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mexico national under - 20 football team | https://en.wikipedia.org/wiki/Mexico_national_under-20_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17736508-2.html.csv | superlative | of the managers of the mexico national under - 20 football team , juan carlos chávez has the most games played . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '11', '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', 'played'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; played }'}, 'manager'], 'result': 'juan carlos chávez', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; played } ; manager }'}, 'juan carlos chávez'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; played } ; manager } ; juan carlos chávez } = true', 'tointer': 'select the row whose played record of all rows is maximum . the manager record of this row is juan carlos chávez .'} | eq { hop { argmax { all_rows ; played } ; manager } ; juan carlos chávez } = true | select the row whose played record of all rows is maximum . the manager record of this row is juan carlos chávez . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'played_5': 5, 'manager_6': 6, 'juan carlos chávez_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'played_5': 'played', 'manager_6': 'manager', 'juan carlos chávez_7': 'juan carlos chávez'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'played_5': [0], 'manager_6': [1], 'juan carlos chávez_7': [2]} | ['manager', 'mexico career', 'played', 'drawn', 'lost', 'win %'] | [['horacio casarin', '1977', '5', '4', '0', '20.0'], ['mario velarde', '1983', '3', '1', '2', '0.00'], ['jesús del muro', '1985 , 1998 - 1999', '12', '1', '2', '75.00'], ['alfonso portugal diaz', '1991', '4', '2', '1', '25.0'], ['juan de dios castillo', '1992 - 1993', '7', '2', '1', '60'], ['juan manuel alvarez', '1994', '3', '0', '1', '56.6'], ['josé luis real', '1996 - 1997 , 2001', '12', '3', '3', '50.00'], ['eduardo rergis', '2002 - 2003', '6', '1', '3', '33.3'], ['humberto grondona', '2005', '3', '0', '2', '33.3'], ['jesús ramírez', '2007 - 2009', '8', '1', '1', '75.00'], ['juan carlos chávez', '2009 - 2011', '19', '3', '4', '63.15'], ['sergio almaguer', '2011 -', '5', '0', '0', '100']] |
list of ra - aus certified aircraft types | https://en.wikipedia.org/wiki/List_of_RA-Aus_certified_aircraft_types | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17699890-1.html.csv | majority | all aus certified aircraft types have 2 seats . | {'scope': 'all', 'col': '5', 'most_or_all': 'all', 'criterion': 'equal', 'value': '2', 'subset': None} | {'func': 'all_eq', 'args': ['all_rows', 'seats', '2'], 'result': True, 'ind': 0, 'tointer': 'for the seats records of all rows , all of them are equal to 2 .', 'tostr': 'all_eq { all_rows ; seats ; 2 } = true'} | all_eq { all_rows ; seats ; 2 } = true | for the seats records of all rows , all of them are equal to 2 . | 1 | 1 | {'all_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'seats_3': 3, '2_4': 4} | {'all_eq_0': 'all_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'seats_3': 'seats', '2_4': '2'} | {'all_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'seats_3': [0], '2_4': [0]} | ['manufacturer', 'model', 'kit / factory', 'wing', 'seats'] | [['aeroprakt', 'a - 22 foxbat', 'factory', 'high wing', '2'], ['allegro', 'allegro 2000 and allegro 2007', 'approved kit and factory built', 'high wing', '2'], ['evektor', 'sportstar', 'factory', 'low', '2'], ['jabiru', 'j120', 'factory', 'high', '2'], ['jabiru', 'j160', 'both', 'high', '2'], ['jabiru', 'j170', 'both', 'high', '2'], ['jabiru', 'j230', 'both', 'high', '2'], ['jabiru', 'j250', 'kit', 'high', '2'], ['jabiru', 'ul - d', 'kit', 'high', '2'], ['pipistrel', 'sinus', 'factory & kit built approved', 'high wing', '2'], ['pipistrel', 'virus - virus sw ( short wing )', 'factory & kit built approved', 'high wing', '2'], ['savage classic , savage cruiser , savage cub', 'cub', 'factory & kit built approved', 'high wing', '2'], ['tl 2000 sting carbon', 'sting', 'approved factory built', 'low wing', '2'], ['raj hamsa ultralights', 'x - air hanuman', 'approved kit or lsa', 'high wing', '2'], ['x - air standard', 'x - air standard', 'approved kit', 'high wing', '2']] |
1999 - 2000 manchester united f.c. season | https://en.wikipedia.org/wiki/1999%E2%80%932000_Manchester_United_F.C._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12988799-9.html.csv | superlative | the highest attendance in the 1999-2000 manchester united f.c. season was for the game on march 15 , 2000 . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', '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', 'attendance'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; attendance }'}, 'date'], 'result': '15 march 2000', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; attendance } ; date }'}, '15 march 2000'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; attendance } ; date } ; 15 march 2000 } = true', 'tointer': 'select the row whose attendance record of all rows is maximum . the date record of this row is 15 march 2000 .'} | eq { hop { argmax { all_rows ; attendance } ; date } ; 15 march 2000 } = true | select the row whose attendance record of all rows is maximum . the date record of this row is 15 march 2000 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, 'date_6': 6, '15 march 2000_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', 'date_6': 'date', '15 march 2000_7': '15 march 2000'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], 'date_6': [1], '15 march 2000_7': [2]} | ['date', 'opponents', 'h / a', 'result f - a', 'attendance', 'group position'] | [['23 november 1999', 'fiorentina', 'a', '0 - 2', '36002', '3rd'], ['8 december 1999', 'valencia', 'h', '3 - 0', '54606', '2nd'], ['1 march 2000', 'bordeaux', 'h', '2 - 0', '59786', '2nd'], ['7 march 2000', 'bordeaux', 'a', '2 - 1', '30130', '1st'], ['15 march 2000', 'fiorentina', 'h', '3 - 1', '59926', '1st'], ['21 march 2000', 'valencia', 'a', '0 - 0', '40419', '1st']] |
1999 - 2000 real madrid c.f. season | https://en.wikipedia.org/wiki/1999%E2%80%932000_Real_Madrid_C.F._season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18515909-2.html.csv | aggregation | the total transfer fees paid to move players during the 1999-2000 real madrid c.f. season was 95700000 . | {'scope': 'all', 'col': '7', 'type': 'sum', 'result': '95700000', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'transfer fee'], 'result': '95700000', 'ind': 0, 'tostr': 'sum { all_rows ; transfer fee }'}, '95700000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; transfer fee } ; 95700000 } = true', 'tointer': 'the sum of the transfer fee record of all rows is 95700000 .'} | round_eq { sum { all_rows ; transfer fee } ; 95700000 } = true | the sum of the transfer fee record of all rows is 95700000 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'transfer fee_4': 4, '95700000_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'transfer fee_4': 'transfer fee', '95700000_5': '95700000'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'transfer fee_4': [0], '95700000_5': [1]} | ['nat', 'name', 'moving from', 'type', 'transfer window', 'ends', 'transfer fee'] | [['eng', 'mcmanaman', 'liverpool', 'transfer', 'summer', '2003', 'free'], ['fra', 'anelka', 'arsenal', 'transfer', 'summer', '2000', '34000000'], ['bih', 'baljić', 'fenerbahçe', 'transfer', 'summer', '2002', '26000000'], ['esp', 'helguera', 'espanyol', 'transfer', 'summer', '2007', '15000000'], ['esp', 'm salgado', 'celta de vigo', 'transfer', 'summer', '2009', '12000000'], ['cameroon', 'geremi', 'gençlerbirliği', 'transfer', 'summer', '2003', '4200000'], ['arg', 'bizarri', 'racing', 'transfer', 'summer', '2000', '2000000'], ['bra', 'júlio césar', 'valladolid', 'transfer', 'summer', '2000', '2500000']] |
2007 - 08 philadelphia flyers season | https://en.wikipedia.org/wiki/2007%E2%80%9308_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11902580-4.html.csv | comparative | the philadelphia flyers had a game against the pittsburgh visitor earlier than boston in the the 2007 - 08 season . | {'row_1': '6', 'row_2': '13', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'pittsburgh'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose visitor record fuzzily matches to pittsburgh .', 'tostr': 'filter_eq { all_rows ; visitor ; pittsburgh }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; visitor ; pittsburgh } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to pittsburgh . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'visitor', 'boston'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose visitor record fuzzily matches to boston .', 'tostr': 'filter_eq { all_rows ; visitor ; boston }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; visitor ; boston } ; date }', 'tointer': 'select the rows whose visitor record fuzzily matches to boston . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; visitor ; pittsburgh } ; date } ; hop { filter_eq { all_rows ; visitor ; boston } ; date } } = true', 'tointer': 'select the rows whose visitor record fuzzily matches to pittsburgh . take the date record of this row . select the rows whose visitor record fuzzily matches to boston . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; visitor ; pittsburgh } ; date } ; hop { filter_eq { all_rows ; visitor ; boston } ; date } } = true | select the rows whose visitor record fuzzily matches to pittsburgh . take the date record of this row . select the rows whose visitor record fuzzily matches to boston . 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, 'visitor_7': 7, 'pittsburgh_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'visitor_11': 11, 'boston_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', 'visitor_7': 'visitor', 'pittsburgh_8': 'pittsburgh', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'visitor_11': 'visitor', 'boston_12': 'boston', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'visitor_7': [0], 'pittsburgh_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'visitor_11': [1], 'boston_12': [1], 'date_13': [3]} | ['date', 'visitor', 'score', 'home', 'decision', 'attendance', 'record'] | [['november 1', 'philadelphia', '2 - 5', 'montreal', 'biron', '21173', '7 - 4 - 0'], ['november 2', 'philadelphia', '3 - 2', 'washington', 'niittymaki', '16055', '8 - 4 - 0'], ['november 5', 'philadelphia', '0 - 2', 'ny rangers', 'biron', '18200', '8 - 5 - 0'], ['november 7', 'philadelphia', '3 - 1', 'pittsburgh', 'biron', '17132', '9 - 5 - 0'], ['november 8', 'philadelphia', '1 - 4', 'new jersey', 'biron', '14948', '9 - 6 - 0'], ['november 10', 'pittsburgh', '2 - 5', 'philadelphia', 'biron', '19859', '10 - 6 - 0'], ['november 12', 'ny islanders', '2 - 3', 'philadelphia', 'biron', '19312', '11 - 6 - 0'], ['november 15', 'ny rangers', '4 - 3', 'philadelphia', 'biron', '19571', '11 - 6 - 1'], ['november 17', 'new jersey', '6 - 2', 'philadelphia', 'biron', '19621', '11 - 7 - 1'], ['november 21', 'philadelphia', '6 - 3', 'carolina', 'biron', '16351', '12 - 7 - 1'], ['november 23', 'washington', '4 - 3', 'philadelphia', 'biron', '19727', '12 - 7 - 2'], ['november 24', 'philadelphia', '4 - 3', 'ottawa', 'niittymaki', '20128', '13 - 7 - 2'], ['november 26', 'boston', '6 - 3', 'philadelphia', 'niittymaki', '19457', '13 - 8 - 2'], ['november 28', 'philadelphia', '3 - 1', 'carolina', 'biron', '15108', '14 - 8 - 2']] |
maryland public television | https://en.wikipedia.org/wiki/Maryland_Public_Television | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1381064-1.html.csv | count | a total of two maryland public television channels had their first air date on july 4 , 1987 . | {'scope': 'all', 'criterion': 'equal', 'value': 'july 4 , 1987', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'first air date', 'july 4 , 1987'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose first air date record fuzzily matches to july 4 , 1987 .', 'tostr': 'filter_eq { all_rows ; first air date ; july 4 , 1987 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; first air date ; july 4 , 1987 } }', 'tointer': 'select the rows whose first air date record fuzzily matches to july 4 , 1987 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; first air date ; july 4 , 1987 } } ; 2 } = true', 'tointer': 'select the rows whose first air date record fuzzily matches to july 4 , 1987 . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; first air date ; july 4 , 1987 } } ; 2 } = true | select the rows whose first air date record fuzzily matches to july 4 , 1987 . 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, 'first air date_5': 5, 'july 4, 1987_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', 'first air date_5': 'first air date', 'july 4, 1987_6': 'july 4 , 1987', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'first air date_5': [0], 'july 4, 1987_6': [0], '2_7': [2]} | ['station', 'city of license', 'channels tv / rf', 'first air date', 'haat', 'facility id', 'public license information'] | [['wmpb', 'baltimore', '67 ( psip ) 29 ( uhf )', 'october 5 , 1969', '309 m', '65944', 'profile cdbs'], ['wmpt 1', 'annapolis', '22 ( psip ) 42 ( uhf )', 'september 22 , 1975', '289 m', '65942', 'profile cdbs'], ['wcpb', 'salisbury', '28 ( psip ) 28 ( uhf )', 'march 18 , 1971', '155 m', '40618', 'profile cdbs'], ['wwpb', 'hagerstown', '31 ( psip ) 44 ( uhf )', 'october 5 , 1974', '369 m', '65943', 'profile cdbs'], ['wgpt', 'oakland', '36 ( psip ) 36 ( uhf )', 'july 4 , 1987', '285 m', '40619', 'profile cdbs'], ['wfpt', 'frederick', '62 ( psip ) 28 ( uhf )', 'july 4 , 1987', '158 m', '40626', 'profile cdbs']] |
1932 boston braves ( nfl ) season | https://en.wikipedia.org/wiki/1932_Boston_Braves_%28NFL%29_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14608543-1.html.csv | comparative | in the 1932 boston braves season , the chicago bears were the opponent 7 days before the staten island stapletons . | {'row_1': '5', 'row_2': '6', 'col': '2', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '7', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'chicago bears'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to chicago bears .', 'tostr': 'filter_eq { all_rows ; opponent ; chicago bears }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; chicago bears } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to chicago bears . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'staten island stapletons'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to staten island stapletons .', 'tostr': 'filter_eq { all_rows ; opponent ; staten island stapletons }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; staten island stapletons } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to staten island stapletons . take the date record of this row .'}], 'result': '-7', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; opponent ; chicago bears } ; date } ; hop { filter_eq { all_rows ; opponent ; staten island stapletons } ; date } }'}, '-7'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; opponent ; chicago bears } ; date } ; hop { filter_eq { all_rows ; opponent ; staten island stapletons } ; date } } ; -7 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to chicago bears . take the date record of this row . select the rows whose opponent record fuzzily matches to staten island stapletons . take the date record of this row . the second record is 7 larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; opponent ; chicago bears } ; date } ; hop { filter_eq { all_rows ; opponent ; staten island stapletons } ; date } } ; -7 } = true | select the rows whose opponent record fuzzily matches to chicago bears . take the date record of this row . select the rows whose opponent record fuzzily matches to staten island stapletons . take the date record of this row . the second record is 7 larger than the first record . | 6 | 6 | {'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'opponent_8': 8, 'chicago bears_9': 9, 'date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'opponent_12': 12, 'staten island stapletons_13': 13, 'date_14': 14, '-7_15': 15} | {'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'opponent_8': 'opponent', 'chicago bears_9': 'chicago bears', 'date_10': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'opponent_12': 'opponent', 'staten island stapletons_13': 'staten island stapletons', 'date_14': 'date', '-7_15': '-7'} | {'eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'opponent_8': [0], 'chicago bears_9': [0], 'date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'opponent_12': [1], 'staten island stapletons_13': [1], 'date_14': [3], '-7_15': [5]} | ['week', 'date', 'opponent', 'result', 'game site', 'record'] | [['1', 'october 2 , 1932', 'brooklyn dodgers', 'l 14 - 0', 'braves field', '0 - 1'], ['2', 'october 9 , 1932', 'new york giants', 'w 14 - 6', 'braves field', '1 - 1'], ['3', 'october 16 , 1932', 'chicago cardinals', 'l 9 - 0', 'braves field', '1 - 2'], ['4', 'october 23 , 1932', 'new york giants', 't 0 - 0', 'polo grounds', '1 - 2 - 1'], ['5', 'october 30 , 1932', 'chicago bears', 't 7 - 7', 'braves field', '1 - 2 - 2'], ['6', 'november 6 , 1932', 'staten island stapletons', 'w 19 - 6', 'braves field', '2 - 2 - 2'], ['7', 'november 13 , 1932', 'green bay packers', 'l 21 - 0', 'braves field', '2 - 3 - 2'], ['8', 'november 20 , 1932', 'portsmouth spartans', 'l 10 - 0', 'universal stadium', '2 - 4 - 2'], ['9', 'november 27 , 1932', 'chicago cardinals', 'w 8 - 6', 'comiskey park', '3 - 4 - 2'], ['10', 'december 4 , 1932', 'brooklyn dodgers', 'w 7 - 0', 'ebbets field', '4 - 4 - 2']] |
icl 20s world series 2007 - 08 | https://en.wikipedia.org/wiki/ICL_20s_World_Series_2007%E2%80%9308 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17103566-1.html.csv | unique | imran nazir is the only man of the match who played for icl pakistan . | {'scope': 'all', 'row': '2', 'col': '7', 'col_other': 'n/a', 'criterion': 'fuzzily_match', 'value': 'icl pakistan', 'subset': None} | {'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'man of the match', 'icl pakistan'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose man of the match record fuzzily matches to icl pakistan .', 'tostr': 'filter_eq { all_rows ; man of the match ; icl pakistan }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; man of the match ; icl pakistan } } = true', 'tointer': 'select the rows whose man of the match record fuzzily matches to icl pakistan . there is only one such row in the table .'} | only { filter_eq { all_rows ; man of the match ; icl pakistan } } = true | select the rows whose man of the match record fuzzily matches to icl pakistan . 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, 'man of the match_4': 4, 'icl pakistan_5': 5} | {'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'man of the match_4': 'man of the match', 'icl pakistan_5': 'icl pakistan'} | {'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'man of the match_4': [0], 'icl pakistan_5': [0]} | ['match number', 'date', 'venue', 'team 1', 'team 2', 'result', 'man of the match'] | [['1', 'april 9', 'hyderabad', 'icl world', 'icl india', 'icl world by 8 wickets', 'damien martyn ( icl world )'], ['2', 'april 10', 'hyderabad', 'icl pakistan', 'icl world', 'icl pakistan by 9 wickets', 'imran nazir ( icl pakistan )'], ['3', 'april 11', 'hyderabad', 'icl india', 'icl pakistan', 'icl india by 4 wickets', 'ibrahim khaleel ( icl india )'], ['4', 'april 12', 'hyderabad', 'icl india', 'icl world', 'icl india by 4 wickets', 'stuart binny ( icl india )'], ['5', 'april 13', 'hyderabad', 'icl india', 'icl pakistan', 'icl india by 4 wickets', 'tejinder pal singh ( icl india )']] |
1913 world wrestling championships | https://en.wikipedia.org/wiki/1913_World_Wrestling_Championships | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15980739-1.html.csv | comparative | at the 1913 world wrestling championships , sweden won one more gold medal than germany won . | {'row_1': '1', 'row_2': '2', 'col': '3', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'yes', 'diff_result': None} | {'func': 'and', 'args': [{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'sweden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to sweden .', 'tostr': 'filter_eq { all_rows ; nation ; sweden }'}, 'gold'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; sweden } ; gold }', 'tointer': 'select the rows whose nation record fuzzily matches to sweden . take the gold record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'germany'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to germany .', 'tostr': 'filter_eq { all_rows ; nation ; germany }'}, 'gold'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; germany } ; gold }', 'tointer': 'select the rows whose nation record fuzzily matches to germany . take the gold record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; hop { filter_eq { all_rows ; nation ; germany } ; gold } }', 'tointer': 'select the rows whose nation record fuzzily matches to sweden . take the gold record of this row . select the rows whose nation record fuzzily matches to germany . take the gold record of this row . the first record is greater than the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'sweden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record fuzzily matches to sweden .', 'tostr': 'filter_eq { all_rows ; nation ; sweden }'}, 'gold'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nation ; sweden } ; gold }', 'tointer': 'select the rows whose nation record fuzzily matches to sweden . take the gold record of this row .'}, '2'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; 2 }', 'tointer': 'the gold record of the first row is 2 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nation', 'germany'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose nation record fuzzily matches to germany .', 'tostr': 'filter_eq { all_rows ; nation ; germany }'}, 'gold'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; nation ; germany } ; gold }', 'tointer': 'select the rows whose nation record fuzzily matches to germany . take the gold record of this row .'}, '1'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; nation ; germany } ; gold } ; 1 }', 'tointer': 'the gold record of the second row is 1 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; 2 } ; eq { hop { filter_eq { all_rows ; nation ; germany } ; gold } ; 1 } }', 'tointer': 'the gold record of the first row is 2 . the gold record of the second row is 1 .'}], 'result': True, 'ind': 8, 'tostr': 'and { greater { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; hop { filter_eq { all_rows ; nation ; germany } ; gold } } ; and { eq { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; 2 } ; eq { hop { filter_eq { all_rows ; nation ; germany } ; gold } ; 1 } } } = true', 'tointer': 'select the rows whose nation record fuzzily matches to sweden . take the gold record of this row . select the rows whose nation record fuzzily matches to germany . take the gold record of this row . the first record is greater than the second record . the gold record of the first row is 2 . the gold record of the second row is 1 .'} | and { greater { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; hop { filter_eq { all_rows ; nation ; germany } ; gold } } ; and { eq { hop { filter_eq { all_rows ; nation ; sweden } ; gold } ; 2 } ; eq { hop { filter_eq { all_rows ; nation ; germany } ; gold } ; 1 } } } = true | select the rows whose nation record fuzzily matches to sweden . take the gold record of this row . select the rows whose nation record fuzzily matches to germany . take the gold record of this row . the first record is greater than the second record . the gold record of the first row is 2 . the gold record of the second row is 1 . | 13 | 9 | {'and_8': 8, 'result_9': 9, 'greater_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'nation_11': 11, 'sweden_12': 12, 'gold_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'nation_15': 15, 'germany_16': 16, 'gold_17': 17, 'and_7': 7, 'eq_5': 5, '2_18': 18, 'eq_6': 6, '1_19': 19} | {'and_8': 'and', 'result_9': 'true', 'greater_4': 'greater', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'nation_11': 'nation', 'sweden_12': 'sweden', 'gold_13': 'gold', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'nation_15': 'nation', 'germany_16': 'germany', 'gold_17': 'gold', 'and_7': 'and', 'eq_5': 'eq', '2_18': '2', 'eq_6': 'eq', '1_19': '1'} | {'and_8': [9], 'result_9': [], 'greater_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'nation_11': [0], 'sweden_12': [0], 'gold_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'nation_15': [1], 'germany_16': [1], 'gold_17': [3], 'and_7': [8], 'eq_5': [7], '2_18': [5], 'eq_6': [7], '1_19': [6]} | ['rank', 'nation', 'gold', 'silver', 'bronze', 'total'] | [['1', 'sweden', '2', '2', '0', '4'], ['2', 'germany', '1', '1', '3', '5'], ['3', 'russia', '1', '0', '0', '1'], ['4', 'austria', '0', '1', '0', '1'], ['5', 'bohemia', '0', '0', '1', '1'], ['total', 'total', '4', '4', '4', '12']] |
scotland national rugby league team match results | https://en.wikipedia.org/wiki/Scotland_national_rugby_league_team_match_results | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18304748-2.html.csv | aggregation | the average crowd attendance of scotland national rugby league matches is 2900 . | {'scope': 'all', 'col': '5', 'type': 'average', 'result': '2900', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '2900', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '2900'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 2900 } = true', 'tointer': 'the average of the attendance record of all rows is 2900 .'} | round_eq { avg { all_rows ; attendance } ; 2900 } = true | the average of the attendance record of all rows is 2900 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '2900_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '2900_5': '2900'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '2900_5': [1]} | ['date', 'result', 'competition', 'venue', 'attendance'] | [['29 october 2000', 'scotland 16 - 17 new zealand māori', 'world cup', 'glasgow', '2000'], ['1 november 2000', 'ireland 18 - 6 scotland', 'world cup', 'dublin', '2000'], ['5 november 2000', 'scotland 12 - 20 samoa', 'world cup', 'edinburgh', '2000'], ['3 july 2001', 'france 24 - 40 scotland', 'friendly', 'lezignan', '3000'], ['26 october 2003', 'scotland 22 - 24 ireland', 'european nations cup', 'glasgow', '1000'], ['9 november 2003', 'france 6 - 8 scotland', 'european nations cup', 'narbonne', '2000'], ['24 october 2004', 'scotland 30 - 22 wales', 'european nations cup', 'glasgow', '1000'], ['29 october 2004', 'ireland 43 - 10 scotland', 'european nations cup', 'navan', '600'], ['16 october 2005', 'wales 22 - 14 scotland', 'european nations cup', 'bridgend', '1000'], ['23 october 2005', 'scotland 6 - 12 ireland', 'european nations cup', 'glasgow', '1000'], ['29 october 2006', 'wales 14 - 21 scotland', 'world cup qualification', 'bridgend', '2000'], ['27 october 2007', 'france 46 - 16 scotland', 'friendly', 'perpignan', '7000'], ['4 november 2007', 'scotland 16 - 18 wales', 'world cup qualification', 'glasgow', '1000'], ['26 october 2008', 'scotland 18 - 36 france', 'world cup', 'canberra', '9000'], ['5 november 2008', 'scotland 18 - 16 fiji', 'world cup', 'gosford', '10000'], ['8 november 2008', 'scotland 0 - 48 tonga', 'world cup', 'rockhampton', '6000'], ['17 october 2009', 'italy - 0 - 104 scotland', 'european nations cup', 'padova', '2139'], ['1 november 2009', 'scotland 22 - 10 lebanon', 'european nations cup', 'glasgow', '752'], ['8 november 2009', 'wales 28 - 16 scotland', 'european nations cup', 'bridgend', '1608']] |
skal vi danse ? ( season 6 ) | https://en.wikipedia.org/wiki/Skal_vi_danse%3F_%28season_6%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28677723-14.html.csv | count | for season 6 of skal vi danse ? , when the total was over 30 , there were two times that the style was jive . | {'scope': 'subset', 'criterion': 'equal', 'value': 'jive', 'result': '2', 'col': '2', 'subset': {'col': '8', 'criterion': 'greater_than', 'value': '30'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'total', '30'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; total ; 30 }', 'tointer': 'select the rows whose total record is greater than 30 .'}, 'style', 'jive'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose total record is greater than 30 . among these rows , select the rows whose style record fuzzily matches to jive .', 'tostr': 'filter_eq { filter_greater { all_rows ; total ; 30 } ; style ; jive }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater { all_rows ; total ; 30 } ; style ; jive } }', 'tointer': 'select the rows whose total record is greater than 30 . among these rows , select the rows whose style record fuzzily matches to jive . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater { all_rows ; total ; 30 } ; style ; jive } } ; 2 } = true', 'tointer': 'select the rows whose total record is greater than 30 . among these rows , select the rows whose style record fuzzily matches to jive . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater { all_rows ; total ; 30 } ; style ; jive } } ; 2 } = true | select the rows whose total record is greater than 30 . among these rows , select the rows whose style record fuzzily matches to jive . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_0': 0, 'all_rows_5': 5, 'total_6': 6, '30_7': 7, 'style_8': 8, 'jive_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_0': 'filter_greater', 'all_rows_5': 'all_rows', 'total_6': 'total', '30_7': '30', 'style_8': 'style', 'jive_9': 'jive', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_0': [1], 'all_rows_5': [0], 'total_6': [0], '30_7': [0], 'style_8': [1], 'jive_9': [1], '2_10': [3]} | ['couple', 'style', 'music', 'trine dehli cleve', 'tor fløysvik', 'karianne gulliksen', 'christer tornell', 'total'] | [['åsleik & nadia', 'samba', 'for once in my life - stevie wonder', '8', '8', '7', '7', '30'], ['åsleik & nadia', 'jive', 'footloose - kenny loggins', '10', '10', '10', '9', '39'], ['maria & asmund', 'tango', "i 've seen that face before - grace jones", '8', '8', '8', '8', '32'], ['maria & asmund', 'jive', 'hanky panky - madonna', '9', '8', '9', '9', '35'], ['stig & alexandra', 'english waltz', "if i ai n't got you - alicia keys", '10', '9', '10', '9', '38'], ['stig & alexandra', 'jive', "i 'm so excited - the pointer sisters", '7', '6', '7', '7', '27'], ['aylar & egor', 'pasodoble', 'el secondo orchester - felix gary', '8', '10', '9', '8', '35']] |
4x4 ( casiopea album ) | https://en.wikipedia.org/wiki/4x4_%28Casiopea_album%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12703608-1.html.csv | majority | a majority of the 4x4 albums were off of the alfa records label . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'alfa records', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'label', 'alfa records'], 'result': True, 'ind': 0, 'tointer': 'for the label records of all rows , most of them fuzzily match to alfa records .', 'tostr': 'most_eq { all_rows ; label ; alfa records } = true'} | most_eq { all_rows ; label ; alfa records } = true | for the label records of all rows , most of them fuzzily match to alfa records . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'label_3': 3, 'alfa records_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'label_3': 'label', 'alfa records_4': 'alfa records'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'label_3': [0], 'alfa records_4': [0]} | ['region', 'date', 'label', 'format', 'catalog'] | [['japan', 'december 16 , 1982', 'alfa records', 'stereo lp', 'alr - 28045'], ['japan', 'february 22 , 1984', 'alfa records', 'cd', '38xa - 10'], ['japan', 'january 25 , 1987', 'alfa records', 'cd', '32xa - 114'], ['japan', 'march 21 , 1992', 'alfa records', 'cd', 'alca - 277'], ['japan', 'july 27 , 1994', 'alfa records', 'cd', 'alca - 9008'], ['japan', 'july 23 , 1998', 'alfa records', 'cd', 'alca - 9203'], ['japan', 'january 23 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2208'], ['japan', 'february 14 , 2002', 'village records', 'ed remaster cd', 'vrcl - 2228'], ['japan', 'may 27 , 2009', 'sony music direct', 'ed remaster cd', 'mhcl - 20010']] |
