year . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '48.8', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'points'], 'result': '48.8', 'ind': 0, 'tostr': 'avg { all_rows ; points }'}, '48.8'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; points } ; 48.8 } = true', 'tointer': 'the average of the points record of all rows is 48.8 .'} | round_eq { avg { all_rows ; points } ; 48.8 } = true | the average of the points record of all rows is 48.8 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'points_4': 4, '48.8_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'points_4': 'points', '48.8_5': '48.8'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'points_4': [0], '48.8_5': [1]} | ['year', 'class', 'team', 'points', 'wins'] | [['1979', '350cc', 'yamaha', '3', '0'], ['1980', '250cc', 'yamaha', '4', '0'], ['1982', '250cc', 'yamaha', '4', '0'], ['1982', '500cc', 'suzuki', '0', '0'], ['1983', '250cc', 'yamaha', '14', '0'], ['1984', '500cc', 'honda', '14', '0'], ['1985', '250cc', 'romer - juchem', '29', '0'], ['1986', '250cc', 'hb - honda', '10'... |
1990 dallas cowboys season | https://en.wikipedia.org/wiki/1990_Dallas_Cowboys_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11281728-2.html.csv | superlative | the texas stadium was the first venue used by the dallas cowboys during the 1990 season . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '5', '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 }'}, 'venue'], 'result': 'texas stadium', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date } ; venue }'}, 'texas stadium'], 'result': True, 'ind': 2, '... | eq { hop { argmin { all_rows ; date } ; venue } ; texas stadium } = true | select the row whose date record of all rows is minimum . the venue record of this row is texas stadium . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, 'venue_6': 6, 'texas stadium_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', 'venue_6': 'venue', 'texas stadium_7': 'texas stadium'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], 'venue_6': [1], 'texas stadium_7': [2]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance'] | [['1', '1990 - 09 - 09', 'san diego chargers', 'w 17 - 14', 'texas stadium', '48063'], ['2', '1990 - 09 - 16', 'new york giants', 'l 28 - 7', 'texas stadium', '61090'], ['3', '1990 - 09 - 23', 'washington redskins', 'l 19 - 15', 'robert f kennedy memorial stadium', '53804'], ['4', '1990 - 09 - 30', 'new york giants', '... |
comparison of e - book readers | https://en.wikipedia.org/wiki/Comparison_of_e-book_readers | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1149661-3.html.csv | majority | most of the models have a screen size of at least seven inches . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '7', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'screen size ( inch )', '7'], 'result': True, 'ind': 0, 'tointer': 'for the screen size ( inch ) records of all rows , most of them are greater than or equal to 7 .', 'tostr': 'most_greater_eq { all_rows ; screen size ( inch ) ; 7 } = true'} | most_greater_eq { all_rows ; screen size ( inch ) ; 7 } = true | for the screen size ( inch ) records of all rows , most of them are greater than or equal to 7 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'screen size (inch)_3': 3, '7_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'screen size (inch)_3': 'screen size ( inch )', '7_4': '7'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'screen size (inch)_3': [0], '7_4': [0]} | ['maker', 'model', 'intro year', 'screen size ( inch )', 'screen type', 'weight', 'screen pixels', 'hours reading', 'touch screen', 'wireless network', 'internal storage', 'card reader slot'] | [['aluratek', 'libre touch ebook reader', '2011', '7', 'lcd', 'g ( oz )', '480 800', '8', 'yes', 'yes , wi - fi', '4 gb', 'microsd'], ['aluratek', 'libre air ebook reader', '2011', '5', 'lcd', 'g ( oz )', '480 640', '20', 'no', 'yes , wi - fi', '512 mb', 'microsd'], ['aluratek', 'libre color ebook reader', '2010', '7',... |
telecommunications in moldova | https://en.wikipedia.org/wiki/Telecommunications_in_Moldova | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19246-1.html.csv | unique | among the telecommunications in moldova that were launched in 2005 the only one with connection speed 236.8 kbit/s is moldcell . | {'scope': 'subset', 'row': '4', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': '236.8 kbit/s', 'subset': {'col': '5', 'criterion': 'fuzzily_match', 'value': '2005'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'launch date ( ddmmyyyy )', '2005'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 }', 'tointer': 'select the rows whose launch date ( ddmmyyy... | and { only { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } } ; eq { hop { filter_eq { filter_eq { all_rows ; launch date ( ddmmyyyy ) ; 2005 } ; connection speed ; 236.8 kbit/s } ; carrier } ; moldcell } } = true | select the rows whose launch date ( ddmmyyyy ) record fuzzily matches to 2005 . among these rows , select the rows whose connection speed record fuzzily matches to 236.8 kbit/s . there is only one such row in the table . the carrier record of this unqiue row is moldcell . | 8 | 6 | {'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'launch date (ddmmyyyy)_8': 8, '2005_9': 9, 'connection speed_10': 10, '236.8kbit/s_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'carrier_12': 12, 'moldcell_13': 13} | {'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'launch date (ddmmyyyy)_8': 'launch date ( ddmmyyyy )', '2005_9': '2005', 'connection speed_10': 'connection speed', '236.8kbit/s_11': '236.8 kbit/s', 'str_eq_4': 'str... | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'launch date (ddmmyyyy)_8': [0], '2005_9': [0], 'connection speed_10': [1], '236.8kbit/s_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'carrier_12': [3], 'moldcell_13': [4]} | ['carrier', 'standard', 'frequency', 'connection speed', 'launch date ( ddmmyyyy )'] | [['orange', 'gsm gprs', '900 mhz and 1800 mhz', '56 kbit / s', '14.09.2005'], ['orange', 'gsm edge', '900 mhz and 1800 mhz', '236.8 kbit / s', '17.04.2006'], ['moldcell', 'gsm gprs', '900 mhz and 1800 mhz', '56 kbit / s', '31.01.2005'], ['moldcell', 'gsm edge', '900 mhz and 1800 mhz', '236.8 kbit / s', '07.06.2005'], [... |
1949 vfl season | https://en.wikipedia.org/wiki/1949_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10809351-5.html.csv | majority | all games of the 1949 vfl season were played on the 14th of may . | {'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '14 may 1949', 'subset': None} | {'func': 'all_str_eq', 'args': ['all_rows', 'date', '14 may 1949'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 14 may 1949 .', 'tostr': 'all_eq { all_rows ; date ; 14 may 1949 } = true'} | all_eq { all_rows ; date ; 14 may 1949 } = true | for the date records of all rows , all of them fuzzily match to 14 may 1949 . | 1 | 1 | {'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '14 may 1949_4': 4} | {'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '14 may 1949_4': '14 may 1949'} | {'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '14 may 1949_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['melbourne', '5.16 ( 46 )', 'north melbourne', '6.12 ( 48 )', 'mcg', '19000', '14 may 1949'], ['geelong', '15.13 ( 103 )', 'st kilda', '10.11 ( 71 )', 'kardinia park', '15500', '14 may 1949'], ['essendon', '11.18 ( 84 )', 'richmond', '9.15 ( 69 )', 'windy hill', '21000', '14 may 1949'], ['carlton', '16.8 ( 104 )', 'c... |
shane hall | https://en.wikipedia.org/wiki/Shane_Hall | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2649597-1.html.csv | comparative | shane hall drove more formula one races in the year 2001 than he did in the year 2003 . | {'row_1': '7', 'row_2': '9', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2001'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 2001 .', 'tostr': 'filter_eq { all_rows ; year ; 2001 }'}, 'races'], 'result': None, 'ind': 2, 'tostr': 'ho... | greater { hop { filter_eq { all_rows ; year ; 2001 } ; races } ; hop { filter_eq { all_rows ; year ; 2003 } ; races } } = true | select the rows whose year record fuzzily matches to 2001 . take the races record of this row . select the rows whose year record fuzzily matches to 2003 . take the races record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '2001_8': 8, 'races_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '2003_12': 12, 'races_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '2001_8': '2001', 'races_9': 'races', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '2003_12': '2003', 'races_1... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '2001_8': [0], 'races_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '2003_12': [1], 'races_13': [3]} | ['year', 'races', 'wins', 'poles', 'top 5', 'top 10', 'dnf', 'finish', 'start', 'winnings', 'season rank', 'team ( s )'] | [['1995', '2', '0', '0', '0', '0', '0', '24.0', '37.0', '5225', '75th', 'stegell motorsports'], ['1996', '14', '0', '0', '0', '0', '6', '26.4', '25.1', '63865', '42nd', 'stegell motorsports'], ['1997', '28', '0', '1', '0', '1', '10', '27.1', '21.6', '196656', '23rd', 'stegell motorsports'], ['1998', '31', '0', '1', '0'... |
red dwarf | https://en.wikipedia.org/wiki/Red_Dwarf | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25721-4.html.csv | count | there were three region 2 dvd releases of the show red dwarf in the year 2004 . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2004', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region 2', '2004'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose region 2 record fuzzily matches to 2004 .', 'tostr': 'filter_eq { all_rows ; region 2 ; 2004 }'}], 'result': '3', 'ind': 1, 'tostr': 'count {... | eq { count { filter_eq { all_rows ; region 2 ; 2004 } } ; 3 } = true | select the rows whose region 2 record fuzzily matches to 2004 . 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, 'region 2_5': 5, '2004_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', 'region 2_5': 'region 2', '2004_6': '2004', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'region 2_5': [0], '2004_6': [0], '3_7': [2]} | ['release', 'of discs', 'region 1', 'region 2', 'region 4'] | [['series i', '2', '25 february 2003', '4 november 2002', '3 december 2002'], ['series ii', '2', '25 february 2003', '10 february 2003', '1 april 2003'], ['series iii', '2', '3 february 2004', '3 november 2003', '18 november 2003'], ['series iv', '2', '3 february 2004', '16 february 2004', '9 march 2004'], ['just the s... |