united states house of representatives elections , 1972 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1972 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341707-15.html.csv | count | four of the incumbents were affiliated with the democratic party . | {'scope': 'all', 'criterion': 'equal', 'value': 'democratic', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose party record fuzzily matches to democratic .', 'tostr': 'filter_eq { all_rows ; party ; democratic }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; party ; democratic } }', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; party ; democratic } } ; 4 } = true', 'tointer': 'select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; party ; democratic } } ; 4 } = true | select the rows whose party record fuzzily matches to democratic . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'party_5': 5, 'democratic_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'party_5': 'party', 'democratic_6': 'democratic', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'party_5': [0], 'democratic_6': [0], '4_7': [2]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['illinois 1', 'ralph h metcalfe', 'democratic', '1970', 're - elected', 'ralph h metcalfe ( d ) 91.4 % louis coggs ( r ) 8.6 %'], ['illinois 4', 'ed derwinski', 'republican', '1958', 're - elected', "ed derwinski ( r ) 70.5 % c f ' bob ' dore ( d ) 29.5 %"], ['illinois 10', 'abner j mikva redistricted from the 2nd district', 'democratic', '1968', 'lost re - election republican gain', 'samuel h young ( r ) 51.6 % abner j mikva ( d ) 48.4 %'], ['illinois 11', 'frank annunzio redistricted from the 7th district', 'democratic', '1964', 're - elected', 'frank annunzio ( d ) 53.3 % john j hoellen ( r ) 46.7 %'], ['illinois 11', 'roman c pucinski', 'democratic', '1958', 'retired to run for us senate democratic loss', 'frank annunzio ( d ) 53.3 % john j hoellen ( r ) 46.7 %'], ['illinois 12', 'phil crane redistricted from the 13th district', 'republican', '1969', 're - elected', 'phil crane ( r ) 74.2 % edwin l frank ( d ) 25.8 %'], ['illinois 15', 'cliffard d carlson', 'republican', 'april 4 , 1972 ( special )', 'retired republican loss', 'leslie c arends ( r ) 57.2 % tim l hall ( d ) 42.8 %'], ['illinois 19', 'tom railsback', 'republican', '1966', 're - elected', 'tom railsback ( r ) unopposed'], ['illinois 20', 'paul findley', 'republican', '1960', 're - elected', "paul findley ( r ) 68.8 % robert s o ' shea ( d ) 31.2 %"]] |
westinghouse broadcasting | https://en.wikipedia.org/wiki/Westinghouse_Broadcasting | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1553485-1.html.csv | majority | the majority of westinghouse broadcasting company channels are now currently cbs owned - and - operated ( o & o ) . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'cbs owned - and - operated ( o & o )', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'current affiliation', 'cbs owned - and - operated ( o & o )'], 'result': True, 'ind': 0, 'tointer': 'for the current affiliation records of all rows , most of them fuzzily match to cbs owned - and - operated ( o & o ) .', 'tostr': 'most_eq { all_rows ; current affiliation ; cbs owned - and - operated ( o & o ) } = true'} | most_eq { all_rows ; current affiliation ; cbs owned - and - operated ( o & o ) } = true | for the current affiliation records of all rows , most of them fuzzily match to cbs owned - and - operated ( o & o ) . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'current affiliation_3': 3, 'cbs owned - and - operated (o&o)_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'current affiliation_3': 'current affiliation', 'cbs owned - and - operated (o&o)_4': 'cbs owned - and - operated ( o & o )'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'current affiliation_3': [0], 'cbs owned - and - operated (o&o)_4': [0]} | ['city of license / market', 'station', 'channel tv ( dt )', 'years owned', 'current affiliation'] | [['san francisco - oakland - san jose', 'kpix', '5 ( 29 )', '1954 - 1995', 'cbs owned - and - operated ( o & o )'], ['baltimore', 'wjz - tv', '13 ( 13 )', '1957 - 1995', 'cbs owned - and - operated ( o & o )'], ['boston', 'wbz - tv', '4 ( 30 )', '1948 - 1995', 'cbs owned - and - operated ( o & o )'], ['charlotte', 'wpcq - tv ( now wcnc - tv )', '36 ( 22 )', '1980 - 1985', 'nbc affiliate owned by belo corporation'], ['cleveland', 'kyw - tv ( now wkyc - tv )', '3 ( 17 )', '1956 - 1965', 'nbc affiliate owned by gannett company'], ['philadelphia', 'wptz / kyw - tv', '3 ( 26 )', '1953 - 1956 1965 - 1995', 'cbs owned - and - operated ( o & o )']] |
1999 denver broncos season | https://en.wikipedia.org/wiki/1999_Denver_Broncos_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17990473-1.html.csv | comparative | the denver broncos played against the tampa bay buccaneers before they played against the green bay packers . | {'row_1': '3', 'row_2': '6', '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', 'opponent', 'tampa bay buccaneers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to tampa bay buccaneers .', 'tostr': 'filter_eq { all_rows ; opponent ; tampa bay buccaneers }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; tampa bay buccaneers } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to tampa bay buccaneers . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'green bay packers'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers .', 'tostr': 'filter_eq { all_rows ; opponent ; green bay packers }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; green bay packers } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; tampa bay buccaneers } ; date } ; hop { filter_eq { all_rows ; opponent ; green bay packers } ; date } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to tampa bay buccaneers . take the date record of this row . select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; tampa bay buccaneers } ; date } ; hop { filter_eq { all_rows ; opponent ; green bay packers } ; date } } = true | select the rows whose opponent record fuzzily matches to tampa bay buccaneers . take the date record of this row . select the rows whose opponent record fuzzily matches to green bay packers . take the date record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'tampa bay buccaneers_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'green bay packers_12': 12, 'date_13': 13} | {'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'tampa bay buccaneers_8': 'tampa bay buccaneers', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'green bay packers_12': 'green bay packers', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'tampa bay buccaneers_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'green bay packers_12': [1], 'date_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 13 , 1999', 'miami dolphins', 'l 38 - 21', '75623'], ['2', 'september 19 , 1999', 'kansas city chiefs', 'l 26 - 10', '78683'], ['3', 'september 26 , 1999', 'tampa bay buccaneers', 'l 13 - 10', '65297'], ['4', 'october 3 , 1999', 'new york jets', 'l 21 - 13', '74181'], ['5', 'october 10 , 1999', 'oakland raiders', 'w 16 - 13', '55704'], ['6', 'october 17 , 1999', 'green bay packers', 'w 31 - 10', '73352'], ['7', 'october 24 , 1999', 'new england patriots', 'l 24 - 23', '60011'], ['8', 'october 31 , 1999', 'minnesota vikings', 'l 23 - 20', '75021'], ['9', 'november 7 , 1999', 'san diego chargers', 'w 33 - 17', '61204'], ['10', 'november 14 , 1999', 'seattle seahawks', 'l 20 - 17', '66314'], ['11', 'november 22 , 1999', 'oakland raiders', 'w 27 - 21', '70012'], ['13', 'december 5 , 1999', 'kansas city chiefs', 'l 16 - 10', '73855'], ['14', 'december 13 , 1999', 'jacksonville jaguars', 'l 27 - 24', '71357'], ['15', 'december 19 , 1999', 'seattle seahawks', 'w 36 - 30', '65987'], ['16', 'december 25 , 1999', 'detroit lions', 'w 17 - 7', '73158'], ['17', 'january 2 , 2000', 'san diego chargers', 'l 12 - 6', '69278']] |
2001 - 02 philadelphia flyers season | https://en.wikipedia.org/wiki/2001%E2%80%9302_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14347256-5.html.csv | ordinal | the philadelphia flyers ' game against tampa bay lightning was the earliest in the 2001 - 02 season . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'game', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; game ; 1 }'}, 'opponent'], 'result': 'tampa bay lightning', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; game ; 1 } ; opponent }'}, 'tampa bay lightning'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; game ; 1 } ; opponent } ; tampa bay lightning } = true', 'tointer': 'select the row whose game record of all rows is 1st minimum . the opponent record of this row is tampa bay lightning .'} | eq { hop { nth_argmin { all_rows ; game ; 1 } ; opponent } ; tampa bay lightning } = true | select the row whose game record of all rows is 1st minimum . the opponent record of this row is tampa bay lightning . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'game_5': 5, '1_6': 6, 'opponent_7': 7, 'tampa bay lightning_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'game_5': 'game', '1_6': '1', 'opponent_7': 'opponent', 'tampa bay lightning_8': 'tampa bay lightning'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'game_5': [0], '1_6': [0], 'opponent_7': [1], 'tampa bay lightning_8': [2]} | ['game', 'december', 'opponent', 'score', 'record', 'points'] | [['24', '1', 'tampa bay lightning', '2 - 0', '11 - 7 - 5 - 1', '28'], ['25', '4', 'new york islanders', '3 - 2', '12 - 7 - 5 - 1', '30'], ['26', '6', 'new york islanders', '0 - 2', '12 - 8 - 5 - 1', '30'], ['27', '8', 'minnesota wild', '5 - 1', '13 - 8 - 5 - 1', '32'], ['28', '10', 'atlanta thrashers', '3 - 1', '14 - 8 - 5 - 1', '34'], ['29', '13', 'montreal canadiens', '2 - 3', '14 - 9 - 5 - 1', '34'], ['30', '15', 'boston bruins', '5 - 2', '15 - 9 - 5 - 1', '36'], ['31', '16', 'edmonton oilers', '2 - 3', '15 - 10 - 5 - 1', '36'], ['32', '18', 'st louis blues', '6 - 3', '16 - 10 - 5 - 1', '38'], ['33', '20', 'dallas stars', '2 - 1', '17 - 10 - 5 - 1', '40'], ['34', '22', 'carolina hurricanes', '4 - 3 ot', '18 - 10 - 5 - 1', '42'], ['35', '26', 'washington capitals', '4 - 1', '19 - 10 - 5 - 1', '44'], ['36', '28', 'phoenix coyotes', '2 - 4', '19 - 11 - 5 - 1', '44'], ['37', '29', 'colorado avalanche', '5 - 2', '20 - 11 - 5 - 1', '46'], ['38', '31', 'vancouver canucks', '2 - 1', '21 - 11 - 5 - 1', '48']] |
eurovision song contest 1970 | https://en.wikipedia.org/wiki/Eurovision_Song_Contest_1970 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184813-1.html.csv | superlative | the song " all kinds of everything " earned the most points of any song . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '12', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '3', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'song'], 'result': 'all kinds of everything', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; song }'}, 'all kinds of everything'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; song } ; all kinds of everything } = true', 'tointer': 'select the row whose points record of all rows is maximum . the song record of this row is all kinds of everything .'} | eq { hop { argmax { all_rows ; points } ; song } ; all kinds of everything } = true | select the row whose points record of all rows is maximum . the song record of this row is all kinds of everything . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'song_6': 6, 'all kinds of everything_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', 'song_6': 'song', 'all kinds of everything_7': 'all kinds of everything'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'song_6': [1], 'all kinds of everything_7': [2]} | ['language', 'artist', 'song', 'place', 'points'] | [['dutch', 'hearts of soul', 'waterman', '7', '7'], ['french', 'henri dès', 'retour', '4', '8'], ['italian', 'gianni morandi', 'occhi di ragazza', '8', '5'], ['slovene', 'eva sršen', 'pridi , dala ti bom cvet', '11', '4'], ['french', 'jean vallée', "viens l'oublier", '8', '5'], ['french', 'guy bonnet', 'marie - blanche', '4', '8'], ['english', 'mary hopkin', "knock , knock who 's there", '2', '26'], ['french', 'david alexandre winter', 'je suis tombé du ciel', '12', '0'], ['spanish', 'julio iglesias', 'gwendolyne', '4', '8'], ['french', 'dominique dussault', 'marlène', '8', '5'], ['german', 'katja ebstein', 'wunder gibt es immer wieder', '3', '12'], ['english', 'dana', 'all kinds of everything', '1', '32']] |
1998 pga championship | https://en.wikipedia.org/wiki/1998_PGA_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18048776-5.html.csv | ordinal | in the 1998 pga championship , first place went to fiji 's vijay singh . | {'scope': 'all', 'row': '1', 'col': '1', 'order': '1', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': None} | {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'place', '1'], 'result': '1', 'ind': 0, 'tostr': 'nth_min { all_rows ; place ; 1 }', 'tointer': 'the 1st minimum place record of all rows is 1 .'}, '1'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; place ; 1 } ; 1 }', 'tointer': 'the 1st minimum place record of all rows is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'place', '1'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; place ; 1 }'}, 'player'], 'result': 'vijay singh', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; place ; 1 } ; player }'}, 'vijay singh'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; place ; 1 } ; player } ; vijay singh }', 'tointer': 'the player record of the row with 1st minimum place record is vijay singh .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_min { all_rows ; place ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; place ; 1 } ; player } ; vijay singh } } = true', 'tointer': 'the 1st minimum place record of all rows is 1 . the player record of the row with 1st minimum place record is vijay singh .'} | and { eq { nth_min { all_rows ; place ; 1 } ; 1 } ; eq { hop { nth_argmin { all_rows ; place ; 1 } ; player } ; vijay singh } } = true | the 1st minimum place record of all rows is 1 . the player record of the row with 1st minimum place record is vijay singh . | 6 | 6 | {'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_7': 7, 'place_8': 8, '1_9': 9, '1_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_11': 11, 'place_12': 12, '1_13': 13, 'player_14': 14, 'vijay singh_15': 15} | {'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_7': 'all_rows', 'place_8': 'place', '1_9': '1', '1_10': '1', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_11': 'all_rows', 'place_12': 'place', '1_13': '1', 'player_14': 'player', 'vijay singh_15': 'vijay singh'} | {'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_min_0': [1], 'all_rows_7': [0], 'place_8': [0], '1_9': [0], '1_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmin_2': [3], 'all_rows_11': [2], 'place_12': [2], '1_13': [2], 'player_14': [3], 'vijay singh_15': [4]} | ['place', 'player', 'country', 'score', 'to par'] | [['1', 'vijay singh', 'fiji', '70 + 66 = 136', '4'], ['t2', 'scott gump', 'united states', '68 + 69 = 136', '3'], ['t2', 'colin montgomerie', 'scotland', '70 + 67 = 137', '3'], ['t2', 'steve stricker', 'united states', '69 + 68 = 137', '3'], ['t5', 'steve elkington', 'australia', '69 + 69 = 138', '2'], ['t5', 'brad faxon', 'united states', '70 + 68 = 138', '2'], ['t5', 'davis love iii', 'united states', '70 + 68 = 138', '2'], ['t5', 'andrew magee', 'united states', '70 + 68 = 138', '2'], ['t5', 'tiger woods', 'united states', '66 + 72 = 138', '2'], ['t10', 'john cook', 'united states', '71 + 68 = 139', '1'], ['t10', 'glen day', 'united states', '68 + 71 = 139', '1'], ['t10', 'david frost', 'south africa', '70 + 69 = 139', '1'], ['t10', 'frank lickliter', 'united states', '68 + 71 = 139', '1'], ['t10', "mark o'meara", 'united states', '69 + 70 = 139', '1']] |
wtbs - ld | https://en.wikipedia.org/wiki/WTBS-LD | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1097268-1.html.csv | count | there are four channels with an aspect of 4:3 . | {'scope': 'all', 'criterion': 'equal', 'value': '4:3', 'result': '4', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'aspect', '4:3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose aspect record fuzzily matches to 4:3 .', 'tostr': 'filter_eq { all_rows ; aspect ; 4:3 }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; aspect ; 4:3 } }', 'tointer': 'select the rows whose aspect record fuzzily matches to 4:3 . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; aspect ; 4:3 } } ; 4 } = true', 'tointer': 'select the rows whose aspect record fuzzily matches to 4:3 . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; aspect ; 4:3 } } ; 4 } = true | select the rows whose aspect record fuzzily matches to 4:3 . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'aspect_5': 5, '4:3_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'aspect_5': 'aspect', '4:3_6': '4:3', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'aspect_5': [0], '4:3_6': [0], '4_7': [2]} | ['channel', 'video', 'aspect', 'psip short name', 'programming'] | [['26.1', '1080i', '16:9', 'mfox', 'mundofox'], ['26.2', '480i', '4:3', 'lwn', 'live well network'], ['26.4', '480i', '4:3', 'jtv', 'jewelry tv'], ['26.5', '480i', '4:3', 'f24news', 'france 24 blank screen'], ['26.8', '480i', '4:3', 'tuff tv', 'tuff tv']] |
illinois women 's open | https://en.wikipedia.org/wiki/Illinois_Women%27s_Open | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11177356-1.html.csv | superlative | 2001 was the year that had the highest total winning score of the illinois women 's open . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'winning score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; winning score }'}, 'year'], 'result': '2001', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; winning score } ; year }'}, '2001'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; winning score } ; year } ; 2001 } = true', 'tointer': 'select the row whose winning score record of all rows is maximum . the year record of this row is 2001 .'} | eq { hop { argmax { all_rows ; winning score } ; year } ; 2001 } = true | select the row whose winning score record of all rows is maximum . the year record of this row is 2001 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'winning score_5': 5, 'year_6': 6, '2001_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'winning score_5': 'winning score', 'year_6': 'year', '2001_7': '2001'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'winning score_5': [0], 'year_6': [1], '2001_7': [2]} | ['year', 'champion', 'winning score', 'low amateur', 'low professional'] | [['2013', 'elise swartout', '216 ( e )', 'not avail', 'nicole jeray 216 ( e )'], ['2012', 'samantha troyanovich', '216 ( e )', 'samantha troyanovich', 'not avail 216 ( e )'], ['2011', 'jenna pearson', '216 ( e )', 'not avail', 'not avail 216 ( e )'], ['2010', 'allison fouch', '217 ( + 1 )', 'katherine hepler', 'allison fouch 217 ( + 1 )'], ['2009', 'a - aimee neff', '209 ( 7 )', 'aimee neff', 'brittany johnston 212 ( 4 )'], ['2008', 'a - aimee neff 7', '208 ( 8 )', 'aimee neff', 'seul ki park 214 ( 2 )'], ['2007', 'a - nicole schachner 6', '215 ( 1 ) playoff', 'nicole schachner', 'jenna pearson 215 ( 1 )'], ['2006', 'a - jenna pearson', '208 ( 8 )', 'jenna pearson', 'carolyn barnett - howe 213 ( 3 )'], ['2005', 'a - annika welander 5', '207 ( 9 )', 'annika welander', 'allison finney 208 ( 8 )'], ['2004', 'sarah johnston 4', '212 ( 4 )', 'noriko nakazaki 217 ( + 1 )', 'sarah johnston'], ['2003', 'nicole jeray', '212 ( 4 )', 'alexis wooster 219 ( + 3 )', 'nicole jeray'], ['2002', 'maria long', '217 ( 1 )', 'rebecca halpern 222 ( + 6 ) sarah pesavento 222 ( + 6 )', 'maria long'], ['2001', 'a - emily gilley', '223 ( + 7 )', 'emily gilley', 'dagne root 229 ( + 13 )'], ['2000', 'a - emily gilley', '217 ( + 1 )', 'emily gilley', 'jennifer broggi 219 ( + 3 )'], ['1999', 'a - kerry postillion', '214 ( 2 )', 'kerry postillion', 'margie arnold 216 ( e )'], ['1998', 'nicole jeray', '211 ( 5 )', 'kerry postillion 215 ( 1 )', 'nicole jeray'], ['1997', 'a - kerry postillion 3', '218 ( + 2 ) playoff', 'kerry postillion', 'diane daugherty 218 ( + 2 )'], ['1996', 'a - kerry postillion 2', '219 ( + 3 )', 'kerry postillion', 'margie arnold 227 ( + 11 )'], ['1995', 'diane daugherty 1', '139 ( 5 ) rain shortened', 'kristin milligan 146 ( + 2 )', 'diane daugherty']] |
2007 - 08 tennessee volunteers basketball team | https://en.wikipedia.org/wiki/2007%E2%80%9308_Tennessee_Volunteers_basketball_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14290955-1.html.csv | aggregation | the average height of the 2007 - 08 tennessee volunteers basketball team was 6 - 5 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '6 - 5', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'height'], 'result': '6 - 5', 'ind': 0, 'tostr': 'avg { all_rows ; height }'}, '6 - 5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; height } ; 6 - 5 } = true', 'tointer': 'the average of the height record of all rows is 6 - 5 .'} | round_eq { avg { all_rows ; height } ; 6 - 5 } = true | the average of the height record of all rows is 6 - 5 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'height_4': 4, '6 - 5_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'height_4': 'height', '6 - 5_5': '6 - 5'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'height_4': [0], '6 - 5_5': [1]} | ['name', 'number', 'team position', 'height', 'year'] | [['ramar smith', '12', '1', '6 - 1', 'sophomore'], ['jajuan smith', '2', '2', '6 - 2', 'senior'], ['chris lofton - c', '5', '3', '6 - 2', 'senior'], ['tyler smith', '1', '4', '6 - 7', 'sophomore'], ['wayne chism', '4', '5', '6 - 9', 'sophomore'], ['jp prince', '30', '6', '6 - 7', 'sophomore'], ['jordan howell', '15', '7', '6 - 3', 'senior'], ['brian williams', '33', '8', '6 - 10', 'freshman'], ['duke crews', '32', '9', '6 - 8', 'sophomore'], ['ryan childress', '34', '10', '6 - 9', 'junior'], ['josh tabb', '25', '11', '6 - 4', 'sophomore'], ['jayson ebio', '7', '12', '5 - 8', 'freshman ( redshirted )']] |
saturn aura | https://en.wikipedia.org/wiki/Saturn_Aura | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1373768-1.html.csv | superlative | the green line gets the best fuel mileage among all the other saturn aura engines . | {'scope': 'all', 'col_superlative': '7', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'fuel mileage ( latest epa mpg - us )'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; fuel mileage ( latest epa mpg - us ) }'}, 'trim'], 'result': 'green line', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; fuel mileage ( latest epa mpg - us ) } ; trim }'}, 'green line'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; fuel mileage ( latest epa mpg - us ) } ; trim } ; green line } = true', 'tointer': 'select the row whose fuel mileage ( latest epa mpg - us ) record of all rows is maximum . the trim record of this row is green line .'} | eq { hop { argmax { all_rows ; fuel mileage ( latest epa mpg - us ) } ; trim } ; green line } = true | select the row whose fuel mileage ( latest epa mpg - us ) record of all rows is maximum . the trim record of this row is green line . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'fuel mileage (latest epa mpg - us )_5': 5, 'trim_6': 6, 'green line_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'fuel mileage (latest epa mpg - us )_5': 'fuel mileage ( latest epa mpg - us )', 'trim_6': 'trim', 'green line_7': 'green line'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'fuel mileage (latest epa mpg - us )_5': [0], 'trim_6': [1], 'green line_7': [2]} | ['trim', 'engine', 'displacement', 'power', 'torque', 'transmission', 'fuel mileage ( latest epa mpg - us )'] | [['green line', '2.4 l lat i4 ( bas hybrid )', 'cc ( cuin )', '164hp ( 124 kw )', 'n / a', '4 - speed 4t45 - e', '26 city , 34 hwy , 29 comb'], ['xe ( 2008 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '4 - speed 4t45 - e', '22 city , 30 hwy , 25 comb'], ['xe ( 2009 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '6 - speed 6t40', '22 city , 33 hwy , 26 comb'], ['xe ( 2007 - 08 )', '3.5 l lz4 v6', 'cc ( cuin )', '219hp ( 162 kw )', 'n / a', '4 - speed 4t45 - e', '18 city , 29 hwy , 22 comb'], ['xr ( 2009 )', '2.4 l le5 i4', 'cc ( cuin )', '-', 'n / a', '6 - speed 6t40', '22 city , 33 hwy , 26 comb']] |
1981 cincinnati bengals season | https://en.wikipedia.org/wiki/1981_Cincinnati_Bengals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16764846-2.html.csv | majority | most of the games the cincinnati bengals played in the 1981 season were won by them . | {'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'} | most_eq { all_rows ; result ; w } = true | for the result records of all rows , most of them fuzzily match to w . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 6 , 1981', 'seattle seahawks', 'w 27 - 21', '41177'], ['2', 'september 13 , 1981', 'new york jets', 'w 31 - 30', '49454'], ['3', 'september 20 , 1981', 'cleveland browns', 'l 20 - 17', '52170'], ['4', 'september 27 , 1981', 'buffalo bills', 'w 27 - 24', '46418'], ['5', 'october 4 , 1981', 'houston oilers', 'l 17 - 10', '44350'], ['6', 'october 11 , 1981', 'baltimore colts', 'w 41 - 19', '33060'], ['7', 'october 18 , 1981', 'pittsburgh steelers', 'w 34 - 7', '57090'], ['8', 'october 25 , 1981', 'new orleans saints', 'l 17 - 7', '46336'], ['9', 'november 1 , 1981', 'houston oilers', 'w 34 - 21', '54736'], ['10', 'november 8 , 1981', 'san diego chargers', 'w 40 - 17', '51259'], ['11', 'november 15 , 1981', 'los angeles rams', 'w 24 - 10', '56836'], ['12', 'november 22 , 1981', 'denver broncos', 'w 38 - 21', '57207'], ['13', 'november 29 , 1981', 'cleveland browns', 'w 41 - 21', '75186'], ['14', 'december 6 , 1981', 'san francisco 49ers', 'l 21 - 3', '56796'], ['15', 'december 13 , 1981', 'pittsburgh steelers', 'w 17 - 10', '50623'], ['16', 'december 20 , 1981', 'atlanta falcons', 'w 30 - 28', '35972']] |
got \ xc5 \ x8dji line | https://en.wikipedia.org/wiki/Got%C5%8Dji_Line | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11482596-1.html.csv | count | two of the japanese railway stations are located in the city of tagawa . | {'scope': 'all', 'criterion': 'equal', 'value': 'tagawa', 'result': '2', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'tagawa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to tagawa .', 'tostr': 'filter_eq { all_rows ; location ; tagawa }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; location ; tagawa } }', 'tointer': 'select the rows whose location record fuzzily matches to tagawa . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; location ; tagawa } } ; 2 } = true', 'tointer': 'select the rows whose location record fuzzily matches to tagawa . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; location ; tagawa } } ; 2 } = true | select the rows whose location record fuzzily matches to tagawa . 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, 'location_5': 5, 'tagawa_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', 'location_5': 'location', 'tagawa_6': 'tagawa', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'location_5': [0], 'tagawa_6': [0], '2_7': [2]} | ['station', 'japanese', 'distance ( km )', 'rapid', 'location'] | [['tagawa - gotōji', '田川後藤寺', '0.0', '●', 'tagawa'], ['funao', '船尾', '3.4', '↑', 'tagawa'], ['chikuzen - shōnai', '筑前庄内', '7.1', '↑', 'iizuka'], ['shimo - kamoo', '下鴨生', '8.3', '↑', 'kama'], ['kami - mio', '上三緒', '10.2', '↑', 'iizuka'], ['shin - iizuka', '新飯塚', '13.3', '●', 'iizuka']] |
seattle supersonics all - time roster | https://en.wikipedia.org/wiki/Seattle_SuperSonics_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16772687-8.html.csv | count | there are two players on the all-time supersonics roster that play the position of c. | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'c', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'c'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to c .', 'tostr': 'filter_eq { all_rows ; position ; c }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; c } }', 'tointer': 'select the rows whose position record fuzzily matches to c . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; c } } ; 2 } = true', 'tointer': 'select the rows whose position record fuzzily matches to c . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; position ; c } } ; 2 } = true | select the rows whose position record fuzzily matches to c . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'c_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'c_6': 'c', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'c_6': [0], '2_7': [2]} | ['player', 'nationality', 'jersey number ( s )', 'position', 'years', 'from'] | [['mickaël gelabale', 'france', '15', 'sf', '2006 - 2008', 'real madrid'], ['dick gibbs', 'united states', '21', 'sf / sg', '1973 - 1974', 'utep'], ['eddie gill', 'united states', '6', 'pg', '2008', 'weber state'], ['kendall gill', 'united states', '13', 'sg / sf', '1993 - 1995', 'illinois'], ['herm gilliam', 'united states', '3', 'g / sf', '1975 - 1976', 'purdue'], ['greg graham', 'united states', '21', 'sg', '1996 - 1997', 'indiana'], ['horace grant', 'united states', '54', 'pf / c', '1999 - 2000', 'clemson'], ['leonard gray', 'united states', '11', 'pf', '1974 - 1976', 'cal state - long beach'], ['jeff green', 'united states', '22', 'sf / pf', '2007 - 2008', 'georgetown'], ['mike green', 'united states', '23', 'c / pf', '1976 - 1977', 'louisiana tech'], ['john greig', 'united states', '22', 'f', '1982 - 1983', 'oregon'], ['adrian griffin', 'united states', '22', 'g / sf', '2008', 'seton hall']] |
emily hewson | https://en.wikipedia.org/wiki/Emily_Hewson | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15272495-2.html.csv | superlative | the last time the emily hewson was a winner in a match was on september 26 , 2004 . | {'scope': 'subset', 'col_superlative': '2', 'row_superlative': '2', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': {'col': '1', 'criterion': 'equal', 'value': 'winner'}} | {'func': 'eq', 'args': [{'func': 'max', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'outcome', 'winner'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; outcome ; winner }', 'tointer': 'select the rows whose outcome record fuzzily matches to winner .'}, 'date'], 'result': '26 september 2004', 'ind': 1, 'tostr': 'max { filter_eq { all_rows ; outcome ; winner } ; date }', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . the maximum date record of these rows is 26 september 2004 .'}, '26 september 2004'], 'result': True, 'ind': 2, 'tostr': 'eq { max { filter_eq { all_rows ; outcome ; winner } ; date } ; 26 september 2004 } = true', 'tointer': 'select the rows whose outcome record fuzzily matches to winner . the maximum date record of these rows is 26 september 2004 .'} | eq { max { filter_eq { all_rows ; outcome ; winner } ; date } ; 26 september 2004 } = true | select the rows whose outcome record fuzzily matches to winner . the maximum date record of these rows is 26 september 2004 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'max_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'outcome_5': 5, 'winner_6': 6, 'date_7': 7, '26 september 2004_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'max_1': 'max', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'outcome_5': 'outcome', 'winner_6': 'winner', 'date_7': 'date', '26 september 2004_8': '26 september 2004'} | {'eq_2': [3], 'result_3': [], 'max_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'outcome_5': [0], 'winner_6': [0], 'date_7': [1], '26 september 2004_8': [2]} | ['outcome', 'date', 'tournament', 'surface', 'opponent in the final', 'score'] | [['winner', '28 march 2004', 'yarrawonga , australia', 'grass', 'kavitha krishnamurthy', '6 - 7 ( 4 - 7 ) 7 - 6 ( 8 - 6 ) 6 - 3'], ['winner', '26 september 2004', 'hiroshima , japan', 'grass', 'yurika sema', '6 - 1 7 - 6 ( 8 - 6 )'], ['runner - up', '20 march 2005', 'yarrawonga , australia', 'grass', 'marina erakovic', '3 - 6 6 - 4 4 - 6'], ['runner - up', '30 july 2005', 'dublin , ireland', 'carpet', 'suzanne van hartingsveldt', '3 - 6 2 - 6'], ['runner - up', '3 september 2005', 'gladstone , australia', 'hard', 'daniella dominikovic', '4 - 6 3 - 6']] |
2008 oafl season | https://en.wikipedia.org/wiki/2008_OAFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15764352-3.html.csv | majority | most of the games on 5-31-08 were played at humber college north . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'humber college north', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'ground', 'humber college north'], 'result': True, 'ind': 0, 'tointer': 'for the ground records of all rows , most of them fuzzily match to humber college north .', 'tostr': 'most_eq { all_rows ; ground ; humber college north } = true'} | most_eq { all_rows ; ground ; humber college north } = true | for the ground records of all rows , most of them fuzzily match to humber college north . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'ground_3': 3, 'humber college north_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'ground_3': 'ground', 'humber college north_4': 'humber college north'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'ground_3': [0], 'humber college north_4': [0]} | ['date', 'time', 'home', 'away', 'score', 'ground'] | [['2008 - 05 - 31', '10:00', 'toronto downtown dingos', 'broadview hawks', '34 - 86', 'humber college north'], ['2008 - 05 - 31', '11:00', 'hamilton wildcats', 'etobicoke kangaroos', '52 - 110', 'humber college north'], ['2008 - 05 - 31', '14:00', 'ottawa swans', 'high park demons', '20 - 99', 'rideau carleton raceway'], ['2008 - 05 - 31', '14:00', 'guelph gargoyles', 'central blues', '65 - 19', 'magaret green park'], ['2008 - 05 - 31', '14:00', 'toronto eagles', 'toronto rebels', '106 - 35', 'humber college north']] |
rowing at the 2008 summer olympics - men 's double sculls | https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Men%27s_double_sculls | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662686-3.html.csv | superlative | for rowing at the 2008 summer olympics - men 's double sculls , the fastsest time for an estonian racer was 6:27:95 . | {'scope': 'subset', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '3', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'estonia'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'estonia'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; estonia }', 'tointer': 'select the rows whose country record fuzzily matches to estonia .'}, 'time'], 'result': '6:27.95', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; country ; estonia } ; time }', 'tointer': 'select the rows whose country record fuzzily matches to estonia . the minimum time record of these rows is 6:27.95 .'}, '6:27.95'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; country ; estonia } ; time } ; 6:27.95 } = true', 'tointer': 'select the rows whose country record fuzzily matches to estonia . the minimum time record of these rows is 6:27.95 .'} | eq { min { filter_eq { all_rows ; country ; estonia } ; time } ; 6:27.95 } = true | select the rows whose country record fuzzily matches to estonia . the minimum time record of these rows is 6:27.95 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'country_5': 5, 'estonia_6': 6, 'time_7': 7, '6:27.95_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'country_5': 'country', 'estonia_6': 'estonia', 'time_7': 'time', '6:27.95_8': '6:27.95'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'country_5': [0], 'estonia_6': [0], 'time_7': [1], '6:27.95_8': [2]} | ['rank', 'rowers', 'country', 'time', 'notes'] | [['1', 'matthew wells , stephen rowbotham', 'great britain', '6:26.33', 'sa / b'], ['2', 'ante kušurin , mario vekić', 'croatia', '6:27.38', 'sa / b'], ['3', 'tõnu endrekson , jüri jaanson', 'estonia', '6:27.95', 'sa / b'], ['4', 'alexander kornilov , alexey svirin', 'russia', '6:44.46', 'r'], ['5', 'haidar nozad , hussein jebur', 'iraq', '7:00:46', 'r']] |
1966 los angeles rams season | https://en.wikipedia.org/wiki/1966_Los_Angeles_Rams_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11171288-1.html.csv | count | in the 1966 los angeles rams ' season , it lost 1 of the 2 games played against the minnesota vikings . | {'scope': 'subset', 'criterion': 'equal', 'value': 'l', 'result': '1', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'minnesota vikings'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'minnesota vikings'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; opponent ; minnesota vikings }', 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings .'}, 'result', 'l'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings . among these rows , select the rows whose result record fuzzily matches to l .', 'tostr': 'filter_eq { filter_eq { all_rows ; opponent ; minnesota vikings } ; result ; l }'}], 'result': '1', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; opponent ; minnesota vikings } ; result ; l } }', 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings . among these rows , select the rows whose result record fuzzily matches to l . the number of such rows is 1 .'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; opponent ; minnesota vikings } ; result ; l } } ; 1 } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to minnesota vikings . among these rows , select the rows whose result record fuzzily matches to l . the number of such rows is 1 .'} | eq { count { filter_eq { filter_eq { all_rows ; opponent ; minnesota vikings } ; result ; l } } ; 1 } = true | select the rows whose opponent record fuzzily matches to minnesota vikings . among these rows , select the rows whose result record fuzzily matches to l . 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, 'opponent_6': 6, 'minnesota vikings_7': 7, 'result_8': 8, 'l_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', 'opponent_6': 'opponent', 'minnesota vikings_7': 'minnesota vikings', 'result_8': 'result', 'l_9': 'l', '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], 'opponent_6': [0], 'minnesota vikings_7': [0], 'result_8': [1], 'l_9': [1], '1_10': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 11 , 1966', 'atlanta falcons', 'w 19 - 14', '54418'], ['2', 'september 16 , 1966', 'chicago bears', 'w 31 - 17', '58916'], ['3', 'september 25 , 1966', 'green bay packers', 'l 24 - 13', '50861'], ['4', 'september 30 , 1966', 'san francisco 49ers', 'w 34 - 3', '45642'], ['5', 'october 9 , 1966', 'detroit lions', 'w 14 - 7', '52793'], ['6', 'october 16 , 1966', 'minnesota vikings', 'l 35 - 7', '47426'], ['7', 'october 23 , 1966', 'chicago bears', 'l 17 - 10', '47475'], ['8', 'october 30 , 1966', 'baltimore colts', 'l 17 - 3', '57898'], ['9', 'november 6 , 1966', 'san francisco 49ers', 'l 21 - 13', '35372'], ['10', 'november 13 , 1966', 'new york giants', 'w 55 - 14', '34746'], ['11', 'november 20 , 1966', 'minnesota vikings', 'w 21 - 6', '38775'], ['12', 'november 27 , 1966', 'baltimore colts', 'w 23 - 7', '60238'], ['13', 'december 4 , 1966', 'detroit lions', 'w 23 - 3', '40039'], ['15', 'december 18 , 1966', 'green bay packers', 'l 27 - 23', '72416']] |
1987 200 miles of norisring | https://en.wikipedia.org/wiki/1987_200_Miles_of_Norisring | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16861730-2.html.csv | count | a total of eight drivers used a porsche 962 c type chassis - engine in the 1987 200 miles of norisring race . | {'scope': 'all', 'criterion': 'equal', 'value': 'porsche 962 c', 'result': '8', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis - engine', 'porsche 962 c'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis - engine record fuzzily matches to porsche 962 c .', 'tostr': 'filter_eq { all_rows ; chassis - engine ; porsche 962 c }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; chassis - engine ; porsche 962 c } }', 'tointer': 'select the rows whose chassis - engine record fuzzily matches to porsche 962 c . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; chassis - engine ; porsche 962 c } } ; 8 } = true', 'tointer': 'select the rows whose chassis - engine record fuzzily matches to porsche 962 c . the number of such rows is 8 .'} | eq { count { filter_eq { all_rows ; chassis - engine ; porsche 962 c } } ; 8 } = true | select the rows whose chassis - engine record fuzzily matches to porsche 962 c . the number of such rows is 8 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'chassis - engine_5': 5, 'porsche 962 c_6': 6, '8_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'chassis - engine_5': 'chassis - engine', 'porsche 962 c_6': 'porsche 962 c', '8_7': '8'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'chassis - engine_5': [0], 'porsche 962 c_6': [0], '8_7': [2]} | ['class', 'team', 'driver', 'chassis - engine', 'laps'] | [['c1', 'silk cut jaguar', 'raul boesel', 'jaguar xjr - 8', '77'], ['c1', 'liqui moly equipe', 'jonathan palmer', 'porsche 962 c', '77'], ['c1', 'brun motorsport', 'jochen mass', 'porsche 962 c', '76'], ['c1', 'joest racing', 'stanley dickens', 'porsche 962 c', '75'], ['c1', 'primagaz competition', 'pierre yver', 'porsche 962 c', '72'], ['c2', 'swiftair ecurie ecosse', 'david leslie', 'ecosse c286 - ford', '72'], ['c2', 'spice engineering', 'gordon spice', 'spice se86c - ford', '71'], ['c2', 'tiga ford denmark', 'john sheldon', 'tiga gc287 - ford', '70'], ['c2', 'spice engineering', 'nick adams', 'spice se87c - ford', '70'], ['c1', 'brun motorsport', 'jésus pareja', 'porsche 962 c', '70'], ['c2', 'kelmar racing', 'ranieri randaccio', 'tiga gc85 - ford', '69'], ['c2', 'schanche racing', 'martin schanche', 'argo jm19b - zakspeed', '64'], ['c1', 'porsche kremer racing', 'kris nissen', 'porsche 962 c', '75'], ['c1', 'blaupunkt joest racing', 'klaus ludwig', 'porsche 962 c', '77'], ['c1', 'porsche ag', 'derek bell', 'porsche 962 c', '61'], ['c2', 'swiftair ecurie ecosse', 'mike wilds', 'ecosse c286 - ford', '25']] |
communist league ( new zealand ) | https://en.wikipedia.org/wiki/Communist_League_%28New_Zealand%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1110530-1.html.csv | ordinal | 2002 had the 2nd highest amount of votes for the communist league . | {'row': '5', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'votes', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; votes ; 2 }'}, 'election'], 'result': '2002', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; votes ; 2 } ; election }'}, '2002'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; votes ; 2 } ; election } ; 2002 } = true', 'tointer': 'select the row whose votes record of all rows is 2nd maximum . the election record of this row is 2002 .'} | eq { hop { nth_argmax { all_rows ; votes ; 2 } ; election } ; 2002 } = true | select the row whose votes record of all rows is 2nd maximum . the election record of this row is 2002 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'votes_5': 5, '2_6': 6, 'election_7': 7, '2002_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'votes_5': 'votes', '2_6': '2', 'election_7': 'election', '2002_8': '2002'} | {'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'votes_5': [0], '2_6': [0], 'election_7': [1], '2002_8': [2]} | ['election', 'candidates', 'seats won', 'votes', '% of vote'] | [['1990', '9', '0', '210', '0.01'], ['1993', '2', '0', '84', '0.00'], ['1996', '2', '0', '99', '0.00'], ['1999', '2', '0', '89', '0.00'], ['2002', '2', '0', '171', '0.01'], ['2005', '2', '0', '107', '0.00'], ['2008', '2', '0', '74', '0.00']] |
kairat nurdauletov | https://en.wikipedia.org/wiki/Kairat_Nurdauletov | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12706952-1.html.csv | majority | most of the competitions that kairat nurdauletov participated in were held in the month september . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'september', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'date', 'september'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , most of them fuzzily match to september .', 'tostr': 'most_eq { all_rows ; date ; september } = true'} | most_eq { all_rows ; date ; september } = true | for the date records of all rows , most of them fuzzily match to september . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'september_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'september_4': 'september'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'september_4': [0]} | ['date', 'venue', 'score', 'result', 'competition'] | [['8 september 2007', 'central stadium , almaty , kazakhstan', '1 - 1', 'draw', 'friendly'], ['7 october 2011', 'king baudouin stadium , almaty , kazakhstan', '4 - 1', 'lost', 'friendly'], ['1 june 2012', 'central stadium , almaty , kazakhstan', '5 - 2', 'win', 'friendly'], ['7 september 2012', 'astana arena , astana , kazakhstan', '1 - 2', 'loss', 'world cup 2014 qualilfier'], ['6 september 2013', 'astana arena , astana , kazakhstan', '2 - 1', 'win', 'world cup 2014 qualilfier']] |
1978 green bay packers season | https://en.wikipedia.org/wiki/1978_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14656160-1.html.csv | count | two of these green bay packers players had the position of quarterback . | {'scope': 'all', 'criterion': 'equal', 'value': 'quarterback', 'result': '2', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'quarterback'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to quarterback .', 'tostr': 'filter_eq { all_rows ; position ; quarterback }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; quarterback } }', 'tointer': 'select the rows whose position record fuzzily matches to quarterback . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; quarterback } } ; 2 } = true', 'tointer': 'select the rows whose position record fuzzily matches to quarterback . the number of such rows is 2 .'} | eq { count { filter_eq { all_rows ; position ; quarterback } } ; 2 } = true | select the rows whose position record fuzzily matches to quarterback . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'quarterback_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'quarterback_6': 'quarterback', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'quarterback_6': [0], '2_7': [2]} | ['round', 'pick', 'player', 'position', 'school'] | [['1', '6', 'james lofton', 'wide receiver', 'stanford'], ['2', '34', 'michael hunt', 'linebacker', 'minnesota'], ['3', '62', 'estus hood', 'defensive back', 'illinois state'], ['5', '116', 'mike douglass', 'linebacker', 'san diego state'], ['5', '128', 'willie wilder', 'running back', 'florida'], ['6', '144', 'leotis harris', 'guard', 'arkansas'], ['7', '172', 'george plasketes', 'linebacker', 'ole miss'], ['8', '200', 'dennis sproul', 'quarterback', 'arizona state'], ['9', '228', 'keith myers', 'quarterback', 'utah state'], ['10', '256', 'larry key', 'running back', 'florida state'], ['10', '259', 'mark totten', 'center', 'florida'], ['11', '284', 'terry jones', 'defensive tackle', 'alabama'], ['12', '312', 'eason ramson', 'tight end', 'washington state']] |
1989 open championship | https://en.wikipedia.org/wiki/1989_Open_Championship | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18135501-6.html.csv | aggregation | in the 1989 open championship the average score of the players was 277 . | {'scope': 'all', 'col': '4', 'type': 'average', 'result': '277', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '277', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '277'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 277 } = true', 'tointer': 'the average of the score record of all rows is 277 .'} | round_eq { avg { all_rows ; score } ; 277 } = true | the average of the score record of all rows is 277 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '277_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '277_5': '277'} | {'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '277_5': [1]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['t1', 'mark calcavecchia', 'united states', '71 + 68 + 68 + 68 = 275', '- 13', 'playoff'], ['t1', 'greg norman', 'australia', '69 + 70 + 72 + 64 = 275', '- 13', 'playoff'], ['t1', 'wayne grady', 'australia', '68 + 67 + 69 + 71 = 275', '- 13', 'playoff'], ['4', 'tom watson', 'united states', '69 + 68 + 68 + 72 = 277', '- 11', '40000'], ['5', 'jodie mudd', 'united states', '73 + 67 + 68 + 70 = 278', '- 10', '30000'], ['t6', 'fred couples', 'united states', '68 + 71 + 68 + 72 = 279', '- 9', '26000'], ['t6', 'david feherty', 'northern ireland', '71 + 67 + 69 + 72 = 279', '- 9', '26000'], ['t8', 'eduardo romero', 'argentina', '68 + 70 + 75 + 67 = 280', '- 8', '21000'], ['t8', 'paul azinger', 'united states', '68 + 73 + 67 + 72 = 280', '- 8', '21000'], ['t8', 'payne stewart', 'united states', '72 + 65 + 69 + 74 = 280', '- 8', '21000']] |
2001 senior pga tour | https://en.wikipedia.org/wiki/2001_Senior_PGA_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11603267-3.html.csv | majority | most of the players won three or more times . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '3', 'subset': None} | {'func': 'most_greater_eq', 'args': ['all_rows', 'wins', '3'], 'result': True, 'ind': 0, 'tointer': 'for the wins records of all rows , most of them are greater than or equal to 3 .', 'tostr': 'most_greater_eq { all_rows ; wins ; 3 } = true'} | most_greater_eq { all_rows ; wins ; 3 } = true | for the wins records of all rows , most of them are greater than or equal to 3 . | 1 | 1 | {'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'wins_3': 3, '3_4': 4} | {'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'wins_3': 'wins', '3_4': '3'} | {'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'wins_3': [0], '3_4': [0]} | ['rank', 'player', 'country', 'earnings', 'events', 'wins'] | [['1', 'allen doyle', 'united states', '2553582', '34', '2'], ['2', 'bruce fleisher', 'united states', '2411543', '31', '3'], ['3', 'hale irwin', 'united states', '2147422', '26', '3'], ['4', 'larry nelson', 'united states', '2109936', '28', '5'], ['5', 'gil morgan', 'united states', '1885871', '24', '2']] |
the yardbirds discography | https://en.wikipedia.org/wiki/The_Yardbirds_discography | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15258059-1.html.csv | aggregation | of their albums originated in the us , the yardbirds averaged a high chart ranking of 70 . | {'scope': 'subset', 'col': '5', 'type': 'average', 'result': '70', 'subset': {'col': '3', 'criterion': 'equal', 'value': 'us'}} | {'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'origin', 'us'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; origin ; us }', 'tointer': 'select the rows whose origin record fuzzily matches to us .'}, 'chart no'], 'result': '70', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; origin ; us } ; chart no }'}, '70'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; origin ; us } ; chart no } ; 70 } = true', 'tointer': 'select the rows whose origin record fuzzily matches to us . the average of the chart no record of these rows is 70 .'} | round_eq { avg { filter_eq { all_rows ; origin ; us } ; chart no } ; 70 } = true | select the rows whose origin record fuzzily matches to us . the average of the chart no record of these rows is 70 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'origin_5': 5, 'us_6': 6, 'chart no_7': 7, '70_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'origin_5': 'origin', 'us_6': 'us', 'chart no_7': 'chart no', '70_8': '70'} | {'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'origin_5': [0], 'us_6': [0], 'chart no_7': [1], '70_8': [2]} | ['date', 'title', 'origin', 'label & cat no', 'chart no'] | [['6 / 1965', 'for your love', 'us', 'epic ln 24167 / bn - 26167', '96'], ['11 / 1965', 'having a rave up with the yardbirds', 'us', 'epic ln 24177 / bn 26177', '53'], ['7 / 1966', 'yardbirds aka roger the engineer', 'uk', 'columbia sx 6063 / scx 6063', '20'], ['7 / 1966', 'over under sideways down', 'us', 'epic ln 24210 / bn 26210', '52'], ['8 / 1967', 'little games', 'us', 'epic ln 24313 / bn 26313', '80']] |
2008 - 09 san antonio spurs season | https://en.wikipedia.org/wiki/2008%E2%80%9309_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17288845-11.html.csv | unique | during this period of the 2008-09 san antonio spurs season , the san antonio spurs experienced their only win on april 20th . | {'scope': 'all', 'row': '2', 'col': '4', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; score ; w }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; score ; w } }', 'tointer': 'select the rows whose score record fuzzily matches to w . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'score', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose score record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; score ; w }'}, 'date'], 'result': 'april 20', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; score ; w } ; date }'}, 'april 20'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; score ; w } ; date } ; april 20 }', 'tointer': 'the date record of this unqiue row is april 20 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; score ; w } } ; eq { hop { filter_eq { all_rows ; score ; w } ; date } ; april 20 } } = true', 'tointer': 'select the rows whose score record fuzzily matches to w . there is only one such row in the table . the date record of this unqiue row is april 20 .'} | and { only { filter_eq { all_rows ; score ; w } } ; eq { hop { filter_eq { all_rows ; score ; w } ; date } ; april 20 } } = true | select the rows whose score record fuzzily matches to w . there is only one such row in the table . the date record of this unqiue row is april 20 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'score_7': 7, 'w_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'april 20_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'score_7': 'score', 'w_8': 'w', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'april 20_10': 'april 20'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'score_7': [0], 'w_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'april 20_10': [3]} | ['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'series'] | [['1', 'april 18', 'dallas', 'l 97 - 105 ( ot )', 'tim duncan ( 27 )', 'tim duncan ( 9 )', 'tony parker ( 8 )', 'at & t center 18797', '0 - 1'], ['2', 'april 20', 'dallas', 'w 105 - 84 ( ot )', 'tony parker ( 38 )', 'tim duncan ( 11 )', 'tony parker ( 8 )', 'at & t center 18797', '1 - 1'], ['3', 'april 23', 'dallas', 'l 67 - 88 ( ot )', 'tony parker ( 12 )', 'kurt thomas ( 10 )', 'tony parker ( 3 )', 'american airlines center 20491', '1 - 2'], ['4', 'april 25', 'dallas', 'l 90 - 99 ( ot )', 'tony parker ( 43 )', 'tim duncan ( 10 )', 'tim duncan ( 7 )', 'american airlines center 20829', '1 - 3'], ['5', 'april 28', 'dallas', 'l 93 - 106 ( ot )', 'tim duncan ( 31 )', 'tim duncan ( 12 )', 'tony parker ( 6 )', 'at & t center 20829', '1 - 4']] |
merlin ( series 2 ) | https://en.wikipedia.org/wiki/Merlin_%28series_2%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29063233-1.html.csv | unique | sweet dreams is the only merlin ( series 2 ) episode written by lucy watkins . | {'scope': 'all', 'row': '10', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'lucy watkins', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'lucy watkins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to lucy watkins .', 'tostr': 'filter_eq { all_rows ; written by ; lucy watkins }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; written by ; lucy watkins } }', 'tointer': 'select the rows whose written by record fuzzily matches to lucy watkins . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'lucy watkins'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to lucy watkins .', 'tostr': 'filter_eq { all_rows ; written by ; lucy watkins }'}, 'title'], 'result': 'sweet dreams', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; written by ; lucy watkins } ; title }'}, 'sweet dreams'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; written by ; lucy watkins } ; title } ; sweet dreams }', 'tointer': 'the title record of this unqiue row is sweet dreams .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; written by ; lucy watkins } } ; eq { hop { filter_eq { all_rows ; written by ; lucy watkins } ; title } ; sweet dreams } } = true', 'tointer': 'select the rows whose written by record fuzzily matches to lucy watkins . there is only one such row in the table . the title record of this unqiue row is sweet dreams .'} | and { only { filter_eq { all_rows ; written by ; lucy watkins } } ; eq { hop { filter_eq { all_rows ; written by ; lucy watkins } ; title } ; sweet dreams } } = true | select the rows whose written by record fuzzily matches to lucy watkins . there is only one such row in the table . the title record of this unqiue row is sweet dreams . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'written by_7': 7, 'lucy watkins_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'title_9': 9, 'sweet dreams_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'written by_7': 'written by', 'lucy watkins_8': 'lucy watkins', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'title_9': 'title', 'sweet dreams_10': 'sweet dreams'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'written by_7': [0], 'lucy watkins_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'title_9': [2], 'sweet dreams_10': [3]} | ['no overall', 'no for series', 'title', 'directed by', 'written by', 'original air date', 'uk viewers ( million )'] | [['14', '1', 'the curse of cornelius sigan', 'david moore', 'julian jones', '19 september 2009', '5.77'], ['15', '2', 'the once and future queen', 'jeremy webb', 'howard overman', '26 september 2009', '5.94'], ['16', '3', 'the nightmare begins', 'jeremy webb', 'ben vanstone', '3 october 2009', '6.09'], ['17', '4', 'lancelot and guinevere', 'david moore', 'howard overman', '10 october 2009', '5.69'], ['18', '5', 'beauty and the beast ( part 1 )', 'david moore', 'jake michie', '24 october 2009', '5.53'], ['19', '6', 'beauty and the beast ( part 2 )', 'metin huseyin', 'ben vanstone', '31 october 2009', '6.14'], ['20', '7', 'the witchfinder', 'jeremy webb', 'jake michie', '7 november 2009', '5.62'], ['21', '8', 'the sins of the father', 'metin huseyin', 'howard overman', '14 november 2009', '6.16'], ['22', '9', 'the lady of the lake', 'metin huseyin', 'julian jones', '21 november 2009', '6.30'], ['23', '10', 'sweet dreams', 'alice troughton', 'lucy watkins', '28 november 2009', '6.02'], ['24', '11', "the witch 's quickening", 'alice troughton', 'jake michie', '5 december 2009', '6.01'], ['25', '12', 'the fires of idirsholas', 'jeremy webb', 'julian jones', '12 december 2009', '6.01']] |
usage share of operating systems | https://en.wikipedia.org/wiki/Usage_share_of_operating_systems | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11381701-3.html.csv | ordinal | considering different sources in the list of usage share of operating systems , the second highest share indicated to windows operating system was given by international data corporation source . | {'row': '4', 'col': '9', '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', 'windows', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; windows ; 2 }'}, 'source'], 'result': 'international data corporation', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; windows ; 2 } ; source }'}, 'international data corporation'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; windows ; 2 } ; source } ; international data corporation } = true', 'tointer': 'select the row whose windows record of all rows is 2nd maximum . the source record of this row is international data corporation .'} | eq { hop { nth_argmax { all_rows ; windows ; 2 } ; source } ; international data corporation } = true | select the row whose windows record of all rows is 2nd maximum . the source record of this row is international data corporation . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'windows_5': 5, '2_6': 6, 'source_7': 7, 'international data corporation_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', 'windows_5': 'windows', '2_6': '2', 'source_7': 'source', 'international data corporation_8': 'international data corporation'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'windows_5': [0], '2_6': [0], 'source_7': [1], 'international data corporation_8': [2]} | ['source', 'date', 'method', 'ios', 'android', 'blackberry', 'symbian / series 40', 'bada', 'windows', 'other'] | [['comscore reports ( us only )', 'may - 13', 'subscribers , us', '39.20 %', '52.40 %', '4.80 %', '0.40 %', 'n / a', '3.00 %', 'n / a'], ['gartner', 'may - 13', 'units sold', '18.2 %', '74.4 %', '3.0 %', '0.6 %', '0.7 %', '2.9 %', '0.3 %'], ['gartner', 'aug - 13', 'units sold', '14.2 %', '79.0 %', '2.7 %', '0.3 %', '0.4 %', '3.3 %', '0.2 %'], ['international data corporation', 'may - 13', 'units shipped', '17.3 %', '75.0 %', '2.9 %', '0.6', 'n / a', '3.2 %', '0.0 %'], ['net market share', 'july - 13', 'browsing', '58.26 %', '25.28 %', '3.23 %', '2.23 %', '0.05 %', '1.15 %', '0.19 %'], ['statcounter global stats', 'july - 13', 'browsing', '24.80 %', '38.34 %', '3.66 %', '20.76 %', '4.64 %', '1.52', '2.66'], ['wikimedia', 'mar - 13', 'browsing', '66.53 %', '25.93 %', '2.02 %', '3.03 %', '0.42 %', '1.85 %', '0.7 %']] |