list of largest nordic companies | https://en.wikipedia.org/wiki/List_of_largest_Nordic_companies | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12794433-3.html.csv | majority | the majority of largest nordic companies are headquartered in sweden . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'sweden', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'headquarters', 'sweden'], 'result': True, 'ind': 0, 'tointer': 'for the headquarters records of all rows , most of them fuzzily match to sweden .', 'tostr': 'most_eq { all_rows ; headquarters ; sweden } = true'} | most_eq { all_rows ; headquarters ; sweden } = true | for the headquarters records of all rows , most of them fuzzily match to sweden . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'headquarters_3': 3, 'sweden_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'headquarters_3': 'headquarters', 'sweden_4': 'sweden'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'headquarters_3': [0], 'sweden_4': [0]} | ['rank', 'company', 'headquarters', 'industry', 'employees', 'reference date'] | [['1', 'iss', 'copenhagen , denmark', 'facility management', '534500', '2011'], ['2', 'securitas', 'stockholm , sweden', 'security services', '272425', '2011'], ['3', 'nokia', 'espoo , finland', 'technology', '130050', '2011'], ['4', 'ap mãller - maersk', 'copenhagen , denmark', 'transportation', '117080', '2011'], ['5... |
list of how it 's made episodes | https://en.wikipedia.org/wiki/List_of_How_It%27s_Made_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15187735-12.html.csv | unique | only episode 147 of how it 's made drama series have segmented parts 1 and 2 . | {'scope': 'all', 'row': '4', 'col': '6', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'part 1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'segment c', 'part 1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose segment c record fuzzily matches to part 1 .', 'tostr': 'filter_eq { all_rows ; segment c ; part 1 }'}], 'result': True, 'ind': 1, 'tostr'... | and { only { filter_eq { all_rows ; segment c ; part 1 } } ; eq { hop { filter_eq { all_rows ; segment c ; part 1 } ; episode } ; 147 } } = true | select the rows whose segment c record fuzzily matches to part 1 . there is only one such row in the table . the episode record of this unqiue row is 147 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'segment c_7': 7, 'part 1_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'episode_9': 9, '147_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'segment c_7': 'segment c', 'part 1_8': 'part 1', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'episode_9': 'episode', '147_10': '147'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'segment c_7': [0], 'part 1_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'episode_9': [2], '147_10': [3]} | ['series ep', 'episode', 'netflix', 'segment a', 'segment b', 'segment c', 'segment d'] | [['12 - 01', '144', 's06e14', 'pneumatic impact wrenches', 'cultured marble sinks', 'plantain chips', 'nascar stock cars'], ['12 - 02', '145', 's06e15', 'jaws of life', 'artificial christmas trees', 'soda crackers', 'ratchets'], ['12 - 03', '146', 's06e16', 's thermometer', 'produce scales', 'aircraft painting', 'luxur... |
2008 in paraguayan football | https://en.wikipedia.org/wiki/2008_in_Paraguayan_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17334827-6.html.csv | superlative | the june 18 , 2008 game was the highest scoring game for paraguay in the year 2008 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'date'], 'result': 'june 18 , 2008', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; date }'}, 'june 18 , 2008'], 'result': True, 'ind': 2... | eq { hop { argmax { all_rows ; score } ; date } ; june 18 , 2008 } = true | select the row whose score record of all rows is maximum . the date record of this row is june 18 , 2008 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'date_6': 6, 'june 18 , 2008_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'date_6': 'date', 'june 18 , 2008_7': 'june 18 , 2008'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'date_6': [1], 'june 18 , 2008_7': [2]} | ['date', 'venue', 'score', 'comp', 'paraguay scorers', 'report'] | [['june 15 , 2008', 'defensores del chaco asunción , paraguay', '2 - 0', 'wcq 2010', "santa cruz 26 ' cabañas 49 '", 'report'], ['june 18 , 2008', 'estadio hernando siles la paz , bolivia', '4 - 2', 'wcq 2010', "santa cruz 66 ' haedo valdez 82 '", 'report'], ['september 6 , 2008', 'estadio monumental buenos aires , arg... |