weltklang | https://en.wikipedia.org/wiki/Weltklang | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18948956-2.html.csv | count | of weltklang 's tracks , there were four that were put out on the release classic electro . | {'scope': 'all', 'criterion': 'equal', 'value': 'classic electro', 'result': '4', 'col': '1', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'release', 'classic electro'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose release record fuzzily matches to classic electro .', 'tostr': 'filter_eq { all_rows ; release ; classic electro }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; release ; classic electro } }', 'tointer': 'select the rows whose release record fuzzily matches to classic electro . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; release ; classic electro } } ; 4 } = true', 'tointer': 'select the rows whose release record fuzzily matches to classic electro . the number of such rows is 4 .'} | eq { count { filter_eq { all_rows ; release ; classic electro } } ; 4 } = true | select the rows whose release record fuzzily matches to classic electro . the number of such rows is 4 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'release_5': 5, 'classic electro_6': 6, '4_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'release_5': 'release', 'classic electro_6': 'classic electro', '4_7': '4'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'release_5': [0], 'classic electro_6': [0], '4_7': [2]} | ['release', 'track', 'format', 'label', 'year'] | [['liebesgrüsse aus ost - berlin', 'mono 45upm - romance adieu ( weltklang remix )', '12', 'exil - system', '2006'], ['a dark wave from the black sea', 'aeronautica - rocket bomb ( weltklang remix )', 'cd', 'exil - system', '2007'], ['the greater key', 'asmodeus x - typhoon ( weltklang remix )', 'cd', 'latex records', '2008'], ['classic electro', 'p1 / e - 49 second dance ( weltklang remix )', 'cd', 'electro emotions', '2008'], ['classic electro', 'mono 45upm - romance adieu ( weltklang remix )', 'cd', 'electro emotions', '2008'], ['classic electro', 'kinder aus asbest - hey engel ( weltklang remix )', 'cd', 'electro emotions', '2008'], ['classic electro', 'sonnenbrandt - entweder / oder ( weltklang remix )', 'cd', 'electro emotions', '2008']] |
teen age message | https://en.wikipedia.org/wiki/Teen_Age_Message | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1820752-1.html.csv | superlative | the delphinus was the first constellation used for sending a teen age message . | {'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'date sent'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date sent }'}, 'constellation'], 'result': 'delphinus', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date sent } ; constellation }'}, 'delphinus'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date sent } ; constellation } ; delphinus } = true', 'tointer': 'select the row whose date sent record of all rows is minimum . the constellation record of this row is delphinus .'} | eq { hop { argmin { all_rows ; date sent } ; constellation } ; delphinus } = true | select the row whose date sent record of all rows is minimum . the constellation record of this row is delphinus . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date sent_5': 5, 'constellation_6': 6, 'delphinus_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date sent_5': 'date sent', 'constellation_6': 'constellation', 'delphinus_7': 'delphinus'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date sent_5': [0], 'constellation_6': [1], 'delphinus_7': [2]} | ['hd designation', 'constellation', 'distance ( ly )', 'spectral type', 'signal power ( kw )', 'date sent', 'arrival date'] | [['hd197076', 'delphinus', '68.5', 'g5v', '126', 'august 29 , 2001', 'february 2070'], ['hd95128', 'ursa major', '45.9', 'g0v', '96', 'september 3 , 2001', 'july 2047'], ['hd50692', 'gemini', '56.3', 'g0v', '96', 'september 3 , 2001', 'december 2057'], ['hd126053', 'virgo', '57.4', 'g1v', '96', 'september 3 , 2001', 'january 2059'], ['hd76151', 'hydra', '55.7', 'g2v', '96', 'september 4 , 2001', 'may 2057'], ['hd193664', 'draco', '57.4', 'g3v', '96', 'september 4 , 2001', 'january 2059']] |
2002 - 03 san antonio spurs season | https://en.wikipedia.org/wiki/2002%E2%80%9303_San_Antonio_Spurs_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13667936-7.html.csv | ordinal | the win against the warriors was the 2nd game the spur 's played in 2002-2003 . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '4', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 2 }'}, 'home'], 'result': 'warriors', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 2 } ; home }'}, 'warriors'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 2 } ; home } ; warriors } = true', 'tointer': 'select the row whose date record of all rows is 2nd minimum . the home record of this row is warriors .'} | eq { hop { nth_argmin { all_rows ; date ; 2 } ; home } ; warriors } = true | select the row whose date record of all rows is 2nd minimum . the home record of this row is warriors . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '2_6': 6, 'home_7': 7, 'warriors_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '2_6': '2', 'home_7': 'home', 'warriors_8': 'warriors'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '2_6': [0], 'home_7': [1], 'warriors_8': [2]} | ['date', 'visitor', 'score', 'home', 'leading scorer', 'record'] | [['1 february 2003', 'spurs', '67 - 65', 'heat', 'tony parker ( 18 )', '31 - 16'], ['5 february 2003', 'spurs', '103 - 99', 'warriors', 'tim duncan ( 30 )', '32 - 16'], ['6 february 2003', 'spurs', '83 - 74', 'nuggets', 'tim duncan ( 25 )', '33 - 16'], ['11 february 2003', 'spurs', '116 - 111', 'blazers', 'tim duncan ( 36 )', '34 - 16'], ['14 february 2003', 'spurs', '103 - 95', 'lakers', 'tim duncan ( 28 )', '35 - 16'], ['16 february 2003', 'spurs', '104 - 101', 'kings', 'tim duncan ( 34 )', '36 - 16'], ['18 february 2003', 'nuggets', '76 - 101', 'spurs', 'bruce bowen ( 18 )', '37 - 16'], ['20 february 2003', 'spurs', '87 - 95', 'mavericks', 'malik rose ( 25 )', '37 - 17'], ['22 february 2003', 'pacers', '96 - 105', 'spurs', 'tim duncan ( 21 )', '38 - 17'], ['25 february 2003', 'heat', '69 - 84', 'spurs', 'tim duncan ( 17 )', '39 - 17']] |
1926 - 27 new york rangers season | https://en.wikipedia.org/wiki/1926%E2%80%9327_New_York_Rangers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15950317-6.html.csv | comparative | during march of the 1926-7 new york rangers season , they played the montreal maroons before they played the boston bruins . | {'row_1': '2', 'row_2': '9', 'col': '2', 'col_other': '3', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'montreal maroons'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to montreal maroons .', 'tostr': 'filter_eq { all_rows ; opponent ; montreal maroons }'}, 'march'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; montreal maroons } ; march }', 'tointer': 'select the rows whose opponent record fuzzily matches to montreal maroons . take the march record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'boston bruins'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to boston bruins .', 'tostr': 'filter_eq { all_rows ; opponent ; boston bruins }'}, 'march'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; boston bruins } ; march }', 'tointer': 'select the rows whose opponent record fuzzily matches to boston bruins . take the march record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; montreal maroons } ; march } ; hop { filter_eq { all_rows ; opponent ; boston bruins } ; march } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to montreal maroons . take the march record of this row . select the rows whose opponent record fuzzily matches to boston bruins . take the march record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; opponent ; montreal maroons } ; march } ; hop { filter_eq { all_rows ; opponent ; boston bruins } ; march } } = true | select the rows whose opponent record fuzzily matches to montreal maroons . take the march record of this row . select the rows whose opponent record fuzzily matches to boston bruins . take the march record of this row . the first record is less than the second record . | 5 | 5 | {'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'opponent_7': 7, 'montreal maroons_8': 8, 'march_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'boston bruins_12': 12, 'march_13': 13} | {'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'opponent_7': 'opponent', 'montreal maroons_8': 'montreal maroons', 'march_9': 'march', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'boston bruins_12': 'boston bruins', 'march_13': 'march'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'montreal maroons_8': [0], 'march_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'boston bruins_12': [1], 'march_13': [3]} | ['game', 'march', 'opponent', 'score', 'record'] | [['36', '1', 'chicago black hawks', '3 - 0', '20 - 12 - 4'], ['37', '5', 'montreal maroons', '0 - 0 ot', '20 - 12 - 5'], ['38', '13', 'detroit cougars', '2 - 2 ot', '20 - 12 - 6'], ['39', '15', 'pittsburgh pirates', '5 - 0', '21 - 12 - 6'], ['40', '17', 'detroit cougars', '2 - 0', '22 - 12 - 6'], ['41', '20', 'new york americans', '2 - 1', '23 - 12 - 6'], ['42', '22', 'pittsburgh pirates', '4 - 1', '24 - 12 - 6'], ['43', '25', 'chicago black hawks', '4 - 0', '25 - 12 - 6'], ['44', '26', 'boston bruins', '4 - 3 ot', '25 - 13 - 6']] |
2000 masters tournament | https://en.wikipedia.org/wiki/2000_Masters_Tournament | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514630-7.html.csv | superlative | in the 2000 masters tournament , the highest amount of money for a player not from the united states was vijay singh . | {'scope': 'subset', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2,3', 'subset': {'col': '3', 'criterion': 'not_equal', 'value': 'united states'}} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_not_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_not_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record does not match to united states .'}, 'money'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_not_eq { all_rows ; country ; united states } ; money }'}, 'player'], 'result': 'vijay singh', 'ind': 2, 'tostr': 'hop { argmax { filter_not_eq { all_rows ; country ; united states } ; money } ; player }'}, 'vijay singh'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_not_eq { all_rows ; country ; united states } ; money } ; player } ; vijay singh } = true', 'tointer': 'select the rows whose country record does not match to united states . select the row whose money record of these rows is maximum . the player record of this row is vijay singh .'} | eq { hop { argmax { filter_not_eq { all_rows ; country ; united states } ; money } ; player } ; vijay singh } = true | select the rows whose country record does not match to united states . select the row whose money record of these rows is maximum . the player record of this row is vijay singh . | 4 | 4 | {'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_not_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'money_8': 8, 'player_9': 9, 'vijay singh_10': 10} | {'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_not_eq_0': 'filter_str_not_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'money_8': 'money', 'player_9': 'player', 'vijay singh_10': 'vijay singh'} | {'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_not_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'money_8': [1], 'player_9': [2], 'vijay singh_10': [3]} | ['place', 'player', 'country', 'score', 'to par', 'money'] | [['1', 'vijay singh', 'fiji', '72 + 67 + 70 + 69 = 278', '- 10', '828000'], ['2', 'ernie els', 'south africa', '72 + 67 + 74 + 68 = 281', '- 7', '496800'], ['t3', 'david duval', 'united states', '73 + 65 + 74 + 70 = 282', '- 6', '266800'], ['t3', 'loren roberts', 'united states', '73 + 69 + 71 + 69 = 282', '- 6', '266800'], ['5', 'tiger woods', 'united states', '75 + 72 + 68 + 69 = 284', '- 4', '184000'], ['6', 'tom lehman', 'united states', '69 + 72 + 75 + 69 = 285', '- 3', '165600'], ['t7', 'carlos franco', 'paraguay', '79 + 68 + 70 + 69 = 286', '- 2', '143367'], ['t7', 'davis love iii', 'united states', '75 + 72 + 68 + 71 = 286', '- 2', '143367'], ['t7', 'phil mickelson', 'united states', '71 + 68 + 76 + 71 = 286', '- 2', '143367'], ['10', 'hal sutton', 'united states', '72 + 75 + 71 + 69 = 287', '- 1', '124200']] |
portuguese legislative election , 1991 | https://en.wikipedia.org/wiki/Portuguese_legislative_election%2C_1991 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1886589-1.html.csv | superlative | in the 1991 portuguese legislative election , the august 4th polling results revealed that this date had the highest socialist support than any other date in the election . | {'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', 'socialist'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; socialist }'}, 'date released'], 'result': 'august 4 , 1991', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; socialist } ; date released }'}, 'august 4 , 1991'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; socialist } ; date released } ; august 4 , 1991 } = true', 'tointer': 'select the row whose socialist record of all rows is maximum . the date released record of this row is august 4 , 1991 .'} | eq { hop { argmax { all_rows ; socialist } ; date released } ; august 4 , 1991 } = true | select the row whose socialist record of all rows is maximum . the date released record of this row is august 4 , 1991 . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'socialist_5': 5, 'date released_6': 6, 'august 4 , 1991_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'socialist_5': 'socialist', 'date released_6': 'date released', 'august 4 , 1991_7': 'august 4 , 1991'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'socialist_5': [0], 'date released_6': [1], 'august 4 , 1991_7': [2]} | ['date released', 'polling institute', 'social democratic', 'socialist', 'green - communist', 'democratic and social centre', 'lead'] | [['october 6 , 1991', 'election results', '50.6 % 135 seats', '29.1 % 72 seats', '8.8 % 17 seats', '4.4 % 5 seats', '21.5 %'], ['october 6 , 1991', 'exit poll - rtp1 universidade católica', '48.0 % - 51.9 %', '28.5 % - 31.5 %', '7.5 % - 10.0 %', '4.5 % - 5.5 %', '19.5 % - 20.4 %'], ['october 6 , 1991', 'exit poll - tsf / expresso euroexpansão', '45.8 % - 50.2 %', '29.8 % - 33.9 %', '6.8 % - 9.1 %', '3.7 % - 5.5 %', '16.0 % - 16.3 %'], ['october 6 , 1991', 'exit poll - antena1 euroteste', '47.0 % - 50.0 %', '31.0 % - 34.0 %', '7.5 % - 10.0 %', '4.0 % - 5.0 %', '16.0 %'], ['september 28 , 1991', 'euroteste', '47.3 %', '35.5 %', '8.5 %', '4.1 %', '11.8 %'], ['september 28 , 1991', 'euroteste', '46.0 %', '37.0 %', '9.7 %', '3.9 %', '9.0 %'], ['september 28 , 1991', 'euroexpansão', '44.0 %', '33.0 %', '9.0 %', '6.0 %', '11.0 %'], ['september 27 , 1991', 'marktest', '43.1 %', '32.8 %', '7.7 %', '4.6 %', '10.3 %'], ['september 27 , 1991', 'pluriteste', '41.2 %', '34.7 %', '8.4 %', '8.1 %', '6.5 %'], ['september 20 , 1991', 'euroteste', '45.6 %', '35.5 %', '10.0 %', '4.4 %', '10.1 %'], ['september 20 , 1991', 'marktest', '41.9 %', '31.9 %', '7.3 %', '4.4 %', '10.0 %'], ['september 16 , 1991', 'pluriteste', '39.2 %', '26.6 %', '6.2 %', '6.0 %', '12.6 %'], ['september 16 , 1991', 'euroteste', '45.1 %', '34.5 %', '10.2 %', '5.2 %', '10.6 %'], ['september 14 , 1991', 'norma', '45.0 %', '37.5 %', '11.2 %', '3.5 %', '7.5 %'], ['august 28 , 1991', 'euroexpansão / marktest', '35.3 %', '36.8 %', '8.7 %', '4.9 %', '1.5 %'], ['august 4 , 1991', 'euroteste / jn', '47.5 %', '37.8 %', '12.3 %', '8.2 %', '7.7 %']] |
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/2-12794433-2.html.csv | comparative | in 2008 , iceland had only a fifth of sweden 's total of the largest nordic companies . | {'row_1': '5', 'row_2': '1', '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', 'iceland'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to iceland .', 'tostr': 'filter_eq { all_rows ; country ; iceland }'}, '2008 - list'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; iceland } ; 2008 - list }', 'tointer': 'select the rows whose country record fuzzily matches to iceland . take the 2008 - list record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'sweden'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to sweden .', 'tostr': 'filter_eq { all_rows ; country ; sweden }'}, '2008 - list'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; sweden } ; 2008 - list }', 'tointer': 'select the rows whose country record fuzzily matches to sweden . take the 2008 - list record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; country ; iceland } ; 2008 - list } ; hop { filter_eq { all_rows ; country ; sweden } ; 2008 - list } } = true', 'tointer': 'select the rows whose country record fuzzily matches to iceland . take the 2008 - list record of this row . select the rows whose country record fuzzily matches to sweden . take the 2008 - list record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; country ; iceland } ; 2008 - list } ; hop { filter_eq { all_rows ; country ; sweden } ; 2008 - list } } = true | select the rows whose country record fuzzily matches to iceland . take the 2008 - list record of this row . select the rows whose country record fuzzily matches to sweden . take the 2008 - list 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, 'iceland_8': 8, '2008 - list_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'sweden_12': 12, '2008 - list_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', 'iceland_8': 'iceland', '2008 - list_9': '2008 - list', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'sweden_12': 'sweden', '2008 - list_13': '2008 - list'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'iceland_8': [0], '2008 - list_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'sweden_12': [1], '2008 - list_13': [3]} | ['country', '2008 - list', '2009 - list', '2010 - list', '2011 - list', '2012 - list'] | [['sweden', '20', '22', '27', '22', '25'], ['finland', '16', '13', '11', '12', '12'], ['norway', '14', '9', '10', '10', '9'], ['denmark', '9', '12', '13', '10', '10'], ['iceland', '4', '0', '0', '0', '0']] |
media in kelowna | https://en.wikipedia.org/wiki/Media_in_Kelowna | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18409326-1.html.csv | unique | am 1150 is the only am radio station in kelowna . | {'scope': 'all', 'row': '1', 'col': '1', 'col_other': '3', 'criterion': 'fuzzily_match', 'value': 'am', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'frequency', 'am'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose frequency record fuzzily matches to am .', 'tostr': 'filter_eq { all_rows ; frequency ; am }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; frequency ; am } }', 'tointer': 'select the rows whose frequency record fuzzily matches to am . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'frequency', 'am'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose frequency record fuzzily matches to am .', 'tostr': 'filter_eq { all_rows ; frequency ; am }'}, 'branding'], 'result': 'am 1150', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; frequency ; am } ; branding }'}, 'am 1150'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; frequency ; am } ; branding } ; am 1150 }', 'tointer': 'the branding record of this unqiue row is am 1150 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; frequency ; am } } ; eq { hop { filter_eq { all_rows ; frequency ; am } ; branding } ; am 1150 } } = true', 'tointer': 'select the rows whose frequency record fuzzily matches to am . there is only one such row in the table . the branding record of this unqiue row is am 1150 .'} | and { only { filter_eq { all_rows ; frequency ; am } } ; eq { hop { filter_eq { all_rows ; frequency ; am } ; branding } ; am 1150 } } = true | select the rows whose frequency record fuzzily matches to am . there is only one such row in the table . the branding record of this unqiue row is am 1150 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'frequency_7': 7, 'am_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'branding_9': 9, 'am 1150_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'frequency_7': 'frequency', 'am_8': 'am', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'branding_9': 'branding', 'am 1150_10': 'am 1150'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'frequency_7': [0], 'am_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'branding_9': [2], 'am 1150_10': [3]} | ['frequency', 'call sign', 'branding', 'format', 'owner'] | [['1150 am', 'ckfr', 'am 1150', 'news / talk', 'astral media'], ['00 88.9 fm', 'cbtk - fm', 'cbc radio one', 'public news / talk', 'canadian broadcasting corporation'], ['00 89.7 fm', 'cbu - fm - 3', 'cbc radio 2', 'public music', 'canadian broadcasting corporation'], ['00 90.5 fm', 'cbuf - fm - 2', 'première chaîne', 'public news / talk', 'canadian broadcasting corporation'], ['00 96.3 fm', 'ckko - fm', 'k96 .3', 'classic rock', 'sun country cablevision'], ['00 99.9 fm', 'chsu - fm', '99.9 sun fm', 'contemporary hits radio', 'bell media'], ['0 101.5 fm', 'cilk - fm', '101.5 ez rock', 'adult contemporary', 'bell media'], ['0 103.1 fm', 'ckqq - fm', 'q103', 'hot adult contemporary', 'jim pattison group'], ['0 103.9 fm', 'cjui - fm', '103.9 the juice', 'adult hits', 'vista broadcast group'], ['0 104.7 fm', 'cklz - fm', 'power 104', 'active rock', 'jim pattison group']] |
memphis grizzlies all - time roster | https://en.wikipedia.org/wiki/Memphis_Grizzlies_all-time_roster | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16494599-17.html.csv | superlative | of the players on the memphis grizzlies all - time roster , bryant reeves ' years for grizzlies started the earliest . | {'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', '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', 'years for grizzlies'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; years for grizzlies }'}, 'player'], 'result': 'bryant reeves', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; years for grizzlies } ; player }'}, 'bryant reeves'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; years for grizzlies } ; player } ; bryant reeves } = true', 'tointer': 'select the row whose years for grizzlies record of all rows is minimum . the player record of this row is bryant reeves .'} | eq { hop { argmin { all_rows ; years for grizzlies } ; player } ; bryant reeves } = true | select the row whose years for grizzlies record of all rows is minimum . the player record of this row is bryant reeves . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'years for grizzlies_5': 5, 'player_6': 6, 'bryant reeves_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'years for grizzlies_5': 'years for grizzlies', 'player_6': 'player', 'bryant reeves_7': 'bryant reeves'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'years for grizzlies_5': [0], 'player_6': [1], 'bryant reeves_7': [2]} | ['player', 'nationality', 'position', 'years for grizzlies', 'school / club team'] | [['zach randolph', 'united states', 'power forward', '2009 - present', 'michigan state'], ['willie reed', 'united states', 'forward - center', '2012 - present', 'st louis'], ['bryant reeves', 'united states', 'center', '1995 - 2001', 'oklahoma state'], ['rodrick rhodes', 'united states', 'guard - forward', '1998 - 1999', 'usc'], ['jeremy richardson', 'united states', 'shooting guard', '2007 - 2008', 'delta state'], ['anthony roberson', 'united states', 'shooting guard', '2005 - 2006', 'florida'], ['lawrence roberts', 'united states', 'power forward', '2005 - 2007', 'mississippi state'], ['chris robinson', 'united states', 'shooting guard', '1996 - 1998', 'western kentucky'], ['larry robinson', 'united states', 'guard - forward', '1997 - 1998', 'centenary'], ['roy rogers', 'united states', 'power forward', '1996 - 1997', 'alabama']] |
united states house of representatives elections , 1800 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1800 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668401-17.html.csv | majority | the majority of virginia incumbents in the 1800 united states house of representatives elections were with the democratic - republican party . | {'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democratic - republican', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic - republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic - republican .', 'tostr': 'most_eq { all_rows ; party ; democratic - republican } = true'} | most_eq { all_rows ; party ; democratic - republican } = true | for the party records of all rows , most of them fuzzily match to democratic - republican . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic - republican_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic - republican_4': 'democratic - republican'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic - republican_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'result', 'candidates'] | [['virginia 2', 'david holmes', 'democratic - republican', '1797', 're - elected', 'david holmes ( dr ) alexander sinclair ( f )'], ['virginia 4', 'abram trigg', 'democratic - republican', '1797', 're - elected', 'abram trigg ( dr )'], ['virginia 5', 'john j trigg', 'democratic - republican', '1797', 're - elected', 'john j trigg ( dr )'], ['virginia 6', 'matthew clay', 'democratic - republican', '1797', 're - elected', 'matthew clay ( dr )'], ['virginia 7', 'john randolph', 'democratic - republican', '1799', 're - elected', 'john randolph ( dr )'], ['virginia 8', 'samuel goode', 'federalist', '1799', 'democratic - republican gain', 'thomas claiborne ( dr )'], ['virginia 9', 'joseph eggleston', 'democratic - republican', '1798 ( special )', 'democratic - republican hold', 'william b giles ( dr )'], ['virginia 10', 'edwin gray', 'democratic - republican', '1799', 're - elected', 'edwin gray ( dr ) nicholas faulcon ( dr )'], ['virginia 12', 'thomas evans', 'federalist', '1797', 'retired federalist hold', 'john stratton ( f ) john page ( dr )'], ['virginia 13', 'littleton waller tazewell', 'democratic - republican', '1800 ( special )', 'retired democratic - republican hold', 'john clopton ( dr ) samuel tyler ( dr )'], ['virginia 14', 'samuel j cabell', 'democratic - republican', '1795', 're - elected', 'samuel j cabell ( dr )'], ['virginia 15', 'john dawson', 'democratic - republican', '1797', 're - elected', 'john dawson ( dr )'], ['virginia 18', 'john nicholas', 'democratic - republican', '1793', 'retired democratic - republican hold', 'philip r thompson ( dr ) john blackwell ( f )']] |
list of manchester united f.c. records and statistics | https://en.wikipedia.org/wiki/List_of_Manchester_United_F.C._records_and_statistics | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12783587-1.html.csv | comparative | gary neville has a higher total score than alex stepny . | {'row_1': '5', 'row_2': '6', 'col': '8', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'gary neville'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to gary neville .', 'tostr': 'filter_eq { all_rows ; name ; gary neville }'}, 'total'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; gary neville } ; total }', 'tointer': 'select the rows whose name record fuzzily matches to gary neville . take the total record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'alex stepney'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to alex stepney .', 'tostr': 'filter_eq { all_rows ; name ; alex stepney }'}, 'total'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; alex stepney } ; total }', 'tointer': 'select the rows whose name record fuzzily matches to alex stepney . take the total record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; name ; gary neville } ; total } ; hop { filter_eq { all_rows ; name ; alex stepney } ; total } } = true', 'tointer': 'select the rows whose name record fuzzily matches to gary neville . take the total record of this row . select the rows whose name record fuzzily matches to alex stepney . take the total record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; name ; gary neville } ; total } ; hop { filter_eq { all_rows ; name ; alex stepney } ; total } } = true | select the rows whose name record fuzzily matches to gary neville . take the total record of this row . select the rows whose name record fuzzily matches to alex stepney . take the total 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, 'gary neville_8': 8, 'total_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'alex stepney_12': 12, 'total_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', 'gary neville_8': 'gary neville', 'total_9': 'total', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'alex stepney_12': 'alex stepney', 'total_13': 'total'} | {'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'gary neville_8': [0], 'total_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'alex stepney_12': [1], 'total_13': [3]} | ['name', 'years', 'league', 'fa cup', 'league cup', 'europe', 'other', 'total'] | [['ryan giggs', '1991 - present', '664 ( 113 )', '0 74 ( 12 )', '0 40 0 ( 6 )', '152 ( 23 )', '0 19 0 ( 3 )', '949 ( 157 )'], ['bobby charlton', '1956 - 1973', '606 0 ( 2 )', '0 78 0 ( 0 )', '0 24 0 ( 0 )', '0 45 0 ( 0 )', '00 5 0 ( 0 )', '758 00 ( 2 )'], ['paul scholes', '1994 - 2011 2012 - 2013', '499 ( 95 )', '0 49 ( 17 )', '0 21 0 ( 7 )', '134 ( 21 )', '0 15 0 ( 1 )', '718 ( 141 )'], ['bill foulkes', '1952 - 1970', '566 0 ( 3 )', '0 61 0 ( 0 )', '00 3 0 ( 0 )', '0 52 0 ( 0 )', '00 6 0 ( 0 )', '688 00 ( 3 )'], ['gary neville', '1992 - 2011', '400 ( 21 )', '0 47 0 ( 3 )', '0 25 0 ( 2 )', '117 0 ( 8 )', '0 13 0 ( 2 )', '602 0 ( 36 )'], ['alex stepney', '1966 - 1978', '433 0 ( 0 )', '0 44 0 ( 0 )', '0 35 0 ( 0 )', '0 23 0 ( 0 )', '00 4 0 ( 0 )', '539 00 ( 0 )'], ['tony dunne', '1960 - 1973', '414 0 ( 0 )', '0 55 0 ( 1 )', '0 21 0 ( 0 )', '0 40 0 ( 0 )', '00 5 0 ( 0 )', '535 00 ( 1 )'], ['denis irwin', '1990 - 2002', '368 ( 12 )', '0 43 0 ( 1 )', '0 31 0 ( 3 )', '0 75 0 ( 2 )', '0 12 0 ( 0 )', '529 0 ( 18 )'], ['joe spence', '1919 - 1933', '481 0 ( 0 )', '0 29 0 ( 0 )', '00 0 0 ( 0 )', '00 0 0 ( 0 )', '00 0 0 ( 0 )', '510 00 ( 0 )'], ['arthur albiston', '1974 - 1988', '379 ( 15 )', '0 36 0 ( 0 )', '0 40 0 ( 2 )', '0 27 0 ( 1 )', '00 3 0 ( 0 )', '485 0 ( 18 )']] |
list of bored to death episodes | https://en.wikipedia.org/wiki/List_of_Bored_to_Death_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26136228-3.html.csv | comparative | for the show bored to death , episode 1 aired 7 days before episode 2 . | {'row_1': '1', 'row_2': '2', 'col': '6', 'col_other': '2', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '7 days', 'bigger': 'row2'}} | {'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'episode no', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose episode no record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; episode no ; 1 }'}, 'original air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; episode no ; 1 } ; original air date }', 'tointer': 'select the rows whose episode no record fuzzily matches to 1 . take the original air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'episode no', '2'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose episode no record fuzzily matches to 2 .', 'tostr': 'filter_eq { all_rows ; episode no ; 2 }'}, 'original air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; episode no ; 2 } ; original air date }', 'tointer': 'select the rows whose episode no record fuzzily matches to 2 . take the original air date record of this row .'}], 'result': '-7 days', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; episode no ; 1 } ; original air date } ; hop { filter_eq { all_rows ; episode no ; 2 } ; original air date } }'}, '-7 days'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; episode no ; 1 } ; original air date } ; hop { filter_eq { all_rows ; episode no ; 2 } ; original air date } } ; -7 days } = true', 'tointer': 'select the rows whose episode no record fuzzily matches to 1 . take the original air date record of this row . select the rows whose episode no record fuzzily matches to 2 . take the original air date record of this row . the second record is 7 days larger than the first record .'} | eq { diff { hop { filter_eq { all_rows ; episode no ; 1 } ; original air date } ; hop { filter_eq { all_rows ; episode no ; 2 } ; original air date } } ; -7 days } = true | select the rows whose episode no record fuzzily matches to 1 . take the original air date record of this row . select the rows whose episode no record fuzzily matches to 2 . take the original air date record of this row . the second record is 7 days larger than the first record . | 6 | 6 | {'str_eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'episode no_8': 8, '1_9': 9, 'original air date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'episode no_12': 12, '2_13': 13, 'original air date_14': 14, '-7 days_15': 15} | {'str_eq_5': 'str_eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'episode no_8': 'episode no', '1_9': '1', 'original air date_10': 'original air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'episode no_12': 'episode no', '2_13': '2', 'original air date_14': 'original air date', '-7 days_15': '-7 days'} | {'str_eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'episode no_8': [0], '1_9': [0], 'original air date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'episode no_12': [1], '2_13': [1], 'original air date_14': [3], '-7 days_15': [5]} | ['series no', 'episode no', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )'] | [['9', '1', 'escape from the dungeon !', 'alan taylor', 'jonathan ames', 'september 26 , 2010', '1.05'], ['10', '2', 'make it quick , fitzgerald !', 'alan taylor', 'jonathan ames', 'october 3 , 2010', '1.08'], ['11', '3', 'the gowanus canal has gonorrhea !', 'michael lehmann', 'martin gero & jonathan ames', 'october 10 , 2010', '0.86'], ['12', '4', "i 've been living like a demented god !", 'michael lehmann', 'donick cary & jonathan ames', 'october 17 , 2010', '0.82'], ['13', '5', 'forty - two down !', 'troy miller', 'tami sagher & jonathan ames', 'october 24 , 2010', '1.01'], ['14', '6', 'the case of the grievous clerical error !', 'tristram shapeero', 'sam sklaver & jonathan ames', 'october 31 , 2010', '0.69'], ['15', '7', 'escape from the castle !', 'adam bernstein', 'donick cary & jonathan ames', 'november 7 , 2010', '1.10']] |
list of tallest buildings in ottawa - gatineau | https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Ottawa%E2%80%93Gatineau | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1722347-2.html.csv | unique | the building located on 265 laurier avenue w is the only building below 20 floors to be amongst the tallest buildings in the city . | {'scope': 'all', 'row': '11', 'col': '4', 'col_other': '1', 'criterion': 'less_than', 'value': '20', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'floors', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose floors record is less than 20 .', 'tostr': 'filter_less { all_rows ; floors ; 20 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; floors ; 20 } }', 'tointer': 'select the rows whose floors record is less than 20 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'floors', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose floors record is less than 20 .', 'tostr': 'filter_less { all_rows ; floors ; 20 }'}, 'building'], 'result': '265 laurier avenue w', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; floors ; 20 } ; building }'}, '265 laurier avenue w'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; floors ; 20 } ; building } ; 265 laurier avenue w }', 'tointer': 'the building record of this unqiue row is 265 laurier avenue w .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; floors ; 20 } } ; eq { hop { filter_less { all_rows ; floors ; 20 } ; building } ; 265 laurier avenue w } } = true', 'tointer': 'select the rows whose floors record is less than 20 . there is only one such row in the table . the building record of this unqiue row is 265 laurier avenue w .'} | and { only { filter_less { all_rows ; floors ; 20 } } ; eq { hop { filter_less { all_rows ; floors ; 20 } ; building } ; 265 laurier avenue w } } = true | select the rows whose floors record is less than 20 . there is only one such row in the table . the building record of this unqiue row is 265 laurier avenue w . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'floors_7': 7, '20_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'building_9': 9, '265 laurier avenue w_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'floors_7': 'floors', '20_8': '20', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'building_9': 'building', '265 laurier avenue w_10': '265 laurier avenue w'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'floors_7': [0], '20_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'building_9': [2], '265 laurier avenue w_10': [3]} | ['building', 'location', 'height', 'floors', 'status'] | [['richcraft - dow honda site tower i', 'little italy', '-', '48', 'proposed'], ['richcraft - dow honda site tower ii', 'little italy', '-', '48', 'proposed'], ['claridge icon', 'little italy', '-', '45', 'approved'], ['lebreton mews tower a', 'bayview yards', '-', '32', 'approved'], ['claridge - 1040 somerset street', 'hintonburg', '-', '39', 'proposed'], ['lebreton mews tower b', 'bayview yards', '-', '29', 'approved'], ['soho italia', 'little italy', '-', '36', 'approved 30 stories / height increase proposed'], ['the rhombus', 'mechanicsville', '-', '32', 'approved'], ['150 elgin', 'downtown', '-', '23', 'under construction'], ['claridge plaza iii', 'sandy hill', '-', '28', 'under construction'], ['265 laurier avenue w', 'downtown', '-', '19', 'proposed'], ['claridge plaza iv', 'sandy hill', '-', '28', 'under construction'], ['tribeca i', 'centretown', '-', '27', 'under construction'], ['tribeca ii', 'centretown', '-', '27', 'under construction'], ['nepean tower', 'centretown', '-', '27', 'approved']] |
2007 - 08 uci america tour | https://en.wikipedia.org/wiki/2007%E2%80%9308_UCI_America_Tour | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15519312-1.html.csv | unique | tour de santa catarina is the only race that took place in brazil . | {'scope': 'all', 'row': '5', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'brazil', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'brazil'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to brazil .', 'tostr': 'filter_eq { all_rows ; location ; brazil }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; brazil } }', 'tointer': 'select the rows whose location record fuzzily matches to brazil . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'brazil'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to brazil .', 'tostr': 'filter_eq { all_rows ; location ; brazil }'}, 'race name'], 'result': 'tour de santa catarina', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; brazil } ; race name }'}, 'tour de santa catarina'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; brazil } ; race name } ; tour de santa catarina }', 'tointer': 'the race name record of this unqiue row is tour de santa catarina .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; brazil } } ; eq { hop { filter_eq { all_rows ; location ; brazil } ; race name } ; tour de santa catarina } } = true', 'tointer': 'select the rows whose location record fuzzily matches to brazil . there is only one such row in the table . the race name record of this unqiue row is tour de santa catarina .'} | and { only { filter_eq { all_rows ; location ; brazil } } ; eq { hop { filter_eq { all_rows ; location ; brazil } ; race name } ; tour de santa catarina } } = true | select the rows whose location record fuzzily matches to brazil . there is only one such row in the table . the race name record of this unqiue row is tour de santa catarina . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'brazil_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'race name_9': 9, 'tour de santa catarina_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', 'brazil_8': 'brazil', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'race name_9': 'race name', 'tour de santa catarina_10': 'tour de santa catarina'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'brazil_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'race name_9': [2], 'tour de santa catarina_10': [3]} | ['date', 'race name', 'location', 'uci rating', 'winner', 'team'] | [['7 - 14 october', 'clasico ciclistico banfoandes', 'venezuela', '2.2', 'sergio luis henao ( col )', 'colombia és pasión coldeportes'], ['7 - 14 october', 'vuelta chihuahua internacional', 'mexico', '2.2', 'francisco mancebo ( esp )', 'relax - gam'], ['20 october - 1 november', 'vuelta a guatemala', 'guatemala', '2.2', 'carlos lópez ( mex )', "canel 's - turbo - mayordomo"], ['6 - 11 november', 'doble copacabana gp fides', 'bolivia', '2.2', 'óscar soliz ( bol )', 'coordinadora ebsa'], ['15 - 25 november', 'tour de santa catarina', 'brazil', '2.2', 'alex diniz ( bra )', 'scott - marcondes cesar - são josé dos campos'], ['17 - 25 november', 'vuelta a ecuador', 'ecuador', '2.2', 'alex atapuma ( col )', 'indernariño'], ['14 - 28 december', 'vuelta ciclista a costa rica', 'costa rica', '2.2', 'henry raabe ( crc )', 'bcr - pizza hut']] |
vitamin k deficiency | https://en.wikipedia.org/wiki/Vitamin_K_deficiency | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-20592988-1.html.csv | unique | bernard - soulier syndrome is the only condition that has both decreased or unaffected outcomes for platelet count . | {'scope': 'all', 'row': '14', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'decreased or unaffected', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'platelet count', 'decreased or unaffected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose platelet count record fuzzily matches to decreased or unaffected .', 'tostr': 'filter_eq { all_rows ; platelet count ; decreased or unaffected }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; platelet count ; decreased or unaffected } }', 'tointer': 'select the rows whose platelet count record fuzzily matches to decreased or unaffected . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'platelet count', 'decreased or unaffected'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose platelet count record fuzzily matches to decreased or unaffected .', 'tostr': 'filter_eq { all_rows ; platelet count ; decreased or unaffected }'}, 'condition'], 'result': 'bernard - soulier syndrome', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; platelet count ; decreased or unaffected } ; condition }'}, 'bernard - soulier syndrome'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; platelet count ; decreased or unaffected } ; condition } ; bernard - soulier syndrome }', 'tointer': 'the condition record of this unqiue row is bernard - soulier syndrome .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; platelet count ; decreased or unaffected } } ; eq { hop { filter_eq { all_rows ; platelet count ; decreased or unaffected } ; condition } ; bernard - soulier syndrome } } = true', 'tointer': 'select the rows whose platelet count record fuzzily matches to decreased or unaffected . there is only one such row in the table . the condition record of this unqiue row is bernard - soulier syndrome .'} | and { only { filter_eq { all_rows ; platelet count ; decreased or unaffected } } ; eq { hop { filter_eq { all_rows ; platelet count ; decreased or unaffected } ; condition } ; bernard - soulier syndrome } } = true | select the rows whose platelet count record fuzzily matches to decreased or unaffected . there is only one such row in the table . the condition record of this unqiue row is bernard - soulier syndrome . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'platelet count_7': 7, 'decreased or unaffected_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'condition_9': 9, 'bernard - soulier syndrome_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'platelet count_7': 'platelet count', 'decreased or unaffected_8': 'decreased or unaffected', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'condition_9': 'condition', 'bernard - soulier syndrome_10': 'bernard - soulier syndrome'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'platelet count_7': [0], 'decreased or unaffected_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'condition_9': [2], 'bernard - soulier syndrome_10': [3]} | ['condition', 'prothrombin time', 'partial thromboplastin time', 'bleeding time', 'platelet count'] | [['vitamin k deficiency or warfarin', 'prolonged', 'normal or mildly prolonged', 'unaffected', 'unaffected'], ['disseminated intravascular coagulation', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['von willebrand disease', 'unaffected', 'prolonged or unaffected', 'prolonged', 'unaffected'], ['hemophilia', 'unaffected', 'prolonged', 'unaffected', 'unaffected'], ['aspirin', 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['thrombocytopenia', 'unaffected', 'unaffected', 'prolonged', 'decreased'], ['liver failure , early', 'prolonged', 'unaffected', 'unaffected', 'unaffected'], ['liver failure , end - stage', 'prolonged', 'prolonged', 'prolonged', 'decreased'], ['uremia', 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['congenital afibrinogenemia', 'prolonged', 'prolonged', 'prolonged', 'unaffected'], ['factor v deficiency', 'prolonged', 'prolonged', 'unaffected', 'unaffected'], ['factor x deficiency as seen in amyloid purpura', 'prolonged', 'prolonged', 'unaffected', 'unaffected'], ["glanzmann 's thrombasthenia", 'unaffected', 'unaffected', 'prolonged', 'unaffected'], ['bernard - soulier syndrome', 'unaffected', 'unaffected', 'prolonged', 'decreased or unaffected'], ['factor xii deficiency', 'unaffected', 'prolonged', 'unaffected', 'unaffected']] |
roberto traven | https://en.wikipedia.org/wiki/Roberto_Traven | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10819986-2.html.csv | majority | the majority of roberto traven 's fights resulted in a win for roberto traven . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'win', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'res', 'win'], 'result': True, 'ind': 0, 'tointer': 'for the res records of all rows , most of them fuzzily match to win .', 'tostr': 'most_eq { all_rows ; res ; win } = true'} | most_eq { all_rows ; res ; win } = true | for the res 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, 'res_3': 3, 'win_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'res_3': 'res', 'win_4': 'win'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'res_3': [0], 'win_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time', 'location'] | [['loss', '6 - 4 - 1', 'john salter', 'ko ( punches )', 'adrenaline mma 3', '1', '2:15', 'birmingham , alabama , united states'], ['draw', '6 - 3 - 1', 'yukiya naito', 'draw', 'warriors realm 3', '3', '5:00', 'brisbane , australia'], ['loss', '6 - 3', 'elvis sinosic', 'ko ( punch )', 'warriors realm 1', '2', '0:35', 'queensland , australia'], ['loss', '6 - 2', 'frank mir', 'submission ( armbar )', 'ufc 34', '1', '1:05', 'las vegas , nevada'], ['win', '6 - 1', 'mikhail borissov', 'decision ( unanimous )', 'rings : king of kings 2000 block a', '2', '5:00', 'tokyo , japan'], ['loss', '5 - 1', 'dave menne', 'decision ( unanimous )', 'rings : king of kings 2000 block a', '3', '5:00', 'tokyo , japan'], ['win', '5 - 0', 'gueorguiev tzvetkov', 'decision ( majority )', 'rings : millennium combine 2', '2', '5:00', 'tokyo , japan'], ['win', '4 - 0', 'maxim tarasov', 'submission ( rear naked choke )', 'absolute fighting championship 2', '1', '2:47', 'moscow , russia'], ['win', '3 - 0', 'leonid efremov', 'submission ( punches )', 'absolute fighting championship 2', '1', '2:54', 'moscow , russia'], ['win', '2 - 0', 'artyom vilgulevsky', 'submission ( rear naked choke )', 'absolute fighting championship 2', '1', '2:28', 'moscow , russia'], ['win', '1 - 0', 'dave berry', 'submission ( strikes )', 'ufc 11', '1', '1:23', 'augusta , georgia , united states']] |
1965 vfl season | https://en.wikipedia.org/wiki/1965_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10788451-13.html.csv | majority | the majority of venues drew a crowd size of over 10000 in the 1965 vfl season . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '10000', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'crowd', '10000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 10000 .', 'tostr': 'most_greater { all_rows ; crowd ; 10000 } = true'} | most_greater { all_rows ; crowd ; 10000 } = true | for the crowd records of all rows , most of them are greater than 10000 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '10000_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '10000_4': '10000'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '10000_4': [0]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['st kilda', '18.9 ( 117 )', 'south melbourne', '6.12 ( 48 )', 'moorabbin oval', '18709', '24 july 1965'], ['fitzroy', '7.13 ( 55 )', 'footscray', '6.6 ( 42 )', 'brunswick street oval', '7456', '24 july 1965'], ['north melbourne', '11.15 ( 81 )', 'melbourne', '9.6 ( 60 )', 'city of coburg oval', '8312', '24 july 1965'], ['hawthorn', '7.5 ( 47 )', 'essendon', '10.11 ( 71 )', 'glenferrie oval', '11400', '24 july 1965'], ['richmond', '8.8 ( 56 )', 'collingwood', '12.7 ( 79 )', 'mcg', '56360', '24 july 1965'], ['geelong', '5.9 ( 39 )', 'carlton', '9.12 ( 66 )', 'kardinia park', '19568', '24 july 1965']] |
list of criminal minds : suspect behavior episodes | https://en.wikipedia.org/wiki/List_of_Criminal_Minds%3A_Suspect_Behavior_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28358487-3.html.csv | unique | episode 1 , two of a kind , was the only episode that had more than 11 million us viewers . | {'scope': 'all', 'row': '1', 'col': '5', 'col_other': '1,2', 'criterion': 'greater_than', 'value': '11.0', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( million )', '11.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is greater than 11.0 .', 'tostr': 'filter_greater { all_rows ; us viewers ( million ) ; 11.0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } }', 'tointer': 'select the rows whose us viewers ( million ) record is greater than 11.0 . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( million )', '11.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is greater than 11.0 .', 'tostr': 'filter_greater { all_rows ; us viewers ( million ) ; 11.0 }'}, 'no'], 'result': '1', 'ind': 2, 'tostr': 'hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; no }'}, '1'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; no } ; 1 }', 'tointer': 'the no record of this unqiue row is 1 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'us viewers ( million )', '11.0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose us viewers ( million ) record is greater than 11.0 .', 'tostr': 'filter_greater { all_rows ; us viewers ( million ) ; 11.0 }'}, 'title'], 'result': 'two of a kind', 'ind': 4, 'tostr': 'hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; title }'}, 'two of a kind'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; title } ; two of a kind }', 'tointer': 'the title record of this unqiue row is two of a kind .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; no } ; 1 } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; title } ; two of a kind } }', 'tointer': 'the no record of this unqiue row is 1 . the title record of this unqiue row is two of a kind .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } } ; and { eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; no } ; 1 } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; title } ; two of a kind } } } = true', 'tointer': 'select the rows whose us viewers ( million ) record is greater than 11.0 . there is only one such row in the table . the no record of this unqiue row is 1 . the title record of this unqiue row is two of a kind .'} | and { only { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } } ; and { eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; no } ; 1 } ; eq { hop { filter_greater { all_rows ; us viewers ( million ) ; 11.0 } ; title } ; two of a kind } } } = true | select the rows whose us viewers ( million ) record is greater than 11.0 . there is only one such row in the table . the no record of this unqiue row is 1 . the title record of this unqiue row is two of a kind . | 10 | 8 | {'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_greater_0': 0, 'all_rows_9': 9, 'us viewers (million)_10': 10, '11.0_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, 'no_12': 12, '1_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'title_14': 14, 'two of a kind_15': 15} | {'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_greater_0': 'filter_greater', 'all_rows_9': 'all_rows', 'us viewers (million)_10': 'us viewers ( million )', '11.0_11': '11.0', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'no_12': 'no', '1_13': '1', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'title_14': 'title', 'two of a kind_15': 'two of a kind'} | {'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_greater_0': [1, 2, 4], 'all_rows_9': [0], 'us viewers (million)_10': [0], '11.0_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], 'no_12': [2], '1_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'title_14': [4], 'two of a kind_15': [5]} | ['no', 'title', 'directed by', 'written by', 'us viewers ( million )', 'original air date', 'production code'] | [['1', 'two of a kind', 'john terlesky', 'rob fresco', '13.06', 'february 16 , 2011', '107'], ['2', 'lonely hearts', 'michael watkins', 'shintaro shimosawa', '9.81', 'february 23 , 2011', '104'], ['3', 'see no evil', 'rob spera', 'barry schindel', '10.36', 'march 2 , 2011', '109'], ['4', 'one shot kill', 'terry mcdonough', 'rob fresco', '9.12', 'march 9 , 2011', '102'], ['5', 'here is the fire', 'andrew bernstein', 'chris mundy & ian goldberg', '10.33', 'march 16 , 2011', '101'], ['6', 'devotion', 'stephen cragg', 'shintaro shimosawa', '8.80', 'march 23 , 2011', '111'], ['7', 'jane', 'rob hardy', 'glen mazzara', '9.53', 'march 30 , 2011', '108'], ['8', 'nighthawk', 'dwight little', 'ian goldberg', '9.12', 'april 6 , 2011', '106'], ['9', 'smother', 'phil abraham', 'melissa blake & joy blake', '9.96', 'april 13 , 2011', '105'], ['10', 'the time is now', 'tim matheson', 'joy blake & melissa blake', '8.83', 'may 4 , 2011', '110'], ['11', 'strays', 'anna j foerster', 'chris mundy & glen mazzara', '9.31', 'may 11 , 2011', '103'], ['12', 'the girl in the blue mask', 'félix alcalá', 'mark richard', '8.46', 'may 18 , 2011', '112']] |
1980 cleveland browns season | https://en.wikipedia.org/wiki/1980_Cleveland_Browns_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10651215-2.html.csv | ordinal | in 1980 , the second highest attended browns game was against the denver broncos . | {'row': '5', 'col': '5', 'order': '2', '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', 'attendance', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 2 }'}, 'opponent'], 'result': 'denver broncos', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 2 } ; opponent }'}, 'denver broncos'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; opponent } ; denver broncos } = true', 'tointer': 'select the row whose attendance record of all rows is 2nd maximum . the opponent record of this row is denver broncos .'} | eq { hop { nth_argmax { all_rows ; attendance ; 2 } ; opponent } ; denver broncos } = true | select the row whose attendance record of all rows is 2nd maximum . the opponent record of this row is denver broncos . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '2_6': 6, 'opponent_7': 7, 'denver broncos_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '2_6': '2', 'opponent_7': 'opponent', 'denver broncos_8': 'denver broncos'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '2_6': [0], 'opponent_7': [1], 'denver broncos_8': [2]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 7 , 1980', 'new england patriots', 'l 34 - 17', '49222'], ['2', 'september 15 , 1980', 'houston oilers', 'l 16 - 7', '80243'], ['3', 'september 21 , 1980', 'kansas city chiefs', 'w 20 - 13', '63614'], ['4', 'september 28 , 1980', 'tampa bay buccaneers', 'w 34 - 27', '65540'], ['5', 'october 5 , 1980', 'denver broncos', 'l 19 - 16', '81065'], ['6', 'october 12 , 1980', 'seattle seahawks', 'w 27 - 3', '61366'], ['7', 'october 19 , 1980', 'green bay packers', 'w 26 - 21', '75548'], ['8', 'october 26 , 1980', 'pittsburgh steelers', 'w 27 - 26', '79095'], ['9', 'november 3 , 1980', 'chicago bears', 'w 27 - 21', '84225'], ['10', 'november 9 , 1980', 'baltimore colts', 'w 28 - 27', '45369'], ['11', 'november 16 , 1980', 'pittsburgh steelers', 'l 16 - 13', '54563'], ['12', 'november 23 , 1980', 'cincinnati bengals', 'w 31 - 7', '79253'], ['13', 'november 30 , 1980', 'houston oilers', 'w 17 - 14', '51514'], ['14', 'december 7 , 1980', 'new york jets', 'w 17 - 14', '78454'], ['15', 'december 14 , 1980', 'minnesota vikings', 'l 28 - 23', '42202'], ['16', 'december 21 , 1980', 'cincinnati bengals', 'w 27 - 24', '50058']] |
equestrian at the asian games | https://en.wikipedia.org/wiki/Equestrian_at_the_Asian_Games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14781412-8.html.csv | majority | the majority of these events took place before 2009 . | {'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '2009', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'year', '2009'], 'result': True, 'ind': 0, 'tointer': 'for the year records of all rows , most of them are less than 2009 .', 'tostr': 'most_less { all_rows ; year ; 2009 } = true'} | most_less { all_rows ; year ; 2009 } = true | for the year records of all rows , most of them are less than 2009 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'year_3': 3, '2009_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'year_3': 'year', '2009_4': '2009'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'year_3': [0], '2009_4': [0]} | ['year', 'location', 'gold', 'silver', 'bronze'] | [['1982', 'new delhi', 'nadia al - moutawaa', 'jamila al - moutawaa', 'bariaa salem al - sabbah'], ['1986', 'seoul', 'takashi tomura', 'shuichi toki', 'ryuzo okuno'], ['1994', 'hiroshima', 'konoshin kuwahara', 'ryuzo okuno', 'natya chantrasmi'], ['1998', 'bangkok', 'jin kanno', 'sohn bong - gak', 'quzier ambak fathil'], ['2002', 'busan', 'mikaela marã\xada jaworski', 'lee jin - kyung', 'tadayoshi hayashi'], ['2006', 'doha', 'ali yousuf al - rumaihi', 'jasmine chen - shao man', 'joo jung - hyun'], ['2010', 'guangzhou', 'ramzy al duhami', 'latifa al maktom', 'khaled al - eid']] |
list of people in playboy 2000 - 09 | https://en.wikipedia.org/wiki/List_of_people_in_Playboy_2000%E2%80%9309 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1566852-5.html.csv | unique | the 3-04 issue was the only april playboy issue to feature two alternate cover models . | {'scope': 'all', 'row': '3', 'col': '2', 'col_other': '1', 'criterion': 'fuzzily_match', 'value': 'two alternative covers', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cover model', 'two alternative covers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cover model record fuzzily matches to two alternative covers .', 'tostr': 'filter_eq { all_rows ; cover model ; two alternative covers }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; cover model ; two alternative covers } }', 'tointer': 'select the rows whose cover model record fuzzily matches to two alternative covers . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'cover model', 'two alternative covers'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose cover model record fuzzily matches to two alternative covers .', 'tostr': 'filter_eq { all_rows ; cover model ; two alternative covers }'}, 'date'], 'result': '3 - 04', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; cover model ; two alternative covers } ; date }'}, '3 - 04'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; cover model ; two alternative covers } ; date } ; 3 - 04 }', 'tointer': 'the date record of this unqiue row is 3 - 04 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; cover model ; two alternative covers } } ; eq { hop { filter_eq { all_rows ; cover model ; two alternative covers } ; date } ; 3 - 04 } } = true', 'tointer': 'select the rows whose cover model record fuzzily matches to two alternative covers . there is only one such row in the table . the date record of this unqiue row is 3 - 04 .'} | and { only { filter_eq { all_rows ; cover model ; two alternative covers } } ; eq { hop { filter_eq { all_rows ; cover model ; two alternative covers } ; date } ; 3 - 04 } } = true | select the rows whose cover model record fuzzily matches to two alternative covers . there is only one such row in the table . the date record of this unqiue row is 3 - 04 . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'cover model_7': 7, 'two alternative covers_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '3 - 04_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'cover model_7': 'cover model', 'two alternative covers_8': 'two alternative covers', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '3 - 04_10': '3 - 04'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'cover model_7': [0], 'two alternative covers_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '3 - 04_10': [3]} | ['date', 'cover model', 'centerfold model', 'interview subject', '20 questions'] | [['1 - 04', 'none', 'colleen shannon', 'jack nicholson', 'al franken'], ['2 - 04', 'jaime pressly', 'aliya wolf', 'kiefer sutherland', 'dave matthews'], ['3 - 04', 'rena mero , torrie wilson ( two alternative covers )', 'sandra hubby', 'jim carrey', 'william petersen'], ['4 - 04', 'rachel hunter', 'krista kelly', '50 cent', 'kevin smith'], ['5 - 04', 'pamela anderson', 'nicole whitehead', 'johnny depp', 'matthew perry'], ['6 - 04', 'charisma carpenter', 'hiromi oshima', 'derek jeter', 'jude law'], ['7 - 04', 'peta wilson', 'stephanie glasson', 'michael moore', 'christina applegate'], ['8 - 04', 'eva herzigova', 'pilar lastra', 'matt damon', 'spike lee'], ['9 - 04', 'amy acuff', 'scarlett keegan', 'sergey brin & larry page', 'terrel owens'], ['10 - 04', 'evelyn gery', 'kimberly holland', 'donald trump', 'jimmy fallon'], ['11 - 04', 'brooke burke', 'cara zavaleta', 'oliver stone', 'john carmack'], ['12 - 04', 'denise richards', 'tiffany fallon', 'bernie mac', 'dustin hoffman']] |
1931 vfl season | https://en.wikipedia.org/wiki/1931_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10789881-10.html.csv | count | there were 6 game venues used during the 1931 vfl season . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'} | eq { count { filter_all { all_rows ; venue } } ; 6 } = true | select the rows whose venue record is arbitrary . the number of such rows is 6 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '14.12 ( 96 )', 'north melbourne', '3.6 ( 24 )', 'glenferrie oval', '4000', '11 july 1931'], ['fitzroy', '8.10 ( 58 )', 'st kilda', '12.18 ( 90 )', 'brunswick street oval', '11000', '11 july 1931'], ['richmond', '8.18 ( 66 )', 'melbourne', '7.11 ( 53 )', 'punt road oval', '11000', '11 july 1931'], ['geelong', '7.10 ( 52 )', 'footscray', '3.5 ( 23 )', 'corio oval', '9000', '11 july 1931'], ['essendon', '12.9 ( 81 )', 'collingwood', '8.9 ( 57 )', 'windy hill', '10000', '11 july 1931'], ['south melbourne', '10.12 ( 72 )', 'carlton', '11.11 ( 77 )', 'lake oval', '16000', '11 july 1931']] |