teen angels | https://en.wikipedia.org/wiki/Teen_Angels | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18073917-17.html.csv | unique | the year 2011 was the only year that teen angels was nominated in the category favorite music group . | {'scope': 'all', 'row': '6', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'favorite music group', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'favorite music group'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to favorite music group .', 'tostr': 'filter_eq { all_rows ; category ; favorite music group ... | and { only { filter_eq { all_rows ; category ; favorite music group } } ; eq { hop { filter_eq { all_rows ; category ; favorite music group } ; year } ; 2011 } } = true | select the rows whose category record fuzzily matches to favorite music group . there is only one such row in the table . the year record of this unqiue row is 2011 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'category_7': 7, 'favorite music group_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'year_9': 9, '2011_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'category_7': 'category', 'favorite music group_8': 'favorite music group', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'year_9': 'year', '2011_10': '2011'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'category_7': [0], 'favorite music group_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'year_9': [2], '2011_10': [3]} | ['year', 'award', 'category', 'nominated', 'result'] | [['2009', 'capif awards', 'best album by a film / television band', 'teen angels', 'won'], ['2009', 'premios carlos gardel 2009', 'best album by a film / television band', 'teen angels', 'won'], ['2009', 'premios 40 principales', 'best argentine act', 'teen angels', 'won'], ['2010', 'premios carlos gardel 2010', 'best ... |
cass technical high school | https://en.wikipedia.org/wiki/Cass_Technical_High_School | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1198175-1.html.csv | superlative | at cass technical high school , the highest weight was joseph barksdale . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '16', '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', 'weight ( lbs )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; weight ( lbs ) }'}, 'name'], 'result': 'joseph barksdale', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; weight ( lbs ) } ; name }'}, 'joseph barksd... | eq { hop { argmax { all_rows ; weight ( lbs ) } ; name } ; joseph barksdale } = true | select the row whose weight ( lbs ) record of all rows is maximum . the name record of this row is joseph barksdale . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'weight (lbs)_5': 5, 'name_6': 6, 'joseph barksdale_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'weight (lbs)_5': 'weight ( lbs )', 'name_6': 'name', 'joseph barksdale_7': 'joseph barksdale'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'weight (lbs)_5': [0], 'name_6': [1], 'joseph barksdale_7': [2]} | ['name', 'position', 'height', 'weight ( lbs )', 'born', 'college', 'drafted'] | [['walter clago', 'e', "6 ' 0", '195', '6 / / 1899 detroit , mi', 'detroit', 'undrafted'], ['darris mccord', 'de / dt / oe', "6 ' 6", '250', 'january 4 , 1933 detroit , mi', 'tennessee', '1955 , r3 , p11'], ['ben john paolucci', 'dt', "6 ' 2", '240', 'march 5 , 1937 cleveland , oh', 'wayne state', 'undrafted'], ['arnie... |
nevada gaming area | https://en.wikipedia.org/wiki/Nevada_gaming_area | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25438110-5.html.csv | comparative | clark county has a higher number of casinos in the nevada gaming area than south lake tahoe . | {'row_1': '1', 'row_2': '4', 'col': '1', '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', 'county', 'clark'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose county record fuzzily matches to clark .', 'tostr': 'filter_eq { all_rows ; county ; clark }'}, 'casinos'], 'result': None, 'ind': 2, '... | greater { hop { filter_eq { all_rows ; county ; clark } ; casinos } ; hop { filter_eq { all_rows ; county ; south lake tahoe } ; casinos } } = true | select the rows whose county record fuzzily matches to clark . take the casinos record of this row . select the rows whose county record fuzzily matches to south lake tahoe . take the casinos 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, 'county_7': 7, 'clark_8': 8, 'casinos_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'county_11': 11, 'south lake tahoe_12': 12, 'casinos_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', 'county_7': 'county', 'clark_8': 'clark', 'casinos_9': 'casinos', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'county_11': 'county', 'south lake t... | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'county_7': [0], 'clark_8': [0], 'casinos_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'county_11': [1], 'south lake tahoe_12': [1], 'casinos_13': [3]} | ['casinos', 'county', 'road', '1 - jul - 08', 'fy07 millions', 'fy08 millions', 'fy09 millions'] | [['149', 'clark', 'i - 15', '1865746', '10538', '10172', '9081'], ['32', 'washoe', 'i - 80', '410443', '1045', '977', '856'], ['17', 'elko', 'i - 80', '47071', '324', '303', '279'], ['5', 'south lake tahoe', 'route 50', '45180', '283', '307', '264'], ['14', 'carson valley', 'route 395', '54867', '120', '114', '102']] |
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 | comparative | in the tri - state collegiate hockey league , ohio university joined a year later than university of akron . | {'row_1': '5', 'row_2': '1', 'col': '4', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '1 year', 'bigger': 'row1'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'institution', 'ohio university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose institution record fuzzily matches to ohio university .', 'tostr': 'filter_eq { all_rows ; institut... | eq { diff { hop { filter_eq { all_rows ; institution ; ohio university } ; joined tschl } ; hop { filter_eq { all_rows ; institution ; university of akron } ; joined tschl } } ; 1 year } = true | select the rows whose institution record fuzzily matches to ohio university . take the joined tschl record of this row . select the rows whose institution record fuzzily matches to university of akron . take the joined tschl record of this row . the first record is 1 year larger than the second record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'institution_8': 8, 'ohio university_9': 9, 'joined tschl_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'institution_12': 12, 'university of akron_13': 13, 'joined tschl_14': 14, '1 year_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'institution_8': 'institution', 'ohio university_9': 'ohio university', 'joined tschl_10': 'joined tschl', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_r... | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'institution_8': [0], 'ohio university_9': [0], 'joined tschl_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'institution_12': [1], 'university of akron_13': [1], 'joined tschl_14': [3]... | ['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', 'da... |
leaf ( israeli company ) | https://en.wikipedia.org/wiki/Leaf_%28Israeli_company%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16395908-2.html.csv | ordinal | the aptus ii 5 has the lowest iso range values at 25-400 . | {'row': '8', 'col': '6', 'order': '1', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'iso range', '1'], 'result': '25 - 400', 'ind': 0, 'tostr': 'nth_min { all_rows ; iso range ; 1 }', 'tointer': 'the 1st minimum iso range record of all rows is 25 - 400 .'}, '25 - 400'], 'result': True, 'ind': 1, 'tostr': 'eq { nt... | and { eq { nth_min { all_rows ; iso range ; 1 } ; 25 - 400 } ; eq { hop { nth_argmin { all_rows ; iso range ; 1 } ; model } ; aptus - ii 5 } } = true | the 1st minimum iso range record of all rows is 25 - 400 . the model record of the row with 1st minimum iso range record is aptus - ii 5 . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'iso range_8': 8, '1_9': 9, '25 - 400_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'iso range_12': 12, '1_13': 13, 'model_14': 14, 'aptus - ii 5_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'iso range_8': 'iso range', '1_9': '1', '25 - 400_10': '25 - 400', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'iso range_12': 'iso range', '1_13': '1', 'model_... | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'iso range_8': [0], '1_9': [0], '25 - 400_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'iso range_12': [2], '1_13': [2], 'model_14': [3], 'aptus - ii 5_15': [4]} | ['model', 'released', 'sensor size', 'resolution', 'active pixels', 'iso range', 'dynamic range ( f - stops )', 'seconds / frame', 'lens conversion factor', 'display', 'storage'] | [['aptus - ii 12r', '2010', '53.7 x40 .3 mm', '80 mp , 16 - bit', '10320 x 7752', '80 - 800', '12', '1.5', '1.0', '3.5 - inch touchscreen', 'firewire , cf'], ['aptus - ii 12', '2010', '53.7 x40 .3 mm', '80 mp , 16 - bit', '10320 x 7752', '80 - 800', '12', '1.5', '1.0', '3.5 - inch touchscreen', 'firewire , cf'], ['aptu... |