yankee small college conference | https://en.wikipedia.org/wiki/Yankee_Small_College_Conference | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10720390-1.html.csv | superlative | university of new hampshire club sports has the largest enrollment of all institutions in the yankee small college conference . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '13', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'institution'], 'result': 'university of new hampshire club sports', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; institution }'}, 'university of new hampshire club sports'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; institution } ; university of new hampshire club sports } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the institution record of this row is university of new hampshire club sports .'} | eq { hop { argmax { all_rows ; enrollment } ; institution } ; university of new hampshire club sports } = true | select the row whose enrollment record of all rows is maximum . the institution record of this row is university of new hampshire club sports . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'institution_6': 6, 'university of new hampshire club sports_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'institution_6': 'institution', 'university of new hampshire club sports_7': 'university of new hampshire club sports'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'institution_6': [1], 'university of new hampshire club sports_7': [2]} | ['institution', 'location', 'founded', 'affiliation', 'enrollment', 'team nickname'] | [['central maine community college', 'auburn , maine', '1963', 'public junior college', '2720', 'mustangs'], ['college of st joseph', 'rutland , vermont', '1956', 'private', '500', 'saints'], ['eastern maine community college', 'bangor , maine', '1966', 'public junior college', '2099', 'golden eagles'], ['great bay community college', 'portsmouth , new hampshire', '1945', 'public junior college', '1850', 'herons'], ['hampshire college', 'amherst , massachusetts', '1965', 'private', '1463', 'frogs'], ['nashua community college', 'nashua , new hampshire', '1970', 'public junior college', '2147', 'jaguars'], ['new hampshire technical institute', 'concord , new hampshire', '1961', 'public junior college', '4127', 'capitals'], ['northern maine community college', 'presque isle , maine', '1961', 'public junior college', '1129', 'falcons'], ["paul smith 's college", 'paul smiths , new york', '1946', 'private', '1000', 'bobcats'], ['southern maine community college', 'south portland , maine', '1946', 'public junior college', '6261', 'seawolves'], ['university of maine at machias', 'machias , maine', '1909', 'public', '1200', 'clippers'], ['university of maine at augusta', 'augusta , maine', '1965', 'public', '5054', 'moose'], ['university of new hampshire club sports', 'durham , new hampshire', '1866', 'public', '15253', 'wildcats'], ['unity college', 'unity , maine', '1965', 'private', '564', 'rams'], ['vermont technical college', 'randolph , vermont', '1866', 'public', '1453', 'green knights']] |
list of game of the year awards | https://en.wikipedia.org/wiki/List_of_Game_of_the_Year_awards | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1851722-57.html.csv | count | for the game of the year awards , when the year was 2010 or later , two of the games had an action rpg genre . | {'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'action rpg', 'result': '2', 'col': '3', 'subset': {'col': '1', 'criterion': 'greater_than_eq', 'value': '2010'}} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'year', '2010'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; year ; 2010 }', 'tointer': 'select the rows whose year record is greater than or equal to 2010 .'}, 'genre', 'action rpg'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record is greater than or equal to 2010 . among these rows , select the rows whose genre record fuzzily matches to action rpg .', 'tostr': 'filter_eq { filter_greater_eq { all_rows ; year ; 2010 } ; genre ; action rpg }'}], 'result': '2', 'ind': 2, 'tostr': 'count { filter_eq { filter_greater_eq { all_rows ; year ; 2010 } ; genre ; action rpg } }', 'tointer': 'select the rows whose year record is greater than or equal to 2010 . among these rows , select the rows whose genre record fuzzily matches to action rpg . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_greater_eq { all_rows ; year ; 2010 } ; genre ; action rpg } } ; 2 } = true', 'tointer': 'select the rows whose year record is greater than or equal to 2010 . among these rows , select the rows whose genre record fuzzily matches to action rpg . the number of such rows is 2 .'} | eq { count { filter_eq { filter_greater_eq { all_rows ; year ; 2010 } ; genre ; action rpg } } ; 2 } = true | select the rows whose year record is greater than or equal to 2010 . among these rows , select the rows whose genre record fuzzily matches to action rpg . the number of such rows is 2 . | 4 | 4 | {'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_greater_eq_0': 0, 'all_rows_5': 5, 'year_6': 6, '2010_7': 7, 'genre_8': 8, 'action rpg_9': 9, '2_10': 10} | {'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_5': 'all_rows', 'year_6': 'year', '2010_7': '2010', 'genre_8': 'genre', 'action rpg_9': 'action rpg', '2_10': '2'} | {'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_greater_eq_0': [1], 'all_rows_5': [0], 'year_6': [0], '2010_7': [0], 'genre_8': [1], 'action rpg_9': [1], '2_10': [3]} | ['year', 'game', 'genre', 'platform ( s )', 'developer ( s )'] | [['2007', 'portal', 'puzzle , first - person shooter , science fiction', 'xbox 360 , playstation 3 , windows', 'valve corporation'], ['2008', 'braid', 'puzzle , platformer', 'xbox live arcade , playstation network', 'number none , inc'], ['2009', 'uncharted 2 : among thieves', 'action - adventure , third - person shooter', 'playstation 3', 'naughty dog'], ['2010', 'red dead redemption', 'open world , third - person shooter', 'xbox 360 , playstation 3', 'rockstar san diego'], ['2011', 'the elder scrolls v : skyrim', 'action rpg', 'xbox 360 , playstation 3 , windows', 'bethesda game studios'], ['2012', 'mass effect 3', 'action rpg , third - person shooter', 'xbox 360 , playstation 3 , windows', 'bioware']] |
1982 vfl season | https://en.wikipedia.org/wiki/1982_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10824095-16.html.csv | superlative | hawthorn had the highest scoring game of all the teams in the 1982 vfl season . | {'scope': 'all', 'col_superlative': '2', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'home team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; home team score }'}, 'home team'], 'result': 'hawthorn', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; home team score } ; home team }'}, 'hawthorn'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; home team score } ; home team } ; hawthorn } = true', 'tointer': 'select the row whose home team score record of all rows is maximum . the home team record of this row is hawthorn .'} | eq { hop { argmax { all_rows ; home team score } ; home team } ; hawthorn } = true | select the row whose home team score record of all rows is maximum . the home team record of this row is hawthorn . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'home team score_5': 5, 'home team_6': 6, 'hawthorn_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'home team score_5': 'home team score', 'home team_6': 'home team', 'hawthorn_7': 'hawthorn'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'home team score_5': [0], 'home team_6': [1], 'hawthorn_7': [2]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['hawthorn', '32.14 ( 206 )', 'north melbourne', '15.22 ( 112 )', 'princes park', '18760', '10 july 1982'], ['footscray', '25.7 ( 157 )', 'geelong', '17.13 ( 115 )', 'western oval', '14004', '10 july 1982'], ['carlton', '21.13 ( 139 )', 'st kilda', '9.9 ( 63 )', 'vfl park', '27829', '10 july 1982'], ['melbourne', '9.18 ( 72 )', 'richmond', '23.9 ( 147 )', 'mcg', '36161', '17 july 1982'], ['essendon', '12.10 ( 82 )', 'swans', '17.13 ( 115 )', 'windy hill', '22278', '17 july 1982'], ['fitzroy', '10.24 ( 84 )', 'collingwood', '9.10 ( 64 )', 'vfl park', '26105', '17 july 1982']] |
wru division four south east | https://en.wikipedia.org/wiki/WRU_Division_Four_South_East | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13940275-4.html.csv | ordinal | the pentyrch rfc had the highest number of points in the wru division four south east . | {'row': '2', 'col': '11', 'order': '1', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'points', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; points ; 1 }'}, 'club'], 'result': 'pentyrch rfc', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; points ; 1 } ; club }'}, 'pentyrch rfc'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; points ; 1 } ; club } ; pentyrch rfc } = true', 'tointer': 'select the row whose points record of all rows is 1st maximum . the club record of this row is pentyrch rfc .'} | eq { hop { nth_argmax { all_rows ; points ; 1 } ; club } ; pentyrch rfc } = true | select the row whose points record of all rows is 1st maximum . the club record of this row is pentyrch rfc . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, '1_6': 6, 'club_7': 7, 'pentyrch 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', 'points_5': 'points', '1_6': '1', 'club_7': 'club', 'pentyrch rfc_8': 'pentyrch rfc'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], '1_6': [0], 'club_7': [1], 'pentyrch rfc_8': [2]} | ['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'] | [['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['pentyrch rfc', '22', '0', '3', '542', '210', '78', '25', '11', '1', '88'], ['heol y cyw rfc', '22', '2', '3', '513', '219', '70', '24', '9', '3', '84'], ['porth harlequins rfc', '22', '1', '5', '443', '300', '64', '36', '9', '2', '77'], ['cardiff hsob rfc', '22', '0', '9', '554', '442', '73', '63', '8', '4', '64'], ['llantwit major rfc', '22', '0', '10', '465', '397', '58', '57', '8', '6', '62'], ['dowlais rfc', '22', '0', '9', '463', '334', '59', '45', '6', '2', '60'], ['abercwmboi rfc', '22', '0', '10', '398', '358', '50', '44', '5', '5', '54'], ['taffs well rfc', '22', '0', '12', '336', '533', '35', '74', '2', '3', '45'], ['ferndale rfc', '22', '2', '13', '397', '451', '53', '57', '3', '4', '39'], ['tonyrefail rfc', '22', '2', '15', '341', '564', '49', '72', '5', '5', '34'], ['senghenydd rfc', '22', '1', '19', '303', '542', '35', '75', '3', '6', '19'], ['cefn coed rfc', '22', '0', '20', '200', '605', '26', '78', '1', '1', '10']] |
alycia moulton | https://en.wikipedia.org/wiki/Alycia_Moulton | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15096003-2.html.csv | unique | for alycia moulton , when the surface is grass , the only tournament where she was the winner was in rhode island . | {'scope': 'subset', 'row': '4', 'col': '1', 'col_other': '3', 'criterion': 'equal', 'value': 'winner', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'grass'}} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; grass }', 'tointer': 'select the rows whose surface record fuzzily matches to grass .'}, 'outcome', 'winner'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose outcome record fuzzily matches to winner .', 'tostr': 'filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner } }', 'tointer': 'select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose outcome record fuzzily matches to winner . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'surface', 'grass'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; surface ; grass }', 'tointer': 'select the rows whose surface record fuzzily matches to grass .'}, 'outcome', 'winner'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose outcome record fuzzily matches to winner .', 'tostr': 'filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner }'}, 'tournament'], 'result': 'newport , rhode island , usa', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner } ; tournament }'}, 'newport , rhode island , usa'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner } ; tournament } ; newport , rhode island , usa }', 'tointer': 'the tournament record of this unqiue row is newport , rhode island , usa .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner } } ; eq { hop { filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner } ; tournament } ; newport , rhode island , usa } } = true', 'tointer': 'select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose outcome record fuzzily matches to winner . there is only one such row in the table . the tournament record of this unqiue row is newport , rhode island , usa .'} | and { only { filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner } } ; eq { hop { filter_eq { filter_eq { all_rows ; surface ; grass } ; outcome ; winner } ; tournament } ; newport , rhode island , usa } } = true | select the rows whose surface record fuzzily matches to grass . among these rows , select the rows whose outcome record fuzzily matches to winner . there is only one such row in the table . the tournament record of this unqiue row is newport , rhode island , usa . | 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, 'surface_8': 8, 'grass_9': 9, 'outcome_10': 10, 'winner_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'tournament_12': 12, 'newport , rhode island , usa_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', 'surface_8': 'surface', 'grass_9': 'grass', 'outcome_10': 'outcome', 'winner_11': 'winner', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'tournament_12': 'tournament', 'newport , rhode island , usa_13': 'newport , rhode island , usa'} | {'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'surface_8': [0], 'grass_9': [0], 'outcome_10': [1], 'winner_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'tournament_12': [3], 'newport , rhode island , usa_13': [4]} | ['outcome', 'date', 'tournament', 'surface', 'opponent', 'score'] | [['runner - up', 'november 6 , 1982', 'hong kong', 'clay', 'catrin jexell', '3 - 6 , 5 - 7'], ['winner', 'february 28 , 1983', 'ridgewood , usa', 'hard', 'catrin jexell', '6 - 4 , 6 - 2'], ['runner - up', 'june 13 , 1983', 'birmingham , england', 'grass', 'billie jean king', '0 - 6 , 5 - 7'], ['winner', 'july 19 , 1983', 'newport , rhode island , usa', 'grass', 'kimberly shaefer', '6 - 3 , 6 - 2'], ['runner - up', 'august 26 , 1984', 'canadian open , canada', 'hard', 'chris evert - lloyd', '2 - 6 , 6 - 7']] |
christian pescatori | https://en.wikipedia.org/wiki/Christian_Pescatori | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16514839-1.html.csv | comparative | team bms scuderia italia had more laps than the jb racing team . | {'row_1': '1', 'row_2': '2', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'bms scuderia italia'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to bms scuderia italia .', 'tostr': 'filter_eq { all_rows ; team ; bms scuderia italia }'}, 'laps'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; bms scuderia italia } ; laps }', 'tointer': 'select the rows whose team record fuzzily matches to bms scuderia italia . take the laps record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'jb racing'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to jb racing .', 'tostr': 'filter_eq { all_rows ; team ; jb racing }'}, 'laps'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; jb racing } ; laps }', 'tointer': 'select the rows whose team record fuzzily matches to jb racing . take the laps record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; bms scuderia italia } ; laps } ; hop { filter_eq { all_rows ; team ; jb racing } ; laps } } = true', 'tointer': 'select the rows whose team record fuzzily matches to bms scuderia italia . take the laps record of this row . select the rows whose team record fuzzily matches to jb racing . take the laps record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; team ; bms scuderia italia } ; laps } ; hop { filter_eq { all_rows ; team ; jb racing } ; laps } } = true | select the rows whose team record fuzzily matches to bms scuderia italia . take the laps record of this row . select the rows whose team record fuzzily matches to jb racing . take the laps record of this row . the first record is greater than the second record . | 5 | 5 | {'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'bms scuderia italia_8': 8, 'laps_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'jb racing_12': 12, 'laps_13': 13} | {'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'bms scuderia italia_8': 'bms scuderia italia', 'laps_9': 'laps', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'jb racing_12': 'jb racing', 'laps_13': 'laps'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'bms scuderia italia_8': [0], 'laps_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'jb racing_12': [1], 'laps_13': [3]} | ['year', 'team', 'co - drivers', 'class', 'laps', 'pos', 'class pos'] | [['1997', 'bms scuderia italia', 'pierluigi martini antônio hermann de azevedo', 'gt1', '317', '8th', '4th'], ['1999', 'jb racing', 'jérôme policand mauro baldi', 'lmp', '71', 'dnf', 'dnf'], ['2001', 'audi sport north america', 'laurent aïello rinaldo capello', 'lmp900', '320', '2nd', '2nd'], ['2002', 'audi sport north america', 'johnny herbert rinaldo capello', 'lmp900', '374', '2nd', '2nd'], ['2005', 'bms scuderia italia', 'fabrizio gollin miguel ramos', 'gt1', '67', 'dnf', 'dnf'], ['2006', 'bms scuderia italia', 'fabrizio gollin fabio babini', 'gt1', '3', 'dnf', 'dnf']] |
ray sefo | https://en.wikipedia.org/wiki/Ray_Sefo | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1533651-2.html.csv | majority | the majority of ray sefos fights had a method of tko . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'tko', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'method', 'tko'], 'result': True, 'ind': 0, 'tointer': 'for the method records of all rows , most of them fuzzily match to tko .', 'tostr': 'most_eq { all_rows ; method ; tko } = true'} | most_eq { all_rows ; method ; tko } = true | for the method records of all rows , most of them fuzzily match to tko . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'method_3': 3, 'tko_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'method_3': 'method', 'tko_4': 'tko'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'method_3': [0], 'tko_4': [0]} | ['date', 'result', 'opponent', 'location', 'method', 'round', 'record'] | [['2001 - 09 - 02', 'loss', 'chester hughes', 'elgin , illinois , usa', 'ko', '1', '5 - 1 - 0'], ['2001 - 06 - 03', 'win', 'joe lenhart', 'elgin , illinois , usa', 'tko', '1', '5 - 0 - 0'], ['2001 - 02 - 11', 'win', 'steve griffin', 'elgin , illinois , usa', 'tko', '1', '4 - 0 - 0'], ['1996 - 10 - 05', 'win', 'nicky faamata', 'auckland , new zealand', 'tko', '3', '3 - 0 - 0'], ['1995 - 03 - 16', 'win', 'paul baker', 'auckland , new zealand', 'decision', '4', '2 - 0 - 0'], ['1994 - 11 - 24', 'win', 'alex katu', 'auckland , new zealand', 'tko', '1', '1 - 0 - 0']] |
2005 philadelphia barrage season | https://en.wikipedia.org/wiki/2005_Philadelphia_Barrage_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12075099-1.html.csv | count | the philadelphia barrage played at their home field a total of six times . | {'scope': 'all', 'criterion': 'equal', 'value': 'home', 'result': '6', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'home / away', 'home'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose home / away record fuzzily matches to home .', 'tostr': 'filter_eq { all_rows ; home / away ; home }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; home / away ; home } }', 'tointer': 'select the rows whose home / away record fuzzily matches to home . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; home / away ; home } } ; 6 } = true', 'tointer': 'select the rows whose home / away record fuzzily matches to home . the number of such rows is 6 .'} | eq { count { filter_eq { all_rows ; home / away ; home } } ; 6 } = true | select the rows whose home / away record fuzzily matches to home . 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, 'home / away_5': 5, 'home_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', 'home / away_5': 'home / away', 'home_6': 'home', '6_7': '6'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'home / away_5': [0], 'home_6': [0], '6_7': [2]} | ['date', 'opponent', 'home / away', 'field', 'result'] | [['may 29', 'cannons', 'home', 'villanova stadium', 'l 12 - 13'], ['june 4', 'lizards', 'home', 'villanova stadium', 'l 14 - 19'], ['june 12', 'bayhawks', 'away', 'johnny unitas stadium', 'l 9 - 31'], ['june 18', 'pride', 'away', 'alumni stadium ( kean university )', 'w 11 - 10'], ['june 25', 'lizards', 'away', 'mitchel athletic complex', 'l 12 - 18'], ['june 30', 'cannons', 'away', 'nickerson field', 'w 15 - 14'], ['july 9', 'rattlers', 'away', 'bishop kearney field', 'w 26 - 15'], ['july 14', 'rattlers', 'home', 'villanova stadium', 'l 10 - 14'], ['july 23', 'cannons', 'away', 'nickerson field', 'l 10 - 11'], ['july 28', 'lizards', 'home', 'villanova stadium', 'w 16 - 14'], ['august 4', 'bayhawks', 'home', 'villanova stadium', 'l 9 - 19'], ['august 11', 'pride', 'home', 'villanova stadium', 'l 12 - 16']] |
new democratic party candidates , 2008 canadian federal election | https://en.wikipedia.org/wiki/New_Democratic_Party_candidates%2C_2008_Canadian_federal_election | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10953705-1.html.csv | aggregation | during the 2008 canadian federal election for new democratic party candidates the total combined number of votes was 65680 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '65680', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'votes'], 'result': '65680', 'ind': 0, 'tostr': 'sum { all_rows ; votes }'}, '65680'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; votes } ; 65680 } = true', 'tointer': 'the sum of the votes record of all rows is 65680 .'} | round_eq { sum { all_rows ; votes } ; 65680 } = true | the sum of the votes record of all rows is 65680 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'votes_4': 4, '65680_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'votes_4': 'votes', '65680_5': '65680'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'votes_4': [0], '65680_5': [1]} | ['riding', 'candidate', 'gender', 'residence', 'occupation', 'votes', 'rank'] | [['avalon', 'randy wayne dawe', 'm', "clark 's beach", 'truck driver', '5707', '3rd'], ['bonavista-gander-grand falls-windsor', 'jason holley', 'm', 'amherst cove', 'artist', '3577', '3rd'], ['humber-st barbe-baie verte', 'mark kennedy', 'm', 'corner brook', 'engineering technician', '4603', '2nd'], ['labrador', 'phyllis artiss', 'f', "st john 's", 'retired university professor', '1378', '2nd'], ["random-burin-st george 's", 'terry white', 'm', 'stephenville', 'carpenter', '5563', '2nd'], ["st john 's east", 'jack harris', 'm', "st john 's", 'lawyer', '30881', '1st'], ["st john 's south-mount pearl", 'ryan cleary', 'm', "st john 's", 'journalist', '13971', '2nd']] |
kyaz | https://en.wikipedia.org/wiki/KYAZ | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1755656-1.html.csv | count | kyaz broadcasts in 4:3 aspect ration on seven different channels . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': '4:3', 'result': '7', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'aspect', '4:3'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose aspect record fuzzily matches to 4:3 .', 'tostr': 'filter_eq { all_rows ; aspect ; 4:3 }'}], 'result': '7', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; aspect ; 4:3 } }', 'tointer': 'select the rows whose aspect record fuzzily matches to 4:3 . the number of such rows is 7 .'}, '7'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; aspect ; 4:3 } } ; 7 } = true', 'tointer': 'select the rows whose aspect record fuzzily matches to 4:3 . the number of such rows is 7 .'} | eq { count { filter_eq { all_rows ; aspect ; 4:3 } } ; 7 } = true | select the rows whose aspect record fuzzily matches to 4:3 . the number of such rows is 7 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'aspect_5': 5, '4:3_6': 6, '7_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'aspect_5': 'aspect', '4:3_6': '4:3', '7_7': '7'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'aspect_5': [0], '4:3_6': [0], '7_7': [2]} | ['channel', 'video', 'aspect', 'psip short name', 'programming'] | [['51.1', '480i', '4:3', 'kyaz - 1', 'azteca amãrica'], ['51.2', '480i', '4:3', 'kyaz - 2', 'vietface tv'], ['51.3', '480i', '4:3', 'kyaz - 3', 'saigon network television'], ['51.4', '480i', '4:3', 'kyaz - 4', 'new tang dynasty television'], ['51.5', '480i', '4:3', 'kyaz - 5', 'global tv'], ['51.6', '480i', '4:3', 'kyaz - 6', 'latv'], ['51.7', '480i', '4:3', 'kyaz - 7', 'vietmax']] |
1988 green bay packers season | https://en.wikipedia.org/wiki/1988_Green_Bay_Packers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14650373-1.html.csv | ordinal | the first player that the packers picked in the 1988 season was sterling sharpe . | {'row': '1', 'col': '1', 'order': '1', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'pick', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; pick ; 1 }'}, 'player'], 'result': 'sterling sharpe', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; pick ; 1 } ; player }'}, 'sterling sharpe'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; pick ; 1 } ; player } ; sterling sharpe } = true', 'tointer': 'select the row whose pick record of all rows is 1st minimum . the player record of this row is sterling sharpe .'} | eq { hop { nth_argmin { all_rows ; pick ; 1 } ; player } ; sterling sharpe } = true | select the row whose pick record of all rows is 1st minimum . the player record of this row is sterling sharpe . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'pick_5': 5, '1_6': 6, 'player_7': 7, 'sterling sharpe_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'pick_5': 'pick', '1_6': '1', 'player_7': 'player', 'sterling sharpe_8': 'sterling sharpe'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'pick_5': [0], '1_6': [0], 'player_7': [1], 'sterling sharpe_8': [2]} | ['pick', 'nfl team', 'player', 'position', 'college'] | [['7', 'green bay packers', 'sterling sharpe', 'wide receiver', 'south carolina'], ['34', 'green bay packers', 'shawn patterson', 'defensive end', 'arizona state'], ['61', 'green bay packers', 'keith woodside', 'running back', 'texas a & m'], ['88', 'green bay packers', 'rollin putzier', 'nose tackle', 'oregon'], ['89', 'green bay packers', 'chuck cecil', 'safety', 'arizona'], ['144', 'green bay packers', 'nate hill', 'defensive end', 'auburn'], ['173', 'green bay packers', 'gary richard', 'cornerback', 'pittsburgh'], ['200', 'green bay packers', 'patrick collins', 'running back', 'oklahoma']] |
1970 isle of man tt | https://en.wikipedia.org/wiki/1970_Isle_of_Man_TT | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10301911-1.html.csv | ordinal | the rider with the third highest speed was ray pickrell . | {'row': '3', 'col': '4', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'speed', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; speed ; 3 }'}, 'rider'], 'result': 'ray pickrell', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; speed ; 3 } ; rider }'}, 'ray pickrell'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; speed ; 3 } ; rider } ; ray pickrell } = true', 'tointer': 'select the row whose speed record of all rows is 3rd maximum . the rider record of this row is ray pickrell .'} | eq { hop { nth_argmax { all_rows ; speed ; 3 } ; rider } ; ray pickrell } = true | select the row whose speed record of all rows is 3rd maximum . the rider record of this row is ray pickrell . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'speed_5': 5, '3_6': 6, 'rider_7': 7, 'ray pickrell_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', 'speed_5': 'speed', '3_6': '3', 'rider_7': 'rider', 'ray pickrell_8': 'ray pickrell'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'speed_5': [0], '3_6': [0], 'rider_7': [1], 'ray pickrell_8': [2]} | ['rank', 'rider', 'team', 'speed', 'time'] | [['1', 'malcolm uphill', 'triumph', '97.71 mph', '1:55.51.4'], ['2', 'peter williams', 'norton', '97.69 mph', '1:55.52.6'], ['3', 'ray pickrell', 'norton', '95.86 mph', '1:58.05.2'], ['4', 'tom dickie', 'triumph', '94.14 mph', '2:00.15.0'], ['5', 'bob heath', 'bsa', '94.09 mph', '2:00.19.0'], ['6', 'hans - otto butenuth', 'bmw', '93.54 mph', '2:01.01.8'], ['7', 'steve spencer', 'norton', '93.18 mph', '2:01.29.2'], ['8', 'tommy robb', 'honda', '92.26 mph', '2:02.42.0'], ['9', 'john cooper', 'honda', '91.32 mph', '2:03.57.6'], ['10', 'pat mahoney', 'norton', '89.77 mph', '2:06.06.0']] |
tasmania cricket team first - class records | https://en.wikipedia.org/wiki/Tasmania_cricket_team_first-class_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14412861-10.html.csv | count | 5 players are listed in the tasmania cricket team first - class records . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '3', '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': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; player } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 5 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 5 .'} | eq { count { filter_all { all_rows ; player } } ; 5 } = true | select the rows whose player record is arbitrary . the number of such rows is 5 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'player_5': 5, '5_6': 6} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'player_5': 'player', '5_6': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'player_5': [0], '5_6': [2]} | ['rank', 'runs', 'player', 'opponent', 'venue', 'season'] | [['1', '274', 'jack badcock', 'victoria', 'ntca ground , launceston', '1933 - 34'], ['2', '265', 'dene hills', 'south australia', 'bellerive oval , hobart', '1997 - 98'], ['3', '245', 'jamie cox', 'new south wales', 'bellerive oval , hobart', '1999 - 2000'], ['4', '233', 'ricky ponting', 'queensland', 'albion', '2000 - 01'], ['5', '227', 'david boon', 'victoria', 'mcg , melbourne', '1983 - 84']] |
1947 in brazilian football | https://en.wikipedia.org/wiki/1947_in_Brazilian_football | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15318779-1.html.csv | superlative | palmeiras earned the most points of any brazilian football team in 1947 . | {'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'palmeiras', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'palmeiras'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; team } ; palmeiras } = true', 'tointer': 'select the row whose points record of all rows is maximum . the team record of this row is palmeiras .'} | eq { hop { argmax { all_rows ; points } ; team } ; palmeiras } = true | select the row whose points record of all rows is maximum . the team record of this row is palmeiras . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'palmeiras_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'palmeiras_7': 'palmeiras'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'palmeiras_7': [2]} | ['position', 'team', 'points', 'played', 'won', 'drawn', 'lost', 'for', 'against', 'difference'] | [['1', 'palmeiras', '36', '20', '17', '2', '1', '51', '16', '35'], ['2', 'corinthians', '32', '20', '14', '4', '2', '54', '19', '35'], ['3', 'portuguesa', '27', '20', '11', '5', '4', '43', '28', '15'], ['4', 'são paulo', '25', '20', '8', '9', '3', '48', '27', '21'], ['5', 'ypiranga - sp', '21', '20', '9', '3', '8', '36', '26', '10'], ['6', 'santos', '19', '20', '6', '7', '7', '33', '27', '6'], ['7', 'juventus', '16', '20', '5', '6', '9', '29', '45', '- 16'], ['8', 'portuguesa santista', '15', '20', '6', '3', '11', '27', '42', '- 15'], ['9', 'comercial - sp', '11', '20', '5', '1', '14', '25', '59', '- 34'], ['10', 'nacional - sp', '10', '20', '3', '4', '13', '25', '47', '- 22']] |