2007 - 08 los angeles clippers season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Los_Angeles_Clippers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11965402-7.html.csv | aggregation | the average crowd attendance during the 2007 - 08 los angeles clippers season was 17863 . | {'scope': 'all', 'col': '6', 'type': 'average', 'result': '17863', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '17863', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '17863'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 17863 } = true', 'tointer': 'the average of the attendance record of all rows... | round_eq { avg { all_rows ; attendance } ; 17863 } = true | the average of the attendance record of all rows is 17863 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '17863_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '17863_5': '17863'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '17863_5': [1]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'attendance', 'record'] | [['march 1 , 2008', 'pistons', '103 - 73', 'clippers', 'corey maggette ( 22 )', '19271', '19 - 38'], ['march 3 , 2008', 'sixers', '106 - 80', 'clippers', 'al thornton ( 20 )', '15691', '19 - 39'], ['march 5 , 2008', 'kings', '109 - 116', 'clippers', 'al thornton ( 27 )', '17030', '20 - 39'], ['march 7 , 2008', 'clipper... |
list of tallest buildings in montreal | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Montreal | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1722194-5.html.csv | count | 2 of the tallest buildings in montreal have 47 floors . | {'scope': 'all', 'criterion': 'equal', 'value': '47', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'floors', '47'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose floors record is equal to 47 .', 'tostr': 'filter_eq { all_rows ; floors ; 47 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ;... | eq { count { filter_eq { all_rows ; floors ; 47 } } ; 2 } = true | select the rows whose floors record is equal to 47 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'floors_5': 5, '47_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'floors_5': 'floors', '47_6': '47', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'floors_5': [0], '47_6': [0], '2_7': [2]} | ['name', 'street address', 'years as tallest', 'of years as tallest', 'height m / ft', 'floors'] | [['notre dame basilica', '110 notre - dame street west', '1829 - 1928', '99 years', '69 / 226', '7'], ['royal bank building', '360 saint jacques street west', '1928 - 1931', '3 years', '121 / 397', '22'], ['sun life building', '1155 metcalfe street', '1931 - 1962', '31 years', '122 / 400', '26'], ['tour cibc', '1155 re... |
6 mm caliber | https://en.wikipedia.org/wiki/6_mm_caliber | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1058122-4.html.csv | superlative | the 6.5 x 68 cartilage has the longest length among all of the 6mm calibers . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'length'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; length }'}, 'name'], 'result': '6.5 x 68', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; length } ; name }'}, '6.5 x 68'], 'result': True, 'ind': 2, 'tostr'... | eq { hop { argmax { all_rows ; length } ; name } ; 6.5 x 68 } = true | select the row whose length record of all rows is maximum . the name record of this row is 6.5 x 68 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'length_5': 5, 'name_6': 6, '6.5 x 68_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'length_5': 'length', 'name_6': 'name', '6.5 x 68_7': '6.5 x 68'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'length_5': [0], 'name_6': [1], '6.5 x 68_7': [2]} | ['name', 'bullet', 'length', 'base', 'shoulder', 'neck'] | [['6.5 x 50 sr arisaka', '6.705 ( 264 )', '50.39 ( 1.984 )', '11.35 ( 447 )', '10.59 ( 417 )', '7.34 ( 289 )'], ['6.5 x 53.5 r dutch mannlicher', '6.756 ( 266 )', '53.59 ( 2.110 )', '11.48 ( 453 )', '10.75 ( 423 )', '7.55 ( 297 )'], ['6.5 x54 mm mannlicher - schãnauer', '6.705 ( 264 )', '53.65 ( 2.112 )', '11.47 ( 452 ... |
2010 fedex cup playoffs | https://en.wikipedia.org/wiki/2010_FedEx_Cup_Playoffs | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28498999-4.html.csv | majority | most of the players tied for second place in the 2010 fedex cup playoffs were from australia . | {'scope': 'subset', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'australia', 'subset': {'col': '1', 'criterion': 'equal', 'value': 't2'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '', 't2'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; ; t2 }', 'tointer': 'select the rows whose record fuzzily matches to t2 .'}, 'country', 'australia'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose record f... | most_eq { filter_eq { all_rows ; ; t2 } ; country ; australia } = true | select the rows whose record fuzzily matches to t2 . for the country records of these rows , most of them fuzzily match to australia . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, '_4': 4, 't2_5': 5, 'country_6': 6, 'australia_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', '_4': '', 't2_5': 't2', 'country_6': 'country', 'australia_7': 'australia'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], '_4': [0], 't2_5': [0], 'country_6': [1], 'australia_7': [1]} | ['', 'player', 'country', 'score', 'to par', 'winnings', 'after', 'before'] | [['1', 'charley hoffman', 'united states', '64 + 67 + 69 + 62 = 262', '- 22', '1350000', '2', '59'], ['t2', 'jason day', 'australia', '63 + 67 + 66 + 71 = 267', '- 17', '560000', '4', '14'], ['t2', 'luke donald', 'england', '65 + 67 + 66 + 69 = 267', '- 17', '560000', '5', '17'], ['t2', 'geoff ogilvy', 'australia', '64... |
iran at the 1998 asian games | https://en.wikipedia.org/wiki/Iran_at_the_1998_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10831471-38.html.csv | majority | for iran at the 1998 asian games , of the events with competitors weight less than 65 kg , most of the atheletes did not advance to the quarterfinal . | {'scope': 'subset', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'did not advance', 'subset': {'col': '2', 'criterion': 'less_than', 'value': '65 kg'}} | {'func': 'most_str_eq', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'event', '65 kg'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; event ; 65 kg }', 'tointer': 'select the rows whose event record is less than 65 kg .'}, 'quarterfinal', 'did not advance'], 'result': True, 'ind': 1, 'tointer': ... | most_eq { filter_less { all_rows ; event ; 65 kg } ; quarterfinal ; did not advance } = true | select the rows whose event record is less than 65 kg . for the quarterfinal records of these rows , most of them fuzzily match to did not advance . | 2 | 2 | {'most_str_eq_1': 1, 'result_2': 2, 'filter_less_0': 0, 'all_rows_3': 3, 'event_4': 4, '65 kg_5': 5, 'quarterfinal_6': 6, 'did not advance_7': 7} | {'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_less_0': 'filter_less', 'all_rows_3': 'all_rows', 'event_4': 'event', '65 kg_5': '65 kg', 'quarterfinal_6': 'quarterfinal', 'did not advance_7': 'did not advance'} | {'most_str_eq_1': [2], 'result_2': [], 'filter_less_0': [1], 'all_rows_3': [0], 'event_4': [0], '65 kg_5': [0], 'quarterfinal_6': [1], 'did not advance_7': [1]} | ['athlete', 'event', 'round of 16', 'quarterfinal', 'semifinal', 'final'] | [['alireza saadat', '52 kg', 'chulhang l 0 - 2', 'did not advance', 'did not advance', 'did not advance'], ['alireza rouzbahani', '56 kg', 'zheng l 0 - 2', 'did not advance', 'did not advance', 'did not advance'], ['ali khodaei', '60 kg', 'n / a', 'zhunuspekov l 1 - 2', 'did not advance', 'did not advance'], ['mansour ... |
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/2-11916083-49.html.csv | aggregation | the average composition of the numismatic coins was about 99 % silver . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '99', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'composition'], 'result': '99', 'ind': 0, 'tostr': 'avg { all_rows ; composition }'}, '99'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; composition } ; 99 } = true', 'tointer': 'the average of the composition record of all rows is 9... | round_eq { avg { all_rows ; composition } ; 99 } = true | the average of the composition record of all rows is 99 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'composition_4': 4, '99_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'composition_4': 'composition', '99_5': '99'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'composition_4': [0], '99_5': [1]} | ['year', 'theme', 'artist', 'composition', 'mintage', 'issue price'] | [['2007', 'blue crystal - piedfort', 'konrad wachelko', '92.5 % silver , 7.5 % copper', '5000', '94.95'], ['2007', 'iridescent crystal - piedfort', 'konrad wachelko', '92.5 % silver , 7.5 % copper', '5000', '94.95'], ['2008', 'amethyst crystal', 'konrad wachelko', '99.99 % silver', '7500', '94.95'], ['2008', 'sapphire ... |
swatch fivb world tour 2006 | https://en.wikipedia.org/wiki/Swatch_FIVB_World_Tour_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18395409-3.html.csv | unique | switzerland was the only nation to win only one gold medal in the 2006 swatch fivb world tour , . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'gold', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose gold record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; gold ; 1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; gold ; 1... | and { only { filter_eq { all_rows ; gold ; 1 } } ; eq { hop { filter_eq { all_rows ; gold ; 1 } ; nation } ; switzerland } } = true | select the rows whose gold record is equal to 1 . there is only one such row in the table . the nation record of this unqiue row is switzerland . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'gold_7': 7, '1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'nation_9': 9, 'switzerland_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'gold_7': 'gold', '1_8': '1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'nation_9': 'nation', 'switzerland_10': 'switzerland'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'gold_7': [0], '1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'nation_9': [2], 'switzerland_10': [3]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'brazil', '17', '18', '15', '50'], ['2', 'united states', '5', '5', '4', '14'], ['3', 'china', '4', '5', '5', '14'], ['4', 'germany', '2', '1', '3', '6'], ['5', 'switzerland', '1', '0', '0', '1'], ['6', 'netherlands', '0', '0', '1', '1'], ['6', 'norway', '0', '0', '1', '1']] |