1962 minnesota vikings season | https://en.wikipedia.org/wiki/1962_Minnesota_Vikings_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10360730-2.html.csv | aggregation | in the 1962 viking 's season , there were a total of 95,901 people attending the last two games . | {'scope': 'subset', 'col': '6', 'type': 'sum', 'result': '95,901', 'subset': {'col': '1', 'criterion': 'greater_than_eq', 'value': '13'}} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'week', '13'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; week ; 13 }', 'tointer': 'select the rows whose week record is greater than or equal to 13 .'}, 'attendance'], 'result': '95,901', 'ind': 1, 'tostr': 'sum { filter_greater_eq { all_rows ; week ; 13 } ; attendance }'}, '95,901'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_greater_eq { all_rows ; week ; 13 } ; attendance } ; 95,901 } = true', 'tointer': 'select the rows whose week record is greater than or equal to 13 . the sum of the attendance record of these rows is 95,901 .'} | round_eq { sum { filter_greater_eq { all_rows ; week ; 13 } ; attendance } ; 95,901 } = true | select the rows whose week record is greater than or equal to 13 . the sum of the attendance record of these rows is 95,901 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'week_5': 5, '13_6': 6, 'attendance_7': 7, '95,901_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'week_5': 'week', '13_6': '13', 'attendance_7': 'attendance', '95,901_8': '95,901'} | {'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'week_5': [0], '13_6': [0], 'attendance_7': [1], '95,901_8': [2]} | ['week', 'date', 'opponent', 'result', 'venue', 'attendance', 'record'] | [['1', '1962 - 09 - 16', 'green bay packers', 'l 34 - 7', 'city stadium', '38669', '0 - 1'], ['2', '1962 - 09 - 23', 'baltimore colts', 'l 34 - 7', 'metropolitan stadium', '30787', '0 - 2'], ['3', '1962 - 09 - 30', 'san francisco 49ers', 'l 21 - 7', 'kezar stadium', '38407', '0 - 3'], ['4', '1962 - 10 - 07', 'chicago bears', 'l 13 - 0', 'metropolitan stadium', '33141', '0 - 4'], ['5', '1962 - 10 - 14', 'green bay packers', 'l 48 - 21', 'metropolitan stadium', '41475', '0 - 5'], ['6', '1962 - 10 - 21', 'los angeles rams', 'w 38 - 14', 'los angeles memorial coliseum', '33071', '1 - 5'], ['7', '1962 - 10 - 28', 'philadelphia eagles', 'w 31 - 21', 'metropolitan stadium', '30071', '2 - 5'], ['8', '1962 - 11 - 04', 'pittsburgh steelers', 'l 39 - 31', 'forbes field', '14462', '2 - 6'], ['9', '1962 - 11 - 11', 'chicago bears', 'l 31 - 30', 'wrigley field', '46984', '2 - 7'], ['10', '1962 - 11 - 18', 'detroit lions', 'l 17 - 6', 'metropolitan stadium', '31257', '2 - 8'], ['11', '1962 - 11 - 25', 'los angeles rams', 't 24 - 24', 'metropolitan stadium', '26728', '2 - 8 - 1'], ['12', '1962 - 12 - 02', 'san francisco 49ers', 'l 35 - 12', 'metropolitan stadium', '33076', '2 - 9 - 1'], ['13', '1962 - 12 - 09', 'detroit lions', 'l 37 - 23', 'tiger stadium', '42256', '2 - 10 - 1'], ['14', '1962 - 12 - 16', 'baltimore colts', 'l 42 - 17', 'memorial stadium', '53645', '2 - 11 - 1']] |
andre roberts ( mixed martial artist ) | https://en.wikipedia.org/wiki/Andre_Roberts_%28mixed_martial_artist%29 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17446451-2.html.csv | majority | the majority of fights ended in the first round for andre roberts . | {'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1', 'subset': None} | {'func': 'most_eq', 'args': ['all_rows', 'round', '1'], 'result': True, 'ind': 0, 'tointer': 'for the round records of all rows , most of them are equal to 1 .', 'tostr': 'most_eq { all_rows ; round ; 1 } = true'} | most_eq { all_rows ; round ; 1 } = true | for the round records of all rows , most of them are equal to 1 . | 1 | 1 | {'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'round_3': 3, '1_4': 4} | {'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'round_3': 'round', '1_4': '1'} | {'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'round_3': [0], '1_4': [0]} | ['res', 'record', 'opponent', 'method', 'event', 'round', 'time'] | [['loss', '14 - 2 - 1', 'dan christison', 'submission ( armbar )', 'wec 13 - heavyweight explosion', '1', '3:26'], ['draw', '14 - 1 - 1', 'ruben villareal', 'draw', 'sb 38 - superbrawl 38', '3', '5:00'], ['win', '14 - 1', 'gabe beauperthy', 'submission ( kimura )', 'ec 57 - extreme challenge 57', '1', '3:34'], ['win', '13 - 1', 'johnathan ivey', 'submission ( bad position )', 'sb 30 - collision course', '1', '1:38'], ['win', '12 - 1', 'ray seraille', 'submission ( neck crank )', 'sb 28 - superbrawl 28', '1', '2:49'], ['win', '11 - 1', 'joe campanella', 'tko', 'ec 27 - extreme challenge 27', '1', '2:07'], ['win', '10 - 1', 'ron waterman', 'ko', 'ufc 21', '1', '2:51'], ['loss', '9 - 1', 'gary goodridge', 'submission ( punches )', 'ufc 19', '1', '0:43'], ['win', '9 - 0', 'jamie schell', 'tko', 'icf 1 - iowa cage fighting 1', '1', '1:25'], ['win', '8 - 0', 'jamie schell', 'tko', 'mfc 1 - midwest fighting 1', '1', '1:35'], ['win', '7 - 0', 'dave kirshman', 'submission', 'mfc 1 - midwest fighting 1', '1', '0:10'], ['win', '6 - 0', 'phil breecher', 'n / a', 'ec 19 - extreme challenge 19', '1', '0:35'], ['win', '5 - 0', 'harry moskowitz', 'ko', 'ufc 17', '1', '3:15'], ['win', '4 - 0', 'jason brewer', 'submission ( strikes )', 'ec 15 - extreme challenge 15', '1', '0:39'], ['win', '3 - 0', 'sam adkins', 'submission', 'ec 11 - extreme challenge 11', '1', '4:02'], ['win', '2 - 0', 'jim axtell', 'submission', 'ec 4 - extreme challenge 4', '1', '5:41'], ['win', '1 - 0', 'trevor thrasher', 'submission', 'ec 2 - extreme challenge 2', '1', '3:59']] |
2010 - 11 danish 1st division | https://en.wikipedia.org/wiki/2010%E2%80%9311_Danish_1st_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27782699-3.html.csv | count | five of the managers left because it was the end of their contract . | {'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'end of contract', 'result': '5', 'col': '3', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'end of contract'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to end of contract .', 'tostr': 'filter_eq { all_rows ; manner of departure ; end of contract }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; manner of departure ; end of contract } }', 'tointer': 'select the rows whose manner of departure record fuzzily matches to end of contract . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; manner of departure ; end of contract } } ; 5 } = true', 'tointer': 'select the rows whose manner of departure record fuzzily matches to end of contract . the number of such rows is 5 .'} | eq { count { filter_eq { all_rows ; manner of departure ; end of contract } } ; 5 } = true | select the rows whose manner of departure record fuzzily matches to end of contract . 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, 'manner of departure_5': 5, 'end of contract_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', 'manner of departure_5': 'manner of departure', 'end of contract_6': 'end of contract', '5_7': '5'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'manner of departure_5': [0], 'end of contract_6': [0], '5_7': [2]} | ['team', 'outgoing manager', 'manner of departure', 'date of vacancy', 'replaced by', 'date of appointment', 'position in table'] | [['aarhus gf', 'erik rasmussen', 'sacked', '20 may 2010', 'peter sørensen', '1 july 2010', 'pre - season'], ['næstved bk', 'kim poulsen', 'mutual consent', '30 june 2010', 'brian flies', '1 july 2010', 'pre - season'], ['fc roskilde', 'martin jungsgaard', 'end of contract', '30 june 2010', 'carsten broe', '1 july 2010', 'pre - season'], ['hobro ik', 'søren kusk', 'end of contract', '30 june 2010', 'jan østergaard', '1 july 2010', 'pre - season'], ['ab', 'flemming christensen', 'end of contract', '30 june 2010', 'kasper kurland', '1 july 2010', 'pre - season'], ['fc fredericia', 'peter sørensen', 'signed by aarhus gf', '30 june 2010', 'thomas thomasberg', '1 july 2010', 'pre - season'], ['fc hjørring', 'thomas thomasberg', 'signed by fc fredericia', '30 june 2010', 'kim poulsen', '1 july 2010', 'pre - season'], ['hobro ik', 'jan østergaard', 'sacked', '2 november 2010', 'jens hammer sørensen', '2 november 2010', '11th'], ['viborg ff', 'lars søndergaard', 'sacked', '24 november 2010', 'steffen højer & søren frederiksen', '24 november 2010', '13th'], ['hobro ik', 'jens hammer sørensen', 'mutual consent', '26 november 2010', 'jakob michelsen', '8 january 2011', '11th'], ['hvidovre if', 'kenneth brylle larsen', 'end of contract', '31 december 2010', 'per nielsen', '1 january 2011', '14th'], ['kolding fc', 'jens letort', 'end of contract', '31 december 2010', 'kim fogh', '1 january 2011', '10th'], ['vejle bk', 'mats gren', 'sacked', '12 april 2011', 'viggo jensen', '14 april 2011', '3rd']] |
1999 - 2000 philadelphia flyers season | https://en.wikipedia.org/wiki/1999%E2%80%932000_Philadelphia_Flyers_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14173105-18.html.csv | ordinal | in the 1999-2000 philadelphia flyers season , the player who was selected 2nd is jeff feniak . | {'row': '2', 'col': '1', 'order': '2', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'round', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; round ; 2 }'}, 'player'], 'result': 'jeff feniak', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; round ; 2 } ; player }'}, 'jeff feniak'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; round ; 2 } ; player } ; jeff feniak } = true', 'tointer': 'select the row whose round record of all rows is 2nd minimum . the player record of this row is jeff feniak .'} | eq { hop { nth_argmin { all_rows ; round ; 2 } ; player } ; jeff feniak } = true | select the row whose round record of all rows is 2nd minimum . the player record of this row is jeff feniak . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'round_5': 5, '2_6': 6, 'player_7': 7, 'jeff feniak_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'round_5': 'round', '2_6': '2', 'player_7': 'player', 'jeff feniak_8': 'jeff feniak'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'round_5': [0], '2_6': [0], 'player_7': [1], 'jeff feniak_8': [2]} | ['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )'] | [['1', 'maxime ouellet', 'goaltender', 'canada', 'quebec remparts ( qmjhl )'], ['4', 'jeff feniak', 'defense', 'canada', 'calgary hitmen ( whl )'], ['6', 'konstantin rudenko', 'forward', 'russia', 'severstal cherepovets ( rus )'], ['7', 'pavel kasparik', 'center', 'czech republic', 'ihc pisek ( cze )'], ['7', 'vaclav pletka', 'left wing', 'czech republic', 'hc oceláři třinec ( cze )'], ['8', 'david nystrom', 'right wing', 'sweden', 'frölunda hc ( elitserien )']] |
2008 atlanta dream season | https://en.wikipedia.org/wiki/2008_Atlanta_Dream_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17103645-10.html.csv | majority | lennox scored the most points 5 times which was more than any other player . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'lennox', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'high points', 'lennox'], 'result': True, 'ind': 0, 'tointer': 'for the high points records of all rows , most of them fuzzily match to lennox .', 'tostr': 'most_eq { all_rows ; high points ; lennox } = true'} | most_eq { all_rows ; high points ; lennox } = true | for the high points records of all rows , most of them fuzzily match to lennox . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'high points_3': 3, 'lennox_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'high points_3': 'high points', 'lennox_4': 'lennox'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'high points_3': [0], 'lennox_4': [0]} | ['game', 'date', 'opponent', 'score', 'high points', 'high rebounds', 'high assists', 'location / attendance', 'record'] | [['16', 'july 1', 'phoenix', '79 - 97', 'lennox ( 18 )', 'lovelace , young ( 7 )', 'latta ( 5 )', 'philips arena 9795', '0 - 16'], ['17', 'july 3', 'houston', '65 - 72', 'lennox ( 15 )', 'feenstra ( 9 )', 'haynie , strother ( 3 )', 'philips arena 7430', '0 - 17'], ['18', 'july 5', 'chicago', '91 - 84', 'lacy , latta ( 18 )', 'young ( 8 )', 'haynie ( 11 )', 'philips arena 8468', '1 - 17'], ['19', 'july 9', 'minnesota', '73 - 67', 'lennox ( 24 )', 'bales ( 11 )', 'haynie ( 5 )', 'target center 5893', '2 - 17'], ['20', 'july 11', 'san antonio', '74 - 82', 'lennox ( 22 )', 'bales ( 9 )', 'lennox ( 4 )', 'at & t center 10943', '2 - 18'], ['21', 'july 13', 'chicago', '66 - 79', 'feenstra ( 21 )', 'feenstra ( 8 )', 'feenstra , haynie , lennox ( 2 )', 'uic pavilion 2907', '2 - 19'], ['22', 'july 16', 'indiana', '81 - 77', 'castro marques ( 24 )', 'bales ( 11 )', 'haynie ( 7 )', 'conseco fieldhouse 9303', '3 - 19'], ['23', 'july 18', 'sacramento', '73 - 77', 'haynie ( 12 )', 'feenstra ( 8 )', 'haynie ( 4 )', 'arco arena 7236', '3 - 20'], ['24', 'july 19', 'phoenix', '84 - 110', 'latta ( 18 )', 'terry ( 11 )', 'latta ( 3 )', 'us airways center 7913', '3 - 21'], ['25', 'july 22', 'sacramento', '66 - 79', 'terry , latta ( 15 )', 'terry ( 9 )', 'haynie ( 4 )', 'philips arena 10431', '3 - 22'], ['26', 'july 25', 'washington', '75 - 81', 'castro marques ( 23 )', 'bales ( 7 )', 'haynie ( 3 )', 'philips arena 8279', '3 - 23'], ['27', 'july 27', 'new york', '76 - 86', 'lennox ( 18 )', 'desouza ( 11 )', 'latta ( 5 )', 'philips arena 8759', '3 - 24']] |
46th united states congress | https://en.wikipedia.org/wiki/46th_United_States_Congress | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2417395-4.html.csv | superlative | william g thompson was the earliest successor to be seated in the 46th united states united states congress . | {'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 successor seated'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; date successor seated }'}, 'successor'], 'result': 'william g thompson ( r )', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; date successor seated } ; successor }'}, 'william g thompson ( r )'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; date successor seated } ; successor } ; william g thompson ( r ) } = true', 'tointer': 'select the row whose date successor seated record of all rows is minimum . the successor record of this row is william g thompson ( r ) .'} | eq { hop { argmin { all_rows ; date successor seated } ; successor } ; william g thompson ( r ) } = true | select the row whose date successor seated record of all rows is minimum . the successor record of this row is william g thompson ( r ) . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'date successor seated_5': 5, 'successor_6': 6, 'william g thompson (r)_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'date successor seated_5': 'date successor seated', 'successor_6': 'successor', 'william g thompson (r)_7': 'william g thompson ( r )'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'date successor seated_5': [0], 'successor_6': [1], 'william g thompson (r)_7': [2]} | ['district', 'vacator', 'reason for change', 'successor', 'date successor seated'] | [['iowa 5th', 'rush clark ( r )', 'died april 29 , 1879', 'william g thompson ( r )', 'october 14 , 1879'], ['ohio 19th', 'james a garfield ( r )', 'resigned 1880', 'ezra b taylor ( r )', 'december 13 , 1880'], ['missouri 7th', 'alfred m lay ( d )', 'died december 8 , 1879', 'john f philips ( d )', 'january 10 , 1880'], ['new york 32nd', 'ray v pierce ( r )', 'resigned september 18 , 1880', 'jonathan scoville ( d )', 'november 12 , 1880'], ['new hampshire 3rd', 'evarts w farr ( r )', 'died november 30 , 1880', 'ossian ray ( r )', 'january 8 , 1881'], ['florida 2nd', 'noble a hull ( d )', 'lost contested election january 22 , 1881', 'horatio bisbee , jr ( r )', 'january 22 , 1881'], ['north carolina 1st', 'joseph j martin ( r )', 'lost contested election january 29 , 1881', 'jesse j yeates ( d )', 'january 29 , 1881']] |
2008 - 09 scottish third division | https://en.wikipedia.org/wiki/2008%E2%80%9309_Scottish_Third_Division | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14003108-1.html.csv | count | in the 2008-9 scottish third division , two clubs had an average attendance of over 500 . | {'scope': 'all', 'criterion': 'greater_than', 'value': '500', 'result': '2', 'col': '6', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'average', '500'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose average record is greater than 500 .', 'tostr': 'filter_greater { all_rows ; average ; 500 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; average ; 500 } }', 'tointer': 'select the rows whose average record is greater than 500 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; average ; 500 } } ; 2 } = true', 'tointer': 'select the rows whose average record is greater than 500 . the number of such rows is 2 .'} | eq { count { filter_greater { all_rows ; average ; 500 } } ; 2 } = true | select the rows whose average record is greater than 500 . the number of such rows is 2 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'average_5': 5, '500_6': 6, '2_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'average_5': 'average', '500_6': '500', '2_7': '2'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'average_5': [0], '500_6': [0], '2_7': [2]} | ['team', 'stadium', 'capacity', 'highest', 'lowest', 'average'] | [['annan athletic', 'galabank stadium', '3500', '1343', '422', '734'], ['dumbarton', 'strathclyde homes stadium', '2025', '1398', '462', '716'], ['stenhousemuir', 'ochilview park', '2624', '805', '311', '496'], ['forfar athletic', 'station park', '5177', '621', '362', '460'], ['east stirlingshire', 'ochilview park', '2624', '812', '343', '450'], ['cowdenbeath', 'central park', '2000', '1181', '193', '415'], ['berwick rangers', 'shielfield park', '4131', '570', '288', '414'], ['elgin city', 'borough briggs', '3927', '537', '276', '392'], ['montrose', 'links park', '3292', '570', '294', '379']] |
2008 primera división de méxico apertura | https://en.wikipedia.org/wiki/2008_Primera_Divisi%C3%B3n_de_M%C3%A9xico_Apertura | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17329364-2.html.csv | unique | miguel brindisi was the only manager in the 2008 primera división de méxico apertura who chose to resign . | {'scope': 'all', 'row': '3', 'col': '3', 'col_other': '2', 'criterion': 'equal', 'value': 'resigned', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'resigned'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to resigned .', 'tostr': 'filter_eq { all_rows ; manner of departure ; resigned }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; manner of departure ; resigned } }', 'tointer': 'select the rows whose manner of departure record fuzzily matches to resigned . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'manner of departure', 'resigned'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose manner of departure record fuzzily matches to resigned .', 'tostr': 'filter_eq { all_rows ; manner of departure ; resigned }'}, 'outgoing manager'], 'result': 'miguel brindisi', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; manner of departure ; resigned } ; outgoing manager }'}, 'miguel brindisi'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; manner of departure ; resigned } ; outgoing manager } ; miguel brindisi }', 'tointer': 'the outgoing manager record of this unqiue row is miguel brindisi .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; manner of departure ; resigned } } ; eq { hop { filter_eq { all_rows ; manner of departure ; resigned } ; outgoing manager } ; miguel brindisi } } = true', 'tointer': 'select the rows whose manner of departure record fuzzily matches to resigned . there is only one such row in the table . the outgoing manager record of this unqiue row is miguel brindisi .'} | and { only { filter_eq { all_rows ; manner of departure ; resigned } } ; eq { hop { filter_eq { all_rows ; manner of departure ; resigned } ; outgoing manager } ; miguel brindisi } } = true | select the rows whose manner of departure record fuzzily matches to resigned . there is only one such row in the table . the outgoing manager record of this unqiue row is miguel brindisi . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'manner of departure_7': 7, 'resigned_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'outgoing manager_9': 9, 'miguel brindisi_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'manner of departure_7': 'manner of departure', 'resigned_8': 'resigned', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'outgoing manager_9': 'outgoing manager', 'miguel brindisi_10': 'miguel brindisi'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'manner of departure_7': [0], 'resigned_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'outgoing manager_9': [2], 'miguel brindisi_10': [3]} | ['team', 'outgoing manager', 'manner of departure', 'date of departure', 'incoming manager', 'date hired', 'position in table'] | [['ciudad juárez', 'sergio orduña', 'sacked', 'aug 18 , 2008', 'héctor eugui', 'aug 19 , 2008', '18th'], ['uag', 'josé trejo', 'sacked', 'sep 1 , 2008', 'miguel herrera', 'sep 2 , 2008', '8th'], ['atlas', 'miguel brindisi', 'resigned', 'sep 4 , 2008', 'darío franco', 'sep 5 , 2008', '17th'], ['puebla', 'josé sánchez', 'sacked', 'sep 17 , 2008', 'mario carrillo', 'sep 17 , 2008', '16th'], ['chiapas', 'sergio almaguer', 'sacked', 'oct 1 , 2008', 'francisco avilán', 'oct 1 , 2008', '18th'], ['necaxa', 'salvador reyes', 'sacked', 'oct 13 , 2008', 'octavio becerril', 'oct 14 , 2008', '18th']] |
the midlands , england | https://en.wikipedia.org/wiki/The_Midlands%2C_England | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-184077-2.html.csv | superlative | in the midlands , england the billesley commons holds the least amount of people . | {'scope': 'all', 'col_superlative': '5', 'row_superlative': '4', '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', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; capacity }'}, 'stadium'], 'result': 'billesley common', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; capacity } ; stadium }'}, 'billesley common'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; capacity } ; stadium } ; billesley common } = true', 'tointer': 'select the row whose capacity record of all rows is minimum . the stadium record of this row is billesley common .'} | eq { hop { argmin { all_rows ; capacity } ; stadium } ; billesley common } = true | select the row whose capacity record of all rows is minimum . the stadium record of this row is billesley common . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'stadium_6': 6, 'billesley common_7': 7} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'stadium_6': 'stadium', 'billesley common_7': 'billesley common'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'stadium_6': [1], 'billesley common_7': [2]} | ['club', 'league', 'city / town', 'stadium', 'capacity'] | [['leicester tigers', 'aviva premiership', 'leicester', 'welford road', '24000'], ['northampton saints', 'aviva premiership', 'northampton', "franklin 's gardens", '13600'], ['worcester warriors', 'aviva premiership', 'worcester', 'sixways stadium', '12068'], ['moseley', 'rfu championship', 'birmingham', 'billesley common', '3000'], ['nottingham', 'rfu championship', 'nottingham', 'meadow lane', '19588']] |
claus jensen | https://en.wikipedia.org/wiki/Claus_Jensen | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1054921-2.html.csv | ordinal | the second to last competition for claus jensen took place in istanbul , turkey . | {'row': '7', 'col': '1', 'order': '7', 'col_other': '2', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None} | {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'date', '7'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; date ; 7 }'}, 'venue'], 'result': 'istanbul , turkey', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; date ; 7 } ; venue }'}, 'istanbul , turkey'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; date ; 7 } ; venue } ; istanbul , turkey } = true', 'tointer': 'select the row whose date record of all rows is 7th minimum . the venue record of this row is istanbul , turkey .'} | eq { hop { nth_argmin { all_rows ; date ; 7 } ; venue } ; istanbul , turkey } = true | select the row whose date record of all rows is 7th minimum . the venue record of this row is istanbul , turkey . | 3 | 3 | {'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'date_5': 5, '7_6': 6, 'venue_7': 7, 'istanbul , turkey_8': 8} | {'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'date_5': 'date', '7_6': '7', 'venue_7': 'venue', 'istanbul , turkey_8': 'istanbul , turkey'} | {'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'date_5': [0], '7_6': [0], 'venue_7': [1], 'istanbul , turkey_8': [2]} | ['date', 'venue', 'score', 'result', 'competition'] | [['24 march 2001', 'valletta , malta', '4 - 0', '5 - 0', '2002 world cup qualification'], ['12 february 2003', 'cairo , egypt', '1 - 1', '4 - 1', 'friendly match'], ['12 february 2003', 'cairo , egypt', '3 - 1', '4 - 1', 'friendly match'], ['12 february 2003', 'cairo , egypt', '4 - 1', '4 - 1', 'friendly match'], ['11 june 2003', 'luxembourg , luxembourg', '1 - 0', '2 - 0', 'euro 2004 qualification'], ['18 august 2004', 'poznan , poland', '4 - 1', '5 - 1', 'friendly match'], ['3 september 2005', 'istanbul , turkey', '1 - 0', '2 - 2', '2006 world cup qualification'], ['7 september 2005', 'copenhagen , denmark', '1 - 0', '6 - 1', '2006 world cup qualification']] |
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/2-18823880-2.html.csv | majority | most of the socket in core i7 microprocessors are lga 1156 . | {'scope': 'all', 'col': '12', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'lga 1156', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'socket', 'lga 1156'], 'result': True, 'ind': 0, 'tointer': 'for the socket records of all rows , most of them fuzzily match to lga 1156 .', 'tostr': 'most_eq { all_rows ; socket ; lga 1156 } = true'} | most_eq { all_rows ; socket ; lga 1156 } = true | for the socket records of all rows , most of them fuzzily match to lga 1156 . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'socket_3': 3, 'lga 1156_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'socket_3': 'socket', 'lga 1156_4': 'lga 1156'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'socket_3': [0], 'lga 1156_4': [0]} | ['model number', 'sspec number', 'frequency', 'turbo', 'cores', 'l2 cache', 'l3 cache', 'i / o bus', 'mult', 'memory', 'voltage', 'socket', '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', 'standard power'], ['core i7 - 860', 'slbjj ( b1 )', '2.8 ghz', '1 / 1 / 4 / 5', '4', '4 256 kb', '8 mb', 'dmi', '21', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'september 2009', 'bv80605001908akbx80605i7860', '284'], ['core i7 - 870', 'slbjg ( b1 )', '2.93 ghz', '2 / 2 / 4 / 5', '4', '4 256 kb', '8 mb', 'dmi', '22', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'september 2009', 'bv80605001905aibx80605i7870', '562'], ['core i7 - 875k', 'slbs2 ( b1 )', '2.93 ghz', '2 / 2 / 4 / 5', '4', '4 256 kb', '8 mb', 'dmi', '22', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'may 2010', 'bv80605001905 ambx80605i7875k', '342'], ['core i7 - 880', 'slbps ( b1 )', '3.07 ghz', '2 / 2 / 4 / 5', '4', '4 256 kb', '8 mb', 'dmi', '23', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'may 2010', 'bv80605002505ag', '583'], ['low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power', 'low power'], ['core i7 - 860s', 'slblg ( b1 )', '2.53 ghz', '0 / 0 / 6 / 7', '4', '4 256 kb', '8 mb', 'dmi', '19', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'january 2010', 'bv80605003210adbx80605i7860s', '337'], ['core i7 - 870s', 'slbq7 ( b1 )', '2.67 ghz', '0 / 0 / 6 / 7', '4', '4 256 kb', '8 mb', 'dmi', '20', '2 ddr3 - 1333', '0.65 - 1.4 v', 'lga 1156', 'july 2010', 'bx80605i7870sbv80605004494ab', '351']] |
2004 arizona cardinals season | https://en.wikipedia.org/wiki/2004_Arizona_Cardinals_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18722259-2.html.csv | comparative | during the 2004 arizona cardinals season , the new york giants game was attended by more people than the new york jets game . | {'row_1': '9', 'row_2': '11', 'col': '5', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'new york giants'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants .', 'tostr': 'filter_eq { all_rows ; opponent ; new york giants }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; new york giants } ; attendance }', 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'new york jets'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to new york jets .', 'tostr': 'filter_eq { all_rows ; opponent ; new york jets }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; new york jets } ; attendance }', 'tointer': 'select the rows whose opponent record fuzzily matches to new york jets . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; opponent ; new york giants } ; attendance } ; hop { filter_eq { all_rows ; opponent ; new york jets } ; attendance } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to new york giants . take the attendance record of this row . select the rows whose opponent record fuzzily matches to new york jets . take the attendance record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; opponent ; new york giants } ; attendance } ; hop { filter_eq { all_rows ; opponent ; new york jets } ; attendance } } = true | select the rows whose opponent record fuzzily matches to new york giants . take the attendance record of this row . select the rows whose opponent record fuzzily matches to new york jets . take the attendance 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, 'opponent_7': 7, 'new york giants_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'new york jets_12': 12, 'attendance_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', 'opponent_7': 'opponent', 'new york giants_8': 'new york giants', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'new york jets_12': 'new york jets', 'attendance_13': 'attendance'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'new york giants_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'new york jets_12': [1], 'attendance_13': [3]} | ['week', 'date', 'opponent', 'result', 'attendance'] | [['1', 'september 12 , 2004', 'st louis rams', 'l 17 - 10', '65538'], ['2', 'september 19 , 2004', 'new england patriots', 'l 23 - 12', '51557'], ['3', 'september 26 , 2004', 'atlanta falcons', 'l 6 - 3', '70534'], ['4', 'october 3 , 2004', 'new orleans saints', 'w 34 - 10', '28109'], ['5', 'october 10 , 2004', 'san francisco 49ers', 'l 31 - 28 ot', '62836'], ['7', 'october 24 , 2004', 'seattle seahawks', 'w 25 - 17', '35695'], ['8', 'october 31 , 2004', 'buffalo bills', 'l 38 - 14', '65887'], ['9', 'november 7 , 2004', 'miami dolphins', 'w 24 - 23', '72612'], ['10', 'november 14 , 2004', 'new york giants', 'w 17 - 14', '42297'], ['11', 'november 21 , 2004', 'carolina panthers', 'l 35 - 10', '72796'], ['12', 'november 28 , 2004', 'new york jets', 'l 13 - 3', '35820'], ['13', 'december 5 , 2004', 'detroit lions', 'l 26 - 12', '62262'], ['14', 'december 12 , 2004', 'san francisco 49ers', 'l 31 - 28 ot', '35069'], ['15', 'december 19 , 2004', 'st louis rams', 'w 31 - 7', '40070'], ['16', 'december 26 , 2004', 'seattle seahawks', 'l 24 - 21', '65825'], ['17', 'january 2 , 2005', 'tampa bay buccaneers', 'w 12 - 7', '31650']] |