1976 vfl season | https://en.wikipedia.org/wiki/1976_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10885968-6.html.csv | count | in the 1976 vfl season , among the games where away team scored below 11.00 , 2 of them had attendance above 15,000 . | {'scope': 'subset', 'criterion': 'greater_than', 'value': '15000', 'result': '2', 'col': '6', 'subset': {'col': '4', 'criterion': 'less_than', 'value': '11.0'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'away team score', '11.0'], 'result': None, 'ind': 0, 'tostr': 'filter_less { all_rows ; away team score ; 11.0 }', 'tointer': 'select the rows whose away team score record is less than 11... | eq { count { filter_greater { filter_less { all_rows ; away team score ; 11.0 } ; crowd ; 15000 } } ; 2 } = true | select the rows whose away team score record is less than 11.0 . among these rows , select the rows whose crowd record is greater than 15000 . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_greater_1': 1, 'filter_less_0': 0, 'all_rows_5': 5, 'away team score_6': 6, '11.0_7': 7, 'crowd_8': 8, '15000_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_greater_1': 'filter_greater', 'filter_less_0': 'filter_less', 'all_rows_5': 'all_rows', 'away team score_6': 'away team score', '11.0_7': '11.0', 'crowd_8': 'crowd', '15000_9': '15000', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_greater_1': [2], 'filter_less_0': [1], 'all_rows_5': [0], 'away team score_6': [0], '11.0_7': [0], 'crowd_8': [1], '15000_9': [1], '2_10': [3]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '11.9 ( 75 )', 'st kilda', '10.10 ( 70 )', 'western oval', '19978', '8 may 1976'], ['collingwood', '14.13 ( 97 )', 'geelong', '15.13 ( 103 )', 'victoria park', '23428', '8 may 1976'], ['south melbourne', '16.12 ( 108 )', 'melbourne', '21.10 ( 136 )', 'lake oval', '14270', '8 may 1976'], ['north melbourne... |
mobile network operators of india | https://en.wikipedia.org/wiki/Mobile_network_operators_of_India | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23801721-1.html.csv | majority | the majority of the mobile networks in india are privately owned . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': 'state - owned', 'subset': None} | {'func': 'most_str_not_eq', 'args': ['all_rows', 'ownership', 'state - owned'], 'result': True, 'ind': 0, 'tointer': 'for the ownership records of all rows , most of them do not match to state - owned .', 'tostr': 'most_not_eq { all_rows ; ownership ; state - owned } = true'} | most_not_eq { all_rows ; ownership ; state - owned } = true | for the ownership records of all rows , most of them do not match to state - owned . | 1 | 1 | {'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'ownership_3': 3, 'state - owned_4': 4} | {'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'ownership_3': 'ownership', 'state - owned_4': 'state - owned'} | {'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'ownership_3': [0], 'state - owned_4': [0]} | ['rank', 'operators name', 'technology', 'subscribers ( in millions )', 'ownership', 'market share'] | [['2', 'reliance communications', 'cdmaone evdo gsm hspa wimax', '154.11 ( september 2012 )', 'reliance adag ( 67 % ) public ( 26 % )', 'n / a'], ['3', 'vodafone', 'gsm edge hsdpa', '155.5 ( october 2013 )', 'vodafone group ( 100 % )', '22.91 % ( october 2013 )'], ['4', 'idea cellular', 'gsm edge hspa', '127.2 ( q2 201... |
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 | unique | konstadinos douvalidis is the only athlete from greece participating in the 110 metres men 's hurdles . | {'scope': 'all', 'row': '5', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'greece', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'greece'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to greece .', 'tostr': 'filter_eq { all_rows ; nationality ; greece }'}], 'result': True, 'ind': 1, '... | and { only { filter_eq { all_rows ; nationality ; greece } } ; eq { hop { filter_eq { all_rows ; nationality ; greece } ; athlete } ; konstadinos douvalidis } } = true | select the rows whose nationality record fuzzily matches to greece . there is only one such row in the table . the athlete record of this unqiue row is konstadinos douvalidis . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'greece_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'athlete_9': 9, 'konstadinos douvalidis_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', 'greece_8': 'greece', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'athlete_9': 'athlete', 'konstadinos douvalidis_10': 'konstadinos douvalidis'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'greece_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'athlete_9': [2], 'konstadinos douvalidis_10': [3]} | ['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', 'gr... |
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