norway in the eurovision song contest 1999 | https://en.wikipedia.org/wiki/Norway_in_the_Eurovision_Song_Contest_1999 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11437346-1.html.csv | count | three songs in norway in the eurovision song contest 1999 received more than 20 points . | {'scope': 'all', 'criterion': 'greater_than', 'value': '20', 'result': '3', 'col': '4', 'subset': None} | {'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '20'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is greater than 20 .', 'tostr': 'filter_greater { all_rows ; points ; 20 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; points ; 20 } }', 'tointer': 'select the rows whose points record is greater than 20 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; points ; 20 } } ; 3 } = true', 'tointer': 'select the rows whose points record is greater than 20 . the number of such rows is 3 .'} | eq { count { filter_greater { all_rows ; points ; 20 } } ; 3 } = true | select the rows whose points record is greater than 20 . 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, 'points_5': 5, '20_6': 6, '3_7': 7} | {'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'points_5': 'points', '20_6': '20', '3_7': '3'} | {'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'points_5': [0], '20_6': [0], '3_7': [2]} | ['draw', 'artist', 'song', 'points', 'place'] | [['1', 'hãvard , dag arnold and ingvild gryting', "i 'll be your friend", '14', '6'], ['2', 'mette hartmann', 'the night before the morning after', '17', '5'], ['3', 'dag brandth', 'untold', '7', '8'], ['4', 'stephen ackles', 'lost again', '19', '4'], ['5', 'midnight sons', 'stay', '35', '2'], ['6', 'tor endresen', 'lover', '28', '3'], ['7', 'toril moe', 'you used to be mine', '14', '6'], ['8', 'stig van eijk', 'living my life without you', '62', '1']] |
bavarian cup | https://en.wikipedia.org/wiki/Bavarian_Cup | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14066180-3.html.csv | superlative | the earlist year the oberbayern cup of the bavarian cup cup was won by fc ingolstadt 04 is 2005 . | {'scope': 'subset', 'col_superlative': '1', 'row_superlative': '8', 'value_mentioned': 'yes', 'max_or_min': 'min', 'other_col': '2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'fc ingolstadt 04'}} | {'func': 'eq', 'args': [{'func': 'min', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'oberbayern', 'fc ingolstadt 04'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; oberbayern ; fc ingolstadt 04 }', 'tointer': 'select the rows whose oberbayern record fuzzily matches to fc ingolstadt 04 .'}, 'season'], 'result': '2005', 'ind': 1, 'tostr': 'min { filter_eq { all_rows ; oberbayern ; fc ingolstadt 04 } ; season }', 'tointer': 'select the rows whose oberbayern record fuzzily matches to fc ingolstadt 04 . the minimum season record of these rows is 2005 .'}, '2005'], 'result': True, 'ind': 2, 'tostr': 'eq { min { filter_eq { all_rows ; oberbayern ; fc ingolstadt 04 } ; season } ; 2005 } = true', 'tointer': 'select the rows whose oberbayern record fuzzily matches to fc ingolstadt 04 . the minimum season record of these rows is 2005 .'} | eq { min { filter_eq { all_rows ; oberbayern ; fc ingolstadt 04 } ; season } ; 2005 } = true | select the rows whose oberbayern record fuzzily matches to fc ingolstadt 04 . the minimum season record of these rows is 2005 . | 3 | 3 | {'eq_2': 2, 'result_3': 3, 'min_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'oberbayern_5': 5, 'fc ingolstadt 04_6': 6, 'season_7': 7, '2005_8': 8} | {'eq_2': 'eq', 'result_3': 'true', 'min_1': 'min', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'oberbayern_5': 'oberbayern', 'fc ingolstadt 04_6': 'fc ingolstadt 04', 'season_7': 'season', '2005_8': '2005'} | {'eq_2': [3], 'result_3': [], 'min_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'oberbayern_5': [0], 'fc ingolstadt 04_6': [0], 'season_7': [1], '2005_8': [2]} | ['season', 'oberbayern', 'niederbayern', 'schwaben', 'mittelfranken'] | [['1998', 'tsv 1860 münchen ii', 'sv schalding - heining', 'bc aichach', 'jahn forchheim'], ['1999', 'tsv 1860 rosenheim', 'spvgg landshut', 'fc augsburg', 'sg quelle fürth'], ['2000', 'fc ismaning', 'sv riedelhütte', 'tsv rain am lech', 'fsv erlangen - bruck'], ['2001', 'fc bayern munich ii', 'spvgg landshut', 'fc gundelfingen', '1 . fc nuremberg ii'], ['2002', 'fc bayern munich ii', 'spvgg landshut', 'fc augsburg', 'greuther fürth ii'], ['2003', 'tsv 1860 münchen ii', 'sv schalding - heining', 'tsv aindling', 'asv zirndorf'], ['2004', "spvgg u ' haching ii", 'spvgg landshut', 'fc augsburg', 'sc 04 schwabach'], ['2005', 'fc ingolstadt 04', '1 . fc bad kötzting', 'fc augsburg', 'sc 04 schwabach'], ['2006', 'fc ingolstadt 04', 'spvgg landshut', 'tsg thannhausen', '1 . fc nuremberg ii'], ['2007', 'fc ingolstadt 04', 'sv schalding - heining', 'tsv 1861 nördlingen', 'sv seligenporten'], ['2008', 'spvgg unterhaching', 'spvgg landshut', '1 . fc sonthofen', 'asv neumarkt'], ['2009', 'spvgg unterhaching', 'sv schalding - heining', 'tsv aindling', 'sc eltersdorf']] |
césar eduardo gonzález | https://en.wikipedia.org/wiki/C%C3%A9sar_Eduardo_Gonz%C3%A1lez | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12690988-1.html.csv | majority | the majority of césar eduardo gonzález 's soccer matches were in friendly competitions . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'friendly', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'competition', 'friendly'], 'result': True, 'ind': 0, 'tointer': 'for the competition records of all rows , most of them fuzzily match to friendly .', 'tostr': 'most_eq { all_rows ; competition ; friendly } = true'} | most_eq { all_rows ; competition ; friendly } = true | for the competition records of all rows , most of them fuzzily match to friendly . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]} | ['goal', 'date', 'score', 'result', 'competition'] | [['1', '24 march 2007', '3 - 1', '3 - 1', 'friendly'], ['2', '3 march 2010', '1 - 2', '1 - 2', 'friendly'], ['3', '9 july 2011', '1 - 0', '1 - 0', '2011 copa américa'], ['4', '22 may 2013', '1 - 1', '2 - 1', 'friendly'], ['5', '10 september 2013', '2 - 1', '3 - 2', '2014 world cup qualifier']] |
1962 vfl season | https://en.wikipedia.org/wiki/1962_VFL_season | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10776868-14.html.csv | aggregation | for the 1962 vfl season the total crowd was 124845 . | {'scope': 'all', 'col': '6', 'type': 'sum', 'result': '124845', 'subset': None} | {'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'crowd'], 'result': '124845', 'ind': 0, 'tostr': 'sum { all_rows ; crowd }'}, '124845'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; crowd } ; 124845 } = true', 'tointer': 'the sum of the crowd record of all rows is 124845 .'} | round_eq { sum { all_rows ; crowd } ; 124845 } = true | the sum of the crowd record of all rows is 124845 . | 2 | 2 | {'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '124845_5': 5} | {'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '124845_5': '124845'} | {'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '124845_5': [1]} | ['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date'] | [['footscray', '6.11 ( 47 )', 'melbourne', '9.14 ( 68 )', 'western oval', '28801', '28 july 1962'], ['collingwood', '11.10 ( 76 )', 'south melbourne', '10.12 ( 72 )', 'victoria park', '19115', '28 july 1962'], ['hawthorn', '11.17 ( 83 )', 'geelong', '16.13 ( 109 )', 'glenferrie oval', '18000', '28 july 1962'], ['st kilda', '13.16 ( 94 )', 'fitzroy', '8.6 ( 54 )', 'junction oval', '18450', '28 july 1962'], ['richmond', '11.17 ( 83 )', 'essendon', '12.12 ( 84 )', 'punt road oval', '24043', '28 july 1962'], ['north melbourne', '7.6 ( 48 )', 'carlton', '11.12 ( 78 )', 'arden street oval', '16436', '28 july 1962']] |
list of free multiplayer online games | https://en.wikipedia.org/wiki/List_of_free_multiplayer_online_games | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17493675-2.html.csv | comparative | ea games released their free multiplayer online game earlier than meathead studios . | {'row_1': '2', 'row_2': '6', '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', 'developer ( s )', 'ea games'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose developer ( s ) record fuzzily matches to ea games .', 'tostr': 'filter_eq { all_rows ; developer ( s ) ; ea games }'}, 'release date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; developer ( s ) ; ea games } ; release date }', 'tointer': 'select the rows whose developer ( s ) record fuzzily matches to ea games . take the release date record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'developer ( s )', 'masthead studios'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose developer ( s ) record fuzzily matches to masthead studios .', 'tostr': 'filter_eq { all_rows ; developer ( s ) ; masthead studios }'}, 'release date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; developer ( s ) ; masthead studios } ; release date }', 'tointer': 'select the rows whose developer ( s ) record fuzzily matches to masthead studios . take the release date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; developer ( s ) ; ea games } ; release date } ; hop { filter_eq { all_rows ; developer ( s ) ; masthead studios } ; release date } } = true', 'tointer': 'select the rows whose developer ( s ) record fuzzily matches to ea games . take the release date record of this row . select the rows whose developer ( s ) record fuzzily matches to masthead studios . take the release date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; developer ( s ) ; ea games } ; release date } ; hop { filter_eq { all_rows ; developer ( s ) ; masthead studios } ; release date } } = true | select the rows whose developer ( s ) record fuzzily matches to ea games . take the release date record of this row . select the rows whose developer ( s ) record fuzzily matches to masthead studios . take the release date 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, 'developer (s)_7': 7, 'ea games_8': 8, 'release date_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'developer (s)_11': 11, 'masthead studios_12': 12, 'release date_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', 'developer (s)_7': 'developer ( s )', 'ea games_8': 'ea games', 'release date_9': 'release date', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'developer (s)_11': 'developer ( s )', 'masthead studios_12': 'masthead studios', 'release date_13': 'release date'} | {'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'developer (s)_7': [0], 'ea games_8': [0], 'release date_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'developer (s)_11': [1], 'masthead studios_12': [1], 'release date_13': [3]} | ['developer ( s )', 'release date', 'required os', 'genre', 'type'] | [['robot entertainment , gas powered games', 'august 16 , 2011', 'windows', 'mmorts', '3d'], ['ea games', '2009', 'windows', 'first - person shooter', '3d'], ['stunlock studios', '2011', 'windows', 'moba', '3d'], ['thq', '2010 - 2011', 'windows', 'real - time strategy', '3d'], ['novel , inc', '2011', 'windows', 'mmorpg', '2d'], ['masthead studios', '2013', 'windows', 'third - person shooter', '3d'], ['riot games', '2008 - 2011', 'windows , os x', 'moba', '3d'], ['valve corporation', '2007', 'windows , os x , linux', 'first - person shooter', '3d']] |
ect mainline rail | https://en.wikipedia.org/wiki/ECT_Mainline_Rail | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15805928-1.html.csv | unique | the heart of wessex is the only rail that uses intercity swallow as a livery . | {'scope': 'all', 'row': '3', 'col': '4', 'col_other': '3', 'criterion': 'equal', 'value': 'intercity swallow', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'livery', 'intercity swallow'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose livery record fuzzily matches to intercity swallow .', 'tostr': 'filter_eq { all_rows ; livery ; intercity swallow }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; livery ; intercity swallow } }', 'tointer': 'select the rows whose livery record fuzzily matches to intercity swallow . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'livery', 'intercity swallow'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose livery record fuzzily matches to intercity swallow .', 'tostr': 'filter_eq { all_rows ; livery ; intercity swallow }'}, 'name'], 'result': 'the heart of wessex', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; livery ; intercity swallow } ; name }'}, 'the heart of wessex'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; livery ; intercity swallow } ; name } ; the heart of wessex }', 'tointer': 'the name record of this unqiue row is the heart of wessex .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; livery ; intercity swallow } } ; eq { hop { filter_eq { all_rows ; livery ; intercity swallow } ; name } ; the heart of wessex } } = true', 'tointer': 'select the rows whose livery record fuzzily matches to intercity swallow . there is only one such row in the table . the name record of this unqiue row is the heart of wessex .'} | and { only { filter_eq { all_rows ; livery ; intercity swallow } } ; eq { hop { filter_eq { all_rows ; livery ; intercity swallow } ; name } ; the heart of wessex } } = true | select the rows whose livery record fuzzily matches to intercity swallow . there is only one such row in the table . the name record of this unqiue row is the heart of wessex . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'livery_7': 7, 'intercity swallow_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'the heart of wessex_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'livery_7': 'livery', 'intercity swallow_8': 'intercity swallow', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'the heart of wessex_10': 'the heart of wessex'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'livery_7': [0], 'intercity swallow_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'the heart of wessex_10': [3]} | ['number', 'class', 'name', 'livery', 'notes'] | [['31128', '31', 'charybdis', 'fragonset black', 'now operated by nemesis rail'], ['31452', '31', 'minotaur', 'fragonset black', 'now operated by network rail'], ['31454', '31', 'the heart of wessex', 'intercity swallow', 'now operated by network rail'], ['31468', '31', 'hydra', 'fragonset black', 'now operated by network rail'], ['31601', '31', 'gauge o guild', 'wessex trains pink', 'now operated by network rail']] |
1901 michigan wolverines football team | https://en.wikipedia.org/wiki/1901_Michigan_Wolverines_football_team | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14342210-14.html.csv | count | 10 players are listed as members of the 1901 michigan wolverines football team . | {'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '10', 'col': '1', '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 } }', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 10 .'}, '10'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; player } } ; 10 } = true', 'tointer': 'select the rows whose player record is arbitrary . the number of such rows is 10 .'} | 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]} | ['player', 'touchdowns ( 5 points )', 'extra points 1 point', 'field goals ( 5 points )', 'total points'] | [['bruce shorts', '13', '53', '1', '123'], ['willie heston', '20', '0', '0', '100'], ['neil snow', '19', '0', '0', '95'], ['albert herrnstein', '12', '0', '0', '60'], ['everett sweeley', '7', '2', '1', '42'], ['hugh white', '6', '0', '0', '30'], ['walter shaw', '4', '7', '0', '27'], ['arthur redner', '5', '0', '0', '25'], ['curtis redden', '4', '0', '0', '20'], ['herb graver', '1', '3', '0', '8']] |
2003 u.s. bank cleveland grand prix | https://en.wikipedia.org/wiki/2003_U.S._Bank_Cleveland_Grand_Prix | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18943126-1.html.csv | unique | at the 2003 u.s. bank cleveland grand prix , , max papis was the only competitor from pk racing . | {'scope': 'all', 'row': '18', 'col': '2', 'col_other': '1', 'criterion': 'equal', 'value': 'pk racing', 'subset': None} | {'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'pk racing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to pk racing .', 'tostr': 'filter_eq { all_rows ; team ; pk racing }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; team ; pk racing } }', 'tointer': 'select the rows whose team record fuzzily matches to pk racing . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'pk racing'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to pk racing .', 'tostr': 'filter_eq { all_rows ; team ; pk racing }'}, 'name'], 'result': 'max papis', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; pk racing } ; name }'}, 'max papis'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; team ; pk racing } ; name } ; max papis }', 'tointer': 'the name record of this unqiue row is max papis .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; team ; pk racing } } ; eq { hop { filter_eq { all_rows ; team ; pk racing } ; name } ; max papis } } = true', 'tointer': 'select the rows whose team record fuzzily matches to pk racing . there is only one such row in the table . the name record of this unqiue row is max papis .'} | and { only { filter_eq { all_rows ; team ; pk racing } } ; eq { hop { filter_eq { all_rows ; team ; pk racing } ; name } ; max papis } } = true | select the rows whose team record fuzzily matches to pk racing . there is only one such row in the table . the name record of this unqiue row is max papis . | 6 | 5 | {'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'pk racing_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'max papis_10': 10} | {'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'pk racing_8': 'pk racing', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'max papis_10': 'max papis'} | {'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'team_7': [0], 'pk racing_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'max papis_10': [3]} | ['name', 'team', 'qual 1', 'qual 2', 'best'] | [['sébastien bourdais', 'newman / haas racing', '59.163', '58.014', '58.014'], ['paul tracy', "team player 's", '58.405', '1:01.294', '58.405'], ['patrick carpentier', "team player 's", '58.868', '58.449', '58.449'], ['oriol servià', 'patrick racing', '59.186', '58.502', '58.502'], ['bruno junqueira', 'newman / haas racing', '59.804', '58.506', '58.506'], ['michel jourdain , jr', 'team rahal', '59.223', '58.700', '58.700'], ['alex tagliani', 'rocketsports racing', '59.247', '58.718', '58.718'], ['mario domínguez', 'herdez competition', '59.535', '58.724', '58.724'], ['roberto moreno', 'herdez competition', '59.954', '58.845', '58.845'], ['jimmy vasser', 'american spirit team johansson', '59.382', '58.861', '58.861'], ['ryan hunter - reay', 'american spirit team johansson', '59.989', '59.073', '59.073'], ['mario haberfeld', 'mi - jack conquest racing', '1:00.333', '59.141', '59.141'], ['darren manning', 'walker racing', '59.776', '59.167', '59.167'], ['adrian fernández', 'fernández racing', '59.340', '59.306', '59.306'], ['rodolfo lavín', 'walker racing', '1:00.670', '59.531', '59.531'], ['tiago monteiro', 'fittipaldi - dingman racing', '1:00.003', '59.822', '59.822'], ['gualter salles', 'dale coyne racing', '1:01.778', '59.968', '59.968'], ['max papis', 'pk racing', '1:00.020', '1:00.080', '1:00.020'], ['geoff boss', 'dale coyne racing', '1:01.103', '1:01.525', '1:01.103']] |
united states house of representatives elections , 2006 | https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006 | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-15.html.csv | majority | the majority of the election results for the incumbents were re-elections . | {'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 're - elected', 'subset': None} | {'func': 'most_str_eq', 'args': ['all_rows', 'results', 're - elected'], 'result': True, 'ind': 0, 'tointer': 'for the results records of all rows , most of them fuzzily match to re - elected .', 'tostr': 'most_eq { all_rows ; results ; re - elected } = true'} | most_eq { all_rows ; results ; re - elected } = true | for the results records of all rows , most of them fuzzily match to re - elected . | 1 | 1 | {'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'results_3': 3, 're - elected_4': 4} | {'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'results_3': 'results', 're - elected_4': 're - elected'} | {'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'results_3': [0], 're - elected_4': [0]} | ['district', 'incumbent', 'party', 'first elected', 'results'] | [['indiana 1', 'pete visclosky', 'democratic', '1984', 're - elected'], ['indiana 2', 'chris chocola', 'republican', '2002', 'lost re - election democratic gain'], ['indiana 3', 'mark souder', 'republican', '1994', 're - elected'], ['indiana 4', 'steve buyer', 'republican', '1992', 're - elected'], ['indiana 5', 'dan burton', 'republican', '1982', 're - elected'], ['indiana 6', 'mike pence', 'republican', '2000', 're - elected'], ['indiana 7', 'julia carson', 'democratic', '1996', 're - elected'], ['indiana 8', 'john hostettler', 'republican', '1994', 'lost re - election democratic gain'], ['indiana 9', 'mike sodrel', 'republican', '2004', 'lost re - election democratic gain']] |
laika come home | https://en.wikipedia.org/wiki/Laika_Come_Home | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1059674-3.html.csv | comparative | laika come home was available to the united kingdom before it was available to the united states . | {'row_1': '1', 'row_2': '4', 'col': '2', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None} | {'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united kingdom'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose country record fuzzily matches to united kingdom .', 'tostr': 'filter_eq { all_rows ; country ; united kingdom }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; country ; united kingdom } ; date }', 'tointer': 'select the rows whose country record fuzzily matches to united kingdom . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose country record fuzzily matches to united states .', 'tostr': 'filter_eq { all_rows ; country ; united states }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; country ; united states } ; date }', 'tointer': 'select the rows whose country record fuzzily matches to united states . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; country ; united kingdom } ; date } ; hop { filter_eq { all_rows ; country ; united states } ; date } } = true', 'tointer': 'select the rows whose country record fuzzily matches to united kingdom . take the date record of this row . select the rows whose country record fuzzily matches to united states . take the date record of this row . the first record is less than the second record .'} | less { hop { filter_eq { all_rows ; country ; united kingdom } ; date } ; hop { filter_eq { all_rows ; country ; united states } ; date } } = true | select the rows whose country record fuzzily matches to united kingdom . take the date record of this row . select the rows whose country record fuzzily matches to united states . 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, 'country_7': 7, 'united kingdom_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'country_11': 11, 'united states_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', 'country_7': 'country', 'united kingdom_8': 'united kingdom', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'country_11': 'country', 'united states_12': 'united states', 'date_13': 'date'} | {'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'country_7': [0], 'united kingdom_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'country_11': [1], 'united states_12': [1], 'date_13': [3]} | ['country', 'date', 'label', 'format', 'catalogue'] | [['united kingdom', '1 july 2002', 'parlophone', 'cd', '540 3622'], ['united kingdom', '1 july 2002', 'parlophone', '2ã - lp', '539 9821'], ['japan', '3 july 2002', 'toshiba - emi', 'cd', 'tocp - 66045'], ['united states', '16 july 2002', 'astralwerks', 'cd', 'asw 40362'], ['united states', '16 july 2002', 'astralwerks', 'cd digipak', 'asw 40522']] |
kiwirail | https://en.wikipedia.org/wiki/KiwiRail | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18217231-2.html.csv | comparative | kiwirail has more dx class locomotives in service than dsc class . | {'row_1': '9', 'row_2': '6', 'col': '4', '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', 'class', 'dx'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class record fuzzily matches to dx .', 'tostr': 'filter_eq { all_rows ; class ; dx }'}, 'number in service'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; class ; dx } ; number in service }', 'tointer': 'select the rows whose class record fuzzily matches to dx . take the number in service record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'dsc'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose class record fuzzily matches to dsc .', 'tostr': 'filter_eq { all_rows ; class ; dsc }'}, 'number in service'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; class ; dsc } ; number in service }', 'tointer': 'select the rows whose class record fuzzily matches to dsc . take the number in service record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; class ; dx } ; number in service } ; hop { filter_eq { all_rows ; class ; dsc } ; number in service } } = true', 'tointer': 'select the rows whose class record fuzzily matches to dx . take the number in service record of this row . select the rows whose class record fuzzily matches to dsc . take the number in service record of this row . the first record is greater than the second record .'} | greater { hop { filter_eq { all_rows ; class ; dx } ; number in service } ; hop { filter_eq { all_rows ; class ; dsc } ; number in service } } = true | select the rows whose class record fuzzily matches to dx . take the number in service record of this row . select the rows whose class record fuzzily matches to dsc . take the number in service 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, 'class_7': 7, 'dx_8': 8, 'number in service_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'class_11': 11, 'dsc_12': 12, 'number in service_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', 'class_7': 'class', 'dx_8': 'dx', 'number in service_9': 'number in service', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'class_11': 'class', 'dsc_12': 'dsc', 'number in service_13': 'number in service'} | {'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'class_7': [0], 'dx_8': [0], 'number in service_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'class_11': [1], 'dsc_12': [1], 'number in service_13': [3]} | ['class', 'introduced', 'number in class', 'number in service', 'power output ( kw )'] | [['dbr', '1980', '10', '7', '709'], ['dc', '1978 - 1981', '85', '69', '1230'], ['dft', '1979 - 1981', '30', '29', '1800'], ['dh', '1979', '6', '6', '672'], ['dl', '2010 -', '48', '40', '2700'], ['dsc', '1959 - 1967', '70', '44', '315'], ['dsg', '1981', '24', '24', '700'], ['dsj', '1982', '5', '5', '350'], ['dx', '1972 - 1975', '49', '46', '2240'], ['dxr', '1993', '2', '2', '2420'], ['ef', '1988 - 1989', '22', '17', '3000'], ['tr', '1936 - 1978', '90', '21', '138']] |
list of essex list a cricket records | https://en.wikipedia.org/wiki/List_of_Essex_List_A_cricket_records | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11337751-4.html.csv | majority | most of the record wicket partnerships for essex scored over 100 runs . | {'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '100', 'subset': None} | {'func': 'most_greater', 'args': ['all_rows', 'runs', '100'], 'result': True, 'ind': 0, 'tointer': 'for the runs records of all rows , most of them are greater than 100 .', 'tostr': 'most_greater { all_rows ; runs ; 100 } = true'} | most_greater { all_rows ; runs ; 100 } = true | for the runs records of all rows , most of them are greater than 100 . | 1 | 1 | {'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'runs_3': 3, '100_4': 4} | {'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'runs_3': 'runs', '100_4': '100'} | {'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'runs_3': [0], '100_4': [0]} | ['wicket partnership', 'runs', 'batsmen', 'opponents', 'venue', 'season'] | [['1st', '269', 'mark pettini jason gallian', 'v surrey', 'the oval', '2008'], ['2nd', '273', 'graham gooch ken mcewan', 'v nottinghamshire', 'nottingham', '1983'], ['3rd', '268', 'graham gooch keith fletcher', 'v sussex', 'hove', '1982'], ['4th', '151', 'ronnie irani paul grayson', 'v northamptonshire', 'northampton', '1999'], ['5th', '190', 'ravi bopara james foster', 'v leicestershire', 'leicester', '2008'], ['6th', '127', 'stuart law robert rollins', 'v hampshire', 'southampton', '1996'], ['7th', '92', 'brian edmeades stuart turner', 'v nottinghamshire', 'chelmsford', '1969'], ['8th', '109', 'ray east neil smith', 'v northamptonshire', 'chelmsford', '1977'], ['9th', '67', 'unknown ray east', 'v gloucestershire', 'chelmsford', '1973'], ['10th', '81', 'stuart turner ray east', 'v yorkshire', 'leeds', '1982']] |
list of criminal minds : suspect behavior episodes | https://en.wikipedia.org/wiki/List_of_Criminal_Minds%3A_Suspect_Behavior_episodes | https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28358487-3.html.csv | majority | most of the episodes of criminal minds : suspect behavior had a production code of less than 110 . | {'scope': 'all', 'col': '7', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '110', 'subset': None} | {'func': 'most_less', 'args': ['all_rows', 'production code', '110'], 'result': True, 'ind': 0, 'tointer': 'for the production code records of all rows , most of them are less than 110 .', 'tostr': 'most_less { all_rows ; production code ; 110 } = true'} | most_less { all_rows ; production code ; 110 } = true | for the production code records of all rows , most of them are less than 110 . | 1 | 1 | {'most_less_0': 0, 'result_1': 1, 'all_rows_2': 2, 'production code_3': 3, '110_4': 4} | {'most_less_0': 'most_less', 'result_1': 'true', 'all_rows_2': 'all_rows', 'production code_3': 'production code', '110_4': '110'} | {'most_less_0': [1], 'result_1': [], 'all_rows_2': [0], 'production code_3': [0], '110_4': [0]} | ['no', 'title', 'directed by', 'written by', 'us viewers ( million )', 'original air date', 'production code'] | [['1', 'two of a kind', 'john terlesky', 'rob fresco', '13.06', 'february 16 , 2011', '107'], ['2', 'lonely hearts', 'michael watkins', 'shintaro shimosawa', '9.81', 'february 23 , 2011', '104'], ['3', 'see no evil', 'rob spera', 'barry schindel', '10.36', 'march 2 , 2011', '109'], ['4', 'one shot kill', 'terry mcdonough', 'rob fresco', '9.12', 'march 9 , 2011', '102'], ['5', 'here is the fire', 'andrew bernstein', 'chris mundy & ian goldberg', '10.33', 'march 16 , 2011', '101'], ['6', 'devotion', 'stephen cragg', 'shintaro shimosawa', '8.80', 'march 23 , 2011', '111'], ['7', 'jane', 'rob hardy', 'glen mazzara', '9.53', 'march 30 , 2011', '108'], ['8', 'nighthawk', 'dwight little', 'ian goldberg', '9.12', 'april 6 , 2011', '106'], ['9', 'smother', 'phil abraham', 'melissa blake & joy blake', '9.96', 'april 13 , 2011', '105'], ['10', 'the time is now', 'tim matheson', 'joy blake & melissa blake', '8.83', 'may 4 , 2011', '110'], ['11', 'strays', 'anna j foerster', 'chris mundy & glen mazzara', '9.31', 'may 11 , 2011', '103'], ['12', 'the girl in the blue mask', 'félix alcalá', 'mark richard', '8.46', 'may 18 , 2011', '112']] |
